2023-01-05 23:18:00,498 - mmseg - INFO - Multi-processing start method is `None` 2023-01-05 23:18:00,499 - mmseg - INFO - OpenCV num_threads is `64 2023-01-05 23:18:00,545 - mmseg - INFO - Environment info: ------------------------------------------------------------ sys.platform: linux Python: 3.8.12 (default, Oct 12 2021, 13:49:34) [GCC 7.5.0] CUDA available: True GPU 0,1,2,3,4,5,6,7: Tesla V100-SXM2-16GB-N CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 PyTorch: 1.11.0 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37 - CuDNN 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.12.0 OpenCV: 4.6.0 MMCV: 1.7.0 MMCV Compiler: GCC 9.3 MMCV CUDA Compiler: 11.3 MMSegmentation: 0.29.1+08f5eeb ------------------------------------------------------------ 2023-01-05 23:18:00,545 - mmseg - INFO - Distributed training: True 2023-01-05 23:18:00,974 - mmseg - INFO - Config: embed_dims = [64, 128, 250, 320] norm_cfg = dict(type='SyncBN', requires_grad=True) model = dict( type='EncoderDecoder', pretrained=None, backbone=dict( type='SimplifiedMixTransformer', in_channels=3, embed_dims=[64, 128, 250, 320], num_stages=4, num_layers=[3, 6, 8, 3], num_heads=[1, 2, 5, 8], patch_sizes=[7, 3, 3, 3], strides=[4, 2, 2, 2], sr_ratios=[8, 4, 2, 1], out_indices=(0, 1, 2, 3), mlp_ratios=[8, 8, 4, 4], qkv_bias=True, drop_rate=0.0, attn_drop_rate=0.0, drop_path_rate=0.1, norm_cfg=dict(type='SyncBN', requires_grad=True)), decode_head=dict( type='DESTHead', in_channels=[64, 128, 250, 320], in_index=[0, 1, 2, 3], channels=64, dropout_ratio=0.1, num_classes=19, norm_cfg=dict(type='SyncBN', requires_grad=True), align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), train_cfg=dict(), test_cfg=dict(mode='slide', crop_size=(1024, 1024), stride=(768, 768))) dataset_type = 'CityscapesDataset' data_root = 'data/cityscapes/' img_norm_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) crop_size = (1024, 1024) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations'), dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), dict(type='RandomCrop', crop_size=(1024, 1024), cat_max_ratio=0.75), dict(type='RandomFlip', prob=0.5), dict(type='PhotoMetricDistortion'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size=(1024, 1024), pad_val=0, seg_pad_val=255), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_semantic_seg']) ] test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(2048, 1024), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ]) ] data = dict( samples_per_gpu=1, workers_per_gpu=1, train=dict( type='CityscapesDataset', data_root='data/cityscapes/', img_dir='leftImg8bit/train', ann_dir='gtFine/train', pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations'), dict( type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), dict( type='RandomCrop', crop_size=(1024, 1024), cat_max_ratio=0.75), dict(type='RandomFlip', prob=0.5), dict(type='PhotoMetricDistortion'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size=(1024, 1024), pad_val=0, seg_pad_val=255), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_semantic_seg']) ]), val=dict( type='CityscapesDataset', data_root='data/cityscapes/', img_dir='leftImg8bit/val', ann_dir='gtFine/val', pipeline=[ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(2048, 1024), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ]) ]), test=dict( type='CityscapesDataset', data_root='data/cityscapes/', img_dir='leftImg8bit/val', ann_dir='gtFine/val', pipeline=[ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(2048, 1024), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict( type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']) ]) ])) log_config = dict( interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) dist_params = dict(backend='nccl') log_level = 'INFO' load_from = None resume_from = None workflow = [('train', 1)] cudnn_benchmark = True optimizer = dict( type='AdamW', lr=6e-05, betas=(0.9, 0.999), weight_decay=0.01, paramwise_cfg=dict( custom_keys=dict( pos_block=dict(decay_mult=0.0), norm=dict(decay_mult=0.0), head=dict(lr_mult=1.0)))) optimizer_config = dict() lr_config = dict( policy='poly', warmup='linear', warmup_iters=1500, warmup_ratio=1e-06, power=1.0, min_lr=0.0, by_epoch=False) runner = dict(type='IterBasedRunner', max_iters=160000) checkpoint_config = dict(by_epoch=False, interval=16000) evaluation = dict(interval=16000, metric='mIoU', pre_eval=True) work_dir = '/workspace/result/train_log' gpu_ids = range(0, 8) auto_resume = False 2023-01-05 23:18:07,299 - mmseg - INFO - Set random seed to 2005041126, deterministic: False 2023-01-05 23:18:08,371 - mmseg - INFO - initialize DESTHead with init_cfg {'type': 'Normal', 'std': 0.01, 'override': {'name': 'conv_seg'}} Name of parameter - Initialization information backbone.layers.0.0.projection.weight - torch.Size([64, 3, 7, 7]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.0.projection.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.0.norm.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.0.norm.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.norm1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.norm1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.q.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.q.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.k.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.k.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.proj.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.proj.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.sr.weight - torch.Size([64, 64, 8, 8]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.sr.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.norm1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.attn.norm1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.norm2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.norm2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.dwconv.dwconv.weight - torch.Size([512, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.dwconv.dwconv.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.pre_layers.0.weight - torch.Size([512, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.pre_layers.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.pre_layers.1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.pre_layers.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.post_layers.0.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.post_layers.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.post_layers.3.weight - torch.Size([64, 512, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.0.ffn.post_layers.3.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.norm1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.norm1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.q.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.q.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.k.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.k.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.proj.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.proj.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.sr.weight - torch.Size([64, 64, 8, 8]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.sr.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.norm1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.attn.norm1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.norm2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.norm2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.dwconv.dwconv.weight - torch.Size([512, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.dwconv.dwconv.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.pre_layers.0.weight - torch.Size([512, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.pre_layers.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.pre_layers.1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.pre_layers.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.post_layers.0.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.post_layers.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.post_layers.3.weight - torch.Size([64, 512, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.1.ffn.post_layers.3.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.norm1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.norm1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.q.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.q.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.k.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.k.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.proj.weight - torch.Size([64, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.proj.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.sr.weight - torch.Size([64, 64, 8, 8]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.sr.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.norm1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.attn.norm1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.norm2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.norm2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.dwconv.dwconv.weight - torch.Size([512, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.dwconv.dwconv.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.pre_layers.0.weight - torch.Size([512, 64, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.pre_layers.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.pre_layers.1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.pre_layers.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.post_layers.0.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.post_layers.0.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.post_layers.3.weight - torch.Size([64, 512, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.1.2.ffn.post_layers.3.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.0.2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.0.projection.weight - torch.Size([128, 64, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.0.projection.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.0.norm.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.0.norm.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.q.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.q.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.k.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.k.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.proj.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.proj.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.sr.weight - torch.Size([128, 128, 4, 4]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.sr.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.attn.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.norm2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.norm2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.dwconv.dwconv.weight - torch.Size([1024, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.dwconv.dwconv.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.pre_layers.0.weight - torch.Size([1024, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.pre_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.pre_layers.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.pre_layers.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.post_layers.0.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.post_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.post_layers.3.weight - torch.Size([128, 1024, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.0.ffn.post_layers.3.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.q.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.q.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.k.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.k.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.proj.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.proj.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.sr.weight - torch.Size([128, 128, 4, 4]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.sr.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.attn.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.norm2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.norm2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.dwconv.dwconv.weight - torch.Size([1024, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.dwconv.dwconv.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.pre_layers.0.weight - torch.Size([1024, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.pre_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.pre_layers.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.pre_layers.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.post_layers.0.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.post_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.post_layers.3.weight - torch.Size([128, 1024, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.1.ffn.post_layers.3.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.q.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.q.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.k.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.k.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.proj.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.proj.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.sr.weight - torch.Size([128, 128, 4, 4]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.sr.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.attn.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.norm2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.norm2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.dwconv.dwconv.weight - torch.Size([1024, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.dwconv.dwconv.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.pre_layers.0.weight - torch.Size([1024, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.pre_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.pre_layers.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.pre_layers.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.post_layers.0.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.post_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.post_layers.3.weight - torch.Size([128, 1024, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.2.ffn.post_layers.3.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.q.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.q.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.k.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.k.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.proj.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.proj.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.sr.weight - torch.Size([128, 128, 4, 4]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.sr.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.attn.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.norm2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.norm2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.dwconv.dwconv.weight - torch.Size([1024, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.dwconv.dwconv.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.pre_layers.0.weight - torch.Size([1024, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.pre_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.pre_layers.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.pre_layers.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.post_layers.0.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.post_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.post_layers.3.weight - torch.Size([128, 1024, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.3.ffn.post_layers.3.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.q.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.q.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.k.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.k.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.proj.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.proj.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.sr.weight - torch.Size([128, 128, 4, 4]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.sr.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.attn.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.norm2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.norm2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.dwconv.dwconv.weight - torch.Size([1024, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.dwconv.dwconv.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.pre_layers.0.weight - torch.Size([1024, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.pre_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.pre_layers.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.pre_layers.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.post_layers.0.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.post_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.post_layers.3.weight - torch.Size([128, 1024, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.4.ffn.post_layers.3.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.q.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.q.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.k.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.k.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.proj.weight - torch.Size([128, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.proj.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.sr.weight - torch.Size([128, 128, 4, 4]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.sr.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.norm1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.attn.norm1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.norm2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.norm2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.dwconv.dwconv.weight - torch.Size([1024, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.dwconv.dwconv.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.pre_layers.0.weight - torch.Size([1024, 128, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.pre_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.pre_layers.1.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.pre_layers.1.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.post_layers.0.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.post_layers.0.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.post_layers.3.weight - torch.Size([128, 1024, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.1.5.ffn.post_layers.3.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.1.2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.0.projection.weight - torch.Size([250, 128, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.0.projection.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.0.norm.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.0.norm.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.q.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.q.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.k.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.k.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.proj.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.proj.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.sr.weight - torch.Size([250, 250, 2, 2]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.sr.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.attn.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.norm2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.norm2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.dwconv.dwconv.weight - torch.Size([1000, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.dwconv.dwconv.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.pre_layers.0.weight - torch.Size([1000, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.pre_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.pre_layers.1.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.pre_layers.1.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.post_layers.0.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.post_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.post_layers.3.weight - torch.Size([250, 1000, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.0.ffn.post_layers.3.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.q.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.q.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.k.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.k.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.proj.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.proj.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.sr.weight - torch.Size([250, 250, 2, 2]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.sr.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.attn.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.norm2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.norm2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.dwconv.dwconv.weight - torch.Size([1000, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.dwconv.dwconv.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.pre_layers.0.weight - torch.Size([1000, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.pre_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.pre_layers.1.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.pre_layers.1.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.post_layers.0.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.post_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.post_layers.3.weight - torch.Size([250, 1000, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.1.ffn.post_layers.3.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.q.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.q.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.k.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.k.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.proj.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.proj.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.sr.weight - torch.Size([250, 250, 2, 2]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.sr.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.attn.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.norm2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.norm2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.dwconv.dwconv.weight - torch.Size([1000, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.dwconv.dwconv.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.pre_layers.0.weight - torch.Size([1000, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.pre_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.pre_layers.1.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.pre_layers.1.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.post_layers.0.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.post_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.post_layers.3.weight - torch.Size([250, 1000, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.2.ffn.post_layers.3.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.q.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.q.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.k.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.k.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.proj.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.proj.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.sr.weight - torch.Size([250, 250, 2, 2]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.sr.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.attn.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.norm2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.norm2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.dwconv.dwconv.weight - torch.Size([1000, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.dwconv.dwconv.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.pre_layers.0.weight - torch.Size([1000, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.pre_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.pre_layers.1.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.pre_layers.1.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.post_layers.0.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.post_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.post_layers.3.weight - torch.Size([250, 1000, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.3.ffn.post_layers.3.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.q.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.q.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.k.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.k.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.proj.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.proj.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.sr.weight - torch.Size([250, 250, 2, 2]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.sr.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.attn.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.norm2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.norm2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.dwconv.dwconv.weight - torch.Size([1000, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.dwconv.dwconv.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.pre_layers.0.weight - torch.Size([1000, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.pre_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.pre_layers.1.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.pre_layers.1.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.post_layers.0.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.post_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.post_layers.3.weight - torch.Size([250, 1000, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.4.ffn.post_layers.3.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.q.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.q.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.k.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.k.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.proj.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.proj.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.sr.weight - torch.Size([250, 250, 2, 2]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.sr.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.attn.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.norm2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.norm2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.dwconv.dwconv.weight - torch.Size([1000, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.dwconv.dwconv.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.pre_layers.0.weight - torch.Size([1000, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.pre_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.pre_layers.1.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.pre_layers.1.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.post_layers.0.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.post_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.post_layers.3.weight - torch.Size([250, 1000, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.5.ffn.post_layers.3.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.q.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.q.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.k.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.k.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.proj.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.proj.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.sr.weight - torch.Size([250, 250, 2, 2]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.sr.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.attn.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.norm2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.norm2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.dwconv.dwconv.weight - torch.Size([1000, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.dwconv.dwconv.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.pre_layers.0.weight - torch.Size([1000, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.pre_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.pre_layers.1.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.pre_layers.1.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.post_layers.0.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.post_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.post_layers.3.weight - torch.Size([250, 1000, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.6.ffn.post_layers.3.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.q.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.q.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.k.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.k.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.proj.weight - torch.Size([250, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.proj.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.sr.weight - torch.Size([250, 250, 2, 2]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.sr.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.norm1.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.attn.norm1.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.norm2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.norm2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.dwconv.dwconv.weight - torch.Size([1000, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.dwconv.dwconv.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.pre_layers.0.weight - torch.Size([1000, 250, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.pre_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.pre_layers.1.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.pre_layers.1.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.post_layers.0.weight - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.post_layers.0.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.post_layers.3.weight - torch.Size([250, 1000, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.1.7.ffn.post_layers.3.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.2.weight - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.2.2.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.0.projection.weight - torch.Size([320, 250, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.0.projection.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.0.norm.weight - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.0.norm.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.norm1.weight - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.norm1.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.attn.q.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.attn.q.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.attn.k.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.attn.k.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.attn.proj.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.attn.proj.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.norm2.weight - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.norm2.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.dwconv.dwconv.weight - torch.Size([1280, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.dwconv.dwconv.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.pre_layers.0.weight - torch.Size([1280, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.pre_layers.0.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.pre_layers.1.weight - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.pre_layers.1.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.post_layers.0.weight - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.post_layers.0.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.post_layers.3.weight - torch.Size([320, 1280, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.0.ffn.post_layers.3.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.norm1.weight - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.norm1.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.attn.q.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.attn.q.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.attn.k.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.attn.k.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.attn.proj.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.attn.proj.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.norm2.weight - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.norm2.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.dwconv.dwconv.weight - torch.Size([1280, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.dwconv.dwconv.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.pre_layers.0.weight - torch.Size([1280, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.pre_layers.0.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.pre_layers.1.weight - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.pre_layers.1.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.post_layers.0.weight - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.post_layers.0.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.post_layers.3.weight - torch.Size([320, 1280, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.1.ffn.post_layers.3.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.norm1.weight - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.norm1.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.attn.q.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.attn.q.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.attn.k.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.attn.k.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.attn.proj.weight - torch.Size([320, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.attn.proj.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.norm2.weight - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.norm2.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.dwconv.dwconv.weight - torch.Size([1280, 1, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.dwconv.dwconv.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.pre_layers.0.weight - torch.Size([1280, 320, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.pre_layers.0.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.pre_layers.1.weight - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.pre_layers.1.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.post_layers.0.weight - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.post_layers.0.bias - torch.Size([1280]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.post_layers.3.weight - torch.Size([320, 1280, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.1.2.ffn.post_layers.3.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.2.weight - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder backbone.layers.3.2.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.conv_seg.weight - torch.Size([19, 64, 1, 1]): NormalInit: mean=0, std=0.01, bias=0 decode_head.conv_seg.bias - torch.Size([19]): NormalInit: mean=0, std=0.01, bias=0 decode_head.convs.0.conv.weight - torch.Size([64, 64, 1, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.convs.0.conv.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.convs.1.conv.weight - torch.Size([128, 128, 1, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.convs.1.conv.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.convs.2.conv.weight - torch.Size([250, 250, 1, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.convs.2.conv.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.convs.3.conv.weight - torch.Size([320, 320, 1, 1]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.convs.3.conv.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.fuse_convs.0.conv.weight - torch.Size([64, 192, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.fuse_convs.0.conv.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.fuse_convs.1.conv.weight - torch.Size([128, 378, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.fuse_convs.1.conv.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.fuse_convs.2.conv.weight - torch.Size([250, 570, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.fuse_convs.2.conv.bias - torch.Size([250]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.fuse_convs.3.conv.weight - torch.Size([320, 320, 3, 3]): The value is the same before and after calling `init_weights` of EncoderDecoder decode_head.fuse_convs.3.conv.bias - torch.Size([320]): The value is the same before and after calling `init_weights` of EncoderDecoder 2023-01-05 23:18:08,385 - mmseg - INFO - EncoderDecoder( (backbone): SimplifiedMixTransformer( (layers): ModuleList( (0): ModuleList( (0): SimplifiedPatchEmbed( (projection): Conv2d(3, 64, kernel_size=(7, 7), stride=(4, 4), padding=(3, 3)) (norm): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (1): ModuleList( (0): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (k): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8)) (norm1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512) ) (pre_layers): Sequential( (0): Conv1d(64, 512, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(512, 64, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (1): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (k): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8)) (norm1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512) ) (pre_layers): Sequential( (0): Conv1d(64, 512, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(512, 64, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (2): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (k): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(64, 64, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8)) (norm1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512) ) (pre_layers): Sequential( (0): Conv1d(64, 512, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(512, 64, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) ) (2): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (1): ModuleList( (0): SimplifiedPatchEmbed( (projection): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1)) (norm): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (1): ModuleList( (0): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (k): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4)) (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024) ) (pre_layers): Sequential( (0): Conv1d(128, 1024, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1024, 128, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (1): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (k): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4)) (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024) ) (pre_layers): Sequential( (0): Conv1d(128, 1024, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1024, 128, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (2): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (k): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4)) (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024) ) (pre_layers): Sequential( (0): Conv1d(128, 1024, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1024, 128, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (3): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (k): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4)) (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024) ) (pre_layers): Sequential( (0): Conv1d(128, 1024, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1024, 128, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (4): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (k): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4)) (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024) ) (pre_layers): Sequential( (0): Conv1d(128, 1024, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1024, 128, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (5): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (k): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(128, 128, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4)) (norm1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024) ) (pre_layers): Sequential( (0): Conv1d(128, 1024, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1024, 128, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) ) (2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (2): ModuleList( (0): SimplifiedPatchEmbed( (projection): Conv2d(128, 250, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1)) (norm): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (1): ModuleList( (0): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (k): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(250, 250, kernel_size=(2, 2), stride=(2, 2)) (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1000, 1000, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1000) ) (pre_layers): Sequential( (0): Conv1d(250, 1000, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1000, 250, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (1): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (k): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(250, 250, kernel_size=(2, 2), stride=(2, 2)) (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1000, 1000, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1000) ) (pre_layers): Sequential( (0): Conv1d(250, 1000, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1000, 250, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (2): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (k): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(250, 250, kernel_size=(2, 2), stride=(2, 2)) (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1000, 1000, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1000) ) (pre_layers): Sequential( (0): Conv1d(250, 1000, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1000, 250, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (3): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (k): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(250, 250, kernel_size=(2, 2), stride=(2, 2)) (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1000, 1000, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1000) ) (pre_layers): Sequential( (0): Conv1d(250, 1000, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1000, 250, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (4): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (k): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(250, 250, kernel_size=(2, 2), stride=(2, 2)) (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1000, 1000, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1000) ) (pre_layers): Sequential( (0): Conv1d(250, 1000, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1000, 250, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (5): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (k): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(250, 250, kernel_size=(2, 2), stride=(2, 2)) (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1000, 1000, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1000) ) (pre_layers): Sequential( (0): Conv1d(250, 1000, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1000, 250, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (6): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (k): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(250, 250, kernel_size=(2, 2), stride=(2, 2)) (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1000, 1000, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1000) ) (pre_layers): Sequential( (0): Conv1d(250, 1000, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1000, 250, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (7): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (k): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(250, 250, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (sr): Conv2d(250, 250, kernel_size=(2, 2), stride=(2, 2)) (norm1): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1000, 1000, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1000) ) (pre_layers): Sequential( (0): Conv1d(250, 1000, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1000, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1000, 250, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) ) (2): SyncBatchNorm(250, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (3): ModuleList( (0): SimplifiedPatchEmbed( (projection): Conv2d(250, 320, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1)) (norm): SyncBatchNorm(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (1): ModuleList( (0): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (k): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280) ) (pre_layers): Sequential( (0): Conv1d(320, 1280, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1280, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1280, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1280, 320, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (1): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (k): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280) ) (pre_layers): Sequential( (0): Conv1d(320, 1280, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1280, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1280, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1280, 320, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) (2): SimpliefiedTransformerEncoderLayer( (norm1): SyncBatchNorm(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (attn): SimplifiedAttention( (q): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (k): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (attn_drop): Dropout(p=0.0, inplace=False) (proj): Conv1d(320, 320, kernel_size=(1,), stride=(1,)) (proj_drop): Dropout(p=0.0, inplace=False) (dropout_layer): DropPath() ) (norm2): SyncBatchNorm(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (ffn): MixFFN( (dwconv): DWConv( (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280) ) (pre_layers): Sequential( (0): Conv1d(320, 1280, kernel_size=(1,), stride=(1,)) (1): SyncBatchNorm(1280, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (post_layers): Sequential( (0): SyncBatchNorm(1280, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (1): ReLU() (2): Dropout(p=0.0, inplace=False) (3): Conv1d(1280, 320, kernel_size=(1,), stride=(1,)) (4): Dropout(p=0.0, inplace=False) ) (dropout_layer): DropPath() ) ) ) (2): SyncBatchNorm(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) ) (decode_head): DESTHead( input_transform=multiple_select, ignore_index=255, align_corners=False (loss_decode): CrossEntropyLoss(avg_non_ignore=False) (conv_seg): Conv2d(64, 19, kernel_size=(1, 1), stride=(1, 1)) (dropout): Dropout2d(p=0.1, inplace=False) (convs): ModuleList( (0): ConvModule( (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1)) (activate): ReLU(inplace=True) ) (1): ConvModule( (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1)) (activate): ReLU(inplace=True) ) (2): ConvModule( (conv): Conv2d(250, 250, kernel_size=(1, 1), stride=(1, 1)) (activate): ReLU(inplace=True) ) (3): ConvModule( (conv): Conv2d(320, 320, kernel_size=(1, 1), stride=(1, 1)) (activate): ReLU(inplace=True) ) ) (fuse_convs): ModuleList( (0): ConvModule( (conv): Conv2d(192, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (activate): ReLU(inplace=True) ) (1): ConvModule( (conv): Conv2d(378, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (activate): ReLU(inplace=True) ) (2): ConvModule( (conv): Conv2d(570, 250, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (activate): ReLU(inplace=True) ) (3): ConvModule( (conv): Conv2d(320, 320, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (activate): ReLU(inplace=True) ) ) (upsample): ModuleList( (0): Sequential( (0): Upsample(scale_factor=2.0, mode=bilinear) ) (1): Sequential( (0): Upsample(scale_factor=2.0, mode=bilinear) ) (2): Sequential( (0): Upsample(scale_factor=2.0, mode=bilinear) ) (3): Sequential( (0): Upsample(scale_factor=2.0, mode=bilinear) ) ) ) init_cfg={'type': 'Normal', 'std': 0.01, 'override': {'name': 'conv_seg'}} ) 2023-01-05 23:18:08,621 - mmseg - INFO - Loaded 2975 images 2023-01-05 23:18:09,435 - mmseg - INFO - Loaded 500 images 2023-01-05 23:18:09,437 - mmseg - INFO - Start running, host: root@3920437, work_dir: /workspace/result/train_log 2023-01-05 23:18:09,437 - mmseg - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) PolyLrUpdaterHook (NORMAL ) CheckpointHook (LOW ) DistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_train_epoch: (VERY_HIGH ) PolyLrUpdaterHook (LOW ) IterTimerHook (LOW ) DistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_train_iter: (VERY_HIGH ) PolyLrUpdaterHook (LOW ) IterTimerHook (LOW ) DistEvalHook -------------------- after_train_iter: (ABOVE_NORMAL) OptimizerHook (NORMAL ) CheckpointHook (LOW ) IterTimerHook (LOW ) DistEvalHook (VERY_LOW ) TextLoggerHook -------------------- after_train_epoch: (NORMAL ) CheckpointHook (LOW ) DistEvalHook (VERY_LOW ) TextLoggerHook -------------------- before_val_epoch: (LOW ) IterTimerHook (VERY_LOW ) TextLoggerHook -------------------- before_val_iter: (LOW ) IterTimerHook -------------------- after_val_iter: (LOW ) IterTimerHook -------------------- after_val_epoch: (VERY_LOW ) TextLoggerHook -------------------- after_run: (VERY_LOW ) TextLoggerHook -------------------- 2023-01-05 23:18:09,438 - mmseg - INFO - workflow: [('train', 1)], max: 160000 iters 2023-01-05 23:18:09,438 - mmseg - INFO - Checkpoints will be saved to /workspace/result/train_log by HardDiskBackend. 2023-01-05 23:18:42,439 - mmseg - INFO - Iter [50/160000] lr: 1.959e-06, eta: 1 day, 1:55:20, time: 0.583, data_time: 0.016, memory: 9591, decode.loss_ce: 2.5273, decode.acc_seg: 4.1548, loss: 2.5273 2023-01-05 23:19:03,431 - mmseg - INFO - Iter [100/160000] lr: 3.958e-06, eta: 22:17:32, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 2.4106, decode.acc_seg: 21.0171, loss: 2.4106 2023-01-05 23:19:24,557 - mmseg - INFO - Iter [150/160000] lr: 5.955e-06, eta: 21:06:37, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 2.1902, decode.acc_seg: 41.8999, loss: 2.1902 2023-01-05 23:19:45,908 - mmseg - INFO - Iter [200/160000] lr: 7.950e-06, eta: 20:34:00, time: 0.427, data_time: 0.010, memory: 9591, decode.loss_ce: 1.6719, decode.acc_seg: 46.1711, loss: 1.6719 2023-01-05 23:20:07,463 - mmseg - INFO - Iter [250/160000] lr: 9.945e-06, eta: 20:16:08, time: 0.430, data_time: 0.010, memory: 9591, decode.loss_ce: 1.4341, decode.acc_seg: 51.7047, loss: 1.4341 2023-01-05 23:20:29,194 - mmseg - INFO - Iter [300/160000] lr: 1.194e-05, eta: 20:06:09, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 1.2396, decode.acc_seg: 58.8616, loss: 1.2396 2023-01-05 23:20:50,427 - mmseg - INFO - Iter [350/160000] lr: 1.393e-05, eta: 19:54:56, time: 0.425, data_time: 0.010, memory: 9591, decode.loss_ce: 1.0901, decode.acc_seg: 61.9000, loss: 1.0901 2023-01-05 23:21:13,638 - mmseg - INFO - Iter [400/160000] lr: 1.592e-05, eta: 19:59:34, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 1.0336, decode.acc_seg: 64.0048, loss: 1.0336 2023-01-05 23:21:35,908 - mmseg - INFO - Iter [450/160000] lr: 1.791e-05, eta: 19:57:34, time: 0.445, data_time: 0.011, memory: 9591, decode.loss_ce: 0.9905, decode.acc_seg: 66.8255, loss: 0.9905 2023-01-05 23:21:57,069 - mmseg - INFO - Iter [500/160000] lr: 1.990e-05, eta: 19:49:57, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.9340, decode.acc_seg: 68.3582, loss: 0.9340 2023-01-05 23:22:18,613 - mmseg - INFO - Iter [550/160000] lr: 2.188e-05, eta: 19:45:32, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.8847, decode.acc_seg: 70.5504, loss: 0.8847 2023-01-05 23:22:40,177 - mmseg - INFO - Iter [600/160000] lr: 2.387e-05, eta: 19:41:47, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.8425, decode.acc_seg: 70.6983, loss: 0.8425 2023-01-05 23:23:01,404 - mmseg - INFO - Iter [650/160000] lr: 2.585e-05, eta: 19:37:21, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.8231, decode.acc_seg: 72.6355, loss: 0.8231 2023-01-05 23:23:22,524 - mmseg - INFO - Iter [700/160000] lr: 2.784e-05, eta: 19:33:01, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.7483, decode.acc_seg: 74.7932, loss: 0.7483 2023-01-05 23:23:47,036 - mmseg - INFO - Iter [750/160000] lr: 2.982e-05, eta: 19:41:07, time: 0.490, data_time: 0.056, memory: 9591, decode.loss_ce: 0.7519, decode.acc_seg: 74.7107, loss: 0.7519 2023-01-05 23:24:08,957 - mmseg - INFO - Iter [800/160000] lr: 3.180e-05, eta: 19:39:44, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.7359, decode.acc_seg: 75.6443, loss: 0.7359 2023-01-05 23:24:29,971 - mmseg - INFO - Iter [850/160000] lr: 3.378e-05, eta: 19:35:34, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.7275, decode.acc_seg: 74.7064, loss: 0.7275 2023-01-05 23:24:51,452 - mmseg - INFO - Iter [900/160000] lr: 3.576e-05, eta: 19:33:12, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.7205, decode.acc_seg: 76.0661, loss: 0.7205 2023-01-05 23:25:12,407 - mmseg - INFO - Iter [950/160000] lr: 3.773e-05, eta: 19:29:34, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.6626, decode.acc_seg: 76.8191, loss: 0.6626 2023-01-05 23:25:33,336 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-05 23:25:33,337 - mmseg - INFO - Iter [1000/160000] lr: 3.971e-05, eta: 19:26:12, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.6605, decode.acc_seg: 77.2848, loss: 0.6605 2023-01-05 23:25:54,598 - mmseg - INFO - Iter [1050/160000] lr: 4.168e-05, eta: 19:23:54, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.6685, decode.acc_seg: 77.4854, loss: 0.6685 2023-01-05 23:26:15,886 - mmseg - INFO - Iter [1100/160000] lr: 4.366e-05, eta: 19:21:57, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.6321, decode.acc_seg: 78.6629, loss: 0.6321 2023-01-05 23:26:39,206 - mmseg - INFO - Iter [1150/160000] lr: 4.563e-05, eta: 19:24:46, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.6489, decode.acc_seg: 77.7224, loss: 0.6489 2023-01-05 23:27:00,389 - mmseg - INFO - Iter [1200/160000] lr: 4.760e-05, eta: 19:22:36, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.6228, decode.acc_seg: 78.9463, loss: 0.6228 2023-01-05 23:27:21,370 - mmseg - INFO - Iter [1250/160000] lr: 4.957e-05, eta: 19:20:06, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.5674, decode.acc_seg: 80.2614, loss: 0.5674 2023-01-05 23:27:43,201 - mmseg - INFO - Iter [1300/160000] lr: 5.154e-05, eta: 19:19:33, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.6061, decode.acc_seg: 78.4481, loss: 0.6061 2023-01-05 23:28:05,364 - mmseg - INFO - Iter [1350/160000] lr: 5.351e-05, eta: 19:19:40, time: 0.443, data_time: 0.012, memory: 9591, decode.loss_ce: 0.5749, decode.acc_seg: 80.5743, loss: 0.5749 2023-01-05 23:28:27,267 - mmseg - INFO - Iter [1400/160000] lr: 5.547e-05, eta: 19:19:18, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.5486, decode.acc_seg: 80.7431, loss: 0.5486 2023-01-05 23:28:49,008 - mmseg - INFO - Iter [1450/160000] lr: 5.744e-05, eta: 19:18:36, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.5657, decode.acc_seg: 80.7138, loss: 0.5657 2023-01-05 23:29:12,504 - mmseg - INFO - Iter [1500/160000] lr: 5.940e-05, eta: 19:20:59, time: 0.470, data_time: 0.057, memory: 9591, decode.loss_ce: 0.5592, decode.acc_seg: 80.7158, loss: 0.5592 2023-01-05 23:29:33,413 - mmseg - INFO - Iter [1550/160000] lr: 5.942e-05, eta: 19:18:49, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.5415, decode.acc_seg: 81.5244, loss: 0.5415 2023-01-05 23:29:54,319 - mmseg - INFO - Iter [1600/160000] lr: 5.940e-05, eta: 19:16:44, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.5599, decode.acc_seg: 81.0157, loss: 0.5599 2023-01-05 23:30:15,493 - mmseg - INFO - Iter [1650/160000] lr: 5.938e-05, eta: 19:15:11, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.5535, decode.acc_seg: 80.7729, loss: 0.5535 2023-01-05 23:30:37,719 - mmseg - INFO - Iter [1700/160000] lr: 5.936e-05, eta: 19:15:19, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4939, decode.acc_seg: 82.5120, loss: 0.4939 2023-01-05 23:30:59,164 - mmseg - INFO - Iter [1750/160000] lr: 5.934e-05, eta: 19:14:19, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.5117, decode.acc_seg: 82.1644, loss: 0.5117 2023-01-05 23:31:20,460 - mmseg - INFO - Iter [1800/160000] lr: 5.933e-05, eta: 19:13:05, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.5222, decode.acc_seg: 81.4383, loss: 0.5222 2023-01-05 23:31:42,417 - mmseg - INFO - Iter [1850/160000] lr: 5.931e-05, eta: 19:12:48, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.5194, decode.acc_seg: 81.7954, loss: 0.5194 2023-01-05 23:32:06,097 - mmseg - INFO - Iter [1900/160000] lr: 5.929e-05, eta: 19:15:00, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.5061, decode.acc_seg: 82.1151, loss: 0.5061 2023-01-05 23:32:26,979 - mmseg - INFO - Iter [1950/160000] lr: 5.927e-05, eta: 19:13:13, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.5419, decode.acc_seg: 80.9800, loss: 0.5419 2023-01-05 23:32:48,515 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-05 23:32:48,515 - mmseg - INFO - Iter [2000/160000] lr: 5.925e-05, eta: 19:12:22, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4974, decode.acc_seg: 82.9838, loss: 0.4974 2023-01-05 23:33:09,937 - mmseg - INFO - Iter [2050/160000] lr: 5.923e-05, eta: 19:11:27, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.4731, decode.acc_seg: 83.4216, loss: 0.4731 2023-01-05 23:33:31,531 - mmseg - INFO - Iter [2100/160000] lr: 5.921e-05, eta: 19:10:44, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4406, decode.acc_seg: 84.2369, loss: 0.4406 2023-01-05 23:33:52,791 - mmseg - INFO - Iter [2150/160000] lr: 5.919e-05, eta: 19:09:38, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4492, decode.acc_seg: 84.3571, loss: 0.4492 2023-01-05 23:34:13,709 - mmseg - INFO - Iter [2200/160000] lr: 5.918e-05, eta: 19:08:09, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4605, decode.acc_seg: 83.6161, loss: 0.4605 2023-01-05 23:34:38,334 - mmseg - INFO - Iter [2250/160000] lr: 5.916e-05, eta: 19:11:03, time: 0.492, data_time: 0.056, memory: 9591, decode.loss_ce: 0.4772, decode.acc_seg: 83.2722, loss: 0.4772 2023-01-05 23:34:59,795 - mmseg - INFO - Iter [2300/160000] lr: 5.914e-05, eta: 19:10:12, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4676, decode.acc_seg: 83.6566, loss: 0.4676 2023-01-05 23:35:20,774 - mmseg - INFO - Iter [2350/160000] lr: 5.912e-05, eta: 19:08:49, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4445, decode.acc_seg: 84.2826, loss: 0.4445 2023-01-05 23:35:41,840 - mmseg - INFO - Iter [2400/160000] lr: 5.910e-05, eta: 19:07:35, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4361, decode.acc_seg: 83.8884, loss: 0.4361 2023-01-05 23:36:03,409 - mmseg - INFO - Iter [2450/160000] lr: 5.908e-05, eta: 19:06:54, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4494, decode.acc_seg: 84.0722, loss: 0.4494 2023-01-05 23:36:24,693 - mmseg - INFO - Iter [2500/160000] lr: 5.906e-05, eta: 19:05:59, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.4271, decode.acc_seg: 84.5849, loss: 0.4271 2023-01-05 23:36:45,919 - mmseg - INFO - Iter [2550/160000] lr: 5.904e-05, eta: 19:05:00, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4326, decode.acc_seg: 84.8642, loss: 0.4326 2023-01-05 23:37:06,988 - mmseg - INFO - Iter [2600/160000] lr: 5.903e-05, eta: 19:03:53, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4275, decode.acc_seg: 84.4349, loss: 0.4275 2023-01-05 23:37:31,711 - mmseg - INFO - Iter [2650/160000] lr: 5.901e-05, eta: 19:06:23, time: 0.494, data_time: 0.057, memory: 9591, decode.loss_ce: 0.4037, decode.acc_seg: 85.5222, loss: 0.4037 2023-01-05 23:37:52,955 - mmseg - INFO - Iter [2700/160000] lr: 5.899e-05, eta: 19:05:27, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4221, decode.acc_seg: 85.0807, loss: 0.4221 2023-01-05 23:38:14,434 - mmseg - INFO - Iter [2750/160000] lr: 5.897e-05, eta: 19:04:44, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4207, decode.acc_seg: 84.9922, loss: 0.4207 2023-01-05 23:38:35,553 - mmseg - INFO - Iter [2800/160000] lr: 5.895e-05, eta: 19:03:42, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3866, decode.acc_seg: 85.9421, loss: 0.3866 2023-01-05 23:38:56,567 - mmseg - INFO - Iter [2850/160000] lr: 5.893e-05, eta: 19:02:35, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4151, decode.acc_seg: 85.2858, loss: 0.4151 2023-01-05 23:39:17,469 - mmseg - INFO - Iter [2900/160000] lr: 5.891e-05, eta: 19:01:24, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4283, decode.acc_seg: 85.2196, loss: 0.4283 2023-01-05 23:39:39,697 - mmseg - INFO - Iter [2950/160000] lr: 5.889e-05, eta: 19:01:25, time: 0.445, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3964, decode.acc_seg: 85.7407, loss: 0.3964 2023-01-05 23:40:02,766 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-05 23:40:02,766 - mmseg - INFO - Iter [3000/160000] lr: 5.888e-05, eta: 19:02:08, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.3825, decode.acc_seg: 86.0843, loss: 0.3825 2023-01-05 23:40:24,383 - mmseg - INFO - Iter [3050/160000] lr: 5.886e-05, eta: 19:01:36, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3835, decode.acc_seg: 85.8638, loss: 0.3835 2023-01-05 23:40:46,208 - mmseg - INFO - Iter [3100/160000] lr: 5.884e-05, eta: 19:01:14, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4032, decode.acc_seg: 85.9283, loss: 0.4032 2023-01-05 23:41:07,575 - mmseg - INFO - Iter [3150/160000] lr: 5.882e-05, eta: 19:00:31, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4130, decode.acc_seg: 85.3773, loss: 0.4130 2023-01-05 23:41:29,411 - mmseg - INFO - Iter [3200/160000] lr: 5.880e-05, eta: 19:00:08, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4057, decode.acc_seg: 85.7193, loss: 0.4057 2023-01-05 23:41:50,859 - mmseg - INFO - Iter [3250/160000] lr: 5.878e-05, eta: 18:59:29, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3894, decode.acc_seg: 86.1356, loss: 0.3894 2023-01-05 23:42:12,492 - mmseg - INFO - Iter [3300/160000] lr: 5.876e-05, eta: 18:59:00, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.3779, decode.acc_seg: 85.9965, loss: 0.3779 2023-01-05 23:42:35,937 - mmseg - INFO - Iter [3350/160000] lr: 5.874e-05, eta: 18:59:54, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.3671, decode.acc_seg: 86.5953, loss: 0.3671 2023-01-05 23:42:57,212 - mmseg - INFO - Iter [3400/160000] lr: 5.873e-05, eta: 18:59:07, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3949, decode.acc_seg: 85.6577, loss: 0.3949 2023-01-05 23:43:18,100 - mmseg - INFO - Iter [3450/160000] lr: 5.871e-05, eta: 18:58:03, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3505, decode.acc_seg: 87.3481, loss: 0.3505 2023-01-05 23:43:40,027 - mmseg - INFO - Iter [3500/160000] lr: 5.869e-05, eta: 18:57:47, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3496, decode.acc_seg: 87.3827, loss: 0.3496 2023-01-05 23:44:00,963 - mmseg - INFO - Iter [3550/160000] lr: 5.867e-05, eta: 18:56:46, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.3653, decode.acc_seg: 86.6480, loss: 0.3653 2023-01-05 23:44:22,217 - mmseg - INFO - Iter [3600/160000] lr: 5.865e-05, eta: 18:56:01, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3433, decode.acc_seg: 87.2862, loss: 0.3433 2023-01-05 23:44:43,505 - mmseg - INFO - Iter [3650/160000] lr: 5.863e-05, eta: 18:55:16, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3908, decode.acc_seg: 85.7151, loss: 0.3908 2023-01-05 23:45:05,029 - mmseg - INFO - Iter [3700/160000] lr: 5.861e-05, eta: 18:54:44, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.4116, decode.acc_seg: 85.5089, loss: 0.4116 2023-01-05 23:45:28,635 - mmseg - INFO - Iter [3750/160000] lr: 5.859e-05, eta: 18:55:39, time: 0.473, data_time: 0.057, memory: 9591, decode.loss_ce: 0.3595, decode.acc_seg: 86.8340, loss: 0.3595 2023-01-05 23:45:49,449 - mmseg - INFO - Iter [3800/160000] lr: 5.858e-05, eta: 18:54:36, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3635, decode.acc_seg: 86.4991, loss: 0.3635 2023-01-05 23:46:11,238 - mmseg - INFO - Iter [3850/160000] lr: 5.856e-05, eta: 18:54:15, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3447, decode.acc_seg: 87.3289, loss: 0.3447 2023-01-05 23:46:32,505 - mmseg - INFO - Iter [3900/160000] lr: 5.854e-05, eta: 18:53:31, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3641, decode.acc_seg: 86.8847, loss: 0.3641 2023-01-05 23:46:53,807 - mmseg - INFO - Iter [3950/160000] lr: 5.852e-05, eta: 18:52:51, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.3582, decode.acc_seg: 86.8592, loss: 0.3582 2023-01-05 23:47:15,285 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-05 23:47:15,286 - mmseg - INFO - Iter [4000/160000] lr: 5.850e-05, eta: 18:52:16, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3641, decode.acc_seg: 86.9726, loss: 0.3641 2023-01-05 23:47:37,450 - mmseg - INFO - Iter [4050/160000] lr: 5.848e-05, eta: 18:52:10, time: 0.443, data_time: 0.012, memory: 9591, decode.loss_ce: 0.3722, decode.acc_seg: 86.6961, loss: 0.3722 2023-01-05 23:48:01,354 - mmseg - INFO - Iter [4100/160000] lr: 5.846e-05, eta: 18:53:08, time: 0.478, data_time: 0.057, memory: 9591, decode.loss_ce: 0.3293, decode.acc_seg: 88.1103, loss: 0.3293 2023-01-05 23:48:22,744 - mmseg - INFO - Iter [4150/160000] lr: 5.844e-05, eta: 18:52:32, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.3366, decode.acc_seg: 87.5670, loss: 0.3366 2023-01-05 23:48:43,981 - mmseg - INFO - Iter [4200/160000] lr: 5.843e-05, eta: 18:51:49, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3479, decode.acc_seg: 87.2346, loss: 0.3479 2023-01-05 23:49:05,119 - mmseg - INFO - Iter [4250/160000] lr: 5.841e-05, eta: 18:51:04, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3491, decode.acc_seg: 87.0744, loss: 0.3491 2023-01-05 23:49:26,812 - mmseg - INFO - Iter [4300/160000] lr: 5.839e-05, eta: 18:50:38, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3613, decode.acc_seg: 87.4293, loss: 0.3613 2023-01-05 23:49:48,485 - mmseg - INFO - Iter [4350/160000] lr: 5.837e-05, eta: 18:50:12, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3175, decode.acc_seg: 88.1105, loss: 0.3175 2023-01-05 23:50:09,355 - mmseg - INFO - Iter [4400/160000] lr: 5.835e-05, eta: 18:49:18, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.3426, decode.acc_seg: 87.3908, loss: 0.3426 2023-01-05 23:50:30,519 - mmseg - INFO - Iter [4450/160000] lr: 5.833e-05, eta: 18:48:35, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3349, decode.acc_seg: 87.4618, loss: 0.3349 2023-01-05 23:50:54,021 - mmseg - INFO - Iter [4500/160000] lr: 5.831e-05, eta: 18:49:13, time: 0.470, data_time: 0.056, memory: 9591, decode.loss_ce: 0.3175, decode.acc_seg: 88.0052, loss: 0.3175 2023-01-05 23:51:15,325 - mmseg - INFO - Iter [4550/160000] lr: 5.829e-05, eta: 18:48:35, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3374, decode.acc_seg: 87.9118, loss: 0.3374 2023-01-05 23:51:36,298 - mmseg - INFO - Iter [4600/160000] lr: 5.828e-05, eta: 18:47:46, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3673, decode.acc_seg: 86.5925, loss: 0.3673 2023-01-05 23:51:57,538 - mmseg - INFO - Iter [4650/160000] lr: 5.826e-05, eta: 18:47:06, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3333, decode.acc_seg: 87.8315, loss: 0.3333 2023-01-05 23:52:18,633 - mmseg - INFO - Iter [4700/160000] lr: 5.824e-05, eta: 18:46:23, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.3492, decode.acc_seg: 87.5182, loss: 0.3492 2023-01-05 23:52:39,928 - mmseg - INFO - Iter [4750/160000] lr: 5.822e-05, eta: 18:45:46, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3243, decode.acc_seg: 88.2425, loss: 0.3243 2023-01-05 23:53:01,083 - mmseg - INFO - Iter [4800/160000] lr: 5.820e-05, eta: 18:45:05, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3663, decode.acc_seg: 87.1447, loss: 0.3663 2023-01-05 23:53:24,292 - mmseg - INFO - Iter [4850/160000] lr: 5.818e-05, eta: 18:45:30, time: 0.464, data_time: 0.055, memory: 9591, decode.loss_ce: 0.3231, decode.acc_seg: 88.2645, loss: 0.3231 2023-01-05 23:53:46,052 - mmseg - INFO - Iter [4900/160000] lr: 5.816e-05, eta: 18:45:08, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3216, decode.acc_seg: 88.4405, loss: 0.3216 2023-01-05 23:54:07,220 - mmseg - INFO - Iter [4950/160000] lr: 5.814e-05, eta: 18:44:27, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3115, decode.acc_seg: 88.1646, loss: 0.3115 2023-01-05 23:54:28,129 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-05 23:54:28,129 - mmseg - INFO - Iter [5000/160000] lr: 5.813e-05, eta: 18:43:39, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3502, decode.acc_seg: 87.7151, loss: 0.3502 2023-01-05 23:54:49,624 - mmseg - INFO - Iter [5050/160000] lr: 5.811e-05, eta: 18:43:10, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3185, decode.acc_seg: 88.1101, loss: 0.3185 2023-01-05 23:55:10,512 - mmseg - INFO - Iter [5100/160000] lr: 5.809e-05, eta: 18:42:22, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3240, decode.acc_seg: 88.1147, loss: 0.3240 2023-01-05 23:55:31,260 - mmseg - INFO - Iter [5150/160000] lr: 5.807e-05, eta: 18:41:30, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3120, decode.acc_seg: 88.5943, loss: 0.3120 2023-01-05 23:55:52,426 - mmseg - INFO - Iter [5200/160000] lr: 5.805e-05, eta: 18:40:52, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3081, decode.acc_seg: 88.3691, loss: 0.3081 2023-01-05 23:56:15,777 - mmseg - INFO - Iter [5250/160000] lr: 5.803e-05, eta: 18:41:18, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.3269, decode.acc_seg: 88.2950, loss: 0.3269 2023-01-05 23:56:37,148 - mmseg - INFO - Iter [5300/160000] lr: 5.801e-05, eta: 18:40:45, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2972, decode.acc_seg: 89.1267, loss: 0.2972 2023-01-05 23:56:59,589 - mmseg - INFO - Iter [5350/160000] lr: 5.799e-05, eta: 18:40:44, time: 0.449, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2911, decode.acc_seg: 89.0185, loss: 0.2911 2023-01-05 23:57:20,960 - mmseg - INFO - Iter [5400/160000] lr: 5.798e-05, eta: 18:40:12, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3203, decode.acc_seg: 87.8506, loss: 0.3203 2023-01-05 23:57:42,950 - mmseg - INFO - Iter [5450/160000] lr: 5.796e-05, eta: 18:39:57, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2993, decode.acc_seg: 88.9283, loss: 0.2993 2023-01-05 23:58:04,268 - mmseg - INFO - Iter [5500/160000] lr: 5.794e-05, eta: 18:39:24, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3245, decode.acc_seg: 88.1204, loss: 0.3245 2023-01-05 23:58:26,427 - mmseg - INFO - Iter [5550/160000] lr: 5.792e-05, eta: 18:39:13, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3517, decode.acc_seg: 87.1335, loss: 0.3517 2023-01-05 23:58:50,183 - mmseg - INFO - Iter [5600/160000] lr: 5.790e-05, eta: 18:39:48, time: 0.476, data_time: 0.057, memory: 9591, decode.loss_ce: 0.3131, decode.acc_seg: 88.5578, loss: 0.3131 2023-01-05 23:59:11,722 - mmseg - INFO - Iter [5650/160000] lr: 5.788e-05, eta: 18:39:20, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3042, decode.acc_seg: 89.0570, loss: 0.3042 2023-01-05 23:59:32,887 - mmseg - INFO - Iter [5700/160000] lr: 5.786e-05, eta: 18:38:42, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2891, decode.acc_seg: 89.5261, loss: 0.2891 2023-01-05 23:59:54,297 - mmseg - INFO - Iter [5750/160000] lr: 5.784e-05, eta: 18:38:11, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2809, decode.acc_seg: 89.5225, loss: 0.2809 2023-01-06 00:00:16,927 - mmseg - INFO - Iter [5800/160000] lr: 5.783e-05, eta: 18:38:12, time: 0.452, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2979, decode.acc_seg: 89.0476, loss: 0.2979 2023-01-06 00:00:38,265 - mmseg - INFO - Iter [5850/160000] lr: 5.781e-05, eta: 18:37:40, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2882, decode.acc_seg: 89.2004, loss: 0.2882 2023-01-06 00:00:59,206 - mmseg - INFO - Iter [5900/160000] lr: 5.779e-05, eta: 18:36:57, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3193, decode.acc_seg: 88.3922, loss: 0.3193 2023-01-06 00:01:20,489 - mmseg - INFO - Iter [5950/160000] lr: 5.777e-05, eta: 18:36:23, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3240, decode.acc_seg: 88.2037, loss: 0.3240 2023-01-06 00:01:44,346 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:01:44,347 - mmseg - INFO - Iter [6000/160000] lr: 5.775e-05, eta: 18:36:56, time: 0.477, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2718, decode.acc_seg: 89.9866, loss: 0.2718 2023-01-06 00:02:06,312 - mmseg - INFO - Iter [6050/160000] lr: 5.773e-05, eta: 18:36:40, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2802, decode.acc_seg: 89.5844, loss: 0.2802 2023-01-06 00:02:28,866 - mmseg - INFO - Iter [6100/160000] lr: 5.771e-05, eta: 18:36:37, time: 0.451, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2942, decode.acc_seg: 89.1613, loss: 0.2942 2023-01-06 00:02:50,905 - mmseg - INFO - Iter [6150/160000] lr: 5.769e-05, eta: 18:36:23, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3119, decode.acc_seg: 88.4999, loss: 0.3119 2023-01-06 00:03:11,840 - mmseg - INFO - Iter [6200/160000] lr: 5.768e-05, eta: 18:35:40, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3219, decode.acc_seg: 88.0968, loss: 0.3219 2023-01-06 00:03:33,584 - mmseg - INFO - Iter [6250/160000] lr: 5.766e-05, eta: 18:35:18, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3168, decode.acc_seg: 88.5480, loss: 0.3168 2023-01-06 00:03:55,067 - mmseg - INFO - Iter [6300/160000] lr: 5.764e-05, eta: 18:34:50, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2993, decode.acc_seg: 88.3073, loss: 0.2993 2023-01-06 00:04:18,795 - mmseg - INFO - Iter [6350/160000] lr: 5.762e-05, eta: 18:35:15, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2855, decode.acc_seg: 89.3658, loss: 0.2855 2023-01-06 00:04:40,250 - mmseg - INFO - Iter [6400/160000] lr: 5.760e-05, eta: 18:34:46, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2832, decode.acc_seg: 89.5322, loss: 0.2832 2023-01-06 00:05:01,252 - mmseg - INFO - Iter [6450/160000] lr: 5.758e-05, eta: 18:34:06, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2784, decode.acc_seg: 89.7702, loss: 0.2784 2023-01-06 00:05:23,672 - mmseg - INFO - Iter [6500/160000] lr: 5.756e-05, eta: 18:34:00, time: 0.448, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3051, decode.acc_seg: 88.8488, loss: 0.3051 2023-01-06 00:05:44,813 - mmseg - INFO - Iter [6550/160000] lr: 5.754e-05, eta: 18:33:22, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2823, decode.acc_seg: 89.4221, loss: 0.2823 2023-01-06 00:06:06,254 - mmseg - INFO - Iter [6600/160000] lr: 5.753e-05, eta: 18:32:54, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2753, decode.acc_seg: 89.5503, loss: 0.2753 2023-01-06 00:06:27,853 - mmseg - INFO - Iter [6650/160000] lr: 5.751e-05, eta: 18:32:28, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2832, decode.acc_seg: 89.4379, loss: 0.2832 2023-01-06 00:06:50,895 - mmseg - INFO - Iter [6700/160000] lr: 5.749e-05, eta: 18:32:35, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.3222, decode.acc_seg: 88.3892, loss: 0.3222 2023-01-06 00:07:12,956 - mmseg - INFO - Iter [6750/160000] lr: 5.747e-05, eta: 18:32:20, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3064, decode.acc_seg: 88.6984, loss: 0.3064 2023-01-06 00:07:34,308 - mmseg - INFO - Iter [6800/160000] lr: 5.745e-05, eta: 18:31:49, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2604, decode.acc_seg: 90.1063, loss: 0.2604 2023-01-06 00:07:56,586 - mmseg - INFO - Iter [6850/160000] lr: 5.743e-05, eta: 18:31:38, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2847, decode.acc_seg: 89.4702, loss: 0.2847 2023-01-06 00:08:18,368 - mmseg - INFO - Iter [6900/160000] lr: 5.741e-05, eta: 18:31:16, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2777, decode.acc_seg: 89.8693, loss: 0.2777 2023-01-06 00:08:39,454 - mmseg - INFO - Iter [6950/160000] lr: 5.739e-05, eta: 18:30:40, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3063, decode.acc_seg: 88.9964, loss: 0.3063 2023-01-06 00:09:01,209 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:09:01,210 - mmseg - INFO - Iter [7000/160000] lr: 5.738e-05, eta: 18:30:17, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2969, decode.acc_seg: 88.8457, loss: 0.2969 2023-01-06 00:09:23,329 - mmseg - INFO - Iter [7050/160000] lr: 5.736e-05, eta: 18:30:03, time: 0.442, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2721, decode.acc_seg: 89.8037, loss: 0.2721 2023-01-06 00:09:47,484 - mmseg - INFO - Iter [7100/160000] lr: 5.734e-05, eta: 18:30:33, time: 0.484, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2894, decode.acc_seg: 88.9966, loss: 0.2894 2023-01-06 00:10:08,427 - mmseg - INFO - Iter [7150/160000] lr: 5.732e-05, eta: 18:29:53, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3051, decode.acc_seg: 88.4797, loss: 0.3051 2023-01-06 00:10:30,004 - mmseg - INFO - Iter [7200/160000] lr: 5.730e-05, eta: 18:29:27, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3001, decode.acc_seg: 89.0193, loss: 0.3001 2023-01-06 00:10:51,557 - mmseg - INFO - Iter [7250/160000] lr: 5.728e-05, eta: 18:29:00, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2784, decode.acc_seg: 89.4852, loss: 0.2784 2023-01-06 00:11:13,562 - mmseg - INFO - Iter [7300/160000] lr: 5.726e-05, eta: 18:28:43, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2803, decode.acc_seg: 89.7231, loss: 0.2803 2023-01-06 00:11:34,717 - mmseg - INFO - Iter [7350/160000] lr: 5.724e-05, eta: 18:28:08, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2793, decode.acc_seg: 89.4945, loss: 0.2793 2023-01-06 00:11:55,991 - mmseg - INFO - Iter [7400/160000] lr: 5.723e-05, eta: 18:27:36, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2828, decode.acc_seg: 89.3284, loss: 0.2828 2023-01-06 00:12:19,048 - mmseg - INFO - Iter [7450/160000] lr: 5.721e-05, eta: 18:27:41, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2664, decode.acc_seg: 90.0261, loss: 0.2664 2023-01-06 00:12:40,721 - mmseg - INFO - Iter [7500/160000] lr: 5.719e-05, eta: 18:27:17, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2761, decode.acc_seg: 89.5876, loss: 0.2761 2023-01-06 00:13:02,099 - mmseg - INFO - Iter [7550/160000] lr: 5.717e-05, eta: 18:26:47, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.3021, decode.acc_seg: 88.9616, loss: 0.3021 2023-01-06 00:13:22,961 - mmseg - INFO - Iter [7600/160000] lr: 5.715e-05, eta: 18:26:06, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2923, decode.acc_seg: 89.4193, loss: 0.2923 2023-01-06 00:13:44,467 - mmseg - INFO - Iter [7650/160000] lr: 5.713e-05, eta: 18:25:39, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2692, decode.acc_seg: 89.7598, loss: 0.2692 2023-01-06 00:14:06,309 - mmseg - INFO - Iter [7700/160000] lr: 5.711e-05, eta: 18:25:18, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2480, decode.acc_seg: 90.6633, loss: 0.2480 2023-01-06 00:14:27,229 - mmseg - INFO - Iter [7750/160000] lr: 5.709e-05, eta: 18:24:40, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2527, decode.acc_seg: 90.6082, loss: 0.2527 2023-01-06 00:14:48,926 - mmseg - INFO - Iter [7800/160000] lr: 5.708e-05, eta: 18:24:17, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2697, decode.acc_seg: 89.9451, loss: 0.2697 2023-01-06 00:15:12,737 - mmseg - INFO - Iter [7850/160000] lr: 5.706e-05, eta: 18:24:35, time: 0.477, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2610, decode.acc_seg: 90.2394, loss: 0.2610 2023-01-06 00:15:33,877 - mmseg - INFO - Iter [7900/160000] lr: 5.704e-05, eta: 18:24:00, time: 0.422, data_time: 0.010, memory: 9591, decode.loss_ce: 0.2593, decode.acc_seg: 89.9139, loss: 0.2593 2023-01-06 00:15:54,986 - mmseg - INFO - Iter [7950/160000] lr: 5.702e-05, eta: 18:23:26, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2963, decode.acc_seg: 88.8952, loss: 0.2963 2023-01-06 00:16:16,257 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:16:16,258 - mmseg - INFO - Iter [8000/160000] lr: 5.700e-05, eta: 18:22:55, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2768, decode.acc_seg: 89.4343, loss: 0.2768 2023-01-06 00:16:38,212 - mmseg - INFO - Iter [8050/160000] lr: 5.698e-05, eta: 18:22:37, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2548, decode.acc_seg: 90.3301, loss: 0.2548 2023-01-06 00:16:59,284 - mmseg - INFO - Iter [8100/160000] lr: 5.696e-05, eta: 18:22:02, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2518, decode.acc_seg: 90.4194, loss: 0.2518 2023-01-06 00:17:20,061 - mmseg - INFO - Iter [8150/160000] lr: 5.694e-05, eta: 18:21:22, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2656, decode.acc_seg: 90.3776, loss: 0.2656 2023-01-06 00:17:43,308 - mmseg - INFO - Iter [8200/160000] lr: 5.693e-05, eta: 18:21:28, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2616, decode.acc_seg: 90.2850, loss: 0.2616 2023-01-06 00:18:04,327 - mmseg - INFO - Iter [8250/160000] lr: 5.691e-05, eta: 18:20:52, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2629, decode.acc_seg: 89.9947, loss: 0.2629 2023-01-06 00:18:25,813 - mmseg - INFO - Iter [8300/160000] lr: 5.689e-05, eta: 18:20:25, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2426, decode.acc_seg: 90.4156, loss: 0.2426 2023-01-06 00:18:46,968 - mmseg - INFO - Iter [8350/160000] lr: 5.687e-05, eta: 18:19:52, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2743, decode.acc_seg: 89.9613, loss: 0.2743 2023-01-06 00:19:08,682 - mmseg - INFO - Iter [8400/160000] lr: 5.685e-05, eta: 18:19:30, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2767, decode.acc_seg: 89.5998, loss: 0.2767 2023-01-06 00:19:30,896 - mmseg - INFO - Iter [8450/160000] lr: 5.683e-05, eta: 18:19:16, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2715, decode.acc_seg: 89.7362, loss: 0.2715 2023-01-06 00:19:53,168 - mmseg - INFO - Iter [8500/160000] lr: 5.681e-05, eta: 18:19:03, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2498, decode.acc_seg: 90.4730, loss: 0.2498 2023-01-06 00:20:14,881 - mmseg - INFO - Iter [8550/160000] lr: 5.679e-05, eta: 18:18:41, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2634, decode.acc_seg: 90.0822, loss: 0.2634 2023-01-06 00:20:39,262 - mmseg - INFO - Iter [8600/160000] lr: 5.678e-05, eta: 18:19:05, time: 0.488, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2610, decode.acc_seg: 90.2352, loss: 0.2610 2023-01-06 00:21:00,461 - mmseg - INFO - Iter [8650/160000] lr: 5.676e-05, eta: 18:18:33, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2814, decode.acc_seg: 89.3543, loss: 0.2814 2023-01-06 00:21:21,954 - mmseg - INFO - Iter [8700/160000] lr: 5.674e-05, eta: 18:18:07, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2561, decode.acc_seg: 90.2752, loss: 0.2561 2023-01-06 00:21:42,897 - mmseg - INFO - Iter [8750/160000] lr: 5.672e-05, eta: 18:17:31, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2483, decode.acc_seg: 90.6933, loss: 0.2483 2023-01-06 00:22:04,365 - mmseg - INFO - Iter [8800/160000] lr: 5.670e-05, eta: 18:17:04, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2546, decode.acc_seg: 90.6056, loss: 0.2546 2023-01-06 00:22:25,526 - mmseg - INFO - Iter [8850/160000] lr: 5.668e-05, eta: 18:16:31, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2654, decode.acc_seg: 90.0556, loss: 0.2654 2023-01-06 00:22:47,471 - mmseg - INFO - Iter [8900/160000] lr: 5.666e-05, eta: 18:16:12, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2570, decode.acc_seg: 90.5734, loss: 0.2570 2023-01-06 00:23:11,828 - mmseg - INFO - Iter [8950/160000] lr: 5.664e-05, eta: 18:16:34, time: 0.487, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2466, decode.acc_seg: 90.6907, loss: 0.2466 2023-01-06 00:23:32,872 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:23:32,873 - mmseg - INFO - Iter [9000/160000] lr: 5.663e-05, eta: 18:16:01, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2668, decode.acc_seg: 90.1863, loss: 0.2668 2023-01-06 00:23:53,774 - mmseg - INFO - Iter [9050/160000] lr: 5.661e-05, eta: 18:15:24, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2521, decode.acc_seg: 90.4387, loss: 0.2521 2023-01-06 00:24:15,739 - mmseg - INFO - Iter [9100/160000] lr: 5.659e-05, eta: 18:15:06, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2612, decode.acc_seg: 89.7016, loss: 0.2612 2023-01-06 00:24:36,533 - mmseg - INFO - Iter [9150/160000] lr: 5.657e-05, eta: 18:14:28, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2484, decode.acc_seg: 90.5226, loss: 0.2484 2023-01-06 00:24:57,546 - mmseg - INFO - Iter [9200/160000] lr: 5.655e-05, eta: 18:13:54, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2528, decode.acc_seg: 90.4790, loss: 0.2528 2023-01-06 00:25:18,810 - mmseg - INFO - Iter [9250/160000] lr: 5.653e-05, eta: 18:13:24, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2725, decode.acc_seg: 89.7828, loss: 0.2725 2023-01-06 00:25:39,802 - mmseg - INFO - Iter [9300/160000] lr: 5.651e-05, eta: 18:12:49, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2759, decode.acc_seg: 90.0816, loss: 0.2759 2023-01-06 00:26:02,898 - mmseg - INFO - Iter [9350/160000] lr: 5.649e-05, eta: 18:12:49, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2665, decode.acc_seg: 90.3299, loss: 0.2665 2023-01-06 00:26:24,913 - mmseg - INFO - Iter [9400/160000] lr: 5.648e-05, eta: 18:12:31, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2533, decode.acc_seg: 90.4146, loss: 0.2533 2023-01-06 00:26:46,125 - mmseg - INFO - Iter [9450/160000] lr: 5.646e-05, eta: 18:12:01, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2532, decode.acc_seg: 90.3226, loss: 0.2532 2023-01-06 00:27:07,685 - mmseg - INFO - Iter [9500/160000] lr: 5.644e-05, eta: 18:11:36, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2689, decode.acc_seg: 89.7176, loss: 0.2689 2023-01-06 00:27:29,077 - mmseg - INFO - Iter [9550/160000] lr: 5.642e-05, eta: 18:11:08, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2313, decode.acc_seg: 91.1998, loss: 0.2313 2023-01-06 00:27:50,955 - mmseg - INFO - Iter [9600/160000] lr: 5.640e-05, eta: 18:10:49, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2296, decode.acc_seg: 91.1035, loss: 0.2296 2023-01-06 00:28:12,289 - mmseg - INFO - Iter [9650/160000] lr: 5.638e-05, eta: 18:10:20, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2647, decode.acc_seg: 90.0607, loss: 0.2647 2023-01-06 00:28:35,889 - mmseg - INFO - Iter [9700/160000] lr: 5.636e-05, eta: 18:10:27, time: 0.472, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2645, decode.acc_seg: 90.1216, loss: 0.2645 2023-01-06 00:28:57,479 - mmseg - INFO - Iter [9750/160000] lr: 5.634e-05, eta: 18:10:02, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2390, decode.acc_seg: 90.8516, loss: 0.2390 2023-01-06 00:29:19,043 - mmseg - INFO - Iter [9800/160000] lr: 5.633e-05, eta: 18:09:38, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2391, decode.acc_seg: 90.9703, loss: 0.2391 2023-01-06 00:29:39,885 - mmseg - INFO - Iter [9850/160000] lr: 5.631e-05, eta: 18:09:02, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2436, decode.acc_seg: 90.7535, loss: 0.2436 2023-01-06 00:30:01,177 - mmseg - INFO - Iter [9900/160000] lr: 5.629e-05, eta: 18:08:33, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2409, decode.acc_seg: 90.8546, loss: 0.2409 2023-01-06 00:30:23,148 - mmseg - INFO - Iter [9950/160000] lr: 5.627e-05, eta: 18:08:15, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2845, decode.acc_seg: 89.6993, loss: 0.2845 2023-01-06 00:30:45,220 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:30:45,221 - mmseg - INFO - Iter [10000/160000] lr: 5.625e-05, eta: 18:07:57, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2679, decode.acc_seg: 89.9684, loss: 0.2679 2023-01-06 00:31:08,934 - mmseg - INFO - Iter [10050/160000] lr: 5.623e-05, eta: 18:08:05, time: 0.474, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2437, decode.acc_seg: 90.9236, loss: 0.2437 2023-01-06 00:31:30,308 - mmseg - INFO - Iter [10100/160000] lr: 5.621e-05, eta: 18:07:37, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2611, decode.acc_seg: 90.3908, loss: 0.2611 2023-01-06 00:31:52,605 - mmseg - INFO - Iter [10150/160000] lr: 5.619e-05, eta: 18:07:23, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2478, decode.acc_seg: 90.6647, loss: 0.2478 2023-01-06 00:32:14,052 - mmseg - INFO - Iter [10200/160000] lr: 5.618e-05, eta: 18:06:57, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2846, decode.acc_seg: 89.6287, loss: 0.2846 2023-01-06 00:32:35,492 - mmseg - INFO - Iter [10250/160000] lr: 5.616e-05, eta: 18:06:30, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2445, decode.acc_seg: 90.8226, loss: 0.2445 2023-01-06 00:32:56,899 - mmseg - INFO - Iter [10300/160000] lr: 5.614e-05, eta: 18:06:03, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2617, decode.acc_seg: 90.4035, loss: 0.2617 2023-01-06 00:33:18,342 - mmseg - INFO - Iter [10350/160000] lr: 5.612e-05, eta: 18:05:37, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2275, decode.acc_seg: 91.1989, loss: 0.2275 2023-01-06 00:33:39,756 - mmseg - INFO - Iter [10400/160000] lr: 5.610e-05, eta: 18:05:10, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2348, decode.acc_seg: 91.0823, loss: 0.2348 2023-01-06 00:34:03,396 - mmseg - INFO - Iter [10450/160000] lr: 5.608e-05, eta: 18:05:15, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2340, decode.acc_seg: 91.1045, loss: 0.2340 2023-01-06 00:34:25,645 - mmseg - INFO - Iter [10500/160000] lr: 5.606e-05, eta: 18:05:00, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2542, decode.acc_seg: 90.3925, loss: 0.2542 2023-01-06 00:34:46,741 - mmseg - INFO - Iter [10550/160000] lr: 5.604e-05, eta: 18:04:29, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2364, decode.acc_seg: 90.8899, loss: 0.2364 2023-01-06 00:35:08,184 - mmseg - INFO - Iter [10600/160000] lr: 5.603e-05, eta: 18:04:03, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2368, decode.acc_seg: 90.9526, loss: 0.2368 2023-01-06 00:35:29,359 - mmseg - INFO - Iter [10650/160000] lr: 5.601e-05, eta: 18:03:32, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2506, decode.acc_seg: 90.5259, loss: 0.2506 2023-01-06 00:35:50,581 - mmseg - INFO - Iter [10700/160000] lr: 5.599e-05, eta: 18:03:03, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2273, decode.acc_seg: 91.3265, loss: 0.2273 2023-01-06 00:36:12,368 - mmseg - INFO - Iter [10750/160000] lr: 5.597e-05, eta: 18:02:42, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2249, decode.acc_seg: 91.5140, loss: 0.2249 2023-01-06 00:36:35,837 - mmseg - INFO - Iter [10800/160000] lr: 5.595e-05, eta: 18:02:44, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2450, decode.acc_seg: 90.5504, loss: 0.2450 2023-01-06 00:36:57,501 - mmseg - INFO - Iter [10850/160000] lr: 5.593e-05, eta: 18:02:20, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2193, decode.acc_seg: 91.4764, loss: 0.2193 2023-01-06 00:37:19,285 - mmseg - INFO - Iter [10900/160000] lr: 5.591e-05, eta: 18:01:59, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2254, decode.acc_seg: 91.3711, loss: 0.2254 2023-01-06 00:37:40,764 - mmseg - INFO - Iter [10950/160000] lr: 5.589e-05, eta: 18:01:33, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2284, decode.acc_seg: 91.4756, loss: 0.2284 2023-01-06 00:38:01,601 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:38:01,601 - mmseg - INFO - Iter [11000/160000] lr: 5.588e-05, eta: 18:00:58, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2503, decode.acc_seg: 90.5360, loss: 0.2503 2023-01-06 00:38:23,356 - mmseg - INFO - Iter [11050/160000] lr: 5.586e-05, eta: 18:00:37, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2390, decode.acc_seg: 91.2837, loss: 0.2390 2023-01-06 00:38:45,287 - mmseg - INFO - Iter [11100/160000] lr: 5.584e-05, eta: 18:00:17, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2401, decode.acc_seg: 90.8409, loss: 0.2401 2023-01-06 00:39:06,963 - mmseg - INFO - Iter [11150/160000] lr: 5.582e-05, eta: 17:59:54, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2270, decode.acc_seg: 91.2473, loss: 0.2270 2023-01-06 00:39:31,922 - mmseg - INFO - Iter [11200/160000] lr: 5.580e-05, eta: 18:00:14, time: 0.499, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2089, decode.acc_seg: 91.8807, loss: 0.2089 2023-01-06 00:39:53,358 - mmseg - INFO - Iter [11250/160000] lr: 5.578e-05, eta: 17:59:48, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2580, decode.acc_seg: 90.3777, loss: 0.2580 2023-01-06 00:40:14,619 - mmseg - INFO - Iter [11300/160000] lr: 5.576e-05, eta: 17:59:20, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2578, decode.acc_seg: 90.3848, loss: 0.2578 2023-01-06 00:40:35,496 - mmseg - INFO - Iter [11350/160000] lr: 5.574e-05, eta: 17:58:46, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2331, decode.acc_seg: 91.0129, loss: 0.2331 2023-01-06 00:40:56,937 - mmseg - INFO - Iter [11400/160000] lr: 5.573e-05, eta: 17:58:20, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2278, decode.acc_seg: 91.2346, loss: 0.2278 2023-01-06 00:41:17,842 - mmseg - INFO - Iter [11450/160000] lr: 5.571e-05, eta: 17:57:47, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2329, decode.acc_seg: 90.8914, loss: 0.2329 2023-01-06 00:41:39,462 - mmseg - INFO - Iter [11500/160000] lr: 5.569e-05, eta: 17:57:24, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2172, decode.acc_seg: 91.5762, loss: 0.2172 2023-01-06 00:42:02,587 - mmseg - INFO - Iter [11550/160000] lr: 5.567e-05, eta: 17:57:19, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2356, decode.acc_seg: 91.1301, loss: 0.2356 2023-01-06 00:42:23,535 - mmseg - INFO - Iter [11600/160000] lr: 5.565e-05, eta: 17:56:47, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2516, decode.acc_seg: 90.4610, loss: 0.2516 2023-01-06 00:42:44,946 - mmseg - INFO - Iter [11650/160000] lr: 5.563e-05, eta: 17:56:21, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2527, decode.acc_seg: 90.7490, loss: 0.2527 2023-01-06 00:43:06,848 - mmseg - INFO - Iter [11700/160000] lr: 5.561e-05, eta: 17:56:00, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2372, decode.acc_seg: 91.3858, loss: 0.2372 2023-01-06 00:43:28,296 - mmseg - INFO - Iter [11750/160000] lr: 5.559e-05, eta: 17:55:35, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2392, decode.acc_seg: 90.9833, loss: 0.2392 2023-01-06 00:43:50,265 - mmseg - INFO - Iter [11800/160000] lr: 5.558e-05, eta: 17:55:15, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2055, decode.acc_seg: 91.9841, loss: 0.2055 2023-01-06 00:44:11,467 - mmseg - INFO - Iter [11850/160000] lr: 5.556e-05, eta: 17:54:47, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2377, decode.acc_seg: 90.9311, loss: 0.2377 2023-01-06 00:44:33,290 - mmseg - INFO - Iter [11900/160000] lr: 5.554e-05, eta: 17:54:25, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2297, decode.acc_seg: 91.1331, loss: 0.2297 2023-01-06 00:44:57,610 - mmseg - INFO - Iter [11950/160000] lr: 5.552e-05, eta: 17:54:36, time: 0.487, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2338, decode.acc_seg: 91.1703, loss: 0.2338 2023-01-06 00:45:18,626 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:45:18,627 - mmseg - INFO - Iter [12000/160000] lr: 5.550e-05, eta: 17:54:04, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2384, decode.acc_seg: 90.9078, loss: 0.2384 2023-01-06 00:45:40,101 - mmseg - INFO - Iter [12050/160000] lr: 5.548e-05, eta: 17:53:39, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2483, decode.acc_seg: 90.6190, loss: 0.2483 2023-01-06 00:46:01,212 - mmseg - INFO - Iter [12100/160000] lr: 5.546e-05, eta: 17:53:09, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2492, decode.acc_seg: 90.7188, loss: 0.2492 2023-01-06 00:46:23,189 - mmseg - INFO - Iter [12150/160000] lr: 5.544e-05, eta: 17:52:50, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2304, decode.acc_seg: 91.3293, loss: 0.2304 2023-01-06 00:46:44,277 - mmseg - INFO - Iter [12200/160000] lr: 5.543e-05, eta: 17:52:20, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2323, decode.acc_seg: 91.2583, loss: 0.2323 2023-01-06 00:47:05,523 - mmseg - INFO - Iter [12250/160000] lr: 5.541e-05, eta: 17:51:52, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2252, decode.acc_seg: 91.2132, loss: 0.2252 2023-01-06 00:47:28,620 - mmseg - INFO - Iter [12300/160000] lr: 5.539e-05, eta: 17:51:46, time: 0.462, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2262, decode.acc_seg: 91.2547, loss: 0.2262 2023-01-06 00:47:49,814 - mmseg - INFO - Iter [12350/160000] lr: 5.537e-05, eta: 17:51:17, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2131, decode.acc_seg: 91.7015, loss: 0.2131 2023-01-06 00:48:11,423 - mmseg - INFO - Iter [12400/160000] lr: 5.535e-05, eta: 17:50:54, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2213, decode.acc_seg: 91.6569, loss: 0.2213 2023-01-06 00:48:33,174 - mmseg - INFO - Iter [12450/160000] lr: 5.533e-05, eta: 17:50:32, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2139, decode.acc_seg: 91.7656, loss: 0.2139 2023-01-06 00:48:55,295 - mmseg - INFO - Iter [12500/160000] lr: 5.531e-05, eta: 17:50:14, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2326, decode.acc_seg: 91.3175, loss: 0.2326 2023-01-06 00:49:16,406 - mmseg - INFO - Iter [12550/160000] lr: 5.529e-05, eta: 17:49:45, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2306, decode.acc_seg: 91.2566, loss: 0.2306 2023-01-06 00:49:38,105 - mmseg - INFO - Iter [12600/160000] lr: 5.528e-05, eta: 17:49:22, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2370, decode.acc_seg: 91.1599, loss: 0.2370 2023-01-06 00:50:01,458 - mmseg - INFO - Iter [12650/160000] lr: 5.526e-05, eta: 17:49:19, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2250, decode.acc_seg: 91.3504, loss: 0.2250 2023-01-06 00:50:22,904 - mmseg - INFO - Iter [12700/160000] lr: 5.524e-05, eta: 17:48:53, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2259, decode.acc_seg: 91.3600, loss: 0.2259 2023-01-06 00:50:44,984 - mmseg - INFO - Iter [12750/160000] lr: 5.522e-05, eta: 17:48:35, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2131, decode.acc_seg: 91.6937, loss: 0.2131 2023-01-06 00:51:06,257 - mmseg - INFO - Iter [12800/160000] lr: 5.520e-05, eta: 17:48:08, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2195, decode.acc_seg: 91.7731, loss: 0.2195 2023-01-06 00:51:27,701 - mmseg - INFO - Iter [12850/160000] lr: 5.518e-05, eta: 17:47:42, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2372, decode.acc_seg: 90.9297, loss: 0.2372 2023-01-06 00:51:48,943 - mmseg - INFO - Iter [12900/160000] lr: 5.516e-05, eta: 17:47:14, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2278, decode.acc_seg: 91.2315, loss: 0.2278 2023-01-06 00:52:09,793 - mmseg - INFO - Iter [12950/160000] lr: 5.514e-05, eta: 17:46:42, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2094, decode.acc_seg: 91.9826, loss: 0.2094 2023-01-06 00:52:30,751 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:52:30,752 - mmseg - INFO - Iter [13000/160000] lr: 5.513e-05, eta: 17:46:11, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2246, decode.acc_seg: 91.2768, loss: 0.2246 2023-01-06 00:52:55,188 - mmseg - INFO - Iter [13050/160000] lr: 5.511e-05, eta: 17:46:20, time: 0.488, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2072, decode.acc_seg: 92.1928, loss: 0.2072 2023-01-06 00:53:16,915 - mmseg - INFO - Iter [13100/160000] lr: 5.509e-05, eta: 17:45:57, time: 0.435, data_time: 0.013, memory: 9591, decode.loss_ce: 0.2160, decode.acc_seg: 91.6662, loss: 0.2160 2023-01-06 00:53:38,478 - mmseg - INFO - Iter [13150/160000] lr: 5.507e-05, eta: 17:45:33, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2158, decode.acc_seg: 91.8580, loss: 0.2158 2023-01-06 00:54:00,220 - mmseg - INFO - Iter [13200/160000] lr: 5.505e-05, eta: 17:45:11, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2263, decode.acc_seg: 91.2977, loss: 0.2263 2023-01-06 00:54:21,900 - mmseg - INFO - Iter [13250/160000] lr: 5.503e-05, eta: 17:44:49, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2040, decode.acc_seg: 92.0855, loss: 0.2040 2023-01-06 00:54:43,328 - mmseg - INFO - Iter [13300/160000] lr: 5.501e-05, eta: 17:44:23, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2160, decode.acc_seg: 91.7501, loss: 0.2160 2023-01-06 00:55:04,379 - mmseg - INFO - Iter [13350/160000] lr: 5.499e-05, eta: 17:43:54, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2234, decode.acc_seg: 91.5591, loss: 0.2234 2023-01-06 00:55:27,465 - mmseg - INFO - Iter [13400/160000] lr: 5.498e-05, eta: 17:43:46, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2298, decode.acc_seg: 91.4683, loss: 0.2298 2023-01-06 00:55:48,691 - mmseg - INFO - Iter [13450/160000] lr: 5.496e-05, eta: 17:43:19, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2242, decode.acc_seg: 91.4517, loss: 0.2242 2023-01-06 00:56:10,587 - mmseg - INFO - Iter [13500/160000] lr: 5.494e-05, eta: 17:42:58, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2295, decode.acc_seg: 91.3186, loss: 0.2295 2023-01-06 00:56:32,447 - mmseg - INFO - Iter [13550/160000] lr: 5.492e-05, eta: 17:42:37, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2292, decode.acc_seg: 91.3064, loss: 0.2292 2023-01-06 00:56:54,058 - mmseg - INFO - Iter [13600/160000] lr: 5.490e-05, eta: 17:42:14, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2179, decode.acc_seg: 91.3279, loss: 0.2179 2023-01-06 00:57:16,106 - mmseg - INFO - Iter [13650/160000] lr: 5.488e-05, eta: 17:41:55, time: 0.441, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2100, decode.acc_seg: 92.0710, loss: 0.2100 2023-01-06 00:57:37,864 - mmseg - INFO - Iter [13700/160000] lr: 5.486e-05, eta: 17:41:33, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2123, decode.acc_seg: 91.7754, loss: 0.2123 2023-01-06 00:58:00,115 - mmseg - INFO - Iter [13750/160000] lr: 5.484e-05, eta: 17:41:17, time: 0.445, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2022, decode.acc_seg: 91.8556, loss: 0.2022 2023-01-06 00:58:23,270 - mmseg - INFO - Iter [13800/160000] lr: 5.483e-05, eta: 17:41:10, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2307, decode.acc_seg: 91.0819, loss: 0.2307 2023-01-06 00:58:44,507 - mmseg - INFO - Iter [13850/160000] lr: 5.481e-05, eta: 17:40:42, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2113, decode.acc_seg: 91.6076, loss: 0.2113 2023-01-06 00:59:06,315 - mmseg - INFO - Iter [13900/160000] lr: 5.479e-05, eta: 17:40:21, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2183, decode.acc_seg: 91.6594, loss: 0.2183 2023-01-06 00:59:27,686 - mmseg - INFO - Iter [13950/160000] lr: 5.477e-05, eta: 17:39:55, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1944, decode.acc_seg: 92.4118, loss: 0.1944 2023-01-06 00:59:50,431 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 00:59:50,431 - mmseg - INFO - Iter [14000/160000] lr: 5.475e-05, eta: 17:39:43, time: 0.455, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2168, decode.acc_seg: 91.5664, loss: 0.2168 2023-01-06 01:00:12,409 - mmseg - INFO - Iter [14050/160000] lr: 5.473e-05, eta: 17:39:23, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2081, decode.acc_seg: 92.2518, loss: 0.2081 2023-01-06 01:00:34,141 - mmseg - INFO - Iter [14100/160000] lr: 5.471e-05, eta: 17:39:01, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2150, decode.acc_seg: 91.5236, loss: 0.2150 2023-01-06 01:00:57,277 - mmseg - INFO - Iter [14150/160000] lr: 5.469e-05, eta: 17:38:53, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2119, decode.acc_seg: 91.8954, loss: 0.2119 2023-01-06 01:01:18,500 - mmseg - INFO - Iter [14200/160000] lr: 5.468e-05, eta: 17:38:26, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2301, decode.acc_seg: 91.3090, loss: 0.2301 2023-01-06 01:01:40,241 - mmseg - INFO - Iter [14250/160000] lr: 5.466e-05, eta: 17:38:04, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2227, decode.acc_seg: 91.4459, loss: 0.2227 2023-01-06 01:02:01,614 - mmseg - INFO - Iter [14300/160000] lr: 5.464e-05, eta: 17:37:38, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2305, decode.acc_seg: 91.1114, loss: 0.2305 2023-01-06 01:02:22,568 - mmseg - INFO - Iter [14350/160000] lr: 5.462e-05, eta: 17:37:08, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2090, decode.acc_seg: 91.9465, loss: 0.2090 2023-01-06 01:02:43,273 - mmseg - INFO - Iter [14400/160000] lr: 5.460e-05, eta: 17:36:35, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2283, decode.acc_seg: 91.4372, loss: 0.2283 2023-01-06 01:03:05,373 - mmseg - INFO - Iter [14450/160000] lr: 5.458e-05, eta: 17:36:17, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2018, decode.acc_seg: 92.2559, loss: 0.2018 2023-01-06 01:03:27,061 - mmseg - INFO - Iter [14500/160000] lr: 5.456e-05, eta: 17:35:54, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2365, decode.acc_seg: 91.1261, loss: 0.2365 2023-01-06 01:03:50,183 - mmseg - INFO - Iter [14550/160000] lr: 5.454e-05, eta: 17:35:46, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2040, decode.acc_seg: 92.0059, loss: 0.2040 2023-01-06 01:04:11,060 - mmseg - INFO - Iter [14600/160000] lr: 5.453e-05, eta: 17:35:15, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2230, decode.acc_seg: 91.7542, loss: 0.2230 2023-01-06 01:04:32,747 - mmseg - INFO - Iter [14650/160000] lr: 5.451e-05, eta: 17:34:52, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2317, decode.acc_seg: 91.2074, loss: 0.2317 2023-01-06 01:04:54,316 - mmseg - INFO - Iter [14700/160000] lr: 5.449e-05, eta: 17:34:29, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1976, decode.acc_seg: 92.3329, loss: 0.1976 2023-01-06 01:05:15,976 - mmseg - INFO - Iter [14750/160000] lr: 5.447e-05, eta: 17:34:06, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2051, decode.acc_seg: 91.7388, loss: 0.2051 2023-01-06 01:05:38,005 - mmseg - INFO - Iter [14800/160000] lr: 5.445e-05, eta: 17:33:46, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2183, decode.acc_seg: 91.4364, loss: 0.2183 2023-01-06 01:05:59,482 - mmseg - INFO - Iter [14850/160000] lr: 5.443e-05, eta: 17:33:22, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2171, decode.acc_seg: 91.3872, loss: 0.2171 2023-01-06 01:06:23,014 - mmseg - INFO - Iter [14900/160000] lr: 5.441e-05, eta: 17:33:17, time: 0.471, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2118, decode.acc_seg: 92.0920, loss: 0.2118 2023-01-06 01:06:44,178 - mmseg - INFO - Iter [14950/160000] lr: 5.439e-05, eta: 17:32:49, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2087, decode.acc_seg: 91.8134, loss: 0.2087 2023-01-06 01:07:05,114 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:07:05,115 - mmseg - INFO - Iter [15000/160000] lr: 5.438e-05, eta: 17:32:20, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2011, decode.acc_seg: 92.2449, loss: 0.2011 2023-01-06 01:07:26,649 - mmseg - INFO - Iter [15050/160000] lr: 5.436e-05, eta: 17:31:55, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2041, decode.acc_seg: 91.9062, loss: 0.2041 2023-01-06 01:07:47,967 - mmseg - INFO - Iter [15100/160000] lr: 5.434e-05, eta: 17:31:29, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2097, decode.acc_seg: 91.9028, loss: 0.2097 2023-01-06 01:08:09,077 - mmseg - INFO - Iter [15150/160000] lr: 5.432e-05, eta: 17:31:01, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2070, decode.acc_seg: 92.0591, loss: 0.2070 2023-01-06 01:08:30,507 - mmseg - INFO - Iter [15200/160000] lr: 5.430e-05, eta: 17:30:36, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2116, decode.acc_seg: 91.7463, loss: 0.2116 2023-01-06 01:08:52,984 - mmseg - INFO - Iter [15250/160000] lr: 5.428e-05, eta: 17:30:21, time: 0.449, data_time: 0.019, memory: 9591, decode.loss_ce: 0.2189, decode.acc_seg: 91.7363, loss: 0.2189 2023-01-06 01:09:17,297 - mmseg - INFO - Iter [15300/160000] lr: 5.426e-05, eta: 17:30:23, time: 0.486, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1987, decode.acc_seg: 92.2296, loss: 0.1987 2023-01-06 01:09:39,021 - mmseg - INFO - Iter [15350/160000] lr: 5.424e-05, eta: 17:30:01, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2081, decode.acc_seg: 91.9397, loss: 0.2081 2023-01-06 01:10:01,050 - mmseg - INFO - Iter [15400/160000] lr: 5.423e-05, eta: 17:29:42, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2272, decode.acc_seg: 91.4197, loss: 0.2272 2023-01-06 01:10:23,561 - mmseg - INFO - Iter [15450/160000] lr: 5.421e-05, eta: 17:29:27, time: 0.451, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2028, decode.acc_seg: 92.0762, loss: 0.2028 2023-01-06 01:10:44,893 - mmseg - INFO - Iter [15500/160000] lr: 5.419e-05, eta: 17:29:01, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2163, decode.acc_seg: 91.7316, loss: 0.2163 2023-01-06 01:11:06,126 - mmseg - INFO - Iter [15550/160000] lr: 5.417e-05, eta: 17:28:34, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2055, decode.acc_seg: 91.9771, loss: 0.2055 2023-01-06 01:11:27,600 - mmseg - INFO - Iter [15600/160000] lr: 5.415e-05, eta: 17:28:09, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2103, decode.acc_seg: 91.9782, loss: 0.2103 2023-01-06 01:11:51,651 - mmseg - INFO - Iter [15650/160000] lr: 5.413e-05, eta: 17:28:08, time: 0.480, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2251, decode.acc_seg: 91.3534, loss: 0.2251 2023-01-06 01:12:12,548 - mmseg - INFO - Iter [15700/160000] lr: 5.411e-05, eta: 17:27:39, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2079, decode.acc_seg: 92.0232, loss: 0.2079 2023-01-06 01:12:33,576 - mmseg - INFO - Iter [15750/160000] lr: 5.409e-05, eta: 17:27:10, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2034, decode.acc_seg: 92.0940, loss: 0.2034 2023-01-06 01:12:54,889 - mmseg - INFO - Iter [15800/160000] lr: 5.408e-05, eta: 17:26:44, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1944, decode.acc_seg: 92.4132, loss: 0.1944 2023-01-06 01:13:17,301 - mmseg - INFO - Iter [15850/160000] lr: 5.406e-05, eta: 17:26:28, time: 0.448, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2340, decode.acc_seg: 91.1282, loss: 0.2340 2023-01-06 01:13:39,532 - mmseg - INFO - Iter [15900/160000] lr: 5.404e-05, eta: 17:26:10, time: 0.445, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2147, decode.acc_seg: 91.9220, loss: 0.2147 2023-01-06 01:14:00,750 - mmseg - INFO - Iter [15950/160000] lr: 5.402e-05, eta: 17:25:43, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1823, decode.acc_seg: 92.6190, loss: 0.1823 2023-01-06 01:14:24,017 - mmseg - INFO - Saving checkpoint at 16000 iterations 2023-01-06 01:14:28,056 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:14:28,057 - mmseg - INFO - Iter [16000/160000] lr: 5.400e-05, eta: 17:26:11, time: 0.546, data_time: 0.057, memory: 9591, decode.loss_ce: 0.2103, decode.acc_seg: 91.6913, loss: 0.2103 2023-01-06 01:15:00,344 - mmseg - INFO - per class results: 2023-01-06 01:15:00,347 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 95.94 | 98.73 | | sidewalk | 70.06 | 78.02 | | building | 87.03 | 94.81 | | wall | 23.25 | 24.49 | | fence | 33.43 | 45.62 | | pole | 45.49 | 53.06 | | traffic light | 41.19 | 47.84 | | traffic sign | 58.34 | 67.74 | | vegetation | 89.27 | 96.23 | | terrain | 50.83 | 59.26 | | sky | 92.24 | 97.29 | | person | 64.42 | 80.51 | | rider | 24.16 | 28.43 | | car | 89.02 | 95.87 | | truck | 28.3 | 34.01 | | bus | 43.95 | 51.66 | | train | 26.81 | 33.43 | | motorcycle | 19.86 | 22.49 | | bicycle | 60.52 | 75.44 | +---------------+-------+-------+ 2023-01-06 01:15:00,347 - mmseg - INFO - Summary: 2023-01-06 01:15:00,347 - mmseg - INFO - +-------+-------+-------+ | aAcc | mIoU | mAcc | +-------+-------+-------+ | 92.73 | 54.95 | 62.36 | +-------+-------+-------+ 2023-01-06 01:15:00,348 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:15:00,348 - mmseg - INFO - Iter(val) [63] aAcc: 0.9273, mIoU: 0.5495, mAcc: 0.6236, IoU.road: 0.9594, IoU.sidewalk: 0.7006, IoU.building: 0.8703, IoU.wall: 0.2325, IoU.fence: 0.3343, IoU.pole: 0.4549, IoU.traffic light: 0.4119, IoU.traffic sign: 0.5834, IoU.vegetation: 0.8927, IoU.terrain: 0.5083, IoU.sky: 0.9224, IoU.person: 0.6442, IoU.rider: 0.2416, IoU.car: 0.8902, IoU.truck: 0.2830, IoU.bus: 0.4395, IoU.train: 0.2681, IoU.motorcycle: 0.1986, IoU.bicycle: 0.6052, Acc.road: 0.9873, Acc.sidewalk: 0.7802, Acc.building: 0.9481, Acc.wall: 0.2449, Acc.fence: 0.4562, Acc.pole: 0.5306, Acc.traffic light: 0.4784, Acc.traffic sign: 0.6774, Acc.vegetation: 0.9623, Acc.terrain: 0.5926, Acc.sky: 0.9729, Acc.person: 0.8051, Acc.rider: 0.2843, Acc.car: 0.9587, Acc.truck: 0.3401, Acc.bus: 0.5166, Acc.train: 0.3343, Acc.motorcycle: 0.2249, Acc.bicycle: 0.7544 2023-01-06 01:15:22,460 - mmseg - INFO - Iter [16050/160000] lr: 5.398e-05, eta: 17:30:42, time: 1.087, data_time: 0.656, memory: 9591, decode.loss_ce: 0.2086, decode.acc_seg: 91.9793, loss: 0.2086 2023-01-06 01:15:43,828 - mmseg - INFO - Iter [16100/160000] lr: 5.396e-05, eta: 17:30:15, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2010, decode.acc_seg: 92.0396, loss: 0.2010 2023-01-06 01:16:04,882 - mmseg - INFO - Iter [16150/160000] lr: 5.394e-05, eta: 17:29:46, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1993, decode.acc_seg: 92.2796, loss: 0.1993 2023-01-06 01:16:26,683 - mmseg - INFO - Iter [16200/160000] lr: 5.393e-05, eta: 17:29:23, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2014, decode.acc_seg: 92.2531, loss: 0.2014 2023-01-06 01:16:48,278 - mmseg - INFO - Iter [16250/160000] lr: 5.391e-05, eta: 17:28:59, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1997, decode.acc_seg: 92.2444, loss: 0.1997 2023-01-06 01:17:09,853 - mmseg - INFO - Iter [16300/160000] lr: 5.389e-05, eta: 17:28:34, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1929, decode.acc_seg: 92.2815, loss: 0.1929 2023-01-06 01:17:31,784 - mmseg - INFO - Iter [16350/160000] lr: 5.387e-05, eta: 17:28:13, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1921, decode.acc_seg: 92.3013, loss: 0.1921 2023-01-06 01:17:55,253 - mmseg - INFO - Iter [16400/160000] lr: 5.385e-05, eta: 17:28:04, time: 0.469, data_time: 0.055, memory: 9591, decode.loss_ce: 0.2002, decode.acc_seg: 92.1664, loss: 0.2002 2023-01-06 01:18:16,280 - mmseg - INFO - Iter [16450/160000] lr: 5.383e-05, eta: 17:27:35, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1934, decode.acc_seg: 92.3109, loss: 0.1934 2023-01-06 01:18:37,453 - mmseg - INFO - Iter [16500/160000] lr: 5.381e-05, eta: 17:27:07, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1791, decode.acc_seg: 92.8344, loss: 0.1791 2023-01-06 01:18:59,254 - mmseg - INFO - Iter [16550/160000] lr: 5.379e-05, eta: 17:26:44, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1923, decode.acc_seg: 92.4072, loss: 0.1923 2023-01-06 01:19:21,533 - mmseg - INFO - Iter [16600/160000] lr: 5.378e-05, eta: 17:26:25, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1950, decode.acc_seg: 92.4580, loss: 0.1950 2023-01-06 01:19:43,929 - mmseg - INFO - Iter [16650/160000] lr: 5.376e-05, eta: 17:26:08, time: 0.448, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2075, decode.acc_seg: 91.8752, loss: 0.2075 2023-01-06 01:20:05,328 - mmseg - INFO - Iter [16700/160000] lr: 5.374e-05, eta: 17:25:42, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2178, decode.acc_seg: 91.8540, loss: 0.2178 2023-01-06 01:20:29,253 - mmseg - INFO - Iter [16750/160000] lr: 5.372e-05, eta: 17:25:37, time: 0.479, data_time: 0.058, memory: 9591, decode.loss_ce: 0.2076, decode.acc_seg: 92.0053, loss: 0.2076 2023-01-06 01:20:50,548 - mmseg - INFO - Iter [16800/160000] lr: 5.370e-05, eta: 17:25:10, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2095, decode.acc_seg: 91.8671, loss: 0.2095 2023-01-06 01:21:11,812 - mmseg - INFO - Iter [16850/160000] lr: 5.368e-05, eta: 17:24:43, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1879, decode.acc_seg: 92.7505, loss: 0.1879 2023-01-06 01:21:34,115 - mmseg - INFO - Iter [16900/160000] lr: 5.366e-05, eta: 17:24:24, time: 0.446, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1841, decode.acc_seg: 92.6676, loss: 0.1841 2023-01-06 01:21:55,654 - mmseg - INFO - Iter [16950/160000] lr: 5.364e-05, eta: 17:24:00, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2139, decode.acc_seg: 92.0440, loss: 0.2139 2023-01-06 01:22:17,200 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:22:17,201 - mmseg - INFO - Iter [17000/160000] lr: 5.363e-05, eta: 17:23:35, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2058, decode.acc_seg: 91.8307, loss: 0.2058 2023-01-06 01:22:39,342 - mmseg - INFO - Iter [17050/160000] lr: 5.361e-05, eta: 17:23:15, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1938, decode.acc_seg: 92.5515, loss: 0.1938 2023-01-06 01:23:00,945 - mmseg - INFO - Iter [17100/160000] lr: 5.359e-05, eta: 17:22:50, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1954, decode.acc_seg: 92.4308, loss: 0.1954 2023-01-06 01:23:24,181 - mmseg - INFO - Iter [17150/160000] lr: 5.357e-05, eta: 17:22:40, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2013, decode.acc_seg: 92.2266, loss: 0.2013 2023-01-06 01:23:45,443 - mmseg - INFO - Iter [17200/160000] lr: 5.355e-05, eta: 17:22:13, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1991, decode.acc_seg: 92.2824, loss: 0.1991 2023-01-06 01:24:06,575 - mmseg - INFO - Iter [17250/160000] lr: 5.353e-05, eta: 17:21:45, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1883, decode.acc_seg: 92.4924, loss: 0.1883 2023-01-06 01:24:27,670 - mmseg - INFO - Iter [17300/160000] lr: 5.351e-05, eta: 17:21:16, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2067, decode.acc_seg: 92.1145, loss: 0.2067 2023-01-06 01:24:49,420 - mmseg - INFO - Iter [17350/160000] lr: 5.349e-05, eta: 17:20:53, time: 0.436, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1926, decode.acc_seg: 92.4943, loss: 0.1926 2023-01-06 01:25:10,739 - mmseg - INFO - Iter [17400/160000] lr: 5.348e-05, eta: 17:20:26, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2042, decode.acc_seg: 92.2376, loss: 0.2042 2023-01-06 01:25:32,989 - mmseg - INFO - Iter [17450/160000] lr: 5.346e-05, eta: 17:20:08, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1974, decode.acc_seg: 92.4426, loss: 0.1974 2023-01-06 01:25:56,536 - mmseg - INFO - Iter [17500/160000] lr: 5.344e-05, eta: 17:19:59, time: 0.470, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1919, decode.acc_seg: 92.4004, loss: 0.1919 2023-01-06 01:26:18,456 - mmseg - INFO - Iter [17550/160000] lr: 5.342e-05, eta: 17:19:37, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2082, decode.acc_seg: 91.7563, loss: 0.2082 2023-01-06 01:26:40,013 - mmseg - INFO - Iter [17600/160000] lr: 5.340e-05, eta: 17:19:13, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2056, decode.acc_seg: 92.1545, loss: 0.2056 2023-01-06 01:27:01,051 - mmseg - INFO - Iter [17650/160000] lr: 5.338e-05, eta: 17:18:44, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1933, decode.acc_seg: 92.5509, loss: 0.1933 2023-01-06 01:27:21,892 - mmseg - INFO - Iter [17700/160000] lr: 5.336e-05, eta: 17:18:14, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2072, decode.acc_seg: 92.1726, loss: 0.2072 2023-01-06 01:27:42,857 - mmseg - INFO - Iter [17750/160000] lr: 5.334e-05, eta: 17:17:44, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1872, decode.acc_seg: 92.7133, loss: 0.1872 2023-01-06 01:28:04,116 - mmseg - INFO - Iter [17800/160000] lr: 5.333e-05, eta: 17:17:17, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1962, decode.acc_seg: 92.5596, loss: 0.1962 2023-01-06 01:28:25,819 - mmseg - INFO - Iter [17850/160000] lr: 5.331e-05, eta: 17:16:54, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1870, decode.acc_seg: 92.6249, loss: 0.1870 2023-01-06 01:28:49,127 - mmseg - INFO - Iter [17900/160000] lr: 5.329e-05, eta: 17:16:44, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2057, decode.acc_seg: 91.9599, loss: 0.2057 2023-01-06 01:29:10,093 - mmseg - INFO - Iter [17950/160000] lr: 5.327e-05, eta: 17:16:14, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2052, decode.acc_seg: 91.9962, loss: 0.2052 2023-01-06 01:29:30,942 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:29:30,943 - mmseg - INFO - Iter [18000/160000] lr: 5.325e-05, eta: 17:15:44, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2075, decode.acc_seg: 92.0593, loss: 0.2075 2023-01-06 01:29:52,341 - mmseg - INFO - Iter [18050/160000] lr: 5.323e-05, eta: 17:15:19, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1942, decode.acc_seg: 92.4051, loss: 0.1942 2023-01-06 01:30:13,281 - mmseg - INFO - Iter [18100/160000] lr: 5.321e-05, eta: 17:14:49, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1963, decode.acc_seg: 92.3004, loss: 0.1963 2023-01-06 01:30:34,631 - mmseg - INFO - Iter [18150/160000] lr: 5.319e-05, eta: 17:14:23, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1747, decode.acc_seg: 93.2484, loss: 0.1747 2023-01-06 01:30:56,322 - mmseg - INFO - Iter [18200/160000] lr: 5.318e-05, eta: 17:14:00, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1962, decode.acc_seg: 92.3570, loss: 0.1962 2023-01-06 01:31:19,853 - mmseg - INFO - Iter [18250/160000] lr: 5.316e-05, eta: 17:13:51, time: 0.471, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1794, decode.acc_seg: 92.9873, loss: 0.1794 2023-01-06 01:31:40,783 - mmseg - INFO - Iter [18300/160000] lr: 5.314e-05, eta: 17:13:22, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1881, decode.acc_seg: 92.5933, loss: 0.1881 2023-01-06 01:32:02,451 - mmseg - INFO - Iter [18350/160000] lr: 5.312e-05, eta: 17:12:58, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1988, decode.acc_seg: 92.4769, loss: 0.1988 2023-01-06 01:32:24,404 - mmseg - INFO - Iter [18400/160000] lr: 5.310e-05, eta: 17:12:37, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1950, decode.acc_seg: 92.3053, loss: 0.1950 2023-01-06 01:32:46,517 - mmseg - INFO - Iter [18450/160000] lr: 5.308e-05, eta: 17:12:17, time: 0.443, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2032, decode.acc_seg: 91.9687, loss: 0.2032 2023-01-06 01:33:07,654 - mmseg - INFO - Iter [18500/160000] lr: 5.306e-05, eta: 17:11:49, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2001, decode.acc_seg: 92.4276, loss: 0.2001 2023-01-06 01:33:28,449 - mmseg - INFO - Iter [18550/160000] lr: 5.304e-05, eta: 17:11:19, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1931, decode.acc_seg: 92.4917, loss: 0.1931 2023-01-06 01:33:49,846 - mmseg - INFO - Iter [18600/160000] lr: 5.303e-05, eta: 17:10:54, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1945, decode.acc_seg: 92.4043, loss: 0.1945 2023-01-06 01:34:13,266 - mmseg - INFO - Iter [18650/160000] lr: 5.301e-05, eta: 17:10:43, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1909, decode.acc_seg: 92.5983, loss: 0.1909 2023-01-06 01:34:35,464 - mmseg - INFO - Iter [18700/160000] lr: 5.299e-05, eta: 17:10:24, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1700, decode.acc_seg: 92.9709, loss: 0.1700 2023-01-06 01:34:56,736 - mmseg - INFO - Iter [18750/160000] lr: 5.297e-05, eta: 17:09:58, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1911, decode.acc_seg: 92.3911, loss: 0.1911 2023-01-06 01:35:17,724 - mmseg - INFO - Iter [18800/160000] lr: 5.295e-05, eta: 17:09:29, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1872, decode.acc_seg: 92.5949, loss: 0.1872 2023-01-06 01:35:38,894 - mmseg - INFO - Iter [18850/160000] lr: 5.293e-05, eta: 17:09:02, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2093, decode.acc_seg: 92.2542, loss: 0.2093 2023-01-06 01:36:01,003 - mmseg - INFO - Iter [18900/160000] lr: 5.291e-05, eta: 17:08:42, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1911, decode.acc_seg: 92.6164, loss: 0.1911 2023-01-06 01:36:22,752 - mmseg - INFO - Iter [18950/160000] lr: 5.289e-05, eta: 17:08:19, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2139, decode.acc_seg: 91.8189, loss: 0.2139 2023-01-06 01:36:46,502 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:36:46,503 - mmseg - INFO - Iter [19000/160000] lr: 5.288e-05, eta: 17:08:11, time: 0.475, data_time: 0.055, memory: 9591, decode.loss_ce: 0.2043, decode.acc_seg: 91.9939, loss: 0.2043 2023-01-06 01:37:07,303 - mmseg - INFO - Iter [19050/160000] lr: 5.286e-05, eta: 17:07:41, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1758, decode.acc_seg: 93.0470, loss: 0.1758 2023-01-06 01:37:29,280 - mmseg - INFO - Iter [19100/160000] lr: 5.284e-05, eta: 17:07:20, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1887, decode.acc_seg: 92.6269, loss: 0.1887 2023-01-06 01:37:50,842 - mmseg - INFO - Iter [19150/160000] lr: 5.282e-05, eta: 17:06:56, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1829, decode.acc_seg: 92.6929, loss: 0.1829 2023-01-06 01:38:12,745 - mmseg - INFO - Iter [19200/160000] lr: 5.280e-05, eta: 17:06:34, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2021, decode.acc_seg: 92.1699, loss: 0.2021 2023-01-06 01:38:34,017 - mmseg - INFO - Iter [19250/160000] lr: 5.278e-05, eta: 17:06:08, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1816, decode.acc_seg: 92.8370, loss: 0.1816 2023-01-06 01:38:56,137 - mmseg - INFO - Iter [19300/160000] lr: 5.276e-05, eta: 17:05:48, time: 0.443, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1958, decode.acc_seg: 92.1513, loss: 0.1958 2023-01-06 01:39:20,505 - mmseg - INFO - Iter [19350/160000] lr: 5.274e-05, eta: 17:05:44, time: 0.487, data_time: 0.056, memory: 9591, decode.loss_ce: 0.2121, decode.acc_seg: 91.8039, loss: 0.2121 2023-01-06 01:39:41,617 - mmseg - INFO - Iter [19400/160000] lr: 5.273e-05, eta: 17:05:17, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2239, decode.acc_seg: 91.5349, loss: 0.2239 2023-01-06 01:40:02,493 - mmseg - INFO - Iter [19450/160000] lr: 5.271e-05, eta: 17:04:48, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1909, decode.acc_seg: 92.5707, loss: 0.1909 2023-01-06 01:40:23,617 - mmseg - INFO - Iter [19500/160000] lr: 5.269e-05, eta: 17:04:21, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1882, decode.acc_seg: 92.6821, loss: 0.1882 2023-01-06 01:40:44,860 - mmseg - INFO - Iter [19550/160000] lr: 5.267e-05, eta: 17:03:54, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1967, decode.acc_seg: 92.1591, loss: 0.1967 2023-01-06 01:41:05,762 - mmseg - INFO - Iter [19600/160000] lr: 5.265e-05, eta: 17:03:25, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1892, decode.acc_seg: 92.7348, loss: 0.1892 2023-01-06 01:41:27,314 - mmseg - INFO - Iter [19650/160000] lr: 5.263e-05, eta: 17:03:01, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2057, decode.acc_seg: 92.3579, loss: 0.2057 2023-01-06 01:41:48,376 - mmseg - INFO - Iter [19700/160000] lr: 5.261e-05, eta: 17:02:34, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1844, decode.acc_seg: 92.8706, loss: 0.1844 2023-01-06 01:42:13,182 - mmseg - INFO - Iter [19750/160000] lr: 5.259e-05, eta: 17:02:32, time: 0.496, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1831, decode.acc_seg: 92.8294, loss: 0.1831 2023-01-06 01:42:35,544 - mmseg - INFO - Iter [19800/160000] lr: 5.258e-05, eta: 17:02:14, time: 0.447, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1774, decode.acc_seg: 92.9340, loss: 0.1774 2023-01-06 01:42:57,023 - mmseg - INFO - Iter [19850/160000] lr: 5.256e-05, eta: 17:01:49, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2005, decode.acc_seg: 92.2531, loss: 0.2005 2023-01-06 01:43:18,788 - mmseg - INFO - Iter [19900/160000] lr: 5.254e-05, eta: 17:01:27, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1946, decode.acc_seg: 92.3929, loss: 0.1946 2023-01-06 01:43:40,065 - mmseg - INFO - Iter [19950/160000] lr: 5.252e-05, eta: 17:01:01, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1775, decode.acc_seg: 93.1591, loss: 0.1775 2023-01-06 01:44:01,173 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:44:01,174 - mmseg - INFO - Iter [20000/160000] lr: 5.250e-05, eta: 17:00:33, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1904, decode.acc_seg: 92.3930, loss: 0.1904 2023-01-06 01:44:22,400 - mmseg - INFO - Iter [20050/160000] lr: 5.248e-05, eta: 17:00:07, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1821, decode.acc_seg: 93.0412, loss: 0.1821 2023-01-06 01:44:46,373 - mmseg - INFO - Iter [20100/160000] lr: 5.246e-05, eta: 17:00:00, time: 0.479, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1918, decode.acc_seg: 92.6073, loss: 0.1918 2023-01-06 01:45:07,944 - mmseg - INFO - Iter [20150/160000] lr: 5.244e-05, eta: 16:59:36, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1867, decode.acc_seg: 92.6524, loss: 0.1867 2023-01-06 01:45:29,726 - mmseg - INFO - Iter [20200/160000] lr: 5.243e-05, eta: 16:59:13, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.2027, decode.acc_seg: 92.0663, loss: 0.2027 2023-01-06 01:45:52,114 - mmseg - INFO - Iter [20250/160000] lr: 5.241e-05, eta: 16:58:55, time: 0.448, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1790, decode.acc_seg: 93.0629, loss: 0.1790 2023-01-06 01:46:13,963 - mmseg - INFO - Iter [20300/160000] lr: 5.239e-05, eta: 16:58:33, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1829, decode.acc_seg: 93.0666, loss: 0.1829 2023-01-06 01:46:36,046 - mmseg - INFO - Iter [20350/160000] lr: 5.237e-05, eta: 16:58:13, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1792, decode.acc_seg: 92.8619, loss: 0.1792 2023-01-06 01:46:56,947 - mmseg - INFO - Iter [20400/160000] lr: 5.235e-05, eta: 16:57:44, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1719, decode.acc_seg: 93.1808, loss: 0.1719 2023-01-06 01:47:17,827 - mmseg - INFO - Iter [20450/160000] lr: 5.233e-05, eta: 16:57:16, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1916, decode.acc_seg: 92.4955, loss: 0.1916 2023-01-06 01:47:40,968 - mmseg - INFO - Iter [20500/160000] lr: 5.231e-05, eta: 16:57:02, time: 0.463, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1882, decode.acc_seg: 92.7745, loss: 0.1882 2023-01-06 01:48:02,282 - mmseg - INFO - Iter [20550/160000] lr: 5.229e-05, eta: 16:56:36, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1839, decode.acc_seg: 92.8853, loss: 0.1839 2023-01-06 01:48:23,371 - mmseg - INFO - Iter [20600/160000] lr: 5.228e-05, eta: 16:56:09, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1826, decode.acc_seg: 93.0936, loss: 0.1826 2023-01-06 01:48:45,906 - mmseg - INFO - Iter [20650/160000] lr: 5.226e-05, eta: 16:55:52, time: 0.451, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1912, decode.acc_seg: 92.7607, loss: 0.1912 2023-01-06 01:49:06,979 - mmseg - INFO - Iter [20700/160000] lr: 5.224e-05, eta: 16:55:25, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1825, decode.acc_seg: 92.9479, loss: 0.1825 2023-01-06 01:49:28,703 - mmseg - INFO - Iter [20750/160000] lr: 5.222e-05, eta: 16:55:02, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1765, decode.acc_seg: 92.9791, loss: 0.1765 2023-01-06 01:49:49,669 - mmseg - INFO - Iter [20800/160000] lr: 5.220e-05, eta: 16:54:34, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.2000, decode.acc_seg: 92.2671, loss: 0.2000 2023-01-06 01:50:13,076 - mmseg - INFO - Iter [20850/160000] lr: 5.218e-05, eta: 16:54:23, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1822, decode.acc_seg: 92.9093, loss: 0.1822 2023-01-06 01:50:34,522 - mmseg - INFO - Iter [20900/160000] lr: 5.216e-05, eta: 16:53:58, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1859, decode.acc_seg: 92.7841, loss: 0.1859 2023-01-06 01:50:55,593 - mmseg - INFO - Iter [20950/160000] lr: 5.214e-05, eta: 16:53:31, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1786, decode.acc_seg: 93.0616, loss: 0.1786 2023-01-06 01:51:16,441 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:51:16,441 - mmseg - INFO - Iter [21000/160000] lr: 5.213e-05, eta: 16:53:02, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1908, decode.acc_seg: 92.4819, loss: 0.1908 2023-01-06 01:51:37,909 - mmseg - INFO - Iter [21050/160000] lr: 5.211e-05, eta: 16:52:38, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1729, decode.acc_seg: 92.9447, loss: 0.1729 2023-01-06 01:51:58,932 - mmseg - INFO - Iter [21100/160000] lr: 5.209e-05, eta: 16:52:10, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1684, decode.acc_seg: 93.3171, loss: 0.1684 2023-01-06 01:52:20,623 - mmseg - INFO - Iter [21150/160000] lr: 5.207e-05, eta: 16:51:47, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1739, decode.acc_seg: 93.0676, loss: 0.1739 2023-01-06 01:52:41,554 - mmseg - INFO - Iter [21200/160000] lr: 5.205e-05, eta: 16:51:19, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1797, decode.acc_seg: 93.1980, loss: 0.1797 2023-01-06 01:53:05,259 - mmseg - INFO - Iter [21250/160000] lr: 5.203e-05, eta: 16:51:09, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1817, decode.acc_seg: 92.7780, loss: 0.1817 2023-01-06 01:53:26,869 - mmseg - INFO - Iter [21300/160000] lr: 5.201e-05, eta: 16:50:46, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1683, decode.acc_seg: 93.3804, loss: 0.1683 2023-01-06 01:53:47,711 - mmseg - INFO - Iter [21350/160000] lr: 5.199e-05, eta: 16:50:17, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1969, decode.acc_seg: 92.4133, loss: 0.1969 2023-01-06 01:54:08,641 - mmseg - INFO - Iter [21400/160000] lr: 5.198e-05, eta: 16:49:50, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1657, decode.acc_seg: 93.3919, loss: 0.1657 2023-01-06 01:54:29,789 - mmseg - INFO - Iter [21450/160000] lr: 5.196e-05, eta: 16:49:23, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1829, decode.acc_seg: 92.7280, loss: 0.1829 2023-01-06 01:54:50,906 - mmseg - INFO - Iter [21500/160000] lr: 5.194e-05, eta: 16:48:56, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1855, decode.acc_seg: 92.8334, loss: 0.1855 2023-01-06 01:55:11,726 - mmseg - INFO - Iter [21550/160000] lr: 5.192e-05, eta: 16:48:28, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1926, decode.acc_seg: 92.2341, loss: 0.1926 2023-01-06 01:55:35,032 - mmseg - INFO - Iter [21600/160000] lr: 5.190e-05, eta: 16:48:15, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1795, decode.acc_seg: 93.0715, loss: 0.1795 2023-01-06 01:55:56,146 - mmseg - INFO - Iter [21650/160000] lr: 5.188e-05, eta: 16:47:49, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1833, decode.acc_seg: 92.9227, loss: 0.1833 2023-01-06 01:56:17,387 - mmseg - INFO - Iter [21700/160000] lr: 5.186e-05, eta: 16:47:23, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1948, decode.acc_seg: 92.5373, loss: 0.1948 2023-01-06 01:56:38,228 - mmseg - INFO - Iter [21750/160000] lr: 5.184e-05, eta: 16:46:55, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1884, decode.acc_seg: 92.5302, loss: 0.1884 2023-01-06 01:56:59,061 - mmseg - INFO - Iter [21800/160000] lr: 5.183e-05, eta: 16:46:27, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1693, decode.acc_seg: 93.1262, loss: 0.1693 2023-01-06 01:57:19,936 - mmseg - INFO - Iter [21850/160000] lr: 5.181e-05, eta: 16:45:59, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1827, decode.acc_seg: 92.9090, loss: 0.1827 2023-01-06 01:57:40,860 - mmseg - INFO - Iter [21900/160000] lr: 5.179e-05, eta: 16:45:31, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1842, decode.acc_seg: 92.9273, loss: 0.1842 2023-01-06 01:58:04,105 - mmseg - INFO - Iter [21950/160000] lr: 5.177e-05, eta: 16:45:18, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1999, decode.acc_seg: 92.4434, loss: 0.1999 2023-01-06 01:58:25,262 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 01:58:25,263 - mmseg - INFO - Iter [22000/160000] lr: 5.175e-05, eta: 16:44:52, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1878, decode.acc_seg: 92.9298, loss: 0.1878 2023-01-06 01:58:46,330 - mmseg - INFO - Iter [22050/160000] lr: 5.173e-05, eta: 16:44:25, time: 0.421, data_time: 0.013, memory: 9591, decode.loss_ce: 0.1878, decode.acc_seg: 92.7923, loss: 0.1878 2023-01-06 01:59:07,163 - mmseg - INFO - Iter [22100/160000] lr: 5.171e-05, eta: 16:43:57, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1793, decode.acc_seg: 92.7089, loss: 0.1793 2023-01-06 01:59:28,545 - mmseg - INFO - Iter [22150/160000] lr: 5.169e-05, eta: 16:43:32, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1566, decode.acc_seg: 93.6663, loss: 0.1566 2023-01-06 01:59:50,598 - mmseg - INFO - Iter [22200/160000] lr: 5.168e-05, eta: 16:43:11, time: 0.441, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1674, decode.acc_seg: 93.1251, loss: 0.1674 2023-01-06 02:00:13,170 - mmseg - INFO - Iter [22250/160000] lr: 5.166e-05, eta: 16:42:54, time: 0.452, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1669, decode.acc_seg: 93.3029, loss: 0.1669 2023-01-06 02:00:34,561 - mmseg - INFO - Iter [22300/160000] lr: 5.164e-05, eta: 16:42:30, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1735, decode.acc_seg: 93.2433, loss: 0.1735 2023-01-06 02:00:57,847 - mmseg - INFO - Iter [22350/160000] lr: 5.162e-05, eta: 16:42:17, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1761, decode.acc_seg: 93.1353, loss: 0.1761 2023-01-06 02:01:19,056 - mmseg - INFO - Iter [22400/160000] lr: 5.160e-05, eta: 16:41:51, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1787, decode.acc_seg: 92.8987, loss: 0.1787 2023-01-06 02:01:40,183 - mmseg - INFO - Iter [22450/160000] lr: 5.158e-05, eta: 16:41:25, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1818, decode.acc_seg: 92.9987, loss: 0.1818 2023-01-06 02:02:02,320 - mmseg - INFO - Iter [22500/160000] lr: 5.156e-05, eta: 16:41:05, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1795, decode.acc_seg: 93.0023, loss: 0.1795 2023-01-06 02:02:23,764 - mmseg - INFO - Iter [22550/160000] lr: 5.154e-05, eta: 16:40:40, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1777, decode.acc_seg: 92.7875, loss: 0.1777 2023-01-06 02:02:44,771 - mmseg - INFO - Iter [22600/160000] lr: 5.153e-05, eta: 16:40:13, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1924, decode.acc_seg: 92.5829, loss: 0.1924 2023-01-06 02:03:06,529 - mmseg - INFO - Iter [22650/160000] lr: 5.151e-05, eta: 16:39:51, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1749, decode.acc_seg: 93.2606, loss: 0.1749 2023-01-06 02:03:29,997 - mmseg - INFO - Iter [22700/160000] lr: 5.149e-05, eta: 16:39:39, time: 0.470, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1734, decode.acc_seg: 93.0448, loss: 0.1734 2023-01-06 02:03:51,046 - mmseg - INFO - Iter [22750/160000] lr: 5.147e-05, eta: 16:39:12, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1717, decode.acc_seg: 93.3820, loss: 0.1717 2023-01-06 02:04:12,385 - mmseg - INFO - Iter [22800/160000] lr: 5.145e-05, eta: 16:38:48, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1633, decode.acc_seg: 93.3567, loss: 0.1633 2023-01-06 02:04:33,760 - mmseg - INFO - Iter [22850/160000] lr: 5.143e-05, eta: 16:38:23, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1768, decode.acc_seg: 92.8955, loss: 0.1768 2023-01-06 02:04:55,305 - mmseg - INFO - Iter [22900/160000] lr: 5.141e-05, eta: 16:37:59, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1692, decode.acc_seg: 93.0207, loss: 0.1692 2023-01-06 02:05:16,477 - mmseg - INFO - Iter [22950/160000] lr: 5.139e-05, eta: 16:37:34, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1761, decode.acc_seg: 93.1878, loss: 0.1761 2023-01-06 02:05:37,678 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 02:05:37,679 - mmseg - INFO - Iter [23000/160000] lr: 5.138e-05, eta: 16:37:08, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1682, decode.acc_seg: 93.4734, loss: 0.1682 2023-01-06 02:05:59,338 - mmseg - INFO - Iter [23050/160000] lr: 5.136e-05, eta: 16:36:45, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1710, decode.acc_seg: 93.4148, loss: 0.1710 2023-01-06 02:06:23,440 - mmseg - INFO - Iter [23100/160000] lr: 5.134e-05, eta: 16:36:37, time: 0.482, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1744, decode.acc_seg: 93.2161, loss: 0.1744 2023-01-06 02:06:44,521 - mmseg - INFO - Iter [23150/160000] lr: 5.132e-05, eta: 16:36:10, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1712, decode.acc_seg: 93.1068, loss: 0.1712 2023-01-06 02:07:06,404 - mmseg - INFO - Iter [23200/160000] lr: 5.130e-05, eta: 16:35:49, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1693, decode.acc_seg: 93.1723, loss: 0.1693 2023-01-06 02:07:27,453 - mmseg - INFO - Iter [23250/160000] lr: 5.128e-05, eta: 16:35:22, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1687, decode.acc_seg: 93.3078, loss: 0.1687 2023-01-06 02:07:48,502 - mmseg - INFO - Iter [23300/160000] lr: 5.126e-05, eta: 16:34:56, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1852, decode.acc_seg: 92.6490, loss: 0.1852 2023-01-06 02:08:09,927 - mmseg - INFO - Iter [23350/160000] lr: 5.124e-05, eta: 16:34:32, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1899, decode.acc_seg: 92.7401, loss: 0.1899 2023-01-06 02:08:31,917 - mmseg - INFO - Iter [23400/160000] lr: 5.123e-05, eta: 16:34:11, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1879, decode.acc_seg: 92.8024, loss: 0.1879 2023-01-06 02:08:55,261 - mmseg - INFO - Iter [23450/160000] lr: 5.121e-05, eta: 16:33:58, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1760, decode.acc_seg: 93.1409, loss: 0.1760 2023-01-06 02:09:16,687 - mmseg - INFO - Iter [23500/160000] lr: 5.119e-05, eta: 16:33:33, time: 0.429, data_time: 0.013, memory: 9591, decode.loss_ce: 0.1785, decode.acc_seg: 92.8862, loss: 0.1785 2023-01-06 02:09:38,813 - mmseg - INFO - Iter [23550/160000] lr: 5.117e-05, eta: 16:33:13, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1758, decode.acc_seg: 92.8341, loss: 0.1758 2023-01-06 02:10:00,402 - mmseg - INFO - Iter [23600/160000] lr: 5.115e-05, eta: 16:32:50, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1751, decode.acc_seg: 93.1084, loss: 0.1751 2023-01-06 02:10:21,437 - mmseg - INFO - Iter [23650/160000] lr: 5.113e-05, eta: 16:32:24, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1740, decode.acc_seg: 93.2753, loss: 0.1740 2023-01-06 02:10:42,778 - mmseg - INFO - Iter [23700/160000] lr: 5.111e-05, eta: 16:31:59, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1827, decode.acc_seg: 92.8619, loss: 0.1827 2023-01-06 02:11:03,785 - mmseg - INFO - Iter [23750/160000] lr: 5.109e-05, eta: 16:31:32, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1781, decode.acc_seg: 93.0230, loss: 0.1781 2023-01-06 02:11:24,755 - mmseg - INFO - Iter [23800/160000] lr: 5.108e-05, eta: 16:31:05, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1924, decode.acc_seg: 92.6125, loss: 0.1924 2023-01-06 02:11:47,954 - mmseg - INFO - Iter [23850/160000] lr: 5.106e-05, eta: 16:30:51, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1858, decode.acc_seg: 92.7621, loss: 0.1858 2023-01-06 02:12:09,873 - mmseg - INFO - Iter [23900/160000] lr: 5.104e-05, eta: 16:30:30, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1864, decode.acc_seg: 92.8997, loss: 0.1864 2023-01-06 02:12:31,086 - mmseg - INFO - Iter [23950/160000] lr: 5.102e-05, eta: 16:30:05, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1642, decode.acc_seg: 93.4750, loss: 0.1642 2023-01-06 02:12:52,707 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 02:12:52,707 - mmseg - INFO - Iter [24000/160000] lr: 5.100e-05, eta: 16:29:42, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1625, decode.acc_seg: 93.4799, loss: 0.1625 2023-01-06 02:13:13,518 - mmseg - INFO - Iter [24050/160000] lr: 5.098e-05, eta: 16:29:14, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1774, decode.acc_seg: 93.0257, loss: 0.1774 2023-01-06 02:13:35,330 - mmseg - INFO - Iter [24100/160000] lr: 5.096e-05, eta: 16:28:52, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1694, decode.acc_seg: 93.2234, loss: 0.1694 2023-01-06 02:13:57,307 - mmseg - INFO - Iter [24150/160000] lr: 5.094e-05, eta: 16:28:31, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1708, decode.acc_seg: 93.3209, loss: 0.1708 2023-01-06 02:14:21,487 - mmseg - INFO - Iter [24200/160000] lr: 5.093e-05, eta: 16:28:22, time: 0.483, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1557, decode.acc_seg: 93.7980, loss: 0.1557 2023-01-06 02:14:42,449 - mmseg - INFO - Iter [24250/160000] lr: 5.091e-05, eta: 16:27:56, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1665, decode.acc_seg: 93.3923, loss: 0.1665 2023-01-06 02:15:03,492 - mmseg - INFO - Iter [24300/160000] lr: 5.089e-05, eta: 16:27:29, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1646, decode.acc_seg: 93.3664, loss: 0.1646 2023-01-06 02:15:24,741 - mmseg - INFO - Iter [24350/160000] lr: 5.087e-05, eta: 16:27:04, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1817, decode.acc_seg: 93.0152, loss: 0.1817 2023-01-06 02:15:46,547 - mmseg - INFO - Iter [24400/160000] lr: 5.085e-05, eta: 16:26:43, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1908, decode.acc_seg: 92.8291, loss: 0.1908 2023-01-06 02:16:08,736 - mmseg - INFO - Iter [24450/160000] lr: 5.083e-05, eta: 16:26:23, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1750, decode.acc_seg: 93.2186, loss: 0.1750 2023-01-06 02:16:30,419 - mmseg - INFO - Iter [24500/160000] lr: 5.081e-05, eta: 16:26:00, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1596, decode.acc_seg: 93.7371, loss: 0.1596 2023-01-06 02:16:52,423 - mmseg - INFO - Iter [24550/160000] lr: 5.079e-05, eta: 16:25:39, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1753, decode.acc_seg: 93.1986, loss: 0.1753 2023-01-06 02:17:16,084 - mmseg - INFO - Iter [24600/160000] lr: 5.078e-05, eta: 16:25:27, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1850, decode.acc_seg: 92.7584, loss: 0.1850 2023-01-06 02:17:37,141 - mmseg - INFO - Iter [24650/160000] lr: 5.076e-05, eta: 16:25:01, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1918, decode.acc_seg: 92.7175, loss: 0.1918 2023-01-06 02:17:58,073 - mmseg - INFO - Iter [24700/160000] lr: 5.074e-05, eta: 16:24:35, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1726, decode.acc_seg: 93.1444, loss: 0.1726 2023-01-06 02:18:19,488 - mmseg - INFO - Iter [24750/160000] lr: 5.072e-05, eta: 16:24:10, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1767, decode.acc_seg: 93.0945, loss: 0.1767 2023-01-06 02:18:40,423 - mmseg - INFO - Iter [24800/160000] lr: 5.070e-05, eta: 16:23:44, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1850, decode.acc_seg: 92.9733, loss: 0.1850 2023-01-06 02:19:01,228 - mmseg - INFO - Iter [24850/160000] lr: 5.068e-05, eta: 16:23:16, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1606, decode.acc_seg: 93.6418, loss: 0.1606 2023-01-06 02:19:22,503 - mmseg - INFO - Iter [24900/160000] lr: 5.066e-05, eta: 16:22:52, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1788, decode.acc_seg: 92.9239, loss: 0.1788 2023-01-06 02:19:45,938 - mmseg - INFO - Iter [24950/160000] lr: 5.064e-05, eta: 16:22:38, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1625, decode.acc_seg: 93.5748, loss: 0.1625 2023-01-06 02:20:07,959 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 02:20:07,960 - mmseg - INFO - Iter [25000/160000] lr: 5.063e-05, eta: 16:22:18, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1829, decode.acc_seg: 92.8066, loss: 0.1829 2023-01-06 02:20:28,900 - mmseg - INFO - Iter [25050/160000] lr: 5.061e-05, eta: 16:21:51, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1715, decode.acc_seg: 93.2450, loss: 0.1715 2023-01-06 02:20:50,897 - mmseg - INFO - Iter [25100/160000] lr: 5.059e-05, eta: 16:21:30, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1661, decode.acc_seg: 93.3978, loss: 0.1661 2023-01-06 02:21:13,205 - mmseg - INFO - Iter [25150/160000] lr: 5.057e-05, eta: 16:21:11, time: 0.447, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1684, decode.acc_seg: 93.2795, loss: 0.1684 2023-01-06 02:21:34,631 - mmseg - INFO - Iter [25200/160000] lr: 5.055e-05, eta: 16:20:47, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1806, decode.acc_seg: 93.0832, loss: 0.1806 2023-01-06 02:21:55,906 - mmseg - INFO - Iter [25250/160000] lr: 5.053e-05, eta: 16:20:22, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1850, decode.acc_seg: 92.7413, loss: 0.1850 2023-01-06 02:22:19,118 - mmseg - INFO - Iter [25300/160000] lr: 5.051e-05, eta: 16:20:08, time: 0.464, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1670, decode.acc_seg: 93.3652, loss: 0.1670 2023-01-06 02:22:40,180 - mmseg - INFO - Iter [25350/160000] lr: 5.049e-05, eta: 16:19:42, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1691, decode.acc_seg: 93.3747, loss: 0.1691 2023-01-06 02:23:02,164 - mmseg - INFO - Iter [25400/160000] lr: 5.048e-05, eta: 16:19:21, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1741, decode.acc_seg: 93.1909, loss: 0.1741 2023-01-06 02:23:23,275 - mmseg - INFO - Iter [25450/160000] lr: 5.046e-05, eta: 16:18:55, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1673, decode.acc_seg: 93.4545, loss: 0.1673 2023-01-06 02:23:44,820 - mmseg - INFO - Iter [25500/160000] lr: 5.044e-05, eta: 16:18:32, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1602, decode.acc_seg: 93.5168, loss: 0.1602 2023-01-06 02:24:06,074 - mmseg - INFO - Iter [25550/160000] lr: 5.042e-05, eta: 16:18:07, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1627, decode.acc_seg: 93.6415, loss: 0.1627 2023-01-06 02:24:27,089 - mmseg - INFO - Iter [25600/160000] lr: 5.040e-05, eta: 16:17:41, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1757, decode.acc_seg: 93.0109, loss: 0.1757 2023-01-06 02:24:48,824 - mmseg - INFO - Iter [25650/160000] lr: 5.038e-05, eta: 16:17:18, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1737, decode.acc_seg: 93.1362, loss: 0.1737 2023-01-06 02:25:12,648 - mmseg - INFO - Iter [25700/160000] lr: 5.036e-05, eta: 16:17:07, time: 0.477, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1557, decode.acc_seg: 93.8054, loss: 0.1557 2023-01-06 02:25:33,547 - mmseg - INFO - Iter [25750/160000] lr: 5.034e-05, eta: 16:16:40, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1636, decode.acc_seg: 93.3881, loss: 0.1636 2023-01-06 02:25:55,236 - mmseg - INFO - Iter [25800/160000] lr: 5.033e-05, eta: 16:16:18, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1722, decode.acc_seg: 93.1536, loss: 0.1722 2023-01-06 02:26:17,377 - mmseg - INFO - Iter [25850/160000] lr: 5.031e-05, eta: 16:15:58, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1559, decode.acc_seg: 93.7946, loss: 0.1559 2023-01-06 02:26:38,060 - mmseg - INFO - Iter [25900/160000] lr: 5.029e-05, eta: 16:15:30, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1841, decode.acc_seg: 92.9920, loss: 0.1841 2023-01-06 02:26:59,479 - mmseg - INFO - Iter [25950/160000] lr: 5.027e-05, eta: 16:15:06, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1652, decode.acc_seg: 93.4083, loss: 0.1652 2023-01-06 02:27:22,108 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 02:27:22,109 - mmseg - INFO - Iter [26000/160000] lr: 5.025e-05, eta: 16:14:48, time: 0.453, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1763, decode.acc_seg: 92.9532, loss: 0.1763 2023-01-06 02:27:45,934 - mmseg - INFO - Iter [26050/160000] lr: 5.023e-05, eta: 16:14:37, time: 0.476, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1865, decode.acc_seg: 92.6833, loss: 0.1865 2023-01-06 02:28:07,550 - mmseg - INFO - Iter [26100/160000] lr: 5.021e-05, eta: 16:14:14, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1747, decode.acc_seg: 93.3467, loss: 0.1747 2023-01-06 02:28:29,733 - mmseg - INFO - Iter [26150/160000] lr: 5.019e-05, eta: 16:13:54, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1677, decode.acc_seg: 93.4303, loss: 0.1677 2023-01-06 02:28:51,514 - mmseg - INFO - Iter [26200/160000] lr: 5.018e-05, eta: 16:13:32, time: 0.436, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1673, decode.acc_seg: 93.5040, loss: 0.1673 2023-01-06 02:29:12,530 - mmseg - INFO - Iter [26250/160000] lr: 5.016e-05, eta: 16:13:06, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1720, decode.acc_seg: 93.1899, loss: 0.1720 2023-01-06 02:29:33,533 - mmseg - INFO - Iter [26300/160000] lr: 5.014e-05, eta: 16:12:40, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1800, decode.acc_seg: 93.0314, loss: 0.1800 2023-01-06 02:29:54,326 - mmseg - INFO - Iter [26350/160000] lr: 5.012e-05, eta: 16:12:13, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1700, decode.acc_seg: 93.1867, loss: 0.1700 2023-01-06 02:30:15,506 - mmseg - INFO - Iter [26400/160000] lr: 5.010e-05, eta: 16:11:48, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1634, decode.acc_seg: 93.4641, loss: 0.1634 2023-01-06 02:30:39,073 - mmseg - INFO - Iter [26450/160000] lr: 5.008e-05, eta: 16:11:35, time: 0.471, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1809, decode.acc_seg: 93.0298, loss: 0.1809 2023-01-06 02:31:00,072 - mmseg - INFO - Iter [26500/160000] lr: 5.006e-05, eta: 16:11:09, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1786, decode.acc_seg: 93.2616, loss: 0.1786 2023-01-06 02:31:21,058 - mmseg - INFO - Iter [26550/160000] lr: 5.004e-05, eta: 16:10:43, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1721, decode.acc_seg: 93.2925, loss: 0.1721 2023-01-06 02:31:42,514 - mmseg - INFO - Iter [26600/160000] lr: 5.003e-05, eta: 16:10:19, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1640, decode.acc_seg: 93.4097, loss: 0.1640 2023-01-06 02:32:04,155 - mmseg - INFO - Iter [26650/160000] lr: 5.001e-05, eta: 16:09:56, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1714, decode.acc_seg: 93.1608, loss: 0.1714 2023-01-06 02:32:25,066 - mmseg - INFO - Iter [26700/160000] lr: 4.999e-05, eta: 16:09:30, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1535, decode.acc_seg: 93.8854, loss: 0.1535 2023-01-06 02:32:45,937 - mmseg - INFO - Iter [26750/160000] lr: 4.997e-05, eta: 16:09:03, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1813, decode.acc_seg: 93.2325, loss: 0.1813 2023-01-06 02:33:09,930 - mmseg - INFO - Iter [26800/160000] lr: 4.995e-05, eta: 16:08:52, time: 0.479, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1658, decode.acc_seg: 93.4180, loss: 0.1658 2023-01-06 02:33:31,311 - mmseg - INFO - Iter [26850/160000] lr: 4.993e-05, eta: 16:08:28, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1598, decode.acc_seg: 93.3830, loss: 0.1598 2023-01-06 02:33:52,137 - mmseg - INFO - Iter [26900/160000] lr: 4.991e-05, eta: 16:08:02, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1778, decode.acc_seg: 92.7635, loss: 0.1778 2023-01-06 02:34:13,229 - mmseg - INFO - Iter [26950/160000] lr: 4.989e-05, eta: 16:07:36, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1700, decode.acc_seg: 93.2770, loss: 0.1700 2023-01-06 02:34:34,009 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 02:34:34,009 - mmseg - INFO - Iter [27000/160000] lr: 4.988e-05, eta: 16:07:09, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1662, decode.acc_seg: 93.6716, loss: 0.1662 2023-01-06 02:34:55,415 - mmseg - INFO - Iter [27050/160000] lr: 4.986e-05, eta: 16:06:46, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1708, decode.acc_seg: 93.1265, loss: 0.1708 2023-01-06 02:35:17,897 - mmseg - INFO - Iter [27100/160000] lr: 4.984e-05, eta: 16:06:27, time: 0.450, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1536, decode.acc_seg: 93.9749, loss: 0.1536 2023-01-06 02:35:39,370 - mmseg - INFO - Iter [27150/160000] lr: 4.982e-05, eta: 16:06:03, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1687, decode.acc_seg: 93.5236, loss: 0.1687 2023-01-06 02:36:02,704 - mmseg - INFO - Iter [27200/160000] lr: 4.980e-05, eta: 16:05:49, time: 0.467, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1637, decode.acc_seg: 93.4346, loss: 0.1637 2023-01-06 02:36:23,475 - mmseg - INFO - Iter [27250/160000] lr: 4.978e-05, eta: 16:05:22, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1494, decode.acc_seg: 94.0656, loss: 0.1494 2023-01-06 02:36:44,822 - mmseg - INFO - Iter [27300/160000] lr: 4.976e-05, eta: 16:04:58, time: 0.427, data_time: 0.010, memory: 9591, decode.loss_ce: 0.1671, decode.acc_seg: 93.2992, loss: 0.1671 2023-01-06 02:37:05,855 - mmseg - INFO - Iter [27350/160000] lr: 4.974e-05, eta: 16:04:32, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1741, decode.acc_seg: 93.2262, loss: 0.1741 2023-01-06 02:37:27,553 - mmseg - INFO - Iter [27400/160000] lr: 4.973e-05, eta: 16:04:10, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1642, decode.acc_seg: 93.6244, loss: 0.1642 2023-01-06 02:37:48,579 - mmseg - INFO - Iter [27450/160000] lr: 4.971e-05, eta: 16:03:44, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1905, decode.acc_seg: 92.7039, loss: 0.1905 2023-01-06 02:38:10,265 - mmseg - INFO - Iter [27500/160000] lr: 4.969e-05, eta: 16:03:22, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1703, decode.acc_seg: 93.2601, loss: 0.1703 2023-01-06 02:38:34,337 - mmseg - INFO - Iter [27550/160000] lr: 4.967e-05, eta: 16:03:11, time: 0.481, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1635, decode.acc_seg: 93.7597, loss: 0.1635 2023-01-06 02:38:56,022 - mmseg - INFO - Iter [27600/160000] lr: 4.965e-05, eta: 16:02:48, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1594, decode.acc_seg: 93.7570, loss: 0.1594 2023-01-06 02:39:17,979 - mmseg - INFO - Iter [27650/160000] lr: 4.963e-05, eta: 16:02:27, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1663, decode.acc_seg: 93.7313, loss: 0.1663 2023-01-06 02:39:39,332 - mmseg - INFO - Iter [27700/160000] lr: 4.961e-05, eta: 16:02:03, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1692, decode.acc_seg: 93.3760, loss: 0.1692 2023-01-06 02:40:00,606 - mmseg - INFO - Iter [27750/160000] lr: 4.959e-05, eta: 16:01:39, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1837, decode.acc_seg: 93.0473, loss: 0.1837 2023-01-06 02:40:21,435 - mmseg - INFO - Iter [27800/160000] lr: 4.958e-05, eta: 16:01:13, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1644, decode.acc_seg: 93.2336, loss: 0.1644 2023-01-06 02:40:42,188 - mmseg - INFO - Iter [27850/160000] lr: 4.956e-05, eta: 16:00:46, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1496, decode.acc_seg: 94.1070, loss: 0.1496 2023-01-06 02:41:03,167 - mmseg - INFO - Iter [27900/160000] lr: 4.954e-05, eta: 16:00:20, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1628, decode.acc_seg: 93.5672, loss: 0.1628 2023-01-06 02:41:27,161 - mmseg - INFO - Iter [27950/160000] lr: 4.952e-05, eta: 16:00:08, time: 0.479, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1636, decode.acc_seg: 93.5014, loss: 0.1636 2023-01-06 02:41:48,290 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 02:41:48,290 - mmseg - INFO - Iter [28000/160000] lr: 4.950e-05, eta: 15:59:43, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1658, decode.acc_seg: 93.4932, loss: 0.1658 2023-01-06 02:42:09,418 - mmseg - INFO - Iter [28050/160000] lr: 4.948e-05, eta: 15:59:18, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1533, decode.acc_seg: 93.9482, loss: 0.1533 2023-01-06 02:42:30,479 - mmseg - INFO - Iter [28100/160000] lr: 4.946e-05, eta: 15:58:53, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1532, decode.acc_seg: 93.8203, loss: 0.1532 2023-01-06 02:42:51,779 - mmseg - INFO - Iter [28150/160000] lr: 4.944e-05, eta: 15:58:29, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1561, decode.acc_seg: 93.7413, loss: 0.1561 2023-01-06 02:43:13,218 - mmseg - INFO - Iter [28200/160000] lr: 4.943e-05, eta: 15:58:05, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1473, decode.acc_seg: 94.1505, loss: 0.1473 2023-01-06 02:43:36,107 - mmseg - INFO - Iter [28250/160000] lr: 4.941e-05, eta: 15:57:48, time: 0.458, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1559, decode.acc_seg: 93.8105, loss: 0.1559 2023-01-06 02:43:59,781 - mmseg - INFO - Iter [28300/160000] lr: 4.939e-05, eta: 15:57:35, time: 0.473, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1683, decode.acc_seg: 93.5505, loss: 0.1683 2023-01-06 02:44:20,984 - mmseg - INFO - Iter [28350/160000] lr: 4.937e-05, eta: 15:57:11, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1663, decode.acc_seg: 93.4006, loss: 0.1663 2023-01-06 02:44:42,378 - mmseg - INFO - Iter [28400/160000] lr: 4.935e-05, eta: 15:56:47, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1599, decode.acc_seg: 93.5797, loss: 0.1599 2023-01-06 02:45:04,254 - mmseg - INFO - Iter [28450/160000] lr: 4.933e-05, eta: 15:56:25, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1799, decode.acc_seg: 92.9754, loss: 0.1799 2023-01-06 02:45:25,202 - mmseg - INFO - Iter [28500/160000] lr: 4.931e-05, eta: 15:56:00, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1659, decode.acc_seg: 93.4401, loss: 0.1659 2023-01-06 02:45:46,327 - mmseg - INFO - Iter [28550/160000] lr: 4.929e-05, eta: 15:55:35, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1667, decode.acc_seg: 93.2767, loss: 0.1667 2023-01-06 02:46:07,400 - mmseg - INFO - Iter [28600/160000] lr: 4.928e-05, eta: 15:55:10, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1663, decode.acc_seg: 93.4612, loss: 0.1663 2023-01-06 02:46:30,578 - mmseg - INFO - Iter [28650/160000] lr: 4.926e-05, eta: 15:54:54, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1856, decode.acc_seg: 92.9144, loss: 0.1856 2023-01-06 02:46:51,798 - mmseg - INFO - Iter [28700/160000] lr: 4.924e-05, eta: 15:54:29, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1586, decode.acc_seg: 93.5625, loss: 0.1586 2023-01-06 02:47:13,251 - mmseg - INFO - Iter [28750/160000] lr: 4.922e-05, eta: 15:54:06, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1661, decode.acc_seg: 93.4372, loss: 0.1661 2023-01-06 02:47:35,553 - mmseg - INFO - Iter [28800/160000] lr: 4.920e-05, eta: 15:53:46, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1663, decode.acc_seg: 93.4609, loss: 0.1663 2023-01-06 02:47:56,528 - mmseg - INFO - Iter [28850/160000] lr: 4.918e-05, eta: 15:53:21, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1545, decode.acc_seg: 93.8310, loss: 0.1545 2023-01-06 02:48:18,148 - mmseg - INFO - Iter [28900/160000] lr: 4.916e-05, eta: 15:52:58, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1599, decode.acc_seg: 93.6042, loss: 0.1599 2023-01-06 02:48:39,047 - mmseg - INFO - Iter [28950/160000] lr: 4.914e-05, eta: 15:52:32, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1525, decode.acc_seg: 93.8434, loss: 0.1525 2023-01-06 02:49:00,313 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 02:49:00,313 - mmseg - INFO - Iter [29000/160000] lr: 4.913e-05, eta: 15:52:08, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1545, decode.acc_seg: 93.9627, loss: 0.1545 2023-01-06 02:49:24,401 - mmseg - INFO - Iter [29050/160000] lr: 4.911e-05, eta: 15:51:56, time: 0.481, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1419, decode.acc_seg: 94.3174, loss: 0.1419 2023-01-06 02:49:46,314 - mmseg - INFO - Iter [29100/160000] lr: 4.909e-05, eta: 15:51:35, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1601, decode.acc_seg: 93.6071, loss: 0.1601 2023-01-06 02:50:08,690 - mmseg - INFO - Iter [29150/160000] lr: 4.907e-05, eta: 15:51:16, time: 0.448, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1673, decode.acc_seg: 93.3045, loss: 0.1673 2023-01-06 02:50:29,661 - mmseg - INFO - Iter [29200/160000] lr: 4.905e-05, eta: 15:50:50, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1536, decode.acc_seg: 93.7537, loss: 0.1536 2023-01-06 02:50:50,506 - mmseg - INFO - Iter [29250/160000] lr: 4.903e-05, eta: 15:50:24, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1495, decode.acc_seg: 93.9147, loss: 0.1495 2023-01-06 02:51:12,334 - mmseg - INFO - Iter [29300/160000] lr: 4.901e-05, eta: 15:50:03, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1762, decode.acc_seg: 93.2741, loss: 0.1762 2023-01-06 02:51:33,691 - mmseg - INFO - Iter [29350/160000] lr: 4.899e-05, eta: 15:49:39, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1651, decode.acc_seg: 93.5848, loss: 0.1651 2023-01-06 02:51:58,657 - mmseg - INFO - Iter [29400/160000] lr: 4.898e-05, eta: 15:49:31, time: 0.500, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1677, decode.acc_seg: 93.2805, loss: 0.1677 2023-01-06 02:52:19,596 - mmseg - INFO - Iter [29450/160000] lr: 4.896e-05, eta: 15:49:05, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1691, decode.acc_seg: 93.6220, loss: 0.1691 2023-01-06 02:52:41,572 - mmseg - INFO - Iter [29500/160000] lr: 4.894e-05, eta: 15:48:44, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1563, decode.acc_seg: 93.7397, loss: 0.1563 2023-01-06 02:53:03,582 - mmseg - INFO - Iter [29550/160000] lr: 4.892e-05, eta: 15:48:23, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1654, decode.acc_seg: 93.7325, loss: 0.1654 2023-01-06 02:53:24,614 - mmseg - INFO - Iter [29600/160000] lr: 4.890e-05, eta: 15:47:58, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1712, decode.acc_seg: 93.4880, loss: 0.1712 2023-01-06 02:53:45,886 - mmseg - INFO - Iter [29650/160000] lr: 4.888e-05, eta: 15:47:34, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1528, decode.acc_seg: 93.9923, loss: 0.1528 2023-01-06 02:54:07,810 - mmseg - INFO - Iter [29700/160000] lr: 4.886e-05, eta: 15:47:13, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1758, decode.acc_seg: 92.9778, loss: 0.1758 2023-01-06 02:54:29,720 - mmseg - INFO - Iter [29750/160000] lr: 4.884e-05, eta: 15:46:51, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1613, decode.acc_seg: 93.5644, loss: 0.1613 2023-01-06 02:54:54,051 - mmseg - INFO - Iter [29800/160000] lr: 4.883e-05, eta: 15:46:40, time: 0.487, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1386, decode.acc_seg: 94.2788, loss: 0.1386 2023-01-06 02:55:15,874 - mmseg - INFO - Iter [29850/160000] lr: 4.881e-05, eta: 15:46:19, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1630, decode.acc_seg: 93.7930, loss: 0.1630 2023-01-06 02:55:36,726 - mmseg - INFO - Iter [29900/160000] lr: 4.879e-05, eta: 15:45:53, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1560, decode.acc_seg: 93.7175, loss: 0.1560 2023-01-06 02:55:57,968 - mmseg - INFO - Iter [29950/160000] lr: 4.877e-05, eta: 15:45:28, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1685, decode.acc_seg: 93.5015, loss: 0.1685 2023-01-06 02:56:19,121 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 02:56:19,121 - mmseg - INFO - Iter [30000/160000] lr: 4.875e-05, eta: 15:45:04, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1541, decode.acc_seg: 93.8857, loss: 0.1541 2023-01-06 02:56:40,740 - mmseg - INFO - Iter [30050/160000] lr: 4.873e-05, eta: 15:44:41, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1564, decode.acc_seg: 93.7798, loss: 0.1564 2023-01-06 02:57:01,842 - mmseg - INFO - Iter [30100/160000] lr: 4.871e-05, eta: 15:44:16, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1605, decode.acc_seg: 93.4722, loss: 0.1605 2023-01-06 02:57:25,254 - mmseg - INFO - Iter [30150/160000] lr: 4.869e-05, eta: 15:44:01, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1442, decode.acc_seg: 94.2620, loss: 0.1442 2023-01-06 02:57:46,101 - mmseg - INFO - Iter [30200/160000] lr: 4.868e-05, eta: 15:43:35, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1460, decode.acc_seg: 93.9777, loss: 0.1460 2023-01-06 02:58:07,032 - mmseg - INFO - Iter [30250/160000] lr: 4.866e-05, eta: 15:43:10, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1535, decode.acc_seg: 93.8901, loss: 0.1535 2023-01-06 02:58:28,022 - mmseg - INFO - Iter [30300/160000] lr: 4.864e-05, eta: 15:42:44, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1668, decode.acc_seg: 93.3560, loss: 0.1668 2023-01-06 02:58:49,609 - mmseg - INFO - Iter [30350/160000] lr: 4.862e-05, eta: 15:42:22, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1549, decode.acc_seg: 93.9013, loss: 0.1549 2023-01-06 02:59:11,069 - mmseg - INFO - Iter [30400/160000] lr: 4.860e-05, eta: 15:41:58, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1571, decode.acc_seg: 93.7658, loss: 0.1571 2023-01-06 02:59:32,755 - mmseg - INFO - Iter [30450/160000] lr: 4.858e-05, eta: 15:41:36, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1553, decode.acc_seg: 93.7417, loss: 0.1553 2023-01-06 02:59:54,148 - mmseg - INFO - Iter [30500/160000] lr: 4.856e-05, eta: 15:41:13, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1573, decode.acc_seg: 93.7849, loss: 0.1573 2023-01-06 03:00:17,660 - mmseg - INFO - Iter [30550/160000] lr: 4.854e-05, eta: 15:40:58, time: 0.470, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1646, decode.acc_seg: 93.3486, loss: 0.1646 2023-01-06 03:00:39,470 - mmseg - INFO - Iter [30600/160000] lr: 4.853e-05, eta: 15:40:36, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1553, decode.acc_seg: 93.9332, loss: 0.1553 2023-01-06 03:01:01,371 - mmseg - INFO - Iter [30650/160000] lr: 4.851e-05, eta: 15:40:15, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1718, decode.acc_seg: 93.5803, loss: 0.1718 2023-01-06 03:01:22,954 - mmseg - INFO - Iter [30700/160000] lr: 4.849e-05, eta: 15:39:52, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1725, decode.acc_seg: 93.1966, loss: 0.1725 2023-01-06 03:01:43,835 - mmseg - INFO - Iter [30750/160000] lr: 4.847e-05, eta: 15:39:26, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1619, decode.acc_seg: 93.3953, loss: 0.1619 2023-01-06 03:02:05,157 - mmseg - INFO - Iter [30800/160000] lr: 4.845e-05, eta: 15:39:02, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1627, decode.acc_seg: 93.5378, loss: 0.1627 2023-01-06 03:02:26,882 - mmseg - INFO - Iter [30850/160000] lr: 4.843e-05, eta: 15:38:40, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1693, decode.acc_seg: 93.2629, loss: 0.1693 2023-01-06 03:02:50,205 - mmseg - INFO - Iter [30900/160000] lr: 4.841e-05, eta: 15:38:25, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1618, decode.acc_seg: 93.5659, loss: 0.1618 2023-01-06 03:03:11,105 - mmseg - INFO - Iter [30950/160000] lr: 4.839e-05, eta: 15:37:59, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1607, decode.acc_seg: 93.5873, loss: 0.1607 2023-01-06 03:03:32,090 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:03:32,090 - mmseg - INFO - Iter [31000/160000] lr: 4.838e-05, eta: 15:37:34, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1726, decode.acc_seg: 93.3804, loss: 0.1726 2023-01-06 03:03:52,882 - mmseg - INFO - Iter [31050/160000] lr: 4.836e-05, eta: 15:37:08, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1597, decode.acc_seg: 93.7227, loss: 0.1597 2023-01-06 03:04:14,136 - mmseg - INFO - Iter [31100/160000] lr: 4.834e-05, eta: 15:36:44, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1540, decode.acc_seg: 93.8849, loss: 0.1540 2023-01-06 03:04:36,099 - mmseg - INFO - Iter [31150/160000] lr: 4.832e-05, eta: 15:36:23, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1613, decode.acc_seg: 93.3316, loss: 0.1613 2023-01-06 03:04:57,937 - mmseg - INFO - Iter [31200/160000] lr: 4.830e-05, eta: 15:36:01, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1752, decode.acc_seg: 93.2364, loss: 0.1752 2023-01-06 03:05:21,908 - mmseg - INFO - Iter [31250/160000] lr: 4.828e-05, eta: 15:35:48, time: 0.479, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1591, decode.acc_seg: 93.7062, loss: 0.1591 2023-01-06 03:05:43,563 - mmseg - INFO - Iter [31300/160000] lr: 4.826e-05, eta: 15:35:26, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1608, decode.acc_seg: 93.6068, loss: 0.1608 2023-01-06 03:06:06,283 - mmseg - INFO - Iter [31350/160000] lr: 4.824e-05, eta: 15:35:08, time: 0.455, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1513, decode.acc_seg: 93.9854, loss: 0.1513 2023-01-06 03:06:28,828 - mmseg - INFO - Iter [31400/160000] lr: 4.823e-05, eta: 15:34:49, time: 0.450, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1751, decode.acc_seg: 93.3870, loss: 0.1751 2023-01-06 03:06:49,904 - mmseg - INFO - Iter [31450/160000] lr: 4.821e-05, eta: 15:34:24, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1736, decode.acc_seg: 93.3568, loss: 0.1736 2023-01-06 03:07:10,889 - mmseg - INFO - Iter [31500/160000] lr: 4.819e-05, eta: 15:33:59, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1566, decode.acc_seg: 93.7457, loss: 0.1566 2023-01-06 03:07:32,256 - mmseg - INFO - Iter [31550/160000] lr: 4.817e-05, eta: 15:33:36, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1453, decode.acc_seg: 94.0824, loss: 0.1453 2023-01-06 03:07:53,698 - mmseg - INFO - Iter [31600/160000] lr: 4.815e-05, eta: 15:33:12, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1525, decode.acc_seg: 93.9611, loss: 0.1525 2023-01-06 03:08:16,802 - mmseg - INFO - Iter [31650/160000] lr: 4.813e-05, eta: 15:32:56, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1697, decode.acc_seg: 93.3518, loss: 0.1697 2023-01-06 03:08:37,684 - mmseg - INFO - Iter [31700/160000] lr: 4.811e-05, eta: 15:32:30, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1556, decode.acc_seg: 93.7718, loss: 0.1556 2023-01-06 03:08:59,451 - mmseg - INFO - Iter [31750/160000] lr: 4.809e-05, eta: 15:32:08, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1653, decode.acc_seg: 93.3082, loss: 0.1653 2023-01-06 03:09:21,561 - mmseg - INFO - Iter [31800/160000] lr: 4.808e-05, eta: 15:31:48, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1550, decode.acc_seg: 93.7927, loss: 0.1550 2023-01-06 03:09:43,108 - mmseg - INFO - Iter [31850/160000] lr: 4.806e-05, eta: 15:31:25, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1553, decode.acc_seg: 93.8712, loss: 0.1553 2023-01-06 03:10:04,753 - mmseg - INFO - Iter [31900/160000] lr: 4.804e-05, eta: 15:31:02, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1535, decode.acc_seg: 93.6649, loss: 0.1535 2023-01-06 03:10:25,587 - mmseg - INFO - Iter [31950/160000] lr: 4.802e-05, eta: 15:30:37, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1555, decode.acc_seg: 93.8994, loss: 0.1555 2023-01-06 03:10:50,114 - mmseg - INFO - Saving checkpoint at 32000 iterations 2023-01-06 03:10:54,105 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:10:54,105 - mmseg - INFO - Iter [32000/160000] lr: 4.800e-05, eta: 15:30:42, time: 0.570, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1524, decode.acc_seg: 94.0232, loss: 0.1524 2023-01-06 03:11:22,293 - mmseg - INFO - per class results: 2023-01-06 03:11:22,295 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 96.98 | 98.67 | | sidewalk | 77.44 | 85.07 | | building | 89.22 | 94.29 | | wall | 40.9 | 47.13 | | fence | 42.43 | 60.39 | | pole | 54.08 | 69.36 | | traffic light | 53.95 | 68.36 | | traffic sign | 66.38 | 75.59 | | vegetation | 90.44 | 96.03 | | terrain | 58.27 | 69.38 | | sky | 92.43 | 97.99 | | person | 69.85 | 79.16 | | rider | 41.49 | 53.93 | | car | 90.01 | 96.59 | | truck | 44.87 | 60.27 | | bus | 37.93 | 40.08 | | train | 36.77 | 67.14 | | motorcycle | 33.49 | 43.72 | | bicycle | 64.55 | 86.21 | +---------------+-------+-------+ 2023-01-06 03:11:22,295 - mmseg - INFO - Summary: 2023-01-06 03:11:22,296 - mmseg - INFO - +-------+-------+-------+ | aAcc | mIoU | mAcc | +-------+-------+-------+ | 93.92 | 62.18 | 73.13 | +-------+-------+-------+ 2023-01-06 03:11:22,297 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:11:22,297 - mmseg - INFO - Iter(val) [63] aAcc: 0.9392, mIoU: 0.6218, mAcc: 0.7313, IoU.road: 0.9698, IoU.sidewalk: 0.7744, IoU.building: 0.8922, IoU.wall: 0.4090, IoU.fence: 0.4243, IoU.pole: 0.5408, IoU.traffic light: 0.5395, IoU.traffic sign: 0.6638, IoU.vegetation: 0.9044, IoU.terrain: 0.5827, IoU.sky: 0.9243, IoU.person: 0.6985, IoU.rider: 0.4149, IoU.car: 0.9001, IoU.truck: 0.4487, IoU.bus: 0.3793, IoU.train: 0.3677, IoU.motorcycle: 0.3349, IoU.bicycle: 0.6455, Acc.road: 0.9867, Acc.sidewalk: 0.8507, Acc.building: 0.9429, Acc.wall: 0.4713, Acc.fence: 0.6039, Acc.pole: 0.6936, Acc.traffic light: 0.6836, Acc.traffic sign: 0.7559, Acc.vegetation: 0.9603, Acc.terrain: 0.6938, Acc.sky: 0.9799, Acc.person: 0.7916, Acc.rider: 0.5393, Acc.car: 0.9659, Acc.truck: 0.6027, Acc.bus: 0.4008, Acc.train: 0.6714, Acc.motorcycle: 0.4372, Acc.bicycle: 0.8621 2023-01-06 03:11:43,935 - mmseg - INFO - Iter [32050/160000] lr: 4.798e-05, eta: 15:32:12, time: 0.996, data_time: 0.575, memory: 9591, decode.loss_ce: 0.1508, decode.acc_seg: 94.1231, loss: 0.1508 2023-01-06 03:12:05,132 - mmseg - INFO - Iter [32100/160000] lr: 4.796e-05, eta: 15:31:47, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1444, decode.acc_seg: 94.1467, loss: 0.1444 2023-01-06 03:12:26,057 - mmseg - INFO - Iter [32150/160000] lr: 4.794e-05, eta: 15:31:22, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1664, decode.acc_seg: 93.5569, loss: 0.1664 2023-01-06 03:12:47,266 - mmseg - INFO - Iter [32200/160000] lr: 4.793e-05, eta: 15:30:57, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1537, decode.acc_seg: 93.8852, loss: 0.1537 2023-01-06 03:13:08,015 - mmseg - INFO - Iter [32250/160000] lr: 4.791e-05, eta: 15:30:31, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1554, decode.acc_seg: 93.8425, loss: 0.1554 2023-01-06 03:13:28,813 - mmseg - INFO - Iter [32300/160000] lr: 4.789e-05, eta: 15:30:05, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1535, decode.acc_seg: 93.8341, loss: 0.1535 2023-01-06 03:13:49,935 - mmseg - INFO - Iter [32350/160000] lr: 4.787e-05, eta: 15:29:40, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1696, decode.acc_seg: 93.3567, loss: 0.1696 2023-01-06 03:14:13,513 - mmseg - INFO - Iter [32400/160000] lr: 4.785e-05, eta: 15:29:25, time: 0.471, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1536, decode.acc_seg: 93.8991, loss: 0.1536 2023-01-06 03:14:34,411 - mmseg - INFO - Iter [32450/160000] lr: 4.783e-05, eta: 15:29:00, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1435, decode.acc_seg: 94.2326, loss: 0.1435 2023-01-06 03:14:55,748 - mmseg - INFO - Iter [32500/160000] lr: 4.781e-05, eta: 15:28:36, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1567, decode.acc_seg: 93.9236, loss: 0.1567 2023-01-06 03:15:16,849 - mmseg - INFO - Iter [32550/160000] lr: 4.779e-05, eta: 15:28:11, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1584, decode.acc_seg: 93.7476, loss: 0.1584 2023-01-06 03:15:37,763 - mmseg - INFO - Iter [32600/160000] lr: 4.778e-05, eta: 15:27:45, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1584, decode.acc_seg: 93.6976, loss: 0.1584 2023-01-06 03:15:58,871 - mmseg - INFO - Iter [32650/160000] lr: 4.776e-05, eta: 15:27:21, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1561, decode.acc_seg: 93.8691, loss: 0.1561 2023-01-06 03:16:20,185 - mmseg - INFO - Iter [32700/160000] lr: 4.774e-05, eta: 15:26:57, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1607, decode.acc_seg: 93.6909, loss: 0.1607 2023-01-06 03:16:44,211 - mmseg - INFO - Iter [32750/160000] lr: 4.772e-05, eta: 15:26:43, time: 0.481, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1552, decode.acc_seg: 93.7427, loss: 0.1552 2023-01-06 03:17:05,311 - mmseg - INFO - Iter [32800/160000] lr: 4.770e-05, eta: 15:26:19, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1546, decode.acc_seg: 93.8840, loss: 0.1546 2023-01-06 03:17:27,469 - mmseg - INFO - Iter [32850/160000] lr: 4.768e-05, eta: 15:25:58, time: 0.443, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1571, decode.acc_seg: 93.7024, loss: 0.1571 2023-01-06 03:17:49,456 - mmseg - INFO - Iter [32900/160000] lr: 4.766e-05, eta: 15:25:37, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1583, decode.acc_seg: 93.8737, loss: 0.1583 2023-01-06 03:18:10,651 - mmseg - INFO - Iter [32950/160000] lr: 4.764e-05, eta: 15:25:12, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1480, decode.acc_seg: 94.2228, loss: 0.1480 2023-01-06 03:18:32,031 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:18:32,032 - mmseg - INFO - Iter [33000/160000] lr: 4.763e-05, eta: 15:24:49, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1545, decode.acc_seg: 93.6937, loss: 0.1545 2023-01-06 03:18:52,898 - mmseg - INFO - Iter [33050/160000] lr: 4.761e-05, eta: 15:24:23, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1561, decode.acc_seg: 93.8837, loss: 0.1561 2023-01-06 03:19:13,808 - mmseg - INFO - Iter [33100/160000] lr: 4.759e-05, eta: 15:23:58, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1589, decode.acc_seg: 93.6197, loss: 0.1589 2023-01-06 03:19:36,914 - mmseg - INFO - Iter [33150/160000] lr: 4.757e-05, eta: 15:23:41, time: 0.462, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1389, decode.acc_seg: 94.3019, loss: 0.1389 2023-01-06 03:19:59,193 - mmseg - INFO - Iter [33200/160000] lr: 4.755e-05, eta: 15:23:20, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1603, decode.acc_seg: 93.7876, loss: 0.1603 2023-01-06 03:20:20,448 - mmseg - INFO - Iter [33250/160000] lr: 4.753e-05, eta: 15:22:56, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1545, decode.acc_seg: 93.9067, loss: 0.1545 2023-01-06 03:20:42,798 - mmseg - INFO - Iter [33300/160000] lr: 4.751e-05, eta: 15:22:36, time: 0.447, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1574, decode.acc_seg: 93.8194, loss: 0.1574 2023-01-06 03:21:04,512 - mmseg - INFO - Iter [33350/160000] lr: 4.749e-05, eta: 15:22:14, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1626, decode.acc_seg: 93.8363, loss: 0.1626 2023-01-06 03:21:26,054 - mmseg - INFO - Iter [33400/160000] lr: 4.748e-05, eta: 15:21:51, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1518, decode.acc_seg: 94.1891, loss: 0.1518 2023-01-06 03:21:47,792 - mmseg - INFO - Iter [33450/160000] lr: 4.746e-05, eta: 15:21:29, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1647, decode.acc_seg: 93.2636, loss: 0.1647 2023-01-06 03:22:11,853 - mmseg - INFO - Iter [33500/160000] lr: 4.744e-05, eta: 15:21:15, time: 0.481, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1521, decode.acc_seg: 94.0208, loss: 0.1521 2023-01-06 03:22:32,781 - mmseg - INFO - Iter [33550/160000] lr: 4.742e-05, eta: 15:20:50, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1561, decode.acc_seg: 93.6799, loss: 0.1561 2023-01-06 03:22:53,651 - mmseg - INFO - Iter [33600/160000] lr: 4.740e-05, eta: 15:20:25, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1578, decode.acc_seg: 93.7113, loss: 0.1578 2023-01-06 03:23:15,628 - mmseg - INFO - Iter [33650/160000] lr: 4.738e-05, eta: 15:20:03, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1529, decode.acc_seg: 93.8737, loss: 0.1529 2023-01-06 03:23:36,421 - mmseg - INFO - Iter [33700/160000] lr: 4.736e-05, eta: 15:19:37, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1526, decode.acc_seg: 93.9598, loss: 0.1526 2023-01-06 03:23:57,454 - mmseg - INFO - Iter [33750/160000] lr: 4.734e-05, eta: 15:19:12, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1641, decode.acc_seg: 93.6218, loss: 0.1641 2023-01-06 03:24:18,283 - mmseg - INFO - Iter [33800/160000] lr: 4.733e-05, eta: 15:18:47, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1433, decode.acc_seg: 94.2260, loss: 0.1433 2023-01-06 03:24:39,470 - mmseg - INFO - Iter [33850/160000] lr: 4.731e-05, eta: 15:18:22, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1513, decode.acc_seg: 93.9649, loss: 0.1513 2023-01-06 03:25:02,615 - mmseg - INFO - Iter [33900/160000] lr: 4.729e-05, eta: 15:18:06, time: 0.464, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1586, decode.acc_seg: 93.7998, loss: 0.1586 2023-01-06 03:25:24,038 - mmseg - INFO - Iter [33950/160000] lr: 4.727e-05, eta: 15:17:42, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1484, decode.acc_seg: 94.0402, loss: 0.1484 2023-01-06 03:25:44,848 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:25:44,848 - mmseg - INFO - Iter [34000/160000] lr: 4.725e-05, eta: 15:17:17, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1511, decode.acc_seg: 94.0898, loss: 0.1511 2023-01-06 03:26:06,441 - mmseg - INFO - Iter [34050/160000] lr: 4.723e-05, eta: 15:16:54, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1502, decode.acc_seg: 93.9310, loss: 0.1502 2023-01-06 03:26:27,890 - mmseg - INFO - Iter [34100/160000] lr: 4.721e-05, eta: 15:16:30, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1496, decode.acc_seg: 93.9292, loss: 0.1496 2023-01-06 03:26:49,232 - mmseg - INFO - Iter [34150/160000] lr: 4.719e-05, eta: 15:16:07, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1554, decode.acc_seg: 93.8180, loss: 0.1554 2023-01-06 03:27:10,371 - mmseg - INFO - Iter [34200/160000] lr: 4.718e-05, eta: 15:15:42, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1441, decode.acc_seg: 94.2527, loss: 0.1441 2023-01-06 03:27:33,812 - mmseg - INFO - Iter [34250/160000] lr: 4.716e-05, eta: 15:15:26, time: 0.469, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1510, decode.acc_seg: 93.9480, loss: 0.1510 2023-01-06 03:27:54,715 - mmseg - INFO - Iter [34300/160000] lr: 4.714e-05, eta: 15:15:01, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1445, decode.acc_seg: 94.2475, loss: 0.1445 2023-01-06 03:28:15,798 - mmseg - INFO - Iter [34350/160000] lr: 4.712e-05, eta: 15:14:37, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1352, decode.acc_seg: 94.4584, loss: 0.1352 2023-01-06 03:28:36,772 - mmseg - INFO - Iter [34400/160000] lr: 4.710e-05, eta: 15:14:11, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1427, decode.acc_seg: 94.1849, loss: 0.1427 2023-01-06 03:28:58,030 - mmseg - INFO - Iter [34450/160000] lr: 4.708e-05, eta: 15:13:48, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1516, decode.acc_seg: 94.0366, loss: 0.1516 2023-01-06 03:29:19,495 - mmseg - INFO - Iter [34500/160000] lr: 4.706e-05, eta: 15:13:24, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1564, decode.acc_seg: 93.8869, loss: 0.1564 2023-01-06 03:29:41,520 - mmseg - INFO - Iter [34550/160000] lr: 4.704e-05, eta: 15:13:03, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1611, decode.acc_seg: 93.6720, loss: 0.1611 2023-01-06 03:30:05,324 - mmseg - INFO - Iter [34600/160000] lr: 4.703e-05, eta: 15:12:49, time: 0.477, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1555, decode.acc_seg: 93.7737, loss: 0.1555 2023-01-06 03:30:26,478 - mmseg - INFO - Iter [34650/160000] lr: 4.701e-05, eta: 15:12:24, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1607, decode.acc_seg: 93.8020, loss: 0.1607 2023-01-06 03:30:47,224 - mmseg - INFO - Iter [34700/160000] lr: 4.699e-05, eta: 15:11:59, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1628, decode.acc_seg: 93.6882, loss: 0.1628 2023-01-06 03:31:08,516 - mmseg - INFO - Iter [34750/160000] lr: 4.697e-05, eta: 15:11:35, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1459, decode.acc_seg: 94.2438, loss: 0.1459 2023-01-06 03:31:30,094 - mmseg - INFO - Iter [34800/160000] lr: 4.695e-05, eta: 15:11:12, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1498, decode.acc_seg: 93.8401, loss: 0.1498 2023-01-06 03:31:51,286 - mmseg - INFO - Iter [34850/160000] lr: 4.693e-05, eta: 15:10:48, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1443, decode.acc_seg: 94.1642, loss: 0.1443 2023-01-06 03:32:12,312 - mmseg - INFO - Iter [34900/160000] lr: 4.691e-05, eta: 15:10:23, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1498, decode.acc_seg: 94.0215, loss: 0.1498 2023-01-06 03:32:33,064 - mmseg - INFO - Iter [34950/160000] lr: 4.689e-05, eta: 15:09:57, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1538, decode.acc_seg: 93.6758, loss: 0.1538 2023-01-06 03:32:57,185 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:32:57,185 - mmseg - INFO - Iter [35000/160000] lr: 4.688e-05, eta: 15:09:44, time: 0.482, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1449, decode.acc_seg: 94.1663, loss: 0.1449 2023-01-06 03:33:18,978 - mmseg - INFO - Iter [35050/160000] lr: 4.686e-05, eta: 15:09:22, time: 0.436, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1453, decode.acc_seg: 94.1178, loss: 0.1453 2023-01-06 03:33:41,204 - mmseg - INFO - Iter [35100/160000] lr: 4.684e-05, eta: 15:09:01, time: 0.445, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1478, decode.acc_seg: 94.0557, loss: 0.1478 2023-01-06 03:34:03,458 - mmseg - INFO - Iter [35150/160000] lr: 4.682e-05, eta: 15:08:41, time: 0.445, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1547, decode.acc_seg: 93.8619, loss: 0.1547 2023-01-06 03:34:25,295 - mmseg - INFO - Iter [35200/160000] lr: 4.680e-05, eta: 15:08:19, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1517, decode.acc_seg: 94.0007, loss: 0.1517 2023-01-06 03:34:46,364 - mmseg - INFO - Iter [35250/160000] lr: 4.678e-05, eta: 15:07:55, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1510, decode.acc_seg: 93.7534, loss: 0.1510 2023-01-06 03:35:07,198 - mmseg - INFO - Iter [35300/160000] lr: 4.676e-05, eta: 15:07:29, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1505, decode.acc_seg: 94.0093, loss: 0.1505 2023-01-06 03:35:30,795 - mmseg - INFO - Iter [35350/160000] lr: 4.674e-05, eta: 15:07:14, time: 0.472, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1401, decode.acc_seg: 94.3671, loss: 0.1401 2023-01-06 03:35:52,289 - mmseg - INFO - Iter [35400/160000] lr: 4.673e-05, eta: 15:06:51, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1406, decode.acc_seg: 94.3021, loss: 0.1406 2023-01-06 03:36:14,632 - mmseg - INFO - Iter [35450/160000] lr: 4.671e-05, eta: 15:06:31, time: 0.447, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1380, decode.acc_seg: 94.3937, loss: 0.1380 2023-01-06 03:36:36,171 - mmseg - INFO - Iter [35500/160000] lr: 4.669e-05, eta: 15:06:08, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1502, decode.acc_seg: 94.0449, loss: 0.1502 2023-01-06 03:36:57,903 - mmseg - INFO - Iter [35550/160000] lr: 4.667e-05, eta: 15:05:45, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1585, decode.acc_seg: 93.7027, loss: 0.1585 2023-01-06 03:37:19,222 - mmseg - INFO - Iter [35600/160000] lr: 4.665e-05, eta: 15:05:22, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1483, decode.acc_seg: 93.9955, loss: 0.1483 2023-01-06 03:37:40,185 - mmseg - INFO - Iter [35650/160000] lr: 4.663e-05, eta: 15:04:57, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1494, decode.acc_seg: 94.0633, loss: 0.1494 2023-01-06 03:38:01,392 - mmseg - INFO - Iter [35700/160000] lr: 4.661e-05, eta: 15:04:33, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1693, decode.acc_seg: 93.4266, loss: 0.1693 2023-01-06 03:38:25,300 - mmseg - INFO - Iter [35750/160000] lr: 4.659e-05, eta: 15:04:18, time: 0.478, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1459, decode.acc_seg: 94.0649, loss: 0.1459 2023-01-06 03:38:46,699 - mmseg - INFO - Iter [35800/160000] lr: 4.658e-05, eta: 15:03:55, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1516, decode.acc_seg: 93.9549, loss: 0.1516 2023-01-06 03:39:08,074 - mmseg - INFO - Iter [35850/160000] lr: 4.656e-05, eta: 15:03:32, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1458, decode.acc_seg: 94.1422, loss: 0.1458 2023-01-06 03:39:29,560 - mmseg - INFO - Iter [35900/160000] lr: 4.654e-05, eta: 15:03:09, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1612, decode.acc_seg: 93.7155, loss: 0.1612 2023-01-06 03:39:50,340 - mmseg - INFO - Iter [35950/160000] lr: 4.652e-05, eta: 15:02:43, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1398, decode.acc_seg: 94.3528, loss: 0.1398 2023-01-06 03:40:11,339 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:40:11,340 - mmseg - INFO - Iter [36000/160000] lr: 4.650e-05, eta: 15:02:18, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1508, decode.acc_seg: 93.8292, loss: 0.1508 2023-01-06 03:40:32,678 - mmseg - INFO - Iter [36050/160000] lr: 4.648e-05, eta: 15:01:55, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1650, decode.acc_seg: 93.6815, loss: 0.1650 2023-01-06 03:40:55,849 - mmseg - INFO - Iter [36100/160000] lr: 4.646e-05, eta: 15:01:38, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1439, decode.acc_seg: 94.2667, loss: 0.1439 2023-01-06 03:41:17,390 - mmseg - INFO - Iter [36150/160000] lr: 4.644e-05, eta: 15:01:15, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1425, decode.acc_seg: 94.4719, loss: 0.1425 2023-01-06 03:41:38,919 - mmseg - INFO - Iter [36200/160000] lr: 4.643e-05, eta: 15:00:52, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1503, decode.acc_seg: 94.1273, loss: 0.1503 2023-01-06 03:42:00,289 - mmseg - INFO - Iter [36250/160000] lr: 4.641e-05, eta: 15:00:28, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1421, decode.acc_seg: 94.2950, loss: 0.1421 2023-01-06 03:42:21,651 - mmseg - INFO - Iter [36300/160000] lr: 4.639e-05, eta: 15:00:05, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1427, decode.acc_seg: 94.2366, loss: 0.1427 2023-01-06 03:42:42,885 - mmseg - INFO - Iter [36350/160000] lr: 4.637e-05, eta: 14:59:41, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1423, decode.acc_seg: 94.1457, loss: 0.1423 2023-01-06 03:43:03,928 - mmseg - INFO - Iter [36400/160000] lr: 4.635e-05, eta: 14:59:17, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1504, decode.acc_seg: 94.0029, loss: 0.1504 2023-01-06 03:43:25,537 - mmseg - INFO - Iter [36450/160000] lr: 4.633e-05, eta: 14:58:54, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1349, decode.acc_seg: 94.5480, loss: 0.1349 2023-01-06 03:43:48,882 - mmseg - INFO - Iter [36500/160000] lr: 4.631e-05, eta: 14:58:37, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1458, decode.acc_seg: 94.2629, loss: 0.1458 2023-01-06 03:44:10,086 - mmseg - INFO - Iter [36550/160000] lr: 4.629e-05, eta: 14:58:14, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1401, decode.acc_seg: 94.3412, loss: 0.1401 2023-01-06 03:44:31,348 - mmseg - INFO - Iter [36600/160000] lr: 4.628e-05, eta: 14:57:50, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1435, decode.acc_seg: 94.2434, loss: 0.1435 2023-01-06 03:44:52,268 - mmseg - INFO - Iter [36650/160000] lr: 4.626e-05, eta: 14:57:25, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1506, decode.acc_seg: 94.0191, loss: 0.1506 2023-01-06 03:45:13,538 - mmseg - INFO - Iter [36700/160000] lr: 4.624e-05, eta: 14:57:01, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1423, decode.acc_seg: 94.2463, loss: 0.1423 2023-01-06 03:45:35,618 - mmseg - INFO - Iter [36750/160000] lr: 4.622e-05, eta: 14:56:40, time: 0.442, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1561, decode.acc_seg: 93.9178, loss: 0.1561 2023-01-06 03:45:57,637 - mmseg - INFO - Iter [36800/160000] lr: 4.620e-05, eta: 14:56:19, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1492, decode.acc_seg: 93.8596, loss: 0.1492 2023-01-06 03:46:21,486 - mmseg - INFO - Iter [36850/160000] lr: 4.618e-05, eta: 14:56:04, time: 0.478, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1429, decode.acc_seg: 94.2973, loss: 0.1429 2023-01-06 03:46:42,254 - mmseg - INFO - Iter [36900/160000] lr: 4.616e-05, eta: 14:55:39, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1460, decode.acc_seg: 94.2579, loss: 0.1460 2023-01-06 03:47:03,818 - mmseg - INFO - Iter [36950/160000] lr: 4.614e-05, eta: 14:55:16, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1351, decode.acc_seg: 94.4848, loss: 0.1351 2023-01-06 03:47:25,822 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:47:25,823 - mmseg - INFO - Iter [37000/160000] lr: 4.613e-05, eta: 14:54:55, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1440, decode.acc_seg: 94.0387, loss: 0.1440 2023-01-06 03:47:46,962 - mmseg - INFO - Iter [37050/160000] lr: 4.611e-05, eta: 14:54:31, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1509, decode.acc_seg: 93.9870, loss: 0.1509 2023-01-06 03:48:08,493 - mmseg - INFO - Iter [37100/160000] lr: 4.609e-05, eta: 14:54:08, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1533, decode.acc_seg: 93.7776, loss: 0.1533 2023-01-06 03:48:30,513 - mmseg - INFO - Iter [37150/160000] lr: 4.607e-05, eta: 14:53:46, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1524, decode.acc_seg: 93.9570, loss: 0.1524 2023-01-06 03:48:51,331 - mmseg - INFO - Iter [37200/160000] lr: 4.605e-05, eta: 14:53:21, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1622, decode.acc_seg: 93.6479, loss: 0.1622 2023-01-06 03:49:14,864 - mmseg - INFO - Iter [37250/160000] lr: 4.603e-05, eta: 14:53:05, time: 0.471, data_time: 0.058, memory: 9591, decode.loss_ce: 0.1517, decode.acc_seg: 93.9789, loss: 0.1517 2023-01-06 03:49:35,688 - mmseg - INFO - Iter [37300/160000] lr: 4.601e-05, eta: 14:52:40, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1443, decode.acc_seg: 94.2358, loss: 0.1443 2023-01-06 03:49:57,272 - mmseg - INFO - Iter [37350/160000] lr: 4.599e-05, eta: 14:52:17, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1409, decode.acc_seg: 94.4321, loss: 0.1409 2023-01-06 03:50:18,340 - mmseg - INFO - Iter [37400/160000] lr: 4.598e-05, eta: 14:51:53, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1628, decode.acc_seg: 93.5139, loss: 0.1628 2023-01-06 03:50:41,131 - mmseg - INFO - Iter [37450/160000] lr: 4.596e-05, eta: 14:51:34, time: 0.456, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1476, decode.acc_seg: 94.2242, loss: 0.1476 2023-01-06 03:51:02,107 - mmseg - INFO - Iter [37500/160000] lr: 4.594e-05, eta: 14:51:10, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1488, decode.acc_seg: 94.0206, loss: 0.1488 2023-01-06 03:51:23,806 - mmseg - INFO - Iter [37550/160000] lr: 4.592e-05, eta: 14:50:48, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1529, decode.acc_seg: 93.9800, loss: 0.1529 2023-01-06 03:51:47,179 - mmseg - INFO - Iter [37600/160000] lr: 4.590e-05, eta: 14:50:31, time: 0.468, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1441, decode.acc_seg: 94.0868, loss: 0.1441 2023-01-06 03:52:08,300 - mmseg - INFO - Iter [37650/160000] lr: 4.588e-05, eta: 14:50:07, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1367, decode.acc_seg: 94.4451, loss: 0.1367 2023-01-06 03:52:29,603 - mmseg - INFO - Iter [37700/160000] lr: 4.586e-05, eta: 14:49:43, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1427, decode.acc_seg: 94.3796, loss: 0.1427 2023-01-06 03:52:51,116 - mmseg - INFO - Iter [37750/160000] lr: 4.584e-05, eta: 14:49:20, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1466, decode.acc_seg: 94.1109, loss: 0.1466 2023-01-06 03:53:12,645 - mmseg - INFO - Iter [37800/160000] lr: 4.583e-05, eta: 14:48:58, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1417, decode.acc_seg: 94.3863, loss: 0.1417 2023-01-06 03:53:33,954 - mmseg - INFO - Iter [37850/160000] lr: 4.581e-05, eta: 14:48:34, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1462, decode.acc_seg: 94.0590, loss: 0.1462 2023-01-06 03:53:54,988 - mmseg - INFO - Iter [37900/160000] lr: 4.579e-05, eta: 14:48:10, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1410, decode.acc_seg: 94.4718, loss: 0.1410 2023-01-06 03:54:18,084 - mmseg - INFO - Iter [37950/160000] lr: 4.577e-05, eta: 14:47:52, time: 0.462, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1386, decode.acc_seg: 94.4726, loss: 0.1386 2023-01-06 03:54:40,025 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 03:54:40,026 - mmseg - INFO - Iter [38000/160000] lr: 4.575e-05, eta: 14:47:31, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1331, decode.acc_seg: 94.7671, loss: 0.1331 2023-01-06 03:55:00,897 - mmseg - INFO - Iter [38050/160000] lr: 4.573e-05, eta: 14:47:06, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1533, decode.acc_seg: 93.9878, loss: 0.1533 2023-01-06 03:55:21,857 - mmseg - INFO - Iter [38100/160000] lr: 4.571e-05, eta: 14:46:41, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1594, decode.acc_seg: 93.6827, loss: 0.1594 2023-01-06 03:55:43,089 - mmseg - INFO - Iter [38150/160000] lr: 4.569e-05, eta: 14:46:17, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1632, decode.acc_seg: 93.5838, loss: 0.1632 2023-01-06 03:56:04,924 - mmseg - INFO - Iter [38200/160000] lr: 4.568e-05, eta: 14:45:56, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1474, decode.acc_seg: 94.2451, loss: 0.1474 2023-01-06 03:56:26,408 - mmseg - INFO - Iter [38250/160000] lr: 4.566e-05, eta: 14:45:33, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1519, decode.acc_seg: 94.0814, loss: 0.1519 2023-01-06 03:56:47,196 - mmseg - INFO - Iter [38300/160000] lr: 4.564e-05, eta: 14:45:08, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1540, decode.acc_seg: 93.7742, loss: 0.1540 2023-01-06 03:57:11,396 - mmseg - INFO - Iter [38350/160000] lr: 4.562e-05, eta: 14:44:53, time: 0.484, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1407, decode.acc_seg: 94.3507, loss: 0.1407 2023-01-06 03:57:32,556 - mmseg - INFO - Iter [38400/160000] lr: 4.560e-05, eta: 14:44:29, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1596, decode.acc_seg: 93.7886, loss: 0.1596 2023-01-06 03:57:54,279 - mmseg - INFO - Iter [38450/160000] lr: 4.558e-05, eta: 14:44:07, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1457, decode.acc_seg: 94.1468, loss: 0.1457 2023-01-06 03:58:15,596 - mmseg - INFO - Iter [38500/160000] lr: 4.556e-05, eta: 14:43:44, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1632, decode.acc_seg: 93.5352, loss: 0.1632 2023-01-06 03:58:36,509 - mmseg - INFO - Iter [38550/160000] lr: 4.554e-05, eta: 14:43:19, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1483, decode.acc_seg: 93.9807, loss: 0.1483 2023-01-06 03:58:57,526 - mmseg - INFO - Iter [38600/160000] lr: 4.553e-05, eta: 14:42:55, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1526, decode.acc_seg: 94.0269, loss: 0.1526 2023-01-06 03:59:18,790 - mmseg - INFO - Iter [38650/160000] lr: 4.551e-05, eta: 14:42:31, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1559, decode.acc_seg: 93.8067, loss: 0.1559 2023-01-06 03:59:43,107 - mmseg - INFO - Iter [38700/160000] lr: 4.549e-05, eta: 14:42:17, time: 0.486, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1506, decode.acc_seg: 94.1171, loss: 0.1506 2023-01-06 04:00:04,488 - mmseg - INFO - Iter [38750/160000] lr: 4.547e-05, eta: 14:41:54, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1244, decode.acc_seg: 94.9218, loss: 0.1244 2023-01-06 04:00:27,105 - mmseg - INFO - Iter [38800/160000] lr: 4.545e-05, eta: 14:41:35, time: 0.452, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1471, decode.acc_seg: 94.2301, loss: 0.1471 2023-01-06 04:00:48,444 - mmseg - INFO - Iter [38850/160000] lr: 4.543e-05, eta: 14:41:11, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1414, decode.acc_seg: 94.3261, loss: 0.1414 2023-01-06 04:01:09,227 - mmseg - INFO - Iter [38900/160000] lr: 4.541e-05, eta: 14:40:46, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1416, decode.acc_seg: 94.1942, loss: 0.1416 2023-01-06 04:01:30,750 - mmseg - INFO - Iter [38950/160000] lr: 4.539e-05, eta: 14:40:24, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1442, decode.acc_seg: 94.1565, loss: 0.1442 2023-01-06 04:01:52,465 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:01:52,466 - mmseg - INFO - Iter [39000/160000] lr: 4.538e-05, eta: 14:40:01, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1518, decode.acc_seg: 94.0781, loss: 0.1518 2023-01-06 04:02:14,210 - mmseg - INFO - Iter [39050/160000] lr: 4.536e-05, eta: 14:39:39, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1450, decode.acc_seg: 94.1989, loss: 0.1450 2023-01-06 04:02:38,058 - mmseg - INFO - Iter [39100/160000] lr: 4.534e-05, eta: 14:39:24, time: 0.477, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1428, decode.acc_seg: 94.1978, loss: 0.1428 2023-01-06 04:03:00,579 - mmseg - INFO - Iter [39150/160000] lr: 4.532e-05, eta: 14:39:04, time: 0.450, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1527, decode.acc_seg: 94.1364, loss: 0.1527 2023-01-06 04:03:21,669 - mmseg - INFO - Iter [39200/160000] lr: 4.530e-05, eta: 14:38:40, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1406, decode.acc_seg: 94.4566, loss: 0.1406 2023-01-06 04:03:43,027 - mmseg - INFO - Iter [39250/160000] lr: 4.528e-05, eta: 14:38:17, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1386, decode.acc_seg: 94.3336, loss: 0.1386 2023-01-06 04:04:04,387 - mmseg - INFO - Iter [39300/160000] lr: 4.526e-05, eta: 14:37:54, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1445, decode.acc_seg: 94.2632, loss: 0.1445 2023-01-06 04:04:25,188 - mmseg - INFO - Iter [39350/160000] lr: 4.524e-05, eta: 14:37:29, time: 0.416, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1438, decode.acc_seg: 94.2401, loss: 0.1438 2023-01-06 04:04:46,587 - mmseg - INFO - Iter [39400/160000] lr: 4.523e-05, eta: 14:37:06, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1461, decode.acc_seg: 94.0503, loss: 0.1461 2023-01-06 04:05:09,991 - mmseg - INFO - Iter [39450/160000] lr: 4.521e-05, eta: 14:36:49, time: 0.468, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1537, decode.acc_seg: 93.8336, loss: 0.1537 2023-01-06 04:05:31,033 - mmseg - INFO - Iter [39500/160000] lr: 4.519e-05, eta: 14:36:24, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1433, decode.acc_seg: 94.2118, loss: 0.1433 2023-01-06 04:05:52,475 - mmseg - INFO - Iter [39550/160000] lr: 4.517e-05, eta: 14:36:01, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1366, decode.acc_seg: 94.6490, loss: 0.1366 2023-01-06 04:06:13,663 - mmseg - INFO - Iter [39600/160000] lr: 4.515e-05, eta: 14:35:38, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1428, decode.acc_seg: 94.2108, loss: 0.1428 2023-01-06 04:06:35,878 - mmseg - INFO - Iter [39650/160000] lr: 4.513e-05, eta: 14:35:17, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1421, decode.acc_seg: 94.3212, loss: 0.1421 2023-01-06 04:06:56,848 - mmseg - INFO - Iter [39700/160000] lr: 4.511e-05, eta: 14:34:53, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1468, decode.acc_seg: 94.1475, loss: 0.1468 2023-01-06 04:07:17,943 - mmseg - INFO - Iter [39750/160000] lr: 4.509e-05, eta: 14:34:29, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1455, decode.acc_seg: 94.2370, loss: 0.1455 2023-01-06 04:07:38,896 - mmseg - INFO - Iter [39800/160000] lr: 4.508e-05, eta: 14:34:04, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1435, decode.acc_seg: 94.1207, loss: 0.1435 2023-01-06 04:08:02,852 - mmseg - INFO - Iter [39850/160000] lr: 4.506e-05, eta: 14:33:49, time: 0.479, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1275, decode.acc_seg: 94.7890, loss: 0.1275 2023-01-06 04:08:24,944 - mmseg - INFO - Iter [39900/160000] lr: 4.504e-05, eta: 14:33:28, time: 0.442, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1459, decode.acc_seg: 94.1254, loss: 0.1459 2023-01-06 04:08:46,707 - mmseg - INFO - Iter [39950/160000] lr: 4.502e-05, eta: 14:33:06, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1319, decode.acc_seg: 94.5854, loss: 0.1319 2023-01-06 04:09:09,297 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:09:09,298 - mmseg - INFO - Iter [40000/160000] lr: 4.500e-05, eta: 14:32:46, time: 0.452, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1477, decode.acc_seg: 93.8768, loss: 0.1477 2023-01-06 04:09:30,566 - mmseg - INFO - Iter [40050/160000] lr: 4.498e-05, eta: 14:32:23, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1414, decode.acc_seg: 94.3472, loss: 0.1414 2023-01-06 04:09:52,792 - mmseg - INFO - Iter [40100/160000] lr: 4.496e-05, eta: 14:32:02, time: 0.444, data_time: 0.023, memory: 9591, decode.loss_ce: 0.1527, decode.acc_seg: 94.0268, loss: 0.1527 2023-01-06 04:10:14,160 - mmseg - INFO - Iter [40150/160000] lr: 4.494e-05, eta: 14:31:39, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1484, decode.acc_seg: 94.0505, loss: 0.1484 2023-01-06 04:10:37,340 - mmseg - INFO - Iter [40200/160000] lr: 4.493e-05, eta: 14:31:21, time: 0.464, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1446, decode.acc_seg: 94.1737, loss: 0.1446 2023-01-06 04:10:58,153 - mmseg - INFO - Iter [40250/160000] lr: 4.491e-05, eta: 14:30:57, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1385, decode.acc_seg: 94.5340, loss: 0.1385 2023-01-06 04:11:19,300 - mmseg - INFO - Iter [40300/160000] lr: 4.489e-05, eta: 14:30:33, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1418, decode.acc_seg: 94.0367, loss: 0.1418 2023-01-06 04:11:40,781 - mmseg - INFO - Iter [40350/160000] lr: 4.487e-05, eta: 14:30:10, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1522, decode.acc_seg: 93.7833, loss: 0.1522 2023-01-06 04:12:01,905 - mmseg - INFO - Iter [40400/160000] lr: 4.485e-05, eta: 14:29:46, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1443, decode.acc_seg: 94.1399, loss: 0.1443 2023-01-06 04:12:23,762 - mmseg - INFO - Iter [40450/160000] lr: 4.483e-05, eta: 14:29:24, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1394, decode.acc_seg: 94.3810, loss: 0.1394 2023-01-06 04:12:44,543 - mmseg - INFO - Iter [40500/160000] lr: 4.481e-05, eta: 14:29:00, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1470, decode.acc_seg: 94.2357, loss: 0.1470 2023-01-06 04:13:08,089 - mmseg - INFO - Iter [40550/160000] lr: 4.479e-05, eta: 14:28:43, time: 0.471, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1457, decode.acc_seg: 94.3045, loss: 0.1457 2023-01-06 04:13:29,399 - mmseg - INFO - Iter [40600/160000] lr: 4.478e-05, eta: 14:28:20, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1364, decode.acc_seg: 94.3683, loss: 0.1364 2023-01-06 04:13:50,603 - mmseg - INFO - Iter [40650/160000] lr: 4.476e-05, eta: 14:27:56, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1537, decode.acc_seg: 94.0323, loss: 0.1537 2023-01-06 04:14:11,364 - mmseg - INFO - Iter [40700/160000] lr: 4.474e-05, eta: 14:27:31, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1409, decode.acc_seg: 94.3383, loss: 0.1409 2023-01-06 04:14:33,224 - mmseg - INFO - Iter [40750/160000] lr: 4.472e-05, eta: 14:27:09, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1555, decode.acc_seg: 93.8488, loss: 0.1555 2023-01-06 04:14:54,582 - mmseg - INFO - Iter [40800/160000] lr: 4.470e-05, eta: 14:26:46, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1434, decode.acc_seg: 94.1454, loss: 0.1434 2023-01-06 04:15:16,085 - mmseg - INFO - Iter [40850/160000] lr: 4.468e-05, eta: 14:26:23, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1554, decode.acc_seg: 93.7824, loss: 0.1554 2023-01-06 04:15:37,706 - mmseg - INFO - Iter [40900/160000] lr: 4.466e-05, eta: 14:26:01, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1674, decode.acc_seg: 93.2757, loss: 0.1674 2023-01-06 04:16:01,061 - mmseg - INFO - Iter [40950/160000] lr: 4.464e-05, eta: 14:25:44, time: 0.467, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1459, decode.acc_seg: 94.0411, loss: 0.1459 2023-01-06 04:16:22,424 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:16:22,424 - mmseg - INFO - Iter [41000/160000] lr: 4.463e-05, eta: 14:25:21, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1462, decode.acc_seg: 94.2479, loss: 0.1462 2023-01-06 04:16:43,270 - mmseg - INFO - Iter [41050/160000] lr: 4.461e-05, eta: 14:24:56, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1461, decode.acc_seg: 94.1911, loss: 0.1461 2023-01-06 04:17:04,679 - mmseg - INFO - Iter [41100/160000] lr: 4.459e-05, eta: 14:24:33, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1432, decode.acc_seg: 94.2991, loss: 0.1432 2023-01-06 04:17:25,919 - mmseg - INFO - Iter [41150/160000] lr: 4.457e-05, eta: 14:24:09, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1389, decode.acc_seg: 94.3350, loss: 0.1389 2023-01-06 04:17:47,549 - mmseg - INFO - Iter [41200/160000] lr: 4.455e-05, eta: 14:23:47, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1396, decode.acc_seg: 94.4999, loss: 0.1396 2023-01-06 04:18:09,017 - mmseg - INFO - Iter [41250/160000] lr: 4.453e-05, eta: 14:23:24, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1344, decode.acc_seg: 94.4163, loss: 0.1344 2023-01-06 04:18:33,111 - mmseg - INFO - Iter [41300/160000] lr: 4.451e-05, eta: 14:23:09, time: 0.481, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1343, decode.acc_seg: 94.6262, loss: 0.1343 2023-01-06 04:18:55,113 - mmseg - INFO - Iter [41350/160000] lr: 4.449e-05, eta: 14:22:48, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1350, decode.acc_seg: 94.3787, loss: 0.1350 2023-01-06 04:19:16,264 - mmseg - INFO - Iter [41400/160000] lr: 4.448e-05, eta: 14:22:24, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1515, decode.acc_seg: 94.3626, loss: 0.1515 2023-01-06 04:19:37,563 - mmseg - INFO - Iter [41450/160000] lr: 4.446e-05, eta: 14:22:01, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1404, decode.acc_seg: 94.4145, loss: 0.1404 2023-01-06 04:19:58,578 - mmseg - INFO - Iter [41500/160000] lr: 4.444e-05, eta: 14:21:37, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1526, decode.acc_seg: 93.9162, loss: 0.1526 2023-01-06 04:20:20,998 - mmseg - INFO - Iter [41550/160000] lr: 4.442e-05, eta: 14:21:17, time: 0.448, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1423, decode.acc_seg: 94.3653, loss: 0.1423 2023-01-06 04:20:42,183 - mmseg - INFO - Iter [41600/160000] lr: 4.440e-05, eta: 14:20:53, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1324, decode.acc_seg: 94.5287, loss: 0.1324 2023-01-06 04:21:04,088 - mmseg - INFO - Iter [41650/160000] lr: 4.438e-05, eta: 14:20:31, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1397, decode.acc_seg: 94.4227, loss: 0.1397 2023-01-06 04:21:27,788 - mmseg - INFO - Iter [41700/160000] lr: 4.436e-05, eta: 14:20:15, time: 0.475, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1336, decode.acc_seg: 94.5388, loss: 0.1336 2023-01-06 04:21:48,843 - mmseg - INFO - Iter [41750/160000] lr: 4.434e-05, eta: 14:19:51, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1488, decode.acc_seg: 94.0851, loss: 0.1488 2023-01-06 04:22:09,818 - mmseg - INFO - Iter [41800/160000] lr: 4.433e-05, eta: 14:19:27, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1387, decode.acc_seg: 94.3159, loss: 0.1387 2023-01-06 04:22:31,684 - mmseg - INFO - Iter [41850/160000] lr: 4.431e-05, eta: 14:19:05, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1347, decode.acc_seg: 94.4731, loss: 0.1347 2023-01-06 04:22:52,691 - mmseg - INFO - Iter [41900/160000] lr: 4.429e-05, eta: 14:18:41, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1431, decode.acc_seg: 94.1441, loss: 0.1431 2023-01-06 04:23:14,120 - mmseg - INFO - Iter [41950/160000] lr: 4.427e-05, eta: 14:18:18, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1345, decode.acc_seg: 94.6305, loss: 0.1345 2023-01-06 04:23:36,487 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:23:36,488 - mmseg - INFO - Iter [42000/160000] lr: 4.425e-05, eta: 14:17:58, time: 0.448, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1358, decode.acc_seg: 94.6395, loss: 0.1358 2023-01-06 04:23:59,486 - mmseg - INFO - Iter [42050/160000] lr: 4.423e-05, eta: 14:17:39, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1355, decode.acc_seg: 94.5719, loss: 0.1355 2023-01-06 04:24:21,373 - mmseg - INFO - Iter [42100/160000] lr: 4.421e-05, eta: 14:17:18, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1475, decode.acc_seg: 94.0153, loss: 0.1475 2023-01-06 04:24:42,369 - mmseg - INFO - Iter [42150/160000] lr: 4.419e-05, eta: 14:16:54, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1397, decode.acc_seg: 94.5215, loss: 0.1397 2023-01-06 04:25:03,963 - mmseg - INFO - Iter [42200/160000] lr: 4.418e-05, eta: 14:16:31, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1452, decode.acc_seg: 94.1525, loss: 0.1452 2023-01-06 04:25:25,419 - mmseg - INFO - Iter [42250/160000] lr: 4.416e-05, eta: 14:16:08, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1384, decode.acc_seg: 94.4371, loss: 0.1384 2023-01-06 04:25:46,729 - mmseg - INFO - Iter [42300/160000] lr: 4.414e-05, eta: 14:15:45, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1276, decode.acc_seg: 94.8080, loss: 0.1276 2023-01-06 04:26:08,507 - mmseg - INFO - Iter [42350/160000] lr: 4.412e-05, eta: 14:15:23, time: 0.436, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1405, decode.acc_seg: 94.2891, loss: 0.1405 2023-01-06 04:26:29,568 - mmseg - INFO - Iter [42400/160000] lr: 4.410e-05, eta: 14:14:59, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1345, decode.acc_seg: 94.5636, loss: 0.1345 2023-01-06 04:26:52,679 - mmseg - INFO - Iter [42450/160000] lr: 4.408e-05, eta: 14:14:41, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1312, decode.acc_seg: 94.7650, loss: 0.1312 2023-01-06 04:27:13,659 - mmseg - INFO - Iter [42500/160000] lr: 4.406e-05, eta: 14:14:17, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1495, decode.acc_seg: 94.0045, loss: 0.1495 2023-01-06 04:27:35,271 - mmseg - INFO - Iter [42550/160000] lr: 4.404e-05, eta: 14:13:55, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1324, decode.acc_seg: 94.5056, loss: 0.1324 2023-01-06 04:27:56,770 - mmseg - INFO - Iter [42600/160000] lr: 4.403e-05, eta: 14:13:32, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1430, decode.acc_seg: 94.2138, loss: 0.1430 2023-01-06 04:28:18,227 - mmseg - INFO - Iter [42650/160000] lr: 4.401e-05, eta: 14:13:09, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1314, decode.acc_seg: 94.4650, loss: 0.1314 2023-01-06 04:28:39,139 - mmseg - INFO - Iter [42700/160000] lr: 4.399e-05, eta: 14:12:45, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1399, decode.acc_seg: 94.5117, loss: 0.1399 2023-01-06 04:29:00,188 - mmseg - INFO - Iter [42750/160000] lr: 4.397e-05, eta: 14:12:21, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1343, decode.acc_seg: 94.5295, loss: 0.1343 2023-01-06 04:29:23,549 - mmseg - INFO - Iter [42800/160000] lr: 4.395e-05, eta: 14:12:03, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1337, decode.acc_seg: 94.5094, loss: 0.1337 2023-01-06 04:29:45,462 - mmseg - INFO - Iter [42850/160000] lr: 4.393e-05, eta: 14:11:42, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1334, decode.acc_seg: 94.6395, loss: 0.1334 2023-01-06 04:30:06,376 - mmseg - INFO - Iter [42900/160000] lr: 4.391e-05, eta: 14:11:18, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1404, decode.acc_seg: 94.2806, loss: 0.1404 2023-01-06 04:30:27,426 - mmseg - INFO - Iter [42950/160000] lr: 4.389e-05, eta: 14:10:54, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1406, decode.acc_seg: 94.3247, loss: 0.1406 2023-01-06 04:30:49,159 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:30:49,159 - mmseg - INFO - Iter [43000/160000] lr: 4.388e-05, eta: 14:10:32, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1283, decode.acc_seg: 94.6940, loss: 0.1283 2023-01-06 04:31:10,998 - mmseg - INFO - Iter [43050/160000] lr: 4.386e-05, eta: 14:10:10, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1423, decode.acc_seg: 94.1189, loss: 0.1423 2023-01-06 04:31:32,093 - mmseg - INFO - Iter [43100/160000] lr: 4.384e-05, eta: 14:09:46, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1357, decode.acc_seg: 94.3721, loss: 0.1357 2023-01-06 04:31:53,925 - mmseg - INFO - Iter [43150/160000] lr: 4.382e-05, eta: 14:09:25, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1438, decode.acc_seg: 94.1977, loss: 0.1438 2023-01-06 04:32:17,698 - mmseg - INFO - Iter [43200/160000] lr: 4.380e-05, eta: 14:09:08, time: 0.475, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1270, decode.acc_seg: 94.7911, loss: 0.1270 2023-01-06 04:32:39,228 - mmseg - INFO - Iter [43250/160000] lr: 4.378e-05, eta: 14:08:46, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1330, decode.acc_seg: 94.7171, loss: 0.1330 2023-01-06 04:33:00,728 - mmseg - INFO - Iter [43300/160000] lr: 4.376e-05, eta: 14:08:23, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1394, decode.acc_seg: 94.3716, loss: 0.1394 2023-01-06 04:33:21,882 - mmseg - INFO - Iter [43350/160000] lr: 4.374e-05, eta: 14:07:59, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1294, decode.acc_seg: 94.6925, loss: 0.1294 2023-01-06 04:33:43,448 - mmseg - INFO - Iter [43400/160000] lr: 4.373e-05, eta: 14:07:37, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1308, decode.acc_seg: 94.6418, loss: 0.1308 2023-01-06 04:34:05,957 - mmseg - INFO - Iter [43450/160000] lr: 4.371e-05, eta: 14:07:17, time: 0.451, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1422, decode.acc_seg: 94.1697, loss: 0.1422 2023-01-06 04:34:27,250 - mmseg - INFO - Iter [43500/160000] lr: 4.369e-05, eta: 14:06:54, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1346, decode.acc_seg: 94.6008, loss: 0.1346 2023-01-06 04:34:51,169 - mmseg - INFO - Iter [43550/160000] lr: 4.367e-05, eta: 14:06:38, time: 0.479, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1473, decode.acc_seg: 93.9153, loss: 0.1473 2023-01-06 04:35:11,897 - mmseg - INFO - Iter [43600/160000] lr: 4.365e-05, eta: 14:06:13, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1315, decode.acc_seg: 94.6853, loss: 0.1315 2023-01-06 04:35:33,874 - mmseg - INFO - Iter [43650/160000] lr: 4.363e-05, eta: 14:05:52, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1343, decode.acc_seg: 94.4847, loss: 0.1343 2023-01-06 04:35:55,550 - mmseg - INFO - Iter [43700/160000] lr: 4.361e-05, eta: 14:05:29, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1302, decode.acc_seg: 94.5707, loss: 0.1302 2023-01-06 04:36:16,455 - mmseg - INFO - Iter [43750/160000] lr: 4.359e-05, eta: 14:05:05, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1408, decode.acc_seg: 94.4145, loss: 0.1408 2023-01-06 04:36:37,792 - mmseg - INFO - Iter [43800/160000] lr: 4.358e-05, eta: 14:04:42, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1444, decode.acc_seg: 94.3067, loss: 0.1444 2023-01-06 04:36:58,690 - mmseg - INFO - Iter [43850/160000] lr: 4.356e-05, eta: 14:04:18, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1473, decode.acc_seg: 94.1397, loss: 0.1473 2023-01-06 04:37:22,010 - mmseg - INFO - Iter [43900/160000] lr: 4.354e-05, eta: 14:04:00, time: 0.466, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1360, decode.acc_seg: 94.5335, loss: 0.1360 2023-01-06 04:37:43,388 - mmseg - INFO - Iter [43950/160000] lr: 4.352e-05, eta: 14:03:37, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1224, decode.acc_seg: 94.9548, loss: 0.1224 2023-01-06 04:38:04,586 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:38:04,587 - mmseg - INFO - Iter [44000/160000] lr: 4.350e-05, eta: 14:03:14, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1309, decode.acc_seg: 94.6090, loss: 0.1309 2023-01-06 04:38:25,660 - mmseg - INFO - Iter [44050/160000] lr: 4.348e-05, eta: 14:02:50, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1558, decode.acc_seg: 93.6921, loss: 0.1558 2023-01-06 04:38:46,972 - mmseg - INFO - Iter [44100/160000] lr: 4.346e-05, eta: 14:02:27, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1466, decode.acc_seg: 94.0977, loss: 0.1466 2023-01-06 04:39:08,294 - mmseg - INFO - Iter [44150/160000] lr: 4.344e-05, eta: 14:02:04, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1346, decode.acc_seg: 94.7316, loss: 0.1346 2023-01-06 04:39:29,429 - mmseg - INFO - Iter [44200/160000] lr: 4.343e-05, eta: 14:01:40, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1378, decode.acc_seg: 94.4456, loss: 0.1378 2023-01-06 04:39:50,304 - mmseg - INFO - Iter [44250/160000] lr: 4.341e-05, eta: 14:01:16, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1344, decode.acc_seg: 94.5704, loss: 0.1344 2023-01-06 04:40:13,288 - mmseg - INFO - Iter [44300/160000] lr: 4.339e-05, eta: 14:00:57, time: 0.460, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1257, decode.acc_seg: 94.8348, loss: 0.1257 2023-01-06 04:40:34,484 - mmseg - INFO - Iter [44350/160000] lr: 4.337e-05, eta: 14:00:34, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1305, decode.acc_seg: 94.7118, loss: 0.1305 2023-01-06 04:40:55,644 - mmseg - INFO - Iter [44400/160000] lr: 4.335e-05, eta: 14:00:10, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1364, decode.acc_seg: 94.5947, loss: 0.1364 2023-01-06 04:41:17,220 - mmseg - INFO - Iter [44450/160000] lr: 4.333e-05, eta: 13:59:48, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1295, decode.acc_seg: 94.7595, loss: 0.1295 2023-01-06 04:41:38,435 - mmseg - INFO - Iter [44500/160000] lr: 4.331e-05, eta: 13:59:25, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1342, decode.acc_seg: 94.5790, loss: 0.1342 2023-01-06 04:41:59,947 - mmseg - INFO - Iter [44550/160000] lr: 4.329e-05, eta: 13:59:02, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1400, decode.acc_seg: 94.5350, loss: 0.1400 2023-01-06 04:42:21,292 - mmseg - INFO - Iter [44600/160000] lr: 4.328e-05, eta: 13:58:39, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1507, decode.acc_seg: 94.1468, loss: 0.1507 2023-01-06 04:42:45,279 - mmseg - INFO - Iter [44650/160000] lr: 4.326e-05, eta: 13:58:23, time: 0.480, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1405, decode.acc_seg: 94.5170, loss: 0.1405 2023-01-06 04:43:06,622 - mmseg - INFO - Iter [44700/160000] lr: 4.324e-05, eta: 13:58:00, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1478, decode.acc_seg: 94.0672, loss: 0.1478 2023-01-06 04:43:27,573 - mmseg - INFO - Iter [44750/160000] lr: 4.322e-05, eta: 13:57:36, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1423, decode.acc_seg: 94.3347, loss: 0.1423 2023-01-06 04:43:49,066 - mmseg - INFO - Iter [44800/160000] lr: 4.320e-05, eta: 13:57:13, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1317, decode.acc_seg: 94.6709, loss: 0.1317 2023-01-06 04:44:10,729 - mmseg - INFO - Iter [44850/160000] lr: 4.318e-05, eta: 13:56:51, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1492, decode.acc_seg: 94.1031, loss: 0.1492 2023-01-06 04:44:31,870 - mmseg - INFO - Iter [44900/160000] lr: 4.316e-05, eta: 13:56:28, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1389, decode.acc_seg: 94.3241, loss: 0.1389 2023-01-06 04:44:53,614 - mmseg - INFO - Iter [44950/160000] lr: 4.314e-05, eta: 13:56:06, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1307, decode.acc_seg: 94.8220, loss: 0.1307 2023-01-06 04:45:14,644 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:45:14,645 - mmseg - INFO - Iter [45000/160000] lr: 4.313e-05, eta: 13:55:42, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1296, decode.acc_seg: 94.6613, loss: 0.1296 2023-01-06 04:45:37,676 - mmseg - INFO - Iter [45050/160000] lr: 4.311e-05, eta: 13:55:23, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1373, decode.acc_seg: 94.5953, loss: 0.1373 2023-01-06 04:45:59,025 - mmseg - INFO - Iter [45100/160000] lr: 4.309e-05, eta: 13:55:00, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1343, decode.acc_seg: 94.5738, loss: 0.1343 2023-01-06 04:46:19,828 - mmseg - INFO - Iter [45150/160000] lr: 4.307e-05, eta: 13:54:36, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1531, decode.acc_seg: 94.0468, loss: 0.1531 2023-01-06 04:46:41,089 - mmseg - INFO - Iter [45200/160000] lr: 4.305e-05, eta: 13:54:13, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1380, decode.acc_seg: 94.5426, loss: 0.1380 2023-01-06 04:47:02,007 - mmseg - INFO - Iter [45250/160000] lr: 4.303e-05, eta: 13:53:49, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1390, decode.acc_seg: 94.4526, loss: 0.1390 2023-01-06 04:47:23,366 - mmseg - INFO - Iter [45300/160000] lr: 4.301e-05, eta: 13:53:26, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1368, decode.acc_seg: 94.5356, loss: 0.1368 2023-01-06 04:47:44,324 - mmseg - INFO - Iter [45350/160000] lr: 4.299e-05, eta: 13:53:02, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1345, decode.acc_seg: 94.4678, loss: 0.1345 2023-01-06 04:48:08,138 - mmseg - INFO - Iter [45400/160000] lr: 4.298e-05, eta: 13:52:45, time: 0.476, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1360, decode.acc_seg: 94.5395, loss: 0.1360 2023-01-06 04:48:29,127 - mmseg - INFO - Iter [45450/160000] lr: 4.296e-05, eta: 13:52:21, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1299, decode.acc_seg: 94.6971, loss: 0.1299 2023-01-06 04:48:50,337 - mmseg - INFO - Iter [45500/160000] lr: 4.294e-05, eta: 13:51:58, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1366, decode.acc_seg: 94.5453, loss: 0.1366 2023-01-06 04:49:11,663 - mmseg - INFO - Iter [45550/160000] lr: 4.292e-05, eta: 13:51:35, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1396, decode.acc_seg: 94.2714, loss: 0.1396 2023-01-06 04:49:33,600 - mmseg - INFO - Iter [45600/160000] lr: 4.290e-05, eta: 13:51:14, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1346, decode.acc_seg: 94.5771, loss: 0.1346 2023-01-06 04:49:54,607 - mmseg - INFO - Iter [45650/160000] lr: 4.288e-05, eta: 13:50:50, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1321, decode.acc_seg: 94.6733, loss: 0.1321 2023-01-06 04:50:15,419 - mmseg - INFO - Iter [45700/160000] lr: 4.286e-05, eta: 13:50:26, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1342, decode.acc_seg: 94.5404, loss: 0.1342 2023-01-06 04:50:37,377 - mmseg - INFO - Iter [45750/160000] lr: 4.284e-05, eta: 13:50:04, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1398, decode.acc_seg: 94.3858, loss: 0.1398 2023-01-06 04:51:01,246 - mmseg - INFO - Iter [45800/160000] lr: 4.283e-05, eta: 13:49:48, time: 0.477, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1331, decode.acc_seg: 94.7293, loss: 0.1331 2023-01-06 04:51:22,125 - mmseg - INFO - Iter [45850/160000] lr: 4.281e-05, eta: 13:49:23, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1289, decode.acc_seg: 94.7425, loss: 0.1289 2023-01-06 04:51:44,065 - mmseg - INFO - Iter [45900/160000] lr: 4.279e-05, eta: 13:49:02, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1316, decode.acc_seg: 94.6559, loss: 0.1316 2023-01-06 04:52:05,480 - mmseg - INFO - Iter [45950/160000] lr: 4.277e-05, eta: 13:48:39, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1293, decode.acc_seg: 94.7019, loss: 0.1293 2023-01-06 04:52:26,882 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:52:26,883 - mmseg - INFO - Iter [46000/160000] lr: 4.275e-05, eta: 13:48:17, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1313, decode.acc_seg: 94.6656, loss: 0.1313 2023-01-06 04:52:48,093 - mmseg - INFO - Iter [46050/160000] lr: 4.273e-05, eta: 13:47:53, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1361, decode.acc_seg: 94.4955, loss: 0.1361 2023-01-06 04:53:09,562 - mmseg - INFO - Iter [46100/160000] lr: 4.271e-05, eta: 13:47:31, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1388, decode.acc_seg: 94.5320, loss: 0.1388 2023-01-06 04:53:32,639 - mmseg - INFO - Iter [46150/160000] lr: 4.269e-05, eta: 13:47:12, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1365, decode.acc_seg: 94.3508, loss: 0.1365 2023-01-06 04:53:53,541 - mmseg - INFO - Iter [46200/160000] lr: 4.268e-05, eta: 13:46:48, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1283, decode.acc_seg: 94.8524, loss: 0.1283 2023-01-06 04:54:14,897 - mmseg - INFO - Iter [46250/160000] lr: 4.266e-05, eta: 13:46:25, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1352, decode.acc_seg: 94.4147, loss: 0.1352 2023-01-06 04:54:36,313 - mmseg - INFO - Iter [46300/160000] lr: 4.264e-05, eta: 13:46:02, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1360, decode.acc_seg: 94.3792, loss: 0.1360 2023-01-06 04:54:57,972 - mmseg - INFO - Iter [46350/160000] lr: 4.262e-05, eta: 13:45:40, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1375, decode.acc_seg: 94.6141, loss: 0.1375 2023-01-06 04:55:19,534 - mmseg - INFO - Iter [46400/160000] lr: 4.260e-05, eta: 13:45:18, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1451, decode.acc_seg: 94.2434, loss: 0.1451 2023-01-06 04:55:40,784 - mmseg - INFO - Iter [46450/160000] lr: 4.258e-05, eta: 13:44:55, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1359, decode.acc_seg: 94.5220, loss: 0.1359 2023-01-06 04:56:01,811 - mmseg - INFO - Iter [46500/160000] lr: 4.256e-05, eta: 13:44:31, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1217, decode.acc_seg: 94.9152, loss: 0.1217 2023-01-06 04:56:25,691 - mmseg - INFO - Iter [46550/160000] lr: 4.254e-05, eta: 13:44:14, time: 0.478, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1230, decode.acc_seg: 94.9867, loss: 0.1230 2023-01-06 04:56:47,268 - mmseg - INFO - Iter [46600/160000] lr: 4.253e-05, eta: 13:43:52, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1377, decode.acc_seg: 94.4444, loss: 0.1377 2023-01-06 04:57:08,472 - mmseg - INFO - Iter [46650/160000] lr: 4.251e-05, eta: 13:43:29, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1279, decode.acc_seg: 94.6336, loss: 0.1279 2023-01-06 04:57:29,993 - mmseg - INFO - Iter [46700/160000] lr: 4.249e-05, eta: 13:43:06, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1421, decode.acc_seg: 94.3741, loss: 0.1421 2023-01-06 04:57:50,896 - mmseg - INFO - Iter [46750/160000] lr: 4.247e-05, eta: 13:42:42, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1302, decode.acc_seg: 94.7833, loss: 0.1302 2023-01-06 04:58:12,349 - mmseg - INFO - Iter [46800/160000] lr: 4.245e-05, eta: 13:42:20, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1412, decode.acc_seg: 94.4892, loss: 0.1412 2023-01-06 04:58:33,381 - mmseg - INFO - Iter [46850/160000] lr: 4.243e-05, eta: 13:41:56, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1334, decode.acc_seg: 94.5911, loss: 0.1334 2023-01-06 04:58:56,710 - mmseg - INFO - Iter [46900/160000] lr: 4.241e-05, eta: 13:41:38, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1312, decode.acc_seg: 94.6741, loss: 0.1312 2023-01-06 04:59:18,714 - mmseg - INFO - Iter [46950/160000] lr: 4.239e-05, eta: 13:41:17, time: 0.441, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1291, decode.acc_seg: 94.8958, loss: 0.1291 2023-01-06 04:59:39,608 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 04:59:39,609 - mmseg - INFO - Iter [47000/160000] lr: 4.238e-05, eta: 13:40:53, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1306, decode.acc_seg: 94.6556, loss: 0.1306 2023-01-06 05:00:00,564 - mmseg - INFO - Iter [47050/160000] lr: 4.236e-05, eta: 13:40:29, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1323, decode.acc_seg: 94.6763, loss: 0.1323 2023-01-06 05:00:22,009 - mmseg - INFO - Iter [47100/160000] lr: 4.234e-05, eta: 13:40:06, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1347, decode.acc_seg: 94.6151, loss: 0.1347 2023-01-06 05:00:43,033 - mmseg - INFO - Iter [47150/160000] lr: 4.232e-05, eta: 13:39:43, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1378, decode.acc_seg: 94.5938, loss: 0.1378 2023-01-06 05:01:05,703 - mmseg - INFO - Iter [47200/160000] lr: 4.230e-05, eta: 13:39:23, time: 0.453, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1376, decode.acc_seg: 94.4990, loss: 0.1376 2023-01-06 05:01:29,274 - mmseg - INFO - Iter [47250/160000] lr: 4.228e-05, eta: 13:39:06, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1260, decode.acc_seg: 94.7946, loss: 0.1260 2023-01-06 05:01:50,945 - mmseg - INFO - Iter [47300/160000] lr: 4.226e-05, eta: 13:38:43, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1289, decode.acc_seg: 94.8023, loss: 0.1289 2023-01-06 05:02:11,909 - mmseg - INFO - Iter [47350/160000] lr: 4.224e-05, eta: 13:38:20, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1257, decode.acc_seg: 94.8008, loss: 0.1257 2023-01-06 05:02:33,768 - mmseg - INFO - Iter [47400/160000] lr: 4.223e-05, eta: 13:37:58, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1345, decode.acc_seg: 94.4866, loss: 0.1345 2023-01-06 05:02:55,126 - mmseg - INFO - Iter [47450/160000] lr: 4.221e-05, eta: 13:37:35, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1398, decode.acc_seg: 94.2521, loss: 0.1398 2023-01-06 05:03:17,288 - mmseg - INFO - Iter [47500/160000] lr: 4.219e-05, eta: 13:37:14, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1365, decode.acc_seg: 94.5248, loss: 0.1365 2023-01-06 05:03:38,284 - mmseg - INFO - Iter [47550/160000] lr: 4.217e-05, eta: 13:36:51, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1252, decode.acc_seg: 94.9223, loss: 0.1252 2023-01-06 05:03:59,608 - mmseg - INFO - Iter [47600/160000] lr: 4.215e-05, eta: 13:36:28, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1509, decode.acc_seg: 93.9340, loss: 0.1509 2023-01-06 05:04:22,909 - mmseg - INFO - Iter [47650/160000] lr: 4.213e-05, eta: 13:36:09, time: 0.466, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1347, decode.acc_seg: 94.5409, loss: 0.1347 2023-01-06 05:04:44,176 - mmseg - INFO - Iter [47700/160000] lr: 4.211e-05, eta: 13:35:46, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1376, decode.acc_seg: 94.4597, loss: 0.1376 2023-01-06 05:05:05,930 - mmseg - INFO - Iter [47750/160000] lr: 4.209e-05, eta: 13:35:24, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1469, decode.acc_seg: 94.2085, loss: 0.1469 2023-01-06 05:05:27,244 - mmseg - INFO - Iter [47800/160000] lr: 4.208e-05, eta: 13:35:02, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1524, decode.acc_seg: 94.1062, loss: 0.1524 2023-01-06 05:05:48,641 - mmseg - INFO - Iter [47850/160000] lr: 4.206e-05, eta: 13:34:39, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1474, decode.acc_seg: 94.1558, loss: 0.1474 2023-01-06 05:06:10,030 - mmseg - INFO - Iter [47900/160000] lr: 4.204e-05, eta: 13:34:16, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1372, decode.acc_seg: 94.6408, loss: 0.1372 2023-01-06 05:06:31,184 - mmseg - INFO - Iter [47950/160000] lr: 4.202e-05, eta: 13:33:53, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1275, decode.acc_seg: 94.7078, loss: 0.1275 2023-01-06 05:06:54,275 - mmseg - INFO - Saving checkpoint at 48000 iterations 2023-01-06 05:06:58,248 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:06:58,248 - mmseg - INFO - Iter [48000/160000] lr: 4.200e-05, eta: 13:33:43, time: 0.541, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1308, decode.acc_seg: 94.6945, loss: 0.1308 2023-01-06 05:07:26,545 - mmseg - INFO - per class results: 2023-01-06 05:07:26,548 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 97.23 | 98.95 | | sidewalk | 78.89 | 87.34 | | building | 90.36 | 95.51 | | wall | 47.58 | 59.13 | | fence | 45.57 | 63.58 | | pole | 54.14 | 61.15 | | traffic light | 56.89 | 66.02 | | traffic sign | 68.72 | 77.64 | | vegetation | 91.25 | 95.79 | | terrain | 57.63 | 66.36 | | sky | 93.99 | 97.7 | | person | 73.89 | 85.0 | | rider | 48.36 | 60.54 | | car | 92.17 | 97.16 | | truck | 43.73 | 49.85 | | bus | 58.64 | 77.3 | | train | 48.69 | 69.03 | | motorcycle | 35.97 | 42.64 | | bicycle | 68.35 | 85.07 | +---------------+-------+-------+ 2023-01-06 05:07:26,548 - mmseg - INFO - Summary: 2023-01-06 05:07:26,548 - mmseg - INFO - +-------+------+-------+ | aAcc | mIoU | mAcc | +-------+------+-------+ | 94.57 | 65.9 | 75.57 | +-------+------+-------+ 2023-01-06 05:07:26,549 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:07:26,549 - mmseg - INFO - Iter(val) [63] aAcc: 0.9457, mIoU: 0.6590, mAcc: 0.7557, IoU.road: 0.9723, IoU.sidewalk: 0.7889, IoU.building: 0.9036, IoU.wall: 0.4758, IoU.fence: 0.4557, IoU.pole: 0.5414, IoU.traffic light: 0.5689, IoU.traffic sign: 0.6872, IoU.vegetation: 0.9125, IoU.terrain: 0.5763, IoU.sky: 0.9399, IoU.person: 0.7389, IoU.rider: 0.4836, IoU.car: 0.9217, IoU.truck: 0.4373, IoU.bus: 0.5864, IoU.train: 0.4869, IoU.motorcycle: 0.3597, IoU.bicycle: 0.6835, Acc.road: 0.9895, Acc.sidewalk: 0.8734, Acc.building: 0.9551, Acc.wall: 0.5913, Acc.fence: 0.6358, Acc.pole: 0.6115, Acc.traffic light: 0.6602, Acc.traffic sign: 0.7764, Acc.vegetation: 0.9579, Acc.terrain: 0.6636, Acc.sky: 0.9770, Acc.person: 0.8500, Acc.rider: 0.6054, Acc.car: 0.9716, Acc.truck: 0.4985, Acc.bus: 0.7730, Acc.train: 0.6903, Acc.motorcycle: 0.4264, Acc.bicycle: 0.8507 2023-01-06 05:07:47,603 - mmseg - INFO - Iter [48050/160000] lr: 4.198e-05, eta: 13:34:26, time: 0.987, data_time: 0.577, memory: 9591, decode.loss_ce: 0.1318, decode.acc_seg: 94.6616, loss: 0.1318 2023-01-06 05:08:08,747 - mmseg - INFO - Iter [48100/160000] lr: 4.196e-05, eta: 13:34:02, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1323, decode.acc_seg: 94.7039, loss: 0.1323 2023-01-06 05:08:30,227 - mmseg - INFO - Iter [48150/160000] lr: 4.194e-05, eta: 13:33:40, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1380, decode.acc_seg: 94.4245, loss: 0.1380 2023-01-06 05:08:51,342 - mmseg - INFO - Iter [48200/160000] lr: 4.193e-05, eta: 13:33:16, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1417, decode.acc_seg: 94.3282, loss: 0.1417 2023-01-06 05:09:12,363 - mmseg - INFO - Iter [48250/160000] lr: 4.191e-05, eta: 13:32:53, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1308, decode.acc_seg: 94.6146, loss: 0.1308 2023-01-06 05:09:33,502 - mmseg - INFO - Iter [48300/160000] lr: 4.189e-05, eta: 13:32:29, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1265, decode.acc_seg: 94.7469, loss: 0.1265 2023-01-06 05:09:54,826 - mmseg - INFO - Iter [48350/160000] lr: 4.187e-05, eta: 13:32:06, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1254, decode.acc_seg: 94.8033, loss: 0.1254 2023-01-06 05:10:18,724 - mmseg - INFO - Iter [48400/160000] lr: 4.185e-05, eta: 13:31:49, time: 0.478, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1332, decode.acc_seg: 94.5500, loss: 0.1332 2023-01-06 05:10:39,849 - mmseg - INFO - Iter [48450/160000] lr: 4.183e-05, eta: 13:31:26, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1317, decode.acc_seg: 94.5669, loss: 0.1317 2023-01-06 05:11:01,716 - mmseg - INFO - Iter [48500/160000] lr: 4.181e-05, eta: 13:31:04, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1252, decode.acc_seg: 94.9962, loss: 0.1252 2023-01-06 05:11:23,772 - mmseg - INFO - Iter [48550/160000] lr: 4.179e-05, eta: 13:30:43, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1350, decode.acc_seg: 94.6178, loss: 0.1350 2023-01-06 05:11:45,213 - mmseg - INFO - Iter [48600/160000] lr: 4.178e-05, eta: 13:30:20, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1319, decode.acc_seg: 94.6866, loss: 0.1319 2023-01-06 05:12:06,595 - mmseg - INFO - Iter [48650/160000] lr: 4.176e-05, eta: 13:29:57, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1257, decode.acc_seg: 94.8516, loss: 0.1257 2023-01-06 05:12:27,804 - mmseg - INFO - Iter [48700/160000] lr: 4.174e-05, eta: 13:29:34, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1347, decode.acc_seg: 94.5897, loss: 0.1347 2023-01-06 05:12:51,096 - mmseg - INFO - Iter [48750/160000] lr: 4.172e-05, eta: 13:29:16, time: 0.467, data_time: 0.058, memory: 9591, decode.loss_ce: 0.1343, decode.acc_seg: 94.5438, loss: 0.1343 2023-01-06 05:13:12,115 - mmseg - INFO - Iter [48800/160000] lr: 4.170e-05, eta: 13:28:52, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1174, decode.acc_seg: 94.9882, loss: 0.1174 2023-01-06 05:13:34,679 - mmseg - INFO - Iter [48850/160000] lr: 4.168e-05, eta: 13:28:32, time: 0.451, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1376, decode.acc_seg: 94.6647, loss: 0.1376 2023-01-06 05:13:55,786 - mmseg - INFO - Iter [48900/160000] lr: 4.166e-05, eta: 13:28:08, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1312, decode.acc_seg: 94.5586, loss: 0.1312 2023-01-06 05:14:16,742 - mmseg - INFO - Iter [48950/160000] lr: 4.164e-05, eta: 13:27:44, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1291, decode.acc_seg: 94.6910, loss: 0.1291 2023-01-06 05:14:38,403 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:14:38,403 - mmseg - INFO - Iter [49000/160000] lr: 4.163e-05, eta: 13:27:22, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1454, decode.acc_seg: 94.2046, loss: 0.1454 2023-01-06 05:14:59,965 - mmseg - INFO - Iter [49050/160000] lr: 4.161e-05, eta: 13:27:00, time: 0.431, data_time: 0.010, memory: 9591, decode.loss_ce: 0.1344, decode.acc_seg: 94.3821, loss: 0.1344 2023-01-06 05:15:21,164 - mmseg - INFO - Iter [49100/160000] lr: 4.159e-05, eta: 13:26:37, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1392, decode.acc_seg: 94.4640, loss: 0.1392 2023-01-06 05:15:44,610 - mmseg - INFO - Iter [49150/160000] lr: 4.157e-05, eta: 13:26:19, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1316, decode.acc_seg: 94.6838, loss: 0.1316 2023-01-06 05:16:05,855 - mmseg - INFO - Iter [49200/160000] lr: 4.155e-05, eta: 13:25:55, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1273, decode.acc_seg: 94.6694, loss: 0.1273 2023-01-06 05:16:26,761 - mmseg - INFO - Iter [49250/160000] lr: 4.153e-05, eta: 13:25:32, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1238, decode.acc_seg: 94.9000, loss: 0.1238 2023-01-06 05:16:48,148 - mmseg - INFO - Iter [49300/160000] lr: 4.151e-05, eta: 13:25:09, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1301, decode.acc_seg: 94.7413, loss: 0.1301 2023-01-06 05:17:09,117 - mmseg - INFO - Iter [49350/160000] lr: 4.149e-05, eta: 13:24:45, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1314, decode.acc_seg: 94.6690, loss: 0.1314 2023-01-06 05:17:30,238 - mmseg - INFO - Iter [49400/160000] lr: 4.148e-05, eta: 13:24:22, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1348, decode.acc_seg: 94.4112, loss: 0.1348 2023-01-06 05:17:52,079 - mmseg - INFO - Iter [49450/160000] lr: 4.146e-05, eta: 13:24:00, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1352, decode.acc_seg: 94.4718, loss: 0.1352 2023-01-06 05:18:15,421 - mmseg - INFO - Iter [49500/160000] lr: 4.144e-05, eta: 13:23:41, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1430, decode.acc_seg: 94.1503, loss: 0.1430 2023-01-06 05:18:36,329 - mmseg - INFO - Iter [49550/160000] lr: 4.142e-05, eta: 13:23:18, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1528, decode.acc_seg: 93.8783, loss: 0.1528 2023-01-06 05:18:57,453 - mmseg - INFO - Iter [49600/160000] lr: 4.140e-05, eta: 13:22:54, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1495, decode.acc_seg: 94.3255, loss: 0.1495 2023-01-06 05:19:18,858 - mmseg - INFO - Iter [49650/160000] lr: 4.138e-05, eta: 13:22:31, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1512, decode.acc_seg: 93.9976, loss: 0.1512 2023-01-06 05:19:39,962 - mmseg - INFO - Iter [49700/160000] lr: 4.136e-05, eta: 13:22:08, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1364, decode.acc_seg: 94.5200, loss: 0.1364 2023-01-06 05:20:01,018 - mmseg - INFO - Iter [49750/160000] lr: 4.134e-05, eta: 13:21:45, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1301, decode.acc_seg: 94.7691, loss: 0.1301 2023-01-06 05:20:22,243 - mmseg - INFO - Iter [49800/160000] lr: 4.133e-05, eta: 13:21:21, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1344, decode.acc_seg: 94.5563, loss: 0.1344 2023-01-06 05:20:45,891 - mmseg - INFO - Iter [49850/160000] lr: 4.131e-05, eta: 13:21:04, time: 0.473, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1278, decode.acc_seg: 94.8946, loss: 0.1278 2023-01-06 05:21:06,719 - mmseg - INFO - Iter [49900/160000] lr: 4.129e-05, eta: 13:20:40, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1179, decode.acc_seg: 95.2031, loss: 0.1179 2023-01-06 05:21:28,194 - mmseg - INFO - Iter [49950/160000] lr: 4.127e-05, eta: 13:20:17, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1321, decode.acc_seg: 94.7975, loss: 0.1321 2023-01-06 05:21:49,525 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:21:49,526 - mmseg - INFO - Iter [50000/160000] lr: 4.125e-05, eta: 13:19:54, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1392, decode.acc_seg: 94.4502, loss: 0.1392 2023-01-06 05:22:10,640 - mmseg - INFO - Iter [50050/160000] lr: 4.123e-05, eta: 13:19:31, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1336, decode.acc_seg: 94.6704, loss: 0.1336 2023-01-06 05:22:32,659 - mmseg - INFO - Iter [50100/160000] lr: 4.121e-05, eta: 13:19:09, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1313, decode.acc_seg: 94.7813, loss: 0.1313 2023-01-06 05:22:53,653 - mmseg - INFO - Iter [50150/160000] lr: 4.119e-05, eta: 13:18:46, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1289, decode.acc_seg: 94.8384, loss: 0.1289 2023-01-06 05:23:15,054 - mmseg - INFO - Iter [50200/160000] lr: 4.118e-05, eta: 13:18:23, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1295, decode.acc_seg: 94.7262, loss: 0.1295 2023-01-06 05:23:38,454 - mmseg - INFO - Iter [50250/160000] lr: 4.116e-05, eta: 13:18:05, time: 0.468, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1374, decode.acc_seg: 94.4536, loss: 0.1374 2023-01-06 05:23:59,565 - mmseg - INFO - Iter [50300/160000] lr: 4.114e-05, eta: 13:17:41, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1241, decode.acc_seg: 95.1339, loss: 0.1241 2023-01-06 05:24:20,683 - mmseg - INFO - Iter [50350/160000] lr: 4.112e-05, eta: 13:17:18, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1353, decode.acc_seg: 94.4267, loss: 0.1353 2023-01-06 05:24:42,402 - mmseg - INFO - Iter [50400/160000] lr: 4.110e-05, eta: 13:16:56, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1300, decode.acc_seg: 94.7870, loss: 0.1300 2023-01-06 05:25:04,236 - mmseg - INFO - Iter [50450/160000] lr: 4.108e-05, eta: 13:16:34, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1339, decode.acc_seg: 94.7601, loss: 0.1339 2023-01-06 05:25:25,484 - mmseg - INFO - Iter [50500/160000] lr: 4.106e-05, eta: 13:16:11, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1317, decode.acc_seg: 94.6861, loss: 0.1317 2023-01-06 05:25:47,011 - mmseg - INFO - Iter [50550/160000] lr: 4.104e-05, eta: 13:15:49, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1334, decode.acc_seg: 94.6565, loss: 0.1334 2023-01-06 05:26:10,996 - mmseg - INFO - Iter [50600/160000] lr: 4.103e-05, eta: 13:15:32, time: 0.479, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1270, decode.acc_seg: 94.8383, loss: 0.1270 2023-01-06 05:26:32,513 - mmseg - INFO - Iter [50650/160000] lr: 4.101e-05, eta: 13:15:09, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1344, decode.acc_seg: 94.5495, loss: 0.1344 2023-01-06 05:26:53,680 - mmseg - INFO - Iter [50700/160000] lr: 4.099e-05, eta: 13:14:46, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1331, decode.acc_seg: 94.8219, loss: 0.1331 2023-01-06 05:27:15,247 - mmseg - INFO - Iter [50750/160000] lr: 4.097e-05, eta: 13:14:24, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1299, decode.acc_seg: 94.8875, loss: 0.1299 2023-01-06 05:27:36,149 - mmseg - INFO - Iter [50800/160000] lr: 4.095e-05, eta: 13:14:00, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1267, decode.acc_seg: 94.9944, loss: 0.1267 2023-01-06 05:27:58,098 - mmseg - INFO - Iter [50850/160000] lr: 4.093e-05, eta: 13:13:38, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1329, decode.acc_seg: 94.6071, loss: 0.1329 2023-01-06 05:28:20,104 - mmseg - INFO - Iter [50900/160000] lr: 4.091e-05, eta: 13:13:17, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1283, decode.acc_seg: 94.6309, loss: 0.1283 2023-01-06 05:28:41,519 - mmseg - INFO - Iter [50950/160000] lr: 4.089e-05, eta: 13:12:54, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1311, decode.acc_seg: 94.5910, loss: 0.1311 2023-01-06 05:29:05,658 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:29:05,658 - mmseg - INFO - Iter [51000/160000] lr: 4.088e-05, eta: 13:12:37, time: 0.483, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1276, decode.acc_seg: 94.6076, loss: 0.1276 2023-01-06 05:29:26,626 - mmseg - INFO - Iter [51050/160000] lr: 4.086e-05, eta: 13:12:14, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1298, decode.acc_seg: 94.8312, loss: 0.1298 2023-01-06 05:29:47,696 - mmseg - INFO - Iter [51100/160000] lr: 4.084e-05, eta: 13:11:50, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1176, decode.acc_seg: 95.1781, loss: 0.1176 2023-01-06 05:30:08,427 - mmseg - INFO - Iter [51150/160000] lr: 4.082e-05, eta: 13:11:26, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1369, decode.acc_seg: 94.6439, loss: 0.1369 2023-01-06 05:30:29,608 - mmseg - INFO - Iter [51200/160000] lr: 4.080e-05, eta: 13:11:03, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1272, decode.acc_seg: 94.9545, loss: 0.1272 2023-01-06 05:30:51,263 - mmseg - INFO - Iter [51250/160000] lr: 4.078e-05, eta: 13:10:41, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1191, decode.acc_seg: 95.1317, loss: 0.1191 2023-01-06 05:31:13,238 - mmseg - INFO - Iter [51300/160000] lr: 4.076e-05, eta: 13:10:20, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1204, decode.acc_seg: 94.9895, loss: 0.1204 2023-01-06 05:31:36,498 - mmseg - INFO - Iter [51350/160000] lr: 4.074e-05, eta: 13:10:01, time: 0.465, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1269, decode.acc_seg: 94.7450, loss: 0.1269 2023-01-06 05:31:57,887 - mmseg - INFO - Iter [51400/160000] lr: 4.073e-05, eta: 13:09:38, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1279, decode.acc_seg: 94.8648, loss: 0.1279 2023-01-06 05:32:19,640 - mmseg - INFO - Iter [51450/160000] lr: 4.071e-05, eta: 13:09:16, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1196, decode.acc_seg: 95.0541, loss: 0.1196 2023-01-06 05:32:40,925 - mmseg - INFO - Iter [51500/160000] lr: 4.069e-05, eta: 13:08:53, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1259, decode.acc_seg: 94.8662, loss: 0.1259 2023-01-06 05:33:03,767 - mmseg - INFO - Iter [51550/160000] lr: 4.067e-05, eta: 13:08:34, time: 0.457, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1290, decode.acc_seg: 94.7263, loss: 0.1290 2023-01-06 05:33:25,437 - mmseg - INFO - Iter [51600/160000] lr: 4.065e-05, eta: 13:08:11, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1300, decode.acc_seg: 94.5935, loss: 0.1300 2023-01-06 05:33:46,329 - mmseg - INFO - Iter [51650/160000] lr: 4.063e-05, eta: 13:07:48, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1290, decode.acc_seg: 94.8063, loss: 0.1290 2023-01-06 05:34:07,267 - mmseg - INFO - Iter [51700/160000] lr: 4.061e-05, eta: 13:07:24, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1278, decode.acc_seg: 94.8620, loss: 0.1278 2023-01-06 05:34:31,000 - mmseg - INFO - Iter [51750/160000] lr: 4.059e-05, eta: 13:07:06, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1239, decode.acc_seg: 95.0238, loss: 0.1239 2023-01-06 05:34:52,384 - mmseg - INFO - Iter [51800/160000] lr: 4.058e-05, eta: 13:06:44, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1264, decode.acc_seg: 94.9667, loss: 0.1264 2023-01-06 05:35:13,424 - mmseg - INFO - Iter [51850/160000] lr: 4.056e-05, eta: 13:06:20, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1308, decode.acc_seg: 94.6608, loss: 0.1308 2023-01-06 05:35:34,919 - mmseg - INFO - Iter [51900/160000] lr: 4.054e-05, eta: 13:05:58, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1320, decode.acc_seg: 94.9048, loss: 0.1320 2023-01-06 05:35:56,470 - mmseg - INFO - Iter [51950/160000] lr: 4.052e-05, eta: 13:05:35, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1394, decode.acc_seg: 94.4871, loss: 0.1394 2023-01-06 05:36:18,106 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:36:18,106 - mmseg - INFO - Iter [52000/160000] lr: 4.050e-05, eta: 13:05:13, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1317, decode.acc_seg: 94.5139, loss: 0.1317 2023-01-06 05:36:39,380 - mmseg - INFO - Iter [52050/160000] lr: 4.048e-05, eta: 13:04:50, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1488, decode.acc_seg: 94.3161, loss: 0.1488 2023-01-06 05:37:02,430 - mmseg - INFO - Iter [52100/160000] lr: 4.046e-05, eta: 13:04:31, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1190, decode.acc_seg: 95.2524, loss: 0.1190 2023-01-06 05:37:23,301 - mmseg - INFO - Iter [52150/160000] lr: 4.044e-05, eta: 13:04:07, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1223, decode.acc_seg: 95.0323, loss: 0.1223 2023-01-06 05:37:44,983 - mmseg - INFO - Iter [52200/160000] lr: 4.043e-05, eta: 13:03:45, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1287, decode.acc_seg: 94.7019, loss: 0.1287 2023-01-06 05:38:07,068 - mmseg - INFO - Iter [52250/160000] lr: 4.041e-05, eta: 13:03:24, time: 0.442, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1306, decode.acc_seg: 94.4610, loss: 0.1306 2023-01-06 05:38:28,959 - mmseg - INFO - Iter [52300/160000] lr: 4.039e-05, eta: 13:03:02, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1246, decode.acc_seg: 95.0023, loss: 0.1246 2023-01-06 05:38:50,195 - mmseg - INFO - Iter [52350/160000] lr: 4.037e-05, eta: 13:02:39, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1244, decode.acc_seg: 95.0114, loss: 0.1244 2023-01-06 05:39:12,334 - mmseg - INFO - Iter [52400/160000] lr: 4.035e-05, eta: 13:02:18, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1417, decode.acc_seg: 94.2615, loss: 0.1417 2023-01-06 05:39:33,801 - mmseg - INFO - Iter [52450/160000] lr: 4.033e-05, eta: 13:01:55, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1337, decode.acc_seg: 94.4967, loss: 0.1337 2023-01-06 05:39:57,412 - mmseg - INFO - Iter [52500/160000] lr: 4.031e-05, eta: 13:01:37, time: 0.472, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1278, decode.acc_seg: 94.8832, loss: 0.1278 2023-01-06 05:40:18,808 - mmseg - INFO - Iter [52550/160000] lr: 4.029e-05, eta: 13:01:15, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1317, decode.acc_seg: 94.6498, loss: 0.1317 2023-01-06 05:40:39,751 - mmseg - INFO - Iter [52600/160000] lr: 4.028e-05, eta: 13:00:51, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1263, decode.acc_seg: 94.8947, loss: 0.1263 2023-01-06 05:41:00,742 - mmseg - INFO - Iter [52650/160000] lr: 4.026e-05, eta: 13:00:28, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1341, decode.acc_seg: 94.5991, loss: 0.1341 2023-01-06 05:41:22,138 - mmseg - INFO - Iter [52700/160000] lr: 4.024e-05, eta: 13:00:05, time: 0.427, data_time: 0.015, memory: 9591, decode.loss_ce: 0.1354, decode.acc_seg: 94.5471, loss: 0.1354 2023-01-06 05:41:43,118 - mmseg - INFO - Iter [52750/160000] lr: 4.022e-05, eta: 12:59:42, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1362, decode.acc_seg: 94.6540, loss: 0.1362 2023-01-06 05:42:04,121 - mmseg - INFO - Iter [52800/160000] lr: 4.020e-05, eta: 12:59:18, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1206, decode.acc_seg: 95.0208, loss: 0.1206 2023-01-06 05:42:27,873 - mmseg - INFO - Iter [52850/160000] lr: 4.018e-05, eta: 12:59:00, time: 0.475, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1339, decode.acc_seg: 94.6578, loss: 0.1339 2023-01-06 05:42:48,760 - mmseg - INFO - Iter [52900/160000] lr: 4.016e-05, eta: 12:58:37, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1209, decode.acc_seg: 95.1071, loss: 0.1209 2023-01-06 05:43:09,674 - mmseg - INFO - Iter [52950/160000] lr: 4.014e-05, eta: 12:58:13, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1225, decode.acc_seg: 94.9531, loss: 0.1225 2023-01-06 05:43:30,995 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:43:30,996 - mmseg - INFO - Iter [53000/160000] lr: 4.013e-05, eta: 12:57:50, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1140, decode.acc_seg: 95.3824, loss: 0.1140 2023-01-06 05:43:52,190 - mmseg - INFO - Iter [53050/160000] lr: 4.011e-05, eta: 12:57:27, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1201, decode.acc_seg: 95.0990, loss: 0.1201 2023-01-06 05:44:14,076 - mmseg - INFO - Iter [53100/160000] lr: 4.009e-05, eta: 12:57:05, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1250, decode.acc_seg: 94.9941, loss: 0.1250 2023-01-06 05:44:34,891 - mmseg - INFO - Iter [53150/160000] lr: 4.007e-05, eta: 12:56:42, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1267, decode.acc_seg: 94.7974, loss: 0.1267 2023-01-06 05:44:58,353 - mmseg - INFO - Iter [53200/160000] lr: 4.005e-05, eta: 12:56:23, time: 0.469, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1324, decode.acc_seg: 94.6151, loss: 0.1324 2023-01-06 05:45:19,120 - mmseg - INFO - Iter [53250/160000] lr: 4.003e-05, eta: 12:55:59, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1206, decode.acc_seg: 94.9344, loss: 0.1206 2023-01-06 05:45:40,775 - mmseg - INFO - Iter [53300/160000] lr: 4.001e-05, eta: 12:55:37, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1208, decode.acc_seg: 95.0155, loss: 0.1208 2023-01-06 05:46:02,070 - mmseg - INFO - Iter [53350/160000] lr: 3.999e-05, eta: 12:55:14, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1258, decode.acc_seg: 94.9528, loss: 0.1258 2023-01-06 05:46:24,031 - mmseg - INFO - Iter [53400/160000] lr: 3.998e-05, eta: 12:54:53, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1217, decode.acc_seg: 94.9256, loss: 0.1217 2023-01-06 05:46:44,823 - mmseg - INFO - Iter [53450/160000] lr: 3.996e-05, eta: 12:54:29, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1320, decode.acc_seg: 94.5738, loss: 0.1320 2023-01-06 05:47:06,078 - mmseg - INFO - Iter [53500/160000] lr: 3.994e-05, eta: 12:54:06, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1247, decode.acc_seg: 94.9296, loss: 0.1247 2023-01-06 05:47:27,548 - mmseg - INFO - Iter [53550/160000] lr: 3.992e-05, eta: 12:53:44, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1316, decode.acc_seg: 94.6504, loss: 0.1316 2023-01-06 05:47:51,309 - mmseg - INFO - Iter [53600/160000] lr: 3.990e-05, eta: 12:53:26, time: 0.475, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1252, decode.acc_seg: 94.8690, loss: 0.1252 2023-01-06 05:48:12,473 - mmseg - INFO - Iter [53650/160000] lr: 3.988e-05, eta: 12:53:03, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1233, decode.acc_seg: 95.0658, loss: 0.1233 2023-01-06 05:48:34,503 - mmseg - INFO - Iter [53700/160000] lr: 3.986e-05, eta: 12:52:41, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1277, decode.acc_seg: 94.7507, loss: 0.1277 2023-01-06 05:48:55,954 - mmseg - INFO - Iter [53750/160000] lr: 3.984e-05, eta: 12:52:19, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1300, decode.acc_seg: 94.8339, loss: 0.1300 2023-01-06 05:49:17,900 - mmseg - INFO - Iter [53800/160000] lr: 3.983e-05, eta: 12:51:57, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1272, decode.acc_seg: 94.8705, loss: 0.1272 2023-01-06 05:49:39,230 - mmseg - INFO - Iter [53850/160000] lr: 3.981e-05, eta: 12:51:34, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1237, decode.acc_seg: 94.8632, loss: 0.1237 2023-01-06 05:50:00,595 - mmseg - INFO - Iter [53900/160000] lr: 3.979e-05, eta: 12:51:12, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1254, decode.acc_seg: 94.9843, loss: 0.1254 2023-01-06 05:50:24,610 - mmseg - INFO - Iter [53950/160000] lr: 3.977e-05, eta: 12:50:54, time: 0.481, data_time: 0.058, memory: 9591, decode.loss_ce: 0.1296, decode.acc_seg: 94.7836, loss: 0.1296 2023-01-06 05:50:45,363 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:50:45,364 - mmseg - INFO - Iter [54000/160000] lr: 3.975e-05, eta: 12:50:30, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1274, decode.acc_seg: 94.7918, loss: 0.1274 2023-01-06 05:51:06,280 - mmseg - INFO - Iter [54050/160000] lr: 3.973e-05, eta: 12:50:07, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1239, decode.acc_seg: 94.9773, loss: 0.1239 2023-01-06 05:51:27,613 - mmseg - INFO - Iter [54100/160000] lr: 3.971e-05, eta: 12:49:44, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1477, decode.acc_seg: 94.3290, loss: 0.1477 2023-01-06 05:51:48,982 - mmseg - INFO - Iter [54150/160000] lr: 3.969e-05, eta: 12:49:21, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1359, decode.acc_seg: 94.3076, loss: 0.1359 2023-01-06 05:52:10,327 - mmseg - INFO - Iter [54200/160000] lr: 3.968e-05, eta: 12:48:59, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1304, decode.acc_seg: 94.8333, loss: 0.1304 2023-01-06 05:52:31,324 - mmseg - INFO - Iter [54250/160000] lr: 3.966e-05, eta: 12:48:35, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1320, decode.acc_seg: 94.6693, loss: 0.1320 2023-01-06 05:52:52,299 - mmseg - INFO - Iter [54300/160000] lr: 3.964e-05, eta: 12:48:12, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1242, decode.acc_seg: 94.8594, loss: 0.1242 2023-01-06 05:53:16,092 - mmseg - INFO - Iter [54350/160000] lr: 3.962e-05, eta: 12:47:54, time: 0.476, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1334, decode.acc_seg: 94.5723, loss: 0.1334 2023-01-06 05:53:37,643 - mmseg - INFO - Iter [54400/160000] lr: 3.960e-05, eta: 12:47:32, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1286, decode.acc_seg: 94.8097, loss: 0.1286 2023-01-06 05:53:59,614 - mmseg - INFO - Iter [54450/160000] lr: 3.958e-05, eta: 12:47:10, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1226, decode.acc_seg: 95.0031, loss: 0.1226 2023-01-06 05:54:20,560 - mmseg - INFO - Iter [54500/160000] lr: 3.956e-05, eta: 12:46:47, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1241, decode.acc_seg: 94.9577, loss: 0.1241 2023-01-06 05:54:41,524 - mmseg - INFO - Iter [54550/160000] lr: 3.954e-05, eta: 12:46:23, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1327, decode.acc_seg: 94.7089, loss: 0.1327 2023-01-06 05:55:03,276 - mmseg - INFO - Iter [54600/160000] lr: 3.953e-05, eta: 12:46:01, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1255, decode.acc_seg: 94.9490, loss: 0.1255 2023-01-06 05:55:24,964 - mmseg - INFO - Iter [54650/160000] lr: 3.951e-05, eta: 12:45:39, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1217, decode.acc_seg: 94.9741, loss: 0.1217 2023-01-06 05:55:49,082 - mmseg - INFO - Iter [54700/160000] lr: 3.949e-05, eta: 12:45:22, time: 0.483, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1410, decode.acc_seg: 94.2000, loss: 0.1410 2023-01-06 05:56:09,859 - mmseg - INFO - Iter [54750/160000] lr: 3.947e-05, eta: 12:44:58, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1152, decode.acc_seg: 95.1600, loss: 0.1152 2023-01-06 05:56:31,739 - mmseg - INFO - Iter [54800/160000] lr: 3.945e-05, eta: 12:44:37, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1291, decode.acc_seg: 94.7720, loss: 0.1291 2023-01-06 05:56:53,063 - mmseg - INFO - Iter [54850/160000] lr: 3.943e-05, eta: 12:44:14, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1283, decode.acc_seg: 94.7121, loss: 0.1283 2023-01-06 05:57:14,007 - mmseg - INFO - Iter [54900/160000] lr: 3.941e-05, eta: 12:43:50, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1341, decode.acc_seg: 94.7384, loss: 0.1341 2023-01-06 05:57:34,829 - mmseg - INFO - Iter [54950/160000] lr: 3.939e-05, eta: 12:43:27, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1233, decode.acc_seg: 94.8651, loss: 0.1233 2023-01-06 05:57:56,712 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 05:57:56,713 - mmseg - INFO - Iter [55000/160000] lr: 3.938e-05, eta: 12:43:05, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1266, decode.acc_seg: 94.9588, loss: 0.1266 2023-01-06 05:58:17,910 - mmseg - INFO - Iter [55050/160000] lr: 3.936e-05, eta: 12:42:42, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1232, decode.acc_seg: 94.9671, loss: 0.1232 2023-01-06 05:58:41,380 - mmseg - INFO - Iter [55100/160000] lr: 3.934e-05, eta: 12:42:23, time: 0.469, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1190, decode.acc_seg: 95.1739, loss: 0.1190 2023-01-06 05:59:03,447 - mmseg - INFO - Iter [55150/160000] lr: 3.932e-05, eta: 12:42:02, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1379, decode.acc_seg: 94.5106, loss: 0.1379 2023-01-06 05:59:24,937 - mmseg - INFO - Iter [55200/160000] lr: 3.930e-05, eta: 12:41:40, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1208, decode.acc_seg: 95.0920, loss: 0.1208 2023-01-06 05:59:46,000 - mmseg - INFO - Iter [55250/160000] lr: 3.928e-05, eta: 12:41:17, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.2552, loss: 0.1160 2023-01-06 06:00:07,374 - mmseg - INFO - Iter [55300/160000] lr: 3.926e-05, eta: 12:40:54, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1215, decode.acc_seg: 95.0065, loss: 0.1215 2023-01-06 06:00:28,240 - mmseg - INFO - Iter [55350/160000] lr: 3.924e-05, eta: 12:40:30, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1185, decode.acc_seg: 95.1829, loss: 0.1185 2023-01-06 06:00:50,114 - mmseg - INFO - Iter [55400/160000] lr: 3.923e-05, eta: 12:40:09, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1323, decode.acc_seg: 94.6935, loss: 0.1323 2023-01-06 06:01:13,378 - mmseg - INFO - Iter [55450/160000] lr: 3.921e-05, eta: 12:39:50, time: 0.466, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1260, decode.acc_seg: 94.8508, loss: 0.1260 2023-01-06 06:01:34,665 - mmseg - INFO - Iter [55500/160000] lr: 3.919e-05, eta: 12:39:27, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1315, decode.acc_seg: 94.7034, loss: 0.1315 2023-01-06 06:01:55,887 - mmseg - INFO - Iter [55550/160000] lr: 3.917e-05, eta: 12:39:04, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1309, decode.acc_seg: 94.6361, loss: 0.1309 2023-01-06 06:02:17,000 - mmseg - INFO - Iter [55600/160000] lr: 3.915e-05, eta: 12:38:41, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1290, decode.acc_seg: 94.7147, loss: 0.1290 2023-01-06 06:02:38,144 - mmseg - INFO - Iter [55650/160000] lr: 3.913e-05, eta: 12:38:18, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1254, decode.acc_seg: 94.7826, loss: 0.1254 2023-01-06 06:02:59,861 - mmseg - INFO - Iter [55700/160000] lr: 3.911e-05, eta: 12:37:56, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1371, decode.acc_seg: 94.5642, loss: 0.1371 2023-01-06 06:03:21,473 - mmseg - INFO - Iter [55750/160000] lr: 3.909e-05, eta: 12:37:34, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1281, decode.acc_seg: 94.9299, loss: 0.1281 2023-01-06 06:03:43,297 - mmseg - INFO - Iter [55800/160000] lr: 3.908e-05, eta: 12:37:12, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1205, decode.acc_seg: 95.0410, loss: 0.1205 2023-01-06 06:04:06,875 - mmseg - INFO - Iter [55850/160000] lr: 3.906e-05, eta: 12:36:53, time: 0.471, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1148, decode.acc_seg: 95.2345, loss: 0.1148 2023-01-06 06:04:28,139 - mmseg - INFO - Iter [55900/160000] lr: 3.904e-05, eta: 12:36:31, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1188, decode.acc_seg: 95.1866, loss: 0.1188 2023-01-06 06:04:48,966 - mmseg - INFO - Iter [55950/160000] lr: 3.902e-05, eta: 12:36:07, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1349, decode.acc_seg: 94.7818, loss: 0.1349 2023-01-06 06:05:09,704 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 06:05:09,705 - mmseg - INFO - Iter [56000/160000] lr: 3.900e-05, eta: 12:35:43, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1352, decode.acc_seg: 94.6514, loss: 0.1352 2023-01-06 06:05:30,822 - mmseg - INFO - Iter [56050/160000] lr: 3.898e-05, eta: 12:35:20, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1168, decode.acc_seg: 95.0311, loss: 0.1168 2023-01-06 06:05:52,783 - mmseg - INFO - Iter [56100/160000] lr: 3.896e-05, eta: 12:34:59, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1280, decode.acc_seg: 94.6695, loss: 0.1280 2023-01-06 06:06:14,480 - mmseg - INFO - Iter [56150/160000] lr: 3.894e-05, eta: 12:34:37, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1317, decode.acc_seg: 94.6521, loss: 0.1317 2023-01-06 06:06:38,681 - mmseg - INFO - Iter [56200/160000] lr: 3.893e-05, eta: 12:34:19, time: 0.483, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1206, decode.acc_seg: 95.0446, loss: 0.1206 2023-01-06 06:06:59,591 - mmseg - INFO - Iter [56250/160000] lr: 3.891e-05, eta: 12:33:56, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1329, decode.acc_seg: 94.6910, loss: 0.1329 2023-01-06 06:07:21,252 - mmseg - INFO - Iter [56300/160000] lr: 3.889e-05, eta: 12:33:34, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1165, decode.acc_seg: 95.2195, loss: 0.1165 2023-01-06 06:07:42,103 - mmseg - INFO - Iter [56350/160000] lr: 3.887e-05, eta: 12:33:10, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1298, decode.acc_seg: 94.7353, loss: 0.1298 2023-01-06 06:08:02,934 - mmseg - INFO - Iter [56400/160000] lr: 3.885e-05, eta: 12:32:47, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1238, decode.acc_seg: 94.9056, loss: 0.1238 2023-01-06 06:08:24,584 - mmseg - INFO - Iter [56450/160000] lr: 3.883e-05, eta: 12:32:25, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1346, decode.acc_seg: 94.5546, loss: 0.1346 2023-01-06 06:08:46,286 - mmseg - INFO - Iter [56500/160000] lr: 3.881e-05, eta: 12:32:03, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1508, decode.acc_seg: 93.9006, loss: 0.1508 2023-01-06 06:09:09,455 - mmseg - INFO - Iter [56550/160000] lr: 3.879e-05, eta: 12:31:43, time: 0.464, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1252, decode.acc_seg: 94.9907, loss: 0.1252 2023-01-06 06:09:30,888 - mmseg - INFO - Iter [56600/160000] lr: 3.878e-05, eta: 12:31:21, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1228, decode.acc_seg: 94.8813, loss: 0.1228 2023-01-06 06:09:52,324 - mmseg - INFO - Iter [56650/160000] lr: 3.876e-05, eta: 12:30:58, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1295, decode.acc_seg: 94.6850, loss: 0.1295 2023-01-06 06:10:13,574 - mmseg - INFO - Iter [56700/160000] lr: 3.874e-05, eta: 12:30:36, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1290, decode.acc_seg: 94.9303, loss: 0.1290 2023-01-06 06:10:34,804 - mmseg - INFO - Iter [56750/160000] lr: 3.872e-05, eta: 12:30:13, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1211, decode.acc_seg: 95.0193, loss: 0.1211 2023-01-06 06:10:55,703 - mmseg - INFO - Iter [56800/160000] lr: 3.870e-05, eta: 12:29:49, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1158, decode.acc_seg: 95.1652, loss: 0.1158 2023-01-06 06:11:16,975 - mmseg - INFO - Iter [56850/160000] lr: 3.868e-05, eta: 12:29:27, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1113, decode.acc_seg: 95.1325, loss: 0.1113 2023-01-06 06:11:38,851 - mmseg - INFO - Iter [56900/160000] lr: 3.866e-05, eta: 12:29:05, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1214, decode.acc_seg: 95.1335, loss: 0.1214 2023-01-06 06:12:01,946 - mmseg - INFO - Iter [56950/160000] lr: 3.864e-05, eta: 12:28:46, time: 0.462, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1126, decode.acc_seg: 95.3439, loss: 0.1126 2023-01-06 06:12:22,918 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 06:12:22,918 - mmseg - INFO - Iter [57000/160000] lr: 3.863e-05, eta: 12:28:22, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1221, decode.acc_seg: 95.0378, loss: 0.1221 2023-01-06 06:12:44,199 - mmseg - INFO - Iter [57050/160000] lr: 3.861e-05, eta: 12:28:00, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1223, decode.acc_seg: 95.0611, loss: 0.1223 2023-01-06 06:13:05,195 - mmseg - INFO - Iter [57100/160000] lr: 3.859e-05, eta: 12:27:36, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1162, decode.acc_seg: 95.1711, loss: 0.1162 2023-01-06 06:13:26,451 - mmseg - INFO - Iter [57150/160000] lr: 3.857e-05, eta: 12:27:14, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1174, decode.acc_seg: 95.2248, loss: 0.1174 2023-01-06 06:13:47,669 - mmseg - INFO - Iter [57200/160000] lr: 3.855e-05, eta: 12:26:51, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1247, decode.acc_seg: 95.0101, loss: 0.1247 2023-01-06 06:14:09,128 - mmseg - INFO - Iter [57250/160000] lr: 3.853e-05, eta: 12:26:28, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1219, decode.acc_seg: 94.9826, loss: 0.1219 2023-01-06 06:14:32,906 - mmseg - INFO - Iter [57300/160000] lr: 3.851e-05, eta: 12:26:10, time: 0.476, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1224, decode.acc_seg: 95.0922, loss: 0.1224 2023-01-06 06:14:54,238 - mmseg - INFO - Iter [57350/160000] lr: 3.849e-05, eta: 12:25:47, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1265, decode.acc_seg: 95.0001, loss: 0.1265 2023-01-06 06:15:15,602 - mmseg - INFO - Iter [57400/160000] lr: 3.848e-05, eta: 12:25:25, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1261, decode.acc_seg: 95.0181, loss: 0.1261 2023-01-06 06:15:36,606 - mmseg - INFO - Iter [57450/160000] lr: 3.846e-05, eta: 12:25:02, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1195, decode.acc_seg: 94.9202, loss: 0.1195 2023-01-06 06:15:58,142 - mmseg - INFO - Iter [57500/160000] lr: 3.844e-05, eta: 12:24:39, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1197, decode.acc_seg: 95.0825, loss: 0.1197 2023-01-06 06:16:19,964 - mmseg - INFO - Iter [57550/160000] lr: 3.842e-05, eta: 12:24:18, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1196, decode.acc_seg: 94.9555, loss: 0.1196 2023-01-06 06:16:40,888 - mmseg - INFO - Iter [57600/160000] lr: 3.840e-05, eta: 12:23:54, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1198, decode.acc_seg: 95.0877, loss: 0.1198 2023-01-06 06:17:02,511 - mmseg - INFO - Iter [57650/160000] lr: 3.838e-05, eta: 12:23:32, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1186, decode.acc_seg: 95.1138, loss: 0.1186 2023-01-06 06:17:26,156 - mmseg - INFO - Iter [57700/160000] lr: 3.836e-05, eta: 12:23:14, time: 0.473, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1242, decode.acc_seg: 94.9620, loss: 0.1242 2023-01-06 06:17:47,250 - mmseg - INFO - Iter [57750/160000] lr: 3.834e-05, eta: 12:22:51, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1241, decode.acc_seg: 94.9734, loss: 0.1241 2023-01-06 06:18:08,800 - mmseg - INFO - Iter [57800/160000] lr: 3.833e-05, eta: 12:22:28, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1293, decode.acc_seg: 94.8134, loss: 0.1293 2023-01-06 06:18:30,285 - mmseg - INFO - Iter [57850/160000] lr: 3.831e-05, eta: 12:22:06, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1127, decode.acc_seg: 95.4383, loss: 0.1127 2023-01-06 06:18:51,107 - mmseg - INFO - Iter [57900/160000] lr: 3.829e-05, eta: 12:21:43, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1163, decode.acc_seg: 95.1015, loss: 0.1163 2023-01-06 06:19:11,883 - mmseg - INFO - Iter [57950/160000] lr: 3.827e-05, eta: 12:21:19, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1257, decode.acc_seg: 94.9417, loss: 0.1257 2023-01-06 06:19:32,977 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 06:19:32,978 - mmseg - INFO - Iter 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[58250/160000] lr: 3.816e-05, eta: 12:19:06, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1298, decode.acc_seg: 94.8520, loss: 0.1298 2023-01-06 06:21:43,894 - mmseg - INFO - Iter [58300/160000] lr: 3.814e-05, eta: 12:18:45, time: 0.448, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1351, decode.acc_seg: 94.6479, loss: 0.1351 2023-01-06 06:22:05,008 - mmseg - INFO - Iter [58350/160000] lr: 3.812e-05, eta: 12:18:22, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1187, decode.acc_seg: 95.2237, loss: 0.1187 2023-01-06 06:22:26,356 - mmseg - INFO - Iter [58400/160000] lr: 3.810e-05, eta: 12:18:00, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1147, decode.acc_seg: 95.3292, loss: 0.1147 2023-01-06 06:22:49,947 - mmseg - INFO - Iter [58450/160000] lr: 3.808e-05, eta: 12:17:41, time: 0.472, data_time: 0.058, memory: 9591, decode.loss_ce: 0.1241, decode.acc_seg: 94.9455, loss: 0.1241 2023-01-06 06:23:11,496 - mmseg - INFO - Iter [58500/160000] lr: 3.806e-05, eta: 12:17:19, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1194, decode.acc_seg: 95.0664, loss: 0.1194 2023-01-06 06:23:32,621 - mmseg - INFO - Iter [58550/160000] lr: 3.804e-05, eta: 12:16:56, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1239, decode.acc_seg: 94.9268, loss: 0.1239 2023-01-06 06:23:53,398 - mmseg - INFO - Iter [58600/160000] lr: 3.803e-05, eta: 12:16:33, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1318, decode.acc_seg: 94.7259, loss: 0.1318 2023-01-06 06:24:14,882 - mmseg - INFO - Iter [58650/160000] lr: 3.801e-05, eta: 12:16:10, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1221, decode.acc_seg: 95.0814, loss: 0.1221 2023-01-06 06:24:36,372 - mmseg - INFO - Iter [58700/160000] lr: 3.799e-05, eta: 12:15:48, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1166, decode.acc_seg: 95.1961, loss: 0.1166 2023-01-06 06:24:57,437 - mmseg - INFO - Iter [58750/160000] lr: 3.797e-05, eta: 12:15:25, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1240, decode.acc_seg: 94.9657, loss: 0.1240 2023-01-06 06:25:21,135 - mmseg - INFO - Iter [58800/160000] lr: 3.795e-05, eta: 12:15:06, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1281, decode.acc_seg: 94.6514, loss: 0.1281 2023-01-06 06:25:42,128 - mmseg - INFO - Iter [58850/160000] lr: 3.793e-05, eta: 12:14:43, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1148, decode.acc_seg: 95.2402, loss: 0.1148 2023-01-06 06:26:03,030 - mmseg - INFO - Iter [58900/160000] lr: 3.791e-05, eta: 12:14:20, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1272, decode.acc_seg: 94.8780, loss: 0.1272 2023-01-06 06:26:24,391 - mmseg - INFO - Iter [58950/160000] lr: 3.789e-05, eta: 12:13:57, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1142, decode.acc_seg: 95.2569, loss: 0.1142 2023-01-06 06:26:46,210 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 06:26:46,211 - mmseg - INFO - Iter [59000/160000] lr: 3.788e-05, eta: 12:13:36, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1148, decode.acc_seg: 95.1113, loss: 0.1148 2023-01-06 06:27:08,156 - mmseg - INFO - Iter [59050/160000] lr: 3.786e-05, eta: 12:13:14, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1224, decode.acc_seg: 95.0063, loss: 0.1224 2023-01-06 06:27:29,696 - mmseg - INFO - Iter [59100/160000] lr: 3.784e-05, eta: 12:12:52, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1314, decode.acc_seg: 94.7411, loss: 0.1314 2023-01-06 06:27:53,954 - mmseg - INFO - Iter [59150/160000] lr: 3.782e-05, eta: 12:12:34, time: 0.486, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1206, decode.acc_seg: 95.1470, loss: 0.1206 2023-01-06 06:28:15,250 - mmseg - INFO - Iter [59200/160000] lr: 3.780e-05, eta: 12:12:12, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1277, decode.acc_seg: 94.7077, loss: 0.1277 2023-01-06 06:28:36,290 - mmseg - INFO - Iter [59250/160000] lr: 3.778e-05, eta: 12:11:49, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1344, decode.acc_seg: 94.5937, loss: 0.1344 2023-01-06 06:28:58,152 - mmseg - INFO - Iter [59300/160000] lr: 3.776e-05, eta: 12:11:27, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1247, decode.acc_seg: 94.9118, loss: 0.1247 2023-01-06 06:29:19,468 - mmseg - INFO - Iter [59350/160000] lr: 3.774e-05, eta: 12:11:04, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1207, decode.acc_seg: 95.0611, loss: 0.1207 2023-01-06 06:29:41,890 - mmseg - INFO - Iter [59400/160000] lr: 3.773e-05, eta: 12:10:44, time: 0.449, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1255, decode.acc_seg: 95.0107, loss: 0.1255 2023-01-06 06:30:03,437 - mmseg - INFO - Iter [59450/160000] lr: 3.771e-05, eta: 12:10:21, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1246, decode.acc_seg: 94.9810, loss: 0.1246 2023-01-06 06:30:24,998 - mmseg - INFO - Iter [59500/160000] lr: 3.769e-05, eta: 12:09:59, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1218, decode.acc_seg: 94.9871, loss: 0.1218 2023-01-06 06:30:48,055 - mmseg - INFO - Iter [59550/160000] lr: 3.767e-05, eta: 12:09:40, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1246, decode.acc_seg: 94.9429, loss: 0.1246 2023-01-06 06:31:09,650 - mmseg - INFO - Iter [59600/160000] lr: 3.765e-05, eta: 12:09:17, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1228, decode.acc_seg: 95.0607, loss: 0.1228 2023-01-06 06:31:30,826 - mmseg - INFO - Iter [59650/160000] lr: 3.763e-05, eta: 12:08:55, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1265, decode.acc_seg: 94.8831, loss: 0.1265 2023-01-06 06:31:51,912 - mmseg - INFO - Iter [59700/160000] lr: 3.761e-05, eta: 12:08:32, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1193, decode.acc_seg: 95.1626, loss: 0.1193 2023-01-06 06:32:12,919 - mmseg - INFO - Iter [59750/160000] lr: 3.759e-05, eta: 12:08:08, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1152, decode.acc_seg: 95.2220, loss: 0.1152 2023-01-06 06:32:33,989 - mmseg - INFO - Iter [59800/160000] lr: 3.758e-05, eta: 12:07:45, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1218, decode.acc_seg: 94.9996, loss: 0.1218 2023-01-06 06:32:55,228 - mmseg - INFO - Iter [59850/160000] lr: 3.756e-05, eta: 12:07:23, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1273, decode.acc_seg: 94.8174, loss: 0.1273 2023-01-06 06:33:18,243 - mmseg - INFO - Iter [59900/160000] lr: 3.754e-05, eta: 12:07:03, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1204, decode.acc_seg: 95.0225, loss: 0.1204 2023-01-06 06:33:39,681 - mmseg - INFO - Iter [59950/160000] lr: 3.752e-05, eta: 12:06:41, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1124, decode.acc_seg: 95.3247, loss: 0.1124 2023-01-06 06:34:00,663 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 06:34:00,663 - mmseg - INFO - Iter [60000/160000] lr: 3.750e-05, eta: 12:06:18, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.2163, loss: 0.1160 2023-01-06 06:34:21,965 - mmseg - INFO - Iter [60050/160000] lr: 3.748e-05, eta: 12:05:55, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1241, decode.acc_seg: 94.8648, loss: 0.1241 2023-01-06 06:34:43,071 - mmseg - INFO - Iter [60100/160000] lr: 3.746e-05, eta: 12:05:32, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1165, decode.acc_seg: 95.3402, loss: 0.1165 2023-01-06 06:35:04,413 - mmseg - INFO - Iter [60150/160000] lr: 3.744e-05, eta: 12:05:09, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1183, decode.acc_seg: 95.0749, loss: 0.1183 2023-01-06 06:35:25,973 - mmseg - INFO - Iter [60200/160000] lr: 3.743e-05, eta: 12:04:47, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1189, decode.acc_seg: 95.2515, loss: 0.1189 2023-01-06 06:35:46,860 - mmseg - INFO - Iter [60250/160000] lr: 3.741e-05, eta: 12:04:24, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1184, decode.acc_seg: 94.9601, loss: 0.1184 2023-01-06 06:36:10,843 - mmseg - INFO - Iter [60300/160000] lr: 3.739e-05, eta: 12:04:06, time: 0.480, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1224, decode.acc_seg: 95.0044, loss: 0.1224 2023-01-06 06:36:32,819 - mmseg - INFO - Iter [60350/160000] lr: 3.737e-05, eta: 12:03:44, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1230, decode.acc_seg: 94.7662, loss: 0.1230 2023-01-06 06:36:53,518 - mmseg - INFO - Iter [60400/160000] lr: 3.735e-05, eta: 12:03:21, time: 0.414, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1200, decode.acc_seg: 95.1545, loss: 0.1200 2023-01-06 06:37:14,635 - mmseg - INFO - Iter [60450/160000] lr: 3.733e-05, eta: 12:02:58, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1164, decode.acc_seg: 95.1811, loss: 0.1164 2023-01-06 06:37:36,965 - mmseg - INFO - Iter [60500/160000] lr: 3.731e-05, eta: 12:02:37, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1167, decode.acc_seg: 95.2812, loss: 0.1167 2023-01-06 06:37:58,358 - mmseg - INFO - Iter [60550/160000] lr: 3.729e-05, eta: 12:02:15, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1115, decode.acc_seg: 95.4559, loss: 0.1115 2023-01-06 06:38:20,401 - mmseg - INFO - Iter [60600/160000] lr: 3.728e-05, eta: 12:01:53, time: 0.441, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1135, decode.acc_seg: 95.2952, loss: 0.1135 2023-01-06 06:38:44,075 - mmseg - INFO - Iter [60650/160000] lr: 3.726e-05, eta: 12:01:34, time: 0.473, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1267, decode.acc_seg: 94.7982, loss: 0.1267 2023-01-06 06:39:05,476 - mmseg - INFO - Iter [60700/160000] lr: 3.724e-05, eta: 12:01:12, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1192, decode.acc_seg: 95.1389, loss: 0.1192 2023-01-06 06:39:27,357 - mmseg - INFO - Iter [60750/160000] lr: 3.722e-05, eta: 12:00:50, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1195, decode.acc_seg: 95.0123, loss: 0.1195 2023-01-06 06:39:48,167 - mmseg - INFO - Iter [60800/160000] lr: 3.720e-05, eta: 12:00:27, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1291, decode.acc_seg: 94.9033, loss: 0.1291 2023-01-06 06:40:09,600 - mmseg - INFO - Iter [60850/160000] lr: 3.718e-05, eta: 12:00:05, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1155, decode.acc_seg: 95.1780, loss: 0.1155 2023-01-06 06:40:31,013 - mmseg - INFO - Iter [60900/160000] lr: 3.716e-05, eta: 11:59:42, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1133, decode.acc_seg: 95.4061, loss: 0.1133 2023-01-06 06:40:51,731 - mmseg - INFO - Iter [60950/160000] lr: 3.714e-05, eta: 11:59:19, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1236, decode.acc_seg: 95.0608, loss: 0.1236 2023-01-06 06:41:13,037 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 06:41:13,038 - mmseg - INFO - Iter [61000/160000] lr: 3.713e-05, eta: 11:58:56, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1158, decode.acc_seg: 95.0682, loss: 0.1158 2023-01-06 06:41:37,035 - mmseg - INFO - Iter [61050/160000] lr: 3.711e-05, eta: 11:58:38, time: 0.481, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1162, decode.acc_seg: 95.2500, loss: 0.1162 2023-01-06 06:41:58,178 - mmseg - INFO - Iter [61100/160000] lr: 3.709e-05, eta: 11:58:15, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1165, decode.acc_seg: 95.3810, loss: 0.1165 2023-01-06 06:42:19,602 - mmseg - INFO - Iter [61150/160000] lr: 3.707e-05, eta: 11:57:53, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1291, decode.acc_seg: 94.7542, loss: 0.1291 2023-01-06 06:42:40,965 - mmseg - INFO - Iter [61200/160000] lr: 3.705e-05, eta: 11:57:30, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1213, decode.acc_seg: 95.0789, loss: 0.1213 2023-01-06 06:43:01,701 - mmseg - INFO - Iter [61250/160000] lr: 3.703e-05, eta: 11:57:07, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1322, decode.acc_seg: 94.6667, loss: 0.1322 2023-01-06 06:43:23,375 - mmseg - INFO - Iter [61300/160000] lr: 3.701e-05, eta: 11:56:45, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1256, decode.acc_seg: 94.9538, loss: 0.1256 2023-01-06 06:43:46,119 - mmseg - INFO - Iter [61350/160000] lr: 3.699e-05, eta: 11:56:25, time: 0.455, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1151, decode.acc_seg: 95.2872, loss: 0.1151 2023-01-06 06:44:09,275 - mmseg - INFO - Iter [61400/160000] lr: 3.698e-05, eta: 11:56:05, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1098, decode.acc_seg: 95.3760, loss: 0.1098 2023-01-06 06:44:31,123 - mmseg - INFO - Iter [61450/160000] lr: 3.696e-05, eta: 11:55:43, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1100, decode.acc_seg: 95.4622, loss: 0.1100 2023-01-06 06:44:52,367 - mmseg - INFO - Iter [61500/160000] lr: 3.694e-05, eta: 11:55:21, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1283, decode.acc_seg: 94.8137, loss: 0.1283 2023-01-06 06:45:13,690 - mmseg - INFO - Iter [61550/160000] lr: 3.692e-05, eta: 11:54:58, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1277, decode.acc_seg: 94.8330, loss: 0.1277 2023-01-06 06:45:35,533 - mmseg - INFO - Iter [61600/160000] lr: 3.690e-05, eta: 11:54:36, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1207, decode.acc_seg: 95.1554, loss: 0.1207 2023-01-06 06:45:57,658 - mmseg - INFO - Iter [61650/160000] lr: 3.688e-05, eta: 11:54:15, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1229, decode.acc_seg: 95.0078, loss: 0.1229 2023-01-06 06:46:18,652 - mmseg - INFO - Iter [61700/160000] lr: 3.686e-05, eta: 11:53:52, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1145, decode.acc_seg: 95.1990, loss: 0.1145 2023-01-06 06:46:39,631 - mmseg - INFO - Iter [61750/160000] lr: 3.684e-05, eta: 11:53:29, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1136, decode.acc_seg: 95.2574, loss: 0.1136 2023-01-06 06:47:02,779 - mmseg - INFO - Iter [61800/160000] lr: 3.683e-05, eta: 11:53:09, time: 0.463, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1190, decode.acc_seg: 95.0735, loss: 0.1190 2023-01-06 06:47:23,588 - mmseg - INFO - Iter [61850/160000] lr: 3.681e-05, eta: 11:52:46, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1095, decode.acc_seg: 95.4812, loss: 0.1095 2023-01-06 06:47:45,016 - mmseg - INFO - Iter [61900/160000] lr: 3.679e-05, eta: 11:52:24, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1155, decode.acc_seg: 95.3930, loss: 0.1155 2023-01-06 06:48:06,091 - mmseg - INFO - Iter [61950/160000] lr: 3.677e-05, eta: 11:52:01, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1244, decode.acc_seg: 94.9519, loss: 0.1244 2023-01-06 06:48:27,142 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 06:48:27,142 - mmseg - INFO - Iter [62000/160000] lr: 3.675e-05, eta: 11:51:38, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1199, decode.acc_seg: 95.0580, loss: 0.1199 2023-01-06 06:48:48,234 - mmseg - INFO - Iter [62050/160000] lr: 3.673e-05, eta: 11:51:15, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1216, decode.acc_seg: 94.9594, loss: 0.1216 2023-01-06 06:49:09,574 - mmseg - INFO - Iter [62100/160000] lr: 3.671e-05, eta: 11:50:52, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1292, decode.acc_seg: 94.8452, loss: 0.1292 2023-01-06 06:49:33,088 - mmseg - INFO - Iter [62150/160000] lr: 3.669e-05, eta: 11:50:33, time: 0.470, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1261, decode.acc_seg: 94.7661, loss: 0.1261 2023-01-06 06:49:54,205 - mmseg - INFO - Iter [62200/160000] lr: 3.668e-05, eta: 11:50:11, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1227, decode.acc_seg: 94.9835, loss: 0.1227 2023-01-06 06:50:15,269 - mmseg - INFO - Iter [62250/160000] lr: 3.666e-05, eta: 11:49:48, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1188, decode.acc_seg: 95.0720, loss: 0.1188 2023-01-06 06:50:36,122 - mmseg - INFO - Iter [62300/160000] lr: 3.664e-05, eta: 11:49:24, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1226, decode.acc_seg: 94.9843, loss: 0.1226 2023-01-06 06:50:57,328 - mmseg - INFO - Iter [62350/160000] lr: 3.662e-05, eta: 11:49:02, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1219, decode.acc_seg: 94.9790, loss: 0.1219 2023-01-06 06:51:18,203 - mmseg - INFO - Iter [62400/160000] lr: 3.660e-05, eta: 11:48:39, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1153, decode.acc_seg: 95.3993, loss: 0.1153 2023-01-06 06:51:39,130 - mmseg - INFO - Iter [62450/160000] lr: 3.658e-05, eta: 11:48:15, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1206, decode.acc_seg: 95.1932, loss: 0.1206 2023-01-06 06:52:02,480 - mmseg - INFO - Iter [62500/160000] lr: 3.656e-05, eta: 11:47:56, time: 0.467, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1100, decode.acc_seg: 95.4957, loss: 0.1100 2023-01-06 06:52:24,197 - mmseg - INFO - Iter [62550/160000] lr: 3.654e-05, eta: 11:47:34, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1213, decode.acc_seg: 95.1677, loss: 0.1213 2023-01-06 06:52:45,211 - mmseg - INFO - Iter [62600/160000] lr: 3.653e-05, eta: 11:47:11, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1147, decode.acc_seg: 95.3212, loss: 0.1147 2023-01-06 06:53:06,250 - mmseg - INFO - Iter [62650/160000] lr: 3.651e-05, eta: 11:46:48, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1268, decode.acc_seg: 94.8402, loss: 0.1268 2023-01-06 06:53:27,557 - mmseg - INFO - Iter [62700/160000] lr: 3.649e-05, eta: 11:46:26, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1174, decode.acc_seg: 95.1330, loss: 0.1174 2023-01-06 06:53:50,034 - mmseg - INFO - Iter [62750/160000] lr: 3.647e-05, eta: 11:46:05, time: 0.449, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1141, decode.acc_seg: 95.2327, loss: 0.1141 2023-01-06 06:54:10,760 - mmseg - INFO - Iter [62800/160000] lr: 3.645e-05, eta: 11:45:42, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1177, decode.acc_seg: 95.2272, loss: 0.1177 2023-01-06 06:54:32,029 - mmseg - INFO - Iter [62850/160000] lr: 3.643e-05, eta: 11:45:19, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1110, decode.acc_seg: 95.3177, loss: 0.1110 2023-01-06 06:54:55,083 - mmseg - INFO - Iter [62900/160000] lr: 3.641e-05, eta: 11:44:59, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1145, decode.acc_seg: 95.2985, loss: 0.1145 2023-01-06 06:55:16,068 - mmseg - INFO - Iter [62950/160000] lr: 3.639e-05, eta: 11:44:36, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1141, decode.acc_seg: 95.2941, loss: 0.1141 2023-01-06 06:55:38,300 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 06:55:38,301 - mmseg - INFO - Iter [63000/160000] lr: 3.638e-05, eta: 11:44:15, time: 0.445, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1250, decode.acc_seg: 94.9485, loss: 0.1250 2023-01-06 06:55:59,108 - mmseg - INFO - Iter [63050/160000] lr: 3.636e-05, eta: 11:43:52, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1148, decode.acc_seg: 95.2385, loss: 0.1148 2023-01-06 06:56:20,666 - mmseg - INFO - Iter [63100/160000] lr: 3.634e-05, eta: 11:43:30, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1269, decode.acc_seg: 95.0465, loss: 0.1269 2023-01-06 06:56:41,625 - mmseg - INFO - Iter [63150/160000] lr: 3.632e-05, eta: 11:43:07, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1207, decode.acc_seg: 95.0292, loss: 0.1207 2023-01-06 06:57:02,882 - mmseg - INFO - Iter [63200/160000] lr: 3.630e-05, eta: 11:42:44, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1217, decode.acc_seg: 95.0615, loss: 0.1217 2023-01-06 06:57:26,385 - mmseg - INFO - Iter [63250/160000] lr: 3.628e-05, eta: 11:42:25, time: 0.471, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1145, decode.acc_seg: 95.2399, loss: 0.1145 2023-01-06 06:57:47,299 - mmseg - INFO - Iter [63300/160000] lr: 3.626e-05, eta: 11:42:02, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1182, decode.acc_seg: 95.1295, loss: 0.1182 2023-01-06 06:58:08,366 - mmseg - INFO - Iter [63350/160000] lr: 3.624e-05, eta: 11:41:39, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1156, decode.acc_seg: 95.2564, loss: 0.1156 2023-01-06 06:58:29,178 - mmseg - INFO - Iter [63400/160000] lr: 3.623e-05, eta: 11:41:16, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1277, decode.acc_seg: 94.8351, loss: 0.1277 2023-01-06 06:58:50,457 - mmseg - INFO - Iter [63450/160000] lr: 3.621e-05, eta: 11:40:53, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.2162, loss: 0.1160 2023-01-06 06:59:11,936 - mmseg - INFO - Iter [63500/160000] lr: 3.619e-05, eta: 11:40:31, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1128, decode.acc_seg: 95.2598, loss: 0.1128 2023-01-06 06:59:33,005 - mmseg - INFO - Iter [63550/160000] lr: 3.617e-05, eta: 11:40:08, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1284, decode.acc_seg: 94.8365, loss: 0.1284 2023-01-06 06:59:54,678 - mmseg - INFO - Iter [63600/160000] lr: 3.615e-05, eta: 11:39:46, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1203, decode.acc_seg: 95.1607, loss: 0.1203 2023-01-06 07:00:18,532 - mmseg - INFO - Iter [63650/160000] lr: 3.613e-05, eta: 11:39:28, time: 0.478, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1276, decode.acc_seg: 94.8182, loss: 0.1276 2023-01-06 07:00:40,031 - mmseg - INFO - Iter [63700/160000] lr: 3.611e-05, eta: 11:39:05, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1318, decode.acc_seg: 94.9799, loss: 0.1318 2023-01-06 07:01:00,871 - mmseg - INFO - Iter [63750/160000] lr: 3.609e-05, eta: 11:38:42, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1198, decode.acc_seg: 94.9823, loss: 0.1198 2023-01-06 07:01:22,629 - mmseg - INFO - Iter [63800/160000] lr: 3.608e-05, eta: 11:38:20, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1257, decode.acc_seg: 95.1292, loss: 0.1257 2023-01-06 07:01:43,391 - mmseg - INFO - Iter [63850/160000] lr: 3.606e-05, eta: 11:37:57, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1231, decode.acc_seg: 95.0532, loss: 0.1231 2023-01-06 07:02:04,250 - mmseg - INFO - Iter [63900/160000] lr: 3.604e-05, eta: 11:37:34, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1286, decode.acc_seg: 94.9259, loss: 0.1286 2023-01-06 07:02:25,797 - mmseg - INFO - Iter [63950/160000] lr: 3.602e-05, eta: 11:37:12, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1120, decode.acc_seg: 95.4718, loss: 0.1120 2023-01-06 07:02:48,941 - mmseg - INFO - Saving checkpoint at 64000 iterations 2023-01-06 07:02:52,836 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:02:52,837 - mmseg - INFO - Iter [64000/160000] lr: 3.600e-05, eta: 11:36:58, time: 0.541, data_time: 0.058, memory: 9591, decode.loss_ce: 0.1179, decode.acc_seg: 95.2536, loss: 0.1179 2023-01-06 07:03:21,208 - mmseg - INFO - per class results: 2023-01-06 07:03:21,211 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 97.65 | 98.73 | | sidewalk | 81.17 | 90.46 | | building | 90.71 | 95.98 | | wall | 46.1 | 52.41 | | fence | 49.98 | 60.29 | | pole | 57.07 | 64.46 | | traffic light | 59.3 | 70.28 | | traffic sign | 71.23 | 79.33 | | vegetation | 91.59 | 96.56 | | terrain | 61.66 | 68.18 | | sky | 94.2 | 98.3 | | person | 75.37 | 87.4 | | rider | 52.04 | 67.86 | | car | 92.08 | 97.66 | | truck | 41.23 | 45.02 | | bus | 62.14 | 70.27 | | train | 46.36 | 72.9 | | motorcycle | 37.7 | 47.32 | | bicycle | 69.97 | 85.02 | +---------------+-------+-------+ 2023-01-06 07:03:21,211 - mmseg - INFO - Summary: 2023-01-06 07:03:21,212 - mmseg - INFO - +-------+-------+-------+ | aAcc | mIoU | mAcc | +-------+-------+-------+ | 94.96 | 67.24 | 76.23 | +-------+-------+-------+ 2023-01-06 07:03:21,212 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:03:21,213 - mmseg - INFO - Iter(val) [63] aAcc: 0.9496, mIoU: 0.6724, mAcc: 0.7623, IoU.road: 0.9765, IoU.sidewalk: 0.8117, IoU.building: 0.9071, IoU.wall: 0.4610, IoU.fence: 0.4998, IoU.pole: 0.5707, IoU.traffic light: 0.5930, IoU.traffic sign: 0.7123, IoU.vegetation: 0.9159, IoU.terrain: 0.6166, IoU.sky: 0.9420, IoU.person: 0.7537, IoU.rider: 0.5204, IoU.car: 0.9208, IoU.truck: 0.4123, IoU.bus: 0.6214, IoU.train: 0.4636, IoU.motorcycle: 0.3770, IoU.bicycle: 0.6997, Acc.road: 0.9873, Acc.sidewalk: 0.9046, Acc.building: 0.9598, Acc.wall: 0.5241, Acc.fence: 0.6029, Acc.pole: 0.6446, Acc.traffic light: 0.7028, Acc.traffic sign: 0.7933, Acc.vegetation: 0.9656, Acc.terrain: 0.6818, Acc.sky: 0.9830, Acc.person: 0.8740, Acc.rider: 0.6786, Acc.car: 0.9766, Acc.truck: 0.4502, Acc.bus: 0.7027, Acc.train: 0.7290, Acc.motorcycle: 0.4732, Acc.bicycle: 0.8502 2023-01-06 07:03:42,071 - mmseg - INFO - Iter [64050/160000] lr: 3.598e-05, eta: 11:37:17, time: 0.984, data_time: 0.579, memory: 9591, decode.loss_ce: 0.1148, decode.acc_seg: 95.2257, loss: 0.1148 2023-01-06 07:04:03,509 - mmseg - INFO - Iter [64100/160000] lr: 3.596e-05, eta: 11:36:55, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1091, decode.acc_seg: 95.3918, loss: 0.1091 2023-01-06 07:04:25,427 - mmseg - INFO - Iter [64150/160000] lr: 3.594e-05, eta: 11:36:33, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1119, decode.acc_seg: 95.3546, loss: 0.1119 2023-01-06 07:04:46,988 - mmseg - INFO - Iter [64200/160000] lr: 3.593e-05, eta: 11:36:11, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1143, decode.acc_seg: 95.2373, loss: 0.1143 2023-01-06 07:05:07,936 - mmseg - INFO - Iter [64250/160000] lr: 3.591e-05, eta: 11:35:48, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1196, decode.acc_seg: 95.1717, loss: 0.1196 2023-01-06 07:05:29,176 - mmseg - INFO - Iter [64300/160000] lr: 3.589e-05, eta: 11:35:25, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1142, decode.acc_seg: 95.2705, loss: 0.1142 2023-01-06 07:05:50,383 - mmseg - INFO - Iter [64350/160000] lr: 3.587e-05, eta: 11:35:03, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1145, decode.acc_seg: 95.2865, loss: 0.1145 2023-01-06 07:06:13,998 - mmseg - INFO - Iter [64400/160000] lr: 3.585e-05, eta: 11:34:44, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1125, decode.acc_seg: 95.2637, loss: 0.1125 2023-01-06 07:06:35,216 - mmseg - INFO - Iter [64450/160000] lr: 3.583e-05, eta: 11:34:21, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1061, decode.acc_seg: 95.5910, loss: 0.1061 2023-01-06 07:06:56,646 - mmseg - INFO - Iter [64500/160000] lr: 3.581e-05, eta: 11:33:59, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1262, decode.acc_seg: 94.9360, loss: 0.1262 2023-01-06 07:07:17,904 - mmseg - INFO - Iter [64550/160000] lr: 3.579e-05, eta: 11:33:36, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1233, decode.acc_seg: 94.9765, loss: 0.1233 2023-01-06 07:07:39,194 - mmseg - INFO - Iter [64600/160000] lr: 3.578e-05, eta: 11:33:13, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1157, decode.acc_seg: 95.2585, loss: 0.1157 2023-01-06 07:08:00,352 - mmseg - INFO - Iter [64650/160000] lr: 3.576e-05, eta: 11:32:51, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1072, decode.acc_seg: 95.6769, loss: 0.1072 2023-01-06 07:08:21,607 - mmseg - INFO - Iter [64700/160000] lr: 3.574e-05, eta: 11:32:28, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1153, decode.acc_seg: 95.3389, loss: 0.1153 2023-01-06 07:08:44,609 - mmseg - INFO - Iter [64750/160000] lr: 3.572e-05, eta: 11:32:08, time: 0.460, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1261, decode.acc_seg: 94.9783, loss: 0.1261 2023-01-06 07:09:05,885 - mmseg - INFO - Iter [64800/160000] lr: 3.570e-05, eta: 11:31:46, time: 0.426, data_time: 0.010, memory: 9591, decode.loss_ce: 0.1219, decode.acc_seg: 95.0337, loss: 0.1219 2023-01-06 07:09:27,019 - mmseg - INFO - Iter [64850/160000] lr: 3.568e-05, eta: 11:31:23, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1203, decode.acc_seg: 95.0722, loss: 0.1203 2023-01-06 07:09:48,028 - mmseg - INFO - Iter [64900/160000] lr: 3.566e-05, eta: 11:31:00, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1213, decode.acc_seg: 95.0553, loss: 0.1213 2023-01-06 07:10:10,214 - mmseg - INFO - Iter [64950/160000] lr: 3.564e-05, eta: 11:30:39, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1159, decode.acc_seg: 95.0197, loss: 0.1159 2023-01-06 07:10:31,482 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:10:31,483 - mmseg - INFO - Iter [65000/160000] lr: 3.563e-05, eta: 11:30:16, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1135, decode.acc_seg: 95.4295, loss: 0.1135 2023-01-06 07:10:52,805 - mmseg - INFO - Iter [65050/160000] lr: 3.561e-05, eta: 11:29:53, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1116, decode.acc_seg: 95.4847, loss: 0.1116 2023-01-06 07:11:13,571 - mmseg - INFO - Iter [65100/160000] lr: 3.559e-05, eta: 11:29:30, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1146, decode.acc_seg: 95.3336, loss: 0.1146 2023-01-06 07:11:38,010 - mmseg - INFO - Iter [65150/160000] lr: 3.557e-05, eta: 11:29:12, time: 0.489, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1167, decode.acc_seg: 95.2361, loss: 0.1167 2023-01-06 07:11:58,801 - mmseg - INFO - Iter [65200/160000] lr: 3.555e-05, eta: 11:28:49, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1154, decode.acc_seg: 95.1105, loss: 0.1154 2023-01-06 07:12:20,355 - mmseg - INFO - Iter [65250/160000] lr: 3.553e-05, eta: 11:28:27, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1130, decode.acc_seg: 95.4200, loss: 0.1130 2023-01-06 07:12:41,754 - mmseg - INFO - Iter [65300/160000] lr: 3.551e-05, eta: 11:28:04, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1167, decode.acc_seg: 95.3130, loss: 0.1167 2023-01-06 07:13:02,905 - mmseg - INFO - Iter [65350/160000] lr: 3.549e-05, eta: 11:27:42, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1170, decode.acc_seg: 95.1511, loss: 0.1170 2023-01-06 07:13:24,024 - mmseg - INFO - Iter [65400/160000] lr: 3.548e-05, eta: 11:27:19, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1112, decode.acc_seg: 95.4731, loss: 0.1112 2023-01-06 07:13:45,021 - mmseg - INFO - Iter [65450/160000] lr: 3.546e-05, eta: 11:26:56, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1149, decode.acc_seg: 95.2204, loss: 0.1149 2023-01-06 07:14:08,950 - mmseg - INFO - Iter [65500/160000] lr: 3.544e-05, eta: 11:26:37, time: 0.478, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1179, decode.acc_seg: 95.2196, loss: 0.1179 2023-01-06 07:14:30,060 - mmseg - INFO - Iter [65550/160000] lr: 3.542e-05, eta: 11:26:14, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1146, decode.acc_seg: 95.2596, loss: 0.1146 2023-01-06 07:14:51,399 - mmseg - INFO - Iter [65600/160000] lr: 3.540e-05, eta: 11:25:52, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1152, decode.acc_seg: 95.2262, loss: 0.1152 2023-01-06 07:15:12,759 - mmseg - INFO - Iter [65650/160000] lr: 3.538e-05, eta: 11:25:30, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1162, decode.acc_seg: 95.2747, loss: 0.1162 2023-01-06 07:15:34,017 - mmseg - INFO - Iter [65700/160000] lr: 3.536e-05, eta: 11:25:07, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1229, decode.acc_seg: 94.8978, loss: 0.1229 2023-01-06 07:15:55,031 - mmseg - INFO - Iter [65750/160000] lr: 3.534e-05, eta: 11:24:44, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1108, decode.acc_seg: 95.4929, loss: 0.1108 2023-01-06 07:16:16,453 - mmseg - INFO - Iter [65800/160000] lr: 3.533e-05, eta: 11:24:22, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1143, decode.acc_seg: 95.2118, loss: 0.1143 2023-01-06 07:16:40,241 - mmseg - INFO - Iter [65850/160000] lr: 3.531e-05, eta: 11:24:03, time: 0.476, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1221, decode.acc_seg: 95.1451, loss: 0.1221 2023-01-06 07:17:01,246 - mmseg - INFO - Iter [65900/160000] lr: 3.529e-05, eta: 11:23:40, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1138, decode.acc_seg: 95.1862, loss: 0.1138 2023-01-06 07:17:21,963 - mmseg - INFO - Iter [65950/160000] lr: 3.527e-05, eta: 11:23:17, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1215, decode.acc_seg: 95.0317, loss: 0.1215 2023-01-06 07:17:42,789 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:17:42,789 - mmseg - INFO - Iter [66000/160000] lr: 3.525e-05, eta: 11:22:53, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1209, decode.acc_seg: 95.1693, loss: 0.1209 2023-01-06 07:18:04,960 - mmseg - INFO - Iter [66050/160000] lr: 3.523e-05, eta: 11:22:32, time: 0.444, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1148, decode.acc_seg: 95.1838, loss: 0.1148 2023-01-06 07:18:25,964 - mmseg - INFO - Iter [66100/160000] lr: 3.521e-05, eta: 11:22:09, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1219, decode.acc_seg: 95.1936, loss: 0.1219 2023-01-06 07:18:47,641 - mmseg - INFO - Iter [66150/160000] lr: 3.519e-05, eta: 11:21:47, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1203, decode.acc_seg: 95.1268, loss: 0.1203 2023-01-06 07:19:09,207 - mmseg - INFO - Iter [66200/160000] lr: 3.518e-05, eta: 11:21:25, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1090, decode.acc_seg: 95.4581, loss: 0.1090 2023-01-06 07:19:33,078 - mmseg - INFO - Iter [66250/160000] lr: 3.516e-05, eta: 11:21:06, time: 0.478, data_time: 0.058, memory: 9591, decode.loss_ce: 0.1171, decode.acc_seg: 95.1222, loss: 0.1171 2023-01-06 07:19:54,108 - mmseg - INFO - Iter [66300/160000] lr: 3.514e-05, eta: 11:20:43, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1105, decode.acc_seg: 95.3895, loss: 0.1105 2023-01-06 07:20:15,908 - mmseg - INFO - Iter [66350/160000] lr: 3.512e-05, eta: 11:20:22, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1186, decode.acc_seg: 95.2288, loss: 0.1186 2023-01-06 07:20:37,938 - mmseg - INFO - Iter [66400/160000] lr: 3.510e-05, eta: 11:20:00, time: 0.441, data_time: 0.013, memory: 9591, decode.loss_ce: 0.1200, decode.acc_seg: 95.0426, loss: 0.1200 2023-01-06 07:20:58,954 - mmseg - INFO - Iter [66450/160000] lr: 3.508e-05, eta: 11:19:37, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1032, decode.acc_seg: 95.7692, loss: 0.1032 2023-01-06 07:21:19,690 - mmseg - INFO - Iter [66500/160000] lr: 3.506e-05, eta: 11:19:14, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1178, decode.acc_seg: 95.2620, loss: 0.1178 2023-01-06 07:21:40,907 - mmseg - INFO - Iter [66550/160000] lr: 3.504e-05, eta: 11:18:51, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1177, decode.acc_seg: 95.1672, loss: 0.1177 2023-01-06 07:22:04,838 - mmseg - INFO - Iter [66600/160000] lr: 3.503e-05, eta: 11:18:33, time: 0.479, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1077, decode.acc_seg: 95.6126, loss: 0.1077 2023-01-06 07:22:25,577 - mmseg - INFO - Iter [66650/160000] lr: 3.501e-05, eta: 11:18:09, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1199, decode.acc_seg: 95.2167, loss: 0.1199 2023-01-06 07:22:46,765 - mmseg - INFO - Iter [66700/160000] lr: 3.499e-05, eta: 11:17:47, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1145, decode.acc_seg: 95.2369, loss: 0.1145 2023-01-06 07:23:07,644 - mmseg - INFO - Iter [66750/160000] lr: 3.497e-05, eta: 11:17:24, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1130, decode.acc_seg: 95.3205, loss: 0.1130 2023-01-06 07:23:28,967 - mmseg - INFO - Iter [66800/160000] lr: 3.495e-05, eta: 11:17:01, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1080, decode.acc_seg: 95.5478, loss: 0.1080 2023-01-06 07:23:49,769 - mmseg - INFO - Iter [66850/160000] lr: 3.493e-05, eta: 11:16:38, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1122, decode.acc_seg: 95.4419, loss: 0.1122 2023-01-06 07:24:11,187 - mmseg - INFO - Iter [66900/160000] lr: 3.491e-05, eta: 11:16:16, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.0987, loss: 0.1160 2023-01-06 07:24:33,903 - mmseg - INFO - Iter [66950/160000] lr: 3.489e-05, eta: 11:15:55, time: 0.454, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1104, decode.acc_seg: 95.2472, loss: 0.1104 2023-01-06 07:24:57,494 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:24:57,495 - mmseg - INFO - Iter [67000/160000] lr: 3.488e-05, eta: 11:15:36, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1277, decode.acc_seg: 94.9186, loss: 0.1277 2023-01-06 07:25:19,301 - mmseg - INFO - Iter [67050/160000] lr: 3.486e-05, eta: 11:15:14, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1145, decode.acc_seg: 95.2491, loss: 0.1145 2023-01-06 07:25:40,246 - mmseg - INFO - Iter [67100/160000] lr: 3.484e-05, eta: 11:14:51, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1148, decode.acc_seg: 95.2102, loss: 0.1148 2023-01-06 07:26:01,644 - mmseg - INFO - Iter [67150/160000] lr: 3.482e-05, eta: 11:14:29, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1122, decode.acc_seg: 95.3159, loss: 0.1122 2023-01-06 07:26:22,834 - mmseg - INFO - Iter [67200/160000] lr: 3.480e-05, eta: 11:14:06, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1106, decode.acc_seg: 95.5058, loss: 0.1106 2023-01-06 07:26:43,601 - mmseg - INFO - Iter [67250/160000] lr: 3.478e-05, eta: 11:13:43, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1092, decode.acc_seg: 95.4185, loss: 0.1092 2023-01-06 07:27:04,946 - mmseg - INFO - Iter [67300/160000] lr: 3.476e-05, eta: 11:13:20, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1148, decode.acc_seg: 95.3004, loss: 0.1148 2023-01-06 07:27:28,240 - mmseg - INFO - Iter [67350/160000] lr: 3.474e-05, eta: 11:13:01, time: 0.465, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1139, decode.acc_seg: 95.2256, loss: 0.1139 2023-01-06 07:27:49,434 - mmseg - INFO - Iter [67400/160000] lr: 3.473e-05, eta: 11:12:38, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1100, decode.acc_seg: 95.3279, loss: 0.1100 2023-01-06 07:28:10,753 - mmseg - INFO - Iter [67450/160000] lr: 3.471e-05, eta: 11:12:16, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1179, decode.acc_seg: 95.2621, loss: 0.1179 2023-01-06 07:28:31,659 - mmseg - INFO - Iter [67500/160000] lr: 3.469e-05, eta: 11:11:53, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1250, decode.acc_seg: 95.1030, loss: 0.1250 2023-01-06 07:28:52,327 - mmseg - INFO - Iter [67550/160000] lr: 3.467e-05, eta: 11:11:29, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1122, decode.acc_seg: 95.4221, loss: 0.1122 2023-01-06 07:29:13,843 - mmseg - INFO - Iter [67600/160000] lr: 3.465e-05, eta: 11:11:07, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1130, decode.acc_seg: 95.4988, loss: 0.1130 2023-01-06 07:29:35,037 - mmseg - INFO - Iter [67650/160000] lr: 3.463e-05, eta: 11:10:45, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1106, decode.acc_seg: 95.4274, loss: 0.1106 2023-01-06 07:29:57,170 - mmseg - INFO - Iter [67700/160000] lr: 3.461e-05, eta: 11:10:23, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1196, decode.acc_seg: 95.0205, loss: 0.1196 2023-01-06 07:30:20,512 - mmseg - INFO - Iter [67750/160000] lr: 3.459e-05, eta: 11:10:04, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1101, decode.acc_seg: 95.4740, loss: 0.1101 2023-01-06 07:30:41,373 - mmseg - INFO - Iter [67800/160000] lr: 3.458e-05, eta: 11:09:41, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1114, decode.acc_seg: 95.4342, loss: 0.1114 2023-01-06 07:31:02,486 - mmseg - INFO - Iter [67850/160000] lr: 3.456e-05, eta: 11:09:18, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1147, decode.acc_seg: 95.2208, loss: 0.1147 2023-01-06 07:31:23,863 - mmseg - INFO - Iter [67900/160000] lr: 3.454e-05, eta: 11:08:55, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1181, decode.acc_seg: 95.2815, loss: 0.1181 2023-01-06 07:31:45,081 - mmseg - INFO - Iter [67950/160000] lr: 3.452e-05, eta: 11:08:33, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1147, decode.acc_seg: 95.2645, loss: 0.1147 2023-01-06 07:32:06,030 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:32:06,030 - mmseg - INFO - Iter [68000/160000] lr: 3.450e-05, eta: 11:08:10, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1219, decode.acc_seg: 95.0438, loss: 0.1219 2023-01-06 07:32:26,955 - mmseg - INFO - Iter [68050/160000] lr: 3.448e-05, eta: 11:07:47, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1094, decode.acc_seg: 95.4113, loss: 0.1094 2023-01-06 07:32:50,757 - mmseg - INFO - Iter [68100/160000] lr: 3.446e-05, eta: 11:07:28, time: 0.475, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1223, decode.acc_seg: 95.1106, loss: 0.1223 2023-01-06 07:33:12,133 - mmseg - INFO - Iter [68150/160000] lr: 3.444e-05, eta: 11:07:06, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1139, decode.acc_seg: 95.2987, loss: 0.1139 2023-01-06 07:33:33,180 - mmseg - INFO - Iter [68200/160000] lr: 3.443e-05, eta: 11:06:43, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1146, decode.acc_seg: 95.2946, loss: 0.1146 2023-01-06 07:33:54,335 - mmseg - INFO - Iter [68250/160000] lr: 3.441e-05, eta: 11:06:20, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1129, decode.acc_seg: 95.2970, loss: 0.1129 2023-01-06 07:34:15,966 - mmseg - INFO - Iter [68300/160000] lr: 3.439e-05, eta: 11:05:58, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1176, decode.acc_seg: 95.1916, loss: 0.1176 2023-01-06 07:34:37,222 - mmseg - INFO - Iter [68350/160000] lr: 3.437e-05, eta: 11:05:36, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1107, decode.acc_seg: 95.3621, loss: 0.1107 2023-01-06 07:34:58,739 - mmseg - INFO - Iter [68400/160000] lr: 3.435e-05, eta: 11:05:14, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1108, decode.acc_seg: 95.4737, loss: 0.1108 2023-01-06 07:35:22,551 - mmseg - INFO - Iter [68450/160000] lr: 3.433e-05, eta: 11:04:54, time: 0.476, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1166, decode.acc_seg: 95.2626, loss: 0.1166 2023-01-06 07:35:44,429 - mmseg - INFO - Iter [68500/160000] lr: 3.431e-05, eta: 11:04:33, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.2949, loss: 0.1160 2023-01-06 07:36:05,384 - mmseg - INFO - Iter [68550/160000] lr: 3.429e-05, eta: 11:04:10, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1128, decode.acc_seg: 95.4247, loss: 0.1128 2023-01-06 07:36:26,297 - mmseg - INFO - Iter [68600/160000] lr: 3.428e-05, eta: 11:03:47, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1154, decode.acc_seg: 95.2017, loss: 0.1154 2023-01-06 07:36:47,736 - mmseg - INFO - Iter [68650/160000] lr: 3.426e-05, eta: 11:03:25, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1105, decode.acc_seg: 95.4794, loss: 0.1105 2023-01-06 07:37:08,947 - mmseg - INFO - Iter [68700/160000] lr: 3.424e-05, eta: 11:03:02, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1059, decode.acc_seg: 95.5951, loss: 0.1059 2023-01-06 07:37:29,665 - mmseg - INFO - Iter [68750/160000] lr: 3.422e-05, eta: 11:02:39, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1078, decode.acc_seg: 95.4733, loss: 0.1078 2023-01-06 07:37:50,577 - mmseg - INFO - Iter [68800/160000] lr: 3.420e-05, eta: 11:02:16, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1159, decode.acc_seg: 95.2678, loss: 0.1159 2023-01-06 07:38:14,660 - mmseg - INFO - Iter [68850/160000] lr: 3.418e-05, eta: 11:01:57, time: 0.482, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1189, decode.acc_seg: 95.1368, loss: 0.1189 2023-01-06 07:38:35,447 - mmseg - INFO - Iter [68900/160000] lr: 3.416e-05, eta: 11:01:34, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1177, decode.acc_seg: 95.1999, loss: 0.1177 2023-01-06 07:38:56,259 - mmseg - INFO - Iter [68950/160000] lr: 3.414e-05, eta: 11:01:11, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1130, decode.acc_seg: 95.3590, loss: 0.1130 2023-01-06 07:39:18,365 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:39:18,365 - mmseg - INFO - Iter [69000/160000] lr: 3.413e-05, eta: 11:00:50, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.2172, loss: 0.1160 2023-01-06 07:39:40,003 - mmseg - INFO - Iter [69050/160000] lr: 3.411e-05, eta: 11:00:28, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1046, decode.acc_seg: 95.6091, loss: 0.1046 2023-01-06 07:40:01,266 - mmseg - INFO - Iter [69100/160000] lr: 3.409e-05, eta: 11:00:05, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1117, decode.acc_seg: 95.4106, loss: 0.1117 2023-01-06 07:40:22,132 - mmseg - INFO - Iter [69150/160000] lr: 3.407e-05, eta: 10:59:42, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1065, decode.acc_seg: 95.6086, loss: 0.1065 2023-01-06 07:40:45,248 - mmseg - INFO - Iter [69200/160000] lr: 3.405e-05, eta: 10:59:22, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1135, decode.acc_seg: 95.2599, loss: 0.1135 2023-01-06 07:41:06,240 - mmseg - INFO - Iter [69250/160000] lr: 3.403e-05, eta: 10:58:59, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1157, decode.acc_seg: 95.2568, loss: 0.1157 2023-01-06 07:41:27,021 - mmseg - INFO - Iter [69300/160000] lr: 3.401e-05, eta: 10:58:36, time: 0.416, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1179, decode.acc_seg: 95.2642, loss: 0.1179 2023-01-06 07:41:47,940 - mmseg - INFO - Iter [69350/160000] lr: 3.399e-05, eta: 10:58:13, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1182, decode.acc_seg: 95.0664, loss: 0.1182 2023-01-06 07:42:09,027 - mmseg - INFO - Iter [69400/160000] lr: 3.398e-05, eta: 10:57:51, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1197, decode.acc_seg: 95.1792, loss: 0.1197 2023-01-06 07:42:30,118 - mmseg - INFO - Iter [69450/160000] lr: 3.396e-05, eta: 10:57:28, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1134, decode.acc_seg: 95.3442, loss: 0.1134 2023-01-06 07:42:51,539 - mmseg - INFO - Iter [69500/160000] lr: 3.394e-05, eta: 10:57:06, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1110, decode.acc_seg: 95.3264, loss: 0.1110 2023-01-06 07:43:12,777 - mmseg - INFO - Iter [69550/160000] lr: 3.392e-05, eta: 10:56:43, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1114, decode.acc_seg: 95.3227, loss: 0.1114 2023-01-06 07:43:36,382 - mmseg - INFO - Iter [69600/160000] lr: 3.390e-05, eta: 10:56:24, time: 0.473, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1112, decode.acc_seg: 95.3175, loss: 0.1112 2023-01-06 07:43:57,469 - mmseg - INFO - Iter [69650/160000] lr: 3.388e-05, eta: 10:56:01, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1084, decode.acc_seg: 95.4830, loss: 0.1084 2023-01-06 07:44:19,131 - mmseg - INFO - Iter [69700/160000] lr: 3.386e-05, eta: 10:55:39, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1153, decode.acc_seg: 95.2107, loss: 0.1153 2023-01-06 07:44:40,535 - mmseg - INFO - Iter [69750/160000] lr: 3.384e-05, eta: 10:55:17, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1172, decode.acc_seg: 95.2507, loss: 0.1172 2023-01-06 07:45:01,260 - mmseg - INFO - Iter [69800/160000] lr: 3.383e-05, eta: 10:54:54, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1156, decode.acc_seg: 95.1768, loss: 0.1156 2023-01-06 07:45:23,144 - mmseg - INFO - Iter [69850/160000] lr: 3.381e-05, eta: 10:54:32, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1116, decode.acc_seg: 95.4415, loss: 0.1116 2023-01-06 07:45:44,632 - mmseg - INFO - Iter [69900/160000] lr: 3.379e-05, eta: 10:54:10, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1209, decode.acc_seg: 95.2263, loss: 0.1209 2023-01-06 07:46:07,517 - mmseg - INFO - Iter [69950/160000] lr: 3.377e-05, eta: 10:53:50, time: 0.458, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1119, decode.acc_seg: 95.3715, loss: 0.1119 2023-01-06 07:46:28,917 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:46:28,917 - mmseg - INFO - Iter 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[70250/160000] lr: 3.366e-05, eta: 10:51:33, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1117, decode.acc_seg: 95.4084, loss: 0.1117 2023-01-06 07:48:35,502 - mmseg - INFO - Iter [70300/160000] lr: 3.364e-05, eta: 10:51:11, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1099, decode.acc_seg: 95.4755, loss: 0.1099 2023-01-06 07:48:58,667 - mmseg - INFO - Iter [70350/160000] lr: 3.362e-05, eta: 10:50:51, time: 0.463, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1064, decode.acc_seg: 95.5325, loss: 0.1064 2023-01-06 07:49:20,356 - mmseg - INFO - Iter [70400/160000] lr: 3.360e-05, eta: 10:50:29, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1052, decode.acc_seg: 95.6551, loss: 0.1052 2023-01-06 07:49:41,704 - mmseg - INFO - Iter [70450/160000] lr: 3.358e-05, eta: 10:50:07, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1088, decode.acc_seg: 95.4945, loss: 0.1088 2023-01-06 07:50:02,519 - mmseg - INFO - Iter [70500/160000] lr: 3.356e-05, eta: 10:49:44, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1175, decode.acc_seg: 95.2332, loss: 0.1175 2023-01-06 07:50:23,746 - mmseg - INFO - Iter [70550/160000] lr: 3.354e-05, eta: 10:49:22, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1192, decode.acc_seg: 95.0424, loss: 0.1192 2023-01-06 07:50:45,246 - mmseg - INFO - Iter [70600/160000] lr: 3.353e-05, eta: 10:49:00, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1163, decode.acc_seg: 95.1461, loss: 0.1163 2023-01-06 07:51:06,069 - mmseg - INFO - Iter [70650/160000] lr: 3.351e-05, eta: 10:48:37, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1076, decode.acc_seg: 95.5457, loss: 0.1076 2023-01-06 07:51:29,359 - mmseg - INFO - Iter [70700/160000] lr: 3.349e-05, eta: 10:48:17, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1108, decode.acc_seg: 95.4900, loss: 0.1108 2023-01-06 07:51:50,091 - mmseg - INFO - Iter [70750/160000] lr: 3.347e-05, eta: 10:47:54, time: 0.415, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1124, decode.acc_seg: 95.3102, loss: 0.1124 2023-01-06 07:52:11,682 - mmseg - INFO - Iter [70800/160000] lr: 3.345e-05, eta: 10:47:32, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1146, decode.acc_seg: 95.3224, loss: 0.1146 2023-01-06 07:52:32,899 - mmseg - INFO - Iter [70850/160000] lr: 3.343e-05, eta: 10:47:09, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1061, decode.acc_seg: 95.5530, loss: 0.1061 2023-01-06 07:52:53,764 - mmseg - INFO - Iter [70900/160000] lr: 3.341e-05, eta: 10:46:46, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1054, decode.acc_seg: 95.6283, loss: 0.1054 2023-01-06 07:53:15,256 - mmseg - INFO - Iter [70950/160000] lr: 3.339e-05, eta: 10:46:24, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1127, decode.acc_seg: 95.4255, loss: 0.1127 2023-01-06 07:53:35,969 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 07:53:35,970 - mmseg - INFO - Iter [71000/160000] lr: 3.338e-05, eta: 10:46:01, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1130, decode.acc_seg: 95.3890, loss: 0.1130 2023-01-06 07:53:57,013 - mmseg - INFO - Iter [71050/160000] lr: 3.336e-05, eta: 10:45:38, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1120, decode.acc_seg: 95.4198, loss: 0.1120 2023-01-06 07:54:20,861 - mmseg - INFO - Iter [71100/160000] lr: 3.334e-05, eta: 10:45:19, time: 0.477, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1176, decode.acc_seg: 95.1413, loss: 0.1176 2023-01-06 07:54:42,083 - mmseg - INFO - Iter [71150/160000] lr: 3.332e-05, eta: 10:44:57, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1216, decode.acc_seg: 95.0821, loss: 0.1216 2023-01-06 07:55:02,827 - mmseg - INFO - Iter [71200/160000] lr: 3.330e-05, eta: 10:44:33, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.6587, loss: 0.1051 2023-01-06 07:55:23,913 - mmseg - INFO - Iter [71250/160000] lr: 3.328e-05, eta: 10:44:11, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1140, decode.acc_seg: 95.4189, loss: 0.1140 2023-01-06 07:55:44,634 - mmseg - INFO - Iter [71300/160000] lr: 3.326e-05, eta: 10:43:48, time: 0.415, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1112, decode.acc_seg: 95.3887, loss: 0.1112 2023-01-06 07:56:05,721 - mmseg - INFO - Iter [71350/160000] lr: 3.324e-05, eta: 10:43:25, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1177, decode.acc_seg: 95.2411, loss: 0.1177 2023-01-06 07:56:26,492 - mmseg - INFO - Iter [71400/160000] lr: 3.323e-05, eta: 10:43:02, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1143, decode.acc_seg: 95.2656, loss: 0.1143 2023-01-06 07:56:49,643 - mmseg - INFO - Iter [71450/160000] lr: 3.321e-05, eta: 10:42:42, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1151, decode.acc_seg: 95.2670, loss: 0.1151 2023-01-06 07:57:10,499 - mmseg - INFO - Iter [71500/160000] lr: 3.319e-05, eta: 10:42:19, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1307, decode.acc_seg: 94.8625, loss: 0.1307 2023-01-06 07:57:32,183 - mmseg - INFO - Iter [71550/160000] lr: 3.317e-05, eta: 10:41:57, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1115, decode.acc_seg: 95.5214, loss: 0.1115 2023-01-06 07:57:54,268 - mmseg - INFO - Iter [71600/160000] lr: 3.315e-05, eta: 10:41:36, time: 0.442, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1178, decode.acc_seg: 95.1635, loss: 0.1178 2023-01-06 07:58:15,322 - mmseg - INFO - Iter [71650/160000] lr: 3.313e-05, eta: 10:41:13, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1101, decode.acc_seg: 95.4318, loss: 0.1101 2023-01-06 07:58:36,380 - mmseg - INFO - Iter [71700/160000] lr: 3.311e-05, eta: 10:40:51, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1073, decode.acc_seg: 95.5170, loss: 0.1073 2023-01-06 07:58:58,131 - mmseg - INFO - Iter [71750/160000] lr: 3.309e-05, eta: 10:40:29, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1100, decode.acc_seg: 95.3758, loss: 0.1100 2023-01-06 07:59:21,494 - mmseg - INFO - Iter [71800/160000] lr: 3.308e-05, eta: 10:40:09, time: 0.467, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1076, decode.acc_seg: 95.5494, loss: 0.1076 2023-01-06 07:59:42,261 - mmseg - INFO - Iter [71850/160000] lr: 3.306e-05, eta: 10:39:46, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1064, decode.acc_seg: 95.6726, loss: 0.1064 2023-01-06 08:00:03,474 - mmseg - INFO - Iter [71900/160000] lr: 3.304e-05, eta: 10:39:23, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1161, decode.acc_seg: 95.2433, loss: 0.1161 2023-01-06 08:00:24,351 - mmseg - INFO - Iter [71950/160000] lr: 3.302e-05, eta: 10:39:01, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1098, decode.acc_seg: 95.5152, loss: 0.1098 2023-01-06 08:00:45,021 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:00:45,021 - mmseg - INFO - Iter [72000/160000] lr: 3.300e-05, eta: 10:38:37, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1076, decode.acc_seg: 95.6033, loss: 0.1076 2023-01-06 08:01:06,680 - mmseg - INFO - Iter [72050/160000] lr: 3.298e-05, eta: 10:38:16, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1086, decode.acc_seg: 95.5654, loss: 0.1086 2023-01-06 08:01:27,349 - mmseg - INFO - Iter [72100/160000] lr: 3.296e-05, eta: 10:37:52, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1098, decode.acc_seg: 95.6576, loss: 0.1098 2023-01-06 08:01:48,116 - mmseg - INFO - Iter [72150/160000] lr: 3.294e-05, eta: 10:37:29, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1081, decode.acc_seg: 95.4273, loss: 0.1081 2023-01-06 08:02:11,511 - mmseg - INFO - Iter [72200/160000] lr: 3.293e-05, eta: 10:37:10, time: 0.468, data_time: 0.058, memory: 9591, decode.loss_ce: 0.1120, decode.acc_seg: 95.3412, loss: 0.1120 2023-01-06 08:02:32,827 - mmseg - INFO - Iter [72250/160000] lr: 3.291e-05, eta: 10:36:47, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.3084, loss: 0.1160 2023-01-06 08:02:54,110 - mmseg - INFO - Iter [72300/160000] lr: 3.289e-05, eta: 10:36:25, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1070, decode.acc_seg: 95.4913, loss: 0.1070 2023-01-06 08:03:15,755 - mmseg - INFO - Iter [72350/160000] lr: 3.287e-05, eta: 10:36:03, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1117, decode.acc_seg: 95.4673, loss: 0.1117 2023-01-06 08:03:36,600 - mmseg - INFO - Iter [72400/160000] lr: 3.285e-05, eta: 10:35:40, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1052, decode.acc_seg: 95.6695, loss: 0.1052 2023-01-06 08:03:57,597 - mmseg - INFO - Iter [72450/160000] lr: 3.283e-05, eta: 10:35:17, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1000, decode.acc_seg: 95.8227, loss: 0.1000 2023-01-06 08:04:19,423 - mmseg - INFO - Iter [72500/160000] lr: 3.281e-05, eta: 10:34:56, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1062, decode.acc_seg: 95.4894, loss: 0.1062 2023-01-06 08:04:42,670 - mmseg - INFO - Iter [72550/160000] lr: 3.279e-05, eta: 10:34:36, time: 0.465, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1142, decode.acc_seg: 95.3460, loss: 0.1142 2023-01-06 08:05:04,489 - mmseg - INFO - Iter [72600/160000] lr: 3.278e-05, eta: 10:34:14, time: 0.436, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1162, decode.acc_seg: 95.1627, loss: 0.1162 2023-01-06 08:05:26,053 - mmseg - INFO - Iter [72650/160000] lr: 3.276e-05, eta: 10:33:52, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1132, decode.acc_seg: 95.4852, loss: 0.1132 2023-01-06 08:05:46,820 - mmseg - INFO - Iter [72700/160000] lr: 3.274e-05, eta: 10:33:29, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1120, decode.acc_seg: 95.4427, loss: 0.1120 2023-01-06 08:06:08,274 - mmseg - INFO - Iter [72750/160000] lr: 3.272e-05, eta: 10:33:07, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1097, decode.acc_seg: 95.4115, loss: 0.1097 2023-01-06 08:06:29,184 - mmseg - INFO - Iter [72800/160000] lr: 3.270e-05, eta: 10:32:44, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1101, decode.acc_seg: 95.4472, loss: 0.1101 2023-01-06 08:06:50,201 - mmseg - INFO - Iter [72850/160000] lr: 3.268e-05, eta: 10:32:21, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.7233, loss: 0.1051 2023-01-06 08:07:10,930 - mmseg - INFO - Iter [72900/160000] lr: 3.266e-05, eta: 10:31:58, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1100, decode.acc_seg: 95.4862, loss: 0.1100 2023-01-06 08:07:34,573 - mmseg - INFO - Iter [72950/160000] lr: 3.264e-05, eta: 10:31:39, time: 0.473, data_time: 0.069, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.6387, loss: 0.1051 2023-01-06 08:07:55,646 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:07:55,647 - mmseg - INFO - Iter [73000/160000] lr: 3.263e-05, eta: 10:31:16, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1090, decode.acc_seg: 95.5184, loss: 0.1090 2023-01-06 08:08:17,270 - mmseg - INFO - Iter [73050/160000] lr: 3.261e-05, eta: 10:30:54, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1090, decode.acc_seg: 95.4949, loss: 0.1090 2023-01-06 08:08:38,283 - mmseg - INFO - Iter [73100/160000] lr: 3.259e-05, eta: 10:30:32, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1197, decode.acc_seg: 95.1743, loss: 0.1197 2023-01-06 08:08:59,637 - mmseg - INFO - Iter [73150/160000] lr: 3.257e-05, eta: 10:30:09, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1129, decode.acc_seg: 95.2563, loss: 0.1129 2023-01-06 08:09:20,805 - mmseg - INFO - Iter [73200/160000] lr: 3.255e-05, eta: 10:29:47, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1138, decode.acc_seg: 95.3222, loss: 0.1138 2023-01-06 08:09:41,903 - mmseg - INFO - Iter [73250/160000] lr: 3.253e-05, eta: 10:29:24, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1227, decode.acc_seg: 95.0554, loss: 0.1227 2023-01-06 08:10:05,578 - mmseg - INFO - Iter [73300/160000] lr: 3.251e-05, eta: 10:29:05, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1149, decode.acc_seg: 95.2523, loss: 0.1149 2023-01-06 08:10:26,804 - mmseg - INFO - Iter [73350/160000] lr: 3.249e-05, eta: 10:28:42, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1003, decode.acc_seg: 95.8448, loss: 0.1003 2023-01-06 08:10:47,893 - mmseg - INFO - Iter [73400/160000] lr: 3.248e-05, eta: 10:28:20, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1111, decode.acc_seg: 95.4334, loss: 0.1111 2023-01-06 08:11:09,105 - mmseg - INFO - Iter [73450/160000] lr: 3.246e-05, eta: 10:27:57, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1145, decode.acc_seg: 95.3938, loss: 0.1145 2023-01-06 08:11:30,122 - mmseg - INFO - Iter [73500/160000] lr: 3.244e-05, eta: 10:27:35, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1134, decode.acc_seg: 95.3665, loss: 0.1134 2023-01-06 08:11:51,503 - mmseg - INFO - Iter [73550/160000] lr: 3.242e-05, eta: 10:27:13, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1309, decode.acc_seg: 94.9485, loss: 0.1309 2023-01-06 08:12:12,283 - mmseg - INFO - Iter [73600/160000] lr: 3.240e-05, eta: 10:26:50, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1179, decode.acc_seg: 95.2173, loss: 0.1179 2023-01-06 08:12:33,031 - mmseg - INFO - Iter [73650/160000] lr: 3.238e-05, eta: 10:26:27, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1069, decode.acc_seg: 95.5223, loss: 0.1069 2023-01-06 08:12:56,910 - mmseg - INFO - Iter [73700/160000] lr: 3.236e-05, eta: 10:26:07, time: 0.478, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1065, decode.acc_seg: 95.6087, loss: 0.1065 2023-01-06 08:13:17,848 - mmseg - INFO - Iter [73750/160000] lr: 3.234e-05, eta: 10:25:45, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1124, decode.acc_seg: 95.3275, loss: 0.1124 2023-01-06 08:13:38,852 - mmseg - INFO - Iter [73800/160000] lr: 3.233e-05, eta: 10:25:22, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1054, decode.acc_seg: 95.5700, loss: 0.1054 2023-01-06 08:13:59,796 - mmseg - INFO - Iter [73850/160000] lr: 3.231e-05, eta: 10:24:59, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1225, decode.acc_seg: 95.0642, loss: 0.1225 2023-01-06 08:14:20,839 - mmseg - INFO - Iter [73900/160000] lr: 3.229e-05, eta: 10:24:37, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1165, decode.acc_seg: 95.3093, loss: 0.1165 2023-01-06 08:14:41,563 - mmseg - INFO - Iter [73950/160000] lr: 3.227e-05, eta: 10:24:14, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1085, decode.acc_seg: 95.5135, loss: 0.1085 2023-01-06 08:15:02,764 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:15:02,764 - mmseg - INFO - Iter [74000/160000] lr: 3.225e-05, eta: 10:23:51, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1045, decode.acc_seg: 95.5714, loss: 0.1045 2023-01-06 08:15:26,098 - mmseg - INFO - Iter [74050/160000] lr: 3.223e-05, eta: 10:23:31, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1072, decode.acc_seg: 95.5931, loss: 0.1072 2023-01-06 08:15:47,402 - mmseg - INFO - Iter [74100/160000] lr: 3.221e-05, eta: 10:23:09, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1055, decode.acc_seg: 95.6522, loss: 0.1055 2023-01-06 08:16:08,608 - mmseg - INFO - Iter [74150/160000] lr: 3.219e-05, eta: 10:22:47, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1129, decode.acc_seg: 95.4825, loss: 0.1129 2023-01-06 08:16:30,076 - mmseg - INFO - Iter [74200/160000] lr: 3.218e-05, eta: 10:22:25, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1063, decode.acc_seg: 95.4899, loss: 0.1063 2023-01-06 08:16:51,496 - mmseg - INFO - Iter [74250/160000] lr: 3.216e-05, eta: 10:22:02, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1072, decode.acc_seg: 95.5950, loss: 0.1072 2023-01-06 08:17:13,155 - mmseg - INFO - Iter [74300/160000] lr: 3.214e-05, eta: 10:21:41, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1063, decode.acc_seg: 95.5822, loss: 0.1063 2023-01-06 08:17:34,380 - mmseg - INFO - Iter [74350/160000] lr: 3.212e-05, eta: 10:21:18, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1064, decode.acc_seg: 95.5691, loss: 0.1064 2023-01-06 08:17:55,902 - mmseg - INFO - Iter [74400/160000] lr: 3.210e-05, eta: 10:20:56, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1149, decode.acc_seg: 95.3426, loss: 0.1149 2023-01-06 08:18:19,189 - mmseg - INFO - Iter [74450/160000] lr: 3.208e-05, eta: 10:20:36, time: 0.466, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1113, decode.acc_seg: 95.4293, loss: 0.1113 2023-01-06 08:18:40,766 - mmseg - INFO - Iter [74500/160000] lr: 3.206e-05, eta: 10:20:14, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1084, decode.acc_seg: 95.4382, loss: 0.1084 2023-01-06 08:19:02,313 - mmseg - INFO - Iter [74550/160000] lr: 3.204e-05, eta: 10:19:52, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1040, decode.acc_seg: 95.6433, loss: 0.1040 2023-01-06 08:19:23,624 - mmseg - INFO - Iter [74600/160000] lr: 3.203e-05, eta: 10:19:30, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1059, decode.acc_seg: 95.5891, loss: 0.1059 2023-01-06 08:19:44,625 - mmseg - INFO - Iter [74650/160000] lr: 3.201e-05, eta: 10:19:07, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1079, decode.acc_seg: 95.6973, loss: 0.1079 2023-01-06 08:20:05,715 - mmseg - INFO - Iter [74700/160000] lr: 3.199e-05, eta: 10:18:45, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1154, decode.acc_seg: 95.3041, loss: 0.1154 2023-01-06 08:20:26,449 - mmseg - INFO - Iter [74750/160000] lr: 3.197e-05, eta: 10:18:22, time: 0.415, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1118, decode.acc_seg: 95.3117, loss: 0.1118 2023-01-06 08:20:50,271 - mmseg - INFO - Iter [74800/160000] lr: 3.195e-05, eta: 10:18:02, time: 0.476, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1251, decode.acc_seg: 94.9838, loss: 0.1251 2023-01-06 08:21:11,633 - mmseg - INFO - Iter [74850/160000] lr: 3.193e-05, eta: 10:17:40, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1083, decode.acc_seg: 95.5694, loss: 0.1083 2023-01-06 08:21:32,352 - mmseg - INFO - Iter [74900/160000] lr: 3.191e-05, eta: 10:17:17, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1164, decode.acc_seg: 95.2055, loss: 0.1164 2023-01-06 08:21:53,122 - mmseg - INFO - Iter [74950/160000] lr: 3.189e-05, eta: 10:16:54, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0994, decode.acc_seg: 95.7529, loss: 0.0994 2023-01-06 08:22:13,836 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:22:13,836 - mmseg - INFO - Iter [75000/160000] lr: 3.188e-05, eta: 10:16:31, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1040, decode.acc_seg: 95.5458, loss: 0.1040 2023-01-06 08:22:34,534 - mmseg - INFO - Iter [75050/160000] lr: 3.186e-05, eta: 10:16:08, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1132, decode.acc_seg: 95.4018, loss: 0.1132 2023-01-06 08:22:55,724 - mmseg - INFO - Iter [75100/160000] lr: 3.184e-05, eta: 10:15:46, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1107, decode.acc_seg: 95.3064, loss: 0.1107 2023-01-06 08:23:19,270 - mmseg - INFO - Iter [75150/160000] lr: 3.182e-05, eta: 10:15:26, time: 0.470, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1038, decode.acc_seg: 95.7308, loss: 0.1038 2023-01-06 08:23:40,405 - mmseg - INFO - Iter [75200/160000] lr: 3.180e-05, eta: 10:15:04, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1056, decode.acc_seg: 95.6300, loss: 0.1056 2023-01-06 08:24:02,321 - mmseg - INFO - Iter [75250/160000] lr: 3.178e-05, eta: 10:14:42, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1012, decode.acc_seg: 95.7288, loss: 0.1012 2023-01-06 08:24:23,491 - mmseg - INFO - Iter [75300/160000] lr: 3.176e-05, eta: 10:14:20, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1168, decode.acc_seg: 95.1835, loss: 0.1168 2023-01-06 08:24:44,291 - mmseg - INFO - Iter [75350/160000] lr: 3.174e-05, eta: 10:13:57, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1113, decode.acc_seg: 95.3545, loss: 0.1113 2023-01-06 08:25:05,264 - mmseg - INFO - Iter [75400/160000] lr: 3.173e-05, eta: 10:13:34, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1106, decode.acc_seg: 95.3846, loss: 0.1106 2023-01-06 08:25:26,527 - mmseg - INFO - Iter [75450/160000] lr: 3.171e-05, eta: 10:13:12, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1120, decode.acc_seg: 95.4537, loss: 0.1120 2023-01-06 08:25:47,777 - mmseg - INFO - Iter [75500/160000] lr: 3.169e-05, eta: 10:12:50, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1093, decode.acc_seg: 95.5427, loss: 0.1093 2023-01-06 08:26:11,129 - mmseg - INFO - Iter [75550/160000] lr: 3.167e-05, eta: 10:12:30, time: 0.467, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1205, decode.acc_seg: 95.1549, loss: 0.1205 2023-01-06 08:26:32,923 - mmseg - INFO - Iter [75600/160000] lr: 3.165e-05, eta: 10:12:08, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1191, decode.acc_seg: 95.1104, loss: 0.1191 2023-01-06 08:26:53,972 - mmseg - INFO - Iter [75650/160000] lr: 3.163e-05, eta: 10:11:45, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1205, decode.acc_seg: 95.2389, loss: 0.1205 2023-01-06 08:27:14,935 - mmseg - INFO - Iter [75700/160000] lr: 3.161e-05, eta: 10:11:23, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1221, decode.acc_seg: 95.1894, loss: 0.1221 2023-01-06 08:27:35,716 - mmseg - INFO - Iter [75750/160000] lr: 3.159e-05, eta: 10:11:00, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1093, decode.acc_seg: 95.5675, loss: 0.1093 2023-01-06 08:27:56,581 - mmseg - INFO - Iter [75800/160000] lr: 3.158e-05, eta: 10:10:37, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1073, decode.acc_seg: 95.4599, loss: 0.1073 2023-01-06 08:28:17,814 - mmseg - INFO - Iter [75850/160000] lr: 3.156e-05, eta: 10:10:15, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1034, decode.acc_seg: 95.7048, loss: 0.1034 2023-01-06 08:28:41,009 - mmseg - INFO - Iter [75900/160000] lr: 3.154e-05, eta: 10:09:55, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1120, decode.acc_seg: 95.4793, loss: 0.1120 2023-01-06 08:29:02,614 - mmseg - INFO - Iter [75950/160000] lr: 3.152e-05, eta: 10:09:33, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.3757, loss: 0.1160 2023-01-06 08:29:24,587 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:29:24,587 - mmseg - INFO - Iter [76000/160000] lr: 3.150e-05, eta: 10:09:11, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1056, decode.acc_seg: 95.6357, loss: 0.1056 2023-01-06 08:29:45,529 - mmseg - INFO - Iter [76050/160000] lr: 3.148e-05, eta: 10:08:49, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1109, decode.acc_seg: 95.3951, loss: 0.1109 2023-01-06 08:30:06,521 - mmseg - INFO - Iter [76100/160000] lr: 3.146e-05, eta: 10:08:26, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1118, decode.acc_seg: 95.4680, loss: 0.1118 2023-01-06 08:30:27,975 - mmseg - INFO - Iter [76150/160000] lr: 3.144e-05, eta: 10:08:04, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1079, decode.acc_seg: 95.5063, loss: 0.1079 2023-01-06 08:30:49,424 - mmseg - INFO - Iter [76200/160000] lr: 3.143e-05, eta: 10:07:42, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1092, decode.acc_seg: 95.5183, loss: 0.1092 2023-01-06 08:31:10,662 - mmseg - INFO - Iter [76250/160000] lr: 3.141e-05, eta: 10:07:19, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1132, decode.acc_seg: 95.3881, loss: 0.1132 2023-01-06 08:31:34,587 - mmseg - INFO - Iter [76300/160000] lr: 3.139e-05, eta: 10:07:00, time: 0.478, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1054, decode.acc_seg: 95.5983, loss: 0.1054 2023-01-06 08:31:55,269 - mmseg - INFO - Iter [76350/160000] lr: 3.137e-05, eta: 10:06:37, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1172, decode.acc_seg: 95.2551, loss: 0.1172 2023-01-06 08:32:16,130 - mmseg - INFO - Iter [76400/160000] lr: 3.135e-05, eta: 10:06:14, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1114, decode.acc_seg: 95.3329, loss: 0.1114 2023-01-06 08:32:37,448 - mmseg - INFO - Iter [76450/160000] lr: 3.133e-05, eta: 10:05:52, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1074, decode.acc_seg: 95.5526, loss: 0.1074 2023-01-06 08:32:58,701 - mmseg - INFO - Iter [76500/160000] lr: 3.131e-05, eta: 10:05:30, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1071, decode.acc_seg: 95.4547, loss: 0.1071 2023-01-06 08:33:19,429 - mmseg - INFO - Iter [76550/160000] lr: 3.129e-05, eta: 10:05:07, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1008, decode.acc_seg: 95.7788, loss: 0.1008 2023-01-06 08:33:40,488 - mmseg - INFO - Iter [76600/160000] lr: 3.128e-05, eta: 10:04:44, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1115, decode.acc_seg: 95.3181, loss: 0.1115 2023-01-06 08:34:04,273 - mmseg - INFO - Iter [76650/160000] lr: 3.126e-05, eta: 10:04:25, time: 0.475, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1050, decode.acc_seg: 95.5490, loss: 0.1050 2023-01-06 08:34:25,568 - mmseg - INFO - Iter [76700/160000] lr: 3.124e-05, eta: 10:04:03, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1092, decode.acc_seg: 95.5514, loss: 0.1092 2023-01-06 08:34:46,656 - mmseg - INFO - Iter [76750/160000] lr: 3.122e-05, eta: 10:03:40, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1056, decode.acc_seg: 95.5594, loss: 0.1056 2023-01-06 08:35:07,382 - mmseg - INFO - Iter [76800/160000] lr: 3.120e-05, eta: 10:03:17, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1092, decode.acc_seg: 95.5333, loss: 0.1092 2023-01-06 08:35:29,051 - mmseg - INFO - Iter [76850/160000] lr: 3.118e-05, eta: 10:02:55, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1040, decode.acc_seg: 95.6707, loss: 0.1040 2023-01-06 08:35:49,929 - mmseg - INFO - Iter [76900/160000] lr: 3.116e-05, eta: 10:02:33, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1098, decode.acc_seg: 95.4314, loss: 0.1098 2023-01-06 08:36:11,013 - mmseg - INFO - Iter [76950/160000] lr: 3.114e-05, eta: 10:02:10, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1110, decode.acc_seg: 95.4824, loss: 0.1110 2023-01-06 08:36:32,389 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:36:32,390 - mmseg - INFO - Iter [77000/160000] lr: 3.113e-05, eta: 10:01:48, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1114, decode.acc_seg: 95.4895, loss: 0.1114 2023-01-06 08:36:55,594 - mmseg - INFO - Iter [77050/160000] lr: 3.111e-05, eta: 10:01:28, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1036, decode.acc_seg: 95.7477, loss: 0.1036 2023-01-06 08:37:17,297 - mmseg - INFO - Iter [77100/160000] lr: 3.109e-05, eta: 10:01:06, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1058, decode.acc_seg: 95.5627, loss: 0.1058 2023-01-06 08:37:38,219 - mmseg - INFO - Iter [77150/160000] lr: 3.107e-05, eta: 10:00:43, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1100, decode.acc_seg: 95.5507, loss: 0.1100 2023-01-06 08:38:00,035 - mmseg - INFO - Iter [77200/160000] lr: 3.105e-05, eta: 10:00:22, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.5897, loss: 0.1051 2023-01-06 08:38:20,791 - mmseg - INFO - Iter [77250/160000] lr: 3.103e-05, eta: 9:59:59, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1048, decode.acc_seg: 95.5696, loss: 0.1048 2023-01-06 08:38:41,751 - mmseg - INFO - Iter [77300/160000] lr: 3.101e-05, eta: 9:59:36, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1010, decode.acc_seg: 95.7482, loss: 0.1010 2023-01-06 08:39:03,180 - mmseg - INFO - Iter [77350/160000] lr: 3.099e-05, eta: 9:59:14, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1090, decode.acc_seg: 95.4900, loss: 0.1090 2023-01-06 08:39:26,551 - mmseg - INFO - Iter [77400/160000] lr: 3.098e-05, eta: 9:58:54, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1036, decode.acc_seg: 95.6539, loss: 0.1036 2023-01-06 08:39:48,261 - mmseg - INFO - Iter [77450/160000] lr: 3.096e-05, eta: 9:58:32, time: 0.434, data_time: 0.018, memory: 9591, decode.loss_ce: 0.1012, decode.acc_seg: 95.7800, loss: 0.1012 2023-01-06 08:40:09,016 - mmseg - INFO - Iter [77500/160000] lr: 3.094e-05, eta: 9:58:10, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1177, decode.acc_seg: 95.1117, loss: 0.1177 2023-01-06 08:40:30,042 - mmseg - INFO - Iter [77550/160000] lr: 3.092e-05, eta: 9:57:47, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1072, decode.acc_seg: 95.5994, loss: 0.1072 2023-01-06 08:40:51,233 - mmseg - INFO - Iter [77600/160000] lr: 3.090e-05, eta: 9:57:25, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1045, decode.acc_seg: 95.6179, loss: 0.1045 2023-01-06 08:41:12,335 - mmseg - INFO - Iter [77650/160000] lr: 3.088e-05, eta: 9:57:02, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1107, decode.acc_seg: 95.4081, loss: 0.1107 2023-01-06 08:41:33,407 - mmseg - INFO - Iter [77700/160000] lr: 3.086e-05, eta: 9:56:40, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1272, decode.acc_seg: 95.0675, loss: 0.1272 2023-01-06 08:41:57,172 - mmseg - INFO - Iter [77750/160000] lr: 3.084e-05, eta: 9:56:20, time: 0.475, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1274, decode.acc_seg: 94.8501, loss: 0.1274 2023-01-06 08:42:18,244 - mmseg - INFO - Iter [77800/160000] lr: 3.083e-05, eta: 9:55:58, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1149, decode.acc_seg: 95.2642, loss: 0.1149 2023-01-06 08:42:39,694 - mmseg - INFO - Iter [77850/160000] lr: 3.081e-05, eta: 9:55:36, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1305, decode.acc_seg: 94.9063, loss: 0.1305 2023-01-06 08:43:00,997 - mmseg - INFO - Iter [77900/160000] lr: 3.079e-05, eta: 9:55:13, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1072, decode.acc_seg: 95.5181, loss: 0.1072 2023-01-06 08:43:21,992 - mmseg - INFO - Iter [77950/160000] lr: 3.077e-05, eta: 9:54:51, time: 0.420, data_time: 0.013, memory: 9591, decode.loss_ce: 0.1173, decode.acc_seg: 94.9713, loss: 0.1173 2023-01-06 08:43:42,670 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:43:42,670 - mmseg - INFO - Iter [78000/160000] lr: 3.075e-05, eta: 9:54:28, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1060, decode.acc_seg: 95.5460, loss: 0.1060 2023-01-06 08:44:04,733 - mmseg - INFO - Iter [78050/160000] lr: 3.073e-05, eta: 9:54:07, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1136, decode.acc_seg: 95.4037, loss: 0.1136 2023-01-06 08:44:25,504 - mmseg - INFO - Iter [78100/160000] lr: 3.071e-05, eta: 9:53:44, time: 0.415, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1086, decode.acc_seg: 95.5679, loss: 0.1086 2023-01-06 08:44:48,937 - mmseg - INFO - Iter [78150/160000] lr: 3.069e-05, eta: 9:53:24, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1101, decode.acc_seg: 95.5341, loss: 0.1101 2023-01-06 08:45:09,934 - mmseg - INFO - Iter [78200/160000] lr: 3.068e-05, eta: 9:53:01, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1061, decode.acc_seg: 95.6542, loss: 0.1061 2023-01-06 08:45:30,857 - mmseg - INFO - Iter [78250/160000] lr: 3.066e-05, eta: 9:52:39, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1036, decode.acc_seg: 95.7112, loss: 0.1036 2023-01-06 08:45:51,548 - mmseg - INFO - Iter [78300/160000] lr: 3.064e-05, eta: 9:52:16, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1100, decode.acc_seg: 95.4908, loss: 0.1100 2023-01-06 08:46:12,905 - mmseg - INFO - Iter [78350/160000] lr: 3.062e-05, eta: 9:51:54, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1035, decode.acc_seg: 95.6407, loss: 0.1035 2023-01-06 08:46:34,106 - mmseg - INFO - Iter [78400/160000] lr: 3.060e-05, eta: 9:51:31, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1160, decode.acc_seg: 95.1735, loss: 0.1160 2023-01-06 08:46:55,030 - mmseg - INFO - Iter [78450/160000] lr: 3.058e-05, eta: 9:51:09, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1055, decode.acc_seg: 95.5954, loss: 0.1055 2023-01-06 08:47:18,515 - mmseg - INFO - Iter [78500/160000] lr: 3.056e-05, eta: 9:50:49, time: 0.470, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1060, decode.acc_seg: 95.5904, loss: 0.1060 2023-01-06 08:47:39,629 - mmseg - INFO - Iter [78550/160000] lr: 3.054e-05, eta: 9:50:26, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1166, decode.acc_seg: 95.4409, loss: 0.1166 2023-01-06 08:48:00,763 - mmseg - INFO - Iter [78600/160000] lr: 3.053e-05, eta: 9:50:04, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1086, decode.acc_seg: 95.5266, loss: 0.1086 2023-01-06 08:48:21,621 - mmseg - INFO - Iter [78650/160000] lr: 3.051e-05, eta: 9:49:41, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1086, decode.acc_seg: 95.4941, loss: 0.1086 2023-01-06 08:48:42,299 - mmseg - INFO - Iter [78700/160000] lr: 3.049e-05, eta: 9:49:19, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1114, decode.acc_seg: 95.3233, loss: 0.1114 2023-01-06 08:49:04,125 - mmseg - INFO - Iter [78750/160000] lr: 3.047e-05, eta: 9:48:57, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1163, decode.acc_seg: 95.2745, loss: 0.1163 2023-01-06 08:49:25,377 - mmseg - INFO - Iter [78800/160000] lr: 3.045e-05, eta: 9:48:35, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1023, decode.acc_seg: 95.7352, loss: 0.1023 2023-01-06 08:49:46,122 - mmseg - INFO - Iter [78850/160000] lr: 3.043e-05, eta: 9:48:12, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1043, decode.acc_seg: 95.6181, loss: 0.1043 2023-01-06 08:50:09,610 - mmseg - INFO - Iter [78900/160000] lr: 3.041e-05, eta: 9:47:52, time: 0.470, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1077, decode.acc_seg: 95.5588, loss: 0.1077 2023-01-06 08:50:31,183 - mmseg - INFO - Iter [78950/160000] lr: 3.039e-05, eta: 9:47:30, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1076, decode.acc_seg: 95.5915, loss: 0.1076 2023-01-06 08:50:52,111 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:50:52,111 - mmseg - INFO - Iter [79000/160000] lr: 3.038e-05, eta: 9:47:07, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0990, decode.acc_seg: 95.8611, loss: 0.0990 2023-01-06 08:51:13,372 - mmseg - INFO - Iter [79050/160000] lr: 3.036e-05, eta: 9:46:45, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1077, decode.acc_seg: 95.5718, loss: 0.1077 2023-01-06 08:51:34,884 - mmseg - INFO - Iter [79100/160000] lr: 3.034e-05, eta: 9:46:23, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1058, decode.acc_seg: 95.6276, loss: 0.1058 2023-01-06 08:51:56,609 - mmseg - INFO - Iter [79150/160000] lr: 3.032e-05, eta: 9:46:01, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1085, decode.acc_seg: 95.4560, loss: 0.1085 2023-01-06 08:52:18,237 - mmseg - INFO - Iter [79200/160000] lr: 3.030e-05, eta: 9:45:40, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1074, decode.acc_seg: 95.5250, loss: 0.1074 2023-01-06 08:52:42,102 - mmseg - INFO - Iter [79250/160000] lr: 3.028e-05, eta: 9:45:20, time: 0.477, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1075, decode.acc_seg: 95.5871, loss: 0.1075 2023-01-06 08:53:03,443 - mmseg - INFO - Iter [79300/160000] lr: 3.026e-05, eta: 9:44:58, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1086, decode.acc_seg: 95.6052, loss: 0.1086 2023-01-06 08:53:24,443 - mmseg - INFO - Iter [79350/160000] lr: 3.024e-05, eta: 9:44:35, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1055, decode.acc_seg: 95.6571, loss: 0.1055 2023-01-06 08:53:45,357 - mmseg - INFO - Iter [79400/160000] lr: 3.023e-05, eta: 9:44:13, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.7637, loss: 0.1051 2023-01-06 08:54:07,075 - mmseg - INFO - Iter [79450/160000] lr: 3.021e-05, eta: 9:43:51, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0989, decode.acc_seg: 95.7791, loss: 0.0989 2023-01-06 08:54:27,894 - mmseg - INFO - Iter [79500/160000] lr: 3.019e-05, eta: 9:43:28, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1075, decode.acc_seg: 95.6981, loss: 0.1075 2023-01-06 08:54:48,727 - mmseg - INFO - Iter [79550/160000] lr: 3.017e-05, eta: 9:43:06, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1030, decode.acc_seg: 95.6208, loss: 0.1030 2023-01-06 08:55:09,675 - mmseg - INFO - Iter [79600/160000] lr: 3.015e-05, eta: 9:42:43, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1000, decode.acc_seg: 95.7610, loss: 0.1000 2023-01-06 08:55:33,287 - mmseg - INFO - Iter [79650/160000] lr: 3.013e-05, eta: 9:42:23, time: 0.472, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1088, decode.acc_seg: 95.4479, loss: 0.1088 2023-01-06 08:55:54,803 - mmseg - INFO - Iter [79700/160000] lr: 3.011e-05, eta: 9:42:01, time: 0.430, data_time: 0.013, memory: 9591, decode.loss_ce: 0.1094, decode.acc_seg: 95.5704, loss: 0.1094 2023-01-06 08:56:16,485 - mmseg - INFO - Iter [79750/160000] lr: 3.009e-05, eta: 9:41:39, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1070, decode.acc_seg: 95.6372, loss: 0.1070 2023-01-06 08:56:37,583 - mmseg - INFO - Iter [79800/160000] lr: 3.008e-05, eta: 9:41:17, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1011, decode.acc_seg: 95.8454, loss: 0.1011 2023-01-06 08:56:58,603 - mmseg - INFO - Iter [79850/160000] lr: 3.006e-05, eta: 9:40:55, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1163, decode.acc_seg: 95.1967, loss: 0.1163 2023-01-06 08:57:19,474 - mmseg - INFO - Iter [79900/160000] lr: 3.004e-05, eta: 9:40:32, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1142, decode.acc_seg: 95.4179, loss: 0.1142 2023-01-06 08:57:40,815 - mmseg - INFO - Iter [79950/160000] lr: 3.002e-05, eta: 9:40:10, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1082, decode.acc_seg: 95.4184, loss: 0.1082 2023-01-06 08:58:03,969 - mmseg - INFO - Saving checkpoint at 80000 iterations 2023-01-06 08:58:07,680 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:58:07,681 - mmseg - INFO - Iter [80000/160000] lr: 3.000e-05, eta: 9:39:53, time: 0.537, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1065, decode.acc_seg: 95.4323, loss: 0.1065 2023-01-06 08:58:35,973 - mmseg - INFO - per class results: 2023-01-06 08:58:35,976 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 97.77 | 98.84 | | sidewalk | 82.09 | 90.93 | | building | 90.57 | 96.71 | | wall | 47.03 | 50.51 | | fence | 48.78 | 57.49 | | pole | 58.53 | 67.87 | | traffic light | 61.28 | 69.47 | | traffic sign | 72.43 | 80.25 | | vegetation | 91.62 | 96.35 | | terrain | 59.93 | 65.47 | | sky | 94.54 | 97.64 | | person | 76.05 | 86.14 | | rider | 51.22 | 65.44 | | car | 91.76 | 94.46 | | truck | 54.47 | 82.22 | | bus | 61.25 | 71.08 | | train | 47.09 | 75.41 | | motorcycle | 46.84 | 56.52 | | bicycle | 70.11 | 85.47 | +---------------+-------+-------+ 2023-01-06 08:58:35,976 - mmseg - INFO - Summary: 2023-01-06 08:58:35,976 - mmseg - INFO - +-------+------+-------+ | aAcc | mIoU | mAcc | +-------+------+-------+ | 95.03 | 68.6 | 78.33 | +-------+------+-------+ 2023-01-06 08:58:35,977 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 08:58:35,978 - mmseg - INFO - Iter(val) [63] aAcc: 0.9503, mIoU: 0.6860, mAcc: 0.7833, IoU.road: 0.9777, IoU.sidewalk: 0.8209, IoU.building: 0.9057, IoU.wall: 0.4703, IoU.fence: 0.4878, IoU.pole: 0.5853, IoU.traffic light: 0.6128, IoU.traffic sign: 0.7243, IoU.vegetation: 0.9162, IoU.terrain: 0.5993, IoU.sky: 0.9454, IoU.person: 0.7605, IoU.rider: 0.5122, IoU.car: 0.9176, IoU.truck: 0.5447, IoU.bus: 0.6125, IoU.train: 0.4709, IoU.motorcycle: 0.4684, IoU.bicycle: 0.7011, Acc.road: 0.9884, Acc.sidewalk: 0.9093, Acc.building: 0.9671, Acc.wall: 0.5051, Acc.fence: 0.5749, Acc.pole: 0.6787, Acc.traffic light: 0.6947, Acc.traffic sign: 0.8025, Acc.vegetation: 0.9635, Acc.terrain: 0.6547, Acc.sky: 0.9764, Acc.person: 0.8614, Acc.rider: 0.6544, Acc.car: 0.9446, Acc.truck: 0.8222, Acc.bus: 0.7108, Acc.train: 0.7541, Acc.motorcycle: 0.5652, Acc.bicycle: 0.8547 2023-01-06 08:58:57,345 - mmseg - INFO - Iter [80050/160000] lr: 2.998e-05, eta: 9:39:59, time: 0.993, data_time: 0.577, memory: 9591, decode.loss_ce: 0.1129, decode.acc_seg: 95.2961, loss: 0.1129 2023-01-06 08:59:18,611 - mmseg - INFO - Iter [80100/160000] lr: 2.996e-05, eta: 9:39:37, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1068, decode.acc_seg: 95.6379, loss: 0.1068 2023-01-06 08:59:39,805 - mmseg - INFO - Iter [80150/160000] lr: 2.994e-05, eta: 9:39:15, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1085, decode.acc_seg: 95.5238, loss: 0.1085 2023-01-06 09:00:01,050 - mmseg - INFO - Iter [80200/160000] lr: 2.993e-05, eta: 9:38:52, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1043, decode.acc_seg: 95.8177, loss: 0.1043 2023-01-06 09:00:22,987 - mmseg - INFO - Iter [80250/160000] lr: 2.991e-05, eta: 9:38:31, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1145, decode.acc_seg: 95.3386, loss: 0.1145 2023-01-06 09:00:44,948 - mmseg - INFO - Iter [80300/160000] lr: 2.989e-05, eta: 9:38:09, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1074, decode.acc_seg: 95.4968, loss: 0.1074 2023-01-06 09:01:05,766 - mmseg - INFO - Iter [80350/160000] lr: 2.987e-05, eta: 9:37:47, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0999, decode.acc_seg: 95.6839, loss: 0.0999 2023-01-06 09:01:28,758 - mmseg - INFO - Iter [80400/160000] lr: 2.985e-05, eta: 9:37:26, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1047, decode.acc_seg: 95.6892, loss: 0.1047 2023-01-06 09:01:49,966 - mmseg - INFO - Iter [80450/160000] lr: 2.983e-05, eta: 9:37:04, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1037, decode.acc_seg: 95.7827, loss: 0.1037 2023-01-06 09:02:12,085 - mmseg - INFO - Iter [80500/160000] lr: 2.981e-05, eta: 9:36:42, time: 0.443, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1008, decode.acc_seg: 95.6695, loss: 0.1008 2023-01-06 09:02:33,872 - mmseg - INFO - Iter [80550/160000] lr: 2.979e-05, eta: 9:36:21, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1020, decode.acc_seg: 95.6536, loss: 0.1020 2023-01-06 09:02:54,997 - mmseg - INFO - Iter [80600/160000] lr: 2.978e-05, eta: 9:35:58, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.6499, loss: 0.1051 2023-01-06 09:03:16,613 - mmseg - INFO - Iter [80650/160000] lr: 2.976e-05, eta: 9:35:36, time: 0.432, data_time: 0.010, memory: 9591, decode.loss_ce: 0.1074, decode.acc_seg: 95.5924, loss: 0.1074 2023-01-06 09:03:38,388 - mmseg - INFO - Iter [80700/160000] lr: 2.974e-05, eta: 9:35:14, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1096, decode.acc_seg: 95.3953, loss: 0.1096 2023-01-06 09:04:01,470 - mmseg - INFO - Iter [80750/160000] lr: 2.972e-05, eta: 9:34:54, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1054, decode.acc_seg: 95.6257, loss: 0.1054 2023-01-06 09:04:22,651 - mmseg - INFO - Iter [80800/160000] lr: 2.970e-05, eta: 9:34:32, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1046, decode.acc_seg: 95.6538, loss: 0.1046 2023-01-06 09:04:44,570 - mmseg - INFO - Iter [80850/160000] lr: 2.968e-05, eta: 9:34:10, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1022, decode.acc_seg: 95.7820, loss: 0.1022 2023-01-06 09:05:05,845 - mmseg - INFO - Iter [80900/160000] lr: 2.966e-05, eta: 9:33:48, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1154, decode.acc_seg: 95.1328, loss: 0.1154 2023-01-06 09:05:28,057 - mmseg - INFO - Iter [80950/160000] lr: 2.964e-05, eta: 9:33:26, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1087, decode.acc_seg: 95.4928, loss: 0.1087 2023-01-06 09:05:49,729 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 09:05:49,730 - mmseg - INFO - Iter [81000/160000] lr: 2.963e-05, eta: 9:33:05, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1050, decode.acc_seg: 95.6674, loss: 0.1050 2023-01-06 09:06:11,370 - mmseg - INFO - Iter [81050/160000] lr: 2.961e-05, eta: 9:32:43, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1074, decode.acc_seg: 95.6861, loss: 0.1074 2023-01-06 09:06:35,799 - mmseg - INFO - Iter [81100/160000] lr: 2.959e-05, eta: 9:32:24, time: 0.489, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1071, decode.acc_seg: 95.4541, loss: 0.1071 2023-01-06 09:06:57,444 - mmseg - INFO - Iter [81150/160000] lr: 2.957e-05, eta: 9:32:02, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1039, decode.acc_seg: 95.6191, loss: 0.1039 2023-01-06 09:07:18,628 - mmseg - INFO - Iter [81200/160000] lr: 2.955e-05, eta: 9:31:39, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1044, decode.acc_seg: 95.6295, loss: 0.1044 2023-01-06 09:07:39,386 - mmseg - INFO - Iter [81250/160000] lr: 2.953e-05, eta: 9:31:17, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1112, decode.acc_seg: 95.4782, loss: 0.1112 2023-01-06 09:08:00,569 - mmseg - INFO - Iter [81300/160000] lr: 2.951e-05, eta: 9:30:54, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1103, decode.acc_seg: 95.4760, loss: 0.1103 2023-01-06 09:08:22,068 - mmseg - INFO - Iter [81350/160000] lr: 2.949e-05, eta: 9:30:32, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1109, decode.acc_seg: 95.4723, loss: 0.1109 2023-01-06 09:08:42,874 - mmseg - INFO - Iter [81400/160000] lr: 2.948e-05, eta: 9:30:10, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1110, decode.acc_seg: 95.4389, loss: 0.1110 2023-01-06 09:09:03,601 - mmseg - INFO - Iter [81450/160000] lr: 2.946e-05, eta: 9:29:47, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1118, decode.acc_seg: 95.3167, loss: 0.1118 2023-01-06 09:09:27,332 - mmseg - INFO - Iter [81500/160000] lr: 2.944e-05, eta: 9:29:27, time: 0.475, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1002, decode.acc_seg: 95.8391, loss: 0.1002 2023-01-06 09:09:48,595 - mmseg - INFO - Iter [81550/160000] lr: 2.942e-05, eta: 9:29:05, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1038, decode.acc_seg: 95.6354, loss: 0.1038 2023-01-06 09:10:10,272 - mmseg - INFO - Iter [81600/160000] lr: 2.940e-05, eta: 9:28:43, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1032, decode.acc_seg: 95.6600, loss: 0.1032 2023-01-06 09:10:31,949 - mmseg - INFO - Iter [81650/160000] lr: 2.938e-05, eta: 9:28:21, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1072, decode.acc_seg: 95.5084, loss: 0.1072 2023-01-06 09:10:54,156 - mmseg - INFO - Iter [81700/160000] lr: 2.936e-05, eta: 9:28:00, time: 0.445, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1011, decode.acc_seg: 95.8029, loss: 0.1011 2023-01-06 09:11:15,656 - mmseg - INFO - Iter [81750/160000] lr: 2.934e-05, eta: 9:27:38, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1087, decode.acc_seg: 95.4317, loss: 0.1087 2023-01-06 09:11:36,540 - mmseg - INFO - Iter [81800/160000] lr: 2.933e-05, eta: 9:27:15, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1053, decode.acc_seg: 95.5653, loss: 0.1053 2023-01-06 09:11:59,867 - mmseg - INFO - Iter [81850/160000] lr: 2.931e-05, eta: 9:26:55, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1021, decode.acc_seg: 95.7186, loss: 0.1021 2023-01-06 09:12:21,185 - mmseg - INFO - Iter [81900/160000] lr: 2.929e-05, eta: 9:26:33, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1024, decode.acc_seg: 95.6929, loss: 0.1024 2023-01-06 09:12:42,735 - mmseg - INFO - Iter [81950/160000] lr: 2.927e-05, eta: 9:26:11, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1050, decode.acc_seg: 95.6576, loss: 0.1050 2023-01-06 09:13:04,174 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 09:13:04,175 - mmseg - INFO - Iter [82000/160000] lr: 2.925e-05, eta: 9:25:49, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1026, decode.acc_seg: 95.6521, loss: 0.1026 2023-01-06 09:13:24,922 - mmseg - INFO - Iter [82050/160000] lr: 2.923e-05, eta: 9:25:26, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1092, decode.acc_seg: 95.5109, loss: 0.1092 2023-01-06 09:13:45,628 - mmseg - INFO - Iter [82100/160000] lr: 2.921e-05, eta: 9:25:03, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1023, decode.acc_seg: 95.7339, loss: 0.1023 2023-01-06 09:14:06,285 - mmseg - INFO - Iter [82150/160000] lr: 2.919e-05, eta: 9:24:40, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1250, decode.acc_seg: 95.1137, loss: 0.1250 2023-01-06 09:14:26,958 - mmseg - INFO - Iter [82200/160000] lr: 2.918e-05, eta: 9:24:18, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1097, decode.acc_seg: 95.4730, loss: 0.1097 2023-01-06 09:14:50,764 - mmseg - INFO - Iter [82250/160000] lr: 2.916e-05, eta: 9:23:58, time: 0.476, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1037, decode.acc_seg: 95.6312, loss: 0.1037 2023-01-06 09:15:11,879 - mmseg - INFO - Iter [82300/160000] lr: 2.914e-05, eta: 9:23:35, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1016, decode.acc_seg: 95.7562, loss: 0.1016 2023-01-06 09:15:33,096 - mmseg - INFO - Iter [82350/160000] lr: 2.912e-05, eta: 9:23:13, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1136, decode.acc_seg: 95.3834, loss: 0.1136 2023-01-06 09:15:54,217 - mmseg - INFO - Iter [82400/160000] lr: 2.910e-05, eta: 9:22:51, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1026, decode.acc_seg: 95.7897, loss: 0.1026 2023-01-06 09:16:15,136 - mmseg - INFO - Iter [82450/160000] lr: 2.908e-05, eta: 9:22:28, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1045, decode.acc_seg: 95.7261, loss: 0.1045 2023-01-06 09:16:36,411 - mmseg - INFO - Iter [82500/160000] lr: 2.906e-05, eta: 9:22:06, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1065, decode.acc_seg: 95.5764, loss: 0.1065 2023-01-06 09:16:57,128 - mmseg - INFO - Iter [82550/160000] lr: 2.904e-05, eta: 9:21:43, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1094, decode.acc_seg: 95.5744, loss: 0.1094 2023-01-06 09:17:20,847 - mmseg - INFO - Iter [82600/160000] lr: 2.903e-05, eta: 9:21:23, time: 0.474, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1094, decode.acc_seg: 95.5430, loss: 0.1094 2023-01-06 09:17:41,988 - mmseg - INFO - Iter [82650/160000] lr: 2.901e-05, eta: 9:21:01, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1073, decode.acc_seg: 95.6682, loss: 0.1073 2023-01-06 09:18:02,604 - mmseg - INFO - Iter [82700/160000] lr: 2.899e-05, eta: 9:20:38, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1031, decode.acc_seg: 95.6573, loss: 0.1031 2023-01-06 09:18:23,290 - mmseg - INFO - Iter [82750/160000] lr: 2.897e-05, eta: 9:20:15, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1048, decode.acc_seg: 95.6551, loss: 0.1048 2023-01-06 09:18:44,584 - mmseg - INFO - Iter [82800/160000] lr: 2.895e-05, eta: 9:19:53, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1032, decode.acc_seg: 95.7614, loss: 0.1032 2023-01-06 09:19:05,489 - mmseg - INFO - Iter [82850/160000] lr: 2.893e-05, eta: 9:19:31, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1063, decode.acc_seg: 95.5172, loss: 0.1063 2023-01-06 09:19:26,198 - mmseg - INFO - Iter [82900/160000] lr: 2.891e-05, eta: 9:19:08, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0997, decode.acc_seg: 95.8465, loss: 0.0997 2023-01-06 09:19:47,289 - mmseg - INFO - Iter [82950/160000] lr: 2.889e-05, eta: 9:18:45, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1055, decode.acc_seg: 95.7341, loss: 0.1055 2023-01-06 09:20:10,754 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 09:20:10,754 - mmseg - INFO - Iter [83000/160000] lr: 2.888e-05, eta: 9:18:25, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1008, decode.acc_seg: 95.8325, loss: 0.1008 2023-01-06 09:20:31,735 - mmseg - INFO - Iter [83050/160000] lr: 2.886e-05, eta: 9:18:03, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1020, decode.acc_seg: 95.6662, loss: 0.1020 2023-01-06 09:20:52,679 - mmseg - INFO - Iter [83100/160000] lr: 2.884e-05, eta: 9:17:40, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0973, decode.acc_seg: 95.8417, loss: 0.0973 2023-01-06 09:21:13,809 - mmseg - INFO - Iter [83150/160000] lr: 2.882e-05, eta: 9:17:18, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0968, decode.acc_seg: 95.9010, loss: 0.0968 2023-01-06 09:21:35,077 - mmseg - INFO - Iter [83200/160000] lr: 2.880e-05, eta: 9:16:56, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1065, decode.acc_seg: 95.7849, loss: 0.1065 2023-01-06 09:21:56,415 - mmseg - INFO - Iter [83250/160000] lr: 2.878e-05, eta: 9:16:34, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1139, decode.acc_seg: 95.3500, loss: 0.1139 2023-01-06 09:22:18,080 - mmseg - INFO - Iter [83300/160000] lr: 2.876e-05, eta: 9:16:12, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1039, decode.acc_seg: 95.7334, loss: 0.1039 2023-01-06 09:22:41,629 - mmseg - INFO - Iter [83350/160000] lr: 2.874e-05, eta: 9:15:52, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1076, decode.acc_seg: 95.6504, loss: 0.1076 2023-01-06 09:23:02,313 - mmseg - INFO - Iter [83400/160000] lr: 2.873e-05, eta: 9:15:29, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1002, decode.acc_seg: 95.7303, loss: 0.1002 2023-01-06 09:23:23,598 - mmseg - INFO - Iter [83450/160000] lr: 2.871e-05, eta: 9:15:07, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1093, decode.acc_seg: 95.6121, loss: 0.1093 2023-01-06 09:23:45,359 - mmseg - INFO - Iter [83500/160000] lr: 2.869e-05, eta: 9:14:45, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1020, decode.acc_seg: 95.7152, loss: 0.1020 2023-01-06 09:24:06,731 - mmseg - INFO - Iter [83550/160000] lr: 2.867e-05, eta: 9:14:23, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0990, decode.acc_seg: 95.8495, loss: 0.0990 2023-01-06 09:24:27,841 - mmseg - INFO - Iter [83600/160000] lr: 2.865e-05, eta: 9:14:01, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1001, decode.acc_seg: 95.7598, loss: 0.1001 2023-01-06 09:24:49,205 - mmseg - INFO - Iter [83650/160000] lr: 2.863e-05, eta: 9:13:38, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1006, decode.acc_seg: 95.6990, loss: 0.1006 2023-01-06 09:25:10,470 - mmseg - INFO - Iter [83700/160000] lr: 2.861e-05, eta: 9:13:16, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1032, decode.acc_seg: 95.7690, loss: 0.1032 2023-01-06 09:25:34,081 - mmseg - INFO - Iter [83750/160000] lr: 2.859e-05, eta: 9:12:56, time: 0.472, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1107, decode.acc_seg: 95.4971, loss: 0.1107 2023-01-06 09:25:54,927 - mmseg - INFO - Iter [83800/160000] lr: 2.858e-05, eta: 9:12:34, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1049, decode.acc_seg: 95.6216, loss: 0.1049 2023-01-06 09:26:16,208 - mmseg - INFO - Iter [83850/160000] lr: 2.856e-05, eta: 9:12:11, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1010, decode.acc_seg: 95.7685, loss: 0.1010 2023-01-06 09:26:37,118 - mmseg - INFO - Iter [83900/160000] lr: 2.854e-05, eta: 9:11:49, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1007, decode.acc_seg: 95.8613, loss: 0.1007 2023-01-06 09:26:57,790 - mmseg - INFO - Iter [83950/160000] lr: 2.852e-05, eta: 9:11:26, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1079, decode.acc_seg: 95.4742, loss: 0.1079 2023-01-06 09:27:18,792 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 09:27:18,793 - mmseg - INFO - Iter [84000/160000] lr: 2.850e-05, eta: 9:11:04, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1002, decode.acc_seg: 95.7587, loss: 0.1002 2023-01-06 09:27:40,541 - mmseg - INFO - Iter [84050/160000] lr: 2.848e-05, eta: 9:10:42, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0997, decode.acc_seg: 95.8487, loss: 0.0997 2023-01-06 09:28:04,151 - mmseg - INFO - Iter [84100/160000] lr: 2.846e-05, eta: 9:10:22, time: 0.473, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1032, decode.acc_seg: 95.7300, loss: 0.1032 2023-01-06 09:28:25,205 - mmseg - INFO - Iter [84150/160000] lr: 2.844e-05, eta: 9:10:00, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1017, decode.acc_seg: 95.7209, loss: 0.1017 2023-01-06 09:28:45,868 - mmseg - INFO - Iter [84200/160000] lr: 2.843e-05, eta: 9:09:37, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0942, decode.acc_seg: 96.0033, loss: 0.0942 2023-01-06 09:29:06,965 - mmseg - INFO - Iter [84250/160000] lr: 2.841e-05, eta: 9:09:14, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1018, decode.acc_seg: 95.8892, loss: 0.1018 2023-01-06 09:29:27,867 - mmseg - INFO - Iter [84300/160000] lr: 2.839e-05, eta: 9:08:52, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0971, decode.acc_seg: 95.8909, loss: 0.0971 2023-01-06 09:29:48,700 - mmseg - INFO - Iter [84350/160000] lr: 2.837e-05, eta: 9:08:29, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1071, decode.acc_seg: 95.6087, loss: 0.1071 2023-01-06 09:30:10,349 - mmseg - INFO - Iter [84400/160000] lr: 2.835e-05, eta: 9:08:07, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.6466, loss: 0.1051 2023-01-06 09:30:33,459 - mmseg - INFO - Iter [84450/160000] lr: 2.833e-05, eta: 9:07:47, time: 0.463, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1068, decode.acc_seg: 95.5633, loss: 0.1068 2023-01-06 09:30:54,468 - mmseg - INFO - Iter [84500/160000] lr: 2.831e-05, eta: 9:07:25, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1149, decode.acc_seg: 95.3485, loss: 0.1149 2023-01-06 09:31:16,041 - mmseg - INFO - Iter [84550/160000] lr: 2.829e-05, eta: 9:07:03, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1019, decode.acc_seg: 95.7566, loss: 0.1019 2023-01-06 09:31:36,731 - mmseg - INFO - Iter [84600/160000] lr: 2.828e-05, eta: 9:06:40, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1054, decode.acc_seg: 95.6813, loss: 0.1054 2023-01-06 09:31:58,178 - mmseg - INFO - Iter [84650/160000] lr: 2.826e-05, eta: 9:06:18, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1107, decode.acc_seg: 95.2821, loss: 0.1107 2023-01-06 09:32:18,907 - mmseg - INFO - Iter [84700/160000] lr: 2.824e-05, eta: 9:05:55, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1019, decode.acc_seg: 95.6182, loss: 0.1019 2023-01-06 09:32:39,644 - mmseg - INFO - Iter [84750/160000] lr: 2.822e-05, eta: 9:05:33, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1140, decode.acc_seg: 95.4281, loss: 0.1140 2023-01-06 09:33:01,591 - mmseg - INFO - Iter [84800/160000] lr: 2.820e-05, eta: 9:05:11, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1064, decode.acc_seg: 95.6322, loss: 0.1064 2023-01-06 09:33:24,963 - mmseg - INFO - Iter [84850/160000] lr: 2.818e-05, eta: 9:04:51, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1052, decode.acc_seg: 95.6408, loss: 0.1052 2023-01-06 09:33:46,817 - mmseg - INFO - Iter [84900/160000] lr: 2.816e-05, eta: 9:04:29, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1042, decode.acc_seg: 95.6243, loss: 0.1042 2023-01-06 09:34:08,436 - mmseg - INFO - Iter [84950/160000] lr: 2.814e-05, eta: 9:04:07, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1030, decode.acc_seg: 95.6412, loss: 0.1030 2023-01-06 09:34:30,124 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 09:34:30,124 - mmseg - INFO - Iter [85000/160000] lr: 2.813e-05, eta: 9:03:45, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1103, decode.acc_seg: 95.4658, loss: 0.1103 2023-01-06 09:34:52,073 - mmseg - INFO - Iter [85050/160000] lr: 2.811e-05, eta: 9:03:24, time: 0.439, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0984, decode.acc_seg: 95.9322, loss: 0.0984 2023-01-06 09:35:13,467 - mmseg - INFO - Iter [85100/160000] lr: 2.809e-05, eta: 9:03:02, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1008, decode.acc_seg: 95.8207, loss: 0.1008 2023-01-06 09:35:34,472 - mmseg - INFO - Iter [85150/160000] lr: 2.807e-05, eta: 9:02:39, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1007, decode.acc_seg: 95.7869, loss: 0.1007 2023-01-06 09:35:57,399 - mmseg - INFO - Iter [85200/160000] lr: 2.805e-05, eta: 9:02:19, time: 0.459, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1090, decode.acc_seg: 95.5990, loss: 0.1090 2023-01-06 09:36:18,922 - mmseg - INFO - Iter [85250/160000] lr: 2.803e-05, eta: 9:01:57, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1103, decode.acc_seg: 95.4527, loss: 0.1103 2023-01-06 09:36:40,961 - mmseg - INFO - Iter [85300/160000] lr: 2.801e-05, eta: 9:01:35, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1121, decode.acc_seg: 95.4385, loss: 0.1121 2023-01-06 09:37:02,329 - mmseg - INFO - Iter [85350/160000] lr: 2.799e-05, eta: 9:01:13, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1029, decode.acc_seg: 95.7511, loss: 0.1029 2023-01-06 09:37:23,420 - mmseg - INFO - Iter [85400/160000] lr: 2.798e-05, eta: 9:00:51, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0993, decode.acc_seg: 95.9371, loss: 0.0993 2023-01-06 09:37:45,097 - mmseg - INFO - Iter [85450/160000] lr: 2.796e-05, eta: 9:00:29, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0972, decode.acc_seg: 95.9172, loss: 0.0972 2023-01-06 09:38:06,145 - mmseg - INFO - Iter [85500/160000] lr: 2.794e-05, eta: 9:00:07, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1067, decode.acc_seg: 95.6114, loss: 0.1067 2023-01-06 09:38:27,547 - mmseg - INFO - Iter [85550/160000] lr: 2.792e-05, eta: 8:59:45, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0997, decode.acc_seg: 95.9145, loss: 0.0997 2023-01-06 09:38:51,212 - mmseg - INFO - Iter [85600/160000] lr: 2.790e-05, eta: 8:59:24, time: 0.473, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1128, decode.acc_seg: 95.4483, loss: 0.1128 2023-01-06 09:39:12,230 - mmseg - INFO - Iter [85650/160000] lr: 2.788e-05, eta: 8:59:02, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1094, decode.acc_seg: 95.5284, loss: 0.1094 2023-01-06 09:39:33,504 - mmseg - INFO - Iter [85700/160000] lr: 2.786e-05, eta: 8:58:40, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1018, decode.acc_seg: 95.8763, loss: 0.1018 2023-01-06 09:39:54,872 - mmseg - INFO - Iter [85750/160000] lr: 2.784e-05, eta: 8:58:18, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1001, decode.acc_seg: 95.6943, loss: 0.1001 2023-01-06 09:40:15,825 - mmseg - INFO - Iter [85800/160000] lr: 2.783e-05, eta: 8:57:55, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1109, decode.acc_seg: 95.5385, loss: 0.1109 2023-01-06 09:40:37,030 - mmseg - INFO - Iter [85850/160000] lr: 2.781e-05, eta: 8:57:33, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1052, decode.acc_seg: 95.6876, loss: 0.1052 2023-01-06 09:40:57,754 - mmseg - INFO - Iter [85900/160000] lr: 2.779e-05, eta: 8:57:11, time: 0.415, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0992, decode.acc_seg: 95.9517, loss: 0.0992 2023-01-06 09:41:20,966 - mmseg - INFO - Iter [85950/160000] lr: 2.777e-05, eta: 8:56:50, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0964, decode.acc_seg: 95.8749, loss: 0.0964 2023-01-06 09:41:41,604 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 09:41:41,605 - mmseg - INFO - Iter [86000/160000] lr: 2.775e-05, eta: 8:56:27, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1010, decode.acc_seg: 95.8019, loss: 0.1010 2023-01-06 09:42:03,066 - mmseg - INFO - Iter [86050/160000] lr: 2.773e-05, eta: 8:56:05, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1004, decode.acc_seg: 95.8463, loss: 0.1004 2023-01-06 09:42:24,679 - mmseg - INFO - Iter [86100/160000] lr: 2.771e-05, eta: 8:55:43, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1072, decode.acc_seg: 95.7008, loss: 0.1072 2023-01-06 09:42:45,451 - mmseg - INFO - Iter [86150/160000] lr: 2.769e-05, eta: 8:55:21, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1033, decode.acc_seg: 95.6887, loss: 0.1033 2023-01-06 09:43:06,549 - mmseg - INFO - Iter [86200/160000] lr: 2.768e-05, eta: 8:54:59, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1030, decode.acc_seg: 95.7127, loss: 0.1030 2023-01-06 09:43:28,004 - mmseg - INFO - Iter [86250/160000] lr: 2.766e-05, eta: 8:54:37, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1054, decode.acc_seg: 95.6266, loss: 0.1054 2023-01-06 09:43:49,156 - mmseg - INFO - Iter [86300/160000] lr: 2.764e-05, eta: 8:54:14, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1015, decode.acc_seg: 95.7480, loss: 0.1015 2023-01-06 09:44:12,868 - mmseg - INFO - Iter [86350/160000] lr: 2.762e-05, eta: 8:53:54, time: 0.474, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1036, decode.acc_seg: 95.6662, loss: 0.1036 2023-01-06 09:44:33,733 - mmseg - INFO - Iter [86400/160000] lr: 2.760e-05, eta: 8:53:32, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1003, decode.acc_seg: 95.8010, loss: 0.1003 2023-01-06 09:44:54,531 - mmseg - INFO - Iter [86450/160000] lr: 2.758e-05, eta: 8:53:09, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0999, decode.acc_seg: 95.7843, loss: 0.0999 2023-01-06 09:45:15,221 - mmseg - INFO - Iter [86500/160000] lr: 2.756e-05, eta: 8:52:47, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0975, decode.acc_seg: 95.8533, loss: 0.0975 2023-01-06 09:45:35,948 - mmseg - INFO - Iter [86550/160000] lr: 2.754e-05, eta: 8:52:24, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1005, decode.acc_seg: 95.7392, loss: 0.1005 2023-01-06 09:45:56,645 - mmseg - INFO - Iter [86600/160000] lr: 2.753e-05, eta: 8:52:01, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1047, decode.acc_seg: 95.7162, loss: 0.1047 2023-01-06 09:46:17,567 - mmseg - INFO - Iter [86650/160000] lr: 2.751e-05, eta: 8:51:39, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1053, decode.acc_seg: 95.8502, loss: 0.1053 2023-01-06 09:46:40,961 - mmseg - INFO - Iter [86700/160000] lr: 2.749e-05, eta: 8:51:19, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1012, decode.acc_seg: 95.6983, loss: 0.1012 2023-01-06 09:47:01,885 - mmseg - INFO - Iter [86750/160000] lr: 2.747e-05, eta: 8:50:56, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0998, decode.acc_seg: 95.7910, loss: 0.0998 2023-01-06 09:47:22,950 - mmseg - INFO - Iter [86800/160000] lr: 2.745e-05, eta: 8:50:34, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.9646, loss: 0.0988 2023-01-06 09:47:43,591 - mmseg - INFO - Iter [86850/160000] lr: 2.743e-05, eta: 8:50:11, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1060, decode.acc_seg: 95.6449, loss: 0.1060 2023-01-06 09:48:04,420 - mmseg - INFO - Iter [86900/160000] lr: 2.741e-05, eta: 8:49:49, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0979, decode.acc_seg: 95.8891, loss: 0.0979 2023-01-06 09:48:25,092 - mmseg - INFO - Iter [86950/160000] lr: 2.739e-05, eta: 8:49:26, time: 0.413, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0961, decode.acc_seg: 95.8322, loss: 0.0961 2023-01-06 09:48:46,239 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 09:48:46,239 - mmseg - INFO - Iter [87000/160000] lr: 2.738e-05, eta: 8:49:04, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1064, decode.acc_seg: 95.6448, loss: 0.1064 2023-01-06 09:49:09,193 - mmseg - INFO - Iter [87050/160000] lr: 2.736e-05, eta: 8:48:43, time: 0.459, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1137, decode.acc_seg: 95.3864, loss: 0.1137 2023-01-06 09:49:29,967 - mmseg - INFO - Iter [87100/160000] lr: 2.734e-05, eta: 8:48:20, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0976, decode.acc_seg: 95.8321, loss: 0.0976 2023-01-06 09:49:50,770 - mmseg - INFO - Iter [87150/160000] lr: 2.732e-05, eta: 8:47:58, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1098, decode.acc_seg: 95.4302, loss: 0.1098 2023-01-06 09:50:11,973 - mmseg - INFO - Iter [87200/160000] lr: 2.730e-05, eta: 8:47:36, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1016, decode.acc_seg: 95.7318, loss: 0.1016 2023-01-06 09:50:33,008 - mmseg - INFO - Iter [87250/160000] lr: 2.728e-05, eta: 8:47:13, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1125, decode.acc_seg: 95.4193, loss: 0.1125 2023-01-06 09:50:54,083 - mmseg - INFO - Iter [87300/160000] lr: 2.726e-05, eta: 8:46:51, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0986, decode.acc_seg: 95.8782, loss: 0.0986 2023-01-06 09:51:15,033 - mmseg - INFO - Iter [87350/160000] lr: 2.724e-05, eta: 8:46:29, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1003, decode.acc_seg: 95.8560, loss: 0.1003 2023-01-06 09:51:37,142 - mmseg - INFO - Iter [87400/160000] lr: 2.723e-05, eta: 8:46:07, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1052, decode.acc_seg: 95.5785, loss: 0.1052 2023-01-06 09:52:00,767 - mmseg - INFO - Iter [87450/160000] lr: 2.721e-05, eta: 8:45:47, time: 0.473, data_time: 0.057, memory: 9591, decode.loss_ce: 0.1052, decode.acc_seg: 95.5975, loss: 0.1052 2023-01-06 09:52:22,234 - mmseg - INFO - Iter [87500/160000] lr: 2.719e-05, eta: 8:45:25, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1105, decode.acc_seg: 95.4910, loss: 0.1105 2023-01-06 09:52:43,897 - mmseg - INFO - Iter [87550/160000] lr: 2.717e-05, eta: 8:45:03, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1117, decode.acc_seg: 95.4475, loss: 0.1117 2023-01-06 09:53:04,613 - mmseg - INFO - Iter [87600/160000] lr: 2.715e-05, eta: 8:44:41, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1027, decode.acc_seg: 95.6894, loss: 0.1027 2023-01-06 09:53:25,483 - mmseg - INFO - Iter [87650/160000] lr: 2.713e-05, eta: 8:44:18, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1061, decode.acc_seg: 95.6054, loss: 0.1061 2023-01-06 09:53:47,418 - mmseg - INFO - Iter [87700/160000] lr: 2.711e-05, eta: 8:43:57, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1192, decode.acc_seg: 95.2083, loss: 0.1192 2023-01-06 09:54:08,115 - mmseg - INFO - Iter [87750/160000] lr: 2.709e-05, eta: 8:43:34, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1189, decode.acc_seg: 95.1613, loss: 0.1189 2023-01-06 09:54:31,194 - mmseg - INFO - Iter [87800/160000] lr: 2.708e-05, eta: 8:43:13, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1029, decode.acc_seg: 95.7174, loss: 0.1029 2023-01-06 09:54:52,743 - mmseg - INFO - Iter [87850/160000] lr: 2.706e-05, eta: 8:42:51, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1012, decode.acc_seg: 95.7853, loss: 0.1012 2023-01-06 09:55:14,186 - mmseg - INFO - Iter [87900/160000] lr: 2.704e-05, eta: 8:42:30, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1010, decode.acc_seg: 95.8126, loss: 0.1010 2023-01-06 09:55:35,049 - mmseg - INFO - Iter [87950/160000] lr: 2.702e-05, eta: 8:42:07, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1030, decode.acc_seg: 95.8580, loss: 0.1030 2023-01-06 09:55:55,991 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 09:55:55,992 - mmseg - INFO - Iter [88000/160000] lr: 2.700e-05, eta: 8:41:45, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1065, decode.acc_seg: 95.6470, loss: 0.1065 2023-01-06 09:56:16,876 - mmseg - INFO - Iter [88050/160000] lr: 2.698e-05, eta: 8:41:22, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1040, decode.acc_seg: 95.7290, loss: 0.1040 2023-01-06 09:56:37,766 - mmseg - INFO - Iter [88100/160000] lr: 2.696e-05, eta: 8:41:00, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0986, decode.acc_seg: 95.8021, loss: 0.0986 2023-01-06 09:56:59,547 - mmseg - INFO - Iter [88150/160000] lr: 2.694e-05, eta: 8:40:38, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1004, decode.acc_seg: 95.8384, loss: 0.1004 2023-01-06 09:57:22,536 - mmseg - INFO - Iter [88200/160000] lr: 2.693e-05, eta: 8:40:17, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1049, decode.acc_seg: 95.6238, loss: 0.1049 2023-01-06 09:57:43,283 - mmseg - INFO - Iter [88250/160000] lr: 2.691e-05, eta: 8:39:55, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1070, decode.acc_seg: 95.7224, loss: 0.1070 2023-01-06 09:58:04,402 - mmseg - INFO - Iter [88300/160000] lr: 2.689e-05, eta: 8:39:33, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1034, decode.acc_seg: 95.6339, loss: 0.1034 2023-01-06 09:58:25,097 - mmseg - INFO - Iter [88350/160000] lr: 2.687e-05, eta: 8:39:10, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0995, decode.acc_seg: 95.7894, loss: 0.0995 2023-01-06 09:58:46,301 - mmseg - INFO - Iter [88400/160000] lr: 2.685e-05, eta: 8:38:48, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1019, decode.acc_seg: 95.7975, loss: 0.1019 2023-01-06 09:59:07,293 - mmseg - INFO - Iter [88450/160000] lr: 2.683e-05, eta: 8:38:25, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1035, decode.acc_seg: 95.6302, loss: 0.1035 2023-01-06 09:59:28,997 - mmseg - INFO - Iter [88500/160000] lr: 2.681e-05, eta: 8:38:04, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0987, decode.acc_seg: 95.8652, loss: 0.0987 2023-01-06 09:59:52,009 - mmseg - INFO - Iter [88550/160000] lr: 2.679e-05, eta: 8:37:43, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1125, decode.acc_seg: 95.4282, loss: 0.1125 2023-01-06 10:00:14,247 - mmseg - INFO - Iter [88600/160000] lr: 2.678e-05, eta: 8:37:22, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1021, decode.acc_seg: 95.7943, loss: 0.1021 2023-01-06 10:00:35,683 - mmseg - INFO - Iter [88650/160000] lr: 2.676e-05, eta: 8:37:00, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1029, decode.acc_seg: 95.6395, loss: 0.1029 2023-01-06 10:00:57,078 - mmseg - INFO - Iter [88700/160000] lr: 2.674e-05, eta: 8:36:38, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1073, decode.acc_seg: 95.6128, loss: 0.1073 2023-01-06 10:01:19,281 - mmseg - INFO - Iter [88750/160000] lr: 2.672e-05, eta: 8:36:16, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0996, decode.acc_seg: 95.7769, loss: 0.0996 2023-01-06 10:01:40,339 - mmseg - INFO - Iter [88800/160000] lr: 2.670e-05, eta: 8:35:54, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1037, decode.acc_seg: 95.7507, loss: 0.1037 2023-01-06 10:02:01,694 - mmseg - INFO - Iter [88850/160000] lr: 2.668e-05, eta: 8:35:32, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1025, decode.acc_seg: 95.7108, loss: 0.1025 2023-01-06 10:02:22,917 - mmseg - INFO - Iter [88900/160000] lr: 2.666e-05, eta: 8:35:10, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0940, decode.acc_seg: 95.9852, loss: 0.0940 2023-01-06 10:02:45,958 - mmseg - INFO - Iter [88950/160000] lr: 2.664e-05, eta: 8:34:49, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0967, decode.acc_seg: 95.8974, loss: 0.0967 2023-01-06 10:03:07,064 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:03:07,065 - mmseg - INFO - Iter [89000/160000] lr: 2.663e-05, eta: 8:34:27, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0979, decode.acc_seg: 95.8410, loss: 0.0979 2023-01-06 10:03:28,137 - mmseg - INFO - Iter [89050/160000] lr: 2.661e-05, eta: 8:34:05, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0976, decode.acc_seg: 96.0209, loss: 0.0976 2023-01-06 10:03:49,242 - mmseg - INFO - Iter [89100/160000] lr: 2.659e-05, eta: 8:33:42, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1016, decode.acc_seg: 95.7963, loss: 0.1016 2023-01-06 10:04:10,333 - mmseg - INFO - Iter [89150/160000] lr: 2.657e-05, eta: 8:33:20, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1024, decode.acc_seg: 95.7636, loss: 0.1024 2023-01-06 10:04:31,786 - mmseg - INFO - Iter [89200/160000] lr: 2.655e-05, eta: 8:32:58, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1033, decode.acc_seg: 95.5753, loss: 0.1033 2023-01-06 10:04:53,033 - mmseg - INFO - Iter [89250/160000] lr: 2.653e-05, eta: 8:32:36, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0990, decode.acc_seg: 95.7981, loss: 0.0990 2023-01-06 10:05:16,169 - mmseg - INFO - Iter [89300/160000] lr: 2.651e-05, eta: 8:32:15, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0982, decode.acc_seg: 95.9550, loss: 0.0982 2023-01-06 10:05:37,889 - mmseg - INFO - Iter [89350/160000] lr: 2.649e-05, eta: 8:31:54, time: 0.434, data_time: 0.014, memory: 9591, decode.loss_ce: 0.0956, decode.acc_seg: 95.9566, loss: 0.0956 2023-01-06 10:05:59,244 - mmseg - INFO - Iter [89400/160000] lr: 2.648e-05, eta: 8:31:32, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1088, decode.acc_seg: 95.5344, loss: 0.1088 2023-01-06 10:06:20,880 - mmseg - INFO - Iter [89450/160000] lr: 2.646e-05, eta: 8:31:10, time: 0.432, data_time: 0.010, memory: 9591, decode.loss_ce: 0.1143, decode.acc_seg: 95.3845, loss: 0.1143 2023-01-06 10:06:42,665 - mmseg - INFO - Iter [89500/160000] lr: 2.644e-05, eta: 8:30:48, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1069, decode.acc_seg: 95.5361, loss: 0.1069 2023-01-06 10:07:03,513 - mmseg - INFO - Iter [89550/160000] lr: 2.642e-05, eta: 8:30:26, time: 0.417, data_time: 0.010, memory: 9591, decode.loss_ce: 0.1021, decode.acc_seg: 95.7500, loss: 0.1021 2023-01-06 10:07:24,160 - mmseg - INFO - Iter [89600/160000] lr: 2.640e-05, eta: 8:30:03, time: 0.413, data_time: 0.010, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.6615, loss: 0.1051 2023-01-06 10:07:44,800 - mmseg - INFO - Iter [89650/160000] lr: 2.638e-05, eta: 8:29:40, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0992, decode.acc_seg: 95.7930, loss: 0.0992 2023-01-06 10:08:08,411 - mmseg - INFO - Iter [89700/160000] lr: 2.636e-05, eta: 8:29:20, time: 0.473, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1000, decode.acc_seg: 95.8919, loss: 0.1000 2023-01-06 10:08:29,299 - mmseg - INFO - Iter [89750/160000] lr: 2.634e-05, eta: 8:28:58, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0986, decode.acc_seg: 95.9467, loss: 0.0986 2023-01-06 10:08:50,635 - mmseg - INFO - Iter [89800/160000] lr: 2.633e-05, eta: 8:28:36, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1002, decode.acc_seg: 95.9109, loss: 0.1002 2023-01-06 10:09:12,242 - mmseg - INFO - Iter [89850/160000] lr: 2.631e-05, eta: 8:28:14, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0989, decode.acc_seg: 95.8470, loss: 0.0989 2023-01-06 10:09:33,464 - mmseg - INFO - Iter [89900/160000] lr: 2.629e-05, eta: 8:27:52, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1047, decode.acc_seg: 95.3901, loss: 0.1047 2023-01-06 10:09:53,976 - mmseg - INFO - Iter [89950/160000] lr: 2.627e-05, eta: 8:27:29, time: 0.410, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1030, decode.acc_seg: 95.7759, loss: 0.1030 2023-01-06 10:10:15,779 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:10:15,780 - mmseg - INFO - Iter [90000/160000] lr: 2.625e-05, eta: 8:27:07, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1000, decode.acc_seg: 95.8676, loss: 0.1000 2023-01-06 10:10:40,208 - mmseg - INFO - Iter [90050/160000] lr: 2.623e-05, eta: 8:26:48, time: 0.488, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0992, decode.acc_seg: 95.7273, loss: 0.0992 2023-01-06 10:11:01,187 - mmseg - INFO - Iter [90100/160000] lr: 2.621e-05, eta: 8:26:25, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1022, decode.acc_seg: 95.6206, loss: 0.1022 2023-01-06 10:11:22,653 - mmseg - INFO - Iter [90150/160000] lr: 2.619e-05, eta: 8:26:04, time: 0.429, data_time: 0.013, memory: 9591, decode.loss_ce: 0.0984, decode.acc_seg: 95.9281, loss: 0.0984 2023-01-06 10:11:44,016 - mmseg - INFO - Iter [90200/160000] lr: 2.618e-05, eta: 8:25:42, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1133, decode.acc_seg: 95.5709, loss: 0.1133 2023-01-06 10:12:05,549 - mmseg - INFO - Iter [90250/160000] lr: 2.616e-05, eta: 8:25:20, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1117, decode.acc_seg: 95.3716, loss: 0.1117 2023-01-06 10:12:26,516 - mmseg - INFO - Iter [90300/160000] lr: 2.614e-05, eta: 8:24:57, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1077, decode.acc_seg: 95.4828, loss: 0.1077 2023-01-06 10:12:47,526 - mmseg - INFO - Iter [90350/160000] lr: 2.612e-05, eta: 8:24:35, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0975, decode.acc_seg: 95.9363, loss: 0.0975 2023-01-06 10:13:10,476 - mmseg - INFO - Iter [90400/160000] lr: 2.610e-05, eta: 8:24:14, time: 0.459, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0940, decode.acc_seg: 95.9867, loss: 0.0940 2023-01-06 10:13:32,002 - mmseg - INFO - Iter [90450/160000] lr: 2.608e-05, eta: 8:23:52, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1004, decode.acc_seg: 95.7768, loss: 0.1004 2023-01-06 10:13:53,378 - mmseg - INFO - Iter [90500/160000] lr: 2.606e-05, eta: 8:23:30, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.8242, loss: 0.0985 2023-01-06 10:14:14,647 - mmseg - INFO - Iter [90550/160000] lr: 2.604e-05, eta: 8:23:08, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1006, decode.acc_seg: 95.7986, loss: 0.1006 2023-01-06 10:14:35,613 - mmseg - INFO - Iter [90600/160000] lr: 2.603e-05, eta: 8:22:46, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0991, decode.acc_seg: 95.7817, loss: 0.0991 2023-01-06 10:14:56,301 - mmseg - INFO - Iter [90650/160000] lr: 2.601e-05, eta: 8:22:23, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1068, decode.acc_seg: 95.5182, loss: 0.1068 2023-01-06 10:15:18,259 - mmseg - INFO - Iter [90700/160000] lr: 2.599e-05, eta: 8:22:02, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1135, decode.acc_seg: 95.4120, loss: 0.1135 2023-01-06 10:15:39,117 - mmseg - INFO - Iter [90750/160000] lr: 2.597e-05, eta: 8:21:39, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1059, decode.acc_seg: 95.6047, loss: 0.1059 2023-01-06 10:16:02,159 - mmseg - INFO - Iter [90800/160000] lr: 2.595e-05, eta: 8:21:19, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.8215, loss: 0.0988 2023-01-06 10:16:22,876 - mmseg - INFO - Iter [90850/160000] lr: 2.593e-05, eta: 8:20:56, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1003, decode.acc_seg: 95.7743, loss: 0.1003 2023-01-06 10:16:43,779 - mmseg - INFO - Iter [90900/160000] lr: 2.591e-05, eta: 8:20:34, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.9896, loss: 0.0985 2023-01-06 10:17:04,834 - mmseg - INFO - Iter [90950/160000] lr: 2.589e-05, eta: 8:20:12, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1114, decode.acc_seg: 95.4805, loss: 0.1114 2023-01-06 10:17:26,169 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:17:26,169 - mmseg - INFO - Iter [91000/160000] lr: 2.588e-05, eta: 8:19:49, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1051, decode.acc_seg: 95.6444, loss: 0.1051 2023-01-06 10:17:47,331 - mmseg - INFO - Iter [91050/160000] lr: 2.586e-05, eta: 8:19:27, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0995, decode.acc_seg: 95.8958, loss: 0.0995 2023-01-06 10:18:08,615 - mmseg - INFO - Iter [91100/160000] lr: 2.584e-05, eta: 8:19:05, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0979, decode.acc_seg: 95.8607, loss: 0.0979 2023-01-06 10:18:31,778 - mmseg - INFO - Iter [91150/160000] lr: 2.582e-05, eta: 8:18:45, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0987, decode.acc_seg: 95.7455, loss: 0.0987 2023-01-06 10:18:52,422 - mmseg - INFO - Iter [91200/160000] lr: 2.580e-05, eta: 8:18:22, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0954, decode.acc_seg: 96.0194, loss: 0.0954 2023-01-06 10:19:13,272 - mmseg - INFO - Iter [91250/160000] lr: 2.578e-05, eta: 8:18:00, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0969, decode.acc_seg: 95.9849, loss: 0.0969 2023-01-06 10:19:34,187 - mmseg - INFO - Iter [91300/160000] lr: 2.576e-05, eta: 8:17:37, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0991, decode.acc_seg: 95.8275, loss: 0.0991 2023-01-06 10:19:55,255 - mmseg - INFO - Iter [91350/160000] lr: 2.574e-05, eta: 8:17:15, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1031, decode.acc_seg: 95.6397, loss: 0.1031 2023-01-06 10:20:16,555 - mmseg - INFO - Iter [91400/160000] lr: 2.573e-05, eta: 8:16:53, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1056, decode.acc_seg: 95.6155, loss: 0.1056 2023-01-06 10:20:38,322 - mmseg - INFO - Iter [91450/160000] lr: 2.571e-05, eta: 8:16:31, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1083, decode.acc_seg: 95.5600, loss: 0.1083 2023-01-06 10:20:59,344 - mmseg - INFO - Iter [91500/160000] lr: 2.569e-05, eta: 8:16:09, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1045, decode.acc_seg: 95.6883, loss: 0.1045 2023-01-06 10:21:23,159 - mmseg - INFO - Iter [91550/160000] lr: 2.567e-05, eta: 8:15:49, time: 0.476, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1040, decode.acc_seg: 95.6753, loss: 0.1040 2023-01-06 10:21:43,925 - mmseg - INFO - Iter [91600/160000] lr: 2.565e-05, eta: 8:15:26, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1023, decode.acc_seg: 95.6121, loss: 0.1023 2023-01-06 10:22:04,810 - mmseg - INFO - Iter [91650/160000] lr: 2.563e-05, eta: 8:15:04, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1000, decode.acc_seg: 95.8302, loss: 0.1000 2023-01-06 10:22:26,306 - mmseg - INFO - Iter [91700/160000] lr: 2.561e-05, eta: 8:14:42, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0989, decode.acc_seg: 95.8850, loss: 0.0989 2023-01-06 10:22:47,392 - mmseg - INFO - Iter [91750/160000] lr: 2.559e-05, eta: 8:14:20, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1046, decode.acc_seg: 95.6901, loss: 0.1046 2023-01-06 10:23:08,476 - mmseg - INFO - Iter [91800/160000] lr: 2.558e-05, eta: 8:13:58, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0983, decode.acc_seg: 95.8865, loss: 0.0983 2023-01-06 10:23:29,025 - mmseg - INFO - Iter [91850/160000] lr: 2.556e-05, eta: 8:13:35, time: 0.411, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0977, decode.acc_seg: 95.9223, loss: 0.0977 2023-01-06 10:23:52,810 - mmseg - INFO - Iter [91900/160000] lr: 2.554e-05, eta: 8:13:15, time: 0.475, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1002, decode.acc_seg: 95.8238, loss: 0.1002 2023-01-06 10:24:13,633 - mmseg - INFO - Iter [91950/160000] lr: 2.552e-05, eta: 8:12:53, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1020, decode.acc_seg: 95.7586, loss: 0.1020 2023-01-06 10:24:34,637 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:24:34,637 - mmseg - INFO - Iter [92000/160000] lr: 2.550e-05, eta: 8:12:30, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1035, decode.acc_seg: 95.7153, loss: 0.1035 2023-01-06 10:24:56,100 - mmseg - INFO - Iter [92050/160000] lr: 2.548e-05, eta: 8:12:08, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1079, decode.acc_seg: 95.6470, loss: 0.1079 2023-01-06 10:25:16,693 - mmseg - INFO - Iter [92100/160000] lr: 2.546e-05, eta: 8:11:46, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0992, decode.acc_seg: 95.7697, loss: 0.0992 2023-01-06 10:25:37,927 - mmseg - INFO - Iter [92150/160000] lr: 2.544e-05, eta: 8:11:24, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0961, decode.acc_seg: 95.9677, loss: 0.0961 2023-01-06 10:25:58,895 - mmseg - INFO - Iter [92200/160000] lr: 2.543e-05, eta: 8:11:01, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0957, decode.acc_seg: 96.0706, loss: 0.0957 2023-01-06 10:26:19,514 - mmseg - INFO - Iter [92250/160000] lr: 2.541e-05, eta: 8:10:39, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0993, decode.acc_seg: 95.7212, loss: 0.0993 2023-01-06 10:26:42,671 - mmseg - INFO - Iter [92300/160000] lr: 2.539e-05, eta: 8:10:18, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0996, decode.acc_seg: 95.8080, loss: 0.0996 2023-01-06 10:27:03,971 - mmseg - INFO - Iter [92350/160000] lr: 2.537e-05, eta: 8:09:56, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0960, decode.acc_seg: 95.9955, loss: 0.0960 2023-01-06 10:27:25,136 - mmseg - INFO - Iter [92400/160000] lr: 2.535e-05, eta: 8:09:34, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0923, decode.acc_seg: 96.0914, loss: 0.0923 2023-01-06 10:27:47,248 - mmseg - INFO - Iter [92450/160000] lr: 2.533e-05, eta: 8:09:13, time: 0.442, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1046, decode.acc_seg: 95.6352, loss: 0.1046 2023-01-06 10:28:09,240 - mmseg - INFO - Iter [92500/160000] lr: 2.531e-05, eta: 8:08:51, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0967, decode.acc_seg: 95.9495, loss: 0.0967 2023-01-06 10:28:30,255 - mmseg - INFO - Iter [92550/160000] lr: 2.529e-05, eta: 8:08:29, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0991, decode.acc_seg: 95.9400, loss: 0.0991 2023-01-06 10:28:51,231 - mmseg - INFO - Iter [92600/160000] lr: 2.528e-05, eta: 8:08:07, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1036, decode.acc_seg: 95.7819, loss: 0.1036 2023-01-06 10:29:15,326 - mmseg - INFO - Iter [92650/160000] lr: 2.526e-05, eta: 8:07:46, time: 0.481, data_time: 0.058, memory: 9591, decode.loss_ce: 0.0956, decode.acc_seg: 96.0066, loss: 0.0956 2023-01-06 10:29:36,991 - mmseg - INFO - Iter [92700/160000] lr: 2.524e-05, eta: 8:07:25, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1040, decode.acc_seg: 95.7871, loss: 0.1040 2023-01-06 10:29:58,076 - mmseg - INFO - Iter [92750/160000] lr: 2.522e-05, eta: 8:07:03, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0954, decode.acc_seg: 95.8884, loss: 0.0954 2023-01-06 10:30:19,460 - mmseg - INFO - Iter [92800/160000] lr: 2.520e-05, eta: 8:06:41, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1000, decode.acc_seg: 95.8044, loss: 0.1000 2023-01-06 10:30:40,359 - mmseg - INFO - Iter [92850/160000] lr: 2.518e-05, eta: 8:06:18, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0965, decode.acc_seg: 95.8792, loss: 0.0965 2023-01-06 10:31:01,029 - mmseg - INFO - Iter [92900/160000] lr: 2.516e-05, eta: 8:05:56, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0998, decode.acc_seg: 95.8236, loss: 0.0998 2023-01-06 10:31:22,166 - mmseg - INFO - Iter [92950/160000] lr: 2.514e-05, eta: 8:05:34, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0934, decode.acc_seg: 96.0882, loss: 0.0934 2023-01-06 10:31:43,089 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:31:43,090 - mmseg - INFO - Iter [93000/160000] lr: 2.513e-05, eta: 8:05:11, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0944, decode.acc_seg: 96.0659, loss: 0.0944 2023-01-06 10:32:06,176 - mmseg - INFO - Iter [93050/160000] lr: 2.511e-05, eta: 8:04:51, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0948, decode.acc_seg: 95.9449, loss: 0.0948 2023-01-06 10:32:26,776 - mmseg - INFO - Iter [93100/160000] lr: 2.509e-05, eta: 8:04:28, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0973, decode.acc_seg: 95.9561, loss: 0.0973 2023-01-06 10:32:47,406 - mmseg - INFO - Iter [93150/160000] lr: 2.507e-05, eta: 8:04:06, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0984, decode.acc_seg: 95.8545, loss: 0.0984 2023-01-06 10:33:09,052 - mmseg - INFO - Iter [93200/160000] lr: 2.505e-05, eta: 8:03:44, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0976, decode.acc_seg: 95.9878, loss: 0.0976 2023-01-06 10:33:30,362 - mmseg - INFO - Iter [93250/160000] lr: 2.503e-05, eta: 8:03:22, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0997, decode.acc_seg: 95.8213, loss: 0.0997 2023-01-06 10:33:51,403 - mmseg - INFO - Iter [93300/160000] lr: 2.501e-05, eta: 8:02:59, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0981, decode.acc_seg: 95.7752, loss: 0.0981 2023-01-06 10:34:13,275 - mmseg - INFO - Iter [93350/160000] lr: 2.499e-05, eta: 8:02:38, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0954, decode.acc_seg: 95.9456, loss: 0.0954 2023-01-06 10:34:37,350 - mmseg - INFO - Iter [93400/160000] lr: 2.498e-05, eta: 8:02:18, time: 0.482, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1003, decode.acc_seg: 95.7447, loss: 0.1003 2023-01-06 10:34:58,459 - mmseg - INFO - Iter [93450/160000] lr: 2.496e-05, eta: 8:01:56, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1025, decode.acc_seg: 95.6568, loss: 0.1025 2023-01-06 10:35:19,671 - mmseg - INFO - Iter [93500/160000] lr: 2.494e-05, eta: 8:01:34, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0972, decode.acc_seg: 95.8466, loss: 0.0972 2023-01-06 10:35:40,580 - mmseg - INFO - Iter [93550/160000] lr: 2.492e-05, eta: 8:01:11, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.2329, loss: 0.0889 2023-01-06 10:36:01,217 - mmseg - INFO - Iter [93600/160000] lr: 2.490e-05, eta: 8:00:49, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1007, decode.acc_seg: 95.8370, loss: 0.1007 2023-01-06 10:36:22,913 - mmseg - INFO - Iter [93650/160000] lr: 2.488e-05, eta: 8:00:27, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0980, decode.acc_seg: 95.9698, loss: 0.0980 2023-01-06 10:36:43,915 - mmseg - INFO - Iter [93700/160000] lr: 2.486e-05, eta: 8:00:05, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0955, decode.acc_seg: 95.9038, loss: 0.0955 2023-01-06 10:37:07,521 - mmseg - INFO - Iter [93750/160000] lr: 2.484e-05, eta: 7:59:44, time: 0.472, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1144, decode.acc_seg: 95.2706, loss: 0.1144 2023-01-06 10:37:29,066 - mmseg - INFO - Iter [93800/160000] lr: 2.483e-05, eta: 7:59:23, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1077, decode.acc_seg: 95.5977, loss: 0.1077 2023-01-06 10:37:50,678 - mmseg - INFO - Iter [93850/160000] lr: 2.481e-05, eta: 7:59:01, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0992, decode.acc_seg: 95.7847, loss: 0.0992 2023-01-06 10:38:11,349 - mmseg - INFO - Iter [93900/160000] lr: 2.479e-05, eta: 7:58:38, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0957, decode.acc_seg: 96.0474, loss: 0.0957 2023-01-06 10:38:32,388 - mmseg - INFO - Iter [93950/160000] lr: 2.477e-05, eta: 7:58:16, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1069, decode.acc_seg: 95.7119, loss: 0.1069 2023-01-06 10:38:54,136 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:38:54,137 - mmseg - INFO - Iter [94000/160000] lr: 2.475e-05, eta: 7:57:54, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1012, decode.acc_seg: 95.7589, loss: 0.1012 2023-01-06 10:39:14,903 - mmseg - INFO - Iter [94050/160000] lr: 2.473e-05, eta: 7:57:32, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0982, decode.acc_seg: 95.8210, loss: 0.0982 2023-01-06 10:39:36,135 - mmseg - INFO - Iter [94100/160000] lr: 2.471e-05, eta: 7:57:10, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1054, decode.acc_seg: 95.5518, loss: 0.1054 2023-01-06 10:39:59,820 - mmseg - INFO - Iter [94150/160000] lr: 2.469e-05, eta: 7:56:50, time: 0.473, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0972, decode.acc_seg: 95.8512, loss: 0.0972 2023-01-06 10:40:21,158 - mmseg - INFO - Iter [94200/160000] lr: 2.468e-05, eta: 7:56:28, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0927, decode.acc_seg: 96.0789, loss: 0.0927 2023-01-06 10:40:42,415 - mmseg - INFO - Iter [94250/160000] lr: 2.466e-05, eta: 7:56:06, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1022, decode.acc_seg: 95.7387, loss: 0.1022 2023-01-06 10:41:03,483 - mmseg - INFO - Iter [94300/160000] lr: 2.464e-05, eta: 7:55:43, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1026, decode.acc_seg: 95.7664, loss: 0.1026 2023-01-06 10:41:24,287 - mmseg - INFO - Iter [94350/160000] lr: 2.462e-05, eta: 7:55:21, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0970, decode.acc_seg: 95.9976, loss: 0.0970 2023-01-06 10:41:45,055 - mmseg - INFO - Iter [94400/160000] lr: 2.460e-05, eta: 7:54:59, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0997, decode.acc_seg: 95.8789, loss: 0.0997 2023-01-06 10:42:05,803 - mmseg - INFO - Iter [94450/160000] lr: 2.458e-05, eta: 7:54:36, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0968, decode.acc_seg: 95.9059, loss: 0.0968 2023-01-06 10:42:29,000 - mmseg - INFO - Iter [94500/160000] lr: 2.456e-05, eta: 7:54:15, time: 0.464, data_time: 0.055, memory: 9591, decode.loss_ce: 0.1031, decode.acc_seg: 95.7666, loss: 0.1031 2023-01-06 10:42:50,539 - mmseg - INFO - Iter [94550/160000] lr: 2.454e-05, eta: 7:53:54, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0943, decode.acc_seg: 95.8812, loss: 0.0943 2023-01-06 10:43:11,612 - mmseg - INFO - Iter [94600/160000] lr: 2.453e-05, eta: 7:53:31, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0996, decode.acc_seg: 95.8187, loss: 0.0996 2023-01-06 10:43:32,692 - mmseg - INFO - Iter [94650/160000] lr: 2.451e-05, eta: 7:53:09, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0984, decode.acc_seg: 95.9427, loss: 0.0984 2023-01-06 10:43:53,924 - mmseg - INFO - Iter [94700/160000] lr: 2.449e-05, eta: 7:52:47, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0961, decode.acc_seg: 95.9701, loss: 0.0961 2023-01-06 10:44:14,721 - mmseg - INFO - Iter [94750/160000] lr: 2.447e-05, eta: 7:52:25, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1114, decode.acc_seg: 95.5514, loss: 0.1114 2023-01-06 10:44:35,598 - mmseg - INFO - Iter [94800/160000] lr: 2.445e-05, eta: 7:52:03, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1063, decode.acc_seg: 95.6276, loss: 0.1063 2023-01-06 10:44:56,288 - mmseg - INFO - Iter [94850/160000] lr: 2.443e-05, eta: 7:51:40, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1047, decode.acc_seg: 95.7591, loss: 0.1047 2023-01-06 10:45:19,150 - mmseg - INFO - Iter [94900/160000] lr: 2.441e-05, eta: 7:51:19, time: 0.457, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1018, decode.acc_seg: 95.8017, loss: 0.1018 2023-01-06 10:45:40,481 - mmseg - INFO - Iter [94950/160000] lr: 2.439e-05, eta: 7:50:57, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1034, decode.acc_seg: 95.5923, loss: 0.1034 2023-01-06 10:46:01,133 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:46:01,133 - mmseg - INFO - Iter [95000/160000] lr: 2.438e-05, eta: 7:50:35, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1053, decode.acc_seg: 95.5945, loss: 0.1053 2023-01-06 10:46:22,297 - mmseg - INFO - Iter [95050/160000] lr: 2.436e-05, eta: 7:50:13, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0932, decode.acc_seg: 96.0898, loss: 0.0932 2023-01-06 10:46:43,527 - mmseg - INFO - Iter [95100/160000] lr: 2.434e-05, eta: 7:49:51, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1010, decode.acc_seg: 95.7889, loss: 0.1010 2023-01-06 10:47:04,285 - mmseg - INFO - Iter [95150/160000] lr: 2.432e-05, eta: 7:49:28, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1072, decode.acc_seg: 95.5651, loss: 0.1072 2023-01-06 10:47:25,271 - mmseg - INFO - Iter [95200/160000] lr: 2.430e-05, eta: 7:49:06, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0976, decode.acc_seg: 95.8719, loss: 0.0976 2023-01-06 10:47:48,625 - mmseg - INFO - Iter [95250/160000] lr: 2.428e-05, eta: 7:48:45, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1048, decode.acc_seg: 95.7105, loss: 0.1048 2023-01-06 10:48:09,293 - mmseg - INFO - Iter [95300/160000] lr: 2.426e-05, eta: 7:48:23, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1034, decode.acc_seg: 95.6622, loss: 0.1034 2023-01-06 10:48:30,137 - mmseg - INFO - Iter [95350/160000] lr: 2.424e-05, eta: 7:48:01, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1007, decode.acc_seg: 95.8137, loss: 0.1007 2023-01-06 10:48:51,152 - mmseg - INFO - Iter [95400/160000] lr: 2.423e-05, eta: 7:47:38, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0961, decode.acc_seg: 95.9366, loss: 0.0961 2023-01-06 10:49:11,918 - mmseg - INFO - Iter [95450/160000] lr: 2.421e-05, eta: 7:47:16, time: 0.416, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0979, decode.acc_seg: 95.8256, loss: 0.0979 2023-01-06 10:49:33,491 - mmseg - INFO - Iter [95500/160000] lr: 2.419e-05, eta: 7:46:54, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0957, decode.acc_seg: 95.9127, loss: 0.0957 2023-01-06 10:49:54,124 - mmseg - INFO - Iter [95550/160000] lr: 2.417e-05, eta: 7:46:32, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0928, decode.acc_seg: 96.0402, loss: 0.0928 2023-01-06 10:50:15,139 - mmseg - INFO - Iter [95600/160000] lr: 2.415e-05, eta: 7:46:10, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0977, decode.acc_seg: 95.8247, loss: 0.0977 2023-01-06 10:50:38,595 - mmseg - INFO - Iter [95650/160000] lr: 2.413e-05, eta: 7:45:49, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1090, decode.acc_seg: 95.4992, loss: 0.1090 2023-01-06 10:50:59,537 - mmseg - INFO - Iter [95700/160000] lr: 2.411e-05, eta: 7:45:27, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0981, decode.acc_seg: 95.8186, loss: 0.0981 2023-01-06 10:51:20,767 - mmseg - INFO - Iter [95750/160000] lr: 2.409e-05, eta: 7:45:05, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0966, decode.acc_seg: 95.9983, loss: 0.0966 2023-01-06 10:51:41,675 - mmseg - INFO - Iter [95800/160000] lr: 2.408e-05, eta: 7:44:43, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0950, decode.acc_seg: 95.9624, loss: 0.0950 2023-01-06 10:52:02,402 - mmseg - INFO - Iter [95850/160000] lr: 2.406e-05, eta: 7:44:20, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1016, decode.acc_seg: 95.8228, loss: 0.1016 2023-01-06 10:52:23,708 - mmseg - INFO - Iter [95900/160000] lr: 2.404e-05, eta: 7:43:58, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0911, decode.acc_seg: 96.1849, loss: 0.0911 2023-01-06 10:52:44,618 - mmseg - INFO - Iter [95950/160000] lr: 2.402e-05, eta: 7:43:36, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1007, decode.acc_seg: 95.7025, loss: 0.1007 2023-01-06 10:53:08,086 - mmseg - INFO - Saving checkpoint at 96000 iterations 2023-01-06 10:53:11,787 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:53:11,788 - mmseg - INFO - Iter [96000/160000] lr: 2.400e-05, eta: 7:43:18, time: 0.544, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1016, decode.acc_seg: 95.8629, loss: 0.1016 2023-01-06 10:53:40,022 - mmseg - INFO - per class results: 2023-01-06 10:53:40,025 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 97.85 | 98.87 | | sidewalk | 82.56 | 91.1 | | building | 91.51 | 95.98 | | wall | 49.34 | 56.97 | | fence | 54.65 | 73.57 | | pole | 59.92 | 69.51 | | traffic light | 63.61 | 75.67 | | traffic sign | 73.35 | 81.72 | | vegetation | 91.83 | 96.44 | | terrain | 60.43 | 67.26 | | sky | 94.16 | 98.32 | | person | 76.99 | 89.76 | | rider | 52.83 | 63.25 | | car | 93.31 | 97.22 | | truck | 60.97 | 66.38 | | bus | 70.68 | 78.44 | | train | 62.86 | 79.22 | | motorcycle | 40.67 | 47.46 | | bicycle | 71.95 | 83.92 | +---------------+-------+-------+ 2023-01-06 10:53:40,025 - mmseg - INFO - Summary: 2023-01-06 10:53:40,025 - mmseg - INFO - +-------+-------+-------+ | aAcc | mIoU | mAcc | +-------+-------+-------+ | 95.36 | 71.02 | 79.53 | +-------+-------+-------+ 2023-01-06 10:53:40,026 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 10:53:40,026 - mmseg - INFO - Iter(val) [63] aAcc: 0.9536, mIoU: 0.7102, mAcc: 0.7953, IoU.road: 0.9785, IoU.sidewalk: 0.8256, IoU.building: 0.9151, IoU.wall: 0.4934, IoU.fence: 0.5465, IoU.pole: 0.5992, IoU.traffic light: 0.6361, IoU.traffic sign: 0.7335, IoU.vegetation: 0.9183, IoU.terrain: 0.6043, IoU.sky: 0.9416, IoU.person: 0.7699, IoU.rider: 0.5283, IoU.car: 0.9331, IoU.truck: 0.6097, IoU.bus: 0.7068, IoU.train: 0.6286, IoU.motorcycle: 0.4067, IoU.bicycle: 0.7195, Acc.road: 0.9887, Acc.sidewalk: 0.9110, Acc.building: 0.9598, Acc.wall: 0.5697, Acc.fence: 0.7357, Acc.pole: 0.6951, Acc.traffic light: 0.7567, Acc.traffic sign: 0.8172, Acc.vegetation: 0.9644, Acc.terrain: 0.6726, Acc.sky: 0.9832, Acc.person: 0.8976, Acc.rider: 0.6325, Acc.car: 0.9722, Acc.truck: 0.6638, Acc.bus: 0.7844, Acc.train: 0.7922, Acc.motorcycle: 0.4746, Acc.bicycle: 0.8392 2023-01-06 10:54:00,802 - mmseg - INFO - Iter [96050/160000] lr: 2.398e-05, eta: 7:43:14, time: 0.980, data_time: 0.576, memory: 9591, decode.loss_ce: 0.0927, decode.acc_seg: 96.0004, loss: 0.0927 2023-01-06 10:54:22,333 - mmseg - INFO - Iter [96100/160000] lr: 2.396e-05, eta: 7:42:52, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0981, decode.acc_seg: 95.9040, loss: 0.0981 2023-01-06 10:54:43,118 - mmseg - INFO - Iter [96150/160000] lr: 2.394e-05, eta: 7:42:30, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1062, decode.acc_seg: 95.6125, loss: 0.1062 2023-01-06 10:55:04,106 - mmseg - INFO - Iter [96200/160000] lr: 2.393e-05, eta: 7:42:08, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1162, decode.acc_seg: 95.2922, loss: 0.1162 2023-01-06 10:55:25,630 - mmseg - INFO - Iter [96250/160000] lr: 2.391e-05, eta: 7:41:46, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1074, decode.acc_seg: 95.6367, loss: 0.1074 2023-01-06 10:55:46,293 - mmseg - INFO - Iter [96300/160000] lr: 2.389e-05, eta: 7:41:24, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1001, decode.acc_seg: 95.8429, loss: 0.1001 2023-01-06 10:56:09,544 - mmseg - INFO - Iter [96350/160000] lr: 2.387e-05, eta: 7:41:03, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0948, decode.acc_seg: 95.9429, loss: 0.0948 2023-01-06 10:56:30,450 - mmseg - INFO - Iter [96400/160000] lr: 2.385e-05, eta: 7:40:41, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0932, decode.acc_seg: 96.1011, loss: 0.0932 2023-01-06 10:56:51,491 - mmseg - INFO - Iter [96450/160000] lr: 2.383e-05, eta: 7:40:18, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1010, decode.acc_seg: 95.8506, loss: 0.1010 2023-01-06 10:57:12,176 - mmseg - INFO - Iter [96500/160000] lr: 2.381e-05, eta: 7:39:56, time: 0.414, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0979, decode.acc_seg: 95.9510, loss: 0.0979 2023-01-06 10:57:33,411 - mmseg - INFO - Iter [96550/160000] lr: 2.379e-05, eta: 7:39:34, time: 0.424, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0956, decode.acc_seg: 96.0766, loss: 0.0956 2023-01-06 10:57:54,336 - mmseg - INFO - Iter [96600/160000] lr: 2.378e-05, eta: 7:39:12, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1034, decode.acc_seg: 95.8016, loss: 0.1034 2023-01-06 10:58:15,245 - mmseg - INFO - Iter [96650/160000] lr: 2.376e-05, eta: 7:38:49, time: 0.418, data_time: 0.010, memory: 9591, decode.loss_ce: 0.1058, decode.acc_seg: 95.6493, loss: 0.1058 2023-01-06 10:58:37,152 - mmseg - INFO - Iter [96700/160000] lr: 2.374e-05, eta: 7:38:28, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1024, decode.acc_seg: 95.7269, loss: 0.1024 2023-01-06 10:59:01,160 - mmseg - INFO - Iter [96750/160000] lr: 2.372e-05, eta: 7:38:08, time: 0.481, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1084, decode.acc_seg: 95.5586, loss: 0.1084 2023-01-06 10:59:22,594 - mmseg - INFO - Iter [96800/160000] lr: 2.370e-05, eta: 7:37:46, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1020, decode.acc_seg: 95.6518, loss: 0.1020 2023-01-06 10:59:43,452 - mmseg - INFO - Iter [96850/160000] lr: 2.368e-05, eta: 7:37:23, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0973, decode.acc_seg: 95.8733, loss: 0.0973 2023-01-06 11:00:05,180 - mmseg - INFO - Iter [96900/160000] lr: 2.366e-05, eta: 7:37:02, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0928, decode.acc_seg: 96.0374, loss: 0.0928 2023-01-06 11:00:26,986 - mmseg - INFO - Iter [96950/160000] lr: 2.364e-05, eta: 7:36:40, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0979, decode.acc_seg: 95.8986, loss: 0.0979 2023-01-06 11:00:48,114 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:00:48,115 - mmseg - INFO - Iter [97000/160000] lr: 2.363e-05, eta: 7:36:18, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1041, decode.acc_seg: 95.6763, loss: 0.1041 2023-01-06 11:01:09,076 - mmseg - INFO - Iter [97050/160000] lr: 2.361e-05, eta: 7:35:56, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0980, decode.acc_seg: 95.9593, loss: 0.0980 2023-01-06 11:01:32,682 - mmseg - INFO - Iter [97100/160000] lr: 2.359e-05, eta: 7:35:35, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.8211, loss: 0.0985 2023-01-06 11:01:54,584 - mmseg - INFO - Iter [97150/160000] lr: 2.357e-05, eta: 7:35:13, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0969, decode.acc_seg: 95.8653, loss: 0.0969 2023-01-06 11:02:16,048 - mmseg - INFO - Iter [97200/160000] lr: 2.355e-05, eta: 7:34:52, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0918, decode.acc_seg: 96.0091, loss: 0.0918 2023-01-06 11:02:36,756 - mmseg - INFO - Iter [97250/160000] lr: 2.353e-05, eta: 7:34:29, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0953, decode.acc_seg: 96.0355, loss: 0.0953 2023-01-06 11:02:57,873 - mmseg - INFO - Iter [97300/160000] lr: 2.351e-05, eta: 7:34:07, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0957, decode.acc_seg: 95.9716, loss: 0.0957 2023-01-06 11:03:18,829 - mmseg - INFO - Iter [97350/160000] lr: 2.349e-05, eta: 7:33:45, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0933, decode.acc_seg: 96.0408, loss: 0.0933 2023-01-06 11:03:39,690 - mmseg - INFO - Iter [97400/160000] lr: 2.348e-05, eta: 7:33:23, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.1081, loss: 0.0915 2023-01-06 11:04:00,335 - mmseg - INFO - Iter [97450/160000] lr: 2.346e-05, eta: 7:33:00, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1016, decode.acc_seg: 95.7451, loss: 0.1016 2023-01-06 11:04:23,558 - mmseg - INFO - Iter [97500/160000] lr: 2.344e-05, eta: 7:32:39, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0969, decode.acc_seg: 95.9201, loss: 0.0969 2023-01-06 11:04:44,302 - mmseg - INFO - Iter [97550/160000] lr: 2.342e-05, eta: 7:32:17, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0970, decode.acc_seg: 95.9959, loss: 0.0970 2023-01-06 11:05:05,087 - mmseg - INFO - Iter [97600/160000] lr: 2.340e-05, eta: 7:31:55, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1001, decode.acc_seg: 95.8645, loss: 0.1001 2023-01-06 11:05:26,083 - mmseg - INFO - Iter [97650/160000] lr: 2.338e-05, eta: 7:31:32, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0973, decode.acc_seg: 95.9608, loss: 0.0973 2023-01-06 11:05:46,940 - mmseg - INFO - Iter [97700/160000] lr: 2.336e-05, eta: 7:31:10, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1013, decode.acc_seg: 95.7948, loss: 0.1013 2023-01-06 11:06:07,579 - mmseg - INFO - Iter [97750/160000] lr: 2.334e-05, eta: 7:30:48, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0937, decode.acc_seg: 96.0385, loss: 0.0937 2023-01-06 11:06:28,550 - mmseg - INFO - Iter [97800/160000] lr: 2.333e-05, eta: 7:30:26, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0952, decode.acc_seg: 96.1567, loss: 0.0952 2023-01-06 11:06:51,825 - mmseg - INFO - Iter [97850/160000] lr: 2.331e-05, eta: 7:30:05, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0948, decode.acc_seg: 96.0780, loss: 0.0948 2023-01-06 11:07:12,605 - mmseg - INFO - Iter [97900/160000] lr: 2.329e-05, eta: 7:29:42, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0921, decode.acc_seg: 96.1451, loss: 0.0921 2023-01-06 11:07:33,292 - mmseg - INFO - Iter [97950/160000] lr: 2.327e-05, eta: 7:29:20, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0955, decode.acc_seg: 95.8530, loss: 0.0955 2023-01-06 11:07:54,222 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:07:54,223 - mmseg - INFO - Iter [98000/160000] lr: 2.325e-05, eta: 7:28:58, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1026, decode.acc_seg: 95.7970, loss: 0.1026 2023-01-06 11:08:15,011 - mmseg - INFO - Iter [98050/160000] lr: 2.323e-05, eta: 7:28:36, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.9444, loss: 0.0988 2023-01-06 11:08:36,454 - mmseg - INFO - Iter [98100/160000] lr: 2.321e-05, eta: 7:28:14, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0974, decode.acc_seg: 95.9367, loss: 0.0974 2023-01-06 11:08:57,107 - mmseg - INFO - Iter [98150/160000] lr: 2.319e-05, eta: 7:27:51, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0981, decode.acc_seg: 95.9107, loss: 0.0981 2023-01-06 11:09:18,258 - mmseg - INFO - Iter [98200/160000] lr: 2.318e-05, eta: 7:27:29, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0957, decode.acc_seg: 96.0588, loss: 0.0957 2023-01-06 11:09:41,428 - mmseg - INFO - Iter [98250/160000] lr: 2.316e-05, eta: 7:27:08, time: 0.463, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0996, decode.acc_seg: 95.8584, loss: 0.0996 2023-01-06 11:10:02,474 - mmseg - INFO - Iter [98300/160000] lr: 2.314e-05, eta: 7:26:46, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.8380, loss: 0.0985 2023-01-06 11:10:23,773 - mmseg - INFO - Iter [98350/160000] lr: 2.312e-05, eta: 7:26:24, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0945, decode.acc_seg: 96.0438, loss: 0.0945 2023-01-06 11:10:44,684 - mmseg - INFO - Iter [98400/160000] lr: 2.310e-05, eta: 7:26:02, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1015, decode.acc_seg: 95.8341, loss: 0.1015 2023-01-06 11:11:05,977 - mmseg - INFO - Iter [98450/160000] lr: 2.308e-05, eta: 7:25:40, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0911, decode.acc_seg: 96.1447, loss: 0.0911 2023-01-06 11:11:26,934 - mmseg - INFO - Iter [98500/160000] lr: 2.306e-05, eta: 7:25:18, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0918, decode.acc_seg: 96.1510, loss: 0.0918 2023-01-06 11:11:47,909 - mmseg - INFO - Iter [98550/160000] lr: 2.304e-05, eta: 7:24:56, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0953, decode.acc_seg: 96.0770, loss: 0.0953 2023-01-06 11:12:11,101 - mmseg - INFO - Iter [98600/160000] lr: 2.303e-05, eta: 7:24:35, time: 0.464, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.8868, loss: 0.0985 2023-01-06 11:12:32,294 - mmseg - INFO - Iter [98650/160000] lr: 2.301e-05, eta: 7:24:13, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0986, decode.acc_seg: 95.9218, loss: 0.0986 2023-01-06 11:12:53,615 - mmseg - INFO - Iter [98700/160000] lr: 2.299e-05, eta: 7:23:51, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0935, decode.acc_seg: 96.1183, loss: 0.0935 2023-01-06 11:13:15,662 - mmseg - INFO - Iter [98750/160000] lr: 2.297e-05, eta: 7:23:29, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0961, decode.acc_seg: 96.0525, loss: 0.0961 2023-01-06 11:13:37,328 - mmseg - INFO - Iter [98800/160000] lr: 2.295e-05, eta: 7:23:07, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0951, decode.acc_seg: 95.9747, loss: 0.0951 2023-01-06 11:13:58,335 - mmseg - INFO - Iter [98850/160000] lr: 2.293e-05, eta: 7:22:45, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1009, decode.acc_seg: 95.8344, loss: 0.1009 2023-01-06 11:14:19,354 - mmseg - INFO - Iter [98900/160000] lr: 2.291e-05, eta: 7:22:23, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0958, decode.acc_seg: 95.8951, loss: 0.0958 2023-01-06 11:14:40,700 - mmseg - INFO - Iter [98950/160000] lr: 2.289e-05, eta: 7:22:01, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0948, decode.acc_seg: 95.9005, loss: 0.0948 2023-01-06 11:15:04,754 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:15:04,754 - mmseg - INFO - Iter [99000/160000] lr: 2.288e-05, eta: 7:21:41, time: 0.481, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0955, decode.acc_seg: 95.9335, loss: 0.0955 2023-01-06 11:15:26,795 - mmseg - INFO - Iter [99050/160000] lr: 2.286e-05, eta: 7:21:19, time: 0.441, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0959, decode.acc_seg: 95.9861, loss: 0.0959 2023-01-06 11:15:48,537 - mmseg - INFO - Iter [99100/160000] lr: 2.284e-05, eta: 7:20:58, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0948, decode.acc_seg: 96.0489, loss: 0.0948 2023-01-06 11:16:09,146 - mmseg - INFO - Iter [99150/160000] lr: 2.282e-05, eta: 7:20:35, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.0594, loss: 0.0915 2023-01-06 11:16:30,250 - mmseg - INFO - Iter [99200/160000] lr: 2.280e-05, eta: 7:20:13, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0945, decode.acc_seg: 96.0733, loss: 0.0945 2023-01-06 11:16:52,202 - mmseg - INFO - Iter [99250/160000] lr: 2.278e-05, eta: 7:19:52, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0955, decode.acc_seg: 95.9969, loss: 0.0955 2023-01-06 11:17:13,859 - mmseg - INFO - Iter [99300/160000] lr: 2.276e-05, eta: 7:19:30, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0946, decode.acc_seg: 96.0253, loss: 0.0946 2023-01-06 11:17:37,260 - mmseg - INFO - Iter [99350/160000] lr: 2.274e-05, eta: 7:19:09, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.8725, loss: 0.0988 2023-01-06 11:17:58,091 - mmseg - INFO - Iter [99400/160000] lr: 2.273e-05, eta: 7:18:47, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1019, decode.acc_seg: 95.8302, loss: 0.1019 2023-01-06 11:18:19,736 - mmseg - INFO - Iter [99450/160000] lr: 2.271e-05, eta: 7:18:25, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0919, decode.acc_seg: 96.1842, loss: 0.0919 2023-01-06 11:18:40,445 - mmseg - INFO - Iter [99500/160000] lr: 2.269e-05, eta: 7:18:03, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0979, decode.acc_seg: 95.9806, loss: 0.0979 2023-01-06 11:19:01,236 - mmseg - INFO - Iter [99550/160000] lr: 2.267e-05, eta: 7:17:40, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0966, decode.acc_seg: 95.8944, loss: 0.0966 2023-01-06 11:19:21,976 - mmseg - INFO - Iter [99600/160000] lr: 2.265e-05, eta: 7:17:18, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0982, decode.acc_seg: 95.8842, loss: 0.0982 2023-01-06 11:19:43,454 - mmseg - INFO - Iter [99650/160000] lr: 2.263e-05, eta: 7:16:56, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.8975, loss: 0.0985 2023-01-06 11:20:07,361 - mmseg - INFO - Iter [99700/160000] lr: 2.261e-05, eta: 7:16:36, time: 0.479, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0951, decode.acc_seg: 96.0189, loss: 0.0951 2023-01-06 11:20:28,302 - mmseg - INFO - Iter [99750/160000] lr: 2.259e-05, eta: 7:16:14, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0970, decode.acc_seg: 95.9739, loss: 0.0970 2023-01-06 11:20:49,046 - mmseg - INFO - Iter [99800/160000] lr: 2.258e-05, eta: 7:15:51, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0934, decode.acc_seg: 96.1618, loss: 0.0934 2023-01-06 11:21:10,682 - mmseg - INFO - Iter [99850/160000] lr: 2.256e-05, eta: 7:15:30, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1009, decode.acc_seg: 95.8821, loss: 0.1009 2023-01-06 11:21:31,794 - mmseg - INFO - Iter [99900/160000] lr: 2.254e-05, eta: 7:15:08, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0959, decode.acc_seg: 95.9111, loss: 0.0959 2023-01-06 11:21:52,720 - mmseg - INFO - Iter [99950/160000] lr: 2.252e-05, eta: 7:14:45, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1003, decode.acc_seg: 95.8905, loss: 0.1003 2023-01-06 11:22:14,404 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:22:14,404 - mmseg - INFO - Iter [100000/160000] lr: 2.250e-05, eta: 7:14:24, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0968, decode.acc_seg: 95.9761, loss: 0.0968 2023-01-06 11:22:35,397 - mmseg - INFO - Iter [100050/160000] lr: 2.248e-05, eta: 7:14:01, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0969, decode.acc_seg: 95.8954, loss: 0.0969 2023-01-06 11:22:59,372 - mmseg - INFO - Iter [100100/160000] lr: 2.246e-05, eta: 7:13:41, time: 0.479, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0927, decode.acc_seg: 96.0117, loss: 0.0927 2023-01-06 11:23:20,240 - mmseg - INFO - Iter [100150/160000] lr: 2.244e-05, eta: 7:13:19, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0925, decode.acc_seg: 96.0776, loss: 0.0925 2023-01-06 11:23:41,131 - mmseg - INFO - Iter [100200/160000] lr: 2.243e-05, eta: 7:12:57, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0960, decode.acc_seg: 95.8931, loss: 0.0960 2023-01-06 11:24:01,803 - mmseg - INFO - Iter [100250/160000] lr: 2.241e-05, eta: 7:12:34, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0958, decode.acc_seg: 96.1033, loss: 0.0958 2023-01-06 11:24:22,751 - mmseg - INFO - Iter [100300/160000] lr: 2.239e-05, eta: 7:12:12, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0959, decode.acc_seg: 96.0192, loss: 0.0959 2023-01-06 11:24:43,897 - mmseg - INFO - Iter [100350/160000] lr: 2.237e-05, eta: 7:11:50, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0941, decode.acc_seg: 96.0762, loss: 0.0941 2023-01-06 11:25:05,583 - mmseg - INFO - Iter [100400/160000] lr: 2.235e-05, eta: 7:11:28, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0939, decode.acc_seg: 96.0624, loss: 0.0939 2023-01-06 11:25:28,855 - mmseg - INFO - Iter [100450/160000] lr: 2.233e-05, eta: 7:11:07, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0984, decode.acc_seg: 95.9065, loss: 0.0984 2023-01-06 11:25:51,074 - mmseg - INFO - Iter [100500/160000] lr: 2.231e-05, eta: 7:10:46, time: 0.445, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0963, decode.acc_seg: 96.0397, loss: 0.0963 2023-01-06 11:26:12,011 - mmseg - INFO - Iter [100550/160000] lr: 2.229e-05, eta: 7:10:24, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0970, decode.acc_seg: 96.0064, loss: 0.0970 2023-01-06 11:26:33,450 - mmseg - INFO - Iter [100600/160000] lr: 2.228e-05, eta: 7:10:02, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0968, decode.acc_seg: 95.9926, loss: 0.0968 2023-01-06 11:26:54,955 - mmseg - INFO - Iter [100650/160000] lr: 2.226e-05, eta: 7:09:40, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0957, decode.acc_seg: 96.0072, loss: 0.0957 2023-01-06 11:27:16,277 - mmseg - INFO - Iter [100700/160000] lr: 2.224e-05, eta: 7:09:18, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0983, decode.acc_seg: 95.9355, loss: 0.0983 2023-01-06 11:27:36,899 - mmseg - INFO - Iter [100750/160000] lr: 2.222e-05, eta: 7:08:56, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0940, decode.acc_seg: 95.9438, loss: 0.0940 2023-01-06 11:27:57,857 - mmseg - INFO - Iter [100800/160000] lr: 2.220e-05, eta: 7:08:34, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1008, decode.acc_seg: 95.7571, loss: 0.1008 2023-01-06 11:28:21,520 - mmseg - INFO - Iter [100850/160000] lr: 2.218e-05, eta: 7:08:13, time: 0.473, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0930, decode.acc_seg: 96.1321, loss: 0.0930 2023-01-06 11:28:42,644 - mmseg - INFO - Iter [100900/160000] lr: 2.216e-05, eta: 7:07:51, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.9596, loss: 0.0985 2023-01-06 11:29:03,841 - mmseg - INFO - Iter [100950/160000] lr: 2.214e-05, eta: 7:07:29, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1025, decode.acc_seg: 95.7872, loss: 0.1025 2023-01-06 11:29:24,759 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:29:24,760 - mmseg - INFO - Iter [101000/160000] lr: 2.213e-05, eta: 7:07:07, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0912, decode.acc_seg: 96.1019, loss: 0.0912 2023-01-06 11:29:46,301 - mmseg - INFO - Iter [101050/160000] lr: 2.211e-05, eta: 7:06:45, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0968, decode.acc_seg: 96.0583, loss: 0.0968 2023-01-06 11:30:07,067 - mmseg - INFO - Iter [101100/160000] lr: 2.209e-05, eta: 7:06:23, time: 0.416, data_time: 0.012, memory: 9591, decode.loss_ce: 0.1133, decode.acc_seg: 95.4214, loss: 0.1133 2023-01-06 11:30:27,770 - mmseg - INFO - Iter [101150/160000] lr: 2.207e-05, eta: 7:06:00, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1029, decode.acc_seg: 95.7828, loss: 0.1029 2023-01-06 11:30:50,783 - mmseg - INFO - Iter [101200/160000] lr: 2.205e-05, eta: 7:05:39, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1010, decode.acc_seg: 95.7888, loss: 0.1010 2023-01-06 11:31:11,551 - mmseg - INFO - Iter [101250/160000] lr: 2.203e-05, eta: 7:05:17, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1001, decode.acc_seg: 95.8709, loss: 0.1001 2023-01-06 11:31:32,510 - mmseg - INFO - Iter [101300/160000] lr: 2.201e-05, eta: 7:04:55, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0938, decode.acc_seg: 96.0081, loss: 0.0938 2023-01-06 11:31:53,863 - mmseg - INFO - Iter [101350/160000] lr: 2.199e-05, eta: 7:04:33, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0936, decode.acc_seg: 96.0835, loss: 0.0936 2023-01-06 11:32:14,632 - mmseg - INFO - Iter [101400/160000] lr: 2.198e-05, eta: 7:04:11, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0967, decode.acc_seg: 95.9840, loss: 0.0967 2023-01-06 11:32:35,859 - mmseg - INFO - Iter [101450/160000] lr: 2.196e-05, eta: 7:03:49, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0964, decode.acc_seg: 95.9213, loss: 0.0964 2023-01-06 11:32:56,822 - mmseg - INFO - Iter [101500/160000] lr: 2.194e-05, eta: 7:03:27, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0958, decode.acc_seg: 95.9758, loss: 0.0958 2023-01-06 11:33:17,441 - mmseg - INFO - Iter [101550/160000] lr: 2.192e-05, eta: 7:03:04, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0914, decode.acc_seg: 96.1812, loss: 0.0914 2023-01-06 11:33:40,703 - mmseg - INFO - Iter [101600/160000] lr: 2.190e-05, eta: 7:02:44, time: 0.465, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0899, decode.acc_seg: 96.1716, loss: 0.0899 2023-01-06 11:34:02,079 - mmseg - INFO - Iter [101650/160000] lr: 2.188e-05, eta: 7:02:22, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0956, decode.acc_seg: 96.0848, loss: 0.0956 2023-01-06 11:34:23,353 - mmseg - INFO - Iter [101700/160000] lr: 2.186e-05, eta: 7:02:00, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0933, decode.acc_seg: 96.0761, loss: 0.0933 2023-01-06 11:34:44,497 - mmseg - INFO - Iter [101750/160000] lr: 2.184e-05, eta: 7:01:38, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0952, decode.acc_seg: 96.0028, loss: 0.0952 2023-01-06 11:35:05,291 - mmseg - INFO - Iter [101800/160000] lr: 2.183e-05, eta: 7:01:15, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1041, decode.acc_seg: 95.8525, loss: 0.1041 2023-01-06 11:35:27,236 - mmseg - INFO - Iter [101850/160000] lr: 2.181e-05, eta: 7:00:54, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0999, decode.acc_seg: 95.9589, loss: 0.0999 2023-01-06 11:35:48,433 - mmseg - INFO - Iter [101900/160000] lr: 2.179e-05, eta: 7:00:32, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1107, decode.acc_seg: 95.8213, loss: 0.1107 2023-01-06 11:36:11,300 - mmseg - INFO - Iter [101950/160000] lr: 2.177e-05, eta: 7:00:11, time: 0.457, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1055, decode.acc_seg: 95.7802, loss: 0.1055 2023-01-06 11:36:33,517 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:36:33,517 - mmseg - INFO - Iter [102000/160000] lr: 2.175e-05, eta: 6:59:49, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.6752, loss: 0.0988 2023-01-06 11:36:54,932 - mmseg - INFO - Iter [102050/160000] lr: 2.173e-05, eta: 6:59:27, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0963, decode.acc_seg: 95.9636, loss: 0.0963 2023-01-06 11:37:16,033 - mmseg - INFO - Iter [102100/160000] lr: 2.171e-05, eta: 6:59:05, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0958, decode.acc_seg: 95.9799, loss: 0.0958 2023-01-06 11:37:37,206 - mmseg - INFO - Iter [102150/160000] lr: 2.169e-05, eta: 6:58:43, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1020, decode.acc_seg: 95.8230, loss: 0.1020 2023-01-06 11:37:58,860 - mmseg - INFO - Iter [102200/160000] lr: 2.168e-05, eta: 6:58:22, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0929, decode.acc_seg: 96.1122, loss: 0.0929 2023-01-06 11:38:20,364 - mmseg - INFO - Iter [102250/160000] lr: 2.166e-05, eta: 6:58:00, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0949, decode.acc_seg: 96.0410, loss: 0.0949 2023-01-06 11:38:41,323 - mmseg - INFO - Iter [102300/160000] lr: 2.164e-05, eta: 6:57:38, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0923, decode.acc_seg: 96.1148, loss: 0.0923 2023-01-06 11:39:04,279 - mmseg - INFO - Iter [102350/160000] lr: 2.162e-05, eta: 6:57:17, time: 0.459, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0949, decode.acc_seg: 96.0204, loss: 0.0949 2023-01-06 11:39:25,921 - mmseg - INFO - Iter [102400/160000] lr: 2.160e-05, eta: 6:56:55, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0973, decode.acc_seg: 95.9707, loss: 0.0973 2023-01-06 11:39:46,729 - mmseg - INFO - Iter [102450/160000] lr: 2.158e-05, eta: 6:56:33, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0931, decode.acc_seg: 96.0496, loss: 0.0931 2023-01-06 11:40:07,535 - mmseg - INFO - Iter [102500/160000] lr: 2.156e-05, eta: 6:56:10, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.9623, loss: 0.0988 2023-01-06 11:40:28,348 - mmseg - INFO - Iter [102550/160000] lr: 2.154e-05, eta: 6:55:48, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0879, decode.acc_seg: 96.2975, loss: 0.0879 2023-01-06 11:40:49,591 - mmseg - INFO - Iter [102600/160000] lr: 2.153e-05, eta: 6:55:26, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0919, decode.acc_seg: 96.0868, loss: 0.0919 2023-01-06 11:41:10,906 - mmseg - INFO - Iter [102650/160000] lr: 2.151e-05, eta: 6:55:04, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0952, decode.acc_seg: 96.0533, loss: 0.0952 2023-01-06 11:41:34,090 - mmseg - INFO - Iter [102700/160000] lr: 2.149e-05, eta: 6:54:43, time: 0.464, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0905, decode.acc_seg: 96.0140, loss: 0.0905 2023-01-06 11:41:54,679 - mmseg - INFO - Iter [102750/160000] lr: 2.147e-05, eta: 6:54:21, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0925, decode.acc_seg: 96.0300, loss: 0.0925 2023-01-06 11:42:15,741 - mmseg - INFO - Iter [102800/160000] lr: 2.145e-05, eta: 6:53:59, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0906, decode.acc_seg: 96.2133, loss: 0.0906 2023-01-06 11:42:36,841 - mmseg - INFO - Iter [102850/160000] lr: 2.143e-05, eta: 6:53:37, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1012, decode.acc_seg: 95.8204, loss: 0.1012 2023-01-06 11:42:57,756 - mmseg - INFO - Iter [102900/160000] lr: 2.141e-05, eta: 6:53:15, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0979, decode.acc_seg: 95.9959, loss: 0.0979 2023-01-06 11:43:18,433 - mmseg - INFO - Iter [102950/160000] lr: 2.139e-05, eta: 6:52:52, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0939, decode.acc_seg: 95.9258, loss: 0.0939 2023-01-06 11:43:39,386 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:43:39,387 - mmseg - INFO - Iter [103000/160000] lr: 2.138e-05, eta: 6:52:30, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0954, decode.acc_seg: 96.0232, loss: 0.0954 2023-01-06 11:44:02,317 - mmseg - INFO - Iter [103050/160000] lr: 2.136e-05, eta: 6:52:09, time: 0.458, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0931, decode.acc_seg: 96.0630, loss: 0.0931 2023-01-06 11:44:23,249 - mmseg - INFO - Iter [103100/160000] lr: 2.134e-05, eta: 6:51:47, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0945, decode.acc_seg: 95.9647, loss: 0.0945 2023-01-06 11:44:44,852 - mmseg - INFO - Iter [103150/160000] lr: 2.132e-05, eta: 6:51:25, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0901, decode.acc_seg: 96.0753, loss: 0.0901 2023-01-06 11:45:05,861 - mmseg - INFO - Iter [103200/160000] lr: 2.130e-05, eta: 6:51:03, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0930, decode.acc_seg: 96.0542, loss: 0.0930 2023-01-06 11:45:26,566 - mmseg - INFO - Iter [103250/160000] lr: 2.128e-05, eta: 6:50:41, time: 0.415, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0970, decode.acc_seg: 96.0405, loss: 0.0970 2023-01-06 11:45:47,592 - mmseg - INFO - Iter [103300/160000] lr: 2.126e-05, eta: 6:50:19, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0972, decode.acc_seg: 95.9798, loss: 0.0972 2023-01-06 11:46:08,669 - mmseg - INFO - Iter [103350/160000] lr: 2.124e-05, eta: 6:49:57, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.2238, loss: 0.0884 2023-01-06 11:46:29,404 - mmseg - INFO - Iter [103400/160000] lr: 2.123e-05, eta: 6:49:35, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0921, decode.acc_seg: 96.1570, loss: 0.0921 2023-01-06 11:46:52,367 - mmseg - INFO - Iter [103450/160000] lr: 2.121e-05, eta: 6:49:14, time: 0.459, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0932, decode.acc_seg: 96.1671, loss: 0.0932 2023-01-06 11:47:13,972 - mmseg - INFO - Iter [103500/160000] lr: 2.119e-05, eta: 6:48:52, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0999, decode.acc_seg: 95.8737, loss: 0.0999 2023-01-06 11:47:35,799 - mmseg - INFO - Iter [103550/160000] lr: 2.117e-05, eta: 6:48:30, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0933, decode.acc_seg: 96.0969, loss: 0.0933 2023-01-06 11:47:56,798 - mmseg - INFO - Iter [103600/160000] lr: 2.115e-05, eta: 6:48:08, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0957, decode.acc_seg: 95.9373, loss: 0.0957 2023-01-06 11:48:17,913 - mmseg - INFO - Iter [103650/160000] lr: 2.113e-05, eta: 6:47:46, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1002, decode.acc_seg: 95.8396, loss: 0.1002 2023-01-06 11:48:38,761 - mmseg - INFO - Iter [103700/160000] lr: 2.111e-05, eta: 6:47:24, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0899, decode.acc_seg: 96.2030, loss: 0.0899 2023-01-06 11:49:00,416 - mmseg - INFO - Iter [103750/160000] lr: 2.109e-05, eta: 6:47:02, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0947, decode.acc_seg: 96.0897, loss: 0.0947 2023-01-06 11:49:24,564 - mmseg - INFO - Iter [103800/160000] lr: 2.108e-05, eta: 6:46:42, time: 0.482, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0933, decode.acc_seg: 96.0547, loss: 0.0933 2023-01-06 11:49:46,503 - mmseg - INFO - Iter [103850/160000] lr: 2.106e-05, eta: 6:46:20, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0944, decode.acc_seg: 96.0183, loss: 0.0944 2023-01-06 11:50:08,014 - mmseg - INFO - Iter [103900/160000] lr: 2.104e-05, eta: 6:45:58, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0942, decode.acc_seg: 95.9900, loss: 0.0942 2023-01-06 11:50:29,130 - mmseg - INFO - Iter [103950/160000] lr: 2.102e-05, eta: 6:45:36, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0992, decode.acc_seg: 95.9892, loss: 0.0992 2023-01-06 11:50:49,874 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:50:49,874 - mmseg - INFO - Iter [104000/160000] lr: 2.100e-05, eta: 6:45:14, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0978, decode.acc_seg: 95.9438, loss: 0.0978 2023-01-06 11:51:12,027 - mmseg - INFO - Iter [104050/160000] lr: 2.098e-05, eta: 6:44:53, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0965, decode.acc_seg: 95.8975, loss: 0.0965 2023-01-06 11:51:32,714 - mmseg - INFO - Iter [104100/160000] lr: 2.096e-05, eta: 6:44:30, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0957, decode.acc_seg: 95.8928, loss: 0.0957 2023-01-06 11:51:54,259 - mmseg - INFO - Iter [104150/160000] lr: 2.094e-05, eta: 6:44:09, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.9220, loss: 0.0988 2023-01-06 11:52:17,467 - mmseg - INFO - Iter [104200/160000] lr: 2.093e-05, eta: 6:43:48, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0953, decode.acc_seg: 96.0313, loss: 0.0953 2023-01-06 11:52:38,453 - mmseg - INFO - Iter [104250/160000] lr: 2.091e-05, eta: 6:43:26, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0912, decode.acc_seg: 96.1747, loss: 0.0912 2023-01-06 11:52:59,699 - mmseg - INFO - Iter [104300/160000] lr: 2.089e-05, eta: 6:43:04, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0912, decode.acc_seg: 96.1703, loss: 0.0912 2023-01-06 11:53:20,438 - mmseg - INFO - Iter [104350/160000] lr: 2.087e-05, eta: 6:42:41, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1000, decode.acc_seg: 95.8282, loss: 0.1000 2023-01-06 11:53:41,544 - mmseg - INFO - Iter [104400/160000] lr: 2.085e-05, eta: 6:42:19, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0967, decode.acc_seg: 95.8812, loss: 0.0967 2023-01-06 11:54:02,433 - mmseg - INFO - Iter [104450/160000] lr: 2.083e-05, eta: 6:41:57, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0973, decode.acc_seg: 95.9261, loss: 0.0973 2023-01-06 11:54:23,747 - mmseg - INFO - Iter [104500/160000] lr: 2.081e-05, eta: 6:41:35, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1005, decode.acc_seg: 95.7593, loss: 0.1005 2023-01-06 11:54:46,892 - mmseg - INFO - Iter [104550/160000] lr: 2.079e-05, eta: 6:41:14, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0921, decode.acc_seg: 96.1848, loss: 0.0921 2023-01-06 11:55:08,584 - mmseg - INFO - Iter [104600/160000] lr: 2.078e-05, eta: 6:40:53, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.1552, loss: 0.0915 2023-01-06 11:55:29,840 - mmseg - INFO - Iter [104650/160000] lr: 2.076e-05, eta: 6:40:31, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0914, decode.acc_seg: 96.1224, loss: 0.0914 2023-01-06 11:55:50,793 - mmseg - INFO - Iter [104700/160000] lr: 2.074e-05, eta: 6:40:09, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0907, decode.acc_seg: 96.1839, loss: 0.0907 2023-01-06 11:56:11,428 - mmseg - INFO - Iter [104750/160000] lr: 2.072e-05, eta: 6:39:46, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0954, decode.acc_seg: 95.9574, loss: 0.0954 2023-01-06 11:56:32,973 - mmseg - INFO - Iter [104800/160000] lr: 2.070e-05, eta: 6:39:24, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0961, decode.acc_seg: 95.9369, loss: 0.0961 2023-01-06 11:56:54,513 - mmseg - INFO - Iter [104850/160000] lr: 2.068e-05, eta: 6:39:03, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0936, decode.acc_seg: 95.9476, loss: 0.0936 2023-01-06 11:57:15,496 - mmseg - INFO - Iter [104900/160000] lr: 2.066e-05, eta: 6:38:41, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0920, decode.acc_seg: 96.1619, loss: 0.0920 2023-01-06 11:57:39,769 - mmseg - INFO - Iter [104950/160000] lr: 2.064e-05, eta: 6:38:20, time: 0.486, data_time: 0.058, memory: 9591, decode.loss_ce: 0.0897, decode.acc_seg: 96.3449, loss: 0.0897 2023-01-06 11:58:00,376 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 11:58:00,377 - mmseg - INFO - Iter [105000/160000] lr: 2.063e-05, eta: 6:37:58, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0967, decode.acc_seg: 95.9180, loss: 0.0967 2023-01-06 11:58:21,808 - mmseg - INFO - Iter [105050/160000] lr: 2.061e-05, eta: 6:37:36, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0966, decode.acc_seg: 95.9034, loss: 0.0966 2023-01-06 11:58:42,564 - mmseg - INFO - Iter [105100/160000] lr: 2.059e-05, eta: 6:37:14, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0993, decode.acc_seg: 95.8918, loss: 0.0993 2023-01-06 11:59:04,296 - mmseg - INFO - Iter [105150/160000] lr: 2.057e-05, eta: 6:36:52, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0970, decode.acc_seg: 95.8588, loss: 0.0970 2023-01-06 11:59:25,394 - mmseg - INFO - Iter [105200/160000] lr: 2.055e-05, eta: 6:36:30, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0887, decode.acc_seg: 96.1887, loss: 0.0887 2023-01-06 11:59:46,986 - mmseg - INFO - Iter [105250/160000] lr: 2.053e-05, eta: 6:36:08, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0936, decode.acc_seg: 96.0971, loss: 0.0936 2023-01-06 12:00:10,452 - mmseg - INFO - Iter [105300/160000] lr: 2.051e-05, eta: 6:35:48, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0885, decode.acc_seg: 96.2305, loss: 0.0885 2023-01-06 12:00:31,369 - mmseg - INFO - Iter [105350/160000] lr: 2.049e-05, eta: 6:35:25, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0940, decode.acc_seg: 96.0492, loss: 0.0940 2023-01-06 12:00:52,720 - mmseg - INFO - Iter [105400/160000] lr: 2.048e-05, eta: 6:35:04, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1004, decode.acc_seg: 95.8484, loss: 0.1004 2023-01-06 12:01:13,478 - mmseg - INFO - Iter [105450/160000] lr: 2.046e-05, eta: 6:34:41, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.1692, loss: 0.0917 2023-01-06 12:01:34,078 - mmseg - INFO - Iter [105500/160000] lr: 2.044e-05, eta: 6:34:19, time: 0.412, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0944, decode.acc_seg: 95.9725, loss: 0.0944 2023-01-06 12:01:55,031 - mmseg - INFO - Iter [105550/160000] lr: 2.042e-05, eta: 6:33:57, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0936, decode.acc_seg: 96.1741, loss: 0.0936 2023-01-06 12:02:16,120 - mmseg - INFO - Iter [105600/160000] lr: 2.040e-05, eta: 6:33:35, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0887, decode.acc_seg: 96.1375, loss: 0.0887 2023-01-06 12:02:40,088 - mmseg - INFO - Iter [105650/160000] lr: 2.038e-05, eta: 6:33:14, time: 0.479, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0934, decode.acc_seg: 95.9927, loss: 0.0934 2023-01-06 12:03:01,093 - mmseg - INFO - Iter [105700/160000] lr: 2.036e-05, eta: 6:32:52, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0975, decode.acc_seg: 95.9879, loss: 0.0975 2023-01-06 12:03:21,705 - mmseg - INFO - Iter [105750/160000] lr: 2.034e-05, eta: 6:32:30, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.1471, loss: 0.0900 2023-01-06 12:03:42,633 - mmseg - INFO - Iter [105800/160000] lr: 2.033e-05, eta: 6:32:08, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.2359, loss: 0.0874 2023-01-06 12:04:03,935 - mmseg - INFO - Iter [105850/160000] lr: 2.031e-05, eta: 6:31:46, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0892, decode.acc_seg: 96.2864, loss: 0.0892 2023-01-06 12:04:25,045 - mmseg - INFO - Iter [105900/160000] lr: 2.029e-05, eta: 6:31:24, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0952, decode.acc_seg: 95.9562, loss: 0.0952 2023-01-06 12:04:46,614 - mmseg - INFO - Iter [105950/160000] lr: 2.027e-05, eta: 6:31:02, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0994, decode.acc_seg: 95.9008, loss: 0.0994 2023-01-06 12:05:08,273 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:05:08,274 - mmseg - INFO - Iter [106000/160000] lr: 2.025e-05, eta: 6:30:41, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.9222, loss: 0.0985 2023-01-06 12:05:31,683 - mmseg - INFO - Iter [106050/160000] lr: 2.023e-05, eta: 6:30:20, time: 0.468, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0939, decode.acc_seg: 96.0803, loss: 0.0939 2023-01-06 12:05:52,397 - mmseg - INFO - Iter [106100/160000] lr: 2.021e-05, eta: 6:29:58, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.2222, loss: 0.0884 2023-01-06 12:06:13,205 - mmseg - INFO - Iter [106150/160000] lr: 2.019e-05, eta: 6:29:35, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0966, decode.acc_seg: 95.8715, loss: 0.0966 2023-01-06 12:06:34,283 - mmseg - INFO - Iter [106200/160000] lr: 2.018e-05, eta: 6:29:13, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0929, decode.acc_seg: 96.0749, loss: 0.0929 2023-01-06 12:06:55,117 - mmseg - INFO - Iter [106250/160000] lr: 2.016e-05, eta: 6:28:51, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0975, decode.acc_seg: 95.9757, loss: 0.0975 2023-01-06 12:07:15,829 - mmseg - INFO - Iter [106300/160000] lr: 2.014e-05, eta: 6:28:29, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0919, decode.acc_seg: 96.0797, loss: 0.0919 2023-01-06 12:07:36,902 - mmseg - INFO - Iter [106350/160000] lr: 2.012e-05, eta: 6:28:07, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.8286, loss: 0.0988 2023-01-06 12:08:00,174 - mmseg - INFO - Iter [106400/160000] lr: 2.010e-05, eta: 6:27:46, time: 0.465, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0962, decode.acc_seg: 96.0543, loss: 0.0962 2023-01-06 12:08:21,294 - mmseg - INFO - Iter [106450/160000] lr: 2.008e-05, eta: 6:27:24, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0856, decode.acc_seg: 96.2712, loss: 0.0856 2023-01-06 12:08:42,166 - mmseg - INFO - Iter [106500/160000] lr: 2.006e-05, eta: 6:27:02, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0897, decode.acc_seg: 96.2534, loss: 0.0897 2023-01-06 12:09:03,092 - mmseg - INFO - Iter [106550/160000] lr: 2.004e-05, eta: 6:26:40, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0914, decode.acc_seg: 96.0111, loss: 0.0914 2023-01-06 12:09:24,455 - mmseg - INFO - Iter [106600/160000] lr: 2.003e-05, eta: 6:26:18, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0932, decode.acc_seg: 96.0006, loss: 0.0932 2023-01-06 12:09:45,570 - mmseg - INFO - Iter [106650/160000] lr: 2.001e-05, eta: 6:25:56, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0945, decode.acc_seg: 95.9553, loss: 0.0945 2023-01-06 12:10:06,356 - mmseg - INFO - Iter [106700/160000] lr: 1.999e-05, eta: 6:25:34, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0950, decode.acc_seg: 95.9786, loss: 0.0950 2023-01-06 12:10:27,023 - mmseg - INFO - Iter [106750/160000] lr: 1.997e-05, eta: 6:25:12, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1003, decode.acc_seg: 95.9757, loss: 0.1003 2023-01-06 12:10:50,141 - mmseg - INFO - Iter [106800/160000] lr: 1.995e-05, eta: 6:24:51, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0936, decode.acc_seg: 96.0242, loss: 0.0936 2023-01-06 12:11:11,481 - mmseg - INFO - Iter [106850/160000] lr: 1.993e-05, eta: 6:24:29, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0987, decode.acc_seg: 95.9894, loss: 0.0987 2023-01-06 12:11:33,021 - mmseg - INFO - Iter [106900/160000] lr: 1.991e-05, eta: 6:24:07, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0932, decode.acc_seg: 96.0524, loss: 0.0932 2023-01-06 12:11:54,225 - mmseg - INFO - Iter [106950/160000] lr: 1.989e-05, eta: 6:23:45, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0955, decode.acc_seg: 96.0270, loss: 0.0955 2023-01-06 12:12:15,006 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:12:15,006 - mmseg - INFO - Iter [107000/160000] lr: 1.988e-05, eta: 6:23:23, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.1800, loss: 0.0889 2023-01-06 12:12:36,069 - mmseg - INFO - Iter [107050/160000] lr: 1.986e-05, eta: 6:23:01, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0966, decode.acc_seg: 95.9888, loss: 0.0966 2023-01-06 12:12:57,453 - mmseg - INFO - Iter [107100/160000] lr: 1.984e-05, eta: 6:22:39, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0924, decode.acc_seg: 95.9641, loss: 0.0924 2023-01-06 12:13:21,673 - mmseg - INFO - Iter [107150/160000] lr: 1.982e-05, eta: 6:22:18, time: 0.484, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0951, decode.acc_seg: 96.0990, loss: 0.0951 2023-01-06 12:13:43,964 - mmseg - INFO - Iter [107200/160000] lr: 1.980e-05, eta: 6:21:57, time: 0.446, data_time: 0.024, memory: 9591, decode.loss_ce: 0.0934, decode.acc_seg: 96.0585, loss: 0.0934 2023-01-06 12:14:04,695 - mmseg - INFO - Iter [107250/160000] lr: 1.978e-05, eta: 6:21:35, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0935, decode.acc_seg: 96.0390, loss: 0.0935 2023-01-06 12:14:25,588 - mmseg - INFO - Iter [107300/160000] lr: 1.976e-05, eta: 6:21:13, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0963, decode.acc_seg: 95.9549, loss: 0.0963 2023-01-06 12:14:46,625 - mmseg - INFO - Iter [107350/160000] lr: 1.974e-05, eta: 6:20:51, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0967, decode.acc_seg: 95.9938, loss: 0.0967 2023-01-06 12:15:08,131 - mmseg - INFO - Iter [107400/160000] lr: 1.973e-05, eta: 6:20:29, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0886, decode.acc_seg: 96.2765, loss: 0.0886 2023-01-06 12:15:28,771 - mmseg - INFO - Iter [107450/160000] lr: 1.971e-05, eta: 6:20:07, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0962, decode.acc_seg: 95.8531, loss: 0.0962 2023-01-06 12:15:49,369 - mmseg - INFO - Iter [107500/160000] lr: 1.969e-05, eta: 6:19:45, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0933, decode.acc_seg: 96.1385, loss: 0.0933 2023-01-06 12:16:13,468 - mmseg - INFO - Iter [107550/160000] lr: 1.967e-05, eta: 6:19:24, time: 0.481, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0945, decode.acc_seg: 95.9960, loss: 0.0945 2023-01-06 12:16:34,489 - mmseg - INFO - Iter [107600/160000] lr: 1.965e-05, eta: 6:19:02, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0966, decode.acc_seg: 95.9489, loss: 0.0966 2023-01-06 12:16:55,487 - mmseg - INFO - Iter [107650/160000] lr: 1.963e-05, eta: 6:18:40, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0937, decode.acc_seg: 96.0571, loss: 0.0937 2023-01-06 12:17:16,061 - mmseg - INFO - Iter [107700/160000] lr: 1.961e-05, eta: 6:18:18, time: 0.411, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0956, decode.acc_seg: 95.9499, loss: 0.0956 2023-01-06 12:17:37,508 - mmseg - INFO - Iter [107750/160000] lr: 1.959e-05, eta: 6:17:56, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0924, decode.acc_seg: 96.1434, loss: 0.0924 2023-01-06 12:17:58,161 - mmseg - INFO - Iter [107800/160000] lr: 1.958e-05, eta: 6:17:34, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0894, decode.acc_seg: 96.2047, loss: 0.0894 2023-01-06 12:18:19,498 - mmseg - INFO - Iter [107850/160000] lr: 1.956e-05, eta: 6:17:12, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0980, decode.acc_seg: 95.8805, loss: 0.0980 2023-01-06 12:18:42,684 - mmseg - INFO - Iter [107900/160000] lr: 1.954e-05, eta: 6:16:51, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0972, decode.acc_seg: 95.9237, loss: 0.0972 2023-01-06 12:19:04,339 - mmseg - INFO - Iter [107950/160000] lr: 1.952e-05, eta: 6:16:29, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.8044, loss: 0.0988 2023-01-06 12:19:25,997 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:19:25,997 - mmseg - INFO - Iter [108000/160000] lr: 1.950e-05, eta: 6:16:07, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0919, decode.acc_seg: 96.1898, loss: 0.0919 2023-01-06 12:19:47,213 - mmseg - INFO - Iter [108050/160000] lr: 1.948e-05, eta: 6:15:45, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1007, decode.acc_seg: 95.8831, loss: 0.1007 2023-01-06 12:20:08,108 - mmseg - INFO - Iter [108100/160000] lr: 1.946e-05, eta: 6:15:23, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0976, decode.acc_seg: 96.0534, loss: 0.0976 2023-01-06 12:20:28,999 - mmseg - INFO - Iter [108150/160000] lr: 1.944e-05, eta: 6:15:01, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0903, decode.acc_seg: 95.8910, loss: 0.0903 2023-01-06 12:20:50,554 - mmseg - INFO - Iter [108200/160000] lr: 1.943e-05, eta: 6:14:39, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0942, decode.acc_seg: 96.0436, loss: 0.0942 2023-01-06 12:21:12,336 - mmseg - INFO - Iter [108250/160000] lr: 1.941e-05, eta: 6:14:18, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0904, decode.acc_seg: 96.2067, loss: 0.0904 2023-01-06 12:21:35,169 - mmseg - INFO - Iter [108300/160000] lr: 1.939e-05, eta: 6:13:57, time: 0.457, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0910, decode.acc_seg: 96.1473, loss: 0.0910 2023-01-06 12:21:56,218 - mmseg - INFO - Iter [108350/160000] lr: 1.937e-05, eta: 6:13:35, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0897, decode.acc_seg: 96.2376, loss: 0.0897 2023-01-06 12:22:17,067 - mmseg - INFO - Iter [108400/160000] lr: 1.935e-05, eta: 6:13:13, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0976, decode.acc_seg: 95.9544, loss: 0.0976 2023-01-06 12:22:38,222 - mmseg - INFO - Iter [108450/160000] lr: 1.933e-05, eta: 6:12:51, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0896, decode.acc_seg: 96.1812, loss: 0.0896 2023-01-06 12:22:59,691 - mmseg - INFO - Iter [108500/160000] lr: 1.931e-05, eta: 6:12:29, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0982, decode.acc_seg: 95.9117, loss: 0.0982 2023-01-06 12:23:20,428 - mmseg - INFO - Iter [108550/160000] lr: 1.929e-05, eta: 6:12:07, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0997, decode.acc_seg: 95.8707, loss: 0.0997 2023-01-06 12:23:41,365 - mmseg - INFO - Iter [108600/160000] lr: 1.928e-05, eta: 6:11:45, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0969, decode.acc_seg: 95.9387, loss: 0.0969 2023-01-06 12:24:04,215 - mmseg - INFO - Iter [108650/160000] lr: 1.926e-05, eta: 6:11:23, time: 0.457, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0927, decode.acc_seg: 96.0087, loss: 0.0927 2023-01-06 12:24:25,349 - mmseg - INFO - Iter [108700/160000] lr: 1.924e-05, eta: 6:11:01, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.2950, loss: 0.0889 2023-01-06 12:24:47,087 - mmseg - INFO - Iter [108750/160000] lr: 1.922e-05, eta: 6:10:40, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0929, decode.acc_seg: 96.0376, loss: 0.0929 2023-01-06 12:25:09,114 - mmseg - INFO - Iter [108800/160000] lr: 1.920e-05, eta: 6:10:18, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0896, decode.acc_seg: 96.3070, loss: 0.0896 2023-01-06 12:25:29,806 - mmseg - INFO - Iter [108850/160000] lr: 1.918e-05, eta: 6:09:56, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0943, decode.acc_seg: 96.0778, loss: 0.0943 2023-01-06 12:25:50,733 - mmseg - INFO - Iter [108900/160000] lr: 1.916e-05, eta: 6:09:34, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0964, decode.acc_seg: 95.9044, loss: 0.0964 2023-01-06 12:26:11,487 - mmseg - INFO - Iter [108950/160000] lr: 1.914e-05, eta: 6:09:12, time: 0.416, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.0552, loss: 0.0908 2023-01-06 12:26:34,353 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:26:34,354 - mmseg - INFO - Iter [109000/160000] lr: 1.913e-05, eta: 6:08:51, time: 0.457, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0891, decode.acc_seg: 96.2351, loss: 0.0891 2023-01-06 12:26:55,638 - mmseg - INFO - Iter [109050/160000] lr: 1.911e-05, eta: 6:08:29, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0906, decode.acc_seg: 96.0960, loss: 0.0906 2023-01-06 12:27:16,525 - mmseg - INFO - Iter [109100/160000] lr: 1.909e-05, eta: 6:08:07, time: 0.418, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.1847, loss: 0.0917 2023-01-06 12:27:37,736 - mmseg - INFO - Iter [109150/160000] lr: 1.907e-05, eta: 6:07:45, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0975, decode.acc_seg: 95.8874, loss: 0.0975 2023-01-06 12:27:58,683 - mmseg - INFO - Iter [109200/160000] lr: 1.905e-05, eta: 6:07:23, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1013, decode.acc_seg: 95.7795, loss: 0.1013 2023-01-06 12:28:19,660 - mmseg - INFO - Iter [109250/160000] lr: 1.903e-05, eta: 6:07:01, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0939, decode.acc_seg: 96.0883, loss: 0.0939 2023-01-06 12:28:40,360 - mmseg - INFO - Iter [109300/160000] lr: 1.901e-05, eta: 6:06:39, time: 0.414, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0995, decode.acc_seg: 95.8436, loss: 0.0995 2023-01-06 12:29:02,166 - mmseg - INFO - Iter [109350/160000] lr: 1.899e-05, eta: 6:06:17, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0946, decode.acc_seg: 95.9866, loss: 0.0946 2023-01-06 12:29:25,607 - mmseg - INFO - Iter [109400/160000] lr: 1.898e-05, eta: 6:05:56, time: 0.469, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0913, decode.acc_seg: 96.1210, loss: 0.0913 2023-01-06 12:29:47,254 - mmseg - INFO - Iter [109450/160000] lr: 1.896e-05, eta: 6:05:34, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0911, decode.acc_seg: 96.1824, loss: 0.0911 2023-01-06 12:30:08,509 - mmseg - INFO - Iter [109500/160000] lr: 1.894e-05, eta: 6:05:12, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0936, decode.acc_seg: 96.0315, loss: 0.0936 2023-01-06 12:30:29,487 - mmseg - INFO - Iter [109550/160000] lr: 1.892e-05, eta: 6:04:50, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0986, decode.acc_seg: 95.9390, loss: 0.0986 2023-01-06 12:30:50,242 - mmseg - INFO - Iter [109600/160000] lr: 1.890e-05, eta: 6:04:28, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0923, decode.acc_seg: 96.0300, loss: 0.0923 2023-01-06 12:31:11,286 - mmseg - INFO - Iter [109650/160000] lr: 1.888e-05, eta: 6:04:06, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0922, decode.acc_seg: 96.2251, loss: 0.0922 2023-01-06 12:31:32,383 - mmseg - INFO - Iter [109700/160000] lr: 1.886e-05, eta: 6:03:44, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0996, decode.acc_seg: 95.7232, loss: 0.0996 2023-01-06 12:31:55,414 - mmseg - INFO - Iter [109750/160000] lr: 1.884e-05, eta: 6:03:23, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0924, decode.acc_seg: 96.1158, loss: 0.0924 2023-01-06 12:32:17,111 - mmseg - INFO - Iter [109800/160000] lr: 1.883e-05, eta: 6:03:02, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0965, decode.acc_seg: 95.9405, loss: 0.0965 2023-01-06 12:32:37,676 - mmseg - INFO - Iter [109850/160000] lr: 1.881e-05, eta: 6:02:39, time: 0.411, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0929, decode.acc_seg: 96.0342, loss: 0.0929 2023-01-06 12:32:58,635 - mmseg - INFO - Iter [109900/160000] lr: 1.879e-05, eta: 6:02:17, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0974, decode.acc_seg: 96.0301, loss: 0.0974 2023-01-06 12:33:20,471 - mmseg - INFO - Iter [109950/160000] lr: 1.877e-05, eta: 6:01:56, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0935, decode.acc_seg: 96.0412, loss: 0.0935 2023-01-06 12:33:41,579 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:33:41,580 - mmseg - INFO - Iter [110000/160000] lr: 1.875e-05, eta: 6:01:34, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0897, decode.acc_seg: 96.1453, loss: 0.0897 2023-01-06 12:34:03,240 - mmseg - INFO - Iter [110050/160000] lr: 1.873e-05, eta: 6:01:12, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0985, decode.acc_seg: 95.8550, loss: 0.0985 2023-01-06 12:34:24,627 - mmseg - INFO - Iter [110100/160000] lr: 1.871e-05, eta: 6:00:50, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0961, decode.acc_seg: 96.0654, loss: 0.0961 2023-01-06 12:34:48,667 - mmseg - INFO - Iter [110150/160000] lr: 1.869e-05, eta: 6:00:30, time: 0.480, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0919, decode.acc_seg: 96.1192, loss: 0.0919 2023-01-06 12:35:09,607 - mmseg - INFO - Iter [110200/160000] lr: 1.868e-05, eta: 6:00:07, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0918, decode.acc_seg: 96.1109, loss: 0.0918 2023-01-06 12:35:30,683 - mmseg - INFO - Iter [110250/160000] lr: 1.866e-05, eta: 5:59:46, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0964, decode.acc_seg: 95.9105, loss: 0.0964 2023-01-06 12:35:52,402 - mmseg - INFO - Iter [110300/160000] lr: 1.864e-05, eta: 5:59:24, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0901, decode.acc_seg: 96.1751, loss: 0.0901 2023-01-06 12:36:13,765 - mmseg - INFO - Iter [110350/160000] lr: 1.862e-05, eta: 5:59:02, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0949, decode.acc_seg: 96.0338, loss: 0.0949 2023-01-06 12:36:34,693 - mmseg - INFO - Iter [110400/160000] lr: 1.860e-05, eta: 5:58:40, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0903, decode.acc_seg: 96.1428, loss: 0.0903 2023-01-06 12:36:56,478 - mmseg - INFO - Iter [110450/160000] lr: 1.858e-05, eta: 5:58:18, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.1455, loss: 0.0908 2023-01-06 12:37:19,908 - mmseg - INFO - Iter [110500/160000] lr: 1.856e-05, eta: 5:57:57, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.3599, loss: 0.0870 2023-01-06 12:37:40,792 - mmseg - INFO - Iter [110550/160000] lr: 1.854e-05, eta: 5:57:35, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0896, decode.acc_seg: 96.1827, loss: 0.0896 2023-01-06 12:38:01,981 - mmseg - INFO - Iter [110600/160000] lr: 1.853e-05, eta: 5:57:13, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0928, decode.acc_seg: 96.0846, loss: 0.0928 2023-01-06 12:38:23,556 - mmseg - INFO - Iter [110650/160000] lr: 1.851e-05, eta: 5:56:52, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0927, decode.acc_seg: 96.0678, loss: 0.0927 2023-01-06 12:38:44,536 - mmseg - INFO - Iter [110700/160000] lr: 1.849e-05, eta: 5:56:30, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0913, decode.acc_seg: 96.0573, loss: 0.0913 2023-01-06 12:39:06,444 - mmseg - INFO - Iter [110750/160000] lr: 1.847e-05, eta: 5:56:08, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0933, decode.acc_seg: 96.1280, loss: 0.0933 2023-01-06 12:39:28,034 - mmseg - INFO - Iter [110800/160000] lr: 1.845e-05, eta: 5:55:46, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0912, decode.acc_seg: 96.1438, loss: 0.0912 2023-01-06 12:39:49,535 - mmseg - INFO - Iter [110850/160000] lr: 1.843e-05, eta: 5:55:25, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0880, decode.acc_seg: 96.1684, loss: 0.0880 2023-01-06 12:40:12,827 - mmseg - INFO - Iter [110900/160000] lr: 1.841e-05, eta: 5:55:04, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0958, decode.acc_seg: 95.9379, loss: 0.0958 2023-01-06 12:40:33,836 - mmseg - INFO - Iter [110950/160000] lr: 1.839e-05, eta: 5:54:42, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0914, decode.acc_seg: 96.1538, loss: 0.0914 2023-01-06 12:40:54,862 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:40:54,862 - mmseg - INFO - Iter [111000/160000] lr: 1.838e-05, eta: 5:54:20, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.2314, loss: 0.0889 2023-01-06 12:41:15,987 - mmseg - INFO - Iter [111050/160000] lr: 1.836e-05, eta: 5:53:58, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0903, decode.acc_seg: 96.1943, loss: 0.0903 2023-01-06 12:41:36,553 - mmseg - INFO - Iter [111100/160000] lr: 1.834e-05, eta: 5:53:35, time: 0.411, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1004, decode.acc_seg: 95.9435, loss: 0.1004 2023-01-06 12:41:57,235 - mmseg - INFO - Iter [111150/160000] lr: 1.832e-05, eta: 5:53:13, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1008, decode.acc_seg: 95.8376, loss: 0.1008 2023-01-06 12:42:17,857 - mmseg - INFO - Iter [111200/160000] lr: 1.830e-05, eta: 5:52:51, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0904, decode.acc_seg: 96.1864, loss: 0.0904 2023-01-06 12:42:40,899 - mmseg - INFO - Iter [111250/160000] lr: 1.828e-05, eta: 5:52:30, time: 0.461, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.1993, loss: 0.0915 2023-01-06 12:43:01,834 - mmseg - INFO - Iter [111300/160000] lr: 1.826e-05, eta: 5:52:08, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.1978, loss: 0.0884 2023-01-06 12:43:22,785 - mmseg - INFO - Iter [111350/160000] lr: 1.824e-05, eta: 5:51:46, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0880, decode.acc_seg: 96.2650, loss: 0.0880 2023-01-06 12:43:44,070 - mmseg - INFO - Iter [111400/160000] lr: 1.823e-05, eta: 5:51:24, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0918, decode.acc_seg: 96.0701, loss: 0.0918 2023-01-06 12:44:05,191 - mmseg - INFO - Iter [111450/160000] lr: 1.821e-05, eta: 5:51:02, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0916, decode.acc_seg: 96.2822, loss: 0.0916 2023-01-06 12:44:26,666 - mmseg - INFO - Iter [111500/160000] lr: 1.819e-05, eta: 5:50:40, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.1187, loss: 0.0915 2023-01-06 12:44:47,277 - mmseg - INFO - Iter [111550/160000] lr: 1.817e-05, eta: 5:50:18, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.0837, loss: 0.0908 2023-01-06 12:45:08,270 - mmseg - INFO - Iter [111600/160000] lr: 1.815e-05, eta: 5:49:56, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.1029, decode.acc_seg: 95.8714, loss: 0.1029 2023-01-06 12:45:31,193 - mmseg - INFO - Iter [111650/160000] lr: 1.813e-05, eta: 5:49:35, time: 0.459, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0923, decode.acc_seg: 96.1155, loss: 0.0923 2023-01-06 12:45:51,870 - mmseg - INFO - Iter [111700/160000] lr: 1.811e-05, eta: 5:49:13, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0868, decode.acc_seg: 96.3654, loss: 0.0868 2023-01-06 12:46:12,653 - mmseg - INFO - Iter [111750/160000] lr: 1.809e-05, eta: 5:48:51, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.3106, loss: 0.0874 2023-01-06 12:46:34,116 - mmseg - INFO - Iter [111800/160000] lr: 1.808e-05, eta: 5:48:29, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3413, loss: 0.0859 2023-01-06 12:46:54,703 - mmseg - INFO - Iter [111850/160000] lr: 1.806e-05, eta: 5:48:07, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0911, decode.acc_seg: 96.1675, loss: 0.0911 2023-01-06 12:47:15,405 - mmseg - INFO - Iter [111900/160000] lr: 1.804e-05, eta: 5:47:45, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0907, decode.acc_seg: 96.1284, loss: 0.0907 2023-01-06 12:47:37,131 - mmseg - INFO - Iter [111950/160000] lr: 1.802e-05, eta: 5:47:23, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0928, decode.acc_seg: 96.0375, loss: 0.0928 2023-01-06 12:48:01,078 - mmseg - INFO - Saving checkpoint at 112000 iterations 2023-01-06 12:48:04,801 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:48:04,802 - mmseg - INFO - Iter [112000/160000] lr: 1.800e-05, eta: 5:47:04, time: 0.554, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0920, decode.acc_seg: 96.0203, loss: 0.0920 2023-01-06 12:48:32,967 - mmseg - INFO - per class results: 2023-01-06 12:48:32,969 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 98.01 | 99.11 | | sidewalk | 83.6 | 90.11 | | building | 91.65 | 96.62 | | wall | 52.62 | 58.52 | | fence | 52.8 | 64.27 | | pole | 60.81 | 69.56 | | traffic light | 64.82 | 76.33 | | traffic sign | 74.44 | 81.6 | | vegetation | 91.78 | 96.59 | | terrain | 58.76 | 65.36 | | sky | 94.8 | 98.03 | | person | 77.44 | 89.57 | | rider | 53.83 | 66.61 | | car | 93.83 | 97.04 | | truck | 64.7 | 81.15 | | bus | 72.35 | 80.14 | | train | 58.23 | 67.16 | | motorcycle | 42.52 | 50.0 | | bicycle | 71.96 | 85.56 | +---------------+-------+-------+ 2023-01-06 12:48:32,970 - mmseg - INFO - Summary: 2023-01-06 12:48:32,970 - mmseg - INFO - +-------+-------+-------+ | aAcc | mIoU | mAcc | +-------+-------+-------+ | 95.52 | 71.52 | 79.65 | +-------+-------+-------+ 2023-01-06 12:48:32,971 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:48:32,971 - mmseg - INFO - Iter(val) [63] aAcc: 0.9552, mIoU: 0.7152, mAcc: 0.7965, IoU.road: 0.9801, IoU.sidewalk: 0.8360, IoU.building: 0.9165, IoU.wall: 0.5262, IoU.fence: 0.5280, IoU.pole: 0.6081, IoU.traffic light: 0.6482, IoU.traffic sign: 0.7444, IoU.vegetation: 0.9178, IoU.terrain: 0.5876, IoU.sky: 0.9480, IoU.person: 0.7744, IoU.rider: 0.5383, IoU.car: 0.9383, IoU.truck: 0.6470, IoU.bus: 0.7235, IoU.train: 0.5823, IoU.motorcycle: 0.4252, IoU.bicycle: 0.7196, Acc.road: 0.9911, Acc.sidewalk: 0.9011, Acc.building: 0.9662, Acc.wall: 0.5852, Acc.fence: 0.6427, Acc.pole: 0.6956, Acc.traffic light: 0.7633, Acc.traffic sign: 0.8160, Acc.vegetation: 0.9659, Acc.terrain: 0.6536, Acc.sky: 0.9803, Acc.person: 0.8957, Acc.rider: 0.6661, Acc.car: 0.9704, Acc.truck: 0.8115, Acc.bus: 0.8014, Acc.train: 0.6716, Acc.motorcycle: 0.5000, Acc.bicycle: 0.8556 2023-01-06 12:48:53,536 - mmseg - INFO - Iter [112050/160000] lr: 1.798e-05, eta: 5:46:54, time: 0.974, data_time: 0.574, memory: 9591, decode.loss_ce: 0.0925, decode.acc_seg: 96.1627, loss: 0.0925 2023-01-06 12:49:14,438 - mmseg - INFO - Iter [112100/160000] lr: 1.796e-05, eta: 5:46:32, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0871, decode.acc_seg: 96.3120, loss: 0.0871 2023-01-06 12:49:35,956 - mmseg - INFO - Iter [112150/160000] lr: 1.794e-05, eta: 5:46:10, time: 0.430, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0949, decode.acc_seg: 96.0749, loss: 0.0949 2023-01-06 12:49:57,415 - mmseg - INFO - Iter [112200/160000] lr: 1.793e-05, eta: 5:45:48, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.1951, loss: 0.0908 2023-01-06 12:50:19,172 - mmseg - INFO - Iter [112250/160000] lr: 1.791e-05, eta: 5:45:27, time: 0.435, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0911, decode.acc_seg: 96.1307, loss: 0.0911 2023-01-06 12:50:40,062 - mmseg - INFO - Iter [112300/160000] lr: 1.789e-05, eta: 5:45:04, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0869, decode.acc_seg: 96.2908, loss: 0.0869 2023-01-06 12:51:03,155 - mmseg - INFO - Iter [112350/160000] lr: 1.787e-05, eta: 5:44:43, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.1017, decode.acc_seg: 95.9037, loss: 0.1017 2023-01-06 12:51:24,680 - mmseg - INFO - Iter [112400/160000] lr: 1.785e-05, eta: 5:44:22, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0898, decode.acc_seg: 96.1594, loss: 0.0898 2023-01-06 12:51:45,276 - mmseg - INFO - Iter [112450/160000] lr: 1.783e-05, eta: 5:43:59, time: 0.412, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0873, decode.acc_seg: 96.3149, loss: 0.0873 2023-01-06 12:52:07,238 - mmseg - INFO - Iter [112500/160000] lr: 1.781e-05, eta: 5:43:38, time: 0.439, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0897, decode.acc_seg: 96.1218, loss: 0.0897 2023-01-06 12:52:27,791 - mmseg - INFO - Iter [112550/160000] lr: 1.779e-05, eta: 5:43:16, time: 0.411, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0887, decode.acc_seg: 96.2698, loss: 0.0887 2023-01-06 12:52:49,150 - mmseg - INFO - Iter [112600/160000] lr: 1.778e-05, eta: 5:42:54, time: 0.427, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0945, decode.acc_seg: 96.1471, loss: 0.0945 2023-01-06 12:53:10,017 - mmseg - INFO - Iter [112650/160000] lr: 1.776e-05, eta: 5:42:32, time: 0.417, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0933, decode.acc_seg: 96.1123, loss: 0.0933 2023-01-06 12:53:31,239 - mmseg - INFO - Iter [112700/160000] lr: 1.774e-05, eta: 5:42:10, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0945, decode.acc_seg: 96.0919, loss: 0.0945 2023-01-06 12:53:54,821 - mmseg - INFO - Iter [112750/160000] lr: 1.772e-05, eta: 5:41:49, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0940, decode.acc_seg: 96.0669, loss: 0.0940 2023-01-06 12:54:16,055 - mmseg - INFO - Iter [112800/160000] lr: 1.770e-05, eta: 5:41:27, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0904, decode.acc_seg: 96.2120, loss: 0.0904 2023-01-06 12:54:37,920 - mmseg - INFO - Iter [112850/160000] lr: 1.768e-05, eta: 5:41:05, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0916, decode.acc_seg: 96.2870, loss: 0.0916 2023-01-06 12:54:59,446 - mmseg - INFO - Iter [112900/160000] lr: 1.766e-05, eta: 5:40:44, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0899, decode.acc_seg: 96.2307, loss: 0.0899 2023-01-06 12:55:21,248 - mmseg - INFO - Iter [112950/160000] lr: 1.764e-05, eta: 5:40:22, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0890, decode.acc_seg: 96.1710, loss: 0.0890 2023-01-06 12:55:41,859 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 12:55:41,860 - mmseg - INFO - Iter [113000/160000] lr: 1.763e-05, eta: 5:40:00, time: 0.412, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3265, loss: 0.0859 2023-01-06 12:56:02,935 - mmseg - INFO - Iter [113050/160000] lr: 1.761e-05, eta: 5:39:38, time: 0.421, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0898, decode.acc_seg: 96.2262, loss: 0.0898 2023-01-06 12:56:25,985 - mmseg - INFO - Iter [113100/160000] lr: 1.759e-05, eta: 5:39:17, time: 0.461, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0926, decode.acc_seg: 96.1205, loss: 0.0926 2023-01-06 12:56:46,660 - mmseg - INFO - Iter [113150/160000] lr: 1.757e-05, eta: 5:38:55, time: 0.413, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0944, decode.acc_seg: 96.0743, loss: 0.0944 2023-01-06 12:57:07,641 - mmseg - INFO - Iter [113200/160000] lr: 1.755e-05, eta: 5:38:33, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.1786, loss: 0.0917 2023-01-06 12:57:29,303 - mmseg - INFO - Iter [113250/160000] lr: 1.753e-05, eta: 5:38:11, time: 0.433, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0886, decode.acc_seg: 96.2597, loss: 0.0886 2023-01-06 12:57:49,929 - mmseg - INFO - Iter [113300/160000] lr: 1.751e-05, eta: 5:37:49, time: 0.412, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0903, decode.acc_seg: 96.1873, loss: 0.0903 2023-01-06 12:58:10,483 - mmseg - INFO - Iter [113350/160000] lr: 1.749e-05, eta: 5:37:27, time: 0.411, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0929, decode.acc_seg: 95.9626, loss: 0.0929 2023-01-06 12:58:31,173 - mmseg - INFO - Iter [113400/160000] lr: 1.748e-05, eta: 5:37:04, time: 0.414, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0871, decode.acc_seg: 96.3580, loss: 0.0871 2023-01-06 12:58:52,180 - mmseg - INFO - Iter [113450/160000] lr: 1.746e-05, eta: 5:36:42, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0901, decode.acc_seg: 96.2077, loss: 0.0901 2023-01-06 12:59:15,856 - mmseg - INFO - Iter [113500/160000] lr: 1.744e-05, eta: 5:36:22, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.1550, loss: 0.0917 2023-01-06 12:59:36,774 - mmseg - INFO - Iter [113550/160000] lr: 1.742e-05, eta: 5:35:59, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0902, decode.acc_seg: 96.1632, loss: 0.0902 2023-01-06 12:59:57,903 - mmseg - INFO - Iter [113600/160000] lr: 1.740e-05, eta: 5:35:38, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0868, decode.acc_seg: 96.3258, loss: 0.0868 2023-01-06 13:00:18,836 - mmseg - INFO - Iter [113650/160000] lr: 1.738e-05, eta: 5:35:16, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0919, decode.acc_seg: 96.0480, loss: 0.0919 2023-01-06 13:00:39,835 - mmseg - INFO - Iter [113700/160000] lr: 1.736e-05, eta: 5:34:54, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0995, decode.acc_seg: 96.0013, loss: 0.0995 2023-01-06 13:01:00,712 - mmseg - INFO - Iter [113750/160000] lr: 1.734e-05, eta: 5:34:32, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.1483, loss: 0.0884 2023-01-06 13:01:22,711 - mmseg - INFO - Iter [113800/160000] lr: 1.733e-05, eta: 5:34:10, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0864, decode.acc_seg: 96.2697, loss: 0.0864 2023-01-06 13:01:45,880 - mmseg - INFO - Iter [113850/160000] lr: 1.731e-05, eta: 5:33:49, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0914, decode.acc_seg: 96.0575, loss: 0.0914 2023-01-06 13:02:06,845 - mmseg - INFO - Iter [113900/160000] lr: 1.729e-05, eta: 5:33:27, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.2552, loss: 0.0884 2023-01-06 13:02:27,883 - mmseg - INFO - Iter [113950/160000] lr: 1.727e-05, eta: 5:33:05, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0947, decode.acc_seg: 96.0911, loss: 0.0947 2023-01-06 13:02:49,424 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:02:49,424 - mmseg - INFO - Iter [114000/160000] lr: 1.725e-05, eta: 5:32:43, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0912, decode.acc_seg: 96.1783, loss: 0.0912 2023-01-06 13:03:10,442 - mmseg - INFO - Iter [114050/160000] lr: 1.723e-05, eta: 5:32:21, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0902, decode.acc_seg: 96.2066, loss: 0.0902 2023-01-06 13:03:31,661 - mmseg - INFO - Iter [114100/160000] lr: 1.721e-05, eta: 5:31:59, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0919, decode.acc_seg: 96.1538, loss: 0.0919 2023-01-06 13:03:52,675 - mmseg - INFO - Iter [114150/160000] lr: 1.719e-05, eta: 5:31:37, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0903, decode.acc_seg: 96.2198, loss: 0.0903 2023-01-06 13:04:13,377 - mmseg - INFO - Iter [114200/160000] lr: 1.718e-05, eta: 5:31:15, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0920, decode.acc_seg: 96.0225, loss: 0.0920 2023-01-06 13:04:37,781 - mmseg - INFO - Iter [114250/160000] lr: 1.716e-05, eta: 5:30:55, time: 0.488, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0912, decode.acc_seg: 96.0748, loss: 0.0912 2023-01-06 13:04:58,798 - mmseg - INFO - Iter [114300/160000] lr: 1.714e-05, eta: 5:30:33, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.0904, loss: 0.0915 2023-01-06 13:05:19,754 - mmseg - INFO - Iter [114350/160000] lr: 1.712e-05, eta: 5:30:11, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.3611, loss: 0.0862 2023-01-06 13:05:40,851 - mmseg - INFO - Iter [114400/160000] lr: 1.710e-05, eta: 5:29:49, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0866, decode.acc_seg: 96.3063, loss: 0.0866 2023-01-06 13:06:01,589 - mmseg - INFO - Iter [114450/160000] lr: 1.708e-05, eta: 5:29:27, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0885, decode.acc_seg: 96.2691, loss: 0.0885 2023-01-06 13:06:22,926 - mmseg - INFO - Iter [114500/160000] lr: 1.706e-05, eta: 5:29:05, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0941, decode.acc_seg: 96.1097, loss: 0.0941 2023-01-06 13:06:44,195 - mmseg - INFO - Iter [114550/160000] lr: 1.704e-05, eta: 5:28:43, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0878, decode.acc_seg: 96.2422, loss: 0.0878 2023-01-06 13:07:07,163 - mmseg - INFO - Iter [114600/160000] lr: 1.703e-05, eta: 5:28:22, time: 0.459, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0955, decode.acc_seg: 95.9378, loss: 0.0955 2023-01-06 13:07:27,800 - mmseg - INFO - Iter [114650/160000] lr: 1.701e-05, eta: 5:28:00, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0922, decode.acc_seg: 96.1653, loss: 0.0922 2023-01-06 13:07:49,155 - mmseg - INFO - Iter [114700/160000] lr: 1.699e-05, eta: 5:27:38, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0938, decode.acc_seg: 96.0906, loss: 0.0938 2023-01-06 13:08:10,515 - mmseg - INFO - Iter [114750/160000] lr: 1.697e-05, eta: 5:27:16, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0950, decode.acc_seg: 96.0939, loss: 0.0950 2023-01-06 13:08:31,093 - mmseg - INFO - Iter [114800/160000] lr: 1.695e-05, eta: 5:26:54, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0913, decode.acc_seg: 96.1164, loss: 0.0913 2023-01-06 13:08:51,696 - mmseg - INFO - Iter [114850/160000] lr: 1.693e-05, eta: 5:26:32, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0898, decode.acc_seg: 96.1745, loss: 0.0898 2023-01-06 13:09:13,054 - mmseg - INFO - Iter [114900/160000] lr: 1.691e-05, eta: 5:26:10, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.3233, loss: 0.0862 2023-01-06 13:09:36,712 - mmseg - INFO - Iter [114950/160000] lr: 1.689e-05, eta: 5:25:49, time: 0.474, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0980, decode.acc_seg: 95.9018, loss: 0.0980 2023-01-06 13:09:57,646 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:09:57,647 - mmseg - INFO - Iter [115000/160000] lr: 1.688e-05, eta: 5:25:27, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0939, decode.acc_seg: 96.1078, loss: 0.0939 2023-01-06 13:10:19,123 - mmseg - INFO - Iter [115050/160000] lr: 1.686e-05, eta: 5:25:05, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0899, decode.acc_seg: 96.2553, loss: 0.0899 2023-01-06 13:10:40,175 - mmseg - INFO - Iter [115100/160000] lr: 1.684e-05, eta: 5:24:43, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0907, decode.acc_seg: 96.1407, loss: 0.0907 2023-01-06 13:11:01,552 - mmseg - INFO - Iter [115150/160000] lr: 1.682e-05, eta: 5:24:21, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0878, decode.acc_seg: 96.3095, loss: 0.0878 2023-01-06 13:11:23,876 - mmseg - INFO - Iter [115200/160000] lr: 1.680e-05, eta: 5:24:00, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0951, decode.acc_seg: 96.0469, loss: 0.0951 2023-01-06 13:11:45,220 - mmseg - INFO - Iter [115250/160000] lr: 1.678e-05, eta: 5:23:38, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0918, decode.acc_seg: 96.2553, loss: 0.0918 2023-01-06 13:12:07,178 - mmseg - INFO - Iter [115300/160000] lr: 1.676e-05, eta: 5:23:16, time: 0.440, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0886, decode.acc_seg: 96.1140, loss: 0.0886 2023-01-06 13:12:30,552 - mmseg - INFO - Iter [115350/160000] lr: 1.674e-05, eta: 5:22:55, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0875, decode.acc_seg: 96.2440, loss: 0.0875 2023-01-06 13:12:51,693 - mmseg - INFO - Iter [115400/160000] lr: 1.673e-05, eta: 5:22:33, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0932, decode.acc_seg: 96.0965, loss: 0.0932 2023-01-06 13:13:12,824 - mmseg - INFO - Iter [115450/160000] lr: 1.671e-05, eta: 5:22:12, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.2595, loss: 0.0877 2023-01-06 13:13:33,772 - mmseg - INFO - Iter [115500/160000] lr: 1.669e-05, eta: 5:21:50, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0934, decode.acc_seg: 96.0387, loss: 0.0934 2023-01-06 13:13:55,147 - mmseg - INFO - Iter [115550/160000] lr: 1.667e-05, eta: 5:21:28, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.1764, loss: 0.0900 2023-01-06 13:14:16,193 - mmseg - INFO - Iter [115600/160000] lr: 1.665e-05, eta: 5:21:06, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0885, decode.acc_seg: 96.2963, loss: 0.0885 2023-01-06 13:14:37,661 - mmseg - INFO - Iter [115650/160000] lr: 1.663e-05, eta: 5:20:44, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0931, decode.acc_seg: 96.1146, loss: 0.0931 2023-01-06 13:15:00,794 - mmseg - INFO - Iter [115700/160000] lr: 1.661e-05, eta: 5:20:23, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0887, decode.acc_seg: 96.2637, loss: 0.0887 2023-01-06 13:15:22,082 - mmseg - INFO - Iter [115750/160000] lr: 1.659e-05, eta: 5:20:01, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.3565, loss: 0.0877 2023-01-06 13:15:43,684 - mmseg - INFO - Iter [115800/160000] lr: 1.658e-05, eta: 5:19:39, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.2365, loss: 0.0889 2023-01-06 13:16:05,832 - mmseg - INFO - Iter [115850/160000] lr: 1.656e-05, eta: 5:19:18, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0895, decode.acc_seg: 96.2434, loss: 0.0895 2023-01-06 13:16:26,642 - mmseg - INFO - Iter [115900/160000] lr: 1.654e-05, eta: 5:18:56, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0910, decode.acc_seg: 96.1465, loss: 0.0910 2023-01-06 13:16:47,560 - mmseg - INFO - Iter [115950/160000] lr: 1.652e-05, eta: 5:18:34, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0891, decode.acc_seg: 96.1138, loss: 0.0891 2023-01-06 13:17:08,907 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:17:08,907 - mmseg - INFO - Iter [116000/160000] lr: 1.650e-05, eta: 5:18:12, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0881, decode.acc_seg: 96.1900, loss: 0.0881 2023-01-06 13:17:29,939 - mmseg - INFO - Iter [116050/160000] lr: 1.648e-05, eta: 5:17:50, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0933, decode.acc_seg: 95.9949, loss: 0.0933 2023-01-06 13:17:53,207 - mmseg - INFO - Iter [116100/160000] lr: 1.646e-05, eta: 5:17:29, time: 0.465, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0926, decode.acc_seg: 96.1080, loss: 0.0926 2023-01-06 13:18:14,305 - mmseg - INFO - Iter [116150/160000] lr: 1.644e-05, eta: 5:17:07, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.2328, loss: 0.0893 2023-01-06 13:18:35,390 - mmseg - INFO - Iter [116200/160000] lr: 1.643e-05, eta: 5:16:45, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0932, decode.acc_seg: 96.0867, loss: 0.0932 2023-01-06 13:18:56,151 - mmseg - INFO - Iter [116250/160000] lr: 1.641e-05, eta: 5:16:23, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0883, decode.acc_seg: 96.2481, loss: 0.0883 2023-01-06 13:19:16,862 - mmseg - INFO - Iter [116300/160000] lr: 1.639e-05, eta: 5:16:01, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0910, decode.acc_seg: 96.2515, loss: 0.0910 2023-01-06 13:19:37,981 - mmseg - INFO - Iter [116350/160000] lr: 1.637e-05, eta: 5:15:39, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0876, decode.acc_seg: 96.2452, loss: 0.0876 2023-01-06 13:19:59,000 - mmseg - INFO - Iter [116400/160000] lr: 1.635e-05, eta: 5:15:17, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0903, decode.acc_seg: 96.1893, loss: 0.0903 2023-01-06 13:20:22,772 - mmseg - INFO - Iter [116450/160000] lr: 1.633e-05, eta: 5:14:56, time: 0.475, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.2712, loss: 0.0877 2023-01-06 13:20:44,397 - mmseg - INFO - Iter [116500/160000] lr: 1.631e-05, eta: 5:14:34, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0867, decode.acc_seg: 96.3777, loss: 0.0867 2023-01-06 13:21:05,201 - mmseg - INFO - Iter [116550/160000] lr: 1.629e-05, eta: 5:14:12, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0910, decode.acc_seg: 96.1292, loss: 0.0910 2023-01-06 13:21:26,461 - mmseg - INFO - Iter [116600/160000] lr: 1.628e-05, eta: 5:13:51, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.0491, loss: 0.0917 2023-01-06 13:21:47,444 - mmseg - INFO - Iter [116650/160000] lr: 1.626e-05, eta: 5:13:29, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0869, decode.acc_seg: 96.2570, loss: 0.0869 2023-01-06 13:22:08,482 - mmseg - INFO - Iter [116700/160000] lr: 1.624e-05, eta: 5:13:07, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.2141, loss: 0.0917 2023-01-06 13:22:29,863 - mmseg - INFO - Iter [116750/160000] lr: 1.622e-05, eta: 5:12:45, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.1140, loss: 0.0915 2023-01-06 13:22:50,599 - mmseg - INFO - Iter [116800/160000] lr: 1.620e-05, eta: 5:12:23, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.4091, loss: 0.0859 2023-01-06 13:23:13,487 - mmseg - INFO - Iter [116850/160000] lr: 1.618e-05, eta: 5:12:01, time: 0.458, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0894, decode.acc_seg: 96.2606, loss: 0.0894 2023-01-06 13:23:34,760 - mmseg - INFO - Iter [116900/160000] lr: 1.616e-05, eta: 5:11:40, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0879, decode.acc_seg: 96.3253, loss: 0.0879 2023-01-06 13:23:55,772 - mmseg - INFO - Iter [116950/160000] lr: 1.614e-05, eta: 5:11:18, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0867, decode.acc_seg: 96.4348, loss: 0.0867 2023-01-06 13:24:16,955 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:24:16,955 - mmseg - INFO - Iter [117000/160000] lr: 1.613e-05, eta: 5:10:56, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.4012, loss: 0.0858 2023-01-06 13:24:37,708 - mmseg - INFO - Iter [117050/160000] lr: 1.611e-05, eta: 5:10:34, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0881, decode.acc_seg: 96.2899, loss: 0.0881 2023-01-06 13:24:58,412 - mmseg - INFO - Iter [117100/160000] lr: 1.609e-05, eta: 5:10:12, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0853, decode.acc_seg: 96.3027, loss: 0.0853 2023-01-06 13:25:19,386 - mmseg - INFO - Iter [117150/160000] lr: 1.607e-05, eta: 5:09:50, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0898, decode.acc_seg: 96.2255, loss: 0.0898 2023-01-06 13:25:42,768 - mmseg - INFO - Iter [117200/160000] lr: 1.605e-05, eta: 5:09:29, time: 0.468, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0866, decode.acc_seg: 96.3231, loss: 0.0866 2023-01-06 13:26:03,659 - mmseg - INFO - Iter [117250/160000] lr: 1.603e-05, eta: 5:09:07, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0912, decode.acc_seg: 96.2116, loss: 0.0912 2023-01-06 13:26:24,741 - mmseg - INFO - Iter [117300/160000] lr: 1.601e-05, eta: 5:08:45, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0929, decode.acc_seg: 96.1020, loss: 0.0929 2023-01-06 13:26:45,373 - mmseg - INFO - Iter [117350/160000] lr: 1.599e-05, eta: 5:08:23, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0888, decode.acc_seg: 96.2095, loss: 0.0888 2023-01-06 13:27:06,158 - mmseg - INFO - Iter [117400/160000] lr: 1.598e-05, eta: 5:08:01, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0883, decode.acc_seg: 96.1777, loss: 0.0883 2023-01-06 13:27:27,611 - mmseg - INFO - Iter [117450/160000] lr: 1.596e-05, eta: 5:07:39, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0847, decode.acc_seg: 96.3883, loss: 0.0847 2023-01-06 13:27:48,343 - mmseg - INFO - Iter [117500/160000] lr: 1.594e-05, eta: 5:07:17, time: 0.415, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0865, decode.acc_seg: 96.3763, loss: 0.0865 2023-01-06 13:28:10,166 - mmseg - INFO - Iter [117550/160000] lr: 1.592e-05, eta: 5:06:55, time: 0.436, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.1815, loss: 0.0889 2023-01-06 13:28:34,029 - mmseg - INFO - Iter [117600/160000] lr: 1.590e-05, eta: 5:06:34, time: 0.478, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.2246, loss: 0.0900 2023-01-06 13:28:54,844 - mmseg - INFO - Iter [117650/160000] lr: 1.588e-05, eta: 5:06:12, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0902, decode.acc_seg: 96.2415, loss: 0.0902 2023-01-06 13:29:15,767 - mmseg - INFO - Iter [117700/160000] lr: 1.586e-05, eta: 5:05:50, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.2507, loss: 0.0893 2023-01-06 13:29:37,015 - mmseg - INFO - Iter [117750/160000] lr: 1.584e-05, eta: 5:05:29, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0914, decode.acc_seg: 96.0189, loss: 0.0914 2023-01-06 13:29:58,045 - mmseg - INFO - Iter [117800/160000] lr: 1.583e-05, eta: 5:05:07, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0916, decode.acc_seg: 96.1111, loss: 0.0916 2023-01-06 13:30:19,196 - mmseg - INFO - Iter [117850/160000] lr: 1.581e-05, eta: 5:04:45, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0882, decode.acc_seg: 96.2713, loss: 0.0882 2023-01-06 13:30:40,174 - mmseg - INFO - Iter [117900/160000] lr: 1.579e-05, eta: 5:04:23, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0888, decode.acc_seg: 96.2804, loss: 0.0888 2023-01-06 13:31:03,236 - mmseg - INFO - Iter [117950/160000] lr: 1.577e-05, eta: 5:04:02, time: 0.462, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0890, decode.acc_seg: 96.2087, loss: 0.0890 2023-01-06 13:31:24,242 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:31:24,243 - mmseg - INFO - Iter [118000/160000] lr: 1.575e-05, eta: 5:03:40, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0880, decode.acc_seg: 96.1726, loss: 0.0880 2023-01-06 13:31:45,572 - mmseg - INFO - Iter [118050/160000] lr: 1.573e-05, eta: 5:03:18, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0879, decode.acc_seg: 96.2648, loss: 0.0879 2023-01-06 13:32:06,452 - mmseg - INFO - Iter [118100/160000] lr: 1.571e-05, eta: 5:02:56, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0903, decode.acc_seg: 96.1973, loss: 0.0903 2023-01-06 13:32:27,515 - mmseg - INFO - Iter [118150/160000] lr: 1.569e-05, eta: 5:02:34, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.2276, loss: 0.0884 2023-01-06 13:32:48,758 - mmseg - INFO - Iter [118200/160000] lr: 1.568e-05, eta: 5:02:12, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.3395, loss: 0.0862 2023-01-06 13:33:09,704 - mmseg - INFO - Iter [118250/160000] lr: 1.566e-05, eta: 5:01:50, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0887, decode.acc_seg: 96.2212, loss: 0.0887 2023-01-06 13:33:32,888 - mmseg - INFO - Iter [118300/160000] lr: 1.564e-05, eta: 5:01:29, time: 0.464, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0942, decode.acc_seg: 96.0947, loss: 0.0942 2023-01-06 13:33:54,630 - mmseg - INFO - Iter [118350/160000] lr: 1.562e-05, eta: 5:01:07, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0895, decode.acc_seg: 96.2495, loss: 0.0895 2023-01-06 13:34:16,140 - mmseg - INFO - Iter [118400/160000] lr: 1.560e-05, eta: 5:00:46, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0988, decode.acc_seg: 95.9074, loss: 0.0988 2023-01-06 13:34:37,942 - mmseg - INFO - Iter [118450/160000] lr: 1.558e-05, eta: 5:00:24, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.1874, loss: 0.0900 2023-01-06 13:34:59,012 - mmseg - INFO - Iter [118500/160000] lr: 1.556e-05, eta: 5:00:02, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0910, decode.acc_seg: 96.1338, loss: 0.0910 2023-01-06 13:35:20,152 - mmseg - INFO - Iter [118550/160000] lr: 1.554e-05, eta: 4:59:40, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.3973, loss: 0.0863 2023-01-06 13:35:41,459 - mmseg - INFO - Iter [118600/160000] lr: 1.553e-05, eta: 4:59:18, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0935, decode.acc_seg: 96.1797, loss: 0.0935 2023-01-06 13:36:02,306 - mmseg - INFO - Iter [118650/160000] lr: 1.551e-05, eta: 4:58:56, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0866, decode.acc_seg: 96.2463, loss: 0.0866 2023-01-06 13:36:25,487 - mmseg - INFO - Iter [118700/160000] lr: 1.549e-05, eta: 4:58:35, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0905, decode.acc_seg: 96.2670, loss: 0.0905 2023-01-06 13:36:47,092 - mmseg - INFO - Iter [118750/160000] lr: 1.547e-05, eta: 4:58:13, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0890, decode.acc_seg: 96.3110, loss: 0.0890 2023-01-06 13:37:07,787 - mmseg - INFO - Iter [118800/160000] lr: 1.545e-05, eta: 4:57:51, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0970, decode.acc_seg: 96.1004, loss: 0.0970 2023-01-06 13:37:29,141 - mmseg - INFO - Iter [118850/160000] lr: 1.543e-05, eta: 4:57:30, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0919, decode.acc_seg: 96.1437, loss: 0.0919 2023-01-06 13:37:50,602 - mmseg - INFO - Iter [118900/160000] lr: 1.541e-05, eta: 4:57:08, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.1989, loss: 0.0908 2023-01-06 13:38:11,517 - mmseg - INFO - Iter [118950/160000] lr: 1.539e-05, eta: 4:56:46, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0851, decode.acc_seg: 96.3049, loss: 0.0851 2023-01-06 13:38:33,420 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:38:33,420 - mmseg - INFO - Iter [119000/160000] lr: 1.538e-05, eta: 4:56:24, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0902, decode.acc_seg: 96.1985, loss: 0.0902 2023-01-06 13:38:57,025 - mmseg - INFO - Iter [119050/160000] lr: 1.536e-05, eta: 4:56:03, time: 0.473, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.2689, loss: 0.0900 2023-01-06 13:39:18,625 - mmseg - INFO - Iter [119100/160000] lr: 1.534e-05, eta: 4:55:41, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0906, decode.acc_seg: 96.1545, loss: 0.0906 2023-01-06 13:39:39,760 - mmseg - INFO - Iter [119150/160000] lr: 1.532e-05, eta: 4:55:20, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0846, decode.acc_seg: 96.4516, loss: 0.0846 2023-01-06 13:40:00,847 - mmseg - INFO - Iter [119200/160000] lr: 1.530e-05, eta: 4:54:58, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0875, decode.acc_seg: 96.3133, loss: 0.0875 2023-01-06 13:40:22,232 - mmseg - INFO - Iter [119250/160000] lr: 1.528e-05, eta: 4:54:36, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0867, decode.acc_seg: 96.4137, loss: 0.0867 2023-01-06 13:40:43,388 - mmseg - INFO - Iter [119300/160000] lr: 1.526e-05, eta: 4:54:14, time: 0.423, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0938, decode.acc_seg: 96.1364, loss: 0.0938 2023-01-06 13:41:04,773 - mmseg - INFO - Iter [119350/160000] lr: 1.524e-05, eta: 4:53:52, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0876, decode.acc_seg: 96.2079, loss: 0.0876 2023-01-06 13:41:25,439 - mmseg - INFO - Iter [119400/160000] lr: 1.523e-05, eta: 4:53:30, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.0941, loss: 0.0915 2023-01-06 13:41:48,964 - mmseg - INFO - Iter [119450/160000] lr: 1.521e-05, eta: 4:53:09, time: 0.471, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.4332, loss: 0.0859 2023-01-06 13:42:10,055 - mmseg - INFO - Iter [119500/160000] lr: 1.519e-05, eta: 4:52:47, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0882, decode.acc_seg: 96.2283, loss: 0.0882 2023-01-06 13:42:31,473 - mmseg - INFO - Iter [119550/160000] lr: 1.517e-05, eta: 4:52:25, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.1783, loss: 0.0893 2023-01-06 13:42:52,575 - mmseg - INFO - Iter [119600/160000] lr: 1.515e-05, eta: 4:52:04, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0930, decode.acc_seg: 95.9355, loss: 0.0930 2023-01-06 13:43:13,195 - mmseg - INFO - Iter [119650/160000] lr: 1.513e-05, eta: 4:51:42, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.2179, loss: 0.0893 2023-01-06 13:43:34,036 - mmseg - INFO - Iter [119700/160000] lr: 1.511e-05, eta: 4:51:20, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0871, decode.acc_seg: 96.2872, loss: 0.0871 2023-01-06 13:43:54,937 - mmseg - INFO - Iter [119750/160000] lr: 1.509e-05, eta: 4:50:58, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0873, decode.acc_seg: 96.3002, loss: 0.0873 2023-01-06 13:44:17,852 - mmseg - INFO - Iter [119800/160000] lr: 1.508e-05, eta: 4:50:36, time: 0.458, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.1400, loss: 0.0908 2023-01-06 13:44:39,776 - mmseg - INFO - Iter [119850/160000] lr: 1.506e-05, eta: 4:50:15, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.2679, loss: 0.0870 2023-01-06 13:45:00,453 - mmseg - INFO - Iter [119900/160000] lr: 1.504e-05, eta: 4:49:53, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.1973, loss: 0.0893 2023-01-06 13:45:21,591 - mmseg - INFO - Iter [119950/160000] lr: 1.502e-05, eta: 4:49:31, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0887, decode.acc_seg: 96.2722, loss: 0.0887 2023-01-06 13:45:42,780 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:45:42,781 - mmseg - INFO - Iter [120000/160000] lr: 1.500e-05, eta: 4:49:09, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.3110, loss: 0.0889 2023-01-06 13:46:03,459 - mmseg - INFO - Iter [120050/160000] lr: 1.498e-05, eta: 4:48:47, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0901, decode.acc_seg: 96.0923, loss: 0.0901 2023-01-06 13:46:24,771 - mmseg - INFO - Iter [120100/160000] lr: 1.496e-05, eta: 4:48:25, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4639, loss: 0.0836 2023-01-06 13:46:45,417 - mmseg - INFO - Iter [120150/160000] lr: 1.494e-05, eta: 4:48:03, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.2705, loss: 0.0889 2023-01-06 13:47:08,811 - mmseg - INFO - Iter [120200/160000] lr: 1.493e-05, eta: 4:47:42, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0880, decode.acc_seg: 96.2678, loss: 0.0880 2023-01-06 13:47:29,652 - mmseg - INFO - Iter [120250/160000] lr: 1.491e-05, eta: 4:47:20, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.2219, loss: 0.0893 2023-01-06 13:47:50,694 - mmseg - INFO - Iter [120300/160000] lr: 1.489e-05, eta: 4:46:58, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0928, decode.acc_seg: 95.9894, loss: 0.0928 2023-01-06 13:48:11,846 - mmseg - INFO - Iter [120350/160000] lr: 1.487e-05, eta: 4:46:36, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0857, decode.acc_seg: 96.3656, loss: 0.0857 2023-01-06 13:48:33,053 - mmseg - INFO - Iter [120400/160000] lr: 1.485e-05, eta: 4:46:14, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0881, decode.acc_seg: 96.3213, loss: 0.0881 2023-01-06 13:48:54,074 - mmseg - INFO - Iter [120450/160000] lr: 1.483e-05, eta: 4:45:52, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0878, decode.acc_seg: 96.3005, loss: 0.0878 2023-01-06 13:49:15,584 - mmseg - INFO - Iter [120500/160000] lr: 1.481e-05, eta: 4:45:31, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0855, decode.acc_seg: 96.3625, loss: 0.0855 2023-01-06 13:49:39,629 - mmseg - INFO - Iter [120550/160000] lr: 1.479e-05, eta: 4:45:10, time: 0.481, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0879, decode.acc_seg: 96.1584, loss: 0.0879 2023-01-06 13:50:00,975 - mmseg - INFO - Iter [120600/160000] lr: 1.478e-05, eta: 4:44:48, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.3219, loss: 0.0870 2023-01-06 13:50:22,613 - mmseg - INFO - Iter [120650/160000] lr: 1.476e-05, eta: 4:44:26, time: 0.433, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0910, decode.acc_seg: 96.1720, loss: 0.0910 2023-01-06 13:50:43,261 - mmseg - INFO - Iter [120700/160000] lr: 1.474e-05, eta: 4:44:04, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.3927, loss: 0.0858 2023-01-06 13:51:03,835 - mmseg - INFO - Iter [120750/160000] lr: 1.472e-05, eta: 4:43:42, time: 0.411, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0909, decode.acc_seg: 96.1699, loss: 0.0909 2023-01-06 13:51:25,003 - mmseg - INFO - Iter [120800/160000] lr: 1.470e-05, eta: 4:43:20, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0923, decode.acc_seg: 96.0768, loss: 0.0923 2023-01-06 13:51:45,740 - mmseg - INFO - Iter [120850/160000] lr: 1.468e-05, eta: 4:42:58, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0864, decode.acc_seg: 96.3232, loss: 0.0864 2023-01-06 13:52:06,683 - mmseg - INFO - Iter [120900/160000] lr: 1.466e-05, eta: 4:42:36, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0848, decode.acc_seg: 96.3310, loss: 0.0848 2023-01-06 13:52:30,196 - mmseg - INFO - Iter [120950/160000] lr: 1.464e-05, eta: 4:42:15, time: 0.471, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.3345, loss: 0.0863 2023-01-06 13:52:51,586 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:52:51,587 - mmseg - INFO - Iter [121000/160000] lr: 1.463e-05, eta: 4:41:54, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0885, decode.acc_seg: 96.2100, loss: 0.0885 2023-01-06 13:53:12,471 - mmseg - INFO - Iter [121050/160000] lr: 1.461e-05, eta: 4:41:32, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0888, decode.acc_seg: 96.2573, loss: 0.0888 2023-01-06 13:53:33,854 - mmseg - INFO - Iter [121100/160000] lr: 1.459e-05, eta: 4:41:10, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.2587, loss: 0.0858 2023-01-06 13:53:54,775 - mmseg - INFO - Iter [121150/160000] lr: 1.457e-05, eta: 4:40:48, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0842, decode.acc_seg: 96.3233, loss: 0.0842 2023-01-06 13:54:15,607 - mmseg - INFO - Iter [121200/160000] lr: 1.455e-05, eta: 4:40:26, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0888, decode.acc_seg: 96.2721, loss: 0.0888 2023-01-06 13:54:37,022 - mmseg - INFO - Iter [121250/160000] lr: 1.453e-05, eta: 4:40:04, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0873, decode.acc_seg: 96.2751, loss: 0.0873 2023-01-06 13:55:00,131 - mmseg - INFO - Iter [121300/160000] lr: 1.451e-05, eta: 4:39:43, time: 0.462, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0888, decode.acc_seg: 96.1580, loss: 0.0888 2023-01-06 13:55:20,750 - mmseg - INFO - Iter [121350/160000] lr: 1.449e-05, eta: 4:39:21, time: 0.412, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0942, decode.acc_seg: 96.0917, loss: 0.0942 2023-01-06 13:55:42,480 - mmseg - INFO - Iter [121400/160000] lr: 1.448e-05, eta: 4:38:59, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.2761, loss: 0.0893 2023-01-06 13:56:03,117 - mmseg - INFO - Iter [121450/160000] lr: 1.446e-05, eta: 4:38:37, time: 0.412, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.2504, loss: 0.0877 2023-01-06 13:56:23,907 - mmseg - INFO - Iter [121500/160000] lr: 1.444e-05, eta: 4:38:15, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.2059, loss: 0.0900 2023-01-06 13:56:45,185 - mmseg - INFO - Iter [121550/160000] lr: 1.442e-05, eta: 4:37:54, time: 0.426, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5309, loss: 0.0821 2023-01-06 13:57:05,910 - mmseg - INFO - Iter [121600/160000] lr: 1.440e-05, eta: 4:37:32, time: 0.415, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.1694, loss: 0.0900 2023-01-06 13:57:29,384 - mmseg - INFO - Iter [121650/160000] lr: 1.438e-05, eta: 4:37:10, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.3381, loss: 0.0845 2023-01-06 13:57:50,343 - mmseg - INFO - Iter [121700/160000] lr: 1.436e-05, eta: 4:36:49, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.2981, loss: 0.0874 2023-01-06 13:58:11,836 - mmseg - INFO - Iter [121750/160000] lr: 1.434e-05, eta: 4:36:27, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0868, decode.acc_seg: 96.0750, loss: 0.0868 2023-01-06 13:58:32,698 - mmseg - INFO - Iter [121800/160000] lr: 1.433e-05, eta: 4:36:05, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.3390, loss: 0.0872 2023-01-06 13:58:54,464 - mmseg - INFO - Iter [121850/160000] lr: 1.431e-05, eta: 4:35:43, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0938, decode.acc_seg: 96.1304, loss: 0.0938 2023-01-06 13:59:15,731 - mmseg - INFO - Iter [121900/160000] lr: 1.429e-05, eta: 4:35:21, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0876, decode.acc_seg: 96.3427, loss: 0.0876 2023-01-06 13:59:37,719 - mmseg - INFO - Iter [121950/160000] lr: 1.427e-05, eta: 4:35:00, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0920, decode.acc_seg: 96.1493, loss: 0.0920 2023-01-06 13:59:59,193 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 13:59:59,194 - mmseg - INFO - Iter [122000/160000] lr: 1.425e-05, eta: 4:34:38, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0878, decode.acc_seg: 96.2912, loss: 0.0878 2023-01-06 14:00:23,041 - mmseg - INFO - Iter [122050/160000] lr: 1.423e-05, eta: 4:34:17, time: 0.477, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0916, decode.acc_seg: 96.1240, loss: 0.0916 2023-01-06 14:00:44,137 - mmseg - INFO - Iter [122100/160000] lr: 1.421e-05, eta: 4:33:55, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0840, decode.acc_seg: 96.4591, loss: 0.0840 2023-01-06 14:01:05,465 - mmseg - INFO - Iter [122150/160000] lr: 1.419e-05, eta: 4:33:33, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0847, decode.acc_seg: 96.3237, loss: 0.0847 2023-01-06 14:01:26,049 - mmseg - INFO - Iter [122200/160000] lr: 1.418e-05, eta: 4:33:11, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.3744, loss: 0.0870 2023-01-06 14:01:48,100 - mmseg - INFO - Iter [122250/160000] lr: 1.416e-05, eta: 4:32:50, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.4106, loss: 0.0858 2023-01-06 14:02:08,961 - mmseg - INFO - Iter [122300/160000] lr: 1.414e-05, eta: 4:32:28, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.1421, loss: 0.0877 2023-01-06 14:02:29,767 - mmseg - INFO - Iter [122350/160000] lr: 1.412e-05, eta: 4:32:06, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.1174, loss: 0.0908 2023-01-06 14:02:52,749 - mmseg - INFO - Iter [122400/160000] lr: 1.410e-05, eta: 4:31:45, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.3602, loss: 0.0860 2023-01-06 14:03:13,967 - mmseg - INFO - Iter [122450/160000] lr: 1.408e-05, eta: 4:31:23, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.3558, loss: 0.0860 2023-01-06 14:03:35,024 - mmseg - INFO - Iter [122500/160000] lr: 1.406e-05, eta: 4:31:01, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0853, decode.acc_seg: 96.4117, loss: 0.0853 2023-01-06 14:03:55,781 - mmseg - INFO - Iter [122550/160000] lr: 1.404e-05, eta: 4:30:39, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0913, decode.acc_seg: 96.1352, loss: 0.0913 2023-01-06 14:04:16,515 - mmseg - INFO - Iter [122600/160000] lr: 1.403e-05, eta: 4:30:17, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0894, decode.acc_seg: 96.1030, loss: 0.0894 2023-01-06 14:04:38,275 - mmseg - INFO - Iter [122650/160000] lr: 1.401e-05, eta: 4:29:55, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0895, decode.acc_seg: 96.3259, loss: 0.0895 2023-01-06 14:04:59,930 - mmseg - INFO - Iter [122700/160000] lr: 1.399e-05, eta: 4:29:34, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0930, decode.acc_seg: 96.1223, loss: 0.0930 2023-01-06 14:05:20,517 - mmseg - INFO - Iter [122750/160000] lr: 1.397e-05, eta: 4:29:12, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.3860, loss: 0.0862 2023-01-06 14:05:43,608 - mmseg - INFO - Iter [122800/160000] lr: 1.395e-05, eta: 4:28:50, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0880, decode.acc_seg: 96.2486, loss: 0.0880 2023-01-06 14:06:05,799 - mmseg - INFO - Iter [122850/160000] lr: 1.393e-05, eta: 4:28:29, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0842, decode.acc_seg: 96.4055, loss: 0.0842 2023-01-06 14:06:27,028 - mmseg - INFO - Iter [122900/160000] lr: 1.391e-05, eta: 4:28:07, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.1982, loss: 0.0874 2023-01-06 14:06:47,981 - mmseg - INFO - Iter [122950/160000] lr: 1.389e-05, eta: 4:27:45, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0899, decode.acc_seg: 96.1321, loss: 0.0899 2023-01-06 14:07:08,868 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:07:08,869 - mmseg - INFO - Iter [123000/160000] lr: 1.388e-05, eta: 4:27:23, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0906, decode.acc_seg: 96.1866, loss: 0.0906 2023-01-06 14:07:30,071 - mmseg - INFO - Iter [123050/160000] lr: 1.386e-05, eta: 4:27:01, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3052, loss: 0.0859 2023-01-06 14:07:51,573 - mmseg - INFO - Iter [123100/160000] lr: 1.384e-05, eta: 4:26:40, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0905, decode.acc_seg: 96.2152, loss: 0.0905 2023-01-06 14:08:14,500 - mmseg - INFO - Iter [123150/160000] lr: 1.382e-05, eta: 4:26:18, time: 0.459, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.4503, loss: 0.0838 2023-01-06 14:08:36,255 - mmseg - INFO - Iter [123200/160000] lr: 1.380e-05, eta: 4:25:57, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.3340, loss: 0.0874 2023-01-06 14:08:57,470 - mmseg - INFO - Iter [123250/160000] lr: 1.378e-05, eta: 4:25:35, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0864, decode.acc_seg: 96.3840, loss: 0.0864 2023-01-06 14:09:19,417 - mmseg - INFO - Iter [123300/160000] lr: 1.376e-05, eta: 4:25:13, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.2306, loss: 0.0900 2023-01-06 14:09:40,689 - mmseg - INFO - Iter [123350/160000] lr: 1.374e-05, eta: 4:24:51, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.3221, loss: 0.0872 2023-01-06 14:10:01,252 - mmseg - INFO - Iter [123400/160000] lr: 1.373e-05, eta: 4:24:29, time: 0.411, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.2879, loss: 0.0877 2023-01-06 14:10:22,483 - mmseg - INFO - Iter [123450/160000] lr: 1.371e-05, eta: 4:24:08, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0892, decode.acc_seg: 96.2024, loss: 0.0892 2023-01-06 14:10:43,264 - mmseg - INFO - Iter [123500/160000] lr: 1.369e-05, eta: 4:23:46, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0869, decode.acc_seg: 96.3333, loss: 0.0869 2023-01-06 14:11:06,303 - mmseg - INFO - Iter [123550/160000] lr: 1.367e-05, eta: 4:23:24, time: 0.461, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0926, decode.acc_seg: 96.1339, loss: 0.0926 2023-01-06 14:11:27,212 - mmseg - INFO - Iter [123600/160000] lr: 1.365e-05, eta: 4:23:02, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0914, decode.acc_seg: 96.1372, loss: 0.0914 2023-01-06 14:11:48,191 - mmseg - INFO - Iter [123650/160000] lr: 1.363e-05, eta: 4:22:41, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0880, decode.acc_seg: 96.3176, loss: 0.0880 2023-01-06 14:12:09,558 - mmseg - INFO - Iter [123700/160000] lr: 1.361e-05, eta: 4:22:19, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.2654, loss: 0.0884 2023-01-06 14:12:30,747 - mmseg - INFO - Iter [123750/160000] lr: 1.359e-05, eta: 4:21:57, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0894, decode.acc_seg: 96.1264, loss: 0.0894 2023-01-06 14:12:52,458 - mmseg - INFO - Iter [123800/160000] lr: 1.358e-05, eta: 4:21:35, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0846, decode.acc_seg: 96.4061, loss: 0.0846 2023-01-06 14:13:13,316 - mmseg - INFO - Iter [123850/160000] lr: 1.356e-05, eta: 4:21:13, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0873, decode.acc_seg: 96.3263, loss: 0.0873 2023-01-06 14:13:36,435 - mmseg - INFO - Iter [123900/160000] lr: 1.354e-05, eta: 4:20:52, time: 0.462, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0852, decode.acc_seg: 96.3909, loss: 0.0852 2023-01-06 14:13:57,855 - mmseg - INFO - Iter [123950/160000] lr: 1.352e-05, eta: 4:20:30, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.3706, loss: 0.0845 2023-01-06 14:14:18,831 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:14:18,832 - mmseg - INFO - Iter [124000/160000] lr: 1.350e-05, eta: 4:20:09, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0881, decode.acc_seg: 96.2364, loss: 0.0881 2023-01-06 14:14:40,567 - mmseg - INFO - Iter [124050/160000] lr: 1.348e-05, eta: 4:19:47, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.4522, loss: 0.0829 2023-01-06 14:15:01,569 - mmseg - INFO - Iter [124100/160000] lr: 1.346e-05, eta: 4:19:25, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.2609, loss: 0.0884 2023-01-06 14:15:22,930 - mmseg - INFO - Iter [124150/160000] lr: 1.344e-05, eta: 4:19:03, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0856, decode.acc_seg: 96.3083, loss: 0.0856 2023-01-06 14:15:44,233 - mmseg - INFO - Iter [124200/160000] lr: 1.343e-05, eta: 4:18:41, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0918, decode.acc_seg: 96.2057, loss: 0.0918 2023-01-06 14:16:07,140 - mmseg - INFO - Iter [124250/160000] lr: 1.341e-05, eta: 4:18:20, time: 0.458, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0875, decode.acc_seg: 96.1455, loss: 0.0875 2023-01-06 14:16:27,872 - mmseg - INFO - Iter [124300/160000] lr: 1.339e-05, eta: 4:17:58, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.2819, loss: 0.0872 2023-01-06 14:16:49,350 - mmseg - INFO - Iter [124350/160000] lr: 1.337e-05, eta: 4:17:36, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.3951, loss: 0.0836 2023-01-06 14:17:10,753 - mmseg - INFO - Iter [124400/160000] lr: 1.335e-05, eta: 4:17:15, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.3340, loss: 0.0872 2023-01-06 14:17:31,635 - mmseg - INFO - Iter [124450/160000] lr: 1.333e-05, eta: 4:16:53, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0840, decode.acc_seg: 96.4584, loss: 0.0840 2023-01-06 14:17:52,693 - mmseg - INFO - Iter [124500/160000] lr: 1.331e-05, eta: 4:16:31, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0887, decode.acc_seg: 96.2832, loss: 0.0887 2023-01-06 14:18:13,465 - mmseg - INFO - Iter [124550/160000] lr: 1.329e-05, eta: 4:16:09, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0910, decode.acc_seg: 96.1447, loss: 0.0910 2023-01-06 14:18:35,070 - mmseg - INFO - Iter [124600/160000] lr: 1.328e-05, eta: 4:15:47, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.3530, loss: 0.0872 2023-01-06 14:18:58,526 - mmseg - INFO - Iter [124650/160000] lr: 1.326e-05, eta: 4:15:26, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0834, decode.acc_seg: 96.4145, loss: 0.0834 2023-01-06 14:19:19,825 - mmseg - INFO - Iter [124700/160000] lr: 1.324e-05, eta: 4:15:04, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.1012, loss: 0.0908 2023-01-06 14:19:41,282 - mmseg - INFO - Iter [124750/160000] lr: 1.322e-05, eta: 4:14:43, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0881, decode.acc_seg: 96.3566, loss: 0.0881 2023-01-06 14:20:02,582 - mmseg - INFO - Iter [124800/160000] lr: 1.320e-05, eta: 4:14:21, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0856, decode.acc_seg: 96.3214, loss: 0.0856 2023-01-06 14:20:23,526 - mmseg - INFO - Iter [124850/160000] lr: 1.318e-05, eta: 4:13:59, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.2329, loss: 0.0917 2023-01-06 14:20:44,725 - mmseg - INFO - Iter [124900/160000] lr: 1.316e-05, eta: 4:13:37, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0916, decode.acc_seg: 96.1896, loss: 0.0916 2023-01-06 14:21:05,482 - mmseg - INFO - Iter [124950/160000] lr: 1.314e-05, eta: 4:13:15, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.3028, loss: 0.0874 2023-01-06 14:21:28,361 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:21:28,362 - mmseg - INFO - Iter [125000/160000] lr: 1.313e-05, eta: 4:12:54, time: 0.458, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0865, decode.acc_seg: 96.3943, loss: 0.0865 2023-01-06 14:21:49,188 - mmseg - INFO - Iter [125050/160000] lr: 1.311e-05, eta: 4:12:32, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.2098, loss: 0.0900 2023-01-06 14:22:10,533 - mmseg - INFO - Iter [125100/160000] lr: 1.309e-05, eta: 4:12:10, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0908, decode.acc_seg: 96.1963, loss: 0.0908 2023-01-06 14:22:31,293 - mmseg - INFO - Iter [125150/160000] lr: 1.307e-05, eta: 4:11:48, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0880, decode.acc_seg: 96.3109, loss: 0.0880 2023-01-06 14:22:52,990 - mmseg - INFO - Iter [125200/160000] lr: 1.305e-05, eta: 4:11:26, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0935, decode.acc_seg: 96.0511, loss: 0.0935 2023-01-06 14:23:15,062 - mmseg - INFO - Iter [125250/160000] lr: 1.303e-05, eta: 4:11:05, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0840, decode.acc_seg: 96.4285, loss: 0.0840 2023-01-06 14:23:35,794 - mmseg - INFO - Iter [125300/160000] lr: 1.301e-05, eta: 4:10:43, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0885, decode.acc_seg: 96.1947, loss: 0.0885 2023-01-06 14:23:56,477 - mmseg - INFO - Iter [125350/160000] lr: 1.299e-05, eta: 4:10:21, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.3708, loss: 0.0850 2023-01-06 14:24:19,922 - mmseg - INFO - Iter [125400/160000] lr: 1.298e-05, eta: 4:10:00, time: 0.468, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.2929, loss: 0.0860 2023-01-06 14:24:41,475 - mmseg - INFO - Iter [125450/160000] lr: 1.296e-05, eta: 4:09:38, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0864, decode.acc_seg: 96.3631, loss: 0.0864 2023-01-06 14:25:02,339 - mmseg - INFO - Iter [125500/160000] lr: 1.294e-05, eta: 4:09:16, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0911, decode.acc_seg: 96.1962, loss: 0.0911 2023-01-06 14:25:23,228 - mmseg - INFO - Iter [125550/160000] lr: 1.292e-05, eta: 4:08:54, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0808, decode.acc_seg: 96.4392, loss: 0.0808 2023-01-06 14:25:44,581 - mmseg - INFO - Iter [125600/160000] lr: 1.290e-05, eta: 4:08:33, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.4436, loss: 0.0850 2023-01-06 14:26:06,326 - mmseg - INFO - Iter [125650/160000] lr: 1.288e-05, eta: 4:08:11, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0871, decode.acc_seg: 96.2899, loss: 0.0871 2023-01-06 14:26:27,808 - mmseg - INFO - Iter [125700/160000] lr: 1.286e-05, eta: 4:07:49, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0861, decode.acc_seg: 96.3085, loss: 0.0861 2023-01-06 14:26:51,297 - mmseg - INFO - Iter [125750/160000] lr: 1.284e-05, eta: 4:07:28, time: 0.470, data_time: 0.058, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.2315, loss: 0.0917 2023-01-06 14:27:12,875 - mmseg - INFO - Iter [125800/160000] lr: 1.283e-05, eta: 4:07:06, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0871, decode.acc_seg: 96.1186, loss: 0.0871 2023-01-06 14:27:33,966 - mmseg - INFO - Iter [125850/160000] lr: 1.281e-05, eta: 4:06:44, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.2627, loss: 0.0889 2023-01-06 14:27:55,400 - mmseg - INFO - Iter [125900/160000] lr: 1.279e-05, eta: 4:06:23, time: 0.429, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0855, decode.acc_seg: 96.3724, loss: 0.0855 2023-01-06 14:28:16,344 - mmseg - INFO - Iter [125950/160000] lr: 1.277e-05, eta: 4:06:01, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0827, decode.acc_seg: 96.4157, loss: 0.0827 2023-01-06 14:28:37,237 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:28:37,237 - mmseg - INFO - Iter [126000/160000] lr: 1.275e-05, eta: 4:05:39, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0843, decode.acc_seg: 96.3413, loss: 0.0843 2023-01-06 14:28:58,367 - mmseg - INFO - Iter [126050/160000] lr: 1.273e-05, eta: 4:05:17, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0851, decode.acc_seg: 96.4275, loss: 0.0851 2023-01-06 14:29:19,785 - mmseg - INFO - Iter [126100/160000] lr: 1.271e-05, eta: 4:04:55, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0866, decode.acc_seg: 96.2471, loss: 0.0866 2023-01-06 14:29:43,394 - mmseg - INFO - Iter [126150/160000] lr: 1.269e-05, eta: 4:04:34, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0851, decode.acc_seg: 96.2629, loss: 0.0851 2023-01-06 14:30:04,489 - mmseg - INFO - Iter [126200/160000] lr: 1.268e-05, eta: 4:04:12, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.4293, loss: 0.0838 2023-01-06 14:30:25,796 - mmseg - INFO - Iter [126250/160000] lr: 1.266e-05, eta: 4:03:51, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0811, decode.acc_seg: 96.5396, loss: 0.0811 2023-01-06 14:30:46,551 - mmseg - INFO - Iter [126300/160000] lr: 1.264e-05, eta: 4:03:29, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0905, decode.acc_seg: 96.2474, loss: 0.0905 2023-01-06 14:31:07,623 - mmseg - INFO - Iter [126350/160000] lr: 1.262e-05, eta: 4:03:07, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.2549, loss: 0.0872 2023-01-06 14:31:28,716 - mmseg - INFO - Iter [126400/160000] lr: 1.260e-05, eta: 4:02:45, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0875, decode.acc_seg: 96.2740, loss: 0.0875 2023-01-06 14:31:49,440 - mmseg - INFO - Iter [126450/160000] lr: 1.258e-05, eta: 4:02:23, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.3315, loss: 0.0863 2023-01-06 14:32:13,235 - mmseg - INFO - Iter [126500/160000] lr: 1.256e-05, eta: 4:02:02, time: 0.476, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.3854, loss: 0.0845 2023-01-06 14:32:33,852 - mmseg - INFO - Iter [126550/160000] lr: 1.254e-05, eta: 4:01:40, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0881, decode.acc_seg: 96.2029, loss: 0.0881 2023-01-06 14:32:55,206 - mmseg - INFO - Iter [126600/160000] lr: 1.253e-05, eta: 4:01:18, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0849, decode.acc_seg: 96.4146, loss: 0.0849 2023-01-06 14:33:15,956 - mmseg - INFO - Iter [126650/160000] lr: 1.251e-05, eta: 4:00:56, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.4782, loss: 0.0832 2023-01-06 14:33:36,612 - mmseg - INFO - Iter [126700/160000] lr: 1.249e-05, eta: 4:00:34, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3157, loss: 0.0859 2023-01-06 14:33:57,806 - mmseg - INFO - Iter [126750/160000] lr: 1.247e-05, eta: 4:00:13, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0865, decode.acc_seg: 96.3609, loss: 0.0865 2023-01-06 14:34:18,678 - mmseg - INFO - Iter [126800/160000] lr: 1.245e-05, eta: 3:59:51, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0914, decode.acc_seg: 96.1871, loss: 0.0914 2023-01-06 14:34:39,848 - mmseg - INFO - Iter [126850/160000] lr: 1.243e-05, eta: 3:59:29, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.3417, loss: 0.0870 2023-01-06 14:35:03,136 - mmseg - INFO - Iter [126900/160000] lr: 1.241e-05, eta: 3:59:08, time: 0.466, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0900, decode.acc_seg: 96.2659, loss: 0.0900 2023-01-06 14:35:24,343 - mmseg - INFO - Iter [126950/160000] lr: 1.239e-05, eta: 3:58:46, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0825, decode.acc_seg: 96.4674, loss: 0.0825 2023-01-06 14:35:45,370 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:35:45,371 - mmseg - INFO - Iter [127000/160000] lr: 1.238e-05, eta: 3:58:24, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0920, decode.acc_seg: 96.0984, loss: 0.0920 2023-01-06 14:36:07,104 - mmseg - INFO - Iter [127050/160000] lr: 1.236e-05, eta: 3:58:02, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0827, decode.acc_seg: 96.4311, loss: 0.0827 2023-01-06 14:36:28,908 - mmseg - INFO - Iter [127100/160000] lr: 1.234e-05, eta: 3:57:41, time: 0.437, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0904, decode.acc_seg: 96.1752, loss: 0.0904 2023-01-06 14:36:49,490 - mmseg - INFO - Iter [127150/160000] lr: 1.232e-05, eta: 3:57:19, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.3544, loss: 0.0874 2023-01-06 14:37:10,731 - mmseg - INFO - Iter [127200/160000] lr: 1.230e-05, eta: 3:56:57, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0847, decode.acc_seg: 96.3611, loss: 0.0847 2023-01-06 14:37:34,309 - mmseg - INFO - Iter [127250/160000] lr: 1.228e-05, eta: 3:56:36, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.2128, loss: 0.0893 2023-01-06 14:37:55,401 - mmseg - INFO - Iter [127300/160000] lr: 1.226e-05, eta: 3:56:14, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0854, decode.acc_seg: 96.3877, loss: 0.0854 2023-01-06 14:38:16,877 - mmseg - INFO - Iter [127350/160000] lr: 1.224e-05, eta: 3:55:52, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.2890, loss: 0.0860 2023-01-06 14:38:37,939 - mmseg - INFO - Iter [127400/160000] lr: 1.223e-05, eta: 3:55:30, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0884, decode.acc_seg: 96.2947, loss: 0.0884 2023-01-06 14:38:59,004 - mmseg - INFO - Iter [127450/160000] lr: 1.221e-05, eta: 3:55:09, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0837, decode.acc_seg: 96.3533, loss: 0.0837 2023-01-06 14:39:19,762 - mmseg - INFO - Iter [127500/160000] lr: 1.219e-05, eta: 3:54:47, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0797, decode.acc_seg: 96.5314, loss: 0.0797 2023-01-06 14:39:41,114 - mmseg - INFO - Iter [127550/160000] lr: 1.217e-05, eta: 3:54:25, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0846, decode.acc_seg: 96.4554, loss: 0.0846 2023-01-06 14:40:04,770 - mmseg - INFO - Iter [127600/160000] lr: 1.215e-05, eta: 3:54:04, time: 0.473, data_time: 0.058, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.2610, loss: 0.0870 2023-01-06 14:40:25,449 - mmseg - INFO - Iter [127650/160000] lr: 1.213e-05, eta: 3:53:42, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0823, decode.acc_seg: 96.4664, loss: 0.0823 2023-01-06 14:40:46,221 - mmseg - INFO - Iter [127700/160000] lr: 1.211e-05, eta: 3:53:20, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0853, decode.acc_seg: 96.3971, loss: 0.0853 2023-01-06 14:41:07,399 - mmseg - INFO - Iter [127750/160000] lr: 1.209e-05, eta: 3:52:58, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.3164, loss: 0.0860 2023-01-06 14:41:28,423 - mmseg - INFO - Iter [127800/160000] lr: 1.208e-05, eta: 3:52:36, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0849, decode.acc_seg: 96.3874, loss: 0.0849 2023-01-06 14:41:49,127 - mmseg - INFO - Iter [127850/160000] lr: 1.206e-05, eta: 3:52:14, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0856, decode.acc_seg: 96.3712, loss: 0.0856 2023-01-06 14:42:10,185 - mmseg - INFO - Iter [127900/160000] lr: 1.204e-05, eta: 3:51:53, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.4381, loss: 0.0833 2023-01-06 14:42:32,212 - mmseg - INFO - Iter [127950/160000] lr: 1.202e-05, eta: 3:51:31, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0851, decode.acc_seg: 96.3497, loss: 0.0851 2023-01-06 14:42:55,949 - mmseg - INFO - Saving checkpoint at 128000 iterations 2023-01-06 14:42:59,749 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:42:59,749 - mmseg - INFO - Iter [128000/160000] lr: 1.200e-05, eta: 3:51:11, time: 0.551, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0861, decode.acc_seg: 96.2802, loss: 0.0861 2023-01-06 14:43:27,985 - mmseg - INFO - per class results: 2023-01-06 14:43:27,987 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 98.09 | 98.92 | | sidewalk | 83.69 | 92.08 | | building | 91.91 | 95.93 | | wall | 54.23 | 64.42 | | fence | 55.43 | 68.72 | | pole | 62.07 | 73.02 | | traffic light | 65.74 | 77.04 | | traffic sign | 75.01 | 81.85 | | vegetation | 92.05 | 96.69 | | terrain | 63.95 | 75.38 | | sky | 94.94 | 97.77 | | person | 77.84 | 87.73 | | rider | 54.47 | 71.53 | | car | 93.9 | 97.27 | | truck | 62.38 | 66.16 | | bus | 71.92 | 85.34 | | train | 56.84 | 65.6 | | motorcycle | 45.29 | 52.01 | | bicycle | 71.76 | 87.88 | +---------------+-------+-------+ 2023-01-06 14:43:27,987 - mmseg - INFO - Summary: 2023-01-06 14:43:27,988 - mmseg - INFO - +-------+-------+-------+ | aAcc | mIoU | mAcc | +-------+-------+-------+ | 95.62 | 72.18 | 80.81 | +-------+-------+-------+ 2023-01-06 14:43:27,989 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:43:27,989 - mmseg - INFO - Iter(val) [63] aAcc: 0.9562, mIoU: 0.7218, mAcc: 0.8081, IoU.road: 0.9809, IoU.sidewalk: 0.8369, IoU.building: 0.9191, IoU.wall: 0.5423, IoU.fence: 0.5543, IoU.pole: 0.6207, IoU.traffic light: 0.6574, IoU.traffic sign: 0.7501, IoU.vegetation: 0.9205, IoU.terrain: 0.6395, IoU.sky: 0.9494, IoU.person: 0.7784, IoU.rider: 0.5447, IoU.car: 0.9390, IoU.truck: 0.6238, IoU.bus: 0.7192, IoU.train: 0.5684, IoU.motorcycle: 0.4529, IoU.bicycle: 0.7176, Acc.road: 0.9892, Acc.sidewalk: 0.9208, Acc.building: 0.9593, Acc.wall: 0.6442, Acc.fence: 0.6872, Acc.pole: 0.7302, Acc.traffic light: 0.7704, Acc.traffic sign: 0.8185, Acc.vegetation: 0.9669, Acc.terrain: 0.7538, Acc.sky: 0.9777, Acc.person: 0.8773, Acc.rider: 0.7153, Acc.car: 0.9727, Acc.truck: 0.6616, Acc.bus: 0.8534, Acc.train: 0.6560, Acc.motorcycle: 0.5201, Acc.bicycle: 0.8788 2023-01-06 14:43:49,654 - mmseg - INFO - Iter [128050/160000] lr: 1.198e-05, eta: 3:50:56, time: 0.998, data_time: 0.575, memory: 9591, decode.loss_ce: 0.0871, decode.acc_seg: 96.3587, loss: 0.0871 2023-01-06 14:44:10,285 - mmseg - INFO - Iter [128100/160000] lr: 1.196e-05, eta: 3:50:34, time: 0.413, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0866, decode.acc_seg: 96.3784, loss: 0.0866 2023-01-06 14:44:31,265 - mmseg - INFO - Iter [128150/160000] lr: 1.194e-05, eta: 3:50:12, time: 0.420, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.4382, loss: 0.0863 2023-01-06 14:44:52,399 - mmseg - INFO - Iter [128200/160000] lr: 1.193e-05, eta: 3:49:51, time: 0.423, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.4176, loss: 0.0833 2023-01-06 14:45:13,444 - mmseg - INFO - Iter [128250/160000] lr: 1.191e-05, eta: 3:49:29, time: 0.421, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.3649, loss: 0.0838 2023-01-06 14:45:34,195 - mmseg - INFO - Iter [128300/160000] lr: 1.189e-05, eta: 3:49:07, time: 0.415, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.3054, loss: 0.0872 2023-01-06 14:45:57,512 - mmseg - INFO - Iter [128350/160000] lr: 1.187e-05, eta: 3:48:46, time: 0.466, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0869, decode.acc_seg: 96.3767, loss: 0.0869 2023-01-06 14:46:19,256 - mmseg - INFO - Iter [128400/160000] lr: 1.185e-05, eta: 3:48:24, time: 0.434, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.3122, loss: 0.0863 2023-01-06 14:46:40,573 - mmseg - INFO - Iter [128450/160000] lr: 1.183e-05, eta: 3:48:02, time: 0.426, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.3303, loss: 0.0872 2023-01-06 14:47:01,811 - mmseg - INFO - Iter [128500/160000] lr: 1.181e-05, eta: 3:47:40, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.1774, loss: 0.0893 2023-01-06 14:47:22,649 - mmseg - INFO - Iter [128550/160000] lr: 1.179e-05, eta: 3:47:18, time: 0.417, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.3876, loss: 0.0858 2023-01-06 14:47:43,221 - mmseg - INFO - Iter [128600/160000] lr: 1.178e-05, eta: 3:46:56, time: 0.411, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.3613, loss: 0.0862 2023-01-06 14:48:04,500 - mmseg - INFO - Iter [128650/160000] lr: 1.176e-05, eta: 3:46:35, time: 0.426, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0849, decode.acc_seg: 96.4327, loss: 0.0849 2023-01-06 14:48:25,938 - mmseg - INFO - Iter [128700/160000] lr: 1.174e-05, eta: 3:46:13, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0889, decode.acc_seg: 96.1992, loss: 0.0889 2023-01-06 14:48:49,847 - mmseg - INFO - Iter [128750/160000] lr: 1.172e-05, eta: 3:45:52, time: 0.479, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0842, decode.acc_seg: 96.3939, loss: 0.0842 2023-01-06 14:49:11,143 - mmseg - INFO - Iter [128800/160000] lr: 1.170e-05, eta: 3:45:30, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0839, decode.acc_seg: 96.4055, loss: 0.0839 2023-01-06 14:49:32,260 - mmseg - INFO - Iter [128850/160000] lr: 1.168e-05, eta: 3:45:08, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.3337, loss: 0.0862 2023-01-06 14:49:53,400 - mmseg - INFO - Iter [128900/160000] lr: 1.166e-05, eta: 3:44:46, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.4670, loss: 0.0828 2023-01-06 14:50:14,104 - mmseg - INFO - Iter [128950/160000] lr: 1.164e-05, eta: 3:44:24, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0955, decode.acc_seg: 96.0462, loss: 0.0955 2023-01-06 14:50:34,908 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:50:34,909 - mmseg - INFO - Iter [129000/160000] lr: 1.163e-05, eta: 3:44:03, time: 0.416, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0854, decode.acc_seg: 96.3735, loss: 0.0854 2023-01-06 14:50:55,938 - mmseg - INFO - Iter [129050/160000] lr: 1.161e-05, eta: 3:43:41, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0861, decode.acc_seg: 96.4095, loss: 0.0861 2023-01-06 14:51:19,006 - mmseg - INFO - Iter [129100/160000] lr: 1.159e-05, eta: 3:43:19, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.2656, loss: 0.0870 2023-01-06 14:51:39,899 - mmseg - INFO - Iter [129150/160000] lr: 1.157e-05, eta: 3:42:57, time: 0.418, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0871, decode.acc_seg: 96.3317, loss: 0.0871 2023-01-06 14:52:00,785 - mmseg - INFO - Iter [129200/160000] lr: 1.155e-05, eta: 3:42:36, time: 0.417, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0811, decode.acc_seg: 96.4212, loss: 0.0811 2023-01-06 14:52:22,317 - mmseg - INFO - Iter [129250/160000] lr: 1.153e-05, eta: 3:42:14, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3628, loss: 0.0859 2023-01-06 14:52:43,099 - mmseg - INFO - Iter [129300/160000] lr: 1.151e-05, eta: 3:41:52, time: 0.416, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0804, decode.acc_seg: 96.4975, loss: 0.0804 2023-01-06 14:53:03,998 - mmseg - INFO - Iter [129350/160000] lr: 1.149e-05, eta: 3:41:30, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0960, decode.acc_seg: 96.1086, loss: 0.0960 2023-01-06 14:53:25,434 - mmseg - INFO - Iter [129400/160000] lr: 1.148e-05, eta: 3:41:08, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0925, decode.acc_seg: 96.1460, loss: 0.0925 2023-01-06 14:53:46,677 - mmseg - INFO - Iter [129450/160000] lr: 1.146e-05, eta: 3:40:47, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0847, decode.acc_seg: 96.3991, loss: 0.0847 2023-01-06 14:54:10,422 - mmseg - INFO - Iter [129500/160000] lr: 1.144e-05, eta: 3:40:25, time: 0.475, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0834, decode.acc_seg: 96.3848, loss: 0.0834 2023-01-06 14:54:31,715 - mmseg - INFO - Iter [129550/160000] lr: 1.142e-05, eta: 3:40:04, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0807, decode.acc_seg: 96.5147, loss: 0.0807 2023-01-06 14:54:52,587 - mmseg - INFO - Iter [129600/160000] lr: 1.140e-05, eta: 3:39:42, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0875, decode.acc_seg: 96.3552, loss: 0.0875 2023-01-06 14:55:14,194 - mmseg - INFO - Iter [129650/160000] lr: 1.138e-05, eta: 3:39:20, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0861, decode.acc_seg: 96.3363, loss: 0.0861 2023-01-06 14:55:34,776 - mmseg - INFO - Iter [129700/160000] lr: 1.136e-05, eta: 3:38:58, time: 0.412, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5208, loss: 0.0821 2023-01-06 14:55:56,931 - mmseg - INFO - Iter [129750/160000] lr: 1.134e-05, eta: 3:38:37, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.4539, loss: 0.0822 2023-01-06 14:56:18,705 - mmseg - INFO - Iter [129800/160000] lr: 1.133e-05, eta: 3:38:15, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.3771, loss: 0.0858 2023-01-06 14:56:42,658 - mmseg - INFO - Iter [129850/160000] lr: 1.131e-05, eta: 3:37:54, time: 0.480, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.3188, loss: 0.0870 2023-01-06 14:57:04,581 - mmseg - INFO - Iter [129900/160000] lr: 1.129e-05, eta: 3:37:32, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0924, decode.acc_seg: 96.3232, loss: 0.0924 2023-01-06 14:57:26,428 - mmseg - INFO - Iter [129950/160000] lr: 1.127e-05, eta: 3:37:10, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0873, decode.acc_seg: 96.2801, loss: 0.0873 2023-01-06 14:57:47,691 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 14:57:47,691 - mmseg - INFO - Iter [130000/160000] lr: 1.125e-05, eta: 3:36:49, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.2269, loss: 0.0877 2023-01-06 14:58:08,751 - mmseg - INFO - Iter [130050/160000] lr: 1.123e-05, eta: 3:36:27, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0878, decode.acc_seg: 96.2765, loss: 0.0878 2023-01-06 14:58:30,599 - mmseg - INFO - Iter [130100/160000] lr: 1.121e-05, eta: 3:36:05, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0861, decode.acc_seg: 96.3341, loss: 0.0861 2023-01-06 14:58:51,847 - mmseg - INFO - Iter [130150/160000] lr: 1.119e-05, eta: 3:35:43, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.2209, loss: 0.0859 2023-01-06 14:59:12,678 - mmseg - INFO - Iter [130200/160000] lr: 1.118e-05, eta: 3:35:22, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.4208, loss: 0.0850 2023-01-06 14:59:36,332 - mmseg - INFO - Iter [130250/160000] lr: 1.116e-05, eta: 3:35:00, time: 0.473, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.3260, loss: 0.0862 2023-01-06 14:59:57,452 - mmseg - INFO - Iter [130300/160000] lr: 1.114e-05, eta: 3:34:39, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5161, loss: 0.0818 2023-01-06 15:00:18,469 - mmseg - INFO - Iter [130350/160000] lr: 1.112e-05, eta: 3:34:17, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0885, decode.acc_seg: 96.2464, loss: 0.0885 2023-01-06 15:00:39,147 - mmseg - INFO - Iter [130400/160000] lr: 1.110e-05, eta: 3:33:55, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.4999, loss: 0.0829 2023-01-06 15:01:00,397 - mmseg - INFO - Iter [130450/160000] lr: 1.108e-05, eta: 3:33:33, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0819, decode.acc_seg: 96.4743, loss: 0.0819 2023-01-06 15:01:21,228 - mmseg - INFO - Iter [130500/160000] lr: 1.106e-05, eta: 3:33:11, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0901, decode.acc_seg: 96.2368, loss: 0.0901 2023-01-06 15:01:42,370 - mmseg - INFO - Iter [130550/160000] lr: 1.104e-05, eta: 3:32:49, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0865, decode.acc_seg: 96.2676, loss: 0.0865 2023-01-06 15:02:05,885 - mmseg - INFO - Iter [130600/160000] lr: 1.103e-05, eta: 3:32:28, time: 0.471, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0861, decode.acc_seg: 96.3422, loss: 0.0861 2023-01-06 15:02:26,648 - mmseg - INFO - Iter [130650/160000] lr: 1.101e-05, eta: 3:32:06, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0901, decode.acc_seg: 96.1534, loss: 0.0901 2023-01-06 15:02:47,965 - mmseg - INFO - Iter [130700/160000] lr: 1.099e-05, eta: 3:31:44, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0880, decode.acc_seg: 96.2630, loss: 0.0880 2023-01-06 15:03:08,975 - mmseg - INFO - Iter [130750/160000] lr: 1.097e-05, eta: 3:31:23, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0948, decode.acc_seg: 96.0682, loss: 0.0948 2023-01-06 15:03:30,559 - mmseg - INFO - Iter [130800/160000] lr: 1.095e-05, eta: 3:31:01, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0865, decode.acc_seg: 96.2973, loss: 0.0865 2023-01-06 15:03:51,530 - mmseg - INFO - Iter [130850/160000] lr: 1.093e-05, eta: 3:30:39, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.4434, loss: 0.0826 2023-01-06 15:04:12,569 - mmseg - INFO - Iter [130900/160000] lr: 1.091e-05, eta: 3:30:17, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0839, decode.acc_seg: 96.3586, loss: 0.0839 2023-01-06 15:04:36,250 - mmseg - INFO - Iter [130950/160000] lr: 1.089e-05, eta: 3:29:56, time: 0.473, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0852, decode.acc_seg: 96.4420, loss: 0.0852 2023-01-06 15:04:57,668 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 15:04:57,669 - mmseg - INFO - Iter [131000/160000] lr: 1.088e-05, eta: 3:29:34, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.3569, loss: 0.0862 2023-01-06 15:05:18,782 - mmseg - INFO - Iter [131050/160000] lr: 1.086e-05, eta: 3:29:12, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.3916, loss: 0.0850 2023-01-06 15:05:39,657 - mmseg - INFO - Iter [131100/160000] lr: 1.084e-05, eta: 3:28:51, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0856, decode.acc_seg: 96.3473, loss: 0.0856 2023-01-06 15:06:00,909 - mmseg - INFO - Iter [131150/160000] lr: 1.082e-05, eta: 3:28:29, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0855, decode.acc_seg: 96.3639, loss: 0.0855 2023-01-06 15:06:21,561 - mmseg - INFO - Iter [131200/160000] lr: 1.080e-05, eta: 3:28:07, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0883, decode.acc_seg: 96.2765, loss: 0.0883 2023-01-06 15:06:42,497 - mmseg - INFO - Iter [131250/160000] lr: 1.078e-05, eta: 3:27:45, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.2640, loss: 0.0828 2023-01-06 15:07:03,647 - mmseg - INFO - Iter [131300/160000] lr: 1.076e-05, eta: 3:27:23, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0840, decode.acc_seg: 96.3692, loss: 0.0840 2023-01-06 15:07:27,083 - mmseg - INFO - Iter [131350/160000] lr: 1.074e-05, eta: 3:27:02, time: 0.469, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.5089, loss: 0.0829 2023-01-06 15:07:47,958 - mmseg - INFO - Iter [131400/160000] lr: 1.073e-05, eta: 3:26:40, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0887, decode.acc_seg: 96.3255, loss: 0.0887 2023-01-06 15:08:09,065 - mmseg - INFO - Iter [131450/160000] lr: 1.071e-05, eta: 3:26:18, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.5352, loss: 0.0828 2023-01-06 15:08:30,571 - mmseg - INFO - Iter [131500/160000] lr: 1.069e-05, eta: 3:25:57, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0848, decode.acc_seg: 96.3950, loss: 0.0848 2023-01-06 15:08:51,817 - mmseg - INFO - Iter [131550/160000] lr: 1.067e-05, eta: 3:25:35, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.3900, loss: 0.0835 2023-01-06 15:09:13,137 - mmseg - INFO - Iter [131600/160000] lr: 1.065e-05, eta: 3:25:13, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.4834, loss: 0.0828 2023-01-06 15:09:33,894 - mmseg - INFO - Iter [131650/160000] lr: 1.063e-05, eta: 3:24:51, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.2870, loss: 0.0860 2023-01-06 15:09:57,204 - mmseg - INFO - Iter [131700/160000] lr: 1.061e-05, eta: 3:24:30, time: 0.466, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3599, loss: 0.0859 2023-01-06 15:10:18,439 - mmseg - INFO - Iter [131750/160000] lr: 1.059e-05, eta: 3:24:08, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.4946, loss: 0.0829 2023-01-06 15:10:39,702 - mmseg - INFO - Iter [131800/160000] lr: 1.058e-05, eta: 3:23:46, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0853, decode.acc_seg: 96.4035, loss: 0.0853 2023-01-06 15:11:01,577 - mmseg - INFO - Iter [131850/160000] lr: 1.056e-05, eta: 3:23:25, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0896, decode.acc_seg: 96.1912, loss: 0.0896 2023-01-06 15:11:22,229 - mmseg - INFO - Iter [131900/160000] lr: 1.054e-05, eta: 3:23:03, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.2943, loss: 0.0874 2023-01-06 15:11:43,035 - mmseg - INFO - Iter [131950/160000] lr: 1.052e-05, eta: 3:22:41, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0846, decode.acc_seg: 96.3611, loss: 0.0846 2023-01-06 15:12:04,009 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 15:12:04,010 - mmseg - INFO - Iter [132000/160000] lr: 1.050e-05, eta: 3:22:19, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0899, decode.acc_seg: 96.1354, loss: 0.0899 2023-01-06 15:12:25,352 - mmseg - INFO - Iter [132050/160000] lr: 1.048e-05, eta: 3:21:57, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0898, decode.acc_seg: 96.2805, loss: 0.0898 2023-01-06 15:12:48,574 - mmseg - INFO - Iter [132100/160000] lr: 1.046e-05, eta: 3:21:36, time: 0.464, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0902, decode.acc_seg: 96.1551, loss: 0.0902 2023-01-06 15:13:09,568 - mmseg - INFO - Iter [132150/160000] lr: 1.044e-05, eta: 3:21:14, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0854, decode.acc_seg: 96.4106, loss: 0.0854 2023-01-06 15:13:30,509 - mmseg - INFO - Iter [132200/160000] lr: 1.043e-05, eta: 3:20:52, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.4561, loss: 0.0812 2023-01-06 15:13:52,031 - mmseg - INFO - Iter [132250/160000] lr: 1.041e-05, eta: 3:20:31, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4009, loss: 0.0836 2023-01-06 15:14:13,714 - mmseg - INFO - Iter [132300/160000] lr: 1.039e-05, eta: 3:20:09, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0861, decode.acc_seg: 96.4578, loss: 0.0861 2023-01-06 15:14:35,289 - mmseg - INFO - Iter [132350/160000] lr: 1.037e-05, eta: 3:19:47, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.4477, loss: 0.0818 2023-01-06 15:14:56,641 - mmseg - INFO - Iter [132400/160000] lr: 1.035e-05, eta: 3:19:25, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.5039, loss: 0.0828 2023-01-06 15:15:20,231 - mmseg - INFO - Iter [132450/160000] lr: 1.033e-05, eta: 3:19:04, time: 0.472, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0898, decode.acc_seg: 96.2120, loss: 0.0898 2023-01-06 15:15:41,527 - mmseg - INFO - Iter [132500/160000] lr: 1.031e-05, eta: 3:18:42, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0830, decode.acc_seg: 96.4466, loss: 0.0830 2023-01-06 15:16:03,049 - mmseg - INFO - Iter [132550/160000] lr: 1.029e-05, eta: 3:18:21, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4208, loss: 0.0836 2023-01-06 15:16:23,862 - mmseg - INFO - Iter [132600/160000] lr: 1.028e-05, eta: 3:17:59, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0843, decode.acc_seg: 96.4953, loss: 0.0843 2023-01-06 15:16:44,695 - mmseg - INFO - Iter [132650/160000] lr: 1.026e-05, eta: 3:17:37, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.3748, loss: 0.0838 2023-01-06 15:17:05,389 - mmseg - INFO - Iter [132700/160000] lr: 1.024e-05, eta: 3:17:15, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.4586, loss: 0.0831 2023-01-06 15:17:26,154 - mmseg - INFO - Iter [132750/160000] lr: 1.022e-05, eta: 3:16:53, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4525, loss: 0.0836 2023-01-06 15:17:46,809 - mmseg - INFO - Iter [132800/160000] lr: 1.020e-05, eta: 3:16:31, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0854, decode.acc_seg: 96.2693, loss: 0.0854 2023-01-06 15:18:09,693 - mmseg - INFO - Iter [132850/160000] lr: 1.018e-05, eta: 3:16:10, time: 0.458, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0934, decode.acc_seg: 96.1058, loss: 0.0934 2023-01-06 15:18:30,752 - mmseg - INFO - Iter [132900/160000] lr: 1.016e-05, eta: 3:15:48, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0839, decode.acc_seg: 96.4071, loss: 0.0839 2023-01-06 15:18:52,308 - mmseg - INFO - Iter [132950/160000] lr: 1.014e-05, eta: 3:15:26, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3242, loss: 0.0859 2023-01-06 15:19:13,526 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 15:19:13,526 - mmseg - INFO - Iter [133000/160000] lr: 1.013e-05, eta: 3:15:05, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.4660, loss: 0.0817 2023-01-06 15:19:34,873 - mmseg - INFO - Iter [133050/160000] lr: 1.011e-05, eta: 3:14:43, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0844, decode.acc_seg: 96.3718, loss: 0.0844 2023-01-06 15:19:56,371 - mmseg - INFO - Iter [133100/160000] lr: 1.009e-05, eta: 3:14:21, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0814, decode.acc_seg: 96.5682, loss: 0.0814 2023-01-06 15:20:18,315 - mmseg - INFO - Iter [133150/160000] lr: 1.007e-05, eta: 3:14:00, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0825, decode.acc_seg: 96.5000, loss: 0.0825 2023-01-06 15:20:41,841 - mmseg - INFO - Iter [133200/160000] lr: 1.005e-05, eta: 3:13:38, time: 0.471, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0902, decode.acc_seg: 96.2252, loss: 0.0902 2023-01-06 15:21:02,481 - mmseg - INFO - Iter [133250/160000] lr: 1.003e-05, eta: 3:13:16, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0816, decode.acc_seg: 96.4462, loss: 0.0816 2023-01-06 15:21:23,590 - mmseg - INFO - Iter [133300/160000] lr: 1.001e-05, eta: 3:12:55, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0856, decode.acc_seg: 96.3557, loss: 0.0856 2023-01-06 15:21:45,311 - mmseg - INFO - Iter [133350/160000] lr: 9.994e-06, eta: 3:12:33, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.4069, loss: 0.0862 2023-01-06 15:22:06,661 - mmseg - INFO - Iter [133400/160000] lr: 9.975e-06, eta: 3:12:11, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0837, decode.acc_seg: 96.4844, loss: 0.0837 2023-01-06 15:22:27,679 - mmseg - INFO - Iter [133450/160000] lr: 9.957e-06, eta: 3:11:49, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.3867, loss: 0.0826 2023-01-06 15:22:49,055 - mmseg - INFO - Iter [133500/160000] lr: 9.938e-06, eta: 3:11:28, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0867, decode.acc_seg: 96.3769, loss: 0.0867 2023-01-06 15:23:12,470 - mmseg - INFO - Iter [133550/160000] lr: 9.919e-06, eta: 3:11:06, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0868, decode.acc_seg: 96.2815, loss: 0.0868 2023-01-06 15:23:33,605 - mmseg - INFO - Iter [133600/160000] lr: 9.900e-06, eta: 3:10:45, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0856, decode.acc_seg: 96.3915, loss: 0.0856 2023-01-06 15:23:54,310 - mmseg - INFO - Iter [133650/160000] lr: 9.882e-06, eta: 3:10:23, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.3956, loss: 0.0858 2023-01-06 15:24:15,682 - mmseg - INFO - Iter [133700/160000] lr: 9.863e-06, eta: 3:10:01, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.3321, loss: 0.0850 2023-01-06 15:24:36,874 - mmseg - INFO - Iter [133750/160000] lr: 9.844e-06, eta: 3:09:39, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0827, decode.acc_seg: 96.4995, loss: 0.0827 2023-01-06 15:24:58,778 - mmseg - INFO - Iter [133800/160000] lr: 9.825e-06, eta: 3:09:18, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0888, decode.acc_seg: 96.2666, loss: 0.0888 2023-01-06 15:25:19,418 - mmseg - INFO - Iter [133850/160000] lr: 9.807e-06, eta: 3:08:56, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.5075, loss: 0.0828 2023-01-06 15:25:40,432 - mmseg - INFO - Iter [133900/160000] lr: 9.788e-06, eta: 3:08:34, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0856, decode.acc_seg: 96.3616, loss: 0.0856 2023-01-06 15:26:03,680 - mmseg - INFO - Iter [133950/160000] lr: 9.769e-06, eta: 3:08:13, time: 0.465, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.3886, loss: 0.0833 2023-01-06 15:26:25,475 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 15:26:25,476 - mmseg - INFO - Iter [134000/160000] lr: 9.750e-06, eta: 3:07:51, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0915, decode.acc_seg: 96.1588, loss: 0.0915 2023-01-06 15:26:47,175 - mmseg - INFO - Iter [134050/160000] lr: 9.732e-06, eta: 3:07:29, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.4750, loss: 0.0817 2023-01-06 15:27:07,887 - mmseg - INFO - Iter [134100/160000] lr: 9.713e-06, eta: 3:07:07, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0848, decode.acc_seg: 96.3524, loss: 0.0848 2023-01-06 15:27:28,753 - mmseg - INFO - Iter [134150/160000] lr: 9.694e-06, eta: 3:06:46, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3500, loss: 0.0859 2023-01-06 15:27:50,203 - mmseg - INFO - Iter [134200/160000] lr: 9.675e-06, eta: 3:06:24, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.5383, loss: 0.0822 2023-01-06 15:28:11,721 - mmseg - INFO - Iter [134250/160000] lr: 9.657e-06, eta: 3:06:02, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0813, decode.acc_seg: 96.5093, loss: 0.0813 2023-01-06 15:28:35,369 - mmseg - INFO - Iter [134300/160000] lr: 9.638e-06, eta: 3:05:41, time: 0.473, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0866, decode.acc_seg: 96.3602, loss: 0.0866 2023-01-06 15:28:56,476 - mmseg - INFO - Iter [134350/160000] lr: 9.619e-06, eta: 3:05:19, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0830, decode.acc_seg: 96.4169, loss: 0.0830 2023-01-06 15:29:17,765 - mmseg - INFO - Iter [134400/160000] lr: 9.600e-06, eta: 3:04:57, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0810, decode.acc_seg: 96.4822, loss: 0.0810 2023-01-06 15:29:38,390 - mmseg - INFO - Iter [134450/160000] lr: 9.582e-06, eta: 3:04:35, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.2702, loss: 0.0877 2023-01-06 15:29:59,844 - mmseg - INFO - Iter [134500/160000] lr: 9.563e-06, eta: 3:04:14, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.5170, loss: 0.0826 2023-01-06 15:30:20,442 - mmseg - INFO - Iter [134550/160000] lr: 9.544e-06, eta: 3:03:52, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.2896, loss: 0.0859 2023-01-06 15:30:41,632 - mmseg - INFO - Iter [134600/160000] lr: 9.525e-06, eta: 3:03:30, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.5523, loss: 0.0805 2023-01-06 15:31:02,764 - mmseg - INFO - Iter [134650/160000] lr: 9.507e-06, eta: 3:03:08, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0819, decode.acc_seg: 96.4861, loss: 0.0819 2023-01-06 15:31:25,975 - mmseg - INFO - Iter [134700/160000] lr: 9.488e-06, eta: 3:02:47, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0813, decode.acc_seg: 96.5144, loss: 0.0813 2023-01-06 15:31:47,222 - mmseg - INFO - Iter [134750/160000] lr: 9.469e-06, eta: 3:02:25, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.4764, loss: 0.0812 2023-01-06 15:32:08,782 - mmseg - INFO - Iter [134800/160000] lr: 9.450e-06, eta: 3:02:03, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.3924, loss: 0.0832 2023-01-06 15:32:29,686 - mmseg - INFO - Iter [134850/160000] lr: 9.432e-06, eta: 3:01:42, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.3857, loss: 0.0831 2023-01-06 15:32:50,332 - mmseg - INFO - Iter [134900/160000] lr: 9.413e-06, eta: 3:01:20, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0827, decode.acc_seg: 96.3769, loss: 0.0827 2023-01-06 15:33:11,003 - mmseg - INFO - Iter [134950/160000] lr: 9.394e-06, eta: 3:00:58, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0917, decode.acc_seg: 96.2016, loss: 0.0917 2023-01-06 15:33:31,841 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 15:33:31,841 - mmseg - INFO - Iter [135000/160000] lr: 9.375e-06, eta: 3:00:36, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.2830, loss: 0.0860 2023-01-06 15:33:55,832 - mmseg - INFO - Iter [135050/160000] lr: 9.357e-06, eta: 3:00:15, time: 0.479, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0849, decode.acc_seg: 96.4440, loss: 0.0849 2023-01-06 15:34:17,316 - mmseg - INFO - Iter [135100/160000] lr: 9.338e-06, eta: 2:59:53, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0898, decode.acc_seg: 96.2214, loss: 0.0898 2023-01-06 15:34:38,163 - mmseg - INFO - Iter [135150/160000] lr: 9.319e-06, eta: 2:59:31, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.4874, loss: 0.0833 2023-01-06 15:35:00,905 - mmseg - INFO - Iter [135200/160000] lr: 9.300e-06, eta: 2:59:10, time: 0.454, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0841, decode.acc_seg: 96.4539, loss: 0.0841 2023-01-06 15:35:22,354 - mmseg - INFO - Iter [135250/160000] lr: 9.282e-06, eta: 2:58:48, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0882, decode.acc_seg: 96.2467, loss: 0.0882 2023-01-06 15:35:43,633 - mmseg - INFO - Iter [135300/160000] lr: 9.263e-06, eta: 2:58:26, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4710, loss: 0.0836 2023-01-06 15:36:05,119 - mmseg - INFO - Iter [135350/160000] lr: 9.244e-06, eta: 2:58:05, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0793, decode.acc_seg: 96.5905, loss: 0.0793 2023-01-06 15:36:25,939 - mmseg - INFO - Iter [135400/160000] lr: 9.225e-06, eta: 2:57:43, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4185, loss: 0.0836 2023-01-06 15:36:48,921 - mmseg - INFO - Iter [135450/160000] lr: 9.207e-06, eta: 2:57:21, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.4895, loss: 0.0817 2023-01-06 15:37:10,073 - mmseg - INFO - Iter [135500/160000] lr: 9.188e-06, eta: 2:57:00, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.3155, loss: 0.0860 2023-01-06 15:37:30,953 - mmseg - INFO - Iter [135550/160000] lr: 9.169e-06, eta: 2:56:38, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.3637, loss: 0.0845 2023-01-06 15:37:52,143 - mmseg - INFO - Iter [135600/160000] lr: 9.150e-06, eta: 2:56:16, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0852, decode.acc_seg: 96.4132, loss: 0.0852 2023-01-06 15:38:12,942 - mmseg - INFO - Iter [135650/160000] lr: 9.132e-06, eta: 2:55:54, time: 0.416, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.4573, loss: 0.0833 2023-01-06 15:38:34,642 - mmseg - INFO - Iter [135700/160000] lr: 9.113e-06, eta: 2:55:32, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0847, decode.acc_seg: 96.4747, loss: 0.0847 2023-01-06 15:38:56,729 - mmseg - INFO - Iter [135750/160000] lr: 9.094e-06, eta: 2:55:11, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.3768, loss: 0.0858 2023-01-06 15:39:20,508 - mmseg - INFO - Iter [135800/160000] lr: 9.075e-06, eta: 2:54:50, time: 0.476, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0843, decode.acc_seg: 96.4488, loss: 0.0843 2023-01-06 15:39:42,086 - mmseg - INFO - Iter [135850/160000] lr: 9.057e-06, eta: 2:54:28, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.4626, loss: 0.0831 2023-01-06 15:40:03,239 - mmseg - INFO - Iter [135900/160000] lr: 9.038e-06, eta: 2:54:06, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4624, loss: 0.0836 2023-01-06 15:40:24,196 - mmseg - INFO - Iter [135950/160000] lr: 9.019e-06, eta: 2:53:44, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0839, decode.acc_seg: 96.3921, loss: 0.0839 2023-01-06 15:40:45,028 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 15:40:45,029 - mmseg - INFO - Iter [136000/160000] lr: 9.000e-06, eta: 2:53:23, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.5500, loss: 0.0805 2023-01-06 15:41:06,358 - mmseg - INFO - Iter [136050/160000] lr: 8.982e-06, eta: 2:53:01, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0834, decode.acc_seg: 96.4204, loss: 0.0834 2023-01-06 15:41:27,734 - mmseg - INFO - Iter [136100/160000] lr: 8.963e-06, eta: 2:52:39, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0913, decode.acc_seg: 96.1793, loss: 0.0913 2023-01-06 15:41:48,518 - mmseg - INFO - Iter [136150/160000] lr: 8.944e-06, eta: 2:52:17, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.3242, loss: 0.0874 2023-01-06 15:42:11,666 - mmseg - INFO - Iter [136200/160000] lr: 8.925e-06, eta: 2:51:56, time: 0.463, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0893, decode.acc_seg: 96.2216, loss: 0.0893 2023-01-06 15:42:32,434 - mmseg - INFO - Iter [136250/160000] lr: 8.907e-06, eta: 2:51:34, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0854, decode.acc_seg: 96.3418, loss: 0.0854 2023-01-06 15:42:54,307 - mmseg - INFO - Iter [136300/160000] lr: 8.888e-06, eta: 2:51:12, time: 0.438, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0807, decode.acc_seg: 96.5200, loss: 0.0807 2023-01-06 15:43:15,365 - mmseg - INFO - Iter [136350/160000] lr: 8.869e-06, eta: 2:50:51, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0844, decode.acc_seg: 96.4345, loss: 0.0844 2023-01-06 15:43:37,023 - mmseg - INFO - Iter [136400/160000] lr: 8.850e-06, eta: 2:50:29, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.4537, loss: 0.0833 2023-01-06 15:43:58,245 - mmseg - INFO - Iter [136450/160000] lr: 8.832e-06, eta: 2:50:07, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0855, decode.acc_seg: 96.3980, loss: 0.0855 2023-01-06 15:44:19,875 - mmseg - INFO - Iter [136500/160000] lr: 8.813e-06, eta: 2:49:45, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0883, decode.acc_seg: 96.2531, loss: 0.0883 2023-01-06 15:44:43,169 - mmseg - INFO - Iter [136550/160000] lr: 8.794e-06, eta: 2:49:24, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.4587, loss: 0.0817 2023-01-06 15:45:04,317 - mmseg - INFO - Iter [136600/160000] lr: 8.775e-06, eta: 2:49:02, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.4773, loss: 0.0826 2023-01-06 15:45:25,356 - mmseg - INFO - Iter [136650/160000] lr: 8.757e-06, eta: 2:48:41, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.4204, loss: 0.0845 2023-01-06 15:45:46,904 - mmseg - INFO - Iter [136700/160000] lr: 8.738e-06, eta: 2:48:19, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0844, decode.acc_seg: 96.4346, loss: 0.0844 2023-01-06 15:46:07,889 - mmseg - INFO - Iter [136750/160000] lr: 8.719e-06, eta: 2:47:57, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.3141, loss: 0.0877 2023-01-06 15:46:28,603 - mmseg - INFO - Iter [136800/160000] lr: 8.700e-06, eta: 2:47:35, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0824, decode.acc_seg: 96.4912, loss: 0.0824 2023-01-06 15:46:49,290 - mmseg - INFO - Iter [136850/160000] lr: 8.682e-06, eta: 2:47:13, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.4412, loss: 0.0828 2023-01-06 15:47:12,199 - mmseg - INFO - Iter [136900/160000] lr: 8.663e-06, eta: 2:46:52, time: 0.458, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0816, decode.acc_seg: 96.3448, loss: 0.0816 2023-01-06 15:47:33,045 - mmseg - INFO - Iter [136950/160000] lr: 8.644e-06, eta: 2:46:30, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.4927, loss: 0.0817 2023-01-06 15:47:53,725 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 15:47:53,725 - mmseg - INFO - Iter [137000/160000] lr: 8.625e-06, eta: 2:46:08, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.5406, loss: 0.0805 2023-01-06 15:48:15,177 - mmseg - INFO - Iter [137050/160000] lr: 8.607e-06, eta: 2:45:47, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0813, decode.acc_seg: 96.5405, loss: 0.0813 2023-01-06 15:48:36,950 - mmseg - INFO - Iter [137100/160000] lr: 8.588e-06, eta: 2:45:25, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0873, decode.acc_seg: 96.3353, loss: 0.0873 2023-01-06 15:48:58,226 - mmseg - INFO - Iter [137150/160000] lr: 8.569e-06, eta: 2:45:03, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.3987, loss: 0.0845 2023-01-06 15:49:19,509 - mmseg - INFO - Iter [137200/160000] lr: 8.550e-06, eta: 2:44:41, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.4113, loss: 0.0833 2023-01-06 15:49:41,731 - mmseg - INFO - Iter [137250/160000] lr: 8.532e-06, eta: 2:44:20, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.4236, loss: 0.0860 2023-01-06 15:50:05,615 - mmseg - INFO - Iter [137300/160000] lr: 8.513e-06, eta: 2:43:59, time: 0.478, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0815, decode.acc_seg: 96.4861, loss: 0.0815 2023-01-06 15:50:26,743 - mmseg - INFO - Iter [137350/160000] lr: 8.494e-06, eta: 2:43:37, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.4290, loss: 0.0838 2023-01-06 15:50:47,501 - mmseg - INFO - Iter [137400/160000] lr: 8.475e-06, eta: 2:43:15, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0846, decode.acc_seg: 96.5177, loss: 0.0846 2023-01-06 15:51:08,228 - mmseg - INFO - Iter [137450/160000] lr: 8.457e-06, eta: 2:42:53, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.4510, loss: 0.0838 2023-01-06 15:51:29,328 - mmseg - INFO - Iter [137500/160000] lr: 8.438e-06, eta: 2:42:31, time: 0.422, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0854, decode.acc_seg: 96.3889, loss: 0.0854 2023-01-06 15:51:49,998 - mmseg - INFO - Iter [137550/160000] lr: 8.419e-06, eta: 2:42:10, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.3090, loss: 0.0858 2023-01-06 15:52:11,628 - mmseg - INFO - Iter [137600/160000] lr: 8.400e-06, eta: 2:41:48, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.5081, loss: 0.0828 2023-01-06 15:52:35,147 - mmseg - INFO - Iter [137650/160000] lr: 8.382e-06, eta: 2:41:26, time: 0.470, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0848, decode.acc_seg: 96.3784, loss: 0.0848 2023-01-06 15:52:56,312 - mmseg - INFO - Iter [137700/160000] lr: 8.363e-06, eta: 2:41:05, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.3513, loss: 0.0877 2023-01-06 15:53:17,160 - mmseg - INFO - Iter [137750/160000] lr: 8.344e-06, eta: 2:40:43, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.3550, loss: 0.0850 2023-01-06 15:53:38,657 - mmseg - INFO - Iter [137800/160000] lr: 8.325e-06, eta: 2:40:21, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0806, decode.acc_seg: 96.5801, loss: 0.0806 2023-01-06 15:53:59,739 - mmseg - INFO - Iter [137850/160000] lr: 8.307e-06, eta: 2:39:59, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.5273, loss: 0.0822 2023-01-06 15:54:20,854 - mmseg - INFO - Iter [137900/160000] lr: 8.288e-06, eta: 2:39:38, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0823, decode.acc_seg: 96.4384, loss: 0.0823 2023-01-06 15:54:43,356 - mmseg - INFO - Iter [137950/160000] lr: 8.269e-06, eta: 2:39:16, time: 0.450, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0815, decode.acc_seg: 96.4975, loss: 0.0815 2023-01-06 15:55:04,665 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 15:55:04,666 - mmseg - INFO - Iter [138000/160000] lr: 8.250e-06, eta: 2:38:54, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0823, decode.acc_seg: 96.4005, loss: 0.0823 2023-01-06 15:55:27,852 - mmseg - INFO - Iter [138050/160000] lr: 8.232e-06, eta: 2:38:33, time: 0.464, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0841, decode.acc_seg: 96.3946, loss: 0.0841 2023-01-06 15:55:49,134 - mmseg - INFO - Iter [138100/160000] lr: 8.213e-06, eta: 2:38:11, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5115, loss: 0.0818 2023-01-06 15:56:10,306 - mmseg - INFO - Iter [138150/160000] lr: 8.194e-06, eta: 2:37:50, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0924, decode.acc_seg: 96.2611, loss: 0.0924 2023-01-06 15:56:30,980 - mmseg - INFO - Iter [138200/160000] lr: 8.175e-06, eta: 2:37:28, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.4403, loss: 0.0833 2023-01-06 15:56:52,671 - mmseg - INFO - Iter [138250/160000] lr: 8.157e-06, eta: 2:37:06, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0806, decode.acc_seg: 96.5950, loss: 0.0806 2023-01-06 15:57:13,548 - mmseg - INFO - Iter [138300/160000] lr: 8.138e-06, eta: 2:36:44, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0823, decode.acc_seg: 96.3857, loss: 0.0823 2023-01-06 15:57:34,416 - mmseg - INFO - Iter [138350/160000] lr: 8.119e-06, eta: 2:36:22, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0793, decode.acc_seg: 96.6417, loss: 0.0793 2023-01-06 15:57:57,879 - mmseg - INFO - Iter [138400/160000] lr: 8.100e-06, eta: 2:36:01, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.5912, loss: 0.0820 2023-01-06 15:58:19,678 - mmseg - INFO - Iter [138450/160000] lr: 8.082e-06, eta: 2:35:39, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.3858, loss: 0.0836 2023-01-06 15:58:40,595 - mmseg - INFO - Iter [138500/160000] lr: 8.063e-06, eta: 2:35:18, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0792, decode.acc_seg: 96.5689, loss: 0.0792 2023-01-06 15:59:01,762 - mmseg - INFO - Iter [138550/160000] lr: 8.044e-06, eta: 2:34:56, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.5012, loss: 0.0822 2023-01-06 15:59:22,499 - mmseg - INFO - Iter [138600/160000] lr: 8.025e-06, eta: 2:34:34, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0844, decode.acc_seg: 96.3916, loss: 0.0844 2023-01-06 15:59:44,467 - mmseg - INFO - Iter [138650/160000] lr: 8.007e-06, eta: 2:34:12, time: 0.439, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0881, decode.acc_seg: 96.3338, loss: 0.0881 2023-01-06 16:00:05,578 - mmseg - INFO - Iter [138700/160000] lr: 7.988e-06, eta: 2:33:51, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0800, decode.acc_seg: 96.5164, loss: 0.0800 2023-01-06 16:00:27,591 - mmseg - INFO - Iter [138750/160000] lr: 7.969e-06, eta: 2:33:29, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.5004, loss: 0.0817 2023-01-06 16:00:50,651 - mmseg - INFO - Iter [138800/160000] lr: 7.950e-06, eta: 2:33:08, time: 0.461, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0866, decode.acc_seg: 96.2787, loss: 0.0866 2023-01-06 16:01:11,448 - mmseg - INFO - Iter [138850/160000] lr: 7.932e-06, eta: 2:32:46, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.6180, loss: 0.0794 2023-01-06 16:01:32,781 - mmseg - INFO - Iter [138900/160000] lr: 7.913e-06, eta: 2:32:24, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.4460, loss: 0.0831 2023-01-06 16:01:54,354 - mmseg - INFO - Iter [138950/160000] lr: 7.894e-06, eta: 2:32:02, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0825, decode.acc_seg: 96.5602, loss: 0.0825 2023-01-06 16:02:16,065 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:02:16,065 - mmseg - INFO - Iter [139000/160000] lr: 7.875e-06, eta: 2:31:41, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0804, decode.acc_seg: 96.6076, loss: 0.0804 2023-01-06 16:02:38,281 - mmseg - INFO - Iter [139050/160000] lr: 7.857e-06, eta: 2:31:19, time: 0.444, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0846, decode.acc_seg: 96.4421, loss: 0.0846 2023-01-06 16:02:59,597 - mmseg - INFO - Iter [139100/160000] lr: 7.838e-06, eta: 2:30:57, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.6466, loss: 0.0805 2023-01-06 16:03:22,955 - mmseg - INFO - Iter [139150/160000] lr: 7.819e-06, eta: 2:30:36, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0892, decode.acc_seg: 96.2203, loss: 0.0892 2023-01-06 16:03:44,455 - mmseg - INFO - Iter [139200/160000] lr: 7.800e-06, eta: 2:30:14, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0844, decode.acc_seg: 96.3687, loss: 0.0844 2023-01-06 16:04:05,435 - mmseg - INFO - Iter [139250/160000] lr: 7.782e-06, eta: 2:29:53, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.3968, loss: 0.0858 2023-01-06 16:04:26,252 - mmseg - INFO - Iter [139300/160000] lr: 7.763e-06, eta: 2:29:31, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5104, loss: 0.0821 2023-01-06 16:04:47,511 - mmseg - INFO - Iter [139350/160000] lr: 7.744e-06, eta: 2:29:09, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.6163, loss: 0.0794 2023-01-06 16:05:08,708 - mmseg - INFO - Iter [139400/160000] lr: 7.725e-06, eta: 2:28:47, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0872, decode.acc_seg: 96.3131, loss: 0.0872 2023-01-06 16:05:30,005 - mmseg - INFO - Iter [139450/160000] lr: 7.707e-06, eta: 2:28:26, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0839, decode.acc_seg: 96.4094, loss: 0.0839 2023-01-06 16:05:51,758 - mmseg - INFO - Iter [139500/160000] lr: 7.688e-06, eta: 2:28:04, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0823, decode.acc_seg: 96.5333, loss: 0.0823 2023-01-06 16:06:14,705 - mmseg - INFO - Iter [139550/160000] lr: 7.669e-06, eta: 2:27:42, time: 0.459, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0802, decode.acc_seg: 96.5116, loss: 0.0802 2023-01-06 16:06:36,037 - mmseg - INFO - Iter [139600/160000] lr: 7.650e-06, eta: 2:27:21, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0841, decode.acc_seg: 96.4501, loss: 0.0841 2023-01-06 16:06:56,917 - mmseg - INFO - Iter [139650/160000] lr: 7.632e-06, eta: 2:26:59, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.3700, loss: 0.0863 2023-01-06 16:07:17,658 - mmseg - INFO - Iter [139700/160000] lr: 7.613e-06, eta: 2:26:37, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0780, decode.acc_seg: 96.6097, loss: 0.0780 2023-01-06 16:07:38,390 - mmseg - INFO - Iter [139750/160000] lr: 7.594e-06, eta: 2:26:15, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0839, decode.acc_seg: 96.4169, loss: 0.0839 2023-01-06 16:08:00,006 - mmseg - INFO - Iter [139800/160000] lr: 7.575e-06, eta: 2:25:54, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.5126, loss: 0.0835 2023-01-06 16:08:20,803 - mmseg - INFO - Iter [139850/160000] lr: 7.557e-06, eta: 2:25:32, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0787, decode.acc_seg: 96.6260, loss: 0.0787 2023-01-06 16:08:44,169 - mmseg - INFO - Iter [139900/160000] lr: 7.538e-06, eta: 2:25:10, time: 0.467, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.4308, loss: 0.0831 2023-01-06 16:09:04,859 - mmseg - INFO - Iter [139950/160000] lr: 7.519e-06, eta: 2:24:49, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0853, decode.acc_seg: 96.3603, loss: 0.0853 2023-01-06 16:09:26,423 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:09:26,423 - mmseg - INFO - Iter [140000/160000] lr: 7.500e-06, eta: 2:24:27, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0840, decode.acc_seg: 96.3848, loss: 0.0840 2023-01-06 16:09:47,582 - mmseg - INFO - Iter [140050/160000] lr: 7.482e-06, eta: 2:24:05, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0895, decode.acc_seg: 96.2721, loss: 0.0895 2023-01-06 16:10:08,782 - mmseg - INFO - Iter [140100/160000] lr: 7.463e-06, eta: 2:23:43, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0802, decode.acc_seg: 96.5918, loss: 0.0802 2023-01-06 16:10:30,360 - mmseg - INFO - Iter [140150/160000] lr: 7.444e-06, eta: 2:23:22, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0879, decode.acc_seg: 96.3352, loss: 0.0879 2023-01-06 16:10:51,054 - mmseg - INFO - Iter [140200/160000] lr: 7.425e-06, eta: 2:23:00, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0809, decode.acc_seg: 96.5229, loss: 0.0809 2023-01-06 16:11:14,393 - mmseg - INFO - Iter [140250/160000] lr: 7.407e-06, eta: 2:22:39, time: 0.467, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4672, loss: 0.0836 2023-01-06 16:11:35,114 - mmseg - INFO - Iter [140300/160000] lr: 7.388e-06, eta: 2:22:17, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.3991, loss: 0.0838 2023-01-06 16:11:56,175 - mmseg - INFO - Iter [140350/160000] lr: 7.369e-06, eta: 2:21:55, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0801, decode.acc_seg: 96.5596, loss: 0.0801 2023-01-06 16:12:17,638 - mmseg - INFO - Iter [140400/160000] lr: 7.350e-06, eta: 2:21:33, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0833, decode.acc_seg: 96.4137, loss: 0.0833 2023-01-06 16:12:39,002 - mmseg - INFO - Iter [140450/160000] lr: 7.332e-06, eta: 2:21:12, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.4919, loss: 0.0822 2023-01-06 16:13:00,777 - mmseg - INFO - Iter [140500/160000] lr: 7.313e-06, eta: 2:20:50, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0827, decode.acc_seg: 96.4666, loss: 0.0827 2023-01-06 16:13:21,790 - mmseg - INFO - Iter [140550/160000] lr: 7.294e-06, eta: 2:20:28, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0811, decode.acc_seg: 96.6114, loss: 0.0811 2023-01-06 16:13:43,393 - mmseg - INFO - Iter [140600/160000] lr: 7.275e-06, eta: 2:20:06, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.5015, loss: 0.0831 2023-01-06 16:14:06,881 - mmseg - INFO - Iter [140650/160000] lr: 7.257e-06, eta: 2:19:45, time: 0.470, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.4697, loss: 0.0845 2023-01-06 16:14:28,351 - mmseg - INFO - Iter [140700/160000] lr: 7.238e-06, eta: 2:19:23, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0806, decode.acc_seg: 96.5365, loss: 0.0806 2023-01-06 16:14:49,936 - mmseg - INFO - Iter [140750/160000] lr: 7.219e-06, eta: 2:19:02, time: 0.432, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.5911, loss: 0.0820 2023-01-06 16:15:10,634 - mmseg - INFO - Iter [140800/160000] lr: 7.200e-06, eta: 2:18:40, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0855, decode.acc_seg: 96.3847, loss: 0.0855 2023-01-06 16:15:32,118 - mmseg - INFO - Iter [140850/160000] lr: 7.182e-06, eta: 2:18:18, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0801, decode.acc_seg: 96.4743, loss: 0.0801 2023-01-06 16:15:53,574 - mmseg - INFO - Iter [140900/160000] lr: 7.163e-06, eta: 2:17:56, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0819, decode.acc_seg: 96.4611, loss: 0.0819 2023-01-06 16:16:14,346 - mmseg - INFO - Iter [140950/160000] lr: 7.144e-06, eta: 2:17:35, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.4615, loss: 0.0829 2023-01-06 16:16:38,206 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:16:38,206 - mmseg - INFO - Iter [141000/160000] lr: 7.125e-06, eta: 2:17:13, time: 0.477, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0800, decode.acc_seg: 96.5847, loss: 0.0800 2023-01-06 16:16:59,012 - mmseg - INFO - Iter [141050/160000] lr: 7.107e-06, eta: 2:16:52, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.5248, loss: 0.0812 2023-01-06 16:17:19,995 - mmseg - INFO - Iter [141100/160000] lr: 7.088e-06, eta: 2:16:30, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0782, decode.acc_seg: 96.6872, loss: 0.0782 2023-01-06 16:17:41,015 - mmseg - INFO - Iter [141150/160000] lr: 7.069e-06, eta: 2:16:08, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.4771, loss: 0.0832 2023-01-06 16:18:02,408 - mmseg - INFO - Iter [141200/160000] lr: 7.050e-06, eta: 2:15:46, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.3741, loss: 0.0850 2023-01-06 16:18:23,522 - mmseg - INFO - Iter [141250/160000] lr: 7.032e-06, eta: 2:15:25, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.5529, loss: 0.0828 2023-01-06 16:18:45,527 - mmseg - INFO - Iter [141300/160000] lr: 7.013e-06, eta: 2:15:03, time: 0.440, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0846, decode.acc_seg: 96.4223, loss: 0.0846 2023-01-06 16:19:07,396 - mmseg - INFO - Iter [141350/160000] lr: 6.994e-06, eta: 2:14:41, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.3727, loss: 0.0838 2023-01-06 16:19:31,402 - mmseg - INFO - Iter [141400/160000] lr: 6.975e-06, eta: 2:14:20, time: 0.480, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0809, decode.acc_seg: 96.5026, loss: 0.0809 2023-01-06 16:19:53,570 - mmseg - INFO - Iter [141450/160000] lr: 6.957e-06, eta: 2:13:58, time: 0.443, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0890, decode.acc_seg: 96.2165, loss: 0.0890 2023-01-06 16:20:14,692 - mmseg - INFO - Iter [141500/160000] lr: 6.938e-06, eta: 2:13:37, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0804, decode.acc_seg: 96.6285, loss: 0.0804 2023-01-06 16:20:35,547 - mmseg - INFO - Iter [141550/160000] lr: 6.919e-06, eta: 2:13:15, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5224, loss: 0.0818 2023-01-06 16:20:57,056 - mmseg - INFO - Iter [141600/160000] lr: 6.900e-06, eta: 2:12:53, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.4278, loss: 0.0820 2023-01-06 16:21:18,579 - mmseg - INFO - Iter [141650/160000] lr: 6.882e-06, eta: 2:12:31, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0776, decode.acc_seg: 96.6157, loss: 0.0776 2023-01-06 16:21:40,186 - mmseg - INFO - Iter [141700/160000] lr: 6.863e-06, eta: 2:12:10, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.3936, loss: 0.0828 2023-01-06 16:22:03,807 - mmseg - INFO - Iter [141750/160000] lr: 6.844e-06, eta: 2:11:48, time: 0.473, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0840, decode.acc_seg: 96.3789, loss: 0.0840 2023-01-06 16:22:25,331 - mmseg - INFO - Iter [141800/160000] lr: 6.825e-06, eta: 2:11:27, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0814, decode.acc_seg: 96.5894, loss: 0.0814 2023-01-06 16:22:46,680 - mmseg - INFO - Iter [141850/160000] lr: 6.807e-06, eta: 2:11:05, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.5509, loss: 0.0812 2023-01-06 16:23:08,008 - mmseg - INFO - Iter [141900/160000] lr: 6.788e-06, eta: 2:10:43, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0846, decode.acc_seg: 96.4204, loss: 0.0846 2023-01-06 16:23:29,005 - mmseg - INFO - Iter [141950/160000] lr: 6.769e-06, eta: 2:10:22, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.3323, loss: 0.0863 2023-01-06 16:23:50,861 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:23:50,861 - mmseg - INFO - Iter [142000/160000] lr: 6.750e-06, eta: 2:10:00, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.4525, loss: 0.0821 2023-01-06 16:24:11,599 - mmseg - INFO - Iter [142050/160000] lr: 6.732e-06, eta: 2:09:38, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.5400, loss: 0.0835 2023-01-06 16:24:32,630 - mmseg - INFO - Iter [142100/160000] lr: 6.713e-06, eta: 2:09:16, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0802, decode.acc_seg: 96.4956, loss: 0.0802 2023-01-06 16:24:56,791 - mmseg - INFO - Iter [142150/160000] lr: 6.694e-06, eta: 2:08:55, time: 0.484, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.5625, loss: 0.0812 2023-01-06 16:25:17,753 - mmseg - INFO - Iter [142200/160000] lr: 6.675e-06, eta: 2:08:33, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0814, decode.acc_seg: 96.5267, loss: 0.0814 2023-01-06 16:25:38,686 - mmseg - INFO - Iter [142250/160000] lr: 6.657e-06, eta: 2:08:11, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5072, loss: 0.0821 2023-01-06 16:26:00,148 - mmseg - INFO - Iter [142300/160000] lr: 6.638e-06, eta: 2:07:50, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0774, decode.acc_seg: 96.6642, loss: 0.0774 2023-01-06 16:26:21,031 - mmseg - INFO - Iter [142350/160000] lr: 6.619e-06, eta: 2:07:28, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0827, decode.acc_seg: 96.4488, loss: 0.0827 2023-01-06 16:26:41,827 - mmseg - INFO - Iter [142400/160000] lr: 6.600e-06, eta: 2:07:06, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5212, loss: 0.0821 2023-01-06 16:27:02,800 - mmseg - INFO - Iter [142450/160000] lr: 6.582e-06, eta: 2:06:44, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0790, decode.acc_seg: 96.6124, loss: 0.0790 2023-01-06 16:27:25,843 - mmseg - INFO - Iter [142500/160000] lr: 6.563e-06, eta: 2:06:23, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0813, decode.acc_seg: 96.5443, loss: 0.0813 2023-01-06 16:27:47,015 - mmseg - INFO - Iter [142550/160000] lr: 6.544e-06, eta: 2:06:01, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.4432, loss: 0.0863 2023-01-06 16:28:08,003 - mmseg - INFO - Iter [142600/160000] lr: 6.525e-06, eta: 2:05:40, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.4175, loss: 0.0829 2023-01-06 16:28:29,209 - mmseg - INFO - Iter [142650/160000] lr: 6.507e-06, eta: 2:05:18, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0791, decode.acc_seg: 96.6192, loss: 0.0791 2023-01-06 16:28:50,580 - mmseg - INFO - Iter [142700/160000] lr: 6.488e-06, eta: 2:04:56, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.5960, loss: 0.0794 2023-01-06 16:29:11,778 - mmseg - INFO - Iter [142750/160000] lr: 6.469e-06, eta: 2:04:34, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0875, decode.acc_seg: 96.3302, loss: 0.0875 2023-01-06 16:29:32,564 - mmseg - INFO - Iter [142800/160000] lr: 6.450e-06, eta: 2:04:13, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0773, decode.acc_seg: 96.6408, loss: 0.0773 2023-01-06 16:29:56,369 - mmseg - INFO - Iter [142850/160000] lr: 6.432e-06, eta: 2:03:51, time: 0.477, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4657, loss: 0.0836 2023-01-06 16:30:17,745 - mmseg - INFO - Iter [142900/160000] lr: 6.413e-06, eta: 2:03:29, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0798, decode.acc_seg: 96.5428, loss: 0.0798 2023-01-06 16:30:39,011 - mmseg - INFO - Iter [142950/160000] lr: 6.394e-06, eta: 2:03:08, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5426, loss: 0.0821 2023-01-06 16:30:59,945 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:30:59,946 - mmseg - INFO - Iter [143000/160000] lr: 6.375e-06, eta: 2:02:46, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.4833, loss: 0.0845 2023-01-06 16:31:21,329 - mmseg - INFO - Iter [143050/160000] lr: 6.357e-06, eta: 2:02:24, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4117, loss: 0.0835 2023-01-06 16:31:42,562 - mmseg - INFO - Iter [143100/160000] lr: 6.338e-06, eta: 2:02:03, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0804, decode.acc_seg: 96.5188, loss: 0.0804 2023-01-06 16:32:04,418 - mmseg - INFO - Iter [143150/160000] lr: 6.319e-06, eta: 2:01:41, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.4841, loss: 0.0794 2023-01-06 16:32:25,507 - mmseg - INFO - Iter [143200/160000] lr: 6.300e-06, eta: 2:01:19, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.6037, loss: 0.0784 2023-01-06 16:32:48,389 - mmseg - INFO - Iter [143250/160000] lr: 6.282e-06, eta: 2:00:58, time: 0.458, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.4792, loss: 0.0812 2023-01-06 16:33:09,659 - mmseg - INFO - Iter [143300/160000] lr: 6.263e-06, eta: 2:00:36, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.4321, loss: 0.0831 2023-01-06 16:33:30,707 - mmseg - INFO - Iter [143350/160000] lr: 6.244e-06, eta: 2:00:14, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0816, decode.acc_seg: 96.5257, loss: 0.0816 2023-01-06 16:33:51,465 - mmseg - INFO - Iter [143400/160000] lr: 6.225e-06, eta: 1:59:52, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0874, decode.acc_seg: 96.3547, loss: 0.0874 2023-01-06 16:34:12,113 - mmseg - INFO - Iter [143450/160000] lr: 6.207e-06, eta: 1:59:31, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0791, decode.acc_seg: 96.4366, loss: 0.0791 2023-01-06 16:34:33,337 - mmseg - INFO - Iter [143500/160000] lr: 6.188e-06, eta: 1:59:09, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0852, decode.acc_seg: 96.4545, loss: 0.0852 2023-01-06 16:34:55,279 - mmseg - INFO - Iter [143550/160000] lr: 6.169e-06, eta: 1:58:47, time: 0.438, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.3916, loss: 0.0850 2023-01-06 16:35:18,642 - mmseg - INFO - Iter [143600/160000] lr: 6.150e-06, eta: 1:58:26, time: 0.468, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0791, decode.acc_seg: 96.5818, loss: 0.0791 2023-01-06 16:35:40,050 - mmseg - INFO - Iter [143650/160000] lr: 6.132e-06, eta: 1:58:04, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0830, decode.acc_seg: 96.4952, loss: 0.0830 2023-01-06 16:36:00,652 - mmseg - INFO - Iter [143700/160000] lr: 6.113e-06, eta: 1:57:42, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0803, decode.acc_seg: 96.4876, loss: 0.0803 2023-01-06 16:36:21,440 - mmseg - INFO - Iter [143750/160000] lr: 6.094e-06, eta: 1:57:21, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0869, decode.acc_seg: 96.3320, loss: 0.0869 2023-01-06 16:36:42,330 - mmseg - INFO - Iter [143800/160000] lr: 6.075e-06, eta: 1:56:59, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.3932, loss: 0.0845 2023-01-06 16:37:03,935 - mmseg - INFO - Iter [143850/160000] lr: 6.057e-06, eta: 1:56:37, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.3350, loss: 0.0835 2023-01-06 16:37:25,257 - mmseg - INFO - Iter [143900/160000] lr: 6.038e-06, eta: 1:56:15, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.3735, loss: 0.0832 2023-01-06 16:37:45,902 - mmseg - INFO - Iter [143950/160000] lr: 6.019e-06, eta: 1:55:54, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0814, decode.acc_seg: 96.4793, loss: 0.0814 2023-01-06 16:38:09,393 - mmseg - INFO - Saving checkpoint at 144000 iterations 2023-01-06 16:38:13,085 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:38:13,086 - mmseg - INFO - Iter [144000/160000] lr: 6.000e-06, eta: 1:55:33, time: 0.544, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0841, decode.acc_seg: 96.5630, loss: 0.0841 2023-01-06 16:38:41,311 - mmseg - INFO - per class results: 2023-01-06 16:38:41,314 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 98.02 | 99.0 | | sidewalk | 83.7 | 91.31 | | building | 92.0 | 96.24 | | wall | 53.91 | 61.54 | | fence | 55.87 | 69.59 | | pole | 62.46 | 73.6 | | traffic light | 66.36 | 78.62 | | traffic sign | 75.33 | 83.26 | | vegetation | 92.09 | 96.14 | | terrain | 62.28 | 75.45 | | sky | 94.81 | 97.95 | | person | 78.37 | 89.44 | | rider | 53.92 | 65.03 | | car | 93.75 | 97.78 | | truck | 69.05 | 75.04 | | bus | 74.85 | 82.88 | | train | 59.29 | 64.3 | | motorcycle | 47.87 | 56.18 | | bicycle | 72.25 | 87.44 | +---------------+-------+-------+ 2023-01-06 16:38:41,314 - mmseg - INFO - Summary: 2023-01-06 16:38:41,315 - mmseg - INFO - +-------+-------+------+ | aAcc | mIoU | mAcc | +-------+-------+------+ | 95.65 | 72.96 | 81.1 | +-------+-------+------+ 2023-01-06 16:38:41,315 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:38:41,316 - mmseg - INFO - Iter(val) [63] aAcc: 0.9565, mIoU: 0.7296, mAcc: 0.8110, IoU.road: 0.9802, IoU.sidewalk: 0.8370, IoU.building: 0.9200, IoU.wall: 0.5391, IoU.fence: 0.5587, IoU.pole: 0.6246, IoU.traffic light: 0.6636, IoU.traffic sign: 0.7533, IoU.vegetation: 0.9209, IoU.terrain: 0.6228, IoU.sky: 0.9481, IoU.person: 0.7837, IoU.rider: 0.5392, IoU.car: 0.9375, IoU.truck: 0.6905, IoU.bus: 0.7485, IoU.train: 0.5929, IoU.motorcycle: 0.4787, IoU.bicycle: 0.7225, Acc.road: 0.9900, Acc.sidewalk: 0.9131, Acc.building: 0.9624, Acc.wall: 0.6154, Acc.fence: 0.6959, Acc.pole: 0.7360, Acc.traffic light: 0.7862, Acc.traffic sign: 0.8326, Acc.vegetation: 0.9614, Acc.terrain: 0.7545, Acc.sky: 0.9795, Acc.person: 0.8944, Acc.rider: 0.6503, Acc.car: 0.9778, Acc.truck: 0.7504, Acc.bus: 0.8288, Acc.train: 0.6430, Acc.motorcycle: 0.5618, Acc.bicycle: 0.8744 2023-01-06 16:39:02,100 - mmseg - INFO - Iter [144050/160000] lr: 5.982e-06, eta: 1:55:14, time: 0.980, data_time: 0.575, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.4883, loss: 0.0826 2023-01-06 16:39:22,711 - mmseg - INFO - Iter [144100/160000] lr: 5.963e-06, eta: 1:54:52, time: 0.412, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0807, decode.acc_seg: 96.5541, loss: 0.0807 2023-01-06 16:39:43,555 - mmseg - INFO - Iter [144150/160000] lr: 5.944e-06, eta: 1:54:30, time: 0.416, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0830, decode.acc_seg: 96.3592, loss: 0.0830 2023-01-06 16:40:04,877 - mmseg - INFO - Iter [144200/160000] lr: 5.925e-06, eta: 1:54:09, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0792, decode.acc_seg: 96.6404, loss: 0.0792 2023-01-06 16:40:25,991 - mmseg - INFO - Iter [144250/160000] lr: 5.907e-06, eta: 1:53:47, time: 0.422, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0859, decode.acc_seg: 96.3128, loss: 0.0859 2023-01-06 16:40:46,576 - mmseg - INFO - Iter [144300/160000] lr: 5.888e-06, eta: 1:53:25, time: 0.412, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.5197, loss: 0.0828 2023-01-06 16:41:09,617 - mmseg - INFO - Iter [144350/160000] lr: 5.869e-06, eta: 1:53:04, time: 0.461, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0790, decode.acc_seg: 96.5355, loss: 0.0790 2023-01-06 16:41:30,567 - mmseg - INFO - Iter [144400/160000] lr: 5.850e-06, eta: 1:52:42, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0885, decode.acc_seg: 96.3337, loss: 0.0885 2023-01-06 16:41:51,448 - mmseg - INFO - Iter [144450/160000] lr: 5.832e-06, eta: 1:52:20, time: 0.418, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0816, decode.acc_seg: 96.5005, loss: 0.0816 2023-01-06 16:42:12,116 - mmseg - INFO - Iter [144500/160000] lr: 5.813e-06, eta: 1:51:58, time: 0.413, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0844, decode.acc_seg: 96.4076, loss: 0.0844 2023-01-06 16:42:33,253 - mmseg - INFO - Iter [144550/160000] lr: 5.794e-06, eta: 1:51:37, time: 0.423, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0823, decode.acc_seg: 96.4634, loss: 0.0823 2023-01-06 16:42:53,943 - mmseg - INFO - Iter [144600/160000] lr: 5.775e-06, eta: 1:51:15, time: 0.414, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.6029, loss: 0.0794 2023-01-06 16:43:15,541 - mmseg - INFO - Iter [144650/160000] lr: 5.757e-06, eta: 1:50:53, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0788, decode.acc_seg: 96.6215, loss: 0.0788 2023-01-06 16:43:36,530 - mmseg - INFO - Iter [144700/160000] lr: 5.738e-06, eta: 1:50:31, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5578, loss: 0.0818 2023-01-06 16:44:00,179 - mmseg - INFO - Iter [144750/160000] lr: 5.719e-06, eta: 1:50:10, time: 0.473, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0787, decode.acc_seg: 96.6138, loss: 0.0787 2023-01-06 16:44:21,981 - mmseg - INFO - Iter [144800/160000] lr: 5.700e-06, eta: 1:49:48, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0879, decode.acc_seg: 96.2316, loss: 0.0879 2023-01-06 16:44:43,264 - mmseg - INFO - Iter [144850/160000] lr: 5.682e-06, eta: 1:49:27, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0797, decode.acc_seg: 96.5213, loss: 0.0797 2023-01-06 16:45:04,451 - mmseg - INFO - Iter [144900/160000] lr: 5.663e-06, eta: 1:49:05, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0796, decode.acc_seg: 96.4611, loss: 0.0796 2023-01-06 16:45:26,160 - mmseg - INFO - Iter [144950/160000] lr: 5.644e-06, eta: 1:48:43, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0811, decode.acc_seg: 96.5250, loss: 0.0811 2023-01-06 16:45:46,734 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:45:46,735 - mmseg - INFO - Iter [145000/160000] lr: 5.625e-06, eta: 1:48:21, time: 0.411, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0801, decode.acc_seg: 96.6083, loss: 0.0801 2023-01-06 16:46:07,577 - mmseg - INFO - Iter [145050/160000] lr: 5.607e-06, eta: 1:48:00, time: 0.417, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0803, decode.acc_seg: 96.5370, loss: 0.0803 2023-01-06 16:46:30,437 - mmseg - INFO - Iter [145100/160000] lr: 5.588e-06, eta: 1:47:38, time: 0.457, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0786, decode.acc_seg: 96.6524, loss: 0.0786 2023-01-06 16:46:51,232 - mmseg - INFO - Iter [145150/160000] lr: 5.569e-06, eta: 1:47:16, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0814, decode.acc_seg: 96.5427, loss: 0.0814 2023-01-06 16:47:13,318 - mmseg - INFO - Iter [145200/160000] lr: 5.550e-06, eta: 1:46:55, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5163, loss: 0.0818 2023-01-06 16:47:34,660 - mmseg - INFO - Iter [145250/160000] lr: 5.532e-06, eta: 1:46:33, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0843, decode.acc_seg: 96.4482, loss: 0.0843 2023-01-06 16:47:55,326 - mmseg - INFO - Iter [145300/160000] lr: 5.513e-06, eta: 1:46:11, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0806, decode.acc_seg: 96.5054, loss: 0.0806 2023-01-06 16:48:15,915 - mmseg - INFO - Iter [145350/160000] lr: 5.494e-06, eta: 1:45:49, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.5387, loss: 0.0812 2023-01-06 16:48:37,257 - mmseg - INFO - Iter [145400/160000] lr: 5.475e-06, eta: 1:45:28, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0787, decode.acc_seg: 96.6331, loss: 0.0787 2023-01-06 16:48:58,001 - mmseg - INFO - Iter [145450/160000] lr: 5.457e-06, eta: 1:45:06, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0772, decode.acc_seg: 96.6881, loss: 0.0772 2023-01-06 16:49:21,605 - mmseg - INFO - Iter [145500/160000] lr: 5.438e-06, eta: 1:44:45, time: 0.472, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.5994, loss: 0.0794 2023-01-06 16:49:42,963 - mmseg - INFO - Iter [145550/160000] lr: 5.419e-06, eta: 1:44:23, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.5343, loss: 0.0826 2023-01-06 16:50:03,913 - mmseg - INFO - Iter [145600/160000] lr: 5.400e-06, eta: 1:44:01, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.4650, loss: 0.0845 2023-01-06 16:50:24,831 - mmseg - INFO - Iter [145650/160000] lr: 5.382e-06, eta: 1:43:39, time: 0.418, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.5387, loss: 0.0820 2023-01-06 16:50:45,557 - mmseg - INFO - Iter [145700/160000] lr: 5.363e-06, eta: 1:43:18, time: 0.415, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0850, decode.acc_seg: 96.4914, loss: 0.0850 2023-01-06 16:51:06,656 - mmseg - INFO - Iter [145750/160000] lr: 5.344e-06, eta: 1:42:56, time: 0.422, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.4702, loss: 0.0826 2023-01-06 16:51:27,833 - mmseg - INFO - Iter [145800/160000] lr: 5.325e-06, eta: 1:42:34, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.4416, loss: 0.0831 2023-01-06 16:51:51,317 - mmseg - INFO - Iter [145850/160000] lr: 5.307e-06, eta: 1:42:13, time: 0.469, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0824, decode.acc_seg: 96.4339, loss: 0.0824 2023-01-06 16:52:12,113 - mmseg - INFO - Iter [145900/160000] lr: 5.288e-06, eta: 1:41:51, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.3588, loss: 0.0838 2023-01-06 16:52:32,926 - mmseg - INFO - Iter [145950/160000] lr: 5.269e-06, eta: 1:41:29, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.5281, loss: 0.0817 2023-01-06 16:52:53,564 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 16:52:53,565 - mmseg - INFO - Iter [146000/160000] lr: 5.250e-06, eta: 1:41:07, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0778, decode.acc_seg: 96.6612, loss: 0.0778 2023-01-06 16:53:14,908 - mmseg - INFO - Iter [146050/160000] lr: 5.232e-06, eta: 1:40:46, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0793, decode.acc_seg: 96.5982, loss: 0.0793 2023-01-06 16:53:36,007 - mmseg - INFO - Iter [146100/160000] lr: 5.213e-06, eta: 1:40:24, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0808, decode.acc_seg: 96.5086, loss: 0.0808 2023-01-06 16:53:57,251 - mmseg - INFO - Iter [146150/160000] lr: 5.194e-06, eta: 1:40:02, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4209, loss: 0.0835 2023-01-06 16:54:21,166 - mmseg - INFO - Iter [146200/160000] lr: 5.175e-06, eta: 1:39:41, time: 0.478, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0780, decode.acc_seg: 96.5883, loss: 0.0780 2023-01-06 16:54:41,746 - mmseg - INFO - Iter [146250/160000] lr: 5.157e-06, eta: 1:39:19, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.4711, loss: 0.0832 2023-01-06 16:55:03,337 - mmseg - INFO - Iter [146300/160000] lr: 5.138e-06, eta: 1:38:57, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0790, decode.acc_seg: 96.6134, loss: 0.0790 2023-01-06 16:55:24,808 - mmseg - INFO - Iter [146350/160000] lr: 5.119e-06, eta: 1:38:36, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.5122, loss: 0.0812 2023-01-06 16:55:46,167 - mmseg - INFO - Iter [146400/160000] lr: 5.100e-06, eta: 1:38:14, time: 0.428, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0806, decode.acc_seg: 96.5438, loss: 0.0806 2023-01-06 16:56:07,015 - mmseg - INFO - Iter [146450/160000] lr: 5.082e-06, eta: 1:37:52, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0847, decode.acc_seg: 96.3979, loss: 0.0847 2023-01-06 16:56:27,923 - mmseg - INFO - Iter [146500/160000] lr: 5.063e-06, eta: 1:37:30, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0814, decode.acc_seg: 96.5367, loss: 0.0814 2023-01-06 16:56:48,742 - mmseg - INFO - Iter [146550/160000] lr: 5.044e-06, eta: 1:37:09, time: 0.417, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5707, loss: 0.0821 2023-01-06 16:57:11,535 - mmseg - INFO - Iter [146600/160000] lr: 5.025e-06, eta: 1:36:47, time: 0.456, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0788, decode.acc_seg: 96.5352, loss: 0.0788 2023-01-06 16:57:32,350 - mmseg - INFO - Iter [146650/160000] lr: 5.007e-06, eta: 1:36:25, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0796, decode.acc_seg: 96.5988, loss: 0.0796 2023-01-06 16:57:53,204 - mmseg - INFO - Iter [146700/160000] lr: 4.988e-06, eta: 1:36:04, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0776, decode.acc_seg: 96.6307, loss: 0.0776 2023-01-06 16:58:14,373 - mmseg - INFO - Iter [146750/160000] lr: 4.969e-06, eta: 1:35:42, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0811, decode.acc_seg: 96.5307, loss: 0.0811 2023-01-06 16:58:35,453 - mmseg - INFO - Iter [146800/160000] lr: 4.950e-06, eta: 1:35:20, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0809, decode.acc_seg: 96.5272, loss: 0.0809 2023-01-06 16:58:56,305 - mmseg - INFO - Iter [146850/160000] lr: 4.932e-06, eta: 1:34:58, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.4963, loss: 0.0820 2023-01-06 16:59:17,474 - mmseg - INFO - Iter [146900/160000] lr: 4.913e-06, eta: 1:34:37, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.4884, loss: 0.0812 2023-01-06 16:59:40,428 - mmseg - INFO - Iter [146950/160000] lr: 4.894e-06, eta: 1:34:15, time: 0.459, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.4016, loss: 0.0828 2023-01-06 17:00:01,045 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:00:01,046 - mmseg - INFO - Iter [147000/160000] lr: 4.875e-06, eta: 1:33:53, time: 0.412, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0804, decode.acc_seg: 96.5162, loss: 0.0804 2023-01-06 17:00:22,119 - mmseg - INFO - Iter [147050/160000] lr: 4.857e-06, eta: 1:33:32, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0773, decode.acc_seg: 96.6051, loss: 0.0773 2023-01-06 17:00:42,898 - mmseg - INFO - Iter [147100/160000] lr: 4.838e-06, eta: 1:33:10, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.4656, loss: 0.0820 2023-01-06 17:01:03,508 - mmseg - INFO - Iter [147150/160000] lr: 4.819e-06, eta: 1:32:48, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0815, decode.acc_seg: 96.5079, loss: 0.0815 2023-01-06 17:01:25,189 - mmseg - INFO - Iter [147200/160000] lr: 4.800e-06, eta: 1:32:26, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0858, decode.acc_seg: 96.3377, loss: 0.0858 2023-01-06 17:01:46,361 - mmseg - INFO - Iter [147250/160000] lr: 4.782e-06, eta: 1:32:05, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.5732, loss: 0.0805 2023-01-06 17:02:07,504 - mmseg - INFO - Iter [147300/160000] lr: 4.763e-06, eta: 1:31:43, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0819, decode.acc_seg: 96.4539, loss: 0.0819 2023-01-06 17:02:30,768 - mmseg - INFO - Iter [147350/160000] lr: 4.744e-06, eta: 1:31:22, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0824, decode.acc_seg: 96.4697, loss: 0.0824 2023-01-06 17:02:52,012 - mmseg - INFO - Iter [147400/160000] lr: 4.725e-06, eta: 1:31:00, time: 0.425, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0764, decode.acc_seg: 96.6604, loss: 0.0764 2023-01-06 17:03:13,360 - mmseg - INFO - Iter [147450/160000] lr: 4.707e-06, eta: 1:30:38, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4963, loss: 0.0835 2023-01-06 17:03:34,440 - mmseg - INFO - Iter [147500/160000] lr: 4.688e-06, eta: 1:30:16, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0787, decode.acc_seg: 96.6235, loss: 0.0787 2023-01-06 17:03:55,744 - mmseg - INFO - Iter [147550/160000] lr: 4.669e-06, eta: 1:29:55, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0876, decode.acc_seg: 96.2861, loss: 0.0876 2023-01-06 17:04:17,412 - mmseg - INFO - Iter [147600/160000] lr: 4.650e-06, eta: 1:29:33, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.5302, loss: 0.0820 2023-01-06 17:04:38,117 - mmseg - INFO - Iter [147650/160000] lr: 4.632e-06, eta: 1:29:11, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0770, decode.acc_seg: 96.6606, loss: 0.0770 2023-01-06 17:05:01,667 - mmseg - INFO - Iter [147700/160000] lr: 4.613e-06, eta: 1:28:50, time: 0.470, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0842, decode.acc_seg: 96.4364, loss: 0.0842 2023-01-06 17:05:23,508 - mmseg - INFO - Iter [147750/160000] lr: 4.594e-06, eta: 1:28:28, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0790, decode.acc_seg: 96.6224, loss: 0.0790 2023-01-06 17:05:44,685 - mmseg - INFO - Iter [147800/160000] lr: 4.575e-06, eta: 1:28:06, time: 0.424, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.4410, loss: 0.0829 2023-01-06 17:06:05,720 - mmseg - INFO - Iter [147850/160000] lr: 4.557e-06, eta: 1:27:45, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0788, decode.acc_seg: 96.5970, loss: 0.0788 2023-01-06 17:06:26,773 - mmseg - INFO - Iter [147900/160000] lr: 4.538e-06, eta: 1:27:23, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0795, decode.acc_seg: 96.6293, loss: 0.0795 2023-01-06 17:06:48,273 - mmseg - INFO - Iter [147950/160000] lr: 4.519e-06, eta: 1:27:01, time: 0.431, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0838, decode.acc_seg: 96.4396, loss: 0.0838 2023-01-06 17:07:09,154 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:07:09,154 - mmseg - INFO - Iter [148000/160000] lr: 4.500e-06, eta: 1:26:40, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0797, decode.acc_seg: 96.5781, loss: 0.0797 2023-01-06 17:07:30,369 - mmseg - INFO - Iter [148050/160000] lr: 4.482e-06, eta: 1:26:18, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.5108, loss: 0.0822 2023-01-06 17:07:53,552 - mmseg - INFO - Iter [148100/160000] lr: 4.463e-06, eta: 1:25:56, time: 0.464, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0797, decode.acc_seg: 96.5936, loss: 0.0797 2023-01-06 17:08:14,963 - mmseg - INFO - Iter [148150/160000] lr: 4.444e-06, eta: 1:25:35, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0848, decode.acc_seg: 96.3568, loss: 0.0848 2023-01-06 17:08:36,466 - mmseg - INFO - Iter [148200/160000] lr: 4.425e-06, eta: 1:25:13, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0808, decode.acc_seg: 96.5383, loss: 0.0808 2023-01-06 17:08:57,686 - mmseg - INFO - Iter [148250/160000] lr: 4.407e-06, eta: 1:24:51, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0830, decode.acc_seg: 96.4140, loss: 0.0830 2023-01-06 17:09:18,516 - mmseg - INFO - Iter [148300/160000] lr: 4.388e-06, eta: 1:24:30, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0801, decode.acc_seg: 96.6009, loss: 0.0801 2023-01-06 17:09:39,515 - mmseg - INFO - Iter [148350/160000] lr: 4.369e-06, eta: 1:24:08, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0798, decode.acc_seg: 96.5975, loss: 0.0798 2023-01-06 17:10:01,285 - mmseg - INFO - Iter [148400/160000] lr: 4.350e-06, eta: 1:23:46, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0800, decode.acc_seg: 96.5890, loss: 0.0800 2023-01-06 17:10:24,993 - mmseg - INFO - Iter [148450/160000] lr: 4.332e-06, eta: 1:23:25, time: 0.474, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0808, decode.acc_seg: 96.6317, loss: 0.0808 2023-01-06 17:10:46,796 - mmseg - INFO - Iter [148500/160000] lr: 4.313e-06, eta: 1:23:03, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4371, loss: 0.0835 2023-01-06 17:11:08,190 - mmseg - INFO - Iter [148550/160000] lr: 4.294e-06, eta: 1:22:41, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0790, decode.acc_seg: 96.5579, loss: 0.0790 2023-01-06 17:11:28,830 - mmseg - INFO - Iter [148600/160000] lr: 4.275e-06, eta: 1:22:20, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.4937, loss: 0.0805 2023-01-06 17:11:49,622 - mmseg - INFO - Iter [148650/160000] lr: 4.257e-06, eta: 1:21:58, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.4458, loss: 0.0832 2023-01-06 17:12:10,585 - mmseg - INFO - Iter [148700/160000] lr: 4.238e-06, eta: 1:21:36, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0824, decode.acc_seg: 96.4744, loss: 0.0824 2023-01-06 17:12:32,197 - mmseg - INFO - Iter [148750/160000] lr: 4.219e-06, eta: 1:21:14, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0825, decode.acc_seg: 96.5041, loss: 0.0825 2023-01-06 17:12:53,869 - mmseg - INFO - Iter [148800/160000] lr: 4.200e-06, eta: 1:20:53, time: 0.434, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.3792, loss: 0.0817 2023-01-06 17:13:17,365 - mmseg - INFO - Iter [148850/160000] lr: 4.182e-06, eta: 1:20:31, time: 0.470, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0783, decode.acc_seg: 96.7117, loss: 0.0783 2023-01-06 17:13:38,845 - mmseg - INFO - Iter [148900/160000] lr: 4.163e-06, eta: 1:20:10, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0825, decode.acc_seg: 96.4084, loss: 0.0825 2023-01-06 17:14:00,475 - mmseg - INFO - Iter [148950/160000] lr: 4.144e-06, eta: 1:19:48, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0778, decode.acc_seg: 96.6683, loss: 0.0778 2023-01-06 17:14:21,540 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:14:21,541 - mmseg - INFO - Iter [149000/160000] lr: 4.125e-06, eta: 1:19:26, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0825, decode.acc_seg: 96.5669, loss: 0.0825 2023-01-06 17:14:42,251 - mmseg - INFO - Iter [149050/160000] lr: 4.107e-06, eta: 1:19:04, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0788, decode.acc_seg: 96.5716, loss: 0.0788 2023-01-06 17:15:03,526 - mmseg - INFO - Iter [149100/160000] lr: 4.088e-06, eta: 1:18:43, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5305, loss: 0.0818 2023-01-06 17:15:24,585 - mmseg - INFO - Iter [149150/160000] lr: 4.069e-06, eta: 1:18:21, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0836, decode.acc_seg: 96.4141, loss: 0.0836 2023-01-06 17:15:47,596 - mmseg - INFO - Iter [149200/160000] lr: 4.050e-06, eta: 1:17:59, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0798, decode.acc_seg: 96.5667, loss: 0.0798 2023-01-06 17:16:08,260 - mmseg - INFO - Iter [149250/160000] lr: 4.032e-06, eta: 1:17:38, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0762, decode.acc_seg: 96.5808, loss: 0.0762 2023-01-06 17:16:30,562 - mmseg - INFO - Iter [149300/160000] lr: 4.013e-06, eta: 1:17:16, time: 0.446, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4174, loss: 0.0835 2023-01-06 17:16:51,302 - mmseg - INFO - Iter [149350/160000] lr: 3.994e-06, eta: 1:16:54, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0816, decode.acc_seg: 96.4999, loss: 0.0816 2023-01-06 17:17:12,488 - mmseg - INFO - Iter [149400/160000] lr: 3.975e-06, eta: 1:16:33, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0861, decode.acc_seg: 96.2958, loss: 0.0861 2023-01-06 17:17:33,231 - mmseg - INFO - Iter [149450/160000] lr: 3.957e-06, eta: 1:16:11, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0799, decode.acc_seg: 96.5324, loss: 0.0799 2023-01-06 17:17:54,208 - mmseg - INFO - Iter [149500/160000] lr: 3.938e-06, eta: 1:15:49, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.4672, loss: 0.0822 2023-01-06 17:18:17,979 - mmseg - INFO - Iter [149550/160000] lr: 3.919e-06, eta: 1:15:28, time: 0.475, data_time: 0.058, memory: 9591, decode.loss_ce: 0.0769, decode.acc_seg: 96.6196, loss: 0.0769 2023-01-06 17:18:38,885 - mmseg - INFO - Iter [149600/160000] lr: 3.900e-06, eta: 1:15:06, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0834, decode.acc_seg: 96.4202, loss: 0.0834 2023-01-06 17:19:00,465 - mmseg - INFO - Iter [149650/160000] lr: 3.882e-06, eta: 1:14:44, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.4940, loss: 0.0821 2023-01-06 17:19:21,899 - mmseg - INFO - Iter [149700/160000] lr: 3.863e-06, eta: 1:14:23, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0798, decode.acc_seg: 96.5161, loss: 0.0798 2023-01-06 17:19:42,920 - mmseg - INFO - Iter [149750/160000] lr: 3.844e-06, eta: 1:14:01, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4432, loss: 0.0835 2023-01-06 17:20:04,291 - mmseg - INFO - Iter [149800/160000] lr: 3.825e-06, eta: 1:13:39, time: 0.427, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0862, decode.acc_seg: 96.2413, loss: 0.0862 2023-01-06 17:20:25,424 - mmseg - INFO - Iter [149850/160000] lr: 3.807e-06, eta: 1:13:18, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0767, decode.acc_seg: 96.6766, loss: 0.0767 2023-01-06 17:20:46,036 - mmseg - INFO - Iter [149900/160000] lr: 3.788e-06, eta: 1:12:56, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0823, decode.acc_seg: 96.5222, loss: 0.0823 2023-01-06 17:21:09,305 - mmseg - INFO - Iter [149950/160000] lr: 3.769e-06, eta: 1:12:34, time: 0.465, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.6014, loss: 0.0794 2023-01-06 17:21:30,585 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:21:30,585 - mmseg - INFO - Iter [150000/160000] lr: 3.750e-06, eta: 1:12:13, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.6164, loss: 0.0794 2023-01-06 17:21:51,422 - mmseg - INFO - Iter [150050/160000] lr: 3.732e-06, eta: 1:11:51, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0802, decode.acc_seg: 96.4729, loss: 0.0802 2023-01-06 17:22:12,312 - mmseg - INFO - Iter [150100/160000] lr: 3.713e-06, eta: 1:11:29, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0863, decode.acc_seg: 96.3532, loss: 0.0863 2023-01-06 17:22:33,493 - mmseg - INFO - Iter [150150/160000] lr: 3.694e-06, eta: 1:11:07, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0772, decode.acc_seg: 96.6827, loss: 0.0772 2023-01-06 17:22:54,413 - mmseg - INFO - Iter [150200/160000] lr: 3.675e-06, eta: 1:10:46, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0775, decode.acc_seg: 96.6746, loss: 0.0775 2023-01-06 17:23:15,471 - mmseg - INFO - Iter [150250/160000] lr: 3.657e-06, eta: 1:10:24, time: 0.422, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.4293, loss: 0.0821 2023-01-06 17:23:38,758 - mmseg - INFO - Iter [150300/160000] lr: 3.638e-06, eta: 1:10:02, time: 0.466, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5314, loss: 0.0818 2023-01-06 17:23:59,460 - mmseg - INFO - Iter [150350/160000] lr: 3.619e-06, eta: 1:09:41, time: 0.414, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0847, decode.acc_seg: 96.3734, loss: 0.0847 2023-01-06 17:24:20,464 - mmseg - INFO - Iter [150400/160000] lr: 3.600e-06, eta: 1:09:19, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0778, decode.acc_seg: 96.5458, loss: 0.0778 2023-01-06 17:24:41,239 - mmseg - INFO - Iter [150450/160000] lr: 3.582e-06, eta: 1:08:57, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0800, decode.acc_seg: 96.4989, loss: 0.0800 2023-01-06 17:25:02,073 - mmseg - INFO - Iter [150500/160000] lr: 3.563e-06, eta: 1:08:36, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0819, decode.acc_seg: 96.4868, loss: 0.0819 2023-01-06 17:25:23,720 - mmseg - INFO - Iter [150550/160000] lr: 3.544e-06, eta: 1:08:14, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0864, decode.acc_seg: 96.2415, loss: 0.0864 2023-01-06 17:25:44,938 - mmseg - INFO - Iter [150600/160000] lr: 3.525e-06, eta: 1:07:52, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0819, decode.acc_seg: 96.4739, loss: 0.0819 2023-01-06 17:26:06,065 - mmseg - INFO - Iter [150650/160000] lr: 3.507e-06, eta: 1:07:31, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0809, decode.acc_seg: 96.6085, loss: 0.0809 2023-01-06 17:26:29,112 - mmseg - INFO - Iter [150700/160000] lr: 3.488e-06, eta: 1:07:09, time: 0.460, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0762, decode.acc_seg: 96.7029, loss: 0.0762 2023-01-06 17:26:50,032 - mmseg - INFO - Iter [150750/160000] lr: 3.469e-06, eta: 1:06:47, time: 0.419, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0823, decode.acc_seg: 96.5051, loss: 0.0823 2023-01-06 17:27:11,108 - mmseg - INFO - Iter [150800/160000] lr: 3.450e-06, eta: 1:06:26, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.4397, loss: 0.0829 2023-01-06 17:27:32,008 - mmseg - INFO - Iter [150850/160000] lr: 3.432e-06, eta: 1:06:04, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.4498, loss: 0.0812 2023-01-06 17:27:52,694 - mmseg - INFO - Iter [150900/160000] lr: 3.413e-06, eta: 1:05:42, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.5242, loss: 0.0832 2023-01-06 17:28:13,499 - mmseg - INFO - Iter [150950/160000] lr: 3.394e-06, eta: 1:05:20, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0762, decode.acc_seg: 96.6010, loss: 0.0762 2023-01-06 17:28:35,026 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:28:35,027 - mmseg - INFO - Iter [151000/160000] lr: 3.375e-06, eta: 1:04:59, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0848, decode.acc_seg: 96.4245, loss: 0.0848 2023-01-06 17:28:58,286 - mmseg - INFO - Iter [151050/160000] lr: 3.357e-06, eta: 1:04:37, time: 0.465, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0793, decode.acc_seg: 96.5635, loss: 0.0793 2023-01-06 17:29:20,336 - mmseg - INFO - Iter [151100/160000] lr: 3.338e-06, eta: 1:04:16, time: 0.442, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.4740, loss: 0.0822 2023-01-06 17:29:41,777 - mmseg - INFO - Iter [151150/160000] lr: 3.319e-06, eta: 1:03:54, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0870, decode.acc_seg: 96.3231, loss: 0.0870 2023-01-06 17:30:03,815 - mmseg - INFO - Iter [151200/160000] lr: 3.300e-06, eta: 1:03:32, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4168, loss: 0.0835 2023-01-06 17:30:24,689 - mmseg - INFO - Iter [151250/160000] lr: 3.282e-06, eta: 1:03:10, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0843, decode.acc_seg: 96.4311, loss: 0.0843 2023-01-06 17:30:45,729 - mmseg - INFO - Iter [151300/160000] lr: 3.263e-06, eta: 1:02:49, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0803, decode.acc_seg: 96.5654, loss: 0.0803 2023-01-06 17:31:06,395 - mmseg - INFO - Iter [151350/160000] lr: 3.244e-06, eta: 1:02:27, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.4690, loss: 0.0832 2023-01-06 17:31:27,627 - mmseg - INFO - Iter [151400/160000] lr: 3.225e-06, eta: 1:02:05, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0800, decode.acc_seg: 96.5472, loss: 0.0800 2023-01-06 17:31:50,650 - mmseg - INFO - Iter [151450/160000] lr: 3.207e-06, eta: 1:01:44, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0837, decode.acc_seg: 96.4483, loss: 0.0837 2023-01-06 17:32:11,426 - mmseg - INFO - Iter [151500/160000] lr: 3.188e-06, eta: 1:01:22, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0787, decode.acc_seg: 96.5880, loss: 0.0787 2023-01-06 17:32:32,473 - mmseg - INFO - Iter [151550/160000] lr: 3.169e-06, eta: 1:01:00, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.3890, loss: 0.0831 2023-01-06 17:32:54,041 - mmseg - INFO - Iter [151600/160000] lr: 3.150e-06, eta: 1:00:39, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0819, decode.acc_seg: 96.5137, loss: 0.0819 2023-01-06 17:33:14,844 - mmseg - INFO - Iter [151650/160000] lr: 3.132e-06, eta: 1:00:17, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0814, decode.acc_seg: 96.4945, loss: 0.0814 2023-01-06 17:33:36,101 - mmseg - INFO - Iter [151700/160000] lr: 3.113e-06, eta: 0:59:55, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0785, decode.acc_seg: 96.6288, loss: 0.0785 2023-01-06 17:33:57,134 - mmseg - INFO - Iter [151750/160000] lr: 3.094e-06, eta: 0:59:34, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0808, decode.acc_seg: 96.5598, loss: 0.0808 2023-01-06 17:34:20,899 - mmseg - INFO - Iter [151800/160000] lr: 3.075e-06, eta: 0:59:12, time: 0.475, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.4983, loss: 0.0832 2023-01-06 17:34:42,038 - mmseg - INFO - Iter [151850/160000] lr: 3.057e-06, eta: 0:58:50, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0799, decode.acc_seg: 96.6151, loss: 0.0799 2023-01-06 17:35:02,811 - mmseg - INFO - Iter [151900/160000] lr: 3.038e-06, eta: 0:58:29, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5642, loss: 0.0821 2023-01-06 17:35:23,924 - mmseg - INFO - Iter [151950/160000] lr: 3.019e-06, eta: 0:58:07, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0845, decode.acc_seg: 96.3698, loss: 0.0845 2023-01-06 17:35:44,852 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:35:44,852 - mmseg - INFO - Iter [152000/160000] lr: 3.000e-06, eta: 0:57:45, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4109, loss: 0.0835 2023-01-06 17:36:06,012 - mmseg - INFO - Iter [152050/160000] lr: 2.982e-06, eta: 0:57:24, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0812, decode.acc_seg: 96.5669, loss: 0.0812 2023-01-06 17:36:26,713 - mmseg - INFO - Iter [152100/160000] lr: 2.963e-06, eta: 0:57:02, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0832, decode.acc_seg: 96.4323, loss: 0.0832 2023-01-06 17:36:49,857 - mmseg - INFO - Iter [152150/160000] lr: 2.944e-06, eta: 0:56:40, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.5443, loss: 0.0821 2023-01-06 17:37:11,617 - mmseg - INFO - Iter [152200/160000] lr: 2.925e-06, eta: 0:56:19, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0831, decode.acc_seg: 96.4171, loss: 0.0831 2023-01-06 17:37:33,364 - mmseg - INFO - Iter [152250/160000] lr: 2.907e-06, eta: 0:55:57, time: 0.435, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.4790, loss: 0.0877 2023-01-06 17:37:54,426 - mmseg - INFO - Iter [152300/160000] lr: 2.888e-06, eta: 0:55:35, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.5748, loss: 0.0805 2023-01-06 17:38:15,643 - mmseg - INFO - Iter [152350/160000] lr: 2.869e-06, eta: 0:55:14, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0798, decode.acc_seg: 96.5620, loss: 0.0798 2023-01-06 17:38:36,783 - mmseg - INFO - Iter [152400/160000] lr: 2.850e-06, eta: 0:54:52, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0796, decode.acc_seg: 96.5565, loss: 0.0796 2023-01-06 17:38:57,551 - mmseg - INFO - Iter [152450/160000] lr: 2.832e-06, eta: 0:54:30, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0808, decode.acc_seg: 96.3683, loss: 0.0808 2023-01-06 17:39:18,515 - mmseg - INFO - Iter [152500/160000] lr: 2.813e-06, eta: 0:54:09, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0781, decode.acc_seg: 96.6217, loss: 0.0781 2023-01-06 17:39:43,339 - mmseg - INFO - Iter [152550/160000] lr: 2.794e-06, eta: 0:53:47, time: 0.497, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0843, decode.acc_seg: 96.3679, loss: 0.0843 2023-01-06 17:40:04,232 - mmseg - INFO - Iter [152600/160000] lr: 2.775e-06, eta: 0:53:25, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0789, decode.acc_seg: 96.6264, loss: 0.0789 2023-01-06 17:40:26,000 - mmseg - INFO - Iter [152650/160000] lr: 2.757e-06, eta: 0:53:04, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.6302, loss: 0.0784 2023-01-06 17:40:47,272 - mmseg - INFO - Iter [152700/160000] lr: 2.738e-06, eta: 0:52:42, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0797, decode.acc_seg: 96.5767, loss: 0.0797 2023-01-06 17:41:08,187 - mmseg - INFO - Iter [152750/160000] lr: 2.719e-06, eta: 0:52:20, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0824, decode.acc_seg: 96.4994, loss: 0.0824 2023-01-06 17:41:29,389 - mmseg - INFO - Iter [152800/160000] lr: 2.700e-06, eta: 0:51:59, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0764, decode.acc_seg: 96.6596, loss: 0.0764 2023-01-06 17:41:50,578 - mmseg - INFO - Iter [152850/160000] lr: 2.682e-06, eta: 0:51:37, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.6449, loss: 0.0784 2023-01-06 17:42:13,857 - mmseg - INFO - Iter [152900/160000] lr: 2.663e-06, eta: 0:51:15, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0877, decode.acc_seg: 96.3667, loss: 0.0877 2023-01-06 17:42:34,816 - mmseg - INFO - Iter [152950/160000] lr: 2.644e-06, eta: 0:50:54, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0796, decode.acc_seg: 96.4998, loss: 0.0796 2023-01-06 17:42:55,792 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:42:55,793 - mmseg - INFO - Iter [153000/160000] lr: 2.625e-06, eta: 0:50:32, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0881, decode.acc_seg: 96.2558, loss: 0.0881 2023-01-06 17:43:16,801 - mmseg - INFO - Iter [153050/160000] lr: 2.607e-06, eta: 0:50:10, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0806, decode.acc_seg: 96.5375, loss: 0.0806 2023-01-06 17:43:38,566 - mmseg - INFO - Iter [153100/160000] lr: 2.588e-06, eta: 0:49:49, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0772, decode.acc_seg: 96.7276, loss: 0.0772 2023-01-06 17:43:59,765 - mmseg - INFO - Iter [153150/160000] lr: 2.569e-06, eta: 0:49:27, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0769, decode.acc_seg: 96.6671, loss: 0.0769 2023-01-06 17:44:21,625 - mmseg - INFO - Iter [153200/160000] lr: 2.550e-06, eta: 0:49:05, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0766, decode.acc_seg: 96.6944, loss: 0.0766 2023-01-06 17:44:42,830 - mmseg - INFO - Iter [153250/160000] lr: 2.532e-06, eta: 0:48:44, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.4907, loss: 0.0820 2023-01-06 17:45:05,899 - mmseg - INFO - Iter [153300/160000] lr: 2.513e-06, eta: 0:48:22, time: 0.461, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0785, decode.acc_seg: 96.6260, loss: 0.0785 2023-01-06 17:45:26,859 - mmseg - INFO - Iter [153350/160000] lr: 2.494e-06, eta: 0:48:00, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0804, decode.acc_seg: 96.6393, loss: 0.0804 2023-01-06 17:45:47,995 - mmseg - INFO - Iter [153400/160000] lr: 2.475e-06, eta: 0:47:39, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0821, decode.acc_seg: 96.4814, loss: 0.0821 2023-01-06 17:46:08,880 - mmseg - INFO - Iter [153450/160000] lr: 2.457e-06, eta: 0:47:17, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.5810, loss: 0.0794 2023-01-06 17:46:29,872 - mmseg - INFO - Iter [153500/160000] lr: 2.438e-06, eta: 0:46:55, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0811, decode.acc_seg: 96.5648, loss: 0.0811 2023-01-06 17:46:50,923 - mmseg - INFO - Iter [153550/160000] lr: 2.419e-06, eta: 0:46:34, time: 0.421, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5103, loss: 0.0818 2023-01-06 17:47:12,184 - mmseg - INFO - Iter [153600/160000] lr: 2.400e-06, eta: 0:46:12, time: 0.425, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0780, decode.acc_seg: 96.6254, loss: 0.0780 2023-01-06 17:47:35,265 - mmseg - INFO - Iter [153650/160000] lr: 2.382e-06, eta: 0:45:50, time: 0.462, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.4329, loss: 0.0826 2023-01-06 17:47:56,435 - mmseg - INFO - Iter [153700/160000] lr: 2.363e-06, eta: 0:45:29, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0819, decode.acc_seg: 96.5745, loss: 0.0819 2023-01-06 17:48:17,298 - mmseg - INFO - Iter [153750/160000] lr: 2.344e-06, eta: 0:45:07, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0790, decode.acc_seg: 96.6342, loss: 0.0790 2023-01-06 17:48:39,001 - mmseg - INFO - Iter [153800/160000] lr: 2.325e-06, eta: 0:44:45, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0779, decode.acc_seg: 96.5470, loss: 0.0779 2023-01-06 17:49:00,512 - mmseg - INFO - Iter [153850/160000] lr: 2.307e-06, eta: 0:44:24, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0778, decode.acc_seg: 96.6041, loss: 0.0778 2023-01-06 17:49:21,374 - mmseg - INFO - Iter [153900/160000] lr: 2.288e-06, eta: 0:44:02, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0771, decode.acc_seg: 96.6511, loss: 0.0771 2023-01-06 17:49:42,363 - mmseg - INFO - Iter [153950/160000] lr: 2.269e-06, eta: 0:43:40, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0783, decode.acc_seg: 96.6278, loss: 0.0783 2023-01-06 17:50:03,830 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:50:03,830 - mmseg - INFO - Iter [154000/160000] lr: 2.250e-06, eta: 0:43:19, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0781, decode.acc_seg: 96.6154, loss: 0.0781 2023-01-06 17:50:26,926 - mmseg - INFO - Iter [154050/160000] lr: 2.232e-06, eta: 0:42:57, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0806, decode.acc_seg: 96.4995, loss: 0.0806 2023-01-06 17:50:48,144 - mmseg - INFO - Iter [154100/160000] lr: 2.213e-06, eta: 0:42:35, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0765, decode.acc_seg: 96.6322, loss: 0.0765 2023-01-06 17:51:08,761 - mmseg - INFO - Iter [154150/160000] lr: 2.194e-06, eta: 0:42:14, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0792, decode.acc_seg: 96.6146, loss: 0.0792 2023-01-06 17:51:29,932 - mmseg - INFO - Iter [154200/160000] lr: 2.175e-06, eta: 0:41:52, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0800, decode.acc_seg: 96.5972, loss: 0.0800 2023-01-06 17:51:51,279 - mmseg - INFO - Iter [154250/160000] lr: 2.157e-06, eta: 0:41:30, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.4326, loss: 0.0860 2023-01-06 17:52:12,907 - mmseg - INFO - Iter [154300/160000] lr: 2.138e-06, eta: 0:41:09, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0760, decode.acc_seg: 96.6947, loss: 0.0760 2023-01-06 17:52:34,451 - mmseg - INFO - Iter [154350/160000] lr: 2.119e-06, eta: 0:40:47, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0824, decode.acc_seg: 96.4929, loss: 0.0824 2023-01-06 17:52:57,765 - mmseg - INFO - Iter [154400/160000] lr: 2.100e-06, eta: 0:40:25, time: 0.466, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0813, decode.acc_seg: 96.5691, loss: 0.0813 2023-01-06 17:53:18,465 - mmseg - INFO - Iter [154450/160000] lr: 2.082e-06, eta: 0:40:04, time: 0.414, data_time: 0.010, memory: 9591, decode.loss_ce: 0.0851, decode.acc_seg: 96.4350, loss: 0.0851 2023-01-06 17:53:39,504 - mmseg - INFO - Iter [154500/160000] lr: 2.063e-06, eta: 0:39:42, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0772, decode.acc_seg: 96.7442, loss: 0.0772 2023-01-06 17:54:00,818 - mmseg - INFO - Iter [154550/160000] lr: 2.044e-06, eta: 0:39:20, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0781, decode.acc_seg: 96.6377, loss: 0.0781 2023-01-06 17:54:21,845 - mmseg - INFO - Iter [154600/160000] lr: 2.025e-06, eta: 0:38:59, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0799, decode.acc_seg: 96.5897, loss: 0.0799 2023-01-06 17:54:42,820 - mmseg - INFO - Iter [154650/160000] lr: 2.007e-06, eta: 0:38:37, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.3872, loss: 0.0818 2023-01-06 17:55:03,823 - mmseg - INFO - Iter [154700/160000] lr: 1.988e-06, eta: 0:38:15, time: 0.421, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0818, decode.acc_seg: 96.5695, loss: 0.0818 2023-01-06 17:55:24,794 - mmseg - INFO - Iter [154750/160000] lr: 1.969e-06, eta: 0:37:54, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0855, decode.acc_seg: 96.3716, loss: 0.0855 2023-01-06 17:55:48,494 - mmseg - INFO - Iter [154800/160000] lr: 1.950e-06, eta: 0:37:32, time: 0.474, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0826, decode.acc_seg: 96.5227, loss: 0.0826 2023-01-06 17:56:09,817 - mmseg - INFO - Iter [154850/160000] lr: 1.932e-06, eta: 0:37:10, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.6186, loss: 0.0784 2023-01-06 17:56:30,510 - mmseg - INFO - Iter [154900/160000] lr: 1.913e-06, eta: 0:36:49, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0785, decode.acc_seg: 96.6381, loss: 0.0785 2023-01-06 17:56:52,040 - mmseg - INFO - Iter [154950/160000] lr: 1.894e-06, eta: 0:36:27, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0827, decode.acc_seg: 96.4919, loss: 0.0827 2023-01-06 17:57:12,699 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 17:57:12,700 - mmseg - INFO - Iter [155000/160000] lr: 1.875e-06, eta: 0:36:05, time: 0.413, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.5128, loss: 0.0817 2023-01-06 17:57:33,861 - mmseg - INFO - Iter [155050/160000] lr: 1.857e-06, eta: 0:35:44, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0776, decode.acc_seg: 96.6512, loss: 0.0776 2023-01-06 17:57:55,409 - mmseg - INFO - Iter [155100/160000] lr: 1.838e-06, eta: 0:35:22, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0815, decode.acc_seg: 96.5672, loss: 0.0815 2023-01-06 17:58:18,565 - mmseg - INFO - Iter [155150/160000] lr: 1.819e-06, eta: 0:35:00, time: 0.464, data_time: 0.057, memory: 9591, decode.loss_ce: 0.0790, decode.acc_seg: 96.6106, loss: 0.0790 2023-01-06 17:58:39,263 - mmseg - INFO - Iter [155200/160000] lr: 1.800e-06, eta: 0:34:39, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0779, decode.acc_seg: 96.6734, loss: 0.0779 2023-01-06 17:59:00,139 - mmseg - INFO - Iter [155250/160000] lr: 1.782e-06, eta: 0:34:17, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0813, decode.acc_seg: 96.4871, loss: 0.0813 2023-01-06 17:59:21,732 - mmseg - INFO - Iter [155300/160000] lr: 1.763e-06, eta: 0:33:55, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.4773, loss: 0.0817 2023-01-06 17:59:43,053 - mmseg - INFO - Iter [155350/160000] lr: 1.744e-06, eta: 0:33:34, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0750, decode.acc_seg: 96.7288, loss: 0.0750 2023-01-06 18:00:04,079 - mmseg - INFO - Iter [155400/160000] lr: 1.725e-06, eta: 0:33:12, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0804, decode.acc_seg: 96.4384, loss: 0.0804 2023-01-06 18:00:25,928 - mmseg - INFO - Iter [155450/160000] lr: 1.707e-06, eta: 0:32:50, time: 0.437, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0791, decode.acc_seg: 96.6609, loss: 0.0791 2023-01-06 18:00:49,244 - mmseg - INFO - Iter [155500/160000] lr: 1.688e-06, eta: 0:32:29, time: 0.466, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0781, decode.acc_seg: 96.6786, loss: 0.0781 2023-01-06 18:01:10,578 - mmseg - INFO - Iter [155550/160000] lr: 1.669e-06, eta: 0:32:07, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0824, decode.acc_seg: 96.5291, loss: 0.0824 2023-01-06 18:01:31,766 - mmseg - INFO - Iter [155600/160000] lr: 1.650e-06, eta: 0:31:45, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.5805, loss: 0.0794 2023-01-06 18:01:53,402 - mmseg - INFO - Iter [155650/160000] lr: 1.632e-06, eta: 0:31:24, time: 0.432, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0753, decode.acc_seg: 96.7036, loss: 0.0753 2023-01-06 18:02:14,592 - mmseg - INFO - Iter [155700/160000] lr: 1.613e-06, eta: 0:31:02, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0775, decode.acc_seg: 96.6369, loss: 0.0775 2023-01-06 18:02:35,423 - mmseg - INFO - Iter [155750/160000] lr: 1.594e-06, eta: 0:30:40, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0816, decode.acc_seg: 96.4835, loss: 0.0816 2023-01-06 18:02:56,678 - mmseg - INFO - Iter [155800/160000] lr: 1.575e-06, eta: 0:30:19, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0785, decode.acc_seg: 96.5573, loss: 0.0785 2023-01-06 18:03:18,168 - mmseg - INFO - Iter [155850/160000] lr: 1.557e-06, eta: 0:29:57, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0803, decode.acc_seg: 96.5229, loss: 0.0803 2023-01-06 18:03:41,525 - mmseg - INFO - Iter [155900/160000] lr: 1.538e-06, eta: 0:29:35, time: 0.467, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0828, decode.acc_seg: 96.5491, loss: 0.0828 2023-01-06 18:04:03,245 - mmseg - INFO - Iter [155950/160000] lr: 1.519e-06, eta: 0:29:14, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0772, decode.acc_seg: 96.6205, loss: 0.0772 2023-01-06 18:04:24,717 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 18:04:24,717 - mmseg - INFO - Iter [156000/160000] lr: 1.500e-06, eta: 0:28:52, time: 0.430, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0785, decode.acc_seg: 96.6381, loss: 0.0785 2023-01-06 18:04:45,739 - mmseg - INFO - Iter [156050/160000] lr: 1.482e-06, eta: 0:28:30, time: 0.420, data_time: 0.012, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.4934, loss: 0.0822 2023-01-06 18:05:06,801 - mmseg - INFO - Iter [156100/160000] lr: 1.463e-06, eta: 0:28:09, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0804, decode.acc_seg: 96.5747, loss: 0.0804 2023-01-06 18:05:27,751 - mmseg - INFO - Iter [156150/160000] lr: 1.444e-06, eta: 0:27:47, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0788, decode.acc_seg: 96.6025, loss: 0.0788 2023-01-06 18:05:49,086 - mmseg - INFO - Iter [156200/160000] lr: 1.425e-06, eta: 0:27:25, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0797, decode.acc_seg: 96.4860, loss: 0.0797 2023-01-06 18:06:13,156 - mmseg - INFO - Iter [156250/160000] lr: 1.407e-06, eta: 0:27:04, time: 0.481, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0868, decode.acc_seg: 96.3669, loss: 0.0868 2023-01-06 18:06:34,199 - mmseg - INFO - Iter [156300/160000] lr: 1.388e-06, eta: 0:26:42, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0810, decode.acc_seg: 96.5045, loss: 0.0810 2023-01-06 18:06:55,345 - mmseg - INFO - Iter [156350/160000] lr: 1.369e-06, eta: 0:26:20, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0756, decode.acc_seg: 96.7395, loss: 0.0756 2023-01-06 18:07:16,734 - mmseg - INFO - Iter [156400/160000] lr: 1.350e-06, eta: 0:25:59, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0779, decode.acc_seg: 96.7206, loss: 0.0779 2023-01-06 18:07:37,501 - mmseg - INFO - Iter [156450/160000] lr: 1.332e-06, eta: 0:25:37, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0781, decode.acc_seg: 96.6564, loss: 0.0781 2023-01-06 18:07:58,100 - mmseg - INFO - Iter [156500/160000] lr: 1.313e-06, eta: 0:25:15, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0769, decode.acc_seg: 96.6374, loss: 0.0769 2023-01-06 18:08:19,018 - mmseg - INFO - Iter [156550/160000] lr: 1.294e-06, eta: 0:24:54, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0860, decode.acc_seg: 96.3145, loss: 0.0860 2023-01-06 18:08:40,119 - mmseg - INFO - Iter [156600/160000] lr: 1.275e-06, eta: 0:24:32, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.5720, loss: 0.0805 2023-01-06 18:09:03,889 - mmseg - INFO - Iter [156650/160000] lr: 1.257e-06, eta: 0:24:10, time: 0.475, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0789, decode.acc_seg: 96.5815, loss: 0.0789 2023-01-06 18:09:25,563 - mmseg - INFO - Iter [156700/160000] lr: 1.238e-06, eta: 0:23:49, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.5694, loss: 0.0794 2023-01-06 18:09:47,275 - mmseg - INFO - Iter [156750/160000] lr: 1.219e-06, eta: 0:23:27, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.5467, loss: 0.0820 2023-01-06 18:10:08,804 - mmseg - INFO - Iter [156800/160000] lr: 1.200e-06, eta: 0:23:06, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0795, decode.acc_seg: 96.6824, loss: 0.0795 2023-01-06 18:10:30,524 - mmseg - INFO - Iter [156850/160000] lr: 1.182e-06, eta: 0:22:44, time: 0.435, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0798, decode.acc_seg: 96.5639, loss: 0.0798 2023-01-06 18:10:51,250 - mmseg - INFO - Iter [156900/160000] lr: 1.163e-06, eta: 0:22:22, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0770, decode.acc_seg: 96.6925, loss: 0.0770 2023-01-06 18:11:12,652 - mmseg - INFO - Iter [156950/160000] lr: 1.144e-06, eta: 0:22:01, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0825, decode.acc_seg: 96.4460, loss: 0.0825 2023-01-06 18:11:36,407 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 18:11:36,408 - mmseg - INFO - Iter [157000/160000] lr: 1.125e-06, eta: 0:21:39, time: 0.475, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.5868, loss: 0.0794 2023-01-06 18:11:57,446 - mmseg - INFO - Iter [157050/160000] lr: 1.107e-06, eta: 0:21:17, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0783, decode.acc_seg: 96.6200, loss: 0.0783 2023-01-06 18:12:18,908 - mmseg - INFO - Iter [157100/160000] lr: 1.088e-06, eta: 0:20:56, time: 0.429, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.5987, loss: 0.0784 2023-01-06 18:12:39,807 - mmseg - INFO - Iter [157150/160000] lr: 1.069e-06, eta: 0:20:34, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0772, decode.acc_seg: 96.5862, loss: 0.0772 2023-01-06 18:13:01,499 - mmseg - INFO - Iter [157200/160000] lr: 1.050e-06, eta: 0:20:12, time: 0.434, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0793, decode.acc_seg: 96.5803, loss: 0.0793 2023-01-06 18:13:22,378 - mmseg - INFO - Iter [157250/160000] lr: 1.032e-06, eta: 0:19:51, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.6570, loss: 0.0784 2023-01-06 18:13:43,088 - mmseg - INFO - Iter [157300/160000] lr: 1.013e-06, eta: 0:19:29, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0810, decode.acc_seg: 96.5504, loss: 0.0810 2023-01-06 18:14:03,966 - mmseg - INFO - Iter [157350/160000] lr: 9.941e-07, eta: 0:19:07, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0829, decode.acc_seg: 96.5046, loss: 0.0829 2023-01-06 18:14:26,861 - mmseg - INFO - Iter [157400/160000] lr: 9.754e-07, eta: 0:18:46, time: 0.458, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0780, decode.acc_seg: 96.6438, loss: 0.0780 2023-01-06 18:14:47,946 - mmseg - INFO - Iter [157450/160000] lr: 9.566e-07, eta: 0:18:24, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0803, decode.acc_seg: 96.6364, loss: 0.0803 2023-01-06 18:15:09,293 - mmseg - INFO - Iter [157500/160000] lr: 9.379e-07, eta: 0:18:02, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.5853, loss: 0.0805 2023-01-06 18:15:30,912 - mmseg - INFO - Iter [157550/160000] lr: 9.191e-07, eta: 0:17:41, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0794, decode.acc_seg: 96.6300, loss: 0.0794 2023-01-06 18:15:51,846 - mmseg - INFO - Iter [157600/160000] lr: 9.004e-07, eta: 0:17:19, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0772, decode.acc_seg: 96.7307, loss: 0.0772 2023-01-06 18:16:13,284 - mmseg - INFO - Iter [157650/160000] lr: 8.816e-07, eta: 0:16:57, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0810, decode.acc_seg: 96.4417, loss: 0.0810 2023-01-06 18:16:34,256 - mmseg - INFO - Iter [157700/160000] lr: 8.629e-07, eta: 0:16:36, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0802, decode.acc_seg: 96.5619, loss: 0.0802 2023-01-06 18:16:57,344 - mmseg - INFO - Iter [157750/160000] lr: 8.441e-07, eta: 0:16:14, time: 0.462, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0747, decode.acc_seg: 96.7731, loss: 0.0747 2023-01-06 18:17:18,243 - mmseg - INFO - Iter [157800/160000] lr: 8.254e-07, eta: 0:15:52, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0778, decode.acc_seg: 96.5410, loss: 0.0778 2023-01-06 18:17:39,119 - mmseg - INFO - Iter [157850/160000] lr: 8.066e-07, eta: 0:15:31, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0775, decode.acc_seg: 96.6014, loss: 0.0775 2023-01-06 18:17:59,900 - mmseg - INFO - Iter [157900/160000] lr: 7.879e-07, eta: 0:15:09, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0796, decode.acc_seg: 96.5769, loss: 0.0796 2023-01-06 18:18:21,231 - mmseg - INFO - Iter [157950/160000] lr: 7.691e-07, eta: 0:14:47, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0802, decode.acc_seg: 96.5324, loss: 0.0802 2023-01-06 18:18:42,448 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 18:18:42,449 - mmseg - INFO - Iter [158000/160000] lr: 7.504e-07, eta: 0:14:26, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0791, decode.acc_seg: 96.5831, loss: 0.0791 2023-01-06 18:19:03,032 - mmseg - INFO - Iter [158050/160000] lr: 7.316e-07, eta: 0:14:04, time: 0.412, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0811, decode.acc_seg: 96.5851, loss: 0.0811 2023-01-06 18:19:23,753 - mmseg - INFO - Iter [158100/160000] lr: 7.129e-07, eta: 0:13:42, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0763, decode.acc_seg: 96.6762, loss: 0.0763 2023-01-06 18:19:47,624 - mmseg - INFO - Iter [158150/160000] lr: 6.941e-07, eta: 0:13:21, time: 0.477, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0800, decode.acc_seg: 96.6418, loss: 0.0800 2023-01-06 18:20:09,254 - mmseg - INFO - Iter [158200/160000] lr: 6.754e-07, eta: 0:12:59, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0865, decode.acc_seg: 96.3080, loss: 0.0865 2023-01-06 18:20:30,345 - mmseg - INFO - Iter [158250/160000] lr: 6.566e-07, eta: 0:12:37, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0739, decode.acc_seg: 96.7322, loss: 0.0739 2023-01-06 18:20:51,902 - mmseg - INFO - Iter [158300/160000] lr: 6.379e-07, eta: 0:12:16, time: 0.431, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0771, decode.acc_seg: 96.6672, loss: 0.0771 2023-01-06 18:21:13,946 - mmseg - INFO - Iter [158350/160000] lr: 6.191e-07, eta: 0:11:54, time: 0.441, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0773, decode.acc_seg: 96.5822, loss: 0.0773 2023-01-06 18:21:35,370 - mmseg - INFO - Iter [158400/160000] lr: 6.004e-07, eta: 0:11:32, time: 0.428, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0809, decode.acc_seg: 96.5057, loss: 0.0809 2023-01-06 18:21:56,483 - mmseg - INFO - Iter [158450/160000] lr: 5.816e-07, eta: 0:11:11, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0801, decode.acc_seg: 96.5453, loss: 0.0801 2023-01-06 18:22:19,842 - mmseg - INFO - Iter [158500/160000] lr: 5.629e-07, eta: 0:10:49, time: 0.467, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.6171, loss: 0.0784 2023-01-06 18:22:40,848 - mmseg - INFO - Iter [158550/160000] lr: 5.441e-07, eta: 0:10:27, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0762, decode.acc_seg: 96.6963, loss: 0.0762 2023-01-06 18:23:01,901 - mmseg - INFO - Iter [158600/160000] lr: 5.254e-07, eta: 0:10:06, time: 0.421, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0798, decode.acc_seg: 96.5366, loss: 0.0798 2023-01-06 18:23:23,227 - mmseg - INFO - Iter [158650/160000] lr: 5.066e-07, eta: 0:09:44, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0841, decode.acc_seg: 96.4242, loss: 0.0841 2023-01-06 18:23:44,060 - mmseg - INFO - Iter [158700/160000] lr: 4.879e-07, eta: 0:09:22, time: 0.417, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0844, decode.acc_seg: 96.4867, loss: 0.0844 2023-01-06 18:24:05,846 - mmseg - INFO - Iter [158750/160000] lr: 4.691e-07, eta: 0:09:01, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0788, decode.acc_seg: 96.5734, loss: 0.0788 2023-01-06 18:24:26,645 - mmseg - INFO - Iter [158800/160000] lr: 4.504e-07, eta: 0:08:39, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0813, decode.acc_seg: 96.4759, loss: 0.0813 2023-01-06 18:24:50,143 - mmseg - INFO - Iter [158850/160000] lr: 4.316e-07, eta: 0:08:18, time: 0.470, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0817, decode.acc_seg: 96.5505, loss: 0.0817 2023-01-06 18:25:11,441 - mmseg - INFO - Iter [158900/160000] lr: 4.129e-07, eta: 0:07:56, time: 0.426, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0854, decode.acc_seg: 96.3764, loss: 0.0854 2023-01-06 18:25:33,275 - mmseg - INFO - Iter [158950/160000] lr: 3.941e-07, eta: 0:07:34, time: 0.436, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0835, decode.acc_seg: 96.4479, loss: 0.0835 2023-01-06 18:25:54,496 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 18:25:54,497 - mmseg - INFO - Iter [159000/160000] lr: 3.754e-07, eta: 0:07:13, time: 0.425, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0805, decode.acc_seg: 96.5506, loss: 0.0805 2023-01-06 18:26:15,204 - mmseg - INFO - Iter [159050/160000] lr: 3.566e-07, eta: 0:06:51, time: 0.414, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0793, decode.acc_seg: 96.6269, loss: 0.0793 2023-01-06 18:26:36,827 - mmseg - INFO - Iter [159100/160000] lr: 3.379e-07, eta: 0:06:29, time: 0.433, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0781, decode.acc_seg: 96.6131, loss: 0.0781 2023-01-06 18:26:57,868 - mmseg - INFO - Iter [159150/160000] lr: 3.191e-07, eta: 0:06:08, time: 0.420, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0843, decode.acc_seg: 96.4718, loss: 0.0843 2023-01-06 18:27:18,635 - mmseg - INFO - Iter [159200/160000] lr: 3.004e-07, eta: 0:05:46, time: 0.416, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0780, decode.acc_seg: 96.6980, loss: 0.0780 2023-01-06 18:27:41,629 - mmseg - INFO - Iter [159250/160000] lr: 2.816e-07, eta: 0:05:24, time: 0.460, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0762, decode.acc_seg: 96.7362, loss: 0.0762 2023-01-06 18:28:02,766 - mmseg - INFO - Iter [159300/160000] lr: 2.629e-07, eta: 0:05:03, time: 0.423, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.5049, loss: 0.0820 2023-01-06 18:28:23,740 - mmseg - INFO - Iter [159350/160000] lr: 2.441e-07, eta: 0:04:41, time: 0.419, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0786, decode.acc_seg: 96.5823, loss: 0.0786 2023-01-06 18:28:44,930 - mmseg - INFO - Iter [159400/160000] lr: 2.254e-07, eta: 0:04:19, time: 0.424, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0747, decode.acc_seg: 96.7338, loss: 0.0747 2023-01-06 18:29:06,028 - mmseg - INFO - Iter [159450/160000] lr: 2.066e-07, eta: 0:03:58, time: 0.422, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0822, decode.acc_seg: 96.4657, loss: 0.0822 2023-01-06 18:29:26,932 - mmseg - INFO - Iter [159500/160000] lr: 1.879e-07, eta: 0:03:36, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0820, decode.acc_seg: 96.4377, loss: 0.0820 2023-01-06 18:29:47,835 - mmseg - INFO - Iter [159550/160000] lr: 1.691e-07, eta: 0:03:14, time: 0.418, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.6675, loss: 0.0784 2023-01-06 18:30:11,401 - mmseg - INFO - Iter [159600/160000] lr: 1.504e-07, eta: 0:02:53, time: 0.471, data_time: 0.055, memory: 9591, decode.loss_ce: 0.0816, decode.acc_seg: 96.4949, loss: 0.0816 2023-01-06 18:30:32,750 - mmseg - INFO - Iter [159650/160000] lr: 1.316e-07, eta: 0:02:31, time: 0.427, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0807, decode.acc_seg: 96.5337, loss: 0.0807 2023-01-06 18:30:55,100 - mmseg - INFO - Iter [159700/160000] lr: 1.129e-07, eta: 0:02:09, time: 0.447, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0797, decode.acc_seg: 96.5682, loss: 0.0797 2023-01-06 18:31:15,831 - mmseg - INFO - Iter [159750/160000] lr: 9.413e-08, eta: 0:01:48, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0753, decode.acc_seg: 96.6228, loss: 0.0753 2023-01-06 18:31:37,308 - mmseg - INFO - Iter [159800/160000] lr: 7.537e-08, eta: 0:01:26, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0784, decode.acc_seg: 96.6383, loss: 0.0784 2023-01-06 18:31:58,813 - mmseg - INFO - Iter [159850/160000] lr: 5.663e-08, eta: 0:01:04, time: 0.430, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0816, decode.acc_seg: 96.5266, loss: 0.0816 2023-01-06 18:32:19,610 - mmseg - INFO - Iter [159900/160000] lr: 3.787e-08, eta: 0:00:43, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0810, decode.acc_seg: 96.6038, loss: 0.0810 2023-01-06 18:32:40,337 - mmseg - INFO - Iter [159950/160000] lr: 1.913e-08, eta: 0:00:21, time: 0.415, data_time: 0.011, memory: 9591, decode.loss_ce: 0.0786, decode.acc_seg: 96.6357, loss: 0.0786 2023-01-06 18:33:03,680 - mmseg - INFO - Saving checkpoint at 160000 iterations 2023-01-06 18:33:07,343 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 18:33:07,344 - mmseg - INFO - Iter [160000/160000] lr: 3.750e-10, eta: 0:00:00, time: 0.540, data_time: 0.056, memory: 9591, decode.loss_ce: 0.0776, decode.acc_seg: 96.6772, loss: 0.0776 2023-01-06 18:33:35,511 - mmseg - INFO - per class results: 2023-01-06 18:33:35,513 - mmseg - INFO - +---------------+-------+-------+ | Class | IoU | Acc | +---------------+-------+-------+ | road | 98.04 | 98.95 | | sidewalk | 83.83 | 91.66 | | building | 92.03 | 96.47 | | wall | 56.35 | 64.59 | | fence | 56.07 | 68.95 | | pole | 62.22 | 71.91 | | traffic light | 66.66 | 78.51 | | traffic sign | 75.43 | 82.51 | | vegetation | 92.27 | 96.34 | | terrain | 63.08 | 74.41 | | sky | 94.68 | 98.21 | | person | 78.34 | 89.86 | | rider | 54.31 | 65.59 | | car | 93.96 | 97.55 | | truck | 68.05 | 74.44 | | bus | 74.11 | 82.45 | | train | 59.45 | 69.6 | | motorcycle | 45.38 | 51.86 | | bicycle | 72.87 | 86.79 | +---------------+-------+-------+ 2023-01-06 18:33:35,513 - mmseg - INFO - Summary: 2023-01-06 18:33:35,514 - mmseg - INFO - +-------+-------+-------+ | aAcc | mIoU | mAcc | +-------+-------+-------+ | 95.71 | 73.01 | 81.09 | +-------+-------+-------+ 2023-01-06 18:33:35,515 - mmseg - INFO - Exp name: dest_simpatt-b3_1024x1024_160k_cityscapes.py 2023-01-06 18:33:35,515 - mmseg - INFO - Iter(val) [63] aAcc: 0.9571, mIoU: 0.7301, mAcc: 0.8109, IoU.road: 0.9804, IoU.sidewalk: 0.8383, IoU.building: 0.9203, IoU.wall: 0.5635, IoU.fence: 0.5607, IoU.pole: 0.6222, IoU.traffic light: 0.6666, IoU.traffic sign: 0.7543, IoU.vegetation: 0.9227, IoU.terrain: 0.6308, IoU.sky: 0.9468, IoU.person: 0.7834, IoU.rider: 0.5431, IoU.car: 0.9396, IoU.truck: 0.6805, IoU.bus: 0.7411, IoU.train: 0.5945, IoU.motorcycle: 0.4538, IoU.bicycle: 0.7287, Acc.road: 0.9895, Acc.sidewalk: 0.9166, Acc.building: 0.9647, Acc.wall: 0.6459, Acc.fence: 0.6895, Acc.pole: 0.7191, Acc.traffic light: 0.7851, Acc.traffic sign: 0.8251, Acc.vegetation: 0.9634, Acc.terrain: 0.7441, Acc.sky: 0.9821, Acc.person: 0.8986, Acc.rider: 0.6559, Acc.car: 0.9755, Acc.truck: 0.7444, Acc.bus: 0.8245, Acc.train: 0.6960, Acc.motorcycle: 0.5186, Acc.bicycle: 0.8679