2023/04/25 12:59:22 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.8.16 (default, Mar 2 2023, 03:21:46) [GCC 11.2.0] CUDA available: True numpy_random_seed: 0 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /nvme/share/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (GCC) 7.5.0 PyTorch: 1.12.1+cu113 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) - 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_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 - CuDNN 8.2.1 - Built with CuDNN 8.3.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -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-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 -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.1, 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: 0.13.1+cu113 OpenCV: 4.7.0 MMEngine: 0.7.2 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 0 deterministic: False diff_rank_seed: True Distributed launcher: pytorch Distributed training: True GPU number: 8 ------------------------------------------------------------ 2023/04/25 12:59:25 - mmengine - INFO - Config: dataset_type = 'SemanticKittiDataset' data_root = 'data/semantickitti/' class_names = [ 'car', 'bicycle', 'motorcycle', 'truck', 'bus', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunck', 'terrian', 'pole', 'traffic-sign' ] labels_map = dict({ 0: 19, 1: 19, 10: 0, 11: 1, 13: 4, 15: 2, 16: 4, 18: 3, 20: 4, 30: 5, 31: 6, 32: 7, 40: 8, 44: 9, 48: 10, 49: 11, 50: 12, 51: 13, 52: 19, 60: 8, 70: 14, 71: 15, 72: 16, 80: 17, 81: 18, 99: 19, 252: 0, 253: 6, 254: 5, 255: 7, 256: 4, 257: 4, 258: 3, 259: 4 }) metainfo = dict( classes=[ 'car', 'bicycle', 'motorcycle', 'truck', 'bus', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunck', 'terrian', 'pole', 'traffic-sign' ], seg_label_mapping=dict({ 0: 19, 1: 19, 10: 0, 11: 1, 13: 4, 15: 2, 16: 4, 18: 3, 20: 4, 30: 5, 31: 6, 32: 7, 40: 8, 44: 9, 48: 10, 49: 11, 50: 12, 51: 13, 52: 19, 60: 8, 70: 14, 71: 15, 72: 16, 80: 17, 81: 18, 99: 19, 252: 0, 253: 6, 254: 5, 255: 7, 256: 4, 257: 4, 258: 3, 259: 4 }), max_label=259) input_modality = dict(use_lidar=True, use_camera=False) backend_args = None train_pipeline = [ dict(type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4), dict( type='LoadAnnotations3D', with_bbox_3d=False, with_label_3d=False, with_seg_3d=True, seg_3d_dtype='np.int32', seg_offset=65536, dataset_type='semantickitti'), dict(type='PointSegClassMapping'), dict( type='RandomChoice', transforms=[[{ 'type': 'LaserMix', 'num_areas': [3, 4, 5, 6], 'pitch_angles': [-25, 3], 'pre_transform': [{ 'type': 'LoadPointsFromFile', 'coord_type': 'LIDAR', 'load_dim': 4, 'use_dim': 4 }, { 'type': 'LoadAnnotations3D', 'with_bbox_3d': False, 'with_label_3d': False, 'with_seg_3d': True, 'seg_3d_dtype': 'np.int32', 'seg_offset': 65536, 'dataset_type': 'semantickitti' }, { 'type': 'PointSegClassMapping' }], 'prob': 1 }], [{ 'type': 'PolarMix', 'instance_classes': [0, 1, 2, 3, 4, 5, 6, 7], 'swap_ratio': 0.5, 'rotate_paste_ratio': 1.0, 'pre_transform': [{ 'type': 'LoadPointsFromFile', 'coord_type': 'LIDAR', 'load_dim': 4, 'use_dim': 4 }, { 'type': 'LoadAnnotations3D', 'with_bbox_3d': False, 'with_label_3d': False, 'with_seg_3d': True, 'seg_3d_dtype': 'np.int32', 'seg_offset': 65536, 'dataset_type': 'semantickitti' }, { 'type': 'PointSegClassMapping' }], 'prob': 1 }]], prob=[0.5, 0.5]), dict( type='GlobalRotScaleTrans', rot_range=[0.0, 6.28318531], scale_ratio_range=[0.95, 1.05], translation_std=[0, 0, 0]), dict(type='Pack3DDetInputs', keys=['points', 'pts_semantic_mask']) ] test_pipeline = [ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4, backend_args=None), dict( type='LoadAnnotations3D', with_bbox_3d=False, with_label_3d=False, with_seg_3d=True, seg_3d_dtype='np.int32', seg_offset=65536, dataset_type='semantickitti', backend_args=None), dict(type='PointSegClassMapping'), dict(type='Pack3DDetInputs', keys=['points', 'pts_semantic_mask']) ] eval_pipeline = [ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4, backend_args=None), dict( type='LoadAnnotations3D', with_bbox_3d=False, with_label_3d=False, with_seg_3d=True, seg_3d_dtype='np.int32', seg_offset=65536, dataset_type='semantickitti', backend_args=None), dict(type='PointSegClassMapping'), dict(type='Pack3DDetInputs', keys=['points', 'pts_semantic_mask']) ] train_dataloader = dict( batch_size=2, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True, seed=0), dataset=dict( type='SemanticKittiDataset', data_root='data/semantickitti/', ann_file='semantickitti_infos_train.pkl', pipeline=[ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4), dict( type='LoadAnnotations3D', with_bbox_3d=False, with_label_3d=False, with_seg_3d=True, seg_3d_dtype='np.int32', seg_offset=65536, dataset_type='semantickitti'), dict(type='PointSegClassMapping'), dict( type='RandomChoice', transforms=[[{ 'type': 'LaserMix', 'num_areas': [3, 4, 5, 6], 'pitch_angles': [-25, 3], 'pre_transform': [{ 'type': 'LoadPointsFromFile', 'coord_type': 'LIDAR', 'load_dim': 4, 'use_dim': 4 }, { 'type': 'LoadAnnotations3D', 'with_bbox_3d': False, 'with_label_3d': False, 'with_seg_3d': True, 'seg_3d_dtype': 'np.int32', 'seg_offset': 65536, 'dataset_type': 'semantickitti' }, { 'type': 'PointSegClassMapping' }], 'prob': 1 }], [{ 'type': 'PolarMix', 'instance_classes': [0, 1, 2, 3, 4, 5, 6, 7], 'swap_ratio': 0.5, 'rotate_paste_ratio': 1.0, 'pre_transform': [{ 'type': 'LoadPointsFromFile', 'coord_type': 'LIDAR', 'load_dim': 4, 'use_dim': 4 }, { 'type': 'LoadAnnotations3D', 'with_bbox_3d': False, 'with_label_3d': False, 'with_seg_3d': True, 'seg_3d_dtype': 'np.int32', 'seg_offset': 65536, 'dataset_type': 'semantickitti' }, { 'type': 'PointSegClassMapping' }], 'prob': 1 }]], prob=[0.5, 0.5]), dict( type='GlobalRotScaleTrans', rot_range=[0.0, 6.28318531], scale_ratio_range=[0.95, 1.05], translation_std=[0, 0, 0]), dict(type='Pack3DDetInputs', keys=['points', 'pts_semantic_mask']) ], metainfo=dict( classes=[ 'car', 'bicycle', 'motorcycle', 'truck', 'bus', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunck', 'terrian', 'pole', 'traffic-sign' ], seg_label_mapping=dict({ 0: 19, 1: 19, 10: 0, 11: 1, 13: 4, 15: 2, 16: 4, 18: 3, 20: 4, 30: 5, 31: 6, 32: 7, 40: 8, 44: 9, 48: 10, 49: 11, 50: 12, 51: 13, 52: 19, 60: 8, 70: 14, 71: 15, 72: 16, 80: 17, 81: 18, 99: 19, 252: 0, 253: 6, 254: 5, 255: 7, 256: 4, 257: 4, 258: 3, 259: 4 }), max_label=259), modality=dict(use_lidar=True, use_camera=False), ignore_index=19, backend_args=None)) test_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='SemanticKittiDataset', data_root='data/semantickitti/', ann_file='semantickitti_infos_val.pkl', pipeline=[ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4, backend_args=None), dict( type='LoadAnnotations3D', with_bbox_3d=False, with_label_3d=False, with_seg_3d=True, seg_3d_dtype='np.int32', seg_offset=65536, dataset_type='semantickitti', backend_args=None), dict(type='PointSegClassMapping'), dict(type='Pack3DDetInputs', keys=['points', 'pts_semantic_mask']) ], metainfo=dict( classes=[ 'car', 'bicycle', 'motorcycle', 'truck', 'bus', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunck', 'terrian', 'pole', 'traffic-sign' ], seg_label_mapping=dict({ 0: 19, 1: 19, 10: 0, 11: 1, 13: 4, 15: 2, 16: 4, 18: 3, 20: 4, 30: 5, 31: 6, 32: 7, 40: 8, 44: 9, 48: 10, 49: 11, 50: 12, 51: 13, 52: 19, 60: 8, 70: 14, 71: 15, 72: 16, 80: 17, 81: 18, 99: 19, 252: 0, 253: 6, 254: 5, 255: 7, 256: 4, 257: 4, 258: 3, 259: 4 }), max_label=259), modality=dict(use_lidar=True, use_camera=False), ignore_index=19, test_mode=True, backend_args=None)) val_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='SemanticKittiDataset', data_root='data/semantickitti/', ann_file='semantickitti_infos_val.pkl', pipeline=[ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4, backend_args=None), dict( type='LoadAnnotations3D', with_bbox_3d=False, with_label_3d=False, with_seg_3d=True, seg_3d_dtype='np.int32', seg_offset=65536, dataset_type='semantickitti', backend_args=None), dict(type='PointSegClassMapping'), dict(type='Pack3DDetInputs', keys=['points', 'pts_semantic_mask']) ], metainfo=dict( classes=[ 'car', 'bicycle', 'motorcycle', 'truck', 'bus', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunck', 'terrian', 'pole', 'traffic-sign' ], seg_label_mapping=dict({ 0: 19, 1: 19, 10: 0, 11: 1, 13: 4, 15: 2, 16: 4, 18: 3, 20: 4, 30: 5, 31: 6, 32: 7, 40: 8, 44: 9, 48: 10, 49: 11, 50: 12, 51: 13, 52: 19, 60: 8, 70: 14, 71: 15, 72: 16, 80: 17, 81: 18, 99: 19, 252: 0, 253: 6, 254: 5, 255: 7, 256: 4, 257: 4, 258: 3, 259: 4 }), max_label=259), modality=dict(use_lidar=True, use_camera=False), ignore_index=19, test_mode=True, backend_args=None)) val_evaluator = dict(type='SegMetric') test_evaluator = dict(type='SegMetric') vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='Det3DLocalVisualizer', vis_backends=[dict(type='LocalVisBackend')], name='visualizer') model = dict( type='MinkUNet', data_preprocessor=dict( type='Det3DDataPreprocessor', voxel=True, voxel_type='minkunet', voxel_layer=dict( max_num_points=-1, point_cloud_range=[-100, -100, -20, 100, 100, 20], voxel_size=[0.05, 0.05, 0.05], max_voxels=(-1, -1))), backbone=dict( type='SPVCNNBackbone', in_channels=4, base_channels=32, encoder_channels=[32, 64, 128, 256], decoder_channels=[256, 128, 96, 96], num_stages=4, drop_ratio=0.3), decode_head=dict( type='MinkUNetHead', channels=96, num_classes=19, dropout_ratio=0, loss_decode=dict(type='mmdet.CrossEntropyLoss', avg_non_ignore=True), ignore_index=19), train_cfg=dict(), test_cfg=dict()) default_scope = 'mmdet3d' default_hooks = dict( timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=50), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict(type='CheckpointHook', interval=1), sampler_seed=dict(type='DistSamplerSeedHook'), visualization=dict(type='Det3DVisualizationHook')) env_cfg = dict( cudnn_benchmark=True, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict(type='LogProcessor', window_size=50, by_epoch=True) log_level = 'INFO' load_from = None resume = False lr = 0.008 optim_wrapper = dict( type='AmpOptimWrapper', loss_scale='dynamic', optimizer=dict(type='AdamW', lr=0.008, weight_decay=0.01), clip_grad=dict(max_norm=10, norm_type=2)) param_scheduler = [ dict( type='MultiStepLR', begin=0, end=36, by_epoch=True, milestones=[24, 32], gamma=0.1) ] train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=36, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') randomness = dict(seed=0, deterministic=False, diff_rank_seed=True) auto_scale_lr = dict(enable=False, base_batch_size=16) launcher = 'pytorch' work_dir = './work_dirs/spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti' 2023/04/25 12:59:30 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook -------------------- before_train: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (VERY_LOW ) CheckpointHook -------------------- before_train_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (NORMAL ) DistSamplerSeedHook -------------------- before_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook -------------------- after_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train_epoch: (NORMAL ) IterTimerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) Det3DVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train: (VERY_LOW ) CheckpointHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) Det3DVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- 2023/04/25 12:59:33 - mmengine - WARNING - The prefix is not set in metric class SegMetric. Name of parameter - Initialization information backbone.conv_input.0.net.0.kernel - torch.Size([27, 4, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.0.net.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.0.net.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.net.0.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.net.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.net.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.net.0.kernel - torch.Size([8, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.net.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.net.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.net.0.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.net.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.net.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.net.3.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.net.4.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.net.4.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.net.0.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.net.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.net.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.net.3.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.net.4.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.net.4.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.net.0.kernel - torch.Size([8, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.net.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.net.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.net.0.kernel - torch.Size([27, 32, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.net.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.net.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.net.3.kernel - torch.Size([27, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.net.4.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.net.4.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.downsample.0.kernel - torch.Size([32, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.downsample.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.downsample.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.net.0.kernel - torch.Size([27, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.net.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.net.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.net.3.kernel - torch.Size([27, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.net.4.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.net.4.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.net.0.kernel - torch.Size([8, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.net.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.net.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.net.0.kernel - torch.Size([27, 64, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.net.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.net.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.net.3.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.net.4.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.net.4.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.downsample.0.kernel - torch.Size([64, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.downsample.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.downsample.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.net.0.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.net.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.net.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.net.3.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.net.4.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.net.4.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.net.0.kernel - torch.Size([8, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.net.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.net.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.net.0.kernel - torch.Size([27, 128, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.net.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.net.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.net.3.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.net.4.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.net.4.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.downsample.0.kernel - torch.Size([128, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.downsample.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.downsample.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.net.0.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.net.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.net.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.net.3.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.net.4.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.net.4.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.net.0.kernel - torch.Size([8, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.net.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.net.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.net.0.kernel - torch.Size([27, 384, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.net.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.net.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.net.3.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.net.4.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.net.4.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.downsample.0.kernel - torch.Size([384, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.downsample.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.downsample.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.net.0.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.net.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.net.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.net.3.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.net.4.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.net.4.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.net.0.kernel - torch.Size([8, 256, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.net.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.net.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.net.0.kernel - torch.Size([27, 192, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.net.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.net.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.net.3.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.net.4.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.net.4.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.downsample.0.kernel - torch.Size([192, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.downsample.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.downsample.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.net.0.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.net.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.net.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.net.3.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.net.4.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.net.4.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.net.0.kernel - torch.Size([8, 128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.net.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.net.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.net.0.kernel - torch.Size([27, 128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.net.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.net.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.net.3.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.net.4.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.net.4.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.downsample.0.kernel - torch.Size([128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.downsample.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.downsample.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.net.0.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.net.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.net.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.net.3.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.net.4.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.net.4.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.net.0.kernel - torch.Size([8, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.net.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.net.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.net.0.kernel - torch.Size([27, 128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.net.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.net.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.net.3.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.net.4.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.net.4.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.downsample.0.kernel - torch.Size([128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.downsample.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.downsample.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.net.0.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.net.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.net.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.net.3.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.net.4.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.net.4.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.0.0.weight - torch.Size([256, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.0.0.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.0.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.0.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.1.0.weight - torch.Size([128, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.1.0.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.1.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.1.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.2.0.weight - torch.Size([96, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.2.0.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.2.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.point_transforms.2.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet decode_head.conv_seg.weight - torch.Size([19, 96]): Initialized by user-defined `init_weights` in MinkUNetHead decode_head.conv_seg.bias - torch.Size([19]): Initialized by user-defined `init_weights` in MinkUNetHead 2023/04/25 12:59:36 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/04/25 12:59:36 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/04/25 12:59:36 - mmengine - INFO - Checkpoints will be saved to /nvme/sunjiahao/projects/mmdetection3d/work_dirs/spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti. 2023/04/25 13:00:18 - mmengine - INFO - Epoch(train) [1][ 50/1196] lr: 8.0000e-03 eta: 9:57:36 time: 0.8338 data_time: 0.0100 memory: 3170 grad_norm: 0.8612 loss: 1.4168 loss_sem_seg: 1.4168 2023/04/25 13:00:58 - mmengine - INFO - Epoch(train) [1][ 100/1196] lr: 8.0000e-03 eta: 9:45:56 time: 0.8031 data_time: 0.0037 memory: 3516 grad_norm: 0.5658 loss: 0.9383 loss_sem_seg: 0.9383 2023/04/25 13:01:39 - mmengine - INFO - Epoch(train) [1][ 150/1196] lr: 8.0000e-03 eta: 9:45:07 time: 0.8178 data_time: 0.0039 memory: 3380 grad_norm: 0.5863 loss: 0.7507 loss_sem_seg: 0.7507 2023/04/25 13:02:18 - mmengine - INFO - Epoch(train) [1][ 200/1196] lr: 8.0000e-03 eta: 9:39:36 time: 0.7912 data_time: 0.0037 memory: 3222 grad_norm: 0.6076 loss: 0.7174 loss_sem_seg: 0.7174 2023/04/25 13:02:56 - mmengine - INFO - Epoch(train) [1][ 250/1196] lr: 8.0000e-03 eta: 9:29:49 time: 0.7476 data_time: 0.0039 memory: 3181 grad_norm: inf loss: 0.6883 loss_sem_seg: 0.6883 2023/04/25 13:03:35 - mmengine - INFO - Epoch(train) [1][ 300/1196] lr: 8.0000e-03 eta: 9:28:44 time: 0.7952 data_time: 0.0039 memory: 3223 grad_norm: 0.7065 loss: 0.6269 loss_sem_seg: 0.6269 2023/04/25 13:04:13 - mmengine - INFO - Epoch(train) [1][ 350/1196] lr: 8.0000e-03 eta: 9:23:32 time: 0.7535 data_time: 0.0039 memory: 3230 grad_norm: 0.6071 loss: 0.6023 loss_sem_seg: 0.6023 2023/04/25 13:04:50 - mmengine - INFO - Epoch(train) [1][ 400/1196] lr: 8.0000e-03 eta: 9:18:50 time: 0.7463 data_time: 0.0036 memory: 3151 grad_norm: 0.6103 loss: 0.6049 loss_sem_seg: 0.6049 2023/04/25 13:05:31 - mmengine - INFO - Epoch(train) [1][ 450/1196] lr: 8.0000e-03 eta: 9:19:37 time: 0.8043 data_time: 0.0036 memory: 3259 grad_norm: 0.5253 loss: 0.5396 loss_sem_seg: 0.5396 2023/04/25 13:06:08 - mmengine - INFO - Epoch(train) [1][ 500/1196] lr: 8.0000e-03 eta: 9:16:38 time: 0.7553 data_time: 0.0036 memory: 3138 grad_norm: 0.6270 loss: 0.5308 loss_sem_seg: 0.5308 2023/04/25 13:06:49 - mmengine - INFO - Epoch(train) [1][ 550/1196] lr: 8.0000e-03 eta: 9:18:12 time: 0.8192 data_time: 0.0036 memory: 3334 grad_norm: 0.5935 loss: 0.5481 loss_sem_seg: 0.5481 2023/04/25 13:07:30 - mmengine - INFO - Epoch(train) [1][ 600/1196] lr: 8.0000e-03 eta: 9:19:01 time: 0.8130 data_time: 0.0038 memory: 3116 grad_norm: 0.5036 loss: 0.5265 loss_sem_seg: 0.5265 2023/04/25 13:08:09 - mmengine - INFO - Epoch(train) [1][ 650/1196] lr: 8.0000e-03 eta: 9:17:32 time: 0.7748 data_time: 0.0035 memory: 3184 grad_norm: 0.5231 loss: 0.5548 loss_sem_seg: 0.5548 2023/04/25 13:08:47 - mmengine - INFO - Epoch(train) [1][ 700/1196] lr: 8.0000e-03 eta: 9:15:33 time: 0.7627 data_time: 0.0036 memory: 3365 grad_norm: 0.5508 loss: 0.4963 loss_sem_seg: 0.4963 2023/04/25 13:09:26 - mmengine - INFO - Epoch(train) [1][ 750/1196] lr: 8.0000e-03 eta: 9:14:28 time: 0.7780 data_time: 0.0040 memory: 3441 grad_norm: 0.5018 loss: 0.4908 loss_sem_seg: 0.4908 2023/04/25 13:10:05 - mmengine - INFO - Epoch(train) [1][ 800/1196] lr: 8.0000e-03 eta: 9:13:35 time: 0.7811 data_time: 0.0037 memory: 3150 grad_norm: 0.5085 loss: 0.4963 loss_sem_seg: 0.4963 2023/04/25 13:10:45 - mmengine - INFO - Epoch(train) [1][ 850/1196] lr: 8.0000e-03 eta: 9:13:49 time: 0.8074 data_time: 0.0040 memory: 3292 grad_norm: 0.4586 loss: 0.4591 loss_sem_seg: 0.4591 2023/04/25 13:11:26 - mmengine - INFO - Epoch(train) [1][ 900/1196] lr: 8.0000e-03 eta: 9:14:18 time: 0.8165 data_time: 0.0036 memory: 3281 grad_norm: 0.5150 loss: 0.4525 loss_sem_seg: 0.4525 2023/04/25 13:12:04 - mmengine - INFO - Epoch(train) [1][ 950/1196] lr: 8.0000e-03 eta: 9:12:50 time: 0.7672 data_time: 0.0034 memory: 3211 grad_norm: 0.4829 loss: 0.4573 loss_sem_seg: 0.4573 2023/04/25 13:12:42 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 13:12:42 - mmengine - INFO - Epoch(train) [1][1000/1196] lr: 8.0000e-03 eta: 9:10:54 time: 0.7511 data_time: 0.0036 memory: 3476 grad_norm: 0.4454 loss: 0.4513 loss_sem_seg: 0.4513 2023/04/25 13:13:19 - mmengine - INFO - Epoch(train) [1][1050/1196] lr: 8.0000e-03 eta: 9:09:00 time: 0.7486 data_time: 0.0035 memory: 3365 grad_norm: 0.3916 loss: 0.4593 loss_sem_seg: 0.4593 2023/04/25 13:13:57 - mmengine - INFO - Epoch(train) [1][1100/1196] lr: 8.0000e-03 eta: 9:07:37 time: 0.7615 data_time: 0.0036 memory: 3411 grad_norm: 0.3992 loss: 0.4233 loss_sem_seg: 0.4233 2023/04/25 13:14:37 - mmengine - INFO - Epoch(train) [1][1150/1196] lr: 8.0000e-03 eta: 9:07:02 time: 0.7851 data_time: 0.0037 memory: 3272 grad_norm: 0.3988 loss: 0.4118 loss_sem_seg: 0.4118 2023/04/25 13:15:11 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 13:15:11 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/04/25 13:15:27 - mmengine - INFO - Epoch(val) [1][ 50/509] eta: 0:01:47 time: 0.2342 data_time: 0.0095 memory: 3302 2023/04/25 13:15:37 - mmengine - INFO - Epoch(val) [1][100/509] eta: 0:01:28 time: 0.2001 data_time: 0.0055 memory: 840 2023/04/25 13:15:50 - mmengine - INFO - Epoch(val) [1][150/509] eta: 0:01:22 time: 0.2533 data_time: 0.0053 memory: 843 2023/04/25 13:16:01 - mmengine - INFO - Epoch(val) [1][200/509] eta: 0:01:10 time: 0.2190 data_time: 0.0053 memory: 834 2023/04/25 13:16:11 - mmengine - INFO - Epoch(val) [1][250/509] eta: 0:00:57 time: 0.2014 data_time: 0.0050 memory: 850 2023/04/25 13:16:21 - mmengine - INFO - Epoch(val) [1][300/509] eta: 0:00:45 time: 0.1974 data_time: 0.0053 memory: 812 2023/04/25 13:16:30 - mmengine - INFO - Epoch(val) [1][350/509] eta: 0:00:33 time: 0.1843 data_time: 0.0055 memory: 825 2023/04/25 13:16:39 - mmengine - INFO - Epoch(val) [1][400/509] eta: 0:00:22 time: 0.1779 data_time: 0.0052 memory: 827 2023/04/25 13:16:49 - mmengine - INFO - Epoch(val) [1][450/509] eta: 0:00:12 time: 0.2142 data_time: 0.0056 memory: 845 2023/04/25 13:17:06 - mmengine - INFO - Epoch(val) [1][500/509] eta: 0:00:01 time: 0.3311 data_time: 0.0049 memory: 832 2023/04/25 13:17:33 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9248 | 0.0103 | 0.2638 | 0.3099 | 0.0349 | 0.4228 | 0.4163 | 0.0000 | 0.8582 | 0.1645 | 0.6987 | 0.0000 | 0.8633 | 0.4996 | 0.8718 | 0.6240 | 0.7046 | 0.5967 | 0.3635 | 0.4541 | 0.8843 | 0.5464 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 13:17:33 - mmengine - INFO - Epoch(val) [1][509/509] car: 0.9248 bicycle: 0.0103 motorcycle: 0.2638 truck: 0.3099 bus: 0.0349 person: 0.4228 bicyclist: 0.4163 motorcyclist: 0.0000 road: 0.8582 parking: 0.1645 sidewalk: 0.6987 other-ground: 0.0000 building: 0.8633 fence: 0.4996 vegetation: 0.8718 trunck: 0.6240 terrian: 0.7046 pole: 0.5967 traffic-sign: 0.3635 miou: 0.4541 acc: 0.8843 acc_cls: 0.5464 data_time: 0.0045 time: 0.3011 2023/04/25 13:18:12 - mmengine - INFO - Epoch(train) [2][ 50/1196] lr: 8.0000e-03 eta: 9:04:57 time: 0.7792 data_time: 0.0044 memory: 3236 grad_norm: 0.3874 loss: 0.4077 loss_sem_seg: 0.4077 2023/04/25 13:18:52 - mmengine - INFO - Epoch(train) [2][ 100/1196] lr: 8.0000e-03 eta: 9:04:41 time: 0.7963 data_time: 0.0034 memory: 3244 grad_norm: 0.4126 loss: 0.3998 loss_sem_seg: 0.3998 2023/04/25 13:19:29 - mmengine - INFO - Epoch(train) [2][ 150/1196] lr: 8.0000e-03 eta: 9:03:14 time: 0.7515 data_time: 0.0036 memory: 3194 grad_norm: 0.3257 loss: 0.3957 loss_sem_seg: 0.3957 2023/04/25 13:20:08 - mmengine - INFO - Epoch(train) [2][ 200/1196] lr: 8.0000e-03 eta: 9:02:35 time: 0.7819 data_time: 0.0035 memory: 3366 grad_norm: 0.3908 loss: 0.4349 loss_sem_seg: 0.4349 2023/04/25 13:20:47 - mmengine - INFO - Epoch(train) [2][ 250/1196] lr: 8.0000e-03 eta: 9:01:55 time: 0.7807 data_time: 0.0036 memory: 3152 grad_norm: 0.3637 loss: 0.3951 loss_sem_seg: 0.3951 2023/04/25 13:21:25 - mmengine - INFO - Epoch(train) [2][ 300/1196] lr: 8.0000e-03 eta: 9:00:47 time: 0.7608 data_time: 0.0041 memory: 2983 grad_norm: 0.3615 loss: 0.3784 loss_sem_seg: 0.3784 2023/04/25 13:22:07 - mmengine - INFO - Epoch(train) [2][ 350/1196] lr: 8.0000e-03 eta: 9:01:14 time: 0.8300 data_time: 0.0037 memory: 3113 grad_norm: 0.3668 loss: 0.4037 loss_sem_seg: 0.4037 2023/04/25 13:22:48 - mmengine - INFO - Epoch(train) [2][ 400/1196] lr: 8.0000e-03 eta: 9:01:26 time: 0.8211 data_time: 0.0187 memory: 3135 grad_norm: 0.3523 loss: 0.3988 loss_sem_seg: 0.3988 2023/04/25 13:23:26 - mmengine - INFO - Epoch(train) [2][ 450/1196] lr: 8.0000e-03 eta: 9:00:18 time: 0.7605 data_time: 0.0036 memory: 3201 grad_norm: 0.3492 loss: 0.3997 loss_sem_seg: 0.3997 2023/04/25 13:24:07 - mmengine - INFO - Epoch(train) [2][ 500/1196] lr: 8.0000e-03 eta: 9:00:19 time: 0.8165 data_time: 0.0034 memory: 3362 grad_norm: 0.3556 loss: 0.4004 loss_sem_seg: 0.4004 2023/04/25 13:24:44 - mmengine - INFO - Epoch(train) [2][ 550/1196] lr: 8.0000e-03 eta: 8:59:06 time: 0.7547 data_time: 0.0039 memory: 3241 grad_norm: 0.3290 loss: 0.4046 loss_sem_seg: 0.4046 2023/04/25 13:25:25 - mmengine - INFO - Epoch(train) [2][ 600/1196] lr: 8.0000e-03 eta: 8:58:55 time: 0.8079 data_time: 0.0037 memory: 3203 grad_norm: 0.3180 loss: 0.3939 loss_sem_seg: 0.3939 2023/04/25 13:26:04 - mmengine - INFO - Epoch(train) [2][ 650/1196] lr: 8.0000e-03 eta: 8:58:18 time: 0.7857 data_time: 0.0036 memory: 3211 grad_norm: 0.3185 loss: 0.3702 loss_sem_seg: 0.3702 2023/04/25 13:26:46 - mmengine - INFO - Epoch(train) [2][ 700/1196] lr: 8.0000e-03 eta: 8:58:44 time: 0.8441 data_time: 0.0036 memory: 3173 grad_norm: 0.2835 loss: 0.3796 loss_sem_seg: 0.3796 2023/04/25 13:27:26 - mmengine - INFO - Epoch(train) [2][ 750/1196] lr: 8.0000e-03 eta: 8:58:09 time: 0.7886 data_time: 0.0041 memory: 3214 grad_norm: 0.3400 loss: 0.3548 loss_sem_seg: 0.3548 2023/04/25 13:28:07 - mmengine - INFO - Epoch(train) [2][ 800/1196] lr: 8.0000e-03 eta: 8:58:18 time: 0.8330 data_time: 0.0037 memory: 3040 grad_norm: 0.2848 loss: 0.3486 loss_sem_seg: 0.3486 2023/04/25 13:28:10 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 13:28:45 - mmengine - INFO - Epoch(train) [2][ 850/1196] lr: 8.0000e-03 eta: 8:57:07 time: 0.7546 data_time: 0.0035 memory: 3166 grad_norm: 0.3053 loss: 0.3411 loss_sem_seg: 0.3411 2023/04/25 13:29:26 - mmengine - INFO - Epoch(train) [2][ 900/1196] lr: 8.0000e-03 eta: 8:57:06 time: 0.8256 data_time: 0.0038 memory: 3498 grad_norm: 0.2642 loss: 0.3568 loss_sem_seg: 0.3568 2023/04/25 13:30:04 - mmengine - INFO - Epoch(train) [2][ 950/1196] lr: 8.0000e-03 eta: 8:55:54 time: 0.7518 data_time: 0.0038 memory: 3105 grad_norm: 0.3003 loss: 0.3616 loss_sem_seg: 0.3616 2023/04/25 13:30:44 - mmengine - INFO - Epoch(train) [2][1000/1196] lr: 8.0000e-03 eta: 8:55:31 time: 0.8037 data_time: 0.0034 memory: 3330 grad_norm: 0.2580 loss: 0.3665 loss_sem_seg: 0.3665 2023/04/25 13:31:08 - mmengine - INFO - Epoch(train) [2][1050/1196] lr: 8.0000e-03 eta: 8:50:07 time: 0.4737 data_time: 0.0036 memory: 3174 grad_norm: 0.2654 loss: 0.3435 loss_sem_seg: 0.3435 2023/04/25 13:31:26 - mmengine - INFO - Epoch(train) [2][1100/1196] lr: 8.0000e-03 eta: 8:43:21 time: 0.3649 data_time: 0.0034 memory: 3113 grad_norm: 0.2569 loss: 0.3646 loss_sem_seg: 0.3646 2023/04/25 13:31:44 - mmengine - INFO - Epoch(train) [2][1150/1196] lr: 8.0000e-03 eta: 8:36:50 time: 0.3647 data_time: 0.0034 memory: 3445 grad_norm: 0.2759 loss: 0.3797 loss_sem_seg: 0.3797 2023/04/25 13:32:01 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 13:32:01 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/04/25 13:32:10 - mmengine - INFO - Epoch(val) [2][ 50/509] eta: 0:00:38 time: 0.0844 data_time: 0.0051 memory: 3638 2023/04/25 13:32:14 - mmengine - INFO - Epoch(val) [2][100/509] eta: 0:00:33 time: 0.0813 data_time: 0.0052 memory: 840 2023/04/25 13:32:18 - mmengine - INFO - Epoch(val) [2][150/509] eta: 0:00:29 time: 0.0804 data_time: 0.0055 memory: 843 2023/04/25 13:32:22 - mmengine - INFO - Epoch(val) [2][200/509] eta: 0:00:25 time: 0.0801 data_time: 0.0049 memory: 834 2023/04/25 13:32:26 - mmengine - INFO - Epoch(val) [2][250/509] eta: 0:00:21 time: 0.0824 data_time: 0.0055 memory: 850 2023/04/25 13:32:30 - mmengine - INFO - Epoch(val) [2][300/509] eta: 0:00:16 time: 0.0767 data_time: 0.0052 memory: 812 2023/04/25 13:32:34 - mmengine - INFO - Epoch(val) [2][350/509] eta: 0:00:12 time: 0.0796 data_time: 0.0054 memory: 825 2023/04/25 13:32:38 - mmengine - INFO - Epoch(val) [2][400/509] eta: 0:00:08 time: 0.0830 data_time: 0.0052 memory: 827 2023/04/25 13:32:42 - mmengine - INFO - Epoch(val) [2][450/509] eta: 0:00:04 time: 0.0819 data_time: 0.0051 memory: 845 2023/04/25 13:32:46 - mmengine - INFO - Epoch(val) [2][500/509] eta: 0:00:00 time: 0.0773 data_time: 0.0045 memory: 832 2023/04/25 13:33:09 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9159 | 0.2104 | 0.4330 | 0.4907 | 0.0959 | 0.5721 | 0.5032 | 0.0011 | 0.9121 | 0.1762 | 0.7700 | 0.0029 | 0.8745 | 0.5865 | 0.8794 | 0.6395 | 0.7594 | 0.6132 | 0.4424 | 0.5199 | 0.9057 | 0.6183 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 13:33:09 - mmengine - INFO - Epoch(val) [2][509/509] car: 0.9159 bicycle: 0.2104 motorcycle: 0.4330 truck: 0.4907 bus: 0.0959 person: 0.5721 bicyclist: 0.5032 motorcyclist: 0.0011 road: 0.9121 parking: 0.1762 sidewalk: 0.7700 other-ground: 0.0029 building: 0.8745 fence: 0.5865 vegetation: 0.8794 trunck: 0.6395 terrian: 0.7594 pole: 0.6132 traffic-sign: 0.4424 miou: 0.5199 acc: 0.9057 acc_cls: 0.6183 data_time: 0.0044 time: 0.0780 2023/04/25 13:33:43 - mmengine - INFO - Epoch(train) [3][ 50/1196] lr: 8.0000e-03 eta: 8:29:08 time: 0.6708 data_time: 0.0053 memory: 3138 grad_norm: 0.2407 loss: 0.3638 loss_sem_seg: 0.3638 2023/04/25 13:34:23 - mmengine - INFO - Epoch(train) [3][ 100/1196] lr: 8.0000e-03 eta: 8:29:22 time: 0.8146 data_time: 0.0041 memory: 3068 grad_norm: inf loss: 0.3493 loss_sem_seg: 0.3493 2023/04/25 13:35:05 - mmengine - INFO - Epoch(train) [3][ 150/1196] lr: 8.0000e-03 eta: 8:29:38 time: 0.8215 data_time: 0.0038 memory: 3281 grad_norm: 0.2694 loss: 0.3597 loss_sem_seg: 0.3597 2023/04/25 13:35:44 - mmengine - INFO - Epoch(train) [3][ 200/1196] lr: 8.0000e-03 eta: 8:29:24 time: 0.7845 data_time: 0.0039 memory: 3122 grad_norm: 0.2721 loss: 0.3500 loss_sem_seg: 0.3500 2023/04/25 13:36:25 - mmengine - INFO - Epoch(train) [3][ 250/1196] lr: 8.0000e-03 eta: 8:29:36 time: 0.8208 data_time: 0.0038 memory: 3564 grad_norm: 0.2868 loss: 0.3471 loss_sem_seg: 0.3471 2023/04/25 13:37:04 - mmengine - INFO - Epoch(train) [3][ 300/1196] lr: 8.0000e-03 eta: 8:29:21 time: 0.7875 data_time: 0.0037 memory: 3160 grad_norm: 0.2312 loss: 0.3432 loss_sem_seg: 0.3432 2023/04/25 13:37:44 - mmengine - INFO - Epoch(train) [3][ 350/1196] lr: 8.0000e-03 eta: 8:29:14 time: 0.7982 data_time: 0.0037 memory: 3134 grad_norm: 0.2488 loss: 0.3505 loss_sem_seg: 0.3505 2023/04/25 13:38:25 - mmengine - INFO - Epoch(train) [3][ 400/1196] lr: 8.0000e-03 eta: 8:29:13 time: 0.8093 data_time: 0.0040 memory: 3165 grad_norm: 0.2486 loss: 0.3292 loss_sem_seg: 0.3292 2023/04/25 13:39:04 - mmengine - INFO - Epoch(train) [3][ 450/1196] lr: 8.0000e-03 eta: 8:28:59 time: 0.7926 data_time: 0.0040 memory: 3442 grad_norm: 0.2484 loss: 0.3171 loss_sem_seg: 0.3171 2023/04/25 13:39:45 - mmengine - INFO - Epoch(train) [3][ 500/1196] lr: 8.0000e-03 eta: 8:28:57 time: 0.8121 data_time: 0.0037 memory: 3270 grad_norm: 0.2497 loss: 0.3198 loss_sem_seg: 0.3198 2023/04/25 13:40:24 - mmengine - INFO - Epoch(train) [3][ 550/1196] lr: 8.0000e-03 eta: 8:28:40 time: 0.7903 data_time: 0.0036 memory: 3475 grad_norm: 0.2487 loss: 0.3231 loss_sem_seg: 0.3231 2023/04/25 13:41:05 - mmengine - INFO - Epoch(train) [3][ 600/1196] lr: 8.0000e-03 eta: 8:28:34 time: 0.8098 data_time: 0.0036 memory: 3305 grad_norm: 0.2445 loss: 0.3319 loss_sem_seg: 0.3319 2023/04/25 13:41:10 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 13:41:44 - mmengine - INFO - Epoch(train) [3][ 650/1196] lr: 8.0000e-03 eta: 8:28:17 time: 0.7931 data_time: 0.0039 memory: 3213 grad_norm: 0.2503 loss: 0.3147 loss_sem_seg: 0.3147 2023/04/25 13:42:25 - mmengine - INFO - Epoch(train) [3][ 700/1196] lr: 8.0000e-03 eta: 8:28:07 time: 0.8056 data_time: 0.0037 memory: 3320 grad_norm: 0.2522 loss: 0.3229 loss_sem_seg: 0.3229 2023/04/25 13:43:03 - mmengine - INFO - Epoch(train) [3][ 750/1196] lr: 8.0000e-03 eta: 8:27:31 time: 0.7666 data_time: 0.0037 memory: 3340 grad_norm: 0.2421 loss: 0.3405 loss_sem_seg: 0.3405 2023/04/25 13:43:44 - mmengine - INFO - Epoch(train) [3][ 800/1196] lr: 8.0000e-03 eta: 8:27:25 time: 0.8141 data_time: 0.0037 memory: 3186 grad_norm: 0.2216 loss: 0.3114 loss_sem_seg: 0.3114 2023/04/25 13:44:21 - mmengine - INFO - Epoch(train) [3][ 850/1196] lr: 8.0000e-03 eta: 8:26:37 time: 0.7479 data_time: 0.0038 memory: 3198 grad_norm: 0.2084 loss: 0.3350 loss_sem_seg: 0.3350 2023/04/25 13:45:01 - mmengine - INFO - Epoch(train) [3][ 900/1196] lr: 8.0000e-03 eta: 8:26:23 time: 0.8037 data_time: 0.0037 memory: 3108 grad_norm: 0.2435 loss: 0.3040 loss_sem_seg: 0.3040 2023/04/25 13:45:40 - mmengine - INFO - Epoch(train) [3][ 950/1196] lr: 8.0000e-03 eta: 8:25:47 time: 0.7682 data_time: 0.0041 memory: 3291 grad_norm: 0.2620 loss: 0.3300 loss_sem_seg: 0.3300 2023/04/25 13:46:20 - mmengine - INFO - Epoch(train) [3][1000/1196] lr: 8.0000e-03 eta: 8:25:29 time: 0.7988 data_time: 0.0037 memory: 3281 grad_norm: 0.2313 loss: 0.3207 loss_sem_seg: 0.3207 2023/04/25 13:46:59 - mmengine - INFO - Epoch(train) [3][1050/1196] lr: 8.0000e-03 eta: 8:25:07 time: 0.7917 data_time: 0.0038 memory: 3135 grad_norm: 0.2296 loss: 0.3354 loss_sem_seg: 0.3354 2023/04/25 13:47:38 - mmengine - INFO - Epoch(train) [3][1100/1196] lr: 8.0000e-03 eta: 8:24:36 time: 0.7776 data_time: 0.0038 memory: 3531 grad_norm: 0.2208 loss: 0.3146 loss_sem_seg: 0.3146 2023/04/25 13:48:16 - mmengine - INFO - Epoch(train) [3][1150/1196] lr: 8.0000e-03 eta: 8:23:51 time: 0.7533 data_time: 0.0038 memory: 3263 grad_norm: 0.2231 loss: 0.3206 loss_sem_seg: 0.3206 2023/04/25 13:48:52 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 13:48:52 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/04/25 13:49:10 - mmengine - INFO - Epoch(val) [3][ 50/509] eta: 0:01:55 time: 0.2518 data_time: 0.0057 memory: 3199 2023/04/25 13:49:21 - mmengine - INFO - Epoch(val) [3][100/509] eta: 0:01:38 time: 0.2278 data_time: 0.0052 memory: 840 2023/04/25 13:49:33 - mmengine - INFO - Epoch(val) [3][150/509] eta: 0:01:24 time: 0.2306 data_time: 0.0057 memory: 843 2023/04/25 13:49:44 - mmengine - INFO - Epoch(val) [3][200/509] eta: 0:01:13 time: 0.2356 data_time: 0.0053 memory: 834 2023/04/25 13:49:55 - mmengine - INFO - Epoch(val) [3][250/509] eta: 0:00:59 time: 0.2102 data_time: 0.0054 memory: 850 2023/04/25 13:50:05 - mmengine - INFO - Epoch(val) [3][300/509] eta: 0:00:47 time: 0.1990 data_time: 0.0050 memory: 812 2023/04/25 13:50:17 - mmengine - INFO - Epoch(val) [3][350/509] eta: 0:00:36 time: 0.2485 data_time: 0.0055 memory: 825 2023/04/25 13:50:29 - mmengine - INFO - Epoch(val) [3][400/509] eta: 0:00:24 time: 0.2300 data_time: 0.0056 memory: 827 2023/04/25 13:50:45 - mmengine - INFO - Epoch(val) [3][450/509] eta: 0:00:14 time: 0.3251 data_time: 0.0049 memory: 845 2023/04/25 13:51:01 - mmengine - INFO - Epoch(val) [3][500/509] eta: 0:00:02 time: 0.3211 data_time: 0.0047 memory: 832 2023/04/25 13:51:30 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9445 | 0.1588 | 0.5120 | 0.6210 | 0.3675 | 0.6425 | 0.7842 | 0.0004 | 0.9170 | 0.3169 | 0.7887 | 0.0047 | 0.8896 | 0.5731 | 0.8962 | 0.6351 | 0.7812 | 0.6424 | 0.4576 | 0.5754 | 0.9165 | 0.6533 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 13:51:30 - mmengine - INFO - Epoch(val) [3][509/509] car: 0.9445 bicycle: 0.1588 motorcycle: 0.5120 truck: 0.6210 bus: 0.3675 person: 0.6425 bicyclist: 0.7842 motorcyclist: 0.0004 road: 0.9170 parking: 0.3169 sidewalk: 0.7887 other-ground: 0.0047 building: 0.8896 fence: 0.5731 vegetation: 0.8962 trunck: 0.6351 terrian: 0.7812 pole: 0.6424 traffic-sign: 0.4576 miou: 0.5754 acc: 0.9165 acc_cls: 0.6533 data_time: 0.0045 time: 0.3228 2023/04/25 13:52:09 - mmengine - INFO - Epoch(train) [4][ 50/1196] lr: 8.0000e-03 eta: 8:23:03 time: 0.7952 data_time: 0.0047 memory: 3047 grad_norm: 0.2067 loss: 0.2969 loss_sem_seg: 0.2969 2023/04/25 13:52:50 - mmengine - INFO - Epoch(train) [4][ 100/1196] lr: 8.0000e-03 eta: 8:22:48 time: 0.8085 data_time: 0.0038 memory: 3106 grad_norm: 0.2040 loss: 0.3105 loss_sem_seg: 0.3105 2023/04/25 13:53:29 - mmengine - INFO - Epoch(train) [4][ 150/1196] lr: 8.0000e-03 eta: 8:22:18 time: 0.7830 data_time: 0.0039 memory: 3203 grad_norm: 0.2399 loss: 0.3174 loss_sem_seg: 0.3174 2023/04/25 13:54:09 - mmengine - INFO - Epoch(train) [4][ 200/1196] lr: 8.0000e-03 eta: 8:21:56 time: 0.7966 data_time: 0.0039 memory: 3173 grad_norm: 0.1994 loss: 0.2980 loss_sem_seg: 0.2980 2023/04/25 13:54:47 - mmengine - INFO - Epoch(train) [4][ 250/1196] lr: 8.0000e-03 eta: 8:21:14 time: 0.7613 data_time: 0.0041 memory: 3100 grad_norm: 0.2026 loss: 0.3163 loss_sem_seg: 0.3163 2023/04/25 13:55:25 - mmengine - INFO - Epoch(train) [4][ 300/1196] lr: 8.0000e-03 eta: 8:20:37 time: 0.7690 data_time: 0.0039 memory: 3268 grad_norm: 0.2211 loss: 0.3085 loss_sem_seg: 0.3085 2023/04/25 13:56:05 - mmengine - INFO - Epoch(train) [4][ 350/1196] lr: 8.0000e-03 eta: 8:20:15 time: 0.7990 data_time: 0.0038 memory: 3757 grad_norm: 0.2068 loss: 0.3129 loss_sem_seg: 0.3129 2023/04/25 13:56:47 - mmengine - INFO - Epoch(train) [4][ 400/1196] lr: 8.0000e-03 eta: 8:20:06 time: 0.8271 data_time: 0.0037 memory: 3185 grad_norm: 0.2064 loss: 0.3242 loss_sem_seg: 0.3242 2023/04/25 13:56:57 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 13:57:25 - mmengine - INFO - Epoch(train) [4][ 450/1196] lr: 8.0000e-03 eta: 8:19:25 time: 0.7638 data_time: 0.0043 memory: 3239 grad_norm: 0.2239 loss: 0.3211 loss_sem_seg: 0.3211 2023/04/25 13:58:05 - mmengine - INFO - Epoch(train) [4][ 500/1196] lr: 8.0000e-03 eta: 8:19:03 time: 0.8012 data_time: 0.0039 memory: 3221 grad_norm: 0.2026 loss: 0.3300 loss_sem_seg: 0.3300 2023/04/25 13:58:46 - mmengine - INFO - Epoch(train) [4][ 550/1196] lr: 8.0000e-03 eta: 8:18:48 time: 0.8194 data_time: 0.0038 memory: 3158 grad_norm: 0.2050 loss: 0.3155 loss_sem_seg: 0.3155 2023/04/25 13:59:25 - mmengine - INFO - Epoch(train) [4][ 600/1196] lr: 8.0000e-03 eta: 8:18:15 time: 0.7798 data_time: 0.0039 memory: 3365 grad_norm: 0.2150 loss: 0.3200 loss_sem_seg: 0.3200 2023/04/25 14:00:04 - mmengine - INFO - Epoch(train) [4][ 650/1196] lr: 8.0000e-03 eta: 8:17:46 time: 0.7910 data_time: 0.0040 memory: 3091 grad_norm: 0.1765 loss: 0.2912 loss_sem_seg: 0.2912 2023/04/25 14:00:44 - mmengine - INFO - Epoch(train) [4][ 700/1196] lr: 8.0000e-03 eta: 8:17:20 time: 0.7957 data_time: 0.0041 memory: 3128 grad_norm: 0.1981 loss: 0.3058 loss_sem_seg: 0.3058 2023/04/25 14:01:25 - mmengine - INFO - Epoch(train) [4][ 750/1196] lr: 8.0000e-03 eta: 8:17:00 time: 0.8118 data_time: 0.0040 memory: 3110 grad_norm: 0.1787 loss: 0.2950 loss_sem_seg: 0.2950 2023/04/25 14:02:05 - mmengine - INFO - Epoch(train) [4][ 800/1196] lr: 8.0000e-03 eta: 8:16:34 time: 0.7979 data_time: 0.0041 memory: 3008 grad_norm: 0.2027 loss: 0.2983 loss_sem_seg: 0.2983 2023/04/25 14:02:44 - mmengine - INFO - Epoch(train) [4][ 850/1196] lr: 8.0000e-03 eta: 8:15:57 time: 0.7754 data_time: 0.0042 memory: 3386 grad_norm: 0.2026 loss: 0.3006 loss_sem_seg: 0.3006 2023/04/25 14:03:23 - mmengine - INFO - Epoch(train) [4][ 900/1196] lr: 8.0000e-03 eta: 8:15:31 time: 0.7980 data_time: 0.0042 memory: 3360 grad_norm: 0.1811 loss: 0.2924 loss_sem_seg: 0.2924 2023/04/25 14:04:03 - mmengine - INFO - Epoch(train) [4][ 950/1196] lr: 8.0000e-03 eta: 8:15:00 time: 0.7886 data_time: 0.0042 memory: 3495 grad_norm: 0.1842 loss: 0.3223 loss_sem_seg: 0.3223 2023/04/25 14:04:43 - mmengine - INFO - Epoch(train) [4][1000/1196] lr: 8.0000e-03 eta: 8:14:35 time: 0.8042 data_time: 0.0040 memory: 3247 grad_norm: inf loss: 0.2775 loss_sem_seg: 0.2775 2023/04/25 14:05:22 - mmengine - INFO - Epoch(train) [4][1050/1196] lr: 8.0000e-03 eta: 8:13:58 time: 0.7748 data_time: 0.0042 memory: 3259 grad_norm: 0.1962 loss: 0.3054 loss_sem_seg: 0.3054 2023/04/25 14:06:02 - mmengine - INFO - Epoch(train) [4][1100/1196] lr: 8.0000e-03 eta: 8:13:35 time: 0.8100 data_time: 0.0039 memory: 3320 grad_norm: 0.1777 loss: 0.3086 loss_sem_seg: 0.3086 2023/04/25 14:06:40 - mmengine - INFO - Epoch(train) [4][1150/1196] lr: 8.0000e-03 eta: 8:12:52 time: 0.7604 data_time: 0.0038 memory: 3211 grad_norm: 0.1938 loss: 0.2930 loss_sem_seg: 0.2930 2023/04/25 14:07:16 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 14:07:16 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/04/25 14:07:34 - mmengine - INFO - Epoch(val) [4][ 50/509] eta: 0:01:56 time: 0.2549 data_time: 0.0056 memory: 3189 2023/04/25 14:07:42 - mmengine - INFO - Epoch(val) [4][100/509] eta: 0:01:26 time: 0.1704 data_time: 0.0057 memory: 840 2023/04/25 14:07:55 - mmengine - INFO - Epoch(val) [4][150/509] eta: 0:01:20 time: 0.2508 data_time: 0.0056 memory: 843 2023/04/25 14:08:06 - mmengine - INFO - Epoch(val) [4][200/509] eta: 0:01:10 time: 0.2302 data_time: 0.0054 memory: 834 2023/04/25 14:08:17 - mmengine - INFO - Epoch(val) [4][250/509] eta: 0:00:57 time: 0.2026 data_time: 0.0052 memory: 850 2023/04/25 14:08:29 - mmengine - INFO - Epoch(val) [4][300/509] eta: 0:00:47 time: 0.2437 data_time: 0.0050 memory: 812 2023/04/25 14:08:39 - mmengine - INFO - Epoch(val) [4][350/509] eta: 0:00:35 time: 0.1984 data_time: 0.0049 memory: 825 2023/04/25 14:08:51 - mmengine - INFO - Epoch(val) [4][400/509] eta: 0:00:24 time: 0.2422 data_time: 0.0050 memory: 827 2023/04/25 14:09:06 - mmengine - INFO - Epoch(val) [4][450/509] eta: 0:00:13 time: 0.3050 data_time: 0.0049 memory: 845 2023/04/25 14:09:26 - mmengine - INFO - Epoch(val) [4][500/509] eta: 0:00:02 time: 0.3895 data_time: 0.0045 memory: 832 2023/04/25 14:10:12 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9531 | 0.4204 | 0.6140 | 0.4460 | 0.3731 | 0.6606 | 0.7391 | 0.0310 | 0.9270 | 0.2866 | 0.8068 | 0.0278 | 0.9028 | 0.5844 | 0.8843 | 0.6647 | 0.7577 | 0.6370 | 0.4712 | 0.5888 | 0.9159 | 0.6948 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 14:10:12 - mmengine - INFO - Epoch(val) [4][509/509] car: 0.9531 bicycle: 0.4204 motorcycle: 0.6140 truck: 0.4460 bus: 0.3731 person: 0.6606 bicyclist: 0.7391 motorcyclist: 0.0310 road: 0.9270 parking: 0.2866 sidewalk: 0.8068 other-ground: 0.0278 building: 0.9028 fence: 0.5844 vegetation: 0.8843 trunck: 0.6647 terrian: 0.7577 pole: 0.6370 traffic-sign: 0.4712 miou: 0.5888 acc: 0.9159 acc_cls: 0.6948 data_time: 0.0042 time: 0.3867 2023/04/25 14:10:52 - mmengine - INFO - Epoch(train) [5][ 50/1196] lr: 8.0000e-03 eta: 8:11:46 time: 0.7897 data_time: 0.0047 memory: 3115 grad_norm: 0.1929 loss: 0.2978 loss_sem_seg: 0.2978 2023/04/25 14:11:32 - mmengine - INFO - Epoch(train) [5][ 100/1196] lr: 8.0000e-03 eta: 8:11:18 time: 0.7986 data_time: 0.0037 memory: 3240 grad_norm: 0.1689 loss: 0.3013 loss_sem_seg: 0.3013 2023/04/25 14:12:11 - mmengine - INFO - Epoch(train) [5][ 150/1196] lr: 8.0000e-03 eta: 8:10:48 time: 0.7946 data_time: 0.0037 memory: 3178 grad_norm: 0.1685 loss: 0.2820 loss_sem_seg: 0.2820 2023/04/25 14:12:51 - mmengine - INFO - Epoch(train) [5][ 200/1196] lr: 8.0000e-03 eta: 8:10:21 time: 0.8025 data_time: 0.0037 memory: 3283 grad_norm: 0.1743 loss: 0.2927 loss_sem_seg: 0.2927 2023/04/25 14:13:04 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 14:13:31 - mmengine - INFO - Epoch(train) [5][ 250/1196] lr: 8.0000e-03 eta: 8:09:47 time: 0.7859 data_time: 0.0038 memory: 3294 grad_norm: 0.1702 loss: 0.3092 loss_sem_seg: 0.3092 2023/04/25 14:14:09 - mmengine - INFO - Epoch(train) [5][ 300/1196] lr: 8.0000e-03 eta: 8:09:07 time: 0.7693 data_time: 0.0036 memory: 3193 grad_norm: 0.1820 loss: 0.2966 loss_sem_seg: 0.2966 2023/04/25 14:14:50 - mmengine - INFO - Epoch(train) [5][ 350/1196] lr: 8.0000e-03 eta: 8:08:44 time: 0.8157 data_time: 0.0037 memory: 3087 grad_norm: 0.1728 loss: 0.2915 loss_sem_seg: 0.2915 2023/04/25 14:15:29 - mmengine - INFO - Epoch(train) [5][ 400/1196] lr: 8.0000e-03 eta: 8:08:09 time: 0.7808 data_time: 0.0037 memory: 3349 grad_norm: 0.1698 loss: 0.3065 loss_sem_seg: 0.3065 2023/04/25 14:16:09 - mmengine - INFO - Epoch(train) [5][ 450/1196] lr: 8.0000e-03 eta: 8:07:43 time: 0.8086 data_time: 0.0035 memory: 3163 grad_norm: 0.1636 loss: 0.2905 loss_sem_seg: 0.2905 2023/04/25 14:16:50 - mmengine - INFO - Epoch(train) [5][ 500/1196] lr: 8.0000e-03 eta: 8:07:19 time: 0.8158 data_time: 0.0035 memory: 3243 grad_norm: 0.1805 loss: 0.2789 loss_sem_seg: 0.2789 2023/04/25 14:17:31 - mmengine - INFO - Epoch(train) [5][ 550/1196] lr: 8.0000e-03 eta: 8:06:52 time: 0.8083 data_time: 0.0037 memory: 3200 grad_norm: 0.1833 loss: 0.2855 loss_sem_seg: 0.2855 2023/04/25 14:18:11 - mmengine - INFO - Epoch(train) [5][ 600/1196] lr: 8.0000e-03 eta: 8:06:24 time: 0.8039 data_time: 0.0035 memory: 3284 grad_norm: 0.1897 loss: 0.3075 loss_sem_seg: 0.3075 2023/04/25 14:18:50 - mmengine - INFO - Epoch(train) [5][ 650/1196] lr: 8.0000e-03 eta: 8:05:45 time: 0.7749 data_time: 0.0038 memory: 3165 grad_norm: 0.1605 loss: 0.2839 loss_sem_seg: 0.2839 2023/04/25 14:19:31 - mmengine - INFO - Epoch(train) [5][ 700/1196] lr: 8.0000e-03 eta: 8:05:22 time: 0.8212 data_time: 0.0035 memory: 3262 grad_norm: 0.1688 loss: 0.3002 loss_sem_seg: 0.3002 2023/04/25 14:20:09 - mmengine - INFO - Epoch(train) [5][ 750/1196] lr: 8.0000e-03 eta: 8:04:40 time: 0.7644 data_time: 0.0037 memory: 3136 grad_norm: 0.1655 loss: 0.2904 loss_sem_seg: 0.2904 2023/04/25 14:20:49 - mmengine - INFO - Epoch(train) [5][ 800/1196] lr: 8.0000e-03 eta: 8:04:13 time: 0.8110 data_time: 0.0035 memory: 3135 grad_norm: 0.1646 loss: 0.2804 loss_sem_seg: 0.2804 2023/04/25 14:21:29 - mmengine - INFO - Epoch(train) [5][ 850/1196] lr: 8.0000e-03 eta: 8:03:37 time: 0.7837 data_time: 0.0037 memory: 3166 grad_norm: 0.1661 loss: 0.2780 loss_sem_seg: 0.2780 2023/04/25 14:22:08 - mmengine - INFO - Epoch(train) [5][ 900/1196] lr: 8.0000e-03 eta: 8:03:04 time: 0.7922 data_time: 0.0035 memory: 3050 grad_norm: 0.1786 loss: 0.2869 loss_sem_seg: 0.2869 2023/04/25 14:22:47 - mmengine - INFO - Epoch(train) [5][ 950/1196] lr: 8.0000e-03 eta: 8:02:27 time: 0.7792 data_time: 0.0037 memory: 3180 grad_norm: 0.1679 loss: 0.2744 loss_sem_seg: 0.2744 2023/04/25 14:23:28 - mmengine - INFO - Epoch(train) [5][1000/1196] lr: 8.0000e-03 eta: 8:02:00 time: 0.8141 data_time: 0.0035 memory: 3250 grad_norm: 0.1774 loss: 0.2732 loss_sem_seg: 0.2732 2023/04/25 14:24:06 - mmengine - INFO - Epoch(train) [5][1050/1196] lr: 8.0000e-03 eta: 8:01:19 time: 0.7686 data_time: 0.0036 memory: 3171 grad_norm: 0.1472 loss: 0.2747 loss_sem_seg: 0.2747 2023/04/25 14:24:47 - mmengine - INFO - Epoch(train) [5][1100/1196] lr: 8.0000e-03 eta: 8:00:54 time: 0.8198 data_time: 0.0036 memory: 3257 grad_norm: 0.1544 loss: 0.2769 loss_sem_seg: 0.2769 2023/04/25 14:25:26 - mmengine - INFO - Epoch(train) [5][1150/1196] lr: 8.0000e-03 eta: 8:00:12 time: 0.7668 data_time: 0.0037 memory: 3150 grad_norm: 0.1570 loss: 0.2939 loss_sem_seg: 0.2939 2023/04/25 14:26:01 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 14:26:01 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/04/25 14:26:17 - mmengine - INFO - Epoch(val) [5][ 50/509] eta: 0:01:43 time: 0.2251 data_time: 0.0057 memory: 3110 2023/04/25 14:26:26 - mmengine - INFO - Epoch(val) [5][100/509] eta: 0:01:22 time: 0.1803 data_time: 0.0053 memory: 840 2023/04/25 14:26:37 - mmengine - INFO - Epoch(val) [5][150/509] eta: 0:01:14 time: 0.2137 data_time: 0.0055 memory: 843 2023/04/25 14:26:47 - mmengine - INFO - Epoch(val) [5][200/509] eta: 0:01:02 time: 0.1935 data_time: 0.0056 memory: 834 2023/04/25 14:26:56 - mmengine - INFO - Epoch(val) [5][250/509] eta: 0:00:52 time: 0.1942 data_time: 0.0058 memory: 850 2023/04/25 14:27:06 - mmengine - INFO - Epoch(val) [5][300/509] eta: 0:00:41 time: 0.1877 data_time: 0.0053 memory: 812 2023/04/25 14:27:16 - mmengine - INFO - Epoch(val) [5][350/509] eta: 0:00:31 time: 0.2042 data_time: 0.0058 memory: 825 2023/04/25 14:27:27 - mmengine - INFO - Epoch(val) [5][400/509] eta: 0:00:22 time: 0.2246 data_time: 0.0054 memory: 827 2023/04/25 14:27:40 - mmengine - INFO - Epoch(val) [5][450/509] eta: 0:00:12 time: 0.2487 data_time: 0.0056 memory: 845 2023/04/25 14:27:55 - mmengine - INFO - Epoch(val) [5][500/509] eta: 0:00:01 time: 0.3177 data_time: 0.0048 memory: 832 2023/04/25 14:28:27 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9621 | 0.3645 | 0.6747 | 0.5908 | 0.6255 | 0.6725 | 0.8131 | 0.0273 | 0.9304 | 0.4260 | 0.8037 | 0.0023 | 0.8958 | 0.5911 | 0.8957 | 0.6192 | 0.7858 | 0.6423 | 0.4939 | 0.6219 | 0.9226 | 0.6894 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 14:28:27 - mmengine - INFO - Epoch(val) [5][509/509] car: 0.9621 bicycle: 0.3645 motorcycle: 0.6747 truck: 0.5908 bus: 0.6255 person: 0.6725 bicyclist: 0.8131 motorcyclist: 0.0273 road: 0.9304 parking: 0.4260 sidewalk: 0.8037 other-ground: 0.0023 building: 0.8958 fence: 0.5911 vegetation: 0.8957 trunck: 0.6192 terrian: 0.7858 pole: 0.6423 traffic-sign: 0.4939 miou: 0.6219 acc: 0.9226 acc_cls: 0.6894 data_time: 0.0047 time: 0.3194 2023/04/25 14:28:43 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 14:29:07 - mmengine - INFO - Epoch(train) [6][ 50/1196] lr: 8.0000e-03 eta: 7:59:03 time: 0.7975 data_time: 0.0046 memory: 3164 grad_norm: 0.1555 loss: 0.2843 loss_sem_seg: 0.2843 2023/04/25 14:29:45 - mmengine - INFO - Epoch(train) [6][ 100/1196] lr: 8.0000e-03 eta: 7:58:21 time: 0.7641 data_time: 0.0036 memory: 3447 grad_norm: 0.1601 loss: 0.2687 loss_sem_seg: 0.2687 2023/04/25 14:30:27 - mmengine - INFO - Epoch(train) [6][ 150/1196] lr: 8.0000e-03 eta: 7:58:00 time: 0.8348 data_time: 0.0036 memory: 3505 grad_norm: 0.1405 loss: 0.2859 loss_sem_seg: 0.2859 2023/04/25 14:31:04 - mmengine - INFO - Epoch(train) [6][ 200/1196] lr: 8.0000e-03 eta: 7:57:11 time: 0.7449 data_time: 0.0035 memory: 3134 grad_norm: 0.1594 loss: 0.2926 loss_sem_seg: 0.2926 2023/04/25 14:31:43 - mmengine - INFO - Epoch(train) [6][ 250/1196] lr: 8.0000e-03 eta: 7:56:37 time: 0.7921 data_time: 0.0036 memory: 3300 grad_norm: 0.1644 loss: 0.2659 loss_sem_seg: 0.2659 2023/04/25 14:32:24 - mmengine - INFO - Epoch(train) [6][ 300/1196] lr: 8.0000e-03 eta: 7:56:08 time: 0.8096 data_time: 0.0034 memory: 3286 grad_norm: 0.1696 loss: 0.2895 loss_sem_seg: 0.2895 2023/04/25 14:33:03 - mmengine - INFO - Epoch(train) [6][ 350/1196] lr: 8.0000e-03 eta: 7:55:30 time: 0.7798 data_time: 0.0035 memory: 3351 grad_norm: 0.1532 loss: 0.2840 loss_sem_seg: 0.2840 2023/04/25 14:33:41 - mmengine - INFO - Epoch(train) [6][ 400/1196] lr: 8.0000e-03 eta: 7:54:46 time: 0.7602 data_time: 0.0035 memory: 3163 grad_norm: 0.1704 loss: 0.2808 loss_sem_seg: 0.2808 2023/04/25 14:34:21 - mmengine - INFO - Epoch(train) [6][ 450/1196] lr: 8.0000e-03 eta: 7:54:13 time: 0.7970 data_time: 0.0036 memory: 3371 grad_norm: 0.1481 loss: 0.2719 loss_sem_seg: 0.2719 2023/04/25 14:35:00 - mmengine - INFO - Epoch(train) [6][ 500/1196] lr: 8.0000e-03 eta: 7:53:38 time: 0.7906 data_time: 0.0036 memory: 3331 grad_norm: 0.1496 loss: 0.2745 loss_sem_seg: 0.2745 2023/04/25 14:35:39 - mmengine - INFO - Epoch(train) [6][ 550/1196] lr: 8.0000e-03 eta: 7:52:57 time: 0.7667 data_time: 0.0036 memory: 3331 grad_norm: 0.1601 loss: 0.2795 loss_sem_seg: 0.2795 2023/04/25 14:36:19 - mmengine - INFO - Epoch(train) [6][ 600/1196] lr: 8.0000e-03 eta: 7:52:26 time: 0.8048 data_time: 0.0035 memory: 3203 grad_norm: 0.1548 loss: 0.2817 loss_sem_seg: 0.2817 2023/04/25 14:36:58 - mmengine - INFO - Epoch(train) [6][ 650/1196] lr: 8.0000e-03 eta: 7:51:51 time: 0.7916 data_time: 0.0037 memory: 3289 grad_norm: 0.1562 loss: 0.2806 loss_sem_seg: 0.2806 2023/04/25 14:37:39 - mmengine - INFO - Epoch(train) [6][ 700/1196] lr: 8.0000e-03 eta: 7:51:19 time: 0.8049 data_time: 0.0034 memory: 3245 grad_norm: 0.1463 loss: 0.2997 loss_sem_seg: 0.2997 2023/04/25 14:38:20 - mmengine - INFO - Epoch(train) [6][ 750/1196] lr: 8.0000e-03 eta: 7:50:52 time: 0.8199 data_time: 0.0036 memory: 3380 grad_norm: 0.1436 loss: 0.2626 loss_sem_seg: 0.2626 2023/04/25 14:39:01 - mmengine - INFO - Epoch(train) [6][ 800/1196] lr: 8.0000e-03 eta: 7:50:26 time: 0.8252 data_time: 0.0035 memory: 3131 grad_norm: 0.1582 loss: 0.2831 loss_sem_seg: 0.2831 2023/04/25 14:39:41 - mmengine - INFO - Epoch(train) [6][ 850/1196] lr: 8.0000e-03 eta: 7:49:55 time: 0.8095 data_time: 0.0037 memory: 3270 grad_norm: 0.1405 loss: 0.2878 loss_sem_seg: 0.2878 2023/04/25 14:40:22 - mmengine - INFO - Epoch(train) [6][ 900/1196] lr: 8.0000e-03 eta: 7:49:27 time: 0.8208 data_time: 0.0038 memory: 3191 grad_norm: 0.1484 loss: 0.2570 loss_sem_seg: 0.2570 2023/04/25 14:41:03 - mmengine - INFO - Epoch(train) [6][ 950/1196] lr: 8.0000e-03 eta: 7:48:56 time: 0.8087 data_time: 0.0035 memory: 3200 grad_norm: 0.1505 loss: 0.2752 loss_sem_seg: 0.2752 2023/04/25 14:41:42 - mmengine - INFO - Epoch(train) [6][1000/1196] lr: 8.0000e-03 eta: 7:48:20 time: 0.7881 data_time: 0.0039 memory: 3387 grad_norm: 0.1506 loss: 0.2638 loss_sem_seg: 0.2638 2023/04/25 14:42:00 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 14:42:24 - mmengine - INFO - Epoch(train) [6][1050/1196] lr: 8.0000e-03 eta: 7:47:56 time: 0.8402 data_time: 0.0036 memory: 3482 grad_norm: 0.1510 loss: 0.2844 loss_sem_seg: 0.2844 2023/04/25 14:43:06 - mmengine - INFO - Epoch(train) [6][1100/1196] lr: 8.0000e-03 eta: 7:47:31 time: 0.8331 data_time: 0.0038 memory: 3402 grad_norm: 0.1469 loss: 0.2684 loss_sem_seg: 0.2684 2023/04/25 14:43:46 - mmengine - INFO - Epoch(train) [6][1150/1196] lr: 8.0000e-03 eta: 7:46:57 time: 0.7998 data_time: 0.0038 memory: 3337 grad_norm: inf loss: 0.2586 loss_sem_seg: 0.2586 2023/04/25 14:44:22 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 14:44:22 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/04/25 14:44:38 - mmengine - INFO - Epoch(val) [6][ 50/509] eta: 0:01:36 time: 0.2095 data_time: 0.0049 memory: 3115 2023/04/25 14:44:47 - mmengine - INFO - Epoch(val) [6][100/509] eta: 0:01:20 time: 0.1857 data_time: 0.0055 memory: 840 2023/04/25 14:44:57 - mmengine - INFO - Epoch(val) [6][150/509] eta: 0:01:11 time: 0.2041 data_time: 0.0049 memory: 843 2023/04/25 14:45:08 - mmengine - INFO - Epoch(val) [6][200/509] eta: 0:01:02 time: 0.2095 data_time: 0.0046 memory: 834 2023/04/25 14:45:18 - mmengine - INFO - Epoch(val) [6][250/509] eta: 0:00:52 time: 0.1978 data_time: 0.0050 memory: 850 2023/04/25 14:45:29 - mmengine - INFO - Epoch(val) [6][300/509] eta: 0:00:42 time: 0.2227 data_time: 0.0053 memory: 812 2023/04/25 14:45:39 - mmengine - INFO - Epoch(val) [6][350/509] eta: 0:00:32 time: 0.2012 data_time: 0.0051 memory: 825 2023/04/25 14:45:50 - mmengine - INFO - Epoch(val) [6][400/509] eta: 0:00:22 time: 0.2218 data_time: 0.0048 memory: 827 2023/04/25 14:46:00 - mmengine - INFO - Epoch(val) [6][450/509] eta: 0:00:12 time: 0.2082 data_time: 0.0054 memory: 845 2023/04/25 14:46:18 - mmengine - INFO - Epoch(val) [6][500/509] eta: 0:00:01 time: 0.3514 data_time: 0.0048 memory: 832 2023/04/25 14:46:42 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9606 | 0.5102 | 0.7010 | 0.6931 | 0.6165 | 0.7089 | 0.8197 | 0.0015 | 0.9290 | 0.4001 | 0.8073 | 0.0775 | 0.8945 | 0.5939 | 0.8996 | 0.6798 | 0.7895 | 0.6324 | 0.5034 | 0.6431 | 0.9238 | 0.7220 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 14:46:42 - mmengine - INFO - Epoch(val) [6][509/509] car: 0.9606 bicycle: 0.5102 motorcycle: 0.7010 truck: 0.6931 bus: 0.6165 person: 0.7089 bicyclist: 0.8197 motorcyclist: 0.0015 road: 0.9290 parking: 0.4001 sidewalk: 0.8073 other-ground: 0.0775 building: 0.8945 fence: 0.5939 vegetation: 0.8996 trunck: 0.6798 terrian: 0.7895 pole: 0.6324 traffic-sign: 0.5034 miou: 0.6431 acc: 0.9238 acc_cls: 0.7220 data_time: 0.0047 time: 0.3472 2023/04/25 14:47:23 - mmengine - INFO - Epoch(train) [7][ 50/1196] lr: 8.0000e-03 eta: 7:45:54 time: 0.8178 data_time: 0.0046 memory: 3126 grad_norm: 0.1609 loss: 0.2684 loss_sem_seg: 0.2684 2023/04/25 14:48:03 - mmengine - INFO - Epoch(train) [7][ 100/1196] lr: 8.0000e-03 eta: 7:45:21 time: 0.8020 data_time: 0.0035 memory: 3320 grad_norm: 0.1467 loss: 0.2789 loss_sem_seg: 0.2789 2023/04/25 14:48:43 - mmengine - INFO - Epoch(train) [7][ 150/1196] lr: 8.0000e-03 eta: 7:44:48 time: 0.8047 data_time: 0.0036 memory: 3226 grad_norm: 0.1385 loss: 0.2615 loss_sem_seg: 0.2615 2023/04/25 14:49:24 - mmengine - INFO - Epoch(train) [7][ 200/1196] lr: 8.0000e-03 eta: 7:44:14 time: 0.8045 data_time: 0.0035 memory: 3192 grad_norm: 0.1691 loss: 0.2831 loss_sem_seg: 0.2831 2023/04/25 14:50:04 - mmengine - INFO - Epoch(train) [7][ 250/1196] lr: 8.0000e-03 eta: 7:43:40 time: 0.8008 data_time: 0.0035 memory: 3205 grad_norm: 0.1525 loss: 0.2655 loss_sem_seg: 0.2655 2023/04/25 14:50:43 - mmengine - INFO - Epoch(train) [7][ 300/1196] lr: 8.0000e-03 eta: 7:43:00 time: 0.7779 data_time: 0.0037 memory: 3372 grad_norm: 0.1373 loss: 0.2801 loss_sem_seg: 0.2801 2023/04/25 14:51:24 - mmengine - INFO - Epoch(train) [7][ 350/1196] lr: 8.0000e-03 eta: 7:42:31 time: 0.8212 data_time: 0.0035 memory: 3406 grad_norm: 0.1583 loss: 0.2585 loss_sem_seg: 0.2585 2023/04/25 14:52:03 - mmengine - INFO - Epoch(train) [7][ 400/1196] lr: 8.0000e-03 eta: 7:41:55 time: 0.7962 data_time: 0.0037 memory: 3174 grad_norm: 0.1447 loss: 0.2727 loss_sem_seg: 0.2727 2023/04/25 14:52:45 - mmengine - INFO - Epoch(train) [7][ 450/1196] lr: 8.0000e-03 eta: 7:41:28 time: 0.8297 data_time: 0.0039 memory: 3249 grad_norm: 0.1346 loss: 0.2718 loss_sem_seg: 0.2718 2023/04/25 14:53:25 - mmengine - INFO - Epoch(train) [7][ 500/1196] lr: 8.0000e-03 eta: 7:40:53 time: 0.7986 data_time: 0.0040 memory: 3234 grad_norm: 0.1458 loss: 0.2883 loss_sem_seg: 0.2883 2023/04/25 14:54:04 - mmengine - INFO - Epoch(train) [7][ 550/1196] lr: 8.0000e-03 eta: 7:40:15 time: 0.7895 data_time: 0.0041 memory: 3177 grad_norm: 0.1518 loss: 0.2575 loss_sem_seg: 0.2575 2023/04/25 14:54:45 - mmengine - INFO - Epoch(train) [7][ 600/1196] lr: 8.0000e-03 eta: 7:39:41 time: 0.8050 data_time: 0.0036 memory: 3131 grad_norm: 0.1433 loss: 0.2721 loss_sem_seg: 0.2721 2023/04/25 14:55:23 - mmengine - INFO - Epoch(train) [7][ 650/1196] lr: 8.0000e-03 eta: 7:38:59 time: 0.7673 data_time: 0.0037 memory: 3056 grad_norm: 0.1482 loss: 0.2853 loss_sem_seg: 0.2853 2023/04/25 14:56:04 - mmengine - INFO - Epoch(train) [7][ 700/1196] lr: 8.0000e-03 eta: 7:38:28 time: 0.8182 data_time: 0.0037 memory: 3283 grad_norm: 0.1598 loss: 0.2776 loss_sem_seg: 0.2776 2023/04/25 14:56:43 - mmengine - INFO - Epoch(train) [7][ 750/1196] lr: 8.0000e-03 eta: 7:37:47 time: 0.7748 data_time: 0.0039 memory: 3072 grad_norm: 0.1408 loss: 0.2642 loss_sem_seg: 0.2642 2023/04/25 14:57:23 - mmengine - INFO - Epoch(train) [7][ 800/1196] lr: 8.0000e-03 eta: 7:37:12 time: 0.8001 data_time: 0.0038 memory: 3043 grad_norm: 0.1376 loss: 0.2660 loss_sem_seg: 0.2660 2023/04/25 14:57:42 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 14:58:03 - mmengine - INFO - Epoch(train) [7][ 850/1196] lr: 8.0000e-03 eta: 7:36:39 time: 0.8064 data_time: 0.0037 memory: 3390 grad_norm: 0.1363 loss: 0.2654 loss_sem_seg: 0.2654 2023/04/25 14:58:43 - mmengine - INFO - Epoch(train) [7][ 900/1196] lr: 8.0000e-03 eta: 7:36:03 time: 0.7995 data_time: 0.0037 memory: 3179 grad_norm: 0.1514 loss: 0.2627 loss_sem_seg: 0.2627 2023/04/25 14:59:23 - mmengine - INFO - Epoch(train) [7][ 950/1196] lr: 8.0000e-03 eta: 7:35:26 time: 0.7926 data_time: 0.0034 memory: 3293 grad_norm: 0.1403 loss: 0.2482 loss_sem_seg: 0.2482 2023/04/25 15:00:04 - mmengine - INFO - Epoch(train) [7][1000/1196] lr: 8.0000e-03 eta: 7:34:57 time: 0.8288 data_time: 0.0035 memory: 3055 grad_norm: 0.1292 loss: 0.2639 loss_sem_seg: 0.2639 2023/04/25 15:00:42 - mmengine - INFO - Epoch(train) [7][1050/1196] lr: 8.0000e-03 eta: 7:34:15 time: 0.7695 data_time: 0.0037 memory: 3097 grad_norm: 0.1384 loss: 0.2787 loss_sem_seg: 0.2787 2023/04/25 15:01:24 - mmengine - INFO - Epoch(train) [7][1100/1196] lr: 8.0000e-03 eta: 7:33:48 time: 0.8398 data_time: 0.0036 memory: 3332 grad_norm: 0.1365 loss: 0.2719 loss_sem_seg: 0.2719 2023/04/25 15:02:05 - mmengine - INFO - Epoch(train) [7][1150/1196] lr: 8.0000e-03 eta: 7:33:15 time: 0.8107 data_time: 0.0039 memory: 3878 grad_norm: 0.1355 loss: 0.2549 loss_sem_seg: 0.2549 2023/04/25 15:02:40 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 15:02:40 - mmengine - INFO - Saving checkpoint at 7 epochs 2023/04/25 15:02:57 - mmengine - INFO - Epoch(val) [7][ 50/509] eta: 0:01:53 time: 0.2479 data_time: 0.0060 memory: 3201 2023/04/25 15:03:08 - mmengine - INFO - Epoch(val) [7][100/509] eta: 0:01:38 time: 0.2332 data_time: 0.0054 memory: 840 2023/04/25 15:03:20 - mmengine - INFO - Epoch(val) [7][150/509] eta: 0:01:25 time: 0.2305 data_time: 0.0054 memory: 843 2023/04/25 15:03:29 - mmengine - INFO - Epoch(val) [7][200/509] eta: 0:01:08 time: 0.1781 data_time: 0.0051 memory: 834 2023/04/25 15:03:39 - mmengine - INFO - Epoch(val) [7][250/509] eta: 0:00:56 time: 0.2046 data_time: 0.0058 memory: 850 2023/04/25 15:03:48 - mmengine - INFO - Epoch(val) [7][300/509] eta: 0:00:44 time: 0.1772 data_time: 0.0052 memory: 812 2023/04/25 15:03:58 - mmengine - INFO - Epoch(val) [7][350/509] eta: 0:00:33 time: 0.1959 data_time: 0.0057 memory: 825 2023/04/25 15:04:08 - mmengine - INFO - Epoch(val) [7][400/509] eta: 0:00:22 time: 0.2064 data_time: 0.0051 memory: 827 2023/04/25 15:04:21 - mmengine - INFO - Epoch(val) [7][450/509] eta: 0:00:12 time: 0.2541 data_time: 0.0057 memory: 845 2023/04/25 15:04:38 - mmengine - INFO - Epoch(val) [7][500/509] eta: 0:00:02 time: 0.3499 data_time: 0.0048 memory: 832 2023/04/25 15:05:15 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9607 | 0.4783 | 0.6566 | 0.6696 | 0.6306 | 0.7161 | 0.7956 | 0.0020 | 0.9262 | 0.4268 | 0.8106 | 0.0477 | 0.9020 | 0.6353 | 0.8772 | 0.6627 | 0.7326 | 0.6474 | 0.5048 | 0.6359 | 0.9168 | 0.7219 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 15:05:15 - mmengine - INFO - Epoch(val) [7][509/509] car: 0.9607 bicycle: 0.4783 motorcycle: 0.6566 truck: 0.6696 bus: 0.6306 person: 0.7161 bicyclist: 0.7956 motorcyclist: 0.0020 road: 0.9262 parking: 0.4268 sidewalk: 0.8106 other-ground: 0.0477 building: 0.9020 fence: 0.6353 vegetation: 0.8772 trunck: 0.6627 terrian: 0.7326 pole: 0.6474 traffic-sign: 0.5048 miou: 0.6359 acc: 0.9168 acc_cls: 0.7219 data_time: 0.0046 time: 0.3589 2023/04/25 15:05:55 - mmengine - INFO - Epoch(train) [8][ 50/1196] lr: 8.0000e-03 eta: 7:32:00 time: 0.8036 data_time: 0.0044 memory: 3145 grad_norm: 0.1445 loss: 0.2668 loss_sem_seg: 0.2668 2023/04/25 15:06:33 - mmengine - INFO - Epoch(train) [8][ 100/1196] lr: 8.0000e-03 eta: 7:31:16 time: 0.7557 data_time: 0.0033 memory: 3256 grad_norm: 0.1331 loss: 0.2631 loss_sem_seg: 0.2631 2023/04/25 15:07:13 - mmengine - INFO - Epoch(train) [8][ 150/1196] lr: 8.0000e-03 eta: 7:30:41 time: 0.8058 data_time: 0.0035 memory: 3422 grad_norm: 0.1341 loss: 0.2751 loss_sem_seg: 0.2751 2023/04/25 15:07:53 - mmengine - INFO - Epoch(train) [8][ 200/1196] lr: 8.0000e-03 eta: 7:30:08 time: 0.8131 data_time: 0.0035 memory: 3166 grad_norm: 0.1320 loss: 0.2354 loss_sem_seg: 0.2354 2023/04/25 15:08:33 - mmengine - INFO - Epoch(train) [8][ 250/1196] lr: 8.0000e-03 eta: 7:29:32 time: 0.7996 data_time: 0.0033 memory: 3236 grad_norm: 0.1374 loss: 0.2599 loss_sem_seg: 0.2599 2023/04/25 15:09:13 - mmengine - INFO - Epoch(train) [8][ 300/1196] lr: 8.0000e-03 eta: 7:28:57 time: 0.8013 data_time: 0.0034 memory: 3194 grad_norm: 0.1408 loss: 0.2700 loss_sem_seg: 0.2700 2023/04/25 15:09:55 - mmengine - INFO - Epoch(train) [8][ 350/1196] lr: 8.0000e-03 eta: 7:28:25 time: 0.8211 data_time: 0.0034 memory: 3051 grad_norm: 0.1294 loss: 0.2586 loss_sem_seg: 0.2586 2023/04/25 15:10:34 - mmengine - INFO - Epoch(train) [8][ 400/1196] lr: 8.0000e-03 eta: 7:27:46 time: 0.7867 data_time: 0.0035 memory: 3177 grad_norm: 0.1302 loss: 0.2655 loss_sem_seg: 0.2655 2023/04/25 15:11:14 - mmengine - INFO - Epoch(train) [8][ 450/1196] lr: 8.0000e-03 eta: 7:27:10 time: 0.7977 data_time: 0.0034 memory: 3541 grad_norm: 0.1490 loss: 0.2611 loss_sem_seg: 0.2611 2023/04/25 15:11:55 - mmengine - INFO - Epoch(train) [8][ 500/1196] lr: 8.0000e-03 eta: 7:26:38 time: 0.8227 data_time: 0.0034 memory: 3361 grad_norm: 0.1268 loss: 0.2505 loss_sem_seg: 0.2505 2023/04/25 15:12:35 - mmengine - INFO - Epoch(train) [8][ 550/1196] lr: 8.0000e-03 eta: 7:26:02 time: 0.7991 data_time: 0.0033 memory: 3408 grad_norm: 0.1183 loss: 0.2486 loss_sem_seg: 0.2486 2023/04/25 15:13:16 - mmengine - INFO - Epoch(train) [8][ 600/1196] lr: 8.0000e-03 eta: 7:25:31 time: 0.8307 data_time: 0.0035 memory: 3509 grad_norm: 0.1274 loss: 0.2490 loss_sem_seg: 0.2490 2023/04/25 15:13:39 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 15:13:58 - mmengine - INFO - Epoch(train) [8][ 650/1196] lr: 8.0000e-03 eta: 7:25:01 time: 0.8283 data_time: 0.0035 memory: 3320 grad_norm: 0.1338 loss: 0.2648 loss_sem_seg: 0.2648 2023/04/25 15:14:37 - mmengine - INFO - Epoch(train) [8][ 700/1196] lr: 8.0000e-03 eta: 7:24:21 time: 0.7836 data_time: 0.0034 memory: 3196 grad_norm: 0.1347 loss: 0.2384 loss_sem_seg: 0.2384 2023/04/25 15:15:17 - mmengine - INFO - Epoch(train) [8][ 750/1196] lr: 8.0000e-03 eta: 7:23:43 time: 0.7899 data_time: 0.0035 memory: 3307 grad_norm: 0.1284 loss: 0.2432 loss_sem_seg: 0.2432 2023/04/25 15:15:56 - mmengine - INFO - Epoch(train) [8][ 800/1196] lr: 8.0000e-03 eta: 7:23:06 time: 0.7989 data_time: 0.0035 memory: 3691 grad_norm: 0.1359 loss: 0.2441 loss_sem_seg: 0.2441 2023/04/25 15:16:35 - mmengine - INFO - Epoch(train) [8][ 850/1196] lr: 8.0000e-03 eta: 7:22:26 time: 0.7775 data_time: 0.0034 memory: 3178 grad_norm: 0.1375 loss: 0.2671 loss_sem_seg: 0.2671 2023/04/25 15:17:17 - mmengine - INFO - Epoch(train) [8][ 900/1196] lr: 8.0000e-03 eta: 7:21:54 time: 0.8279 data_time: 0.0033 memory: 3387 grad_norm: 0.1270 loss: 0.2443 loss_sem_seg: 0.2443 2023/04/25 15:17:56 - mmengine - INFO - Epoch(train) [8][ 950/1196] lr: 8.0000e-03 eta: 7:21:14 time: 0.7804 data_time: 0.0034 memory: 3151 grad_norm: 0.1354 loss: 0.2553 loss_sem_seg: 0.2553 2023/04/25 15:18:35 - mmengine - INFO - Epoch(train) [8][1000/1196] lr: 8.0000e-03 eta: 7:20:37 time: 0.7942 data_time: 0.0036 memory: 3217 grad_norm: 0.1164 loss: 0.2450 loss_sem_seg: 0.2450 2023/04/25 15:19:17 - mmengine - INFO - Epoch(train) [8][1050/1196] lr: 8.0000e-03 eta: 7:20:06 time: 0.8305 data_time: 0.0035 memory: 3258 grad_norm: 0.1402 loss: 0.2436 loss_sem_seg: 0.2436 2023/04/25 15:19:56 - mmengine - INFO - Epoch(train) [8][1100/1196] lr: 8.0000e-03 eta: 7:19:27 time: 0.7889 data_time: 0.0036 memory: 3256 grad_norm: 0.1412 loss: 0.2788 loss_sem_seg: 0.2788 2023/04/25 15:20:37 - mmengine - INFO - Epoch(train) [8][1150/1196] lr: 8.0000e-03 eta: 7:18:51 time: 0.8055 data_time: 0.0036 memory: 3139 grad_norm: 0.1244 loss: 0.2445 loss_sem_seg: 0.2445 2023/04/25 15:21:13 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 15:21:13 - mmengine - INFO - Saving checkpoint at 8 epochs 2023/04/25 15:21:27 - mmengine - INFO - Epoch(val) [8][ 50/509] eta: 0:01:26 time: 0.1886 data_time: 0.0050 memory: 3290 2023/04/25 15:21:38 - mmengine - INFO - Epoch(val) [8][100/509] eta: 0:01:24 time: 0.2251 data_time: 0.0051 memory: 840 2023/04/25 15:21:47 - mmengine - INFO - Epoch(val) [8][150/509] eta: 0:01:12 time: 0.1889 data_time: 0.0050 memory: 843 2023/04/25 15:21:59 - mmengine - INFO - Epoch(val) [8][200/509] eta: 0:01:04 time: 0.2288 data_time: 0.0056 memory: 834 2023/04/25 15:22:09 - mmengine - INFO - Epoch(val) [8][250/509] eta: 0:00:53 time: 0.1974 data_time: 0.0054 memory: 850 2023/04/25 15:22:18 - mmengine - INFO - Epoch(val) [8][300/509] eta: 0:00:42 time: 0.1835 data_time: 0.0053 memory: 812 2023/04/25 15:22:28 - mmengine - INFO - Epoch(val) [8][350/509] eta: 0:00:32 time: 0.2123 data_time: 0.0054 memory: 825 2023/04/25 15:22:38 - mmengine - INFO - Epoch(val) [8][400/509] eta: 0:00:22 time: 0.1995 data_time: 0.0050 memory: 827 2023/04/25 15:22:53 - mmengine - INFO - Epoch(val) [8][450/509] eta: 0:00:12 time: 0.2915 data_time: 0.0051 memory: 845 2023/04/25 15:23:11 - mmengine - INFO - Epoch(val) [8][500/509] eta: 0:00:02 time: 0.3622 data_time: 0.0045 memory: 832 2023/04/25 15:23:48 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9644 | 0.4438 | 0.6822 | 0.4026 | 0.6212 | 0.6805 | 0.7652 | 0.0911 | 0.9337 | 0.3459 | 0.8112 | 0.0800 | 0.9008 | 0.5704 | 0.8904 | 0.6555 | 0.7785 | 0.6480 | 0.4818 | 0.6183 | 0.9216 | 0.7099 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 15:23:48 - mmengine - INFO - Epoch(val) [8][509/509] car: 0.9644 bicycle: 0.4438 motorcycle: 0.6822 truck: 0.4026 bus: 0.6212 person: 0.6805 bicyclist: 0.7652 motorcyclist: 0.0911 road: 0.9337 parking: 0.3459 sidewalk: 0.8112 other-ground: 0.0800 building: 0.9008 fence: 0.5704 vegetation: 0.8904 trunck: 0.6555 terrian: 0.7785 pole: 0.6480 traffic-sign: 0.4818 miou: 0.6183 acc: 0.9216 acc_cls: 0.7099 data_time: 0.0044 time: 0.3875 2023/04/25 15:24:28 - mmengine - INFO - Epoch(train) [9][ 50/1196] lr: 8.0000e-03 eta: 7:17:38 time: 0.7928 data_time: 0.0044 memory: 3291 grad_norm: 0.1310 loss: 0.2657 loss_sem_seg: 0.2657 2023/04/25 15:25:08 - mmengine - INFO - Epoch(train) [9][ 100/1196] lr: 8.0000e-03 eta: 7:17:01 time: 0.8009 data_time: 0.0035 memory: 3393 grad_norm: inf loss: 0.2626 loss_sem_seg: 0.2626 2023/04/25 15:25:47 - mmengine - INFO - Epoch(train) [9][ 150/1196] lr: 8.0000e-03 eta: 7:16:20 time: 0.7774 data_time: 0.0034 memory: 3175 grad_norm: 0.1372 loss: 0.2592 loss_sem_seg: 0.2592 2023/04/25 15:26:27 - mmengine - INFO - Epoch(train) [9][ 200/1196] lr: 8.0000e-03 eta: 7:15:43 time: 0.7956 data_time: 0.0033 memory: 3310 grad_norm: 0.1223 loss: 0.2678 loss_sem_seg: 0.2678 2023/04/25 15:27:07 - mmengine - INFO - Epoch(train) [9][ 250/1196] lr: 8.0000e-03 eta: 7:15:07 time: 0.8039 data_time: 0.0034 memory: 3318 grad_norm: 0.1178 loss: 0.2394 loss_sem_seg: 0.2394 2023/04/25 15:27:46 - mmengine - INFO - Epoch(train) [9][ 300/1196] lr: 8.0000e-03 eta: 7:14:28 time: 0.7890 data_time: 0.0035 memory: 3268 grad_norm: 0.1251 loss: 0.2596 loss_sem_seg: 0.2596 2023/04/25 15:28:27 - mmengine - INFO - Epoch(train) [9][ 350/1196] lr: 8.0000e-03 eta: 7:13:53 time: 0.8075 data_time: 0.0034 memory: 3210 grad_norm: 0.1247 loss: 0.2606 loss_sem_seg: 0.2606 2023/04/25 15:29:06 - mmengine - INFO - Epoch(train) [9][ 400/1196] lr: 8.0000e-03 eta: 7:13:13 time: 0.7857 data_time: 0.0035 memory: 3050 grad_norm: 0.1185 loss: 0.2554 loss_sem_seg: 0.2554 2023/04/25 15:29:32 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 15:29:47 - mmengine - INFO - Epoch(train) [9][ 450/1196] lr: 8.0000e-03 eta: 7:12:40 time: 0.8199 data_time: 0.0035 memory: 3256 grad_norm: 0.1143 loss: 0.2631 loss_sem_seg: 0.2631 2023/04/25 15:30:28 - mmengine - INFO - Epoch(train) [9][ 500/1196] lr: 8.0000e-03 eta: 7:12:05 time: 0.8145 data_time: 0.0033 memory: 3197 grad_norm: 0.1349 loss: 0.2363 loss_sem_seg: 0.2363 2023/04/25 15:31:06 - mmengine - INFO - Epoch(train) [9][ 550/1196] lr: 8.0000e-03 eta: 7:11:21 time: 0.7587 data_time: 0.0034 memory: 3288 grad_norm: 0.1509 loss: 0.2634 loss_sem_seg: 0.2634 2023/04/25 15:31:47 - mmengine - INFO - Epoch(train) [9][ 600/1196] lr: 8.0000e-03 eta: 7:10:50 time: 0.8359 data_time: 0.0036 memory: 3249 grad_norm: 0.1299 loss: 0.2478 loss_sem_seg: 0.2478 2023/04/25 15:32:26 - mmengine - INFO - Epoch(train) [9][ 650/1196] lr: 8.0000e-03 eta: 7:10:09 time: 0.7727 data_time: 0.0034 memory: 3233 grad_norm: 0.1346 loss: 0.2512 loss_sem_seg: 0.2512 2023/04/25 15:33:06 - mmengine - INFO - Epoch(train) [9][ 700/1196] lr: 8.0000e-03 eta: 7:09:33 time: 0.8060 data_time: 0.0034 memory: 3428 grad_norm: 0.1272 loss: 0.2581 loss_sem_seg: 0.2581 2023/04/25 15:33:45 - mmengine - INFO - Epoch(train) [9][ 750/1196] lr: 8.0000e-03 eta: 7:08:52 time: 0.7769 data_time: 0.0034 memory: 3372 grad_norm: 0.1350 loss: 0.2469 loss_sem_seg: 0.2469 2023/04/25 15:34:25 - mmengine - INFO - Epoch(train) [9][ 800/1196] lr: 8.0000e-03 eta: 7:08:15 time: 0.7990 data_time: 0.0035 memory: 3263 grad_norm: 0.1261 loss: 0.2477 loss_sem_seg: 0.2477 2023/04/25 15:35:04 - mmengine - INFO - Epoch(train) [9][ 850/1196] lr: 8.0000e-03 eta: 7:07:34 time: 0.7770 data_time: 0.0033 memory: 3250 grad_norm: 0.1242 loss: 0.2467 loss_sem_seg: 0.2467 2023/04/25 15:35:44 - mmengine - INFO - Epoch(train) [9][ 900/1196] lr: 8.0000e-03 eta: 7:06:57 time: 0.7986 data_time: 0.0034 memory: 3159 grad_norm: 0.1197 loss: 0.2433 loss_sem_seg: 0.2433 2023/04/25 15:36:24 - mmengine - INFO - Epoch(train) [9][ 950/1196] lr: 8.0000e-03 eta: 7:06:20 time: 0.8039 data_time: 0.0035 memory: 3197 grad_norm: 0.1241 loss: 0.2517 loss_sem_seg: 0.2517 2023/04/25 15:37:05 - mmengine - INFO - Epoch(train) [9][1000/1196] lr: 8.0000e-03 eta: 7:05:45 time: 0.8170 data_time: 0.0035 memory: 3191 grad_norm: 0.1102 loss: 0.2345 loss_sem_seg: 0.2345 2023/04/25 15:37:44 - mmengine - INFO - Epoch(train) [9][1050/1196] lr: 8.0000e-03 eta: 7:05:04 time: 0.7746 data_time: 0.0035 memory: 3315 grad_norm: 0.1320 loss: 0.2590 loss_sem_seg: 0.2590 2023/04/25 15:38:24 - mmengine - INFO - Epoch(train) [9][1100/1196] lr: 8.0000e-03 eta: 7:04:29 time: 0.8150 data_time: 0.0034 memory: 3335 grad_norm: 0.1392 loss: 0.2429 loss_sem_seg: 0.2429 2023/04/25 15:39:04 - mmengine - INFO - Epoch(train) [9][1150/1196] lr: 8.0000e-03 eta: 7:03:52 time: 0.7991 data_time: 0.0033 memory: 3217 grad_norm: 0.1235 loss: 0.2791 loss_sem_seg: 0.2791 2023/04/25 15:39:42 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 15:39:42 - mmengine - INFO - Saving checkpoint at 9 epochs 2023/04/25 15:39:57 - mmengine - INFO - Epoch(val) [9][ 50/509] eta: 0:01:35 time: 0.2085 data_time: 0.0050 memory: 3124 2023/04/25 15:40:08 - mmengine - INFO - Epoch(val) [9][100/509] eta: 0:01:28 time: 0.2255 data_time: 0.0050 memory: 840 2023/04/25 15:40:20 - mmengine - INFO - Epoch(val) [9][150/509] eta: 0:01:19 time: 0.2330 data_time: 0.0049 memory: 843 2023/04/25 15:40:29 - mmengine - INFO - Epoch(val) [9][200/509] eta: 0:01:06 time: 0.1944 data_time: 0.0049 memory: 834 2023/04/25 15:40:38 - mmengine - INFO - Epoch(val) [9][250/509] eta: 0:00:53 time: 0.1796 data_time: 0.0048 memory: 850 2023/04/25 15:40:48 - mmengine - INFO - Epoch(val) [9][300/509] eta: 0:00:42 time: 0.1925 data_time: 0.0048 memory: 812 2023/04/25 15:40:58 - mmengine - INFO - Epoch(val) [9][350/509] eta: 0:00:32 time: 0.1986 data_time: 0.0047 memory: 825 2023/04/25 15:41:09 - mmengine - INFO - Epoch(val) [9][400/509] eta: 0:00:22 time: 0.2264 data_time: 0.0046 memory: 827 2023/04/25 15:41:21 - mmengine - INFO - Epoch(val) [9][450/509] eta: 0:00:12 time: 0.2425 data_time: 0.0048 memory: 845 2023/04/25 15:41:39 - mmengine - INFO - Epoch(val) [9][500/509] eta: 0:00:02 time: 0.3549 data_time: 0.0046 memory: 832 2023/04/25 15:42:12 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9584 | 0.4804 | 0.7216 | 0.6888 | 0.5707 | 0.7143 | 0.8338 | 0.0891 | 0.9318 | 0.3910 | 0.7999 | 0.0122 | 0.9001 | 0.6059 | 0.8982 | 0.6835 | 0.7885 | 0.6535 | 0.5173 | 0.6442 | 0.9235 | 0.7229 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 15:42:12 - mmengine - INFO - Epoch(val) [9][509/509] car: 0.9584 bicycle: 0.4804 motorcycle: 0.7216 truck: 0.6888 bus: 0.5707 person: 0.7143 bicyclist: 0.8338 motorcyclist: 0.0891 road: 0.9318 parking: 0.3910 sidewalk: 0.7999 other-ground: 0.0122 building: 0.9001 fence: 0.6059 vegetation: 0.8982 trunck: 0.6835 terrian: 0.7885 pole: 0.6535 traffic-sign: 0.5173 miou: 0.6442 acc: 0.9235 acc_cls: 0.7229 data_time: 0.0045 time: 0.3830 2023/04/25 15:42:53 - mmengine - INFO - Epoch(train) [10][ 50/1196] lr: 8.0000e-03 eta: 7:02:44 time: 0.8051 data_time: 0.0044 memory: 3145 grad_norm: 0.1196 loss: 0.2442 loss_sem_seg: 0.2442 2023/04/25 15:43:34 - mmengine - INFO - Epoch(train) [10][ 100/1196] lr: 8.0000e-03 eta: 7:02:12 time: 0.8365 data_time: 0.0033 memory: 3145 grad_norm: 0.1358 loss: 0.2573 loss_sem_seg: 0.2573 2023/04/25 15:44:14 - mmengine - INFO - Epoch(train) [10][ 150/1196] lr: 8.0000e-03 eta: 7:01:32 time: 0.7825 data_time: 0.0036 memory: 3156 grad_norm: 0.1297 loss: 0.2591 loss_sem_seg: 0.2591 2023/04/25 15:44:54 - mmengine - INFO - Epoch(train) [10][ 200/1196] lr: 8.0000e-03 eta: 7:00:55 time: 0.8016 data_time: 0.0034 memory: 3385 grad_norm: 0.1251 loss: 0.2562 loss_sem_seg: 0.2562 2023/04/25 15:45:23 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 15:45:35 - mmengine - INFO - Epoch(train) [10][ 250/1196] lr: 8.0000e-03 eta: 7:00:20 time: 0.8169 data_time: 0.0035 memory: 3326 grad_norm: 0.1108 loss: 0.2306 loss_sem_seg: 0.2306 2023/04/25 15:46:13 - mmengine - INFO - Epoch(train) [10][ 300/1196] lr: 8.0000e-03 eta: 6:59:38 time: 0.7718 data_time: 0.0034 memory: 3287 grad_norm: 0.1079 loss: 0.2414 loss_sem_seg: 0.2414 2023/04/25 15:46:54 - mmengine - INFO - Epoch(train) [10][ 350/1196] lr: 8.0000e-03 eta: 6:59:02 time: 0.8105 data_time: 0.0036 memory: 3200 grad_norm: 0.1157 loss: 0.2558 loss_sem_seg: 0.2558 2023/04/25 15:47:34 - mmengine - INFO - Epoch(train) [10][ 400/1196] lr: 8.0000e-03 eta: 6:58:26 time: 0.8109 data_time: 0.0033 memory: 3309 grad_norm: 0.1176 loss: 0.2413 loss_sem_seg: 0.2413 2023/04/25 15:48:13 - mmengine - INFO - Epoch(train) [10][ 450/1196] lr: 8.0000e-03 eta: 6:57:46 time: 0.7836 data_time: 0.0034 memory: 3085 grad_norm: 0.1160 loss: 0.2448 loss_sem_seg: 0.2448 2023/04/25 15:48:54 - mmengine - INFO - Epoch(train) [10][ 500/1196] lr: 8.0000e-03 eta: 6:57:11 time: 0.8156 data_time: 0.0035 memory: 3204 grad_norm: 0.1261 loss: 0.2428 loss_sem_seg: 0.2428 2023/04/25 15:49:32 - mmengine - INFO - Epoch(train) [10][ 550/1196] lr: 8.0000e-03 eta: 6:56:28 time: 0.7593 data_time: 0.0035 memory: 3050 grad_norm: 0.1277 loss: 0.2476 loss_sem_seg: 0.2476 2023/04/25 15:50:13 - mmengine - INFO - Epoch(train) [10][ 600/1196] lr: 8.0000e-03 eta: 6:55:51 time: 0.8088 data_time: 0.0034 memory: 3142 grad_norm: 0.1198 loss: 0.2460 loss_sem_seg: 0.2460 2023/04/25 15:50:53 - mmengine - INFO - Epoch(train) [10][ 650/1196] lr: 8.0000e-03 eta: 6:55:14 time: 0.7995 data_time: 0.0034 memory: 3341 grad_norm: 0.1230 loss: 0.2416 loss_sem_seg: 0.2416 2023/04/25 15:51:33 - mmengine - INFO - Epoch(train) [10][ 700/1196] lr: 8.0000e-03 eta: 6:54:37 time: 0.8073 data_time: 0.0035 memory: 3758 grad_norm: 0.1217 loss: 0.2299 loss_sem_seg: 0.2299 2023/04/25 15:52:14 - mmengine - INFO - Epoch(train) [10][ 750/1196] lr: 8.0000e-03 eta: 6:54:02 time: 0.8209 data_time: 0.0037 memory: 3074 grad_norm: 0.1125 loss: 0.2525 loss_sem_seg: 0.2525 2023/04/25 15:52:55 - mmengine - INFO - Epoch(train) [10][ 800/1196] lr: 8.0000e-03 eta: 6:53:26 time: 0.8123 data_time: 0.0036 memory: 3325 grad_norm: 0.1069 loss: 0.2388 loss_sem_seg: 0.2388 2023/04/25 15:53:34 - mmengine - INFO - Epoch(train) [10][ 850/1196] lr: 8.0000e-03 eta: 6:52:48 time: 0.7972 data_time: 0.0036 memory: 3079 grad_norm: 0.1229 loss: 0.2374 loss_sem_seg: 0.2374 2023/04/25 15:54:15 - mmengine - INFO - Epoch(train) [10][ 900/1196] lr: 8.0000e-03 eta: 6:52:11 time: 0.8022 data_time: 0.0038 memory: 3193 grad_norm: 0.1119 loss: 0.2411 loss_sem_seg: 0.2411 2023/04/25 15:54:54 - mmengine - INFO - Epoch(train) [10][ 950/1196] lr: 8.0000e-03 eta: 6:51:31 time: 0.7861 data_time: 0.0034 memory: 3421 grad_norm: 0.1168 loss: 0.2270 loss_sem_seg: 0.2270 2023/04/25 15:55:32 - mmengine - INFO - Epoch(train) [10][1000/1196] lr: 8.0000e-03 eta: 6:50:48 time: 0.7586 data_time: 0.0037 memory: 3191 grad_norm: 0.1077 loss: 0.2459 loss_sem_seg: 0.2459 2023/04/25 15:56:12 - mmengine - INFO - Epoch(train) [10][1050/1196] lr: 8.0000e-03 eta: 6:50:11 time: 0.8061 data_time: 0.0034 memory: 3217 grad_norm: 0.1132 loss: 0.2401 loss_sem_seg: 0.2401 2023/04/25 15:56:52 - mmengine - INFO - Epoch(train) [10][1100/1196] lr: 8.0000e-03 eta: 6:49:33 time: 0.8012 data_time: 0.0033 memory: 3133 grad_norm: 0.1190 loss: 0.2417 loss_sem_seg: 0.2417 2023/04/25 15:57:31 - mmengine - INFO - Epoch(train) [10][1150/1196] lr: 8.0000e-03 eta: 6:48:53 time: 0.7834 data_time: 0.0034 memory: 3107 grad_norm: 0.1185 loss: 0.2429 loss_sem_seg: 0.2429 2023/04/25 15:58:08 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 15:58:08 - mmengine - INFO - Saving checkpoint at 10 epochs 2023/04/25 15:58:24 - mmengine - INFO - Epoch(val) [10][ 50/509] eta: 0:01:45 time: 0.2291 data_time: 0.0051 memory: 3359 2023/04/25 15:58:35 - mmengine - INFO - Epoch(val) [10][100/509] eta: 0:01:33 time: 0.2296 data_time: 0.0045 memory: 840 2023/04/25 15:58:47 - mmengine - INFO - Epoch(val) [10][150/509] eta: 0:01:21 time: 0.2265 data_time: 0.0049 memory: 843 2023/04/25 15:58:58 - mmengine - INFO - Epoch(val) [10][200/509] eta: 0:01:10 time: 0.2267 data_time: 0.0049 memory: 834 2023/04/25 15:59:07 - mmengine - INFO - Epoch(val) [10][250/509] eta: 0:00:57 time: 0.1889 data_time: 0.0047 memory: 850 2023/04/25 15:59:18 - mmengine - INFO - Epoch(val) [10][300/509] eta: 0:00:45 time: 0.2088 data_time: 0.0049 memory: 812 2023/04/25 15:59:29 - mmengine - INFO - Epoch(val) [10][350/509] eta: 0:00:34 time: 0.2173 data_time: 0.0049 memory: 825 2023/04/25 15:59:40 - mmengine - INFO - Epoch(val) [10][400/509] eta: 0:00:23 time: 0.2293 data_time: 0.0049 memory: 827 2023/04/25 15:59:49 - mmengine - INFO - Epoch(val) [10][450/509] eta: 0:00:12 time: 0.1772 data_time: 0.0048 memory: 845 2023/04/25 16:00:05 - mmengine - INFO - Epoch(val) [10][500/509] eta: 0:00:02 time: 0.3087 data_time: 0.0045 memory: 832 2023/04/25 16:00:42 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9636 | 0.4638 | 0.7088 | 0.8051 | 0.6347 | 0.7086 | 0.8292 | 0.0180 | 0.9358 | 0.4254 | 0.8098 | 0.0606 | 0.9051 | 0.6285 | 0.8946 | 0.6826 | 0.7772 | 0.6604 | 0.5020 | 0.6534 | 0.9244 | 0.7196 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 16:00:42 - mmengine - INFO - Epoch(val) [10][509/509] car: 0.9636 bicycle: 0.4638 motorcycle: 0.7088 truck: 0.8051 bus: 0.6347 person: 0.7086 bicyclist: 0.8292 motorcyclist: 0.0180 road: 0.9358 parking: 0.4254 sidewalk: 0.8098 other-ground: 0.0606 building: 0.9051 fence: 0.6285 vegetation: 0.8946 trunck: 0.6826 terrian: 0.7772 pole: 0.6604 traffic-sign: 0.5020 miou: 0.6534 acc: 0.9244 acc_cls: 0.7196 data_time: 0.0042 time: 0.3101 2023/04/25 16:01:13 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 16:01:21 - mmengine - INFO - Epoch(train) [11][ 50/1196] lr: 8.0000e-03 eta: 6:47:38 time: 0.7807 data_time: 0.0043 memory: 3058 grad_norm: 0.1122 loss: 0.2250 loss_sem_seg: 0.2250 2023/04/25 16:02:01 - mmengine - INFO - Epoch(train) [11][ 100/1196] lr: 8.0000e-03 eta: 6:47:01 time: 0.8047 data_time: 0.0033 memory: 3239 grad_norm: 0.1144 loss: 0.2455 loss_sem_seg: 0.2455 2023/04/25 16:02:40 - mmengine - INFO - Epoch(train) [11][ 150/1196] lr: 8.0000e-03 eta: 6:46:20 time: 0.7739 data_time: 0.0035 memory: 3051 grad_norm: 0.1143 loss: 0.2496 loss_sem_seg: 0.2496 2023/04/25 16:03:18 - mmengine - INFO - Epoch(train) [11][ 200/1196] lr: 8.0000e-03 eta: 6:45:39 time: 0.7799 data_time: 0.0034 memory: 3299 grad_norm: 0.1232 loss: 0.2402 loss_sem_seg: 0.2402 2023/04/25 16:03:59 - mmengine - INFO - Epoch(train) [11][ 250/1196] lr: 8.0000e-03 eta: 6:45:03 time: 0.8097 data_time: 0.0033 memory: 3277 grad_norm: 0.1241 loss: 0.2293 loss_sem_seg: 0.2293 2023/04/25 16:04:39 - mmengine - INFO - Epoch(train) [11][ 300/1196] lr: 8.0000e-03 eta: 6:44:24 time: 0.7953 data_time: 0.0035 memory: 3188 grad_norm: 0.1241 loss: 0.2533 loss_sem_seg: 0.2533 2023/04/25 16:05:19 - mmengine - INFO - Epoch(train) [11][ 350/1196] lr: 8.0000e-03 eta: 6:43:47 time: 0.8103 data_time: 0.0034 memory: 3313 grad_norm: 0.1177 loss: 0.2249 loss_sem_seg: 0.2249 2023/04/25 16:05:59 - mmengine - INFO - Epoch(train) [11][ 400/1196] lr: 8.0000e-03 eta: 6:43:08 time: 0.7894 data_time: 0.0035 memory: 3149 grad_norm: 0.1091 loss: 0.2326 loss_sem_seg: 0.2326 2023/04/25 16:06:39 - mmengine - INFO - Epoch(train) [11][ 450/1196] lr: 8.0000e-03 eta: 6:42:30 time: 0.7982 data_time: 0.0034 memory: 3286 grad_norm: 0.1138 loss: 0.2284 loss_sem_seg: 0.2284 2023/04/25 16:07:19 - mmengine - INFO - Epoch(train) [11][ 500/1196] lr: 8.0000e-03 eta: 6:41:53 time: 0.8046 data_time: 0.0033 memory: 3010 grad_norm: 0.1137 loss: 0.2496 loss_sem_seg: 0.2496 2023/04/25 16:07:56 - mmengine - INFO - Epoch(train) [11][ 550/1196] lr: 8.0000e-03 eta: 6:41:09 time: 0.7521 data_time: 0.0036 memory: 3311 grad_norm: 0.1110 loss: 0.2250 loss_sem_seg: 0.2250 2023/04/25 16:08:36 - mmengine - INFO - Epoch(train) [11][ 600/1196] lr: 8.0000e-03 eta: 6:40:30 time: 0.7934 data_time: 0.0033 memory: 3248 grad_norm: 0.1113 loss: 0.2352 loss_sem_seg: 0.2352 2023/04/25 16:09:17 - mmengine - INFO - Epoch(train) [11][ 650/1196] lr: 8.0000e-03 eta: 6:39:53 time: 0.8071 data_time: 0.0033 memory: 3110 grad_norm: 0.1088 loss: 0.2355 loss_sem_seg: 0.2355 2023/04/25 16:09:54 - mmengine - INFO - Epoch(train) [11][ 700/1196] lr: 8.0000e-03 eta: 6:39:10 time: 0.7585 data_time: 0.0035 memory: 3491 grad_norm: 0.1288 loss: 0.2360 loss_sem_seg: 0.2360 2023/04/25 16:10:35 - mmengine - INFO - Epoch(train) [11][ 750/1196] lr: 8.0000e-03 eta: 6:38:34 time: 0.8128 data_time: 0.0035 memory: 3185 grad_norm: 0.1166 loss: 0.2446 loss_sem_seg: 0.2446 2023/04/25 16:11:14 - mmengine - INFO - Epoch(train) [11][ 800/1196] lr: 8.0000e-03 eta: 6:37:53 time: 0.7759 data_time: 0.0034 memory: 3643 grad_norm: 0.1085 loss: 0.2316 loss_sem_seg: 0.2316 2023/04/25 16:11:54 - mmengine - INFO - Epoch(train) [11][ 850/1196] lr: 8.0000e-03 eta: 6:37:15 time: 0.8000 data_time: 0.0034 memory: 3262 grad_norm: 0.1153 loss: 0.2382 loss_sem_seg: 0.2382 2023/04/25 16:12:34 - mmengine - INFO - Epoch(train) [11][ 900/1196] lr: 8.0000e-03 eta: 6:36:38 time: 0.8094 data_time: 0.0036 memory: 3446 grad_norm: 0.1259 loss: 0.2399 loss_sem_seg: 0.2399 2023/04/25 16:13:12 - mmengine - INFO - Epoch(train) [11][ 950/1196] lr: 8.0000e-03 eta: 6:35:55 time: 0.7601 data_time: 0.0034 memory: 3189 grad_norm: 0.1151 loss: 0.2315 loss_sem_seg: 0.2315 2023/04/25 16:13:53 - mmengine - INFO - Epoch(train) [11][1000/1196] lr: 8.0000e-03 eta: 6:35:18 time: 0.8080 data_time: 0.0036 memory: 3417 grad_norm: 0.1153 loss: 0.2360 loss_sem_seg: 0.2360 2023/04/25 16:14:24 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 16:14:32 - mmengine - INFO - Epoch(train) [11][1050/1196] lr: 8.0000e-03 eta: 6:34:38 time: 0.7812 data_time: 0.0035 memory: 3294 grad_norm: 0.1130 loss: 0.2479 loss_sem_seg: 0.2479 2023/04/25 16:15:12 - mmengine - INFO - Epoch(train) [11][1100/1196] lr: 8.0000e-03 eta: 6:34:00 time: 0.7980 data_time: 0.0034 memory: 3390 grad_norm: 0.1163 loss: 0.2299 loss_sem_seg: 0.2299 2023/04/25 16:15:52 - mmengine - INFO - Epoch(train) [11][1150/1196] lr: 8.0000e-03 eta: 6:33:23 time: 0.8096 data_time: 0.0035 memory: 3284 grad_norm: 0.1312 loss: 0.2554 loss_sem_seg: 0.2554 2023/04/25 16:16:28 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 16:16:28 - mmengine - INFO - Saving checkpoint at 11 epochs 2023/04/25 16:16:44 - mmengine - INFO - Epoch(val) [11][ 50/509] eta: 0:01:45 time: 0.2290 data_time: 0.0049 memory: 3111 2023/04/25 16:16:54 - mmengine - INFO - Epoch(val) [11][100/509] eta: 0:01:30 time: 0.2138 data_time: 0.0044 memory: 840 2023/04/25 16:17:05 - mmengine - INFO - Epoch(val) [11][150/509] eta: 0:01:18 time: 0.2157 data_time: 0.0047 memory: 843 2023/04/25 16:17:16 - mmengine - INFO - Epoch(val) [11][200/509] eta: 0:01:06 time: 0.2083 data_time: 0.0044 memory: 834 2023/04/25 16:17:24 - mmengine - INFO - Epoch(val) [11][250/509] eta: 0:00:53 time: 0.1749 data_time: 0.0047 memory: 850 2023/04/25 16:17:35 - mmengine - INFO - Epoch(val) [11][300/509] eta: 0:00:43 time: 0.2086 data_time: 0.0044 memory: 812 2023/04/25 16:17:44 - mmengine - INFO - Epoch(val) [11][350/509] eta: 0:00:32 time: 0.1886 data_time: 0.0046 memory: 825 2023/04/25 16:17:55 - mmengine - INFO - Epoch(val) [11][400/509] eta: 0:00:22 time: 0.2180 data_time: 0.0044 memory: 827 2023/04/25 16:18:04 - mmengine - INFO - Epoch(val) [11][450/509] eta: 0:00:12 time: 0.1850 data_time: 0.0046 memory: 845 2023/04/25 16:18:20 - mmengine - INFO - Epoch(val) [11][500/509] eta: 0:00:01 time: 0.3160 data_time: 0.0041 memory: 832 2023/04/25 16:18:56 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9554 | 0.5041 | 0.6647 | 0.6336 | 0.5674 | 0.7285 | 0.8574 | 0.0311 | 0.9316 | 0.4522 | 0.8063 | 0.0286 | 0.8892 | 0.5606 | 0.8840 | 0.6514 | 0.7471 | 0.6528 | 0.5208 | 0.6351 | 0.9170 | 0.7304 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 16:18:56 - mmengine - INFO - Epoch(val) [11][509/509] car: 0.9554 bicycle: 0.5041 motorcycle: 0.6647 truck: 0.6336 bus: 0.5674 person: 0.7285 bicyclist: 0.8574 motorcyclist: 0.0311 road: 0.9316 parking: 0.4522 sidewalk: 0.8063 other-ground: 0.0286 building: 0.8892 fence: 0.5606 vegetation: 0.8840 trunck: 0.6514 terrian: 0.7471 pole: 0.6528 traffic-sign: 0.5208 miou: 0.6351 acc: 0.9170 acc_cls: 0.7304 data_time: 0.0040 time: 0.3491 2023/04/25 16:19:37 - mmengine - INFO - Epoch(train) [12][ 50/1196] lr: 8.0000e-03 eta: 6:32:10 time: 0.8182 data_time: 0.0044 memory: 3325 grad_norm: 0.1161 loss: 0.2415 loss_sem_seg: 0.2415 2023/04/25 16:20:16 - mmengine - INFO - Epoch(train) [12][ 100/1196] lr: 8.0000e-03 eta: 6:31:31 time: 0.7958 data_time: 0.0035 memory: 3376 grad_norm: 0.1087 loss: 0.2379 loss_sem_seg: 0.2379 2023/04/25 16:20:56 - mmengine - INFO - Epoch(train) [12][ 150/1196] lr: 8.0000e-03 eta: 6:30:52 time: 0.7875 data_time: 0.0035 memory: 3246 grad_norm: 0.1086 loss: 0.2226 loss_sem_seg: 0.2226 2023/04/25 16:21:35 - mmengine - INFO - Epoch(train) [12][ 200/1196] lr: 8.0000e-03 eta: 6:30:13 time: 0.7927 data_time: 0.0034 memory: 3279 grad_norm: 0.1154 loss: 0.2257 loss_sem_seg: 0.2257 2023/04/25 16:22:15 - mmengine - INFO - Epoch(train) [12][ 250/1196] lr: 8.0000e-03 eta: 6:29:35 time: 0.8014 data_time: 0.0035 memory: 3441 grad_norm: 0.1069 loss: 0.2246 loss_sem_seg: 0.2246 2023/04/25 16:22:55 - mmengine - INFO - Epoch(train) [12][ 300/1196] lr: 8.0000e-03 eta: 6:28:55 time: 0.7824 data_time: 0.0038 memory: 3484 grad_norm: 0.1194 loss: 0.2295 loss_sem_seg: 0.2295 2023/04/25 16:23:34 - mmengine - INFO - Epoch(train) [12][ 350/1196] lr: 8.0000e-03 eta: 6:28:16 time: 0.7918 data_time: 0.0033 memory: 3157 grad_norm: 0.1105 loss: 0.2303 loss_sem_seg: 0.2303 2023/04/25 16:24:15 - mmengine - INFO - Epoch(train) [12][ 400/1196] lr: 8.0000e-03 eta: 6:27:39 time: 0.8113 data_time: 0.0035 memory: 3130 grad_norm: 0.1026 loss: 0.2258 loss_sem_seg: 0.2258 2023/04/25 16:24:55 - mmengine - INFO - Epoch(train) [12][ 450/1196] lr: 8.0000e-03 eta: 6:27:02 time: 0.8159 data_time: 0.0035 memory: 3359 grad_norm: 0.1080 loss: 0.2461 loss_sem_seg: 0.2461 2023/04/25 16:25:36 - mmengine - INFO - Epoch(train) [12][ 500/1196] lr: 8.0000e-03 eta: 6:26:24 time: 0.8023 data_time: 0.0035 memory: 3151 grad_norm: 0.1184 loss: 0.2363 loss_sem_seg: 0.2363 2023/04/25 16:26:14 - mmengine - INFO - Epoch(train) [12][ 550/1196] lr: 8.0000e-03 eta: 6:25:44 time: 0.7765 data_time: 0.0035 memory: 3420 grad_norm: 0.1098 loss: 0.2286 loss_sem_seg: 0.2286 2023/04/25 16:26:55 - mmengine - INFO - Epoch(train) [12][ 600/1196] lr: 8.0000e-03 eta: 6:25:06 time: 0.8081 data_time: 0.0036 memory: 3450 grad_norm: 0.1071 loss: 0.2325 loss_sem_seg: 0.2325 2023/04/25 16:27:36 - mmengine - INFO - Epoch(train) [12][ 650/1196] lr: 8.0000e-03 eta: 6:24:30 time: 0.8156 data_time: 0.0035 memory: 3063 grad_norm: inf loss: 0.2241 loss_sem_seg: 0.2241 2023/04/25 16:28:14 - mmengine - INFO - Epoch(train) [12][ 700/1196] lr: 8.0000e-03 eta: 6:23:49 time: 0.7742 data_time: 0.0037 memory: 3342 grad_norm: 0.1149 loss: 0.2396 loss_sem_seg: 0.2396 2023/04/25 16:28:55 - mmengine - INFO - Epoch(train) [12][ 750/1196] lr: 8.0000e-03 eta: 6:23:11 time: 0.8065 data_time: 0.0036 memory: 3203 grad_norm: 0.0973 loss: 0.2298 loss_sem_seg: 0.2298 2023/04/25 16:29:35 - mmengine - INFO - Epoch(train) [12][ 800/1196] lr: 8.0000e-03 eta: 6:22:34 time: 0.8106 data_time: 0.0034 memory: 3396 grad_norm: 0.0988 loss: 0.2215 loss_sem_seg: 0.2215 2023/04/25 16:30:10 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 16:30:14 - mmengine - INFO - Epoch(train) [12][ 850/1196] lr: 8.0000e-03 eta: 6:21:54 time: 0.7808 data_time: 0.0035 memory: 3398 grad_norm: 0.1138 loss: 0.2402 loss_sem_seg: 0.2402 2023/04/25 16:30:55 - mmengine - INFO - Epoch(train) [12][ 900/1196] lr: 8.0000e-03 eta: 6:21:18 time: 0.8192 data_time: 0.0034 memory: 3671 grad_norm: inf loss: 0.2325 loss_sem_seg: 0.2325 2023/04/25 16:31:33 - mmengine - INFO - Epoch(train) [12][ 950/1196] lr: 8.0000e-03 eta: 6:20:35 time: 0.7610 data_time: 0.0034 memory: 3335 grad_norm: 0.1241 loss: 0.2398 loss_sem_seg: 0.2398 2023/04/25 16:32:14 - mmengine - INFO - Epoch(train) [12][1000/1196] lr: 8.0000e-03 eta: 6:19:58 time: 0.8081 data_time: 0.0034 memory: 3428 grad_norm: 0.1055 loss: 0.2181 loss_sem_seg: 0.2181 2023/04/25 16:32:55 - mmengine - INFO - Epoch(train) [12][1050/1196] lr: 8.0000e-03 eta: 6:19:21 time: 0.8202 data_time: 0.0033 memory: 3093 grad_norm: 0.1226 loss: 0.2299 loss_sem_seg: 0.2299 2023/04/25 16:33:35 - mmengine - INFO - Epoch(train) [12][1100/1196] lr: 8.0000e-03 eta: 6:18:43 time: 0.8019 data_time: 0.0034 memory: 3126 grad_norm: 0.0928 loss: 0.2111 loss_sem_seg: 0.2111 2023/04/25 16:34:15 - mmengine - INFO - Epoch(train) [12][1150/1196] lr: 8.0000e-03 eta: 6:18:06 time: 0.8103 data_time: 0.0036 memory: 3139 grad_norm: 0.1179 loss: 0.2318 loss_sem_seg: 0.2318 2023/04/25 16:34:51 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 16:34:51 - mmengine - INFO - Saving checkpoint at 12 epochs 2023/04/25 16:35:05 - mmengine - INFO - Epoch(val) [12][ 50/509] eta: 0:01:25 time: 0.1873 data_time: 0.0054 memory: 3566 2023/04/25 16:35:14 - mmengine - INFO - Epoch(val) [12][100/509] eta: 0:01:15 time: 0.1840 data_time: 0.0050 memory: 840 2023/04/25 16:35:23 - mmengine - INFO - Epoch(val) [12][150/509] eta: 0:01:07 time: 0.1945 data_time: 0.0053 memory: 843 2023/04/25 16:35:34 - mmengine - INFO - Epoch(val) [12][200/509] eta: 0:01:00 time: 0.2199 data_time: 0.0051 memory: 834 2023/04/25 16:35:46 - mmengine - INFO - Epoch(val) [12][250/509] eta: 0:00:52 time: 0.2250 data_time: 0.0051 memory: 850 2023/04/25 16:35:56 - mmengine - INFO - Epoch(val) [12][300/509] eta: 0:00:42 time: 0.1970 data_time: 0.0048 memory: 812 2023/04/25 16:36:06 - mmengine - INFO - Epoch(val) [12][350/509] eta: 0:00:32 time: 0.2117 data_time: 0.0052 memory: 825 2023/04/25 16:36:18 - mmengine - INFO - Epoch(val) [12][400/509] eta: 0:00:22 time: 0.2449 data_time: 0.0051 memory: 827 2023/04/25 16:36:31 - mmengine - INFO - Epoch(val) [12][450/509] eta: 0:00:12 time: 0.2450 data_time: 0.0051 memory: 845 2023/04/25 16:36:48 - mmengine - INFO - Epoch(val) [12][500/509] eta: 0:00:02 time: 0.3394 data_time: 0.0043 memory: 832 2023/04/25 16:37:19 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9670 | 0.4518 | 0.7732 | 0.6412 | 0.6498 | 0.7282 | 0.8620 | 0.0461 | 0.9366 | 0.4436 | 0.8096 | 0.0897 | 0.9016 | 0.6423 | 0.8893 | 0.6552 | 0.7659 | 0.6542 | 0.4756 | 0.6517 | 0.9230 | 0.7166 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 16:37:19 - mmengine - INFO - Epoch(val) [12][509/509] car: 0.9670 bicycle: 0.4518 motorcycle: 0.7732 truck: 0.6412 bus: 0.6498 person: 0.7282 bicyclist: 0.8620 motorcyclist: 0.0461 road: 0.9366 parking: 0.4436 sidewalk: 0.8096 other-ground: 0.0897 building: 0.9016 fence: 0.6423 vegetation: 0.8893 trunck: 0.6552 terrian: 0.7659 pole: 0.6542 traffic-sign: 0.4756 miou: 0.6517 acc: 0.9230 acc_cls: 0.7166 data_time: 0.0041 time: 0.3846 2023/04/25 16:38:00 - mmengine - INFO - Epoch(train) [13][ 50/1196] lr: 8.0000e-03 eta: 6:16:52 time: 0.8232 data_time: 0.0043 memory: 3221 grad_norm: 0.1077 loss: 0.2386 loss_sem_seg: 0.2386 2023/04/25 16:38:40 - mmengine - INFO - Epoch(train) [13][ 100/1196] lr: 8.0000e-03 eta: 6:16:14 time: 0.7994 data_time: 0.0035 memory: 3068 grad_norm: 0.1075 loss: 0.2190 loss_sem_seg: 0.2190 2023/04/25 16:39:21 - mmengine - INFO - Epoch(train) [13][ 150/1196] lr: 8.0000e-03 eta: 6:15:36 time: 0.8073 data_time: 0.0035 memory: 3259 grad_norm: 0.1103 loss: 0.2550 loss_sem_seg: 0.2550 2023/04/25 16:40:01 - mmengine - INFO - Epoch(train) [13][ 200/1196] lr: 8.0000e-03 eta: 6:14:59 time: 0.8125 data_time: 0.0035 memory: 3352 grad_norm: 0.1086 loss: 0.2216 loss_sem_seg: 0.2216 2023/04/25 16:40:41 - mmengine - INFO - Epoch(train) [13][ 250/1196] lr: 8.0000e-03 eta: 6:14:20 time: 0.7930 data_time: 0.0036 memory: 3130 grad_norm: 0.1026 loss: 0.2231 loss_sem_seg: 0.2231 2023/04/25 16:41:22 - mmengine - INFO - Epoch(train) [13][ 300/1196] lr: 8.0000e-03 eta: 6:13:42 time: 0.8086 data_time: 0.0037 memory: 3480 grad_norm: 0.1063 loss: 0.2232 loss_sem_seg: 0.2232 2023/04/25 16:42:02 - mmengine - INFO - Epoch(train) [13][ 350/1196] lr: 8.0000e-03 eta: 6:13:04 time: 0.8069 data_time: 0.0035 memory: 3420 grad_norm: 0.1155 loss: 0.2155 loss_sem_seg: 0.2155 2023/04/25 16:42:42 - mmengine - INFO - Epoch(train) [13][ 400/1196] lr: 8.0000e-03 eta: 6:12:26 time: 0.7973 data_time: 0.0034 memory: 3236 grad_norm: 0.1072 loss: 0.2361 loss_sem_seg: 0.2361 2023/04/25 16:43:21 - mmengine - INFO - Epoch(train) [13][ 450/1196] lr: 8.0000e-03 eta: 6:11:46 time: 0.7901 data_time: 0.0033 memory: 3097 grad_norm: 0.1116 loss: 0.2381 loss_sem_seg: 0.2381 2023/04/25 16:44:01 - mmengine - INFO - Epoch(train) [13][ 500/1196] lr: 8.0000e-03 eta: 6:11:07 time: 0.7888 data_time: 0.0035 memory: 3346 grad_norm: 0.1058 loss: 0.2356 loss_sem_seg: 0.2356 2023/04/25 16:44:40 - mmengine - INFO - Epoch(train) [13][ 550/1196] lr: 8.0000e-03 eta: 6:10:27 time: 0.7818 data_time: 0.0035 memory: 3444 grad_norm: 0.1075 loss: 0.2271 loss_sem_seg: 0.2271 2023/04/25 16:45:20 - mmengine - INFO - Epoch(train) [13][ 600/1196] lr: 8.0000e-03 eta: 6:09:49 time: 0.8064 data_time: 0.0034 memory: 3221 grad_norm: 0.1078 loss: 0.2308 loss_sem_seg: 0.2308 2023/04/25 16:45:58 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 16:46:00 - mmengine - INFO - Epoch(train) [13][ 650/1196] lr: 8.0000e-03 eta: 6:09:09 time: 0.7921 data_time: 0.0035 memory: 3165 grad_norm: 0.1063 loss: 0.2311 loss_sem_seg: 0.2311 2023/04/25 16:46:40 - mmengine - INFO - Epoch(train) [13][ 700/1196] lr: 8.0000e-03 eta: 6:08:32 time: 0.8082 data_time: 0.0036 memory: 3097 grad_norm: 0.1192 loss: 0.2304 loss_sem_seg: 0.2304 2023/04/25 16:47:21 - mmengine - INFO - Epoch(train) [13][ 750/1196] lr: 8.0000e-03 eta: 6:07:55 time: 0.8211 data_time: 0.0035 memory: 3176 grad_norm: 0.1015 loss: 0.2406 loss_sem_seg: 0.2406 2023/04/25 16:48:01 - mmengine - INFO - Epoch(train) [13][ 800/1196] lr: 8.0000e-03 eta: 6:07:17 time: 0.8036 data_time: 0.0035 memory: 3250 grad_norm: 0.1054 loss: 0.2448 loss_sem_seg: 0.2448 2023/04/25 16:48:42 - mmengine - INFO - Epoch(train) [13][ 850/1196] lr: 8.0000e-03 eta: 6:06:39 time: 0.8120 data_time: 0.0036 memory: 3396 grad_norm: 0.1116 loss: 0.2129 loss_sem_seg: 0.2129 2023/04/25 16:49:23 - mmengine - INFO - Epoch(train) [13][ 900/1196] lr: 8.0000e-03 eta: 6:06:03 time: 0.8199 data_time: 0.0037 memory: 3226 grad_norm: 0.1026 loss: 0.2386 loss_sem_seg: 0.2386 2023/04/25 16:50:02 - mmengine - INFO - Epoch(train) [13][ 950/1196] lr: 8.0000e-03 eta: 6:05:23 time: 0.7893 data_time: 0.0038 memory: 3267 grad_norm: 0.1200 loss: 0.2436 loss_sem_seg: 0.2436 2023/04/25 16:50:42 - mmengine - INFO - Epoch(train) [13][1000/1196] lr: 8.0000e-03 eta: 6:04:44 time: 0.7961 data_time: 0.0041 memory: 3315 grad_norm: 0.1176 loss: 0.2411 loss_sem_seg: 0.2411 2023/04/25 16:51:23 - mmengine - INFO - Epoch(train) [13][1050/1196] lr: 8.0000e-03 eta: 6:04:07 time: 0.8093 data_time: 0.0039 memory: 3057 grad_norm: 0.1129 loss: 0.2370 loss_sem_seg: 0.2370 2023/04/25 16:52:04 - mmengine - INFO - Epoch(train) [13][1100/1196] lr: 8.0000e-03 eta: 6:03:30 time: 0.8217 data_time: 0.0038 memory: 3125 grad_norm: 0.1182 loss: 0.2315 loss_sem_seg: 0.2315 2023/04/25 16:52:43 - mmengine - INFO - Epoch(train) [13][1150/1196] lr: 8.0000e-03 eta: 6:02:49 time: 0.7791 data_time: 0.0040 memory: 3341 grad_norm: 0.1004 loss: 0.2092 loss_sem_seg: 0.2092 2023/04/25 16:53:20 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 16:53:20 - mmengine - INFO - Saving checkpoint at 13 epochs 2023/04/25 16:53:36 - mmengine - INFO - Epoch(val) [13][ 50/509] eta: 0:01:44 time: 0.2272 data_time: 0.0059 memory: 3141 2023/04/25 16:53:47 - mmengine - INFO - Epoch(val) [13][100/509] eta: 0:01:30 time: 0.2159 data_time: 0.0053 memory: 840 2023/04/25 16:53:58 - mmengine - INFO - Epoch(val) [13][150/509] eta: 0:01:18 time: 0.2163 data_time: 0.0054 memory: 843 2023/04/25 16:54:09 - mmengine - INFO - Epoch(val) [13][200/509] eta: 0:01:08 time: 0.2296 data_time: 0.0055 memory: 834 2023/04/25 16:54:21 - mmengine - INFO - Epoch(val) [13][250/509] eta: 0:00:58 time: 0.2369 data_time: 0.0054 memory: 850 2023/04/25 16:54:32 - mmengine - INFO - Epoch(val) [13][300/509] eta: 0:00:46 time: 0.2107 data_time: 0.0054 memory: 812 2023/04/25 16:54:43 - mmengine - INFO - Epoch(val) [13][350/509] eta: 0:00:35 time: 0.2377 data_time: 0.0056 memory: 825 2023/04/25 16:54:54 - mmengine - INFO - Epoch(val) [13][400/509] eta: 0:00:24 time: 0.2169 data_time: 0.0054 memory: 827 2023/04/25 16:55:09 - mmengine - INFO - Epoch(val) [13][450/509] eta: 0:00:13 time: 0.3019 data_time: 0.0055 memory: 845 2023/04/25 16:55:25 - mmengine - INFO - Epoch(val) [13][500/509] eta: 0:00:02 time: 0.3170 data_time: 0.0049 memory: 832 2023/04/25 16:55:57 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9546 | 0.5176 | 0.6882 | 0.6210 | 0.4334 | 0.7453 | 0.8529 | 0.0711 | 0.9372 | 0.3536 | 0.8053 | 0.0076 | 0.9106 | 0.6321 | 0.8814 | 0.6799 | 0.7402 | 0.6577 | 0.5230 | 0.6322 | 0.9181 | 0.7187 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 16:55:57 - mmengine - INFO - Epoch(val) [13][509/509] car: 0.9546 bicycle: 0.5176 motorcycle: 0.6882 truck: 0.6210 bus: 0.4334 person: 0.7453 bicyclist: 0.8529 motorcyclist: 0.0711 road: 0.9372 parking: 0.3536 sidewalk: 0.8053 other-ground: 0.0076 building: 0.9106 fence: 0.6321 vegetation: 0.8814 trunck: 0.6799 terrian: 0.7402 pole: 0.6577 traffic-sign: 0.5230 miou: 0.6322 acc: 0.9181 acc_cls: 0.7187 data_time: 0.0044 time: 0.3546 2023/04/25 16:56:37 - mmengine - INFO - Epoch(train) [14][ 50/1196] lr: 8.0000e-03 eta: 6:01:36 time: 0.7899 data_time: 0.0048 memory: 3039 grad_norm: 0.1091 loss: 0.2342 loss_sem_seg: 0.2342 2023/04/25 16:57:17 - mmengine - INFO - Epoch(train) [14][ 100/1196] lr: 8.0000e-03 eta: 6:00:58 time: 0.8131 data_time: 0.0036 memory: 3366 grad_norm: 0.1153 loss: 0.2179 loss_sem_seg: 0.2179 2023/04/25 16:57:57 - mmengine - INFO - Epoch(train) [14][ 150/1196] lr: 8.0000e-03 eta: 6:00:19 time: 0.7895 data_time: 0.0034 memory: 3230 grad_norm: 0.1236 loss: 0.2380 loss_sem_seg: 0.2380 2023/04/25 16:58:38 - mmengine - INFO - Epoch(train) [14][ 200/1196] lr: 8.0000e-03 eta: 5:59:41 time: 0.8168 data_time: 0.0035 memory: 3357 grad_norm: 0.1029 loss: 0.2198 loss_sem_seg: 0.2198 2023/04/25 16:59:19 - mmengine - INFO - Epoch(train) [14][ 250/1196] lr: 8.0000e-03 eta: 5:59:06 time: 0.8382 data_time: 0.0035 memory: 3309 grad_norm: 0.1026 loss: 0.2286 loss_sem_seg: 0.2286 2023/04/25 16:59:59 - mmengine - INFO - Epoch(train) [14][ 300/1196] lr: 8.0000e-03 eta: 5:58:27 time: 0.7928 data_time: 0.0036 memory: 3765 grad_norm: 0.0981 loss: 0.2203 loss_sem_seg: 0.2203 2023/04/25 17:00:39 - mmengine - INFO - Epoch(train) [14][ 350/1196] lr: 8.0000e-03 eta: 5:57:48 time: 0.8052 data_time: 0.0035 memory: 3034 grad_norm: 0.0998 loss: 0.2347 loss_sem_seg: 0.2347 2023/04/25 17:01:21 - mmengine - INFO - Epoch(train) [14][ 400/1196] lr: 8.0000e-03 eta: 5:57:13 time: 0.8404 data_time: 0.0035 memory: 3162 grad_norm: 0.1089 loss: 0.2282 loss_sem_seg: 0.2282 2023/04/25 17:02:01 - mmengine - INFO - Epoch(train) [14][ 450/1196] lr: 8.0000e-03 eta: 5:56:33 time: 0.7889 data_time: 0.0037 memory: 3192 grad_norm: 0.1043 loss: 0.2358 loss_sem_seg: 0.2358 2023/04/25 17:02:03 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 17:02:42 - mmengine - INFO - Epoch(train) [14][ 500/1196] lr: 8.0000e-03 eta: 5:55:56 time: 0.8193 data_time: 0.0035 memory: 3456 grad_norm: 0.1015 loss: 0.2246 loss_sem_seg: 0.2246 2023/04/25 17:03:22 - mmengine - INFO - Epoch(train) [14][ 550/1196] lr: 8.0000e-03 eta: 5:55:18 time: 0.8080 data_time: 0.0034 memory: 3213 grad_norm: 0.1187 loss: 0.2246 loss_sem_seg: 0.2246 2023/04/25 17:04:02 - mmengine - INFO - Epoch(train) [14][ 600/1196] lr: 8.0000e-03 eta: 5:54:40 time: 0.8016 data_time: 0.0035 memory: 3337 grad_norm: 0.1046 loss: 0.2384 loss_sem_seg: 0.2384 2023/04/25 17:04:42 - mmengine - INFO - Epoch(train) [14][ 650/1196] lr: 8.0000e-03 eta: 5:54:01 time: 0.8013 data_time: 0.0036 memory: 3397 grad_norm: 0.1006 loss: 0.2357 loss_sem_seg: 0.2357 2023/04/25 17:05:21 - mmengine - INFO - Epoch(train) [14][ 700/1196] lr: 8.0000e-03 eta: 5:53:20 time: 0.7794 data_time: 0.0035 memory: 2972 grad_norm: 0.0961 loss: 0.2229 loss_sem_seg: 0.2229 2023/04/25 17:06:02 - mmengine - INFO - Epoch(train) [14][ 750/1196] lr: 8.0000e-03 eta: 5:52:42 time: 0.8102 data_time: 0.0034 memory: 3385 grad_norm: 0.1038 loss: 0.2311 loss_sem_seg: 0.2311 2023/04/25 17:06:43 - mmengine - INFO - Epoch(train) [14][ 800/1196] lr: 8.0000e-03 eta: 5:52:05 time: 0.8159 data_time: 0.0034 memory: 3225 grad_norm: 0.1031 loss: 0.2332 loss_sem_seg: 0.2332 2023/04/25 17:07:22 - mmengine - INFO - Epoch(train) [14][ 850/1196] lr: 8.0000e-03 eta: 5:51:25 time: 0.7905 data_time: 0.0034 memory: 3467 grad_norm: 0.1055 loss: 0.2388 loss_sem_seg: 0.2388 2023/04/25 17:08:02 - mmengine - INFO - Epoch(train) [14][ 900/1196] lr: 8.0000e-03 eta: 5:50:45 time: 0.7877 data_time: 0.0035 memory: 3493 grad_norm: 0.1097 loss: 0.2293 loss_sem_seg: 0.2293 2023/04/25 17:08:43 - mmengine - INFO - Epoch(train) [14][ 950/1196] lr: 8.0000e-03 eta: 5:50:09 time: 0.8244 data_time: 0.0037 memory: 3137 grad_norm: 0.1036 loss: 0.2406 loss_sem_seg: 0.2406 2023/04/25 17:09:22 - mmengine - INFO - Epoch(train) [14][1000/1196] lr: 8.0000e-03 eta: 5:49:29 time: 0.7885 data_time: 0.0037 memory: 3234 grad_norm: 0.0972 loss: 0.2317 loss_sem_seg: 0.2317 2023/04/25 17:10:04 - mmengine - INFO - Epoch(train) [14][1050/1196] lr: 8.0000e-03 eta: 5:48:52 time: 0.8283 data_time: 0.0037 memory: 3349 grad_norm: 0.1111 loss: 0.2376 loss_sem_seg: 0.2376 2023/04/25 17:10:44 - mmengine - INFO - Epoch(train) [14][1100/1196] lr: 8.0000e-03 eta: 5:48:14 time: 0.8047 data_time: 0.0039 memory: 3203 grad_norm: 0.1067 loss: 0.2301 loss_sem_seg: 0.2301 2023/04/25 17:11:25 - mmengine - INFO - Epoch(train) [14][1150/1196] lr: 8.0000e-03 eta: 5:47:37 time: 0.8238 data_time: 0.0042 memory: 3252 grad_norm: 0.1052 loss: 0.2176 loss_sem_seg: 0.2176 2023/04/25 17:12:02 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 17:12:02 - mmengine - INFO - Saving checkpoint at 14 epochs 2023/04/25 17:12:19 - mmengine - INFO - Epoch(val) [14][ 50/509] eta: 0:01:59 time: 0.2593 data_time: 0.0054 memory: 3191 2023/04/25 17:12:32 - mmengine - INFO - Epoch(val) [14][100/509] eta: 0:01:45 time: 0.2573 data_time: 0.0056 memory: 840 2023/04/25 17:12:43 - mmengine - INFO - Epoch(val) [14][150/509] eta: 0:01:28 time: 0.2227 data_time: 0.0051 memory: 843 2023/04/25 17:12:55 - mmengine - INFO - Epoch(val) [14][200/509] eta: 0:01:16 time: 0.2451 data_time: 0.0054 memory: 834 2023/04/25 17:13:06 - mmengine - INFO - Epoch(val) [14][250/509] eta: 0:01:02 time: 0.2142 data_time: 0.0055 memory: 850 2023/04/25 17:13:17 - mmengine - INFO - Epoch(val) [14][300/509] eta: 0:00:49 time: 0.2228 data_time: 0.0055 memory: 812 2023/04/25 17:13:29 - mmengine - INFO - Epoch(val) [14][350/509] eta: 0:00:37 time: 0.2440 data_time: 0.0054 memory: 825 2023/04/25 17:13:43 - mmengine - INFO - Epoch(val) [14][400/509] eta: 0:00:26 time: 0.2665 data_time: 0.0055 memory: 827 2023/04/25 17:13:59 - mmengine - INFO - Epoch(val) [14][450/509] eta: 0:00:14 time: 0.3385 data_time: 0.0050 memory: 845 2023/04/25 17:14:16 - mmengine - INFO - Epoch(val) [14][500/509] eta: 0:00:02 time: 0.3204 data_time: 0.0050 memory: 832 2023/04/25 17:14:46 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9593 | 0.5232 | 0.6443 | 0.4884 | 0.4811 | 0.6916 | 0.8673 | 0.0337 | 0.9323 | 0.4574 | 0.8060 | 0.0487 | 0.9119 | 0.6656 | 0.8928 | 0.7112 | 0.7673 | 0.6517 | 0.4898 | 0.6328 | 0.9232 | 0.7410 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 17:14:46 - mmengine - INFO - Epoch(val) [14][509/509] car: 0.9593 bicycle: 0.5232 motorcycle: 0.6443 truck: 0.4884 bus: 0.4811 person: 0.6916 bicyclist: 0.8673 motorcyclist: 0.0337 road: 0.9323 parking: 0.4574 sidewalk: 0.8060 other-ground: 0.0487 building: 0.9119 fence: 0.6656 vegetation: 0.8928 trunck: 0.7112 terrian: 0.7673 pole: 0.6517 traffic-sign: 0.4898 miou: 0.6328 acc: 0.9232 acc_cls: 0.7410 data_time: 0.0047 time: 0.3214 2023/04/25 17:15:28 - mmengine - INFO - Epoch(train) [15][ 50/1196] lr: 8.0000e-03 eta: 5:46:25 time: 0.8370 data_time: 0.0043 memory: 3325 grad_norm: 0.1068 loss: 0.2262 loss_sem_seg: 0.2262 2023/04/25 17:16:06 - mmengine - INFO - Epoch(train) [15][ 100/1196] lr: 8.0000e-03 eta: 5:45:42 time: 0.7578 data_time: 0.0034 memory: 3135 grad_norm: 0.0979 loss: 0.2324 loss_sem_seg: 0.2324 2023/04/25 17:16:46 - mmengine - INFO - Epoch(train) [15][ 150/1196] lr: 8.0000e-03 eta: 5:45:03 time: 0.7933 data_time: 0.0037 memory: 3380 grad_norm: 0.1141 loss: 0.2412 loss_sem_seg: 0.2412 2023/04/25 17:17:26 - mmengine - INFO - Epoch(train) [15][ 200/1196] lr: 8.0000e-03 eta: 5:44:24 time: 0.8044 data_time: 0.0033 memory: 3130 grad_norm: 0.1050 loss: 0.2361 loss_sem_seg: 0.2361 2023/04/25 17:18:05 - mmengine - INFO - Epoch(train) [15][ 250/1196] lr: 8.0000e-03 eta: 5:43:44 time: 0.7833 data_time: 0.0034 memory: 3178 grad_norm: 0.1124 loss: 0.2356 loss_sem_seg: 0.2356 2023/04/25 17:18:10 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 17:18:45 - mmengine - INFO - Epoch(train) [15][ 300/1196] lr: 8.0000e-03 eta: 5:43:06 time: 0.8052 data_time: 0.0033 memory: 3091 grad_norm: 0.1102 loss: 0.2357 loss_sem_seg: 0.2357 2023/04/25 17:19:25 - mmengine - INFO - Epoch(train) [15][ 350/1196] lr: 8.0000e-03 eta: 5:42:26 time: 0.7872 data_time: 0.0035 memory: 3188 grad_norm: 0.1104 loss: 0.2326 loss_sem_seg: 0.2326 2023/04/25 17:20:04 - mmengine - INFO - Epoch(train) [15][ 400/1196] lr: 8.0000e-03 eta: 5:41:46 time: 0.7921 data_time: 0.0035 memory: 3104 grad_norm: 0.1038 loss: 0.2330 loss_sem_seg: 0.2330 2023/04/25 17:20:44 - mmengine - INFO - Epoch(train) [15][ 450/1196] lr: 8.0000e-03 eta: 5:41:07 time: 0.7892 data_time: 0.0033 memory: 3434 grad_norm: 0.1041 loss: 0.2305 loss_sem_seg: 0.2305 2023/04/25 17:21:23 - mmengine - INFO - Epoch(train) [15][ 500/1196] lr: 8.0000e-03 eta: 5:40:27 time: 0.7927 data_time: 0.0035 memory: 3267 grad_norm: 0.1048 loss: 0.2172 loss_sem_seg: 0.2172 2023/04/25 17:22:04 - mmengine - INFO - Epoch(train) [15][ 550/1196] lr: 8.0000e-03 eta: 5:39:49 time: 0.8153 data_time: 0.0035 memory: 3271 grad_norm: 0.1124 loss: 0.2352 loss_sem_seg: 0.2352 2023/04/25 17:22:44 - mmengine - INFO - Epoch(train) [15][ 600/1196] lr: 8.0000e-03 eta: 5:39:10 time: 0.7924 data_time: 0.0035 memory: 3129 grad_norm: 0.1073 loss: 0.2138 loss_sem_seg: 0.2138 2023/04/25 17:23:23 - mmengine - INFO - Epoch(train) [15][ 650/1196] lr: 8.0000e-03 eta: 5:38:31 time: 0.7972 data_time: 0.0035 memory: 3035 grad_norm: 0.0926 loss: 0.2217 loss_sem_seg: 0.2217 2023/04/25 17:24:03 - mmengine - INFO - Epoch(train) [15][ 700/1196] lr: 8.0000e-03 eta: 5:37:51 time: 0.7919 data_time: 0.0033 memory: 3164 grad_norm: 0.1012 loss: 0.2285 loss_sem_seg: 0.2285 2023/04/25 17:24:44 - mmengine - INFO - Epoch(train) [15][ 750/1196] lr: 8.0000e-03 eta: 5:37:14 time: 0.8245 data_time: 0.0036 memory: 3396 grad_norm: 0.1080 loss: 0.2238 loss_sem_seg: 0.2238 2023/04/25 17:25:24 - mmengine - INFO - Epoch(train) [15][ 800/1196] lr: 8.0000e-03 eta: 5:36:34 time: 0.7851 data_time: 0.0036 memory: 3250 grad_norm: 0.1158 loss: 0.2103 loss_sem_seg: 0.2103 2023/04/25 17:26:04 - mmengine - INFO - Epoch(train) [15][ 850/1196] lr: 8.0000e-03 eta: 5:35:56 time: 0.8084 data_time: 0.0035 memory: 3084 grad_norm: 0.1088 loss: 0.2248 loss_sem_seg: 0.2248 2023/04/25 17:26:42 - mmengine - INFO - Epoch(train) [15][ 900/1196] lr: 8.0000e-03 eta: 5:35:13 time: 0.7558 data_time: 0.0036 memory: 3243 grad_norm: 0.1252 loss: 0.2306 loss_sem_seg: 0.2306 2023/04/25 17:27:22 - mmengine - INFO - Epoch(train) [15][ 950/1196] lr: 8.0000e-03 eta: 5:34:35 time: 0.8055 data_time: 0.0037 memory: 3230 grad_norm: inf loss: 0.2283 loss_sem_seg: 0.2283 2023/04/25 17:28:02 - mmengine - INFO - Epoch(train) [15][1000/1196] lr: 8.0000e-03 eta: 5:33:55 time: 0.7950 data_time: 0.0034 memory: 3189 grad_norm: 0.1010 loss: 0.2132 loss_sem_seg: 0.2132 2023/04/25 17:28:41 - mmengine - INFO - Epoch(train) [15][1050/1196] lr: 8.0000e-03 eta: 5:33:15 time: 0.7789 data_time: 0.0037 memory: 3117 grad_norm: 0.1017 loss: 0.2269 loss_sem_seg: 0.2269 2023/04/25 17:29:22 - mmengine - INFO - Epoch(train) [15][1100/1196] lr: 8.0000e-03 eta: 5:32:37 time: 0.8179 data_time: 0.0036 memory: 3368 grad_norm: 0.0926 loss: 0.2209 loss_sem_seg: 0.2209 2023/04/25 17:30:01 - mmengine - INFO - Epoch(train) [15][1150/1196] lr: 8.0000e-03 eta: 5:31:58 time: 0.7938 data_time: 0.0036 memory: 3130 grad_norm: 0.0915 loss: 0.2115 loss_sem_seg: 0.2115 2023/04/25 17:30:39 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 17:30:39 - mmengine - INFO - Saving checkpoint at 15 epochs 2023/04/25 17:30:55 - mmengine - INFO - Epoch(val) [15][ 50/509] eta: 0:01:45 time: 0.2303 data_time: 0.0051 memory: 3167 2023/04/25 17:31:07 - mmengine - INFO - Epoch(val) [15][100/509] eta: 0:01:35 time: 0.2389 data_time: 0.0052 memory: 840 2023/04/25 17:31:18 - mmengine - INFO - Epoch(val) [15][150/509] eta: 0:01:23 time: 0.2295 data_time: 0.0051 memory: 843 2023/04/25 17:31:30 - mmengine - INFO - Epoch(val) [15][200/509] eta: 0:01:12 time: 0.2388 data_time: 0.0050 memory: 834 2023/04/25 17:31:42 - mmengine - INFO - Epoch(val) [15][250/509] eta: 0:01:00 time: 0.2378 data_time: 0.0055 memory: 850 2023/04/25 17:31:51 - mmengine - INFO - Epoch(val) [15][300/509] eta: 0:00:47 time: 0.1824 data_time: 0.0050 memory: 812 2023/04/25 17:32:03 - mmengine - INFO - Epoch(val) [15][350/509] eta: 0:00:36 time: 0.2277 data_time: 0.0055 memory: 825 2023/04/25 17:32:12 - mmengine - INFO - Epoch(val) [15][400/509] eta: 0:00:24 time: 0.1816 data_time: 0.0048 memory: 827 2023/04/25 17:32:28 - mmengine - INFO - Epoch(val) [15][450/509] eta: 0:00:13 time: 0.3184 data_time: 0.0054 memory: 845 2023/04/25 17:32:43 - mmengine - INFO - Epoch(val) [15][500/509] eta: 0:00:02 time: 0.3092 data_time: 0.0045 memory: 832 2023/04/25 17:33:29 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9559 | 0.4993 | 0.6887 | 0.6498 | 0.5576 | 0.7036 | 0.7940 | 0.0041 | 0.9344 | 0.4699 | 0.8122 | 0.0182 | 0.9040 | 0.6451 | 0.8787 | 0.6861 | 0.7358 | 0.6381 | 0.5065 | 0.6359 | 0.9180 | 0.7237 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 17:33:29 - mmengine - INFO - Epoch(val) [15][509/509] car: 0.9559 bicycle: 0.4993 motorcycle: 0.6887 truck: 0.6498 bus: 0.5576 person: 0.7036 bicyclist: 0.7940 motorcyclist: 0.0041 road: 0.9344 parking: 0.4699 sidewalk: 0.8122 other-ground: 0.0182 building: 0.9040 fence: 0.6451 vegetation: 0.8787 trunck: 0.6861 terrian: 0.7358 pole: 0.6381 traffic-sign: 0.5065 miou: 0.6359 acc: 0.9180 acc_cls: 0.7237 data_time: 0.0043 time: 0.3110 2023/04/25 17:34:08 - mmengine - INFO - Epoch(train) [16][ 50/1196] lr: 8.0000e-03 eta: 5:30:43 time: 0.7879 data_time: 0.0047 memory: 3299 grad_norm: 0.1047 loss: 0.2215 loss_sem_seg: 0.2215 2023/04/25 17:34:16 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 17:34:47 - mmengine - INFO - Epoch(train) [16][ 100/1196] lr: 8.0000e-03 eta: 5:30:03 time: 0.7821 data_time: 0.0033 memory: 3129 grad_norm: 0.1054 loss: 0.2251 loss_sem_seg: 0.2251 2023/04/25 17:35:26 - mmengine - INFO - Epoch(train) [16][ 150/1196] lr: 8.0000e-03 eta: 5:29:23 time: 0.7787 data_time: 0.0035 memory: 3259 grad_norm: 0.1092 loss: 0.2176 loss_sem_seg: 0.2176 2023/04/25 17:36:06 - mmengine - INFO - Epoch(train) [16][ 200/1196] lr: 8.0000e-03 eta: 5:28:44 time: 0.7975 data_time: 0.0036 memory: 3279 grad_norm: 0.1056 loss: 0.2303 loss_sem_seg: 0.2303 2023/04/25 17:36:45 - mmengine - INFO - Epoch(train) [16][ 250/1196] lr: 8.0000e-03 eta: 5:28:03 time: 0.7812 data_time: 0.0036 memory: 3254 grad_norm: 0.1027 loss: 0.2159 loss_sem_seg: 0.2159 2023/04/25 17:37:24 - mmengine - INFO - Epoch(train) [16][ 300/1196] lr: 8.0000e-03 eta: 5:27:23 time: 0.7754 data_time: 0.0035 memory: 3175 grad_norm: 0.1049 loss: 0.2212 loss_sem_seg: 0.2212 2023/04/25 17:38:04 - mmengine - INFO - Epoch(train) [16][ 350/1196] lr: 8.0000e-03 eta: 5:26:44 time: 0.8018 data_time: 0.0033 memory: 3815 grad_norm: 0.0963 loss: 0.2368 loss_sem_seg: 0.2368 2023/04/25 17:38:42 - mmengine - INFO - Epoch(train) [16][ 400/1196] lr: 8.0000e-03 eta: 5:26:02 time: 0.7569 data_time: 0.0034 memory: 3344 grad_norm: 0.1020 loss: 0.2111 loss_sem_seg: 0.2111 2023/04/25 17:39:21 - mmengine - INFO - Epoch(train) [16][ 450/1196] lr: 8.0000e-03 eta: 5:25:22 time: 0.7897 data_time: 0.0035 memory: 3175 grad_norm: 0.1042 loss: 0.2114 loss_sem_seg: 0.2114 2023/04/25 17:40:01 - mmengine - INFO - Epoch(train) [16][ 500/1196] lr: 8.0000e-03 eta: 5:24:43 time: 0.7917 data_time: 0.0035 memory: 3908 grad_norm: 0.1113 loss: 0.2346 loss_sem_seg: 0.2346 2023/04/25 17:40:41 - mmengine - INFO - Epoch(train) [16][ 550/1196] lr: 8.0000e-03 eta: 5:24:04 time: 0.8059 data_time: 0.0035 memory: 3143 grad_norm: 0.1078 loss: 0.2500 loss_sem_seg: 0.2500 2023/04/25 17:41:23 - mmengine - INFO - Epoch(train) [16][ 600/1196] lr: 8.0000e-03 eta: 5:23:28 time: 0.8419 data_time: 0.0034 memory: 3087 grad_norm: 0.0969 loss: 0.2085 loss_sem_seg: 0.2085 2023/04/25 17:42:02 - mmengine - INFO - Epoch(train) [16][ 650/1196] lr: 8.0000e-03 eta: 5:22:47 time: 0.7740 data_time: 0.0034 memory: 3116 grad_norm: 0.1035 loss: 0.2125 loss_sem_seg: 0.2125 2023/04/25 17:42:42 - mmengine - INFO - Epoch(train) [16][ 700/1196] lr: 8.0000e-03 eta: 5:22:08 time: 0.8056 data_time: 0.0035 memory: 3145 grad_norm: 0.1095 loss: 0.2176 loss_sem_seg: 0.2176 2023/04/25 17:43:23 - mmengine - INFO - Epoch(train) [16][ 750/1196] lr: 8.0000e-03 eta: 5:21:30 time: 0.8103 data_time: 0.0035 memory: 3142 grad_norm: 0.1032 loss: 0.2230 loss_sem_seg: 0.2230 2023/04/25 17:44:03 - mmengine - INFO - Epoch(train) [16][ 800/1196] lr: 8.0000e-03 eta: 5:20:52 time: 0.8118 data_time: 0.0036 memory: 3439 grad_norm: 0.1036 loss: 0.2217 loss_sem_seg: 0.2217 2023/04/25 17:44:44 - mmengine - INFO - Epoch(train) [16][ 850/1196] lr: 8.0000e-03 eta: 5:20:13 time: 0.8143 data_time: 0.0034 memory: 3600 grad_norm: 0.1078 loss: 0.2441 loss_sem_seg: 0.2441 2023/04/25 17:45:23 - mmengine - INFO - Epoch(train) [16][ 900/1196] lr: 8.0000e-03 eta: 5:19:33 time: 0.7759 data_time: 0.0036 memory: 3171 grad_norm: 0.1017 loss: 0.2439 loss_sem_seg: 0.2439 2023/04/25 17:46:03 - mmengine - INFO - Epoch(train) [16][ 950/1196] lr: 8.0000e-03 eta: 5:18:54 time: 0.8077 data_time: 0.0035 memory: 3482 grad_norm: 0.0986 loss: 0.2136 loss_sem_seg: 0.2136 2023/04/25 17:46:45 - mmengine - INFO - Epoch(train) [16][1000/1196] lr: 8.0000e-03 eta: 5:18:17 time: 0.8306 data_time: 0.0034 memory: 3189 grad_norm: 0.1124 loss: 0.2356 loss_sem_seg: 0.2356 2023/04/25 17:47:25 - mmengine - INFO - Epoch(train) [16][1050/1196] lr: 8.0000e-03 eta: 5:17:38 time: 0.7976 data_time: 0.0035 memory: 3079 grad_norm: 0.1024 loss: 0.2147 loss_sem_seg: 0.2147 2023/04/25 17:47:33 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 17:48:05 - mmengine - INFO - Epoch(train) [16][1100/1196] lr: 8.0000e-03 eta: 5:16:59 time: 0.8062 data_time: 0.0035 memory: 3338 grad_norm: 0.0975 loss: 0.2074 loss_sem_seg: 0.2074 2023/04/25 17:48:43 - mmengine - INFO - Epoch(train) [16][1150/1196] lr: 8.0000e-03 eta: 5:16:17 time: 0.7507 data_time: 0.0036 memory: 3364 grad_norm: 0.1016 loss: 0.2134 loss_sem_seg: 0.2134 2023/04/25 17:49:20 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 17:49:20 - mmengine - INFO - Saving checkpoint at 16 epochs 2023/04/25 17:49:34 - mmengine - INFO - Epoch(val) [16][ 50/509] eta: 0:01:33 time: 0.2041 data_time: 0.0049 memory: 3270 2023/04/25 17:49:46 - mmengine - INFO - Epoch(val) [16][100/509] eta: 0:01:32 time: 0.2474 data_time: 0.0050 memory: 840 2023/04/25 17:49:56 - mmengine - INFO - Epoch(val) [16][150/509] eta: 0:01:15 time: 0.1833 data_time: 0.0051 memory: 843 2023/04/25 17:50:08 - mmengine - INFO - Epoch(val) [16][200/509] eta: 0:01:08 time: 0.2462 data_time: 0.0050 memory: 834 2023/04/25 17:50:19 - mmengine - INFO - Epoch(val) [16][250/509] eta: 0:00:56 time: 0.2175 data_time: 0.0055 memory: 850 2023/04/25 17:50:29 - mmengine - INFO - Epoch(val) [16][300/509] eta: 0:00:44 time: 0.1932 data_time: 0.0049 memory: 812 2023/04/25 17:50:38 - mmengine - INFO - Epoch(val) [16][350/509] eta: 0:00:33 time: 0.1854 data_time: 0.0052 memory: 825 2023/04/25 17:50:49 - mmengine - INFO - Epoch(val) [16][400/509] eta: 0:00:23 time: 0.2297 data_time: 0.0054 memory: 827 2023/04/25 17:50:59 - mmengine - INFO - Epoch(val) [16][450/509] eta: 0:00:12 time: 0.1936 data_time: 0.0053 memory: 845 2023/04/25 17:51:15 - mmengine - INFO - Epoch(val) [16][500/509] eta: 0:00:02 time: 0.3239 data_time: 0.0049 memory: 832 2023/04/25 17:51:45 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9542 | 0.5467 | 0.7699 | 0.7666 | 0.5220 | 0.7721 | 0.8735 | 0.0324 | 0.9287 | 0.3600 | 0.8060 | 0.0049 | 0.9113 | 0.6685 | 0.8743 | 0.6794 | 0.7180 | 0.6586 | 0.5085 | 0.6503 | 0.9158 | 0.7179 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 17:51:45 - mmengine - INFO - Epoch(val) [16][509/509] car: 0.9542 bicycle: 0.5467 motorcycle: 0.7699 truck: 0.7666 bus: 0.5220 person: 0.7721 bicyclist: 0.8735 motorcyclist: 0.0324 road: 0.9287 parking: 0.3600 sidewalk: 0.8060 other-ground: 0.0049 building: 0.9113 fence: 0.6685 vegetation: 0.8743 trunck: 0.6794 terrian: 0.7180 pole: 0.6586 traffic-sign: 0.5085 miou: 0.6503 acc: 0.9158 acc_cls: 0.7179 data_time: 0.0046 time: 0.3265 2023/04/25 17:52:25 - mmengine - INFO - Epoch(train) [17][ 50/1196] lr: 8.0000e-03 eta: 5:15:02 time: 0.8009 data_time: 0.0045 memory: 3179 grad_norm: 0.1050 loss: 0.2201 loss_sem_seg: 0.2201 2023/04/25 17:53:06 - mmengine - INFO - Epoch(train) [17][ 100/1196] lr: 8.0000e-03 eta: 5:14:24 time: 0.8154 data_time: 0.0034 memory: 3124 grad_norm: 0.1137 loss: 0.2251 loss_sem_seg: 0.2251 2023/04/25 17:53:45 - mmengine - INFO - Epoch(train) [17][ 150/1196] lr: 8.0000e-03 eta: 5:13:44 time: 0.7774 data_time: 0.0034 memory: 3286 grad_norm: 0.0982 loss: 0.2447 loss_sem_seg: 0.2447 2023/04/25 17:54:26 - mmengine - INFO - Epoch(train) [17][ 200/1196] lr: 8.0000e-03 eta: 5:13:06 time: 0.8212 data_time: 0.0036 memory: 3334 grad_norm: 0.0990 loss: 0.2235 loss_sem_seg: 0.2235 2023/04/25 17:55:06 - mmengine - INFO - Epoch(train) [17][ 250/1196] lr: 8.0000e-03 eta: 5:12:26 time: 0.7967 data_time: 0.0035 memory: 3272 grad_norm: 0.1063 loss: 0.2207 loss_sem_seg: 0.2207 2023/04/25 17:55:44 - mmengine - INFO - Epoch(train) [17][ 300/1196] lr: 8.0000e-03 eta: 5:11:46 time: 0.7753 data_time: 0.0036 memory: 3205 grad_norm: 0.1024 loss: 0.2286 loss_sem_seg: 0.2286 2023/04/25 17:56:24 - mmengine - INFO - Epoch(train) [17][ 350/1196] lr: 8.0000e-03 eta: 5:11:06 time: 0.7914 data_time: 0.0035 memory: 3552 grad_norm: 0.1018 loss: 0.2262 loss_sem_seg: 0.2262 2023/04/25 17:57:04 - mmengine - INFO - Epoch(train) [17][ 400/1196] lr: 8.0000e-03 eta: 5:10:27 time: 0.7925 data_time: 0.0035 memory: 3426 grad_norm: 0.1095 loss: 0.2248 loss_sem_seg: 0.2248 2023/04/25 17:57:45 - mmengine - INFO - Epoch(train) [17][ 450/1196] lr: 8.0000e-03 eta: 5:09:49 time: 0.8279 data_time: 0.0037 memory: 3015 grad_norm: 0.1114 loss: 0.2281 loss_sem_seg: 0.2281 2023/04/25 17:58:24 - mmengine - INFO - Epoch(train) [17][ 500/1196] lr: 8.0000e-03 eta: 5:09:09 time: 0.7895 data_time: 0.0037 memory: 3411 grad_norm: 0.1123 loss: 0.2369 loss_sem_seg: 0.2369 2023/04/25 17:59:05 - mmengine - INFO - Epoch(train) [17][ 550/1196] lr: 8.0000e-03 eta: 5:08:31 time: 0.8133 data_time: 0.0040 memory: 3386 grad_norm: 0.1014 loss: 0.2292 loss_sem_seg: 0.2292 2023/04/25 17:59:46 - mmengine - INFO - Epoch(train) [17][ 600/1196] lr: 8.0000e-03 eta: 5:07:52 time: 0.8093 data_time: 0.0034 memory: 3108 grad_norm: 0.1028 loss: 0.2324 loss_sem_seg: 0.2324 2023/04/25 18:00:25 - mmengine - INFO - Epoch(train) [17][ 650/1196] lr: 8.0000e-03 eta: 5:07:13 time: 0.7900 data_time: 0.0035 memory: 3350 grad_norm: 0.0961 loss: 0.2224 loss_sem_seg: 0.2224 2023/04/25 18:01:05 - mmengine - INFO - Epoch(train) [17][ 700/1196] lr: 8.0000e-03 eta: 5:06:34 time: 0.8045 data_time: 0.0035 memory: 3094 grad_norm: 0.0980 loss: 0.2357 loss_sem_seg: 0.2357 2023/04/25 18:01:46 - mmengine - INFO - Epoch(train) [17][ 750/1196] lr: 8.0000e-03 eta: 5:05:55 time: 0.8069 data_time: 0.0035 memory: 3298 grad_norm: 0.0994 loss: 0.2223 loss_sem_seg: 0.2223 2023/04/25 18:02:26 - mmengine - INFO - Epoch(train) [17][ 800/1196] lr: 8.0000e-03 eta: 5:05:16 time: 0.8066 data_time: 0.0036 memory: 3129 grad_norm: 0.1085 loss: 0.2231 loss_sem_seg: 0.2231 2023/04/25 18:03:07 - mmengine - INFO - Epoch(train) [17][ 850/1196] lr: 8.0000e-03 eta: 5:04:38 time: 0.8104 data_time: 0.0035 memory: 3351 grad_norm: 0.0992 loss: 0.2162 loss_sem_seg: 0.2162 2023/04/25 18:03:17 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 18:03:47 - mmengine - INFO - Epoch(train) [17][ 900/1196] lr: 8.0000e-03 eta: 5:03:59 time: 0.8120 data_time: 0.0035 memory: 3178 grad_norm: 0.1124 loss: 0.2162 loss_sem_seg: 0.2162 2023/04/25 18:04:26 - mmengine - INFO - Epoch(train) [17][ 950/1196] lr: 8.0000e-03 eta: 5:03:19 time: 0.7782 data_time: 0.0036 memory: 3186 grad_norm: 0.1108 loss: 0.2343 loss_sem_seg: 0.2343 2023/04/25 18:05:06 - mmengine - INFO - Epoch(train) [17][1000/1196] lr: 8.0000e-03 eta: 5:02:40 time: 0.8067 data_time: 0.0036 memory: 3085 grad_norm: 0.1074 loss: 0.2314 loss_sem_seg: 0.2314 2023/04/25 18:05:47 - mmengine - INFO - Epoch(train) [17][1050/1196] lr: 8.0000e-03 eta: 5:02:01 time: 0.8103 data_time: 0.0034 memory: 3490 grad_norm: 0.1019 loss: 0.2236 loss_sem_seg: 0.2236 2023/04/25 18:06:27 - mmengine - INFO - Epoch(train) [17][1100/1196] lr: 8.0000e-03 eta: 5:01:22 time: 0.7951 data_time: 0.0035 memory: 3208 grad_norm: 0.0992 loss: 0.2194 loss_sem_seg: 0.2194 2023/04/25 18:07:08 - mmengine - INFO - Epoch(train) [17][1150/1196] lr: 8.0000e-03 eta: 5:00:44 time: 0.8193 data_time: 0.0036 memory: 3371 grad_norm: 0.1184 loss: 0.2374 loss_sem_seg: 0.2374 2023/04/25 18:07:43 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 18:07:43 - mmengine - INFO - Saving checkpoint at 17 epochs 2023/04/25 18:07:59 - mmengine - INFO - Epoch(val) [17][ 50/509] eta: 0:01:42 time: 0.2223 data_time: 0.0047 memory: 3390 2023/04/25 18:08:09 - mmengine - INFO - Epoch(val) [17][100/509] eta: 0:01:28 time: 0.2087 data_time: 0.0053 memory: 840 2023/04/25 18:08:20 - mmengine - INFO - Epoch(val) [17][150/509] eta: 0:01:16 time: 0.2120 data_time: 0.0048 memory: 843 2023/04/25 18:08:30 - mmengine - INFO - Epoch(val) [17][200/509] eta: 0:01:06 time: 0.2135 data_time: 0.0047 memory: 834 2023/04/25 18:08:41 - mmengine - INFO - Epoch(val) [17][250/509] eta: 0:00:55 time: 0.2227 data_time: 0.0049 memory: 850 2023/04/25 18:08:53 - mmengine - INFO - Epoch(val) [17][300/509] eta: 0:00:45 time: 0.2377 data_time: 0.0050 memory: 812 2023/04/25 18:09:04 - mmengine - INFO - Epoch(val) [17][350/509] eta: 0:00:34 time: 0.2150 data_time: 0.0050 memory: 825 2023/04/25 18:09:16 - mmengine - INFO - Epoch(val) [17][400/509] eta: 0:00:24 time: 0.2316 data_time: 0.0052 memory: 827 2023/04/25 18:09:29 - mmengine - INFO - Epoch(val) [17][450/509] eta: 0:00:13 time: 0.2615 data_time: 0.0050 memory: 845 2023/04/25 18:09:48 - mmengine - INFO - Epoch(val) [17][500/509] eta: 0:00:02 time: 0.3764 data_time: 0.0043 memory: 832 2023/04/25 18:10:20 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9654 | 0.5470 | 0.7699 | 0.5407 | 0.5548 | 0.7358 | 0.8929 | 0.0044 | 0.9411 | 0.5055 | 0.8073 | 0.0122 | 0.8925 | 0.5720 | 0.8807 | 0.6764 | 0.7407 | 0.6487 | 0.5101 | 0.6420 | 0.9177 | 0.7322 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 18:10:20 - mmengine - INFO - Epoch(val) [17][509/509] car: 0.9654 bicycle: 0.5470 motorcycle: 0.7699 truck: 0.5407 bus: 0.5548 person: 0.7358 bicyclist: 0.8929 motorcyclist: 0.0044 road: 0.9411 parking: 0.5055 sidewalk: 0.8073 other-ground: 0.0122 building: 0.8925 fence: 0.5720 vegetation: 0.8807 trunck: 0.6764 terrian: 0.7407 pole: 0.6487 traffic-sign: 0.5101 miou: 0.6420 acc: 0.9177 acc_cls: 0.7322 data_time: 0.0042 time: 0.3618 2023/04/25 18:11:00 - mmengine - INFO - Epoch(train) [18][ 50/1196] lr: 8.0000e-03 eta: 4:59:26 time: 0.7845 data_time: 0.0044 memory: 3054 grad_norm: 0.1215 loss: 0.2365 loss_sem_seg: 0.2365 2023/04/25 18:11:40 - mmengine - INFO - Epoch(train) [18][ 100/1196] lr: 8.0000e-03 eta: 4:58:47 time: 0.8038 data_time: 0.0035 memory: 3162 grad_norm: 0.0985 loss: 0.2273 loss_sem_seg: 0.2273 2023/04/25 18:12:19 - mmengine - INFO - Epoch(train) [18][ 150/1196] lr: 8.0000e-03 eta: 4:58:07 time: 0.7746 data_time: 0.0035 memory: 3535 grad_norm: 0.1007 loss: 0.2236 loss_sem_seg: 0.2236 2023/04/25 18:12:59 - mmengine - INFO - Epoch(train) [18][ 200/1196] lr: 8.0000e-03 eta: 4:57:28 time: 0.8081 data_time: 0.0035 memory: 3162 grad_norm: 0.0960 loss: 0.2257 loss_sem_seg: 0.2257 2023/04/25 18:13:38 - mmengine - INFO - Epoch(train) [18][ 250/1196] lr: 8.0000e-03 eta: 4:56:48 time: 0.7838 data_time: 0.0034 memory: 3208 grad_norm: 0.1078 loss: 0.2289 loss_sem_seg: 0.2289 2023/04/25 18:14:17 - mmengine - INFO - Epoch(train) [18][ 300/1196] lr: 8.0000e-03 eta: 4:56:08 time: 0.7852 data_time: 0.0035 memory: 3210 grad_norm: 0.1016 loss: 0.2201 loss_sem_seg: 0.2201 2023/04/25 18:14:58 - mmengine - INFO - Epoch(train) [18][ 350/1196] lr: 8.0000e-03 eta: 4:55:29 time: 0.8040 data_time: 0.0034 memory: 3492 grad_norm: 0.1047 loss: 0.2252 loss_sem_seg: 0.2252 2023/04/25 18:15:38 - mmengine - INFO - Epoch(train) [18][ 400/1196] lr: 8.0000e-03 eta: 4:54:50 time: 0.7994 data_time: 0.0035 memory: 3017 grad_norm: 0.1024 loss: 0.2346 loss_sem_seg: 0.2346 2023/04/25 18:16:16 - mmengine - INFO - Epoch(train) [18][ 450/1196] lr: 8.0000e-03 eta: 4:54:09 time: 0.7769 data_time: 0.0034 memory: 3328 grad_norm: 0.0927 loss: 0.2285 loss_sem_seg: 0.2285 2023/04/25 18:16:57 - mmengine - INFO - Epoch(train) [18][ 500/1196] lr: 8.0000e-03 eta: 4:53:31 time: 0.8204 data_time: 0.0034 memory: 3044 grad_norm: 0.1041 loss: 0.2284 loss_sem_seg: 0.2284 2023/04/25 18:17:37 - mmengine - INFO - Epoch(train) [18][ 550/1196] lr: 8.0000e-03 eta: 4:52:51 time: 0.7899 data_time: 0.0036 memory: 3126 grad_norm: 0.1000 loss: 0.2186 loss_sem_seg: 0.2186 2023/04/25 18:18:16 - mmengine - INFO - Epoch(train) [18][ 600/1196] lr: 8.0000e-03 eta: 4:52:11 time: 0.7818 data_time: 0.0034 memory: 3234 grad_norm: 0.0943 loss: 0.2172 loss_sem_seg: 0.2172 2023/04/25 18:18:56 - mmengine - INFO - Epoch(train) [18][ 650/1196] lr: 8.0000e-03 eta: 4:51:32 time: 0.8072 data_time: 0.0035 memory: 3372 grad_norm: 0.0978 loss: 0.2052 loss_sem_seg: 0.2052 2023/04/25 18:19:10 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 18:19:37 - mmengine - INFO - Epoch(train) [18][ 700/1196] lr: 8.0000e-03 eta: 4:50:54 time: 0.8155 data_time: 0.0035 memory: 3509 grad_norm: 0.0925 loss: 0.2275 loss_sem_seg: 0.2275 2023/04/25 18:20:17 - mmengine - INFO - Epoch(train) [18][ 750/1196] lr: 8.0000e-03 eta: 4:50:14 time: 0.7854 data_time: 0.0035 memory: 3305 grad_norm: 0.1045 loss: 0.2283 loss_sem_seg: 0.2283 2023/04/25 18:20:56 - mmengine - INFO - Epoch(train) [18][ 800/1196] lr: 8.0000e-03 eta: 4:49:34 time: 0.7858 data_time: 0.0036 memory: 3173 grad_norm: 0.0928 loss: 0.2288 loss_sem_seg: 0.2288 2023/04/25 18:21:36 - mmengine - INFO - Epoch(train) [18][ 850/1196] lr: 8.0000e-03 eta: 4:48:55 time: 0.8106 data_time: 0.0034 memory: 3119 grad_norm: 0.1032 loss: 0.2240 loss_sem_seg: 0.2240 2023/04/25 18:22:16 - mmengine - INFO - Epoch(train) [18][ 900/1196] lr: 8.0000e-03 eta: 4:48:16 time: 0.8020 data_time: 0.0037 memory: 3279 grad_norm: 0.1091 loss: 0.2293 loss_sem_seg: 0.2293 2023/04/25 18:22:57 - mmengine - INFO - Epoch(train) [18][ 950/1196] lr: 8.0000e-03 eta: 4:47:38 time: 0.8186 data_time: 0.0036 memory: 3393 grad_norm: 0.0944 loss: 0.2196 loss_sem_seg: 0.2196 2023/04/25 18:23:38 - mmengine - INFO - Epoch(train) [18][1000/1196] lr: 8.0000e-03 eta: 4:46:59 time: 0.8037 data_time: 0.0037 memory: 3359 grad_norm: 0.0946 loss: 0.2103 loss_sem_seg: 0.2103 2023/04/25 18:24:16 - mmengine - INFO - Epoch(train) [18][1050/1196] lr: 8.0000e-03 eta: 4:46:18 time: 0.7767 data_time: 0.0035 memory: 3307 grad_norm: 0.1075 loss: 0.2164 loss_sem_seg: 0.2164 2023/04/25 18:24:56 - mmengine - INFO - Epoch(train) [18][1100/1196] lr: 8.0000e-03 eta: 4:45:39 time: 0.8003 data_time: 0.0035 memory: 3250 grad_norm: 0.1028 loss: 0.2175 loss_sem_seg: 0.2175 2023/04/25 18:25:36 - mmengine - INFO - Epoch(train) [18][1150/1196] lr: 8.0000e-03 eta: 4:44:59 time: 0.7818 data_time: 0.0035 memory: 3190 grad_norm: 0.1068 loss: 0.2320 loss_sem_seg: 0.2320 2023/04/25 18:26:11 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 18:26:11 - mmengine - INFO - Saving checkpoint at 18 epochs 2023/04/25 18:26:25 - mmengine - INFO - Epoch(val) [18][ 50/509] eta: 0:01:25 time: 0.1870 data_time: 0.0053 memory: 3211 2023/04/25 18:26:35 - mmengine - INFO - Epoch(val) [18][100/509] eta: 0:01:17 time: 0.1909 data_time: 0.0051 memory: 840 2023/04/25 18:26:45 - mmengine - INFO - Epoch(val) [18][150/509] eta: 0:01:09 time: 0.2026 data_time: 0.0048 memory: 843 2023/04/25 18:26:57 - mmengine - INFO - Epoch(val) [18][200/509] eta: 0:01:03 time: 0.2447 data_time: 0.0050 memory: 834 2023/04/25 18:27:08 - mmengine - INFO - Epoch(val) [18][250/509] eta: 0:00:53 time: 0.2130 data_time: 0.0050 memory: 850 2023/04/25 18:27:18 - mmengine - INFO - Epoch(val) [18][300/509] eta: 0:00:43 time: 0.2061 data_time: 0.0048 memory: 812 2023/04/25 18:27:28 - mmengine - INFO - Epoch(val) [18][350/509] eta: 0:00:32 time: 0.1913 data_time: 0.0046 memory: 825 2023/04/25 18:27:40 - mmengine - INFO - Epoch(val) [18][400/509] eta: 0:00:22 time: 0.2479 data_time: 0.0050 memory: 827 2023/04/25 18:27:49 - mmengine - INFO - Epoch(val) [18][450/509] eta: 0:00:12 time: 0.1855 data_time: 0.0045 memory: 845 2023/04/25 18:28:04 - mmengine - INFO - Epoch(val) [18][500/509] eta: 0:00:01 time: 0.3021 data_time: 0.0047 memory: 832 2023/04/25 18:28:37 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9573 | 0.5280 | 0.7809 | 0.6789 | 0.5594 | 0.7654 | 0.8634 | 0.0370 | 0.9336 | 0.4837 | 0.8126 | 0.0175 | 0.9062 | 0.6014 | 0.8777 | 0.6331 | 0.7427 | 0.6491 | 0.5243 | 0.6501 | 0.9180 | 0.7132 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 18:28:37 - mmengine - INFO - Epoch(val) [18][509/509] car: 0.9573 bicycle: 0.5280 motorcycle: 0.7809 truck: 0.6789 bus: 0.5594 person: 0.7654 bicyclist: 0.8634 motorcyclist: 0.0370 road: 0.9336 parking: 0.4837 sidewalk: 0.8126 other-ground: 0.0175 building: 0.9062 fence: 0.6014 vegetation: 0.8777 trunck: 0.6331 terrian: 0.7427 pole: 0.6491 traffic-sign: 0.5243 miou: 0.6501 acc: 0.9180 acc_cls: 0.7132 data_time: 0.0043 time: 0.3312 2023/04/25 18:29:17 - mmengine - INFO - Epoch(train) [19][ 50/1196] lr: 8.0000e-03 eta: 4:43:42 time: 0.7974 data_time: 0.0044 memory: 3198 grad_norm: 0.0982 loss: 0.2133 loss_sem_seg: 0.2133 2023/04/25 18:29:57 - mmengine - INFO - Epoch(train) [19][ 100/1196] lr: 8.0000e-03 eta: 4:43:03 time: 0.7990 data_time: 0.0035 memory: 3423 grad_norm: 0.0987 loss: 0.2237 loss_sem_seg: 0.2237 2023/04/25 18:30:38 - mmengine - INFO - Epoch(train) [19][ 150/1196] lr: 8.0000e-03 eta: 4:42:24 time: 0.8100 data_time: 0.0038 memory: 3465 grad_norm: 0.1054 loss: 0.2095 loss_sem_seg: 0.2095 2023/04/25 18:31:18 - mmengine - INFO - Epoch(train) [19][ 200/1196] lr: 8.0000e-03 eta: 4:41:46 time: 0.8144 data_time: 0.0035 memory: 3191 grad_norm: inf loss: 0.2262 loss_sem_seg: 0.2262 2023/04/25 18:31:58 - mmengine - INFO - Epoch(train) [19][ 250/1196] lr: 8.0000e-03 eta: 4:41:07 time: 0.8038 data_time: 0.0036 memory: 3103 grad_norm: 0.1018 loss: 0.2232 loss_sem_seg: 0.2232 2023/04/25 18:32:39 - mmengine - INFO - Epoch(train) [19][ 300/1196] lr: 8.0000e-03 eta: 4:40:28 time: 0.8043 data_time: 0.0037 memory: 3326 grad_norm: 0.1112 loss: 0.2266 loss_sem_seg: 0.2266 2023/04/25 18:33:20 - mmengine - INFO - Epoch(train) [19][ 350/1196] lr: 8.0000e-03 eta: 4:39:50 time: 0.8257 data_time: 0.0034 memory: 3313 grad_norm: 0.1018 loss: 0.2228 loss_sem_seg: 0.2228 2023/04/25 18:34:01 - mmengine - INFO - Epoch(train) [19][ 400/1196] lr: 8.0000e-03 eta: 4:39:11 time: 0.8111 data_time: 0.0034 memory: 3144 grad_norm: 0.1029 loss: 0.2169 loss_sem_seg: 0.2169 2023/04/25 18:34:40 - mmengine - INFO - Epoch(train) [19][ 450/1196] lr: 8.0000e-03 eta: 4:38:31 time: 0.7843 data_time: 0.0035 memory: 3175 grad_norm: 0.0893 loss: 0.2137 loss_sem_seg: 0.2137 2023/04/25 18:34:57 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 18:35:20 - mmengine - INFO - Epoch(train) [19][ 500/1196] lr: 8.0000e-03 eta: 4:37:51 time: 0.7972 data_time: 0.0035 memory: 3334 grad_norm: 0.0952 loss: 0.2115 loss_sem_seg: 0.2115 2023/04/25 18:36:01 - mmengine - INFO - Epoch(train) [19][ 550/1196] lr: 8.0000e-03 eta: 4:37:13 time: 0.8232 data_time: 0.0034 memory: 3298 grad_norm: 0.0926 loss: 0.2008 loss_sem_seg: 0.2008 2023/04/25 18:36:41 - mmengine - INFO - Epoch(train) [19][ 600/1196] lr: 8.0000e-03 eta: 4:36:34 time: 0.7967 data_time: 0.0034 memory: 3123 grad_norm: 0.1007 loss: 0.2261 loss_sem_seg: 0.2261 2023/04/25 18:37:22 - mmengine - INFO - Epoch(train) [19][ 650/1196] lr: 8.0000e-03 eta: 4:35:55 time: 0.8216 data_time: 0.0036 memory: 3545 grad_norm: 0.0951 loss: 0.2234 loss_sem_seg: 0.2234 2023/04/25 18:38:03 - mmengine - INFO - Epoch(train) [19][ 700/1196] lr: 8.0000e-03 eta: 4:35:18 time: 0.8340 data_time: 0.0035 memory: 3306 grad_norm: 0.1108 loss: 0.2197 loss_sem_seg: 0.2197 2023/04/25 18:38:43 - mmengine - INFO - Epoch(train) [19][ 750/1196] lr: 8.0000e-03 eta: 4:34:38 time: 0.8016 data_time: 0.0034 memory: 3318 grad_norm: 0.1026 loss: 0.2281 loss_sem_seg: 0.2281 2023/04/25 18:39:23 - mmengine - INFO - Epoch(train) [19][ 800/1196] lr: 8.0000e-03 eta: 4:33:59 time: 0.7967 data_time: 0.0034 memory: 3214 grad_norm: 0.0952 loss: 0.2283 loss_sem_seg: 0.2283 2023/04/25 18:40:04 - mmengine - INFO - Epoch(train) [19][ 850/1196] lr: 8.0000e-03 eta: 4:33:20 time: 0.8038 data_time: 0.0036 memory: 3175 grad_norm: inf loss: 0.2306 loss_sem_seg: 0.2306 2023/04/25 18:40:43 - mmengine - INFO - Epoch(train) [19][ 900/1196] lr: 8.0000e-03 eta: 4:32:40 time: 0.7966 data_time: 0.0036 memory: 3429 grad_norm: 0.1160 loss: 0.2273 loss_sem_seg: 0.2273 2023/04/25 18:41:22 - mmengine - INFO - Epoch(train) [19][ 950/1196] lr: 8.0000e-03 eta: 4:31:59 time: 0.7680 data_time: 0.0035 memory: 3351 grad_norm: 0.1085 loss: 0.2357 loss_sem_seg: 0.2357 2023/04/25 18:42:03 - mmengine - INFO - Epoch(train) [19][1000/1196] lr: 8.0000e-03 eta: 4:31:21 time: 0.8159 data_time: 0.0035 memory: 3332 grad_norm: 0.1015 loss: 0.2082 loss_sem_seg: 0.2082 2023/04/25 18:42:45 - mmengine - INFO - Epoch(train) [19][1050/1196] lr: 8.0000e-03 eta: 4:30:44 time: 0.8474 data_time: 0.0038 memory: 3417 grad_norm: 0.0939 loss: 0.2118 loss_sem_seg: 0.2118 2023/04/25 18:43:25 - mmengine - INFO - Epoch(train) [19][1100/1196] lr: 8.0000e-03 eta: 4:30:04 time: 0.7974 data_time: 0.0034 memory: 3181 grad_norm: 0.1088 loss: 0.2118 loss_sem_seg: 0.2118 2023/04/25 18:44:03 - mmengine - INFO - Epoch(train) [19][1150/1196] lr: 8.0000e-03 eta: 4:29:23 time: 0.7679 data_time: 0.0035 memory: 3293 grad_norm: 0.0999 loss: 0.2073 loss_sem_seg: 0.2073 2023/04/25 18:44:41 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 18:44:41 - mmengine - INFO - Saving checkpoint at 19 epochs 2023/04/25 18:44:58 - mmengine - INFO - Epoch(val) [19][ 50/509] eta: 0:01:55 time: 0.2513 data_time: 0.0049 memory: 3057 2023/04/25 18:45:08 - mmengine - INFO - Epoch(val) [19][100/509] eta: 0:01:34 time: 0.2101 data_time: 0.0049 memory: 840 2023/04/25 18:45:18 - mmengine - INFO - Epoch(val) [19][150/509] eta: 0:01:18 time: 0.1913 data_time: 0.0053 memory: 843 2023/04/25 18:45:27 - mmengine - INFO - Epoch(val) [19][200/509] eta: 0:01:04 time: 0.1837 data_time: 0.0047 memory: 834 2023/04/25 18:45:38 - mmengine - INFO - Epoch(val) [19][250/509] eta: 0:00:54 time: 0.2164 data_time: 0.0052 memory: 850 2023/04/25 18:45:46 - mmengine - INFO - Epoch(val) [19][300/509] eta: 0:00:42 time: 0.1623 data_time: 0.0047 memory: 812 2023/04/25 18:45:55 - mmengine - INFO - Epoch(val) [19][350/509] eta: 0:00:31 time: 0.1751 data_time: 0.0049 memory: 825 2023/04/25 18:46:05 - mmengine - INFO - Epoch(val) [19][400/509] eta: 0:00:21 time: 0.1956 data_time: 0.0045 memory: 827 2023/04/25 18:46:16 - mmengine - INFO - Epoch(val) [19][450/509] eta: 0:00:11 time: 0.2197 data_time: 0.0049 memory: 845 2023/04/25 18:46:32 - mmengine - INFO - Epoch(val) [19][500/509] eta: 0:00:01 time: 0.3348 data_time: 0.0046 memory: 832 2023/04/25 18:47:03 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9590 | 0.5115 | 0.7229 | 0.6694 | 0.5424 | 0.7603 | 0.8662 | 0.0012 | 0.9380 | 0.4215 | 0.8124 | 0.0027 | 0.9111 | 0.6366 | 0.8912 | 0.6555 | 0.7719 | 0.6597 | 0.5153 | 0.6447 | 0.9235 | 0.7116 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 18:47:04 - mmengine - INFO - Epoch(val) [19][509/509] car: 0.9590 bicycle: 0.5115 motorcycle: 0.7229 truck: 0.6694 bus: 0.5424 person: 0.7603 bicyclist: 0.8662 motorcyclist: 0.0012 road: 0.9380 parking: 0.4215 sidewalk: 0.8124 other-ground: 0.0027 building: 0.9111 fence: 0.6366 vegetation: 0.8912 trunck: 0.6555 terrian: 0.7719 pole: 0.6597 traffic-sign: 0.5153 miou: 0.6447 acc: 0.9235 acc_cls: 0.7116 data_time: 0.0045 time: 0.3173 2023/04/25 18:47:43 - mmengine - INFO - Epoch(train) [20][ 50/1196] lr: 8.0000e-03 eta: 4:28:09 time: 0.7993 data_time: 0.0046 memory: 3385 grad_norm: 0.1067 loss: 0.2298 loss_sem_seg: 0.2298 2023/04/25 18:48:22 - mmengine - INFO - Epoch(train) [20][ 100/1196] lr: 8.0000e-03 eta: 4:27:28 time: 0.7789 data_time: 0.0034 memory: 3204 grad_norm: 0.1063 loss: 0.2103 loss_sem_seg: 0.2103 2023/04/25 18:49:04 - mmengine - INFO - Epoch(train) [20][ 150/1196] lr: 8.0000e-03 eta: 4:26:50 time: 0.8225 data_time: 0.0035 memory: 3355 grad_norm: 0.0954 loss: 0.2227 loss_sem_seg: 0.2227 2023/04/25 18:49:44 - mmengine - INFO - Epoch(train) [20][ 200/1196] lr: 8.0000e-03 eta: 4:26:11 time: 0.8133 data_time: 0.0035 memory: 3461 grad_norm: 0.0970 loss: 0.2091 loss_sem_seg: 0.2091 2023/04/25 18:50:25 - mmengine - INFO - Epoch(train) [20][ 250/1196] lr: 8.0000e-03 eta: 4:25:33 time: 0.8167 data_time: 0.0035 memory: 3131 grad_norm: 0.1012 loss: 0.2171 loss_sem_seg: 0.2171 2023/04/25 18:50:45 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 18:51:05 - mmengine - INFO - Epoch(train) [20][ 300/1196] lr: 8.0000e-03 eta: 4:24:53 time: 0.8041 data_time: 0.0035 memory: 3108 grad_norm: 0.0950 loss: 0.2081 loss_sem_seg: 0.2081 2023/04/25 18:51:44 - mmengine - INFO - Epoch(train) [20][ 350/1196] lr: 8.0000e-03 eta: 4:24:13 time: 0.7769 data_time: 0.0036 memory: 3201 grad_norm: 0.1113 loss: 0.2093 loss_sem_seg: 0.2093 2023/04/25 18:52:23 - mmengine - INFO - Epoch(train) [20][ 400/1196] lr: 8.0000e-03 eta: 4:23:32 time: 0.7725 data_time: 0.0035 memory: 3289 grad_norm: 0.1062 loss: 0.2250 loss_sem_seg: 0.2250 2023/04/25 18:53:03 - mmengine - INFO - Epoch(train) [20][ 450/1196] lr: 8.0000e-03 eta: 4:22:53 time: 0.8061 data_time: 0.0035 memory: 3108 grad_norm: 0.1003 loss: 0.2202 loss_sem_seg: 0.2202 2023/04/25 18:53:44 - mmengine - INFO - Epoch(train) [20][ 500/1196] lr: 8.0000e-03 eta: 4:22:14 time: 0.8121 data_time: 0.0034 memory: 3333 grad_norm: 0.0981 loss: 0.1971 loss_sem_seg: 0.1971 2023/04/25 18:54:24 - mmengine - INFO - Epoch(train) [20][ 550/1196] lr: 8.0000e-03 eta: 4:21:35 time: 0.8033 data_time: 0.0037 memory: 3293 grad_norm: 0.0907 loss: 0.2111 loss_sem_seg: 0.2111 2023/04/25 18:55:06 - mmengine - INFO - Epoch(train) [20][ 600/1196] lr: 8.0000e-03 eta: 4:20:57 time: 0.8399 data_time: 0.0035 memory: 3250 grad_norm: 0.0879 loss: 0.1929 loss_sem_seg: 0.1929 2023/04/25 18:55:45 - mmengine - INFO - Epoch(train) [20][ 650/1196] lr: 8.0000e-03 eta: 4:20:17 time: 0.7778 data_time: 0.0035 memory: 3365 grad_norm: 0.0974 loss: 0.2330 loss_sem_seg: 0.2330 2023/04/25 18:56:25 - mmengine - INFO - Epoch(train) [20][ 700/1196] lr: 8.0000e-03 eta: 4:19:38 time: 0.8144 data_time: 0.0035 memory: 3391 grad_norm: 0.0937 loss: 0.2218 loss_sem_seg: 0.2218 2023/04/25 18:57:06 - mmengine - INFO - Epoch(train) [20][ 750/1196] lr: 8.0000e-03 eta: 4:18:59 time: 0.8074 data_time: 0.0037 memory: 3149 grad_norm: 0.0967 loss: 0.2094 loss_sem_seg: 0.2094 2023/04/25 18:57:45 - mmengine - INFO - Epoch(train) [20][ 800/1196] lr: 8.0000e-03 eta: 4:18:19 time: 0.7832 data_time: 0.0035 memory: 3207 grad_norm: 0.1100 loss: 0.2141 loss_sem_seg: 0.2141 2023/04/25 18:58:24 - mmengine - INFO - Epoch(train) [20][ 850/1196] lr: 8.0000e-03 eta: 4:17:39 time: 0.7870 data_time: 0.0036 memory: 3128 grad_norm: 0.1086 loss: 0.2273 loss_sem_seg: 0.2273 2023/04/25 18:59:03 - mmengine - INFO - Epoch(train) [20][ 900/1196] lr: 8.0000e-03 eta: 4:16:59 time: 0.7773 data_time: 0.0037 memory: 3378 grad_norm: 0.1017 loss: 0.2063 loss_sem_seg: 0.2063 2023/04/25 18:59:44 - mmengine - INFO - Epoch(train) [20][ 950/1196] lr: 8.0000e-03 eta: 4:16:20 time: 0.8197 data_time: 0.0035 memory: 3232 grad_norm: 0.1009 loss: 0.2184 loss_sem_seg: 0.2184 2023/04/25 19:00:24 - mmengine - INFO - Epoch(train) [20][1000/1196] lr: 8.0000e-03 eta: 4:15:40 time: 0.7902 data_time: 0.0035 memory: 3121 grad_norm: 0.0937 loss: 0.2059 loss_sem_seg: 0.2059 2023/04/25 19:01:04 - mmengine - INFO - Epoch(train) [20][1050/1196] lr: 8.0000e-03 eta: 4:15:01 time: 0.7957 data_time: 0.0036 memory: 3179 grad_norm: 0.1009 loss: 0.2156 loss_sem_seg: 0.2156 2023/04/25 19:01:43 - mmengine - INFO - Epoch(train) [20][1100/1196] lr: 8.0000e-03 eta: 4:14:21 time: 0.7986 data_time: 0.0034 memory: 3161 grad_norm: 0.1060 loss: 0.2247 loss_sem_seg: 0.2247 2023/04/25 19:02:25 - mmengine - INFO - Epoch(train) [20][1150/1196] lr: 8.0000e-03 eta: 4:13:43 time: 0.8240 data_time: 0.0035 memory: 3175 grad_norm: 0.1003 loss: 0.2066 loss_sem_seg: 0.2066 2023/04/25 19:03:01 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 19:03:01 - mmengine - INFO - Saving checkpoint at 20 epochs 2023/04/25 19:03:17 - mmengine - INFO - Epoch(val) [20][ 50/509] eta: 0:01:43 time: 0.2253 data_time: 0.0048 memory: 3353 2023/04/25 19:03:27 - mmengine - INFO - Epoch(val) [20][100/509] eta: 0:01:28 time: 0.2080 data_time: 0.0046 memory: 840 2023/04/25 19:03:37 - mmengine - INFO - Epoch(val) [20][150/509] eta: 0:01:14 time: 0.1911 data_time: 0.0047 memory: 843 2023/04/25 19:03:46 - mmengine - INFO - Epoch(val) [20][200/509] eta: 0:01:02 time: 0.1896 data_time: 0.0044 memory: 834 2023/04/25 19:03:58 - mmengine - INFO - Epoch(val) [20][250/509] eta: 0:00:54 time: 0.2383 data_time: 0.0048 memory: 850 2023/04/25 19:04:08 - mmengine - INFO - Epoch(val) [20][300/509] eta: 0:00:43 time: 0.1995 data_time: 0.0044 memory: 812 2023/04/25 19:04:18 - mmengine - INFO - Epoch(val) [20][350/509] eta: 0:00:32 time: 0.1928 data_time: 0.0050 memory: 825 2023/04/25 19:04:29 - mmengine - INFO - Epoch(val) [20][400/509] eta: 0:00:22 time: 0.2257 data_time: 0.0045 memory: 827 2023/04/25 19:04:43 - mmengine - INFO - Epoch(val) [20][450/509] eta: 0:00:12 time: 0.2766 data_time: 0.0049 memory: 845 2023/04/25 19:04:59 - mmengine - INFO - Epoch(val) [20][500/509] eta: 0:00:02 time: 0.3240 data_time: 0.0043 memory: 832 2023/04/25 19:05:26 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9600 | 0.5666 | 0.7150 | 0.3485 | 0.5690 | 0.7588 | 0.8688 | 0.0333 | 0.9402 | 0.4293 | 0.8112 | 0.0046 | 0.8894 | 0.5805 | 0.8887 | 0.6782 | 0.7611 | 0.6424 | 0.4894 | 0.6282 | 0.9205 | 0.6953 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 19:05:26 - mmengine - INFO - Epoch(val) [20][509/509] car: 0.9600 bicycle: 0.5666 motorcycle: 0.7150 truck: 0.3485 bus: 0.5690 person: 0.7588 bicyclist: 0.8688 motorcyclist: 0.0333 road: 0.9402 parking: 0.4293 sidewalk: 0.8112 other-ground: 0.0046 building: 0.8894 fence: 0.5805 vegetation: 0.8887 trunck: 0.6782 terrian: 0.7611 pole: 0.6424 traffic-sign: 0.4894 miou: 0.6282 acc: 0.9205 acc_cls: 0.6953 data_time: 0.0041 time: 0.3575 2023/04/25 19:06:07 - mmengine - INFO - Epoch(train) [21][ 50/1196] lr: 8.0000e-03 eta: 4:12:28 time: 0.8208 data_time: 0.0046 memory: 3339 grad_norm: 0.0987 loss: 0.2102 loss_sem_seg: 0.2102 2023/04/25 19:06:30 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 19:06:46 - mmengine - INFO - Epoch(train) [21][ 100/1196] lr: 8.0000e-03 eta: 4:11:47 time: 0.7766 data_time: 0.0035 memory: 3475 grad_norm: 0.0895 loss: 0.1994 loss_sem_seg: 0.1994 2023/04/25 19:07:27 - mmengine - INFO - Epoch(train) [21][ 150/1196] lr: 8.0000e-03 eta: 4:11:09 time: 0.8279 data_time: 0.0035 memory: 3144 grad_norm: 0.1068 loss: 0.2109 loss_sem_seg: 0.2109 2023/04/25 19:08:06 - mmengine - INFO - Epoch(train) [21][ 200/1196] lr: 8.0000e-03 eta: 4:10:29 time: 0.7771 data_time: 0.0034 memory: 3222 grad_norm: 0.0942 loss: 0.2131 loss_sem_seg: 0.2131 2023/04/25 19:08:45 - mmengine - INFO - Epoch(train) [21][ 250/1196] lr: 8.0000e-03 eta: 4:09:49 time: 0.7806 data_time: 0.0034 memory: 3078 grad_norm: 0.1035 loss: 0.2267 loss_sem_seg: 0.2267 2023/04/25 19:09:24 - mmengine - INFO - Epoch(train) [21][ 300/1196] lr: 8.0000e-03 eta: 4:09:08 time: 0.7816 data_time: 0.0034 memory: 3266 grad_norm: 0.1130 loss: 0.2024 loss_sem_seg: 0.2024 2023/04/25 19:10:02 - mmengine - INFO - Epoch(train) [21][ 350/1196] lr: 8.0000e-03 eta: 4:08:27 time: 0.7572 data_time: 0.0034 memory: 3142 grad_norm: 0.1077 loss: 0.2262 loss_sem_seg: 0.2262 2023/04/25 19:10:42 - mmengine - INFO - Epoch(train) [21][ 400/1196] lr: 8.0000e-03 eta: 4:07:48 time: 0.7970 data_time: 0.0034 memory: 3019 grad_norm: 0.0970 loss: 0.2083 loss_sem_seg: 0.2083 2023/04/25 19:11:23 - mmengine - INFO - Epoch(train) [21][ 450/1196] lr: 8.0000e-03 eta: 4:07:09 time: 0.8209 data_time: 0.0035 memory: 3184 grad_norm: 0.1044 loss: 0.2364 loss_sem_seg: 0.2364 2023/04/25 19:12:02 - mmengine - INFO - Epoch(train) [21][ 500/1196] lr: 8.0000e-03 eta: 4:06:29 time: 0.7688 data_time: 0.0036 memory: 3214 grad_norm: 0.1048 loss: 0.2222 loss_sem_seg: 0.2222 2023/04/25 19:12:42 - mmengine - INFO - Epoch(train) [21][ 550/1196] lr: 8.0000e-03 eta: 4:05:49 time: 0.8050 data_time: 0.0034 memory: 3287 grad_norm: 0.1063 loss: 0.2144 loss_sem_seg: 0.2144 2023/04/25 19:13:23 - mmengine - INFO - Epoch(train) [21][ 600/1196] lr: 8.0000e-03 eta: 4:05:10 time: 0.8127 data_time: 0.0034 memory: 3432 grad_norm: 0.1051 loss: 0.2197 loss_sem_seg: 0.2197 2023/04/25 19:14:01 - mmengine - INFO - Epoch(train) [21][ 650/1196] lr: 8.0000e-03 eta: 4:04:30 time: 0.7692 data_time: 0.0036 memory: 3314 grad_norm: 0.1040 loss: 0.2093 loss_sem_seg: 0.2093 2023/04/25 19:14:41 - mmengine - INFO - Epoch(train) [21][ 700/1196] lr: 8.0000e-03 eta: 4:03:50 time: 0.7968 data_time: 0.0037 memory: 3156 grad_norm: 0.0980 loss: 0.2206 loss_sem_seg: 0.2206 2023/04/25 19:15:20 - mmengine - INFO - Epoch(train) [21][ 750/1196] lr: 8.0000e-03 eta: 4:03:10 time: 0.7802 data_time: 0.0034 memory: 3306 grad_norm: 0.1004 loss: 0.2183 loss_sem_seg: 0.2183 2023/04/25 19:15:59 - mmengine - INFO - Epoch(train) [21][ 800/1196] lr: 8.0000e-03 eta: 4:02:30 time: 0.7781 data_time: 0.0035 memory: 3107 grad_norm: 0.1027 loss: 0.2209 loss_sem_seg: 0.2209 2023/04/25 19:16:36 - mmengine - INFO - Epoch(train) [21][ 850/1196] lr: 8.0000e-03 eta: 4:01:49 time: 0.7506 data_time: 0.0034 memory: 3124 grad_norm: 0.0955 loss: 0.2235 loss_sem_seg: 0.2235 2023/04/25 19:17:16 - mmengine - INFO - Epoch(train) [21][ 900/1196] lr: 8.0000e-03 eta: 4:01:09 time: 0.8003 data_time: 0.0034 memory: 3204 grad_norm: 0.0894 loss: 0.2100 loss_sem_seg: 0.2100 2023/04/25 19:17:56 - mmengine - INFO - Epoch(train) [21][ 950/1196] lr: 8.0000e-03 eta: 4:00:29 time: 0.7835 data_time: 0.0036 memory: 3269 grad_norm: 0.1047 loss: 0.2210 loss_sem_seg: 0.2210 2023/04/25 19:18:37 - mmengine - INFO - Epoch(train) [21][1000/1196] lr: 8.0000e-03 eta: 3:59:51 time: 0.8353 data_time: 0.0037 memory: 3284 grad_norm: 0.1084 loss: 0.2028 loss_sem_seg: 0.2028 2023/04/25 19:19:18 - mmengine - INFO - Epoch(train) [21][1050/1196] lr: 8.0000e-03 eta: 3:59:12 time: 0.8237 data_time: 0.0036 memory: 3620 grad_norm: 0.1071 loss: 0.2147 loss_sem_seg: 0.2147 2023/04/25 19:19:42 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 19:19:57 - mmengine - INFO - Epoch(train) [21][1100/1196] lr: 8.0000e-03 eta: 3:58:32 time: 0.7689 data_time: 0.0036 memory: 3335 grad_norm: 0.0948 loss: 0.2103 loss_sem_seg: 0.2103 2023/04/25 19:20:38 - mmengine - INFO - Epoch(train) [21][1150/1196] lr: 8.0000e-03 eta: 3:57:53 time: 0.8191 data_time: 0.0035 memory: 3078 grad_norm: 0.1116 loss: 0.2241 loss_sem_seg: 0.2241 2023/04/25 19:21:14 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 19:21:14 - mmengine - INFO - Saving checkpoint at 21 epochs 2023/04/25 19:21:30 - mmengine - INFO - Epoch(val) [21][ 50/509] eta: 0:01:47 time: 0.2338 data_time: 0.0049 memory: 3094 2023/04/25 19:21:40 - mmengine - INFO - Epoch(val) [21][100/509] eta: 0:01:28 time: 0.1993 data_time: 0.0048 memory: 840 2023/04/25 19:21:53 - mmengine - INFO - Epoch(val) [21][150/509] eta: 0:01:21 time: 0.2508 data_time: 0.0051 memory: 843 2023/04/25 19:22:03 - mmengine - INFO - Epoch(val) [21][200/509] eta: 0:01:08 time: 0.1967 data_time: 0.0048 memory: 834 2023/04/25 19:22:13 - mmengine - INFO - Epoch(val) [21][250/509] eta: 0:00:56 time: 0.2148 data_time: 0.0052 memory: 850 2023/04/25 19:22:25 - mmengine - INFO - Epoch(val) [21][300/509] eta: 0:00:45 time: 0.2247 data_time: 0.0050 memory: 812 2023/04/25 19:22:35 - mmengine - INFO - Epoch(val) [21][350/509] eta: 0:00:34 time: 0.2009 data_time: 0.0054 memory: 825 2023/04/25 19:22:46 - mmengine - INFO - Epoch(val) [21][400/509] eta: 0:00:23 time: 0.2192 data_time: 0.0050 memory: 827 2023/04/25 19:23:02 - mmengine - INFO - Epoch(val) [21][450/509] eta: 0:00:13 time: 0.3326 data_time: 0.0050 memory: 845 2023/04/25 19:23:18 - mmengine - INFO - Epoch(val) [21][500/509] eta: 0:00:02 time: 0.3178 data_time: 0.0047 memory: 832 2023/04/25 19:23:52 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9664 | 0.5188 | 0.7601 | 0.7710 | 0.7069 | 0.7309 | 0.7962 | 0.0154 | 0.9371 | 0.5569 | 0.8149 | 0.0065 | 0.9075 | 0.6082 | 0.8653 | 0.6732 | 0.7092 | 0.6573 | 0.5133 | 0.6587 | 0.9151 | 0.7303 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 19:23:52 - mmengine - INFO - Epoch(val) [21][509/509] car: 0.9664 bicycle: 0.5188 motorcycle: 0.7601 truck: 0.7710 bus: 0.7069 person: 0.7309 bicyclist: 0.7962 motorcyclist: 0.0154 road: 0.9371 parking: 0.5569 sidewalk: 0.8149 other-ground: 0.0065 building: 0.9075 fence: 0.6082 vegetation: 0.8653 trunck: 0.6732 terrian: 0.7092 pole: 0.6573 traffic-sign: 0.5133 miou: 0.6587 acc: 0.9151 acc_cls: 0.7303 data_time: 0.0046 time: 0.3635 2023/04/25 19:24:32 - mmengine - INFO - Epoch(train) [22][ 50/1196] lr: 8.0000e-03 eta: 3:56:37 time: 0.8106 data_time: 0.0045 memory: 3183 grad_norm: 0.1100 loss: 0.2187 loss_sem_seg: 0.2187 2023/04/25 19:25:12 - mmengine - INFO - Epoch(train) [22][ 100/1196] lr: 8.0000e-03 eta: 3:55:58 time: 0.7986 data_time: 0.0035 memory: 3345 grad_norm: 0.0966 loss: 0.2165 loss_sem_seg: 0.2165 2023/04/25 19:25:52 - mmengine - INFO - Epoch(train) [22][ 150/1196] lr: 8.0000e-03 eta: 3:55:18 time: 0.7956 data_time: 0.0036 memory: 3426 grad_norm: 0.1041 loss: 0.2243 loss_sem_seg: 0.2243 2023/04/25 19:26:30 - mmengine - INFO - Epoch(train) [22][ 200/1196] lr: 8.0000e-03 eta: 3:54:38 time: 0.7696 data_time: 0.0034 memory: 3441 grad_norm: 0.1034 loss: 0.2137 loss_sem_seg: 0.2137 2023/04/25 19:27:11 - mmengine - INFO - Epoch(train) [22][ 250/1196] lr: 8.0000e-03 eta: 3:53:59 time: 0.8085 data_time: 0.0036 memory: 3508 grad_norm: 0.0936 loss: 0.2131 loss_sem_seg: 0.2131 2023/04/25 19:27:49 - mmengine - INFO - Epoch(train) [22][ 300/1196] lr: 8.0000e-03 eta: 3:53:18 time: 0.7587 data_time: 0.0035 memory: 3301 grad_norm: 0.1025 loss: 0.2163 loss_sem_seg: 0.2163 2023/04/25 19:28:28 - mmengine - INFO - Epoch(train) [22][ 350/1196] lr: 8.0000e-03 eta: 3:52:38 time: 0.7890 data_time: 0.0036 memory: 3156 grad_norm: 0.1122 loss: 0.2247 loss_sem_seg: 0.2247 2023/04/25 19:29:08 - mmengine - INFO - Epoch(train) [22][ 400/1196] lr: 8.0000e-03 eta: 3:51:58 time: 0.7896 data_time: 0.0035 memory: 3343 grad_norm: 0.1068 loss: 0.2112 loss_sem_seg: 0.2112 2023/04/25 19:29:47 - mmengine - INFO - Epoch(train) [22][ 450/1196] lr: 8.0000e-03 eta: 3:51:18 time: 0.7787 data_time: 0.0034 memory: 3232 grad_norm: 0.1027 loss: 0.2175 loss_sem_seg: 0.2175 2023/04/25 19:30:25 - mmengine - INFO - Epoch(train) [22][ 500/1196] lr: 8.0000e-03 eta: 3:50:37 time: 0.7693 data_time: 0.0035 memory: 3197 grad_norm: 0.0936 loss: 0.2023 loss_sem_seg: 0.2023 2023/04/25 19:31:05 - mmengine - INFO - Epoch(train) [22][ 550/1196] lr: 8.0000e-03 eta: 3:49:58 time: 0.7886 data_time: 0.0035 memory: 3421 grad_norm: 0.0895 loss: 0.2012 loss_sem_seg: 0.2012 2023/04/25 19:31:44 - mmengine - INFO - Epoch(train) [22][ 600/1196] lr: 8.0000e-03 eta: 3:49:18 time: 0.7818 data_time: 0.0036 memory: 3152 grad_norm: 0.0922 loss: 0.1791 loss_sem_seg: 0.1791 2023/04/25 19:32:24 - mmengine - INFO - Epoch(train) [22][ 650/1196] lr: 8.0000e-03 eta: 3:48:38 time: 0.7987 data_time: 0.0035 memory: 3353 grad_norm: 0.0878 loss: 0.2041 loss_sem_seg: 0.2041 2023/04/25 19:33:04 - mmengine - INFO - Epoch(train) [22][ 700/1196] lr: 8.0000e-03 eta: 3:47:59 time: 0.8169 data_time: 0.0035 memory: 3006 grad_norm: 0.0888 loss: 0.2136 loss_sem_seg: 0.2136 2023/04/25 19:33:45 - mmengine - INFO - Epoch(train) [22][ 750/1196] lr: 8.0000e-03 eta: 3:47:20 time: 0.8025 data_time: 0.0036 memory: 3326 grad_norm: 0.0911 loss: 0.1878 loss_sem_seg: 0.1878 2023/04/25 19:34:25 - mmengine - INFO - Epoch(train) [22][ 800/1196] lr: 8.0000e-03 eta: 3:46:41 time: 0.8077 data_time: 0.0037 memory: 3151 grad_norm: 0.1045 loss: 0.2261 loss_sem_seg: 0.2261 2023/04/25 19:35:05 - mmengine - INFO - Epoch(train) [22][ 850/1196] lr: 8.0000e-03 eta: 3:46:01 time: 0.8000 data_time: 0.0037 memory: 3375 grad_norm: 0.1042 loss: 0.2201 loss_sem_seg: 0.2201 2023/04/25 19:35:33 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 19:35:47 - mmengine - INFO - Epoch(train) [22][ 900/1196] lr: 8.0000e-03 eta: 3:45:23 time: 0.8343 data_time: 0.0036 memory: 3308 grad_norm: inf loss: 0.2144 loss_sem_seg: 0.2144 2023/04/25 19:36:26 - mmengine - INFO - Epoch(train) [22][ 950/1196] lr: 8.0000e-03 eta: 3:44:43 time: 0.7837 data_time: 0.0038 memory: 3101 grad_norm: 0.0950 loss: 0.2015 loss_sem_seg: 0.2015 2023/04/25 19:37:06 - mmengine - INFO - Epoch(train) [22][1000/1196] lr: 8.0000e-03 eta: 3:44:04 time: 0.8097 data_time: 0.0036 memory: 3552 grad_norm: 0.1032 loss: 0.2179 loss_sem_seg: 0.2179 2023/04/25 19:37:47 - mmengine - INFO - Epoch(train) [22][1050/1196] lr: 8.0000e-03 eta: 3:43:24 time: 0.8061 data_time: 0.0037 memory: 3296 grad_norm: 0.0957 loss: 0.2139 loss_sem_seg: 0.2139 2023/04/25 19:38:27 - mmengine - INFO - Epoch(train) [22][1100/1196] lr: 8.0000e-03 eta: 3:42:45 time: 0.8089 data_time: 0.0038 memory: 3323 grad_norm: 0.0896 loss: 0.1997 loss_sem_seg: 0.1997 2023/04/25 19:39:07 - mmengine - INFO - Epoch(train) [22][1150/1196] lr: 8.0000e-03 eta: 3:42:05 time: 0.7935 data_time: 0.0036 memory: 3185 grad_norm: 0.0944 loss: 0.2078 loss_sem_seg: 0.2078 2023/04/25 19:39:44 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 19:39:44 - mmengine - INFO - Saving checkpoint at 22 epochs 2023/04/25 19:40:00 - mmengine - INFO - Epoch(val) [22][ 50/509] eta: 0:01:45 time: 0.2296 data_time: 0.0049 memory: 3131 2023/04/25 19:40:11 - mmengine - INFO - Epoch(val) [22][100/509] eta: 0:01:31 time: 0.2193 data_time: 0.0048 memory: 840 2023/04/25 19:40:22 - mmengine - INFO - Epoch(val) [22][150/509] eta: 0:01:19 time: 0.2133 data_time: 0.0049 memory: 843 2023/04/25 19:40:30 - mmengine - INFO - Epoch(val) [22][200/509] eta: 0:01:04 time: 0.1736 data_time: 0.0050 memory: 834 2023/04/25 19:40:40 - mmengine - INFO - Epoch(val) [22][250/509] eta: 0:00:52 time: 0.1863 data_time: 0.0047 memory: 850 2023/04/25 19:40:48 - mmengine - INFO - Epoch(val) [22][300/509] eta: 0:00:41 time: 0.1756 data_time: 0.0049 memory: 812 2023/04/25 19:41:00 - mmengine - INFO - Epoch(val) [22][350/509] eta: 0:00:32 time: 0.2235 data_time: 0.0048 memory: 825 2023/04/25 19:41:10 - mmengine - INFO - Epoch(val) [22][400/509] eta: 0:00:22 time: 0.2042 data_time: 0.0050 memory: 827 2023/04/25 19:41:20 - mmengine - INFO - Epoch(val) [22][450/509] eta: 0:00:12 time: 0.2128 data_time: 0.0053 memory: 845 2023/04/25 19:41:36 - mmengine - INFO - Epoch(val) [22][500/509] eta: 0:00:01 time: 0.3156 data_time: 0.0048 memory: 832 2023/04/25 19:42:08 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9633 | 0.5390 | 0.7582 | 0.6311 | 0.6562 | 0.6948 | 0.8347 | 0.0984 | 0.9400 | 0.4479 | 0.8069 | 0.0185 | 0.9104 | 0.6505 | 0.8870 | 0.6998 | 0.7547 | 0.6630 | 0.5089 | 0.6560 | 0.9223 | 0.7523 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 19:42:08 - mmengine - INFO - Epoch(val) [22][509/509] car: 0.9633 bicycle: 0.5390 motorcycle: 0.7582 truck: 0.6311 bus: 0.6562 person: 0.6948 bicyclist: 0.8347 motorcyclist: 0.0984 road: 0.9400 parking: 0.4479 sidewalk: 0.8069 other-ground: 0.0185 building: 0.9104 fence: 0.6505 vegetation: 0.8870 trunck: 0.6998 terrian: 0.7547 pole: 0.6630 traffic-sign: 0.5089 miou: 0.6560 acc: 0.9223 acc_cls: 0.7523 data_time: 0.0045 time: 0.3213 2023/04/25 19:42:46 - mmengine - INFO - Epoch(train) [23][ 50/1196] lr: 8.0000e-03 eta: 3:40:49 time: 0.7731 data_time: 0.0047 memory: 3237 grad_norm: 0.0939 loss: 0.2137 loss_sem_seg: 0.2137 2023/04/25 19:43:26 - mmengine - INFO - Epoch(train) [23][ 100/1196] lr: 8.0000e-03 eta: 3:40:10 time: 0.7938 data_time: 0.0037 memory: 3338 grad_norm: 0.0906 loss: 0.2087 loss_sem_seg: 0.2087 2023/04/25 19:44:06 - mmengine - INFO - Epoch(train) [23][ 150/1196] lr: 8.0000e-03 eta: 3:39:30 time: 0.7940 data_time: 0.0034 memory: 3145 grad_norm: 0.0852 loss: 0.1901 loss_sem_seg: 0.1901 2023/04/25 19:44:46 - mmengine - INFO - Epoch(train) [23][ 200/1196] lr: 8.0000e-03 eta: 3:38:50 time: 0.7992 data_time: 0.0034 memory: 3123 grad_norm: 0.1118 loss: 0.2183 loss_sem_seg: 0.2183 2023/04/25 19:45:25 - mmengine - INFO - Epoch(train) [23][ 250/1196] lr: 8.0000e-03 eta: 3:38:11 time: 0.7926 data_time: 0.0036 memory: 3357 grad_norm: 0.0936 loss: 0.2141 loss_sem_seg: 0.2141 2023/04/25 19:46:04 - mmengine - INFO - Epoch(train) [23][ 300/1196] lr: 8.0000e-03 eta: 3:37:30 time: 0.7740 data_time: 0.0035 memory: 3409 grad_norm: 0.0933 loss: 0.2145 loss_sem_seg: 0.2145 2023/04/25 19:46:43 - mmengine - INFO - Epoch(train) [23][ 350/1196] lr: 8.0000e-03 eta: 3:36:51 time: 0.7915 data_time: 0.0035 memory: 3181 grad_norm: 0.0966 loss: 0.2185 loss_sem_seg: 0.2185 2023/04/25 19:47:22 - mmengine - INFO - Epoch(train) [23][ 400/1196] lr: 8.0000e-03 eta: 3:36:10 time: 0.7769 data_time: 0.0035 memory: 3156 grad_norm: 0.1027 loss: 0.2099 loss_sem_seg: 0.2099 2023/04/25 19:48:02 - mmengine - INFO - Epoch(train) [23][ 450/1196] lr: 8.0000e-03 eta: 3:35:31 time: 0.8030 data_time: 0.0035 memory: 3237 grad_norm: 0.1124 loss: 0.2285 loss_sem_seg: 0.2285 2023/04/25 19:48:44 - mmengine - INFO - Epoch(train) [23][ 500/1196] lr: 8.0000e-03 eta: 3:34:52 time: 0.8278 data_time: 0.0037 memory: 3170 grad_norm: 0.1066 loss: 0.2163 loss_sem_seg: 0.2163 2023/04/25 19:49:23 - mmengine - INFO - Epoch(train) [23][ 550/1196] lr: 8.0000e-03 eta: 3:34:12 time: 0.7727 data_time: 0.0036 memory: 3127 grad_norm: 0.0927 loss: 0.2112 loss_sem_seg: 0.2112 2023/04/25 19:50:02 - mmengine - INFO - Epoch(train) [23][ 600/1196] lr: 8.0000e-03 eta: 3:33:32 time: 0.7928 data_time: 0.0035 memory: 3083 grad_norm: 0.1006 loss: 0.2179 loss_sem_seg: 0.2179 2023/04/25 19:50:41 - mmengine - INFO - Epoch(train) [23][ 650/1196] lr: 8.0000e-03 eta: 3:32:52 time: 0.7810 data_time: 0.0037 memory: 3090 grad_norm: 0.0989 loss: 0.2144 loss_sem_seg: 0.2144 2023/04/25 19:51:12 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 19:51:22 - mmengine - INFO - Epoch(train) [23][ 700/1196] lr: 8.0000e-03 eta: 3:32:13 time: 0.8103 data_time: 0.0037 memory: 3734 grad_norm: 0.0953 loss: 0.2369 loss_sem_seg: 0.2369 2023/04/25 19:52:01 - mmengine - INFO - Epoch(train) [23][ 750/1196] lr: 8.0000e-03 eta: 3:31:33 time: 0.7911 data_time: 0.0036 memory: 3192 grad_norm: 0.0932 loss: 0.2135 loss_sem_seg: 0.2135 2023/04/25 19:52:41 - mmengine - INFO - Epoch(train) [23][ 800/1196] lr: 8.0000e-03 eta: 3:30:54 time: 0.7953 data_time: 0.0039 memory: 3090 grad_norm: 0.1059 loss: 0.1999 loss_sem_seg: 0.1999 2023/04/25 19:53:21 - mmengine - INFO - Epoch(train) [23][ 850/1196] lr: 8.0000e-03 eta: 3:30:14 time: 0.7921 data_time: 0.0035 memory: 3213 grad_norm: 0.1001 loss: 0.2130 loss_sem_seg: 0.2130 2023/04/25 19:53:59 - mmengine - INFO - Epoch(train) [23][ 900/1196] lr: 8.0000e-03 eta: 3:29:33 time: 0.7652 data_time: 0.0034 memory: 3414 grad_norm: 0.1012 loss: 0.2287 loss_sem_seg: 0.2287 2023/04/25 19:54:39 - mmengine - INFO - Epoch(train) [23][ 950/1196] lr: 8.0000e-03 eta: 3:28:54 time: 0.7913 data_time: 0.0035 memory: 3596 grad_norm: 0.0987 loss: 0.2063 loss_sem_seg: 0.2063 2023/04/25 19:55:18 - mmengine - INFO - Epoch(train) [23][1000/1196] lr: 8.0000e-03 eta: 3:28:14 time: 0.7971 data_time: 0.0034 memory: 3163 grad_norm: 0.0906 loss: 0.2192 loss_sem_seg: 0.2192 2023/04/25 19:55:58 - mmengine - INFO - Epoch(train) [23][1050/1196] lr: 8.0000e-03 eta: 3:27:34 time: 0.7869 data_time: 0.0036 memory: 3328 grad_norm: 0.1066 loss: 0.2142 loss_sem_seg: 0.2142 2023/04/25 19:56:39 - mmengine - INFO - Epoch(train) [23][1100/1196] lr: 8.0000e-03 eta: 3:26:55 time: 0.8216 data_time: 0.0035 memory: 3381 grad_norm: 0.1023 loss: 0.2140 loss_sem_seg: 0.2140 2023/04/25 19:57:18 - mmengine - INFO - Epoch(train) [23][1150/1196] lr: 8.0000e-03 eta: 3:26:15 time: 0.7809 data_time: 0.0038 memory: 3253 grad_norm: 0.1062 loss: 0.2026 loss_sem_seg: 0.2026 2023/04/25 19:57:55 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 19:57:55 - mmengine - INFO - Saving checkpoint at 23 epochs 2023/04/25 19:58:12 - mmengine - INFO - Epoch(val) [23][ 50/509] eta: 0:01:49 time: 0.2375 data_time: 0.0060 memory: 3334 2023/04/25 19:58:22 - mmengine - INFO - Epoch(val) [23][100/509] eta: 0:01:31 time: 0.2101 data_time: 0.0050 memory: 840 2023/04/25 19:58:31 - mmengine - INFO - Epoch(val) [23][150/509] eta: 0:01:14 time: 0.1768 data_time: 0.0056 memory: 843 2023/04/25 19:58:41 - mmengine - INFO - Epoch(val) [23][200/509] eta: 0:01:04 time: 0.2074 data_time: 0.0053 memory: 834 2023/04/25 19:58:52 - mmengine - INFO - Epoch(val) [23][250/509] eta: 0:00:54 time: 0.2120 data_time: 0.0057 memory: 850 2023/04/25 19:59:01 - mmengine - INFO - Epoch(val) [23][300/509] eta: 0:00:42 time: 0.1853 data_time: 0.0055 memory: 812 2023/04/25 19:59:11 - mmengine - INFO - Epoch(val) [23][350/509] eta: 0:00:32 time: 0.1953 data_time: 0.0055 memory: 825 2023/04/25 19:59:23 - mmengine - INFO - Epoch(val) [23][400/509] eta: 0:00:22 time: 0.2366 data_time: 0.0049 memory: 827 2023/04/25 19:59:34 - mmengine - INFO - Epoch(val) [23][450/509] eta: 0:00:12 time: 0.2117 data_time: 0.0053 memory: 845 2023/04/25 19:59:50 - mmengine - INFO - Epoch(val) [23][500/509] eta: 0:00:01 time: 0.3259 data_time: 0.0046 memory: 832 2023/04/25 20:00:13 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9727 | 0.5105 | 0.7506 | 0.6583 | 0.6778 | 0.7482 | 0.8843 | 0.0188 | 0.9372 | 0.4354 | 0.8099 | 0.0059 | 0.9135 | 0.6631 | 0.8862 | 0.6300 | 0.7591 | 0.6471 | 0.5224 | 0.6543 | 0.9231 | 0.7340 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 20:00:13 - mmengine - INFO - Epoch(val) [23][509/509] car: 0.9727 bicycle: 0.5105 motorcycle: 0.7506 truck: 0.6583 bus: 0.6778 person: 0.7482 bicyclist: 0.8843 motorcyclist: 0.0188 road: 0.9372 parking: 0.4354 sidewalk: 0.8099 other-ground: 0.0059 building: 0.9135 fence: 0.6631 vegetation: 0.8862 trunck: 0.6300 terrian: 0.7591 pole: 0.6471 traffic-sign: 0.5224 miou: 0.6543 acc: 0.9231 acc_cls: 0.7340 data_time: 0.0043 time: 0.3369 2023/04/25 20:00:54 - mmengine - INFO - Epoch(train) [24][ 50/1196] lr: 8.0000e-03 eta: 3:25:00 time: 0.8096 data_time: 0.0045 memory: 3268 grad_norm: 0.0916 loss: 0.2086 loss_sem_seg: 0.2086 2023/04/25 20:01:35 - mmengine - INFO - Epoch(train) [24][ 100/1196] lr: 8.0000e-03 eta: 3:24:21 time: 0.8239 data_time: 0.0035 memory: 3121 grad_norm: 0.0982 loss: 0.2131 loss_sem_seg: 0.2131 2023/04/25 20:02:15 - mmengine - INFO - Epoch(train) [24][ 150/1196] lr: 8.0000e-03 eta: 3:23:42 time: 0.7903 data_time: 0.0036 memory: 3113 grad_norm: 0.0988 loss: 0.2116 loss_sem_seg: 0.2116 2023/04/25 20:02:55 - mmengine - INFO - Epoch(train) [24][ 200/1196] lr: 8.0000e-03 eta: 3:23:02 time: 0.8045 data_time: 0.0035 memory: 3107 grad_norm: 0.1024 loss: 0.2096 loss_sem_seg: 0.2096 2023/04/25 20:03:35 - mmengine - INFO - Epoch(train) [24][ 250/1196] lr: 8.0000e-03 eta: 3:22:23 time: 0.7986 data_time: 0.0036 memory: 3155 grad_norm: 0.0989 loss: 0.2091 loss_sem_seg: 0.2091 2023/04/25 20:04:14 - mmengine - INFO - Epoch(train) [24][ 300/1196] lr: 8.0000e-03 eta: 3:21:42 time: 0.7732 data_time: 0.0036 memory: 3182 grad_norm: 0.0942 loss: 0.1950 loss_sem_seg: 0.1950 2023/04/25 20:04:54 - mmengine - INFO - Epoch(train) [24][ 350/1196] lr: 8.0000e-03 eta: 3:21:03 time: 0.8006 data_time: 0.0037 memory: 3463 grad_norm: 0.0922 loss: 0.1984 loss_sem_seg: 0.1984 2023/04/25 20:05:33 - mmengine - INFO - Epoch(train) [24][ 400/1196] lr: 8.0000e-03 eta: 3:20:23 time: 0.7922 data_time: 0.0036 memory: 3456 grad_norm: 0.0919 loss: 0.2151 loss_sem_seg: 0.2151 2023/04/25 20:06:14 - mmengine - INFO - Epoch(train) [24][ 450/1196] lr: 8.0000e-03 eta: 3:19:44 time: 0.8163 data_time: 0.0036 memory: 3279 grad_norm: 0.1005 loss: 0.2168 loss_sem_seg: 0.2168 2023/04/25 20:06:47 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 20:06:53 - mmengine - INFO - Epoch(train) [24][ 500/1196] lr: 8.0000e-03 eta: 3:19:04 time: 0.7885 data_time: 0.0039 memory: 3146 grad_norm: 0.0984 loss: 0.2113 loss_sem_seg: 0.2113 2023/04/25 20:07:34 - mmengine - INFO - Epoch(train) [24][ 550/1196] lr: 8.0000e-03 eta: 3:18:25 time: 0.8064 data_time: 0.0040 memory: 3193 grad_norm: 0.1040 loss: 0.2126 loss_sem_seg: 0.2126 2023/04/25 20:08:13 - mmengine - INFO - Epoch(train) [24][ 600/1196] lr: 8.0000e-03 eta: 3:17:45 time: 0.7950 data_time: 0.0040 memory: 3310 grad_norm: 0.1059 loss: 0.2407 loss_sem_seg: 0.2407 2023/04/25 20:08:53 - mmengine - INFO - Epoch(train) [24][ 650/1196] lr: 8.0000e-03 eta: 3:17:06 time: 0.7971 data_time: 0.0041 memory: 3199 grad_norm: 0.0940 loss: 0.2080 loss_sem_seg: 0.2080 2023/04/25 20:09:34 - mmengine - INFO - Epoch(train) [24][ 700/1196] lr: 8.0000e-03 eta: 3:16:27 time: 0.8219 data_time: 0.0038 memory: 3298 grad_norm: 0.0937 loss: 0.2225 loss_sem_seg: 0.2225 2023/04/25 20:10:16 - mmengine - INFO - Epoch(train) [24][ 750/1196] lr: 8.0000e-03 eta: 3:15:48 time: 0.8241 data_time: 0.0039 memory: 3260 grad_norm: 0.0921 loss: 0.2021 loss_sem_seg: 0.2021 2023/04/25 20:10:54 - mmengine - INFO - Epoch(train) [24][ 800/1196] lr: 8.0000e-03 eta: 3:15:07 time: 0.7697 data_time: 0.0041 memory: 3385 grad_norm: 0.0969 loss: 0.2114 loss_sem_seg: 0.2114 2023/04/25 20:11:34 - mmengine - INFO - Epoch(train) [24][ 850/1196] lr: 8.0000e-03 eta: 3:14:28 time: 0.7992 data_time: 0.0041 memory: 3411 grad_norm: 0.0943 loss: 0.2063 loss_sem_seg: 0.2063 2023/04/25 20:12:15 - mmengine - INFO - Epoch(train) [24][ 900/1196] lr: 8.0000e-03 eta: 3:13:49 time: 0.8080 data_time: 0.0040 memory: 3234 grad_norm: 0.0891 loss: 0.2048 loss_sem_seg: 0.2048 2023/04/25 20:12:54 - mmengine - INFO - Epoch(train) [24][ 950/1196] lr: 8.0000e-03 eta: 3:13:09 time: 0.7939 data_time: 0.0040 memory: 3147 grad_norm: 0.1059 loss: 0.2094 loss_sem_seg: 0.2094 2023/04/25 20:13:35 - mmengine - INFO - Epoch(train) [24][1000/1196] lr: 8.0000e-03 eta: 3:12:30 time: 0.8221 data_time: 0.0039 memory: 3443 grad_norm: 0.0928 loss: 0.2101 loss_sem_seg: 0.2101 2023/04/25 20:14:17 - mmengine - INFO - Epoch(train) [24][1050/1196] lr: 8.0000e-03 eta: 3:11:51 time: 0.8273 data_time: 0.0039 memory: 3282 grad_norm: 0.0971 loss: 0.2122 loss_sem_seg: 0.2122 2023/04/25 20:14:56 - mmengine - INFO - Epoch(train) [24][1100/1196] lr: 8.0000e-03 eta: 3:11:11 time: 0.7812 data_time: 0.0038 memory: 3250 grad_norm: 0.0889 loss: 0.2087 loss_sem_seg: 0.2087 2023/04/25 20:15:36 - mmengine - INFO - Epoch(train) [24][1150/1196] lr: 8.0000e-03 eta: 3:10:32 time: 0.8122 data_time: 0.0039 memory: 3388 grad_norm: inf loss: 0.2148 loss_sem_seg: 0.2148 2023/04/25 20:16:13 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 20:16:13 - mmengine - INFO - Saving checkpoint at 24 epochs 2023/04/25 20:16:30 - mmengine - INFO - Epoch(val) [24][ 50/509] eta: 0:02:00 time: 0.2623 data_time: 0.0054 memory: 3203 2023/04/25 20:16:41 - mmengine - INFO - Epoch(val) [24][100/509] eta: 0:01:37 time: 0.2149 data_time: 0.0045 memory: 840 2023/04/25 20:16:52 - mmengine - INFO - Epoch(val) [24][150/509] eta: 0:01:24 time: 0.2315 data_time: 0.0049 memory: 843 2023/04/25 20:17:02 - mmengine - INFO - Epoch(val) [24][200/509] eta: 0:01:09 time: 0.1882 data_time: 0.0055 memory: 834 2023/04/25 20:17:13 - mmengine - INFO - Epoch(val) [24][250/509] eta: 0:00:57 time: 0.2222 data_time: 0.0052 memory: 850 2023/04/25 20:17:25 - mmengine - INFO - Epoch(val) [24][300/509] eta: 0:00:47 time: 0.2340 data_time: 0.0045 memory: 812 2023/04/25 20:17:37 - mmengine - INFO - Epoch(val) [24][350/509] eta: 0:00:36 time: 0.2418 data_time: 0.0050 memory: 825 2023/04/25 20:17:46 - mmengine - INFO - Epoch(val) [24][400/509] eta: 0:00:24 time: 0.1758 data_time: 0.0044 memory: 827 2023/04/25 20:17:56 - mmengine - INFO - Epoch(val) [24][450/509] eta: 0:00:12 time: 0.2027 data_time: 0.0052 memory: 845 2023/04/25 20:18:14 - mmengine - INFO - Epoch(val) [24][500/509] eta: 0:00:02 time: 0.3580 data_time: 0.0046 memory: 832 2023/04/25 20:18:41 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9647 | 0.5072 | 0.7708 | 0.6346 | 0.6209 | 0.7860 | 0.8643 | 0.0126 | 0.9320 | 0.4440 | 0.8049 | 0.0348 | 0.9136 | 0.6414 | 0.8920 | 0.6701 | 0.7692 | 0.6517 | 0.5139 | 0.6541 | 0.9231 | 0.7328 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 20:18:41 - mmengine - INFO - Epoch(val) [24][509/509] car: 0.9647 bicycle: 0.5072 motorcycle: 0.7708 truck: 0.6346 bus: 0.6209 person: 0.7860 bicyclist: 0.8643 motorcyclist: 0.0126 road: 0.9320 parking: 0.4440 sidewalk: 0.8049 other-ground: 0.0348 building: 0.9136 fence: 0.6414 vegetation: 0.8920 trunck: 0.6701 terrian: 0.7692 pole: 0.6517 traffic-sign: 0.5139 miou: 0.6541 acc: 0.9231 acc_cls: 0.7328 data_time: 0.0045 time: 0.3311 2023/04/25 20:19:21 - mmengine - INFO - Epoch(train) [25][ 50/1196] lr: 8.0000e-04 eta: 3:09:15 time: 0.7848 data_time: 0.0046 memory: 3003 grad_norm: 0.0681 loss: 0.1885 loss_sem_seg: 0.1885 2023/04/25 20:20:00 - mmengine - INFO - Epoch(train) [25][ 100/1196] lr: 8.0000e-04 eta: 3:08:35 time: 0.7868 data_time: 0.0035 memory: 3302 grad_norm: 0.0689 loss: 0.2017 loss_sem_seg: 0.2017 2023/04/25 20:20:40 - mmengine - INFO - Epoch(train) [25][ 150/1196] lr: 8.0000e-04 eta: 3:07:56 time: 0.8078 data_time: 0.0036 memory: 3320 grad_norm: 0.0679 loss: 0.1856 loss_sem_seg: 0.1856 2023/04/25 20:21:20 - mmengine - INFO - Epoch(train) [25][ 200/1196] lr: 8.0000e-04 eta: 3:07:16 time: 0.7837 data_time: 0.0035 memory: 3130 grad_norm: 0.0618 loss: 0.1936 loss_sem_seg: 0.1936 2023/04/25 20:22:00 - mmengine - INFO - Epoch(train) [25][ 250/1196] lr: 8.0000e-04 eta: 3:06:37 time: 0.8162 data_time: 0.0035 memory: 3185 grad_norm: 0.0621 loss: 0.1927 loss_sem_seg: 0.1927 2023/04/25 20:22:36 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 20:22:41 - mmengine - INFO - Epoch(train) [25][ 300/1196] lr: 8.0000e-04 eta: 3:05:57 time: 0.8016 data_time: 0.0035 memory: 3192 grad_norm: 0.0629 loss: 0.1709 loss_sem_seg: 0.1709 2023/04/25 20:23:20 - mmengine - INFO - Epoch(train) [25][ 350/1196] lr: 8.0000e-04 eta: 3:05:18 time: 0.7939 data_time: 0.0035 memory: 3282 grad_norm: 0.0638 loss: 0.1758 loss_sem_seg: 0.1758 2023/04/25 20:24:00 - mmengine - INFO - Epoch(train) [25][ 400/1196] lr: 8.0000e-04 eta: 3:04:38 time: 0.7859 data_time: 0.0036 memory: 3237 grad_norm: 0.0688 loss: 0.1835 loss_sem_seg: 0.1835 2023/04/25 20:24:38 - mmengine - INFO - Epoch(train) [25][ 450/1196] lr: 8.0000e-04 eta: 3:03:57 time: 0.7627 data_time: 0.0036 memory: 3419 grad_norm: 0.0687 loss: 0.1738 loss_sem_seg: 0.1738 2023/04/25 20:25:17 - mmengine - INFO - Epoch(train) [25][ 500/1196] lr: 8.0000e-04 eta: 3:03:17 time: 0.7900 data_time: 0.0036 memory: 3312 grad_norm: 0.0658 loss: 0.1813 loss_sem_seg: 0.1813 2023/04/25 20:25:57 - mmengine - INFO - Epoch(train) [25][ 550/1196] lr: 8.0000e-04 eta: 3:02:38 time: 0.8043 data_time: 0.0034 memory: 3537 grad_norm: 0.0627 loss: 0.1843 loss_sem_seg: 0.1843 2023/04/25 20:26:37 - mmengine - INFO - Epoch(train) [25][ 600/1196] lr: 8.0000e-04 eta: 3:01:58 time: 0.7881 data_time: 0.0035 memory: 3022 grad_norm: 0.0656 loss: 0.1821 loss_sem_seg: 0.1821 2023/04/25 20:27:18 - mmengine - INFO - Epoch(train) [25][ 650/1196] lr: 8.0000e-04 eta: 3:01:19 time: 0.8240 data_time: 0.0035 memory: 3242 grad_norm: 0.0654 loss: 0.1882 loss_sem_seg: 0.1882 2023/04/25 20:27:58 - mmengine - INFO - Epoch(train) [25][ 700/1196] lr: 8.0000e-04 eta: 3:00:40 time: 0.8075 data_time: 0.0037 memory: 3106 grad_norm: 0.0626 loss: 0.1822 loss_sem_seg: 0.1822 2023/04/25 20:28:38 - mmengine - INFO - Epoch(train) [25][ 750/1196] lr: 8.0000e-04 eta: 3:00:00 time: 0.7936 data_time: 0.0037 memory: 3132 grad_norm: 0.0610 loss: 0.1818 loss_sem_seg: 0.1818 2023/04/25 20:29:18 - mmengine - INFO - Epoch(train) [25][ 800/1196] lr: 8.0000e-04 eta: 2:59:20 time: 0.7909 data_time: 0.0038 memory: 3538 grad_norm: 0.0642 loss: 0.1740 loss_sem_seg: 0.1740 2023/04/25 20:29:58 - mmengine - INFO - Epoch(train) [25][ 850/1196] lr: 8.0000e-04 eta: 2:58:41 time: 0.8059 data_time: 0.0040 memory: 3308 grad_norm: 0.0606 loss: 0.1715 loss_sem_seg: 0.1715 2023/04/25 20:30:36 - mmengine - INFO - Epoch(train) [25][ 900/1196] lr: 8.0000e-04 eta: 2:58:00 time: 0.7636 data_time: 0.0037 memory: 3540 grad_norm: 0.0659 loss: 0.1829 loss_sem_seg: 0.1829 2023/04/25 20:31:17 - mmengine - INFO - Epoch(train) [25][ 950/1196] lr: 8.0000e-04 eta: 2:57:21 time: 0.8266 data_time: 0.0040 memory: 3235 grad_norm: 0.0650 loss: 0.1759 loss_sem_seg: 0.1759 2023/04/25 20:31:57 - mmengine - INFO - Epoch(train) [25][1000/1196] lr: 8.0000e-04 eta: 2:56:42 time: 0.7815 data_time: 0.0039 memory: 2916 grad_norm: 0.0621 loss: 0.1661 loss_sem_seg: 0.1661 2023/04/25 20:32:35 - mmengine - INFO - Epoch(train) [25][1050/1196] lr: 8.0000e-04 eta: 2:56:01 time: 0.7776 data_time: 0.0040 memory: 3527 grad_norm: 0.0632 loss: 0.1747 loss_sem_seg: 0.1747 2023/04/25 20:33:15 - mmengine - INFO - Epoch(train) [25][1100/1196] lr: 8.0000e-04 eta: 2:55:22 time: 0.7924 data_time: 0.0040 memory: 3232 grad_norm: 0.0629 loss: 0.1662 loss_sem_seg: 0.1662 2023/04/25 20:33:55 - mmengine - INFO - Epoch(train) [25][1150/1196] lr: 8.0000e-04 eta: 2:54:42 time: 0.7926 data_time: 0.0041 memory: 3428 grad_norm: 0.0630 loss: 0.1796 loss_sem_seg: 0.1796 2023/04/25 20:34:32 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 20:34:32 - mmengine - INFO - Saving checkpoint at 25 epochs 2023/04/25 20:34:48 - mmengine - INFO - Epoch(val) [25][ 50/509] eta: 0:01:46 time: 0.2329 data_time: 0.0057 memory: 3284 2023/04/25 20:35:01 - mmengine - INFO - Epoch(val) [25][100/509] eta: 0:01:40 time: 0.2591 data_time: 0.0052 memory: 840 2023/04/25 20:35:12 - mmengine - INFO - Epoch(val) [25][150/509] eta: 0:01:26 time: 0.2319 data_time: 0.0053 memory: 843 2023/04/25 20:35:21 - mmengine - INFO - Epoch(val) [25][200/509] eta: 0:01:10 time: 0.1841 data_time: 0.0048 memory: 834 2023/04/25 20:35:31 - mmengine - INFO - Epoch(val) [25][250/509] eta: 0:00:56 time: 0.1889 data_time: 0.0051 memory: 850 2023/04/25 20:35:42 - mmengine - INFO - Epoch(val) [25][300/509] eta: 0:00:45 time: 0.2155 data_time: 0.0049 memory: 812 2023/04/25 20:35:51 - mmengine - INFO - Epoch(val) [25][350/509] eta: 0:00:34 time: 0.1895 data_time: 0.0054 memory: 825 2023/04/25 20:36:01 - mmengine - INFO - Epoch(val) [25][400/509] eta: 0:00:23 time: 0.1874 data_time: 0.0049 memory: 827 2023/04/25 20:36:11 - mmengine - INFO - Epoch(val) [25][450/509] eta: 0:00:12 time: 0.2036 data_time: 0.0054 memory: 845 2023/04/25 20:36:27 - mmengine - INFO - Epoch(val) [25][500/509] eta: 0:00:01 time: 0.3202 data_time: 0.0046 memory: 832 2023/04/25 20:36:52 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9732 | 0.5628 | 0.7926 | 0.7385 | 0.7804 | 0.7892 | 0.9090 | 0.0401 | 0.9449 | 0.5183 | 0.8242 | 0.0052 | 0.9142 | 0.6666 | 0.8825 | 0.6901 | 0.7426 | 0.6575 | 0.5246 | 0.6819 | 0.9247 | 0.7555 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 20:36:52 - mmengine - INFO - Epoch(val) [25][509/509] car: 0.9732 bicycle: 0.5628 motorcycle: 0.7926 truck: 0.7385 bus: 0.7804 person: 0.7892 bicyclist: 0.9090 motorcyclist: 0.0401 road: 0.9449 parking: 0.5183 sidewalk: 0.8242 other-ground: 0.0052 building: 0.9142 fence: 0.6666 vegetation: 0.8825 trunck: 0.6901 terrian: 0.7426 pole: 0.6575 traffic-sign: 0.5246 miou: 0.6819 acc: 0.9247 acc_cls: 0.7555 data_time: 0.0043 time: 0.3218 2023/04/25 20:37:32 - mmengine - INFO - Epoch(train) [26][ 50/1196] lr: 8.0000e-04 eta: 2:53:26 time: 0.8057 data_time: 0.0046 memory: 3258 grad_norm: 0.0619 loss: 0.1750 loss_sem_seg: 0.1750 2023/04/25 20:38:13 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 20:38:13 - mmengine - INFO - Epoch(train) [26][ 100/1196] lr: 8.0000e-04 eta: 2:52:47 time: 0.8089 data_time: 0.0035 memory: 3369 grad_norm: 0.0658 loss: 0.1821 loss_sem_seg: 0.1821 2023/04/25 20:38:53 - mmengine - INFO - Epoch(train) [26][ 150/1196] lr: 8.0000e-04 eta: 2:52:08 time: 0.8125 data_time: 0.0036 memory: 3164 grad_norm: 0.0636 loss: 0.1750 loss_sem_seg: 0.1750 2023/04/25 20:39:33 - mmengine - INFO - Epoch(train) [26][ 200/1196] lr: 8.0000e-04 eta: 2:51:28 time: 0.7851 data_time: 0.0035 memory: 3183 grad_norm: 0.0627 loss: 0.1812 loss_sem_seg: 0.1812 2023/04/25 20:40:13 - mmengine - INFO - Epoch(train) [26][ 250/1196] lr: 8.0000e-04 eta: 2:50:48 time: 0.8012 data_time: 0.0034 memory: 3300 grad_norm: 0.0644 loss: 0.1668 loss_sem_seg: 0.1668 2023/04/25 20:40:53 - mmengine - INFO - Epoch(train) [26][ 300/1196] lr: 8.0000e-04 eta: 2:50:09 time: 0.8011 data_time: 0.0035 memory: 3128 grad_norm: 0.0614 loss: 0.1674 loss_sem_seg: 0.1674 2023/04/25 20:41:31 - mmengine - INFO - Epoch(train) [26][ 350/1196] lr: 8.0000e-04 eta: 2:49:28 time: 0.7728 data_time: 0.0034 memory: 3229 grad_norm: 0.0673 loss: 0.1767 loss_sem_seg: 0.1767 2023/04/25 20:42:12 - mmengine - INFO - Epoch(train) [26][ 400/1196] lr: 8.0000e-04 eta: 2:48:49 time: 0.8165 data_time: 0.0036 memory: 3199 grad_norm: 0.0636 loss: 0.1733 loss_sem_seg: 0.1733 2023/04/25 20:42:53 - mmengine - INFO - Epoch(train) [26][ 450/1196] lr: 8.0000e-04 eta: 2:48:10 time: 0.8071 data_time: 0.0035 memory: 3225 grad_norm: 0.0650 loss: 0.1867 loss_sem_seg: 0.1867 2023/04/25 20:43:31 - mmengine - INFO - Epoch(train) [26][ 500/1196] lr: 8.0000e-04 eta: 2:47:29 time: 0.7590 data_time: 0.0036 memory: 3062 grad_norm: 0.0641 loss: 0.1743 loss_sem_seg: 0.1743 2023/04/25 20:44:11 - mmengine - INFO - Epoch(train) [26][ 550/1196] lr: 8.0000e-04 eta: 2:46:50 time: 0.8070 data_time: 0.0035 memory: 3415 grad_norm: 0.0677 loss: 0.1795 loss_sem_seg: 0.1795 2023/04/25 20:44:53 - mmengine - INFO - Epoch(train) [26][ 600/1196] lr: 8.0000e-04 eta: 2:46:11 time: 0.8401 data_time: 0.0036 memory: 3302 grad_norm: 0.0704 loss: 0.1888 loss_sem_seg: 0.1888 2023/04/25 20:45:33 - mmengine - INFO - Epoch(train) [26][ 650/1196] lr: 8.0000e-04 eta: 2:45:32 time: 0.8096 data_time: 0.0035 memory: 3397 grad_norm: 0.0629 loss: 0.1694 loss_sem_seg: 0.1694 2023/04/25 20:46:15 - mmengine - INFO - Epoch(train) [26][ 700/1196] lr: 8.0000e-04 eta: 2:44:53 time: 0.8225 data_time: 0.0035 memory: 3648 grad_norm: 0.0661 loss: 0.1691 loss_sem_seg: 0.1691 2023/04/25 20:46:55 - mmengine - INFO - Epoch(train) [26][ 750/1196] lr: 8.0000e-04 eta: 2:44:13 time: 0.8139 data_time: 0.0036 memory: 3204 grad_norm: 0.0672 loss: 0.1635 loss_sem_seg: 0.1635 2023/04/25 20:47:35 - mmengine - INFO - Epoch(train) [26][ 800/1196] lr: 8.0000e-04 eta: 2:43:34 time: 0.7972 data_time: 0.0036 memory: 3220 grad_norm: 0.0670 loss: 0.1742 loss_sem_seg: 0.1742 2023/04/25 20:48:16 - mmengine - INFO - Epoch(train) [26][ 850/1196] lr: 8.0000e-04 eta: 2:42:54 time: 0.8163 data_time: 0.0036 memory: 3312 grad_norm: 0.0667 loss: 0.1717 loss_sem_seg: 0.1717 2023/04/25 20:48:56 - mmengine - INFO - Epoch(train) [26][ 900/1196] lr: 8.0000e-04 eta: 2:42:15 time: 0.8090 data_time: 0.0034 memory: 3504 grad_norm: 0.0679 loss: 0.1659 loss_sem_seg: 0.1659 2023/04/25 20:49:20 - mmengine - INFO - Epoch(train) [26][ 950/1196] lr: 8.0000e-04 eta: 2:41:29 time: 0.4633 data_time: 0.0035 memory: 3199 grad_norm: 0.0661 loss: 0.1803 loss_sem_seg: 0.1803 2023/04/25 20:49:37 - mmengine - INFO - Epoch(train) [26][1000/1196] lr: 8.0000e-04 eta: 2:40:40 time: 0.3569 data_time: 0.0033 memory: 3068 grad_norm: 0.0661 loss: 0.1733 loss_sem_seg: 0.1733 2023/04/25 20:49:55 - mmengine - INFO - Epoch(train) [26][1050/1196] lr: 8.0000e-04 eta: 2:39:52 time: 0.3567 data_time: 0.0033 memory: 3183 grad_norm: 0.0685 loss: 0.1869 loss_sem_seg: 0.1869 2023/04/25 20:50:13 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 20:50:13 - mmengine - INFO - Epoch(train) [26][1100/1196] lr: 8.0000e-04 eta: 2:39:04 time: 0.3547 data_time: 0.0032 memory: 3036 grad_norm: 0.0656 loss: 0.1696 loss_sem_seg: 0.1696 2023/04/25 20:50:31 - mmengine - INFO - Epoch(train) [26][1150/1196] lr: 8.0000e-04 eta: 2:38:16 time: 0.3580 data_time: 0.0034 memory: 3167 grad_norm: 0.0676 loss: 0.1691 loss_sem_seg: 0.1691 2023/04/25 20:50:47 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 20:50:47 - mmengine - INFO - Saving checkpoint at 26 epochs 2023/04/25 20:50:56 - mmengine - INFO - Epoch(val) [26][ 50/509] eta: 0:00:38 time: 0.0828 data_time: 0.0047 memory: 3364 2023/04/25 20:51:00 - mmengine - INFO - Epoch(val) [26][100/509] eta: 0:00:33 time: 0.0790 data_time: 0.0045 memory: 840 2023/04/25 20:51:04 - mmengine - INFO - Epoch(val) [26][150/509] eta: 0:00:28 time: 0.0783 data_time: 0.0049 memory: 843 2023/04/25 20:51:08 - mmengine - INFO - Epoch(val) [26][200/509] eta: 0:00:24 time: 0.0786 data_time: 0.0046 memory: 834 2023/04/25 20:51:12 - mmengine - INFO - Epoch(val) [26][250/509] eta: 0:00:20 time: 0.0809 data_time: 0.0051 memory: 850 2023/04/25 20:51:16 - mmengine - INFO - Epoch(val) [26][300/509] eta: 0:00:16 time: 0.0754 data_time: 0.0047 memory: 812 2023/04/25 20:51:20 - mmengine - INFO - Epoch(val) [26][350/509] eta: 0:00:12 time: 0.0782 data_time: 0.0049 memory: 825 2023/04/25 20:51:24 - mmengine - INFO - Epoch(val) [26][400/509] eta: 0:00:08 time: 0.0804 data_time: 0.0047 memory: 827 2023/04/25 20:51:28 - mmengine - INFO - Epoch(val) [26][450/509] eta: 0:00:04 time: 0.0831 data_time: 0.0051 memory: 845 2023/04/25 20:51:39 - mmengine - INFO - Epoch(val) [26][500/509] eta: 0:00:00 time: 0.2217 data_time: 0.0045 memory: 832 2023/04/25 20:52:25 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9743 | 0.5613 | 0.7979 | 0.7853 | 0.7867 | 0.7977 | 0.8943 | 0.0155 | 0.9474 | 0.4997 | 0.8262 | 0.0010 | 0.9152 | 0.6645 | 0.8842 | 0.6868 | 0.7507 | 0.6620 | 0.5255 | 0.6830 | 0.9259 | 0.7550 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 20:52:25 - mmengine - INFO - Epoch(val) [26][509/509] car: 0.9743 bicycle: 0.5613 motorcycle: 0.7979 truck: 0.7853 bus: 0.7867 person: 0.7977 bicyclist: 0.8943 motorcyclist: 0.0155 road: 0.9474 parking: 0.4997 sidewalk: 0.8262 other-ground: 0.0010 building: 0.9152 fence: 0.6645 vegetation: 0.8842 trunck: 0.6868 terrian: 0.7507 pole: 0.6620 traffic-sign: 0.5255 miou: 0.6830 acc: 0.9259 acc_cls: 0.7550 data_time: 0.0042 time: 0.2871 2023/04/25 20:53:06 - mmengine - INFO - Epoch(train) [27][ 50/1196] lr: 8.0000e-04 eta: 2:36:53 time: 0.8093 data_time: 0.0048 memory: 3088 grad_norm: 0.0627 loss: 0.1646 loss_sem_seg: 0.1646 2023/04/25 20:53:46 - mmengine - INFO - Epoch(train) [27][ 100/1196] lr: 8.0000e-04 eta: 2:36:14 time: 0.7979 data_time: 0.0036 memory: 3296 grad_norm: 0.0667 loss: 0.1669 loss_sem_seg: 0.1669 2023/04/25 20:54:24 - mmengine - INFO - Epoch(train) [27][ 150/1196] lr: 8.0000e-04 eta: 2:35:34 time: 0.7755 data_time: 0.0035 memory: 3184 grad_norm: 0.0635 loss: 0.1706 loss_sem_seg: 0.1706 2023/04/25 20:55:05 - mmengine - INFO - Epoch(train) [27][ 200/1196] lr: 8.0000e-04 eta: 2:34:54 time: 0.8050 data_time: 0.0036 memory: 3337 grad_norm: 0.0635 loss: 0.1654 loss_sem_seg: 0.1654 2023/04/25 20:55:43 - mmengine - INFO - Epoch(train) [27][ 250/1196] lr: 8.0000e-04 eta: 2:34:15 time: 0.7726 data_time: 0.0035 memory: 3464 grad_norm: 0.0598 loss: 0.1716 loss_sem_seg: 0.1716 2023/04/25 20:56:24 - mmengine - INFO - Epoch(train) [27][ 300/1196] lr: 8.0000e-04 eta: 2:33:35 time: 0.8061 data_time: 0.0036 memory: 3244 grad_norm: 0.0690 loss: 0.1636 loss_sem_seg: 0.1636 2023/04/25 20:57:06 - mmengine - INFO - Epoch(train) [27][ 350/1196] lr: 8.0000e-04 eta: 2:32:57 time: 0.8472 data_time: 0.0036 memory: 3218 grad_norm: 0.0640 loss: 0.1747 loss_sem_seg: 0.1747 2023/04/25 20:57:44 - mmengine - INFO - Epoch(train) [27][ 400/1196] lr: 8.0000e-04 eta: 2:32:17 time: 0.7636 data_time: 0.0036 memory: 3357 grad_norm: 0.0636 loss: 0.1685 loss_sem_seg: 0.1685 2023/04/25 20:58:23 - mmengine - INFO - Epoch(train) [27][ 450/1196] lr: 8.0000e-04 eta: 2:31:37 time: 0.7831 data_time: 0.0036 memory: 3324 grad_norm: 0.0650 loss: 0.1634 loss_sem_seg: 0.1634 2023/04/25 20:59:04 - mmengine - INFO - Epoch(train) [27][ 500/1196] lr: 8.0000e-04 eta: 2:30:58 time: 0.8210 data_time: 0.0036 memory: 3189 grad_norm: 0.0680 loss: 0.1713 loss_sem_seg: 0.1713 2023/04/25 20:59:45 - mmengine - INFO - Epoch(train) [27][ 550/1196] lr: 8.0000e-04 eta: 2:30:19 time: 0.8047 data_time: 0.0037 memory: 3213 grad_norm: 0.0668 loss: 0.1676 loss_sem_seg: 0.1676 2023/04/25 21:00:25 - mmengine - INFO - Epoch(train) [27][ 600/1196] lr: 8.0000e-04 eta: 2:29:40 time: 0.8071 data_time: 0.0037 memory: 3269 grad_norm: 0.0683 loss: 0.1727 loss_sem_seg: 0.1727 2023/04/25 21:01:04 - mmengine - INFO - Epoch(train) [27][ 650/1196] lr: 8.0000e-04 eta: 2:29:00 time: 0.7838 data_time: 0.0038 memory: 3326 grad_norm: 0.0631 loss: 0.1719 loss_sem_seg: 0.1719 2023/04/25 21:01:44 - mmengine - INFO - Epoch(train) [27][ 700/1196] lr: 8.0000e-04 eta: 2:28:21 time: 0.7977 data_time: 0.0035 memory: 3252 grad_norm: 0.0632 loss: 0.1645 loss_sem_seg: 0.1645 2023/04/25 21:02:25 - mmengine - INFO - Epoch(train) [27][ 750/1196] lr: 8.0000e-04 eta: 2:27:42 time: 0.8217 data_time: 0.0035 memory: 3135 grad_norm: 0.0665 loss: 0.1796 loss_sem_seg: 0.1796 2023/04/25 21:03:03 - mmengine - INFO - Epoch(train) [27][ 800/1196] lr: 8.0000e-04 eta: 2:27:02 time: 0.7625 data_time: 0.0037 memory: 3185 grad_norm: 0.0686 loss: 0.1794 loss_sem_seg: 0.1794 2023/04/25 21:03:43 - mmengine - INFO - Epoch(train) [27][ 850/1196] lr: 8.0000e-04 eta: 2:26:22 time: 0.8023 data_time: 0.0036 memory: 3280 grad_norm: 0.0657 loss: 0.1596 loss_sem_seg: 0.1596 2023/04/25 21:04:25 - mmengine - INFO - Epoch(train) [27][ 900/1196] lr: 8.0000e-04 eta: 2:25:44 time: 0.8324 data_time: 0.0037 memory: 3234 grad_norm: 0.0670 loss: 0.1655 loss_sem_seg: 0.1655 2023/04/25 21:04:28 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 21:05:05 - mmengine - INFO - Epoch(train) [27][ 950/1196] lr: 8.0000e-04 eta: 2:25:04 time: 0.7982 data_time: 0.0037 memory: 3384 grad_norm: 0.0615 loss: 0.1733 loss_sem_seg: 0.1733 2023/04/25 21:05:44 - mmengine - INFO - Epoch(train) [27][1000/1196] lr: 8.0000e-04 eta: 2:24:25 time: 0.7856 data_time: 0.0036 memory: 3551 grad_norm: 0.0655 loss: 0.1685 loss_sem_seg: 0.1685 2023/04/25 21:06:25 - mmengine - INFO - Epoch(train) [27][1050/1196] lr: 8.0000e-04 eta: 2:23:45 time: 0.8143 data_time: 0.0037 memory: 3460 grad_norm: 0.0666 loss: 0.1630 loss_sem_seg: 0.1630 2023/04/25 21:07:05 - mmengine - INFO - Epoch(train) [27][1100/1196] lr: 8.0000e-04 eta: 2:23:06 time: 0.8011 data_time: 0.0037 memory: 3562 grad_norm: 0.0632 loss: 0.1677 loss_sem_seg: 0.1677 2023/04/25 21:07:45 - mmengine - INFO - Epoch(train) [27][1150/1196] lr: 8.0000e-04 eta: 2:22:27 time: 0.8082 data_time: 0.0039 memory: 3274 grad_norm: 0.0628 loss: 0.1756 loss_sem_seg: 0.1756 2023/04/25 21:08:24 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 21:08:24 - mmengine - INFO - Saving checkpoint at 27 epochs 2023/04/25 21:08:41 - mmengine - INFO - Epoch(val) [27][ 50/509] eta: 0:01:56 time: 0.2547 data_time: 0.0050 memory: 3256 2023/04/25 21:08:52 - mmengine - INFO - Epoch(val) [27][100/509] eta: 0:01:38 time: 0.2248 data_time: 0.0048 memory: 840 2023/04/25 21:09:03 - mmengine - INFO - Epoch(val) [27][150/509] eta: 0:01:23 time: 0.2151 data_time: 0.0047 memory: 843 2023/04/25 21:09:13 - mmengine - INFO - Epoch(val) [27][200/509] eta: 0:01:10 time: 0.2139 data_time: 0.0050 memory: 834 2023/04/25 21:09:22 - mmengine - INFO - Epoch(val) [27][250/509] eta: 0:00:55 time: 0.1689 data_time: 0.0047 memory: 850 2023/04/25 21:09:34 - mmengine - INFO - Epoch(val) [27][300/509] eta: 0:00:45 time: 0.2390 data_time: 0.0046 memory: 812 2023/04/25 21:09:45 - mmengine - INFO - Epoch(val) [27][350/509] eta: 0:00:35 time: 0.2288 data_time: 0.0048 memory: 825 2023/04/25 21:09:57 - mmengine - INFO - Epoch(val) [27][400/509] eta: 0:00:24 time: 0.2310 data_time: 0.0047 memory: 827 2023/04/25 21:10:13 - mmengine - INFO - Epoch(val) [27][450/509] eta: 0:00:13 time: 0.3217 data_time: 0.0047 memory: 845 2023/04/25 21:10:28 - mmengine - INFO - Epoch(val) [27][500/509] eta: 0:00:02 time: 0.3101 data_time: 0.0045 memory: 832 2023/04/25 21:11:18 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9707 | 0.5568 | 0.7905 | 0.7977 | 0.7363 | 0.8012 | 0.8977 | 0.0543 | 0.9460 | 0.4793 | 0.8251 | 0.0011 | 0.9143 | 0.6561 | 0.8779 | 0.6988 | 0.7331 | 0.6590 | 0.5271 | 0.6802 | 0.9226 | 0.7514 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 21:11:18 - mmengine - INFO - Epoch(val) [27][509/509] car: 0.9707 bicycle: 0.5568 motorcycle: 0.7905 truck: 0.7977 bus: 0.7363 person: 0.8012 bicyclist: 0.8977 motorcyclist: 0.0543 road: 0.9460 parking: 0.4793 sidewalk: 0.8251 other-ground: 0.0011 building: 0.9143 fence: 0.6561 vegetation: 0.8779 trunck: 0.6988 terrian: 0.7331 pole: 0.6590 traffic-sign: 0.5271 miou: 0.6802 acc: 0.9226 acc_cls: 0.7514 data_time: 0.0043 time: 0.3119 2023/04/25 21:11:58 - mmengine - INFO - Epoch(train) [28][ 50/1196] lr: 8.0000e-04 eta: 2:21:12 time: 0.7913 data_time: 0.0045 memory: 3358 grad_norm: 0.0637 loss: 0.1881 loss_sem_seg: 0.1881 2023/04/25 21:12:37 - mmengine - INFO - Epoch(train) [28][ 100/1196] lr: 8.0000e-04 eta: 2:20:32 time: 0.7812 data_time: 0.0037 memory: 3106 grad_norm: 0.0647 loss: 0.1739 loss_sem_seg: 0.1739 2023/04/25 21:13:16 - mmengine - INFO - Epoch(train) [28][ 150/1196] lr: 8.0000e-04 eta: 2:19:52 time: 0.7794 data_time: 0.0035 memory: 3201 grad_norm: 0.0649 loss: 0.1646 loss_sem_seg: 0.1646 2023/04/25 21:13:56 - mmengine - INFO - Epoch(train) [28][ 200/1196] lr: 8.0000e-04 eta: 2:19:13 time: 0.8052 data_time: 0.0037 memory: 3295 grad_norm: 0.0668 loss: 0.1745 loss_sem_seg: 0.1745 2023/04/25 21:14:34 - mmengine - INFO - Epoch(train) [28][ 250/1196] lr: 8.0000e-04 eta: 2:18:33 time: 0.7682 data_time: 0.0036 memory: 3188 grad_norm: 0.0626 loss: 0.1753 loss_sem_seg: 0.1753 2023/04/25 21:15:15 - mmengine - INFO - Epoch(train) [28][ 300/1196] lr: 8.0000e-04 eta: 2:17:54 time: 0.8062 data_time: 0.0037 memory: 3495 grad_norm: 0.0616 loss: 0.1638 loss_sem_seg: 0.1638 2023/04/25 21:15:53 - mmengine - INFO - Epoch(train) [28][ 350/1196] lr: 8.0000e-04 eta: 2:17:14 time: 0.7636 data_time: 0.0036 memory: 3116 grad_norm: 0.0636 loss: 0.1743 loss_sem_seg: 0.1743 2023/04/25 21:16:33 - mmengine - INFO - Epoch(train) [28][ 400/1196] lr: 8.0000e-04 eta: 2:16:34 time: 0.8104 data_time: 0.0036 memory: 3126 grad_norm: 0.0715 loss: 0.1774 loss_sem_seg: 0.1774 2023/04/25 21:17:14 - mmengine - INFO - Epoch(train) [28][ 450/1196] lr: 8.0000e-04 eta: 2:15:55 time: 0.8143 data_time: 0.0037 memory: 3119 grad_norm: inf loss: 0.1693 loss_sem_seg: 0.1693 2023/04/25 21:17:56 - mmengine - INFO - Epoch(train) [28][ 500/1196] lr: 8.0000e-04 eta: 2:15:16 time: 0.8286 data_time: 0.0037 memory: 3133 grad_norm: 0.0672 loss: 0.1690 loss_sem_seg: 0.1690 2023/04/25 21:18:32 - mmengine - INFO - Epoch(train) [28][ 550/1196] lr: 8.0000e-04 eta: 2:14:36 time: 0.7373 data_time: 0.0037 memory: 3318 grad_norm: 0.0653 loss: 0.1751 loss_sem_seg: 0.1751 2023/04/25 21:19:13 - mmengine - INFO - Epoch(train) [28][ 600/1196] lr: 8.0000e-04 eta: 2:13:57 time: 0.8158 data_time: 0.0037 memory: 3441 grad_norm: 0.0714 loss: 0.1779 loss_sem_seg: 0.1779 2023/04/25 21:19:53 - mmengine - INFO - Epoch(train) [28][ 650/1196] lr: 8.0000e-04 eta: 2:13:17 time: 0.7967 data_time: 0.0038 memory: 3119 grad_norm: 0.0660 loss: 0.1685 loss_sem_seg: 0.1685 2023/04/25 21:20:31 - mmengine - INFO - Epoch(train) [28][ 700/1196] lr: 8.0000e-04 eta: 2:12:37 time: 0.7648 data_time: 0.0037 memory: 3367 grad_norm: 0.0635 loss: 0.1624 loss_sem_seg: 0.1624 2023/04/25 21:20:38 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 21:21:11 - mmengine - INFO - Epoch(train) [28][ 750/1196] lr: 8.0000e-04 eta: 2:11:58 time: 0.7985 data_time: 0.0039 memory: 3204 grad_norm: 0.0657 loss: 0.1718 loss_sem_seg: 0.1718 2023/04/25 21:21:50 - mmengine - INFO - Epoch(train) [28][ 800/1196] lr: 8.0000e-04 eta: 2:11:18 time: 0.7782 data_time: 0.0036 memory: 3246 grad_norm: 0.0694 loss: 0.1687 loss_sem_seg: 0.1687 2023/04/25 21:22:30 - mmengine - INFO - Epoch(train) [28][ 850/1196] lr: 8.0000e-04 eta: 2:10:39 time: 0.7949 data_time: 0.0037 memory: 3063 grad_norm: 0.0665 loss: 0.1663 loss_sem_seg: 0.1663 2023/04/25 21:23:09 - mmengine - INFO - Epoch(train) [28][ 900/1196] lr: 8.0000e-04 eta: 2:09:59 time: 0.7863 data_time: 0.0035 memory: 3222 grad_norm: 0.0673 loss: 0.1637 loss_sem_seg: 0.1637 2023/04/25 21:23:48 - mmengine - INFO - Epoch(train) [28][ 950/1196] lr: 8.0000e-04 eta: 2:09:19 time: 0.7725 data_time: 0.0037 memory: 3230 grad_norm: 0.0615 loss: 0.1688 loss_sem_seg: 0.1688 2023/04/25 21:24:28 - mmengine - INFO - Epoch(train) [28][1000/1196] lr: 8.0000e-04 eta: 2:08:40 time: 0.8030 data_time: 0.0036 memory: 3240 grad_norm: 0.0691 loss: 0.1602 loss_sem_seg: 0.1602 2023/04/25 21:25:09 - mmengine - INFO - Epoch(train) [28][1050/1196] lr: 8.0000e-04 eta: 2:08:01 time: 0.8114 data_time: 0.0035 memory: 3096 grad_norm: 0.0669 loss: 0.1644 loss_sem_seg: 0.1644 2023/04/25 21:25:48 - mmengine - INFO - Epoch(train) [28][1100/1196] lr: 8.0000e-04 eta: 2:07:21 time: 0.7852 data_time: 0.0036 memory: 3222 grad_norm: 0.0675 loss: 0.1599 loss_sem_seg: 0.1599 2023/04/25 21:26:29 - mmengine - INFO - Epoch(train) [28][1150/1196] lr: 8.0000e-04 eta: 2:06:42 time: 0.8179 data_time: 0.0034 memory: 3137 grad_norm: 0.0627 loss: 0.1553 loss_sem_seg: 0.1553 2023/04/25 21:27:04 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 21:27:04 - mmengine - INFO - Saving checkpoint at 28 epochs 2023/04/25 21:27:20 - mmengine - INFO - Epoch(val) [28][ 50/509] eta: 0:01:42 time: 0.2242 data_time: 0.0047 memory: 3151 2023/04/25 21:27:29 - mmengine - INFO - Epoch(val) [28][100/509] eta: 0:01:21 time: 0.1759 data_time: 0.0043 memory: 840 2023/04/25 21:27:39 - mmengine - INFO - Epoch(val) [28][150/509] eta: 0:01:13 time: 0.2121 data_time: 0.0047 memory: 843 2023/04/25 21:27:50 - mmengine - INFO - Epoch(val) [28][200/509] eta: 0:01:03 time: 0.2081 data_time: 0.0044 memory: 834 2023/04/25 21:27:58 - mmengine - INFO - Epoch(val) [28][250/509] eta: 0:00:51 time: 0.1750 data_time: 0.0045 memory: 850 2023/04/25 21:28:10 - mmengine - INFO - Epoch(val) [28][300/509] eta: 0:00:42 time: 0.2268 data_time: 0.0045 memory: 812 2023/04/25 21:28:20 - mmengine - INFO - Epoch(val) [28][350/509] eta: 0:00:32 time: 0.2043 data_time: 0.0045 memory: 825 2023/04/25 21:28:29 - mmengine - INFO - Epoch(val) [28][400/509] eta: 0:00:21 time: 0.1784 data_time: 0.0042 memory: 827 2023/04/25 21:28:38 - mmengine - INFO - Epoch(val) [28][450/509] eta: 0:00:11 time: 0.1881 data_time: 0.0046 memory: 845 2023/04/25 21:28:50 - mmengine - INFO - Epoch(val) [28][500/509] eta: 0:00:01 time: 0.2274 data_time: 0.0041 memory: 832 2023/04/25 21:29:21 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9720 | 0.5626 | 0.8160 | 0.7551 | 0.7477 | 0.8094 | 0.8995 | 0.0391 | 0.9460 | 0.4818 | 0.8238 | 0.0014 | 0.9143 | 0.6662 | 0.8802 | 0.6860 | 0.7402 | 0.6640 | 0.5265 | 0.6806 | 0.9237 | 0.7545 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 21:29:21 - mmengine - INFO - Epoch(val) [28][509/509] car: 0.9720 bicycle: 0.5626 motorcycle: 0.8160 truck: 0.7551 bus: 0.7477 person: 0.8094 bicyclist: 0.8995 motorcyclist: 0.0391 road: 0.9460 parking: 0.4818 sidewalk: 0.8238 other-ground: 0.0014 building: 0.9143 fence: 0.6662 vegetation: 0.8802 trunck: 0.6860 terrian: 0.7402 pole: 0.6640 traffic-sign: 0.5265 miou: 0.6806 acc: 0.9237 acc_cls: 0.7545 data_time: 0.0040 time: 0.2648 2023/04/25 21:30:00 - mmengine - INFO - Epoch(train) [29][ 50/1196] lr: 8.0000e-04 eta: 2:05:26 time: 0.7793 data_time: 0.0044 memory: 3249 grad_norm: 0.0660 loss: 0.1679 loss_sem_seg: 0.1679 2023/04/25 21:30:40 - mmengine - INFO - Epoch(train) [29][ 100/1196] lr: 8.0000e-04 eta: 2:04:46 time: 0.7930 data_time: 0.0035 memory: 3176 grad_norm: 0.0655 loss: 0.1581 loss_sem_seg: 0.1581 2023/04/25 21:31:18 - mmengine - INFO - Epoch(train) [29][ 150/1196] lr: 8.0000e-04 eta: 2:04:06 time: 0.7727 data_time: 0.0036 memory: 3346 grad_norm: 0.0645 loss: 0.1694 loss_sem_seg: 0.1694 2023/04/25 21:31:59 - mmengine - INFO - Epoch(train) [29][ 200/1196] lr: 8.0000e-04 eta: 2:03:27 time: 0.8091 data_time: 0.0038 memory: 3292 grad_norm: 0.0711 loss: 0.1520 loss_sem_seg: 0.1520 2023/04/25 21:32:39 - mmengine - INFO - Epoch(train) [29][ 250/1196] lr: 8.0000e-04 eta: 2:02:48 time: 0.8032 data_time: 0.0036 memory: 3439 grad_norm: 0.0639 loss: 0.1679 loss_sem_seg: 0.1679 2023/04/25 21:33:19 - mmengine - INFO - Epoch(train) [29][ 300/1196] lr: 8.0000e-04 eta: 2:02:08 time: 0.7947 data_time: 0.0037 memory: 3234 grad_norm: 0.0644 loss: 0.1645 loss_sem_seg: 0.1645 2023/04/25 21:33:59 - mmengine - INFO - Epoch(train) [29][ 350/1196] lr: 8.0000e-04 eta: 2:01:29 time: 0.8068 data_time: 0.0036 memory: 3271 grad_norm: 0.0697 loss: 0.1674 loss_sem_seg: 0.1674 2023/04/25 21:34:40 - mmengine - INFO - Epoch(train) [29][ 400/1196] lr: 8.0000e-04 eta: 2:00:50 time: 0.8142 data_time: 0.0037 memory: 3284 grad_norm: 0.0682 loss: 0.1722 loss_sem_seg: 0.1722 2023/04/25 21:35:19 - mmengine - INFO - Epoch(train) [29][ 450/1196] lr: 8.0000e-04 eta: 2:00:10 time: 0.7844 data_time: 0.0037 memory: 3446 grad_norm: 0.0641 loss: 0.1618 loss_sem_seg: 0.1618 2023/04/25 21:35:58 - mmengine - INFO - Epoch(train) [29][ 500/1196] lr: 8.0000e-04 eta: 1:59:30 time: 0.7784 data_time: 0.0037 memory: 3461 grad_norm: 0.0684 loss: 0.1698 loss_sem_seg: 0.1698 2023/04/25 21:36:08 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 21:36:38 - mmengine - INFO - Epoch(train) [29][ 550/1196] lr: 8.0000e-04 eta: 1:58:51 time: 0.8049 data_time: 0.0035 memory: 3158 grad_norm: 0.0667 loss: 0.1615 loss_sem_seg: 0.1615 2023/04/25 21:37:19 - mmengine - INFO - Epoch(train) [29][ 600/1196] lr: 8.0000e-04 eta: 1:58:12 time: 0.8112 data_time: 0.0037 memory: 3618 grad_norm: 0.0667 loss: 0.1589 loss_sem_seg: 0.1589 2023/04/25 21:37:59 - mmengine - INFO - Epoch(train) [29][ 650/1196] lr: 8.0000e-04 eta: 1:57:32 time: 0.7984 data_time: 0.0037 memory: 2990 grad_norm: 0.0638 loss: 0.1692 loss_sem_seg: 0.1692 2023/04/25 21:38:39 - mmengine - INFO - Epoch(train) [29][ 700/1196] lr: 8.0000e-04 eta: 1:56:53 time: 0.8115 data_time: 0.0036 memory: 3399 grad_norm: 0.0683 loss: 0.1622 loss_sem_seg: 0.1622 2023/04/25 21:39:18 - mmengine - INFO - Epoch(train) [29][ 750/1196] lr: 8.0000e-04 eta: 1:56:13 time: 0.7683 data_time: 0.0037 memory: 3405 grad_norm: 0.0649 loss: 0.1528 loss_sem_seg: 0.1528 2023/04/25 21:39:57 - mmengine - INFO - Epoch(train) [29][ 800/1196] lr: 8.0000e-04 eta: 1:55:34 time: 0.7861 data_time: 0.0036 memory: 3128 grad_norm: 0.0671 loss: 0.1603 loss_sem_seg: 0.1603 2023/04/25 21:40:36 - mmengine - INFO - Epoch(train) [29][ 850/1196] lr: 8.0000e-04 eta: 1:54:54 time: 0.7920 data_time: 0.0036 memory: 3458 grad_norm: 0.0679 loss: 0.1685 loss_sem_seg: 0.1685 2023/04/25 21:41:17 - mmengine - INFO - Epoch(train) [29][ 900/1196] lr: 8.0000e-04 eta: 1:54:15 time: 0.8031 data_time: 0.0038 memory: 3333 grad_norm: 0.0680 loss: 0.1664 loss_sem_seg: 0.1664 2023/04/25 21:41:57 - mmengine - INFO - Epoch(train) [29][ 950/1196] lr: 8.0000e-04 eta: 1:53:35 time: 0.8122 data_time: 0.0036 memory: 3148 grad_norm: 0.0656 loss: 0.1566 loss_sem_seg: 0.1566 2023/04/25 21:42:36 - mmengine - INFO - Epoch(train) [29][1000/1196] lr: 8.0000e-04 eta: 1:52:56 time: 0.7849 data_time: 0.0037 memory: 3286 grad_norm: 0.0614 loss: 0.1640 loss_sem_seg: 0.1640 2023/04/25 21:43:16 - mmengine - INFO - Epoch(train) [29][1050/1196] lr: 8.0000e-04 eta: 1:52:16 time: 0.7827 data_time: 0.0034 memory: 3098 grad_norm: 0.0652 loss: 0.1679 loss_sem_seg: 0.1679 2023/04/25 21:43:57 - mmengine - INFO - Epoch(train) [29][1100/1196] lr: 8.0000e-04 eta: 1:51:37 time: 0.8273 data_time: 0.0039 memory: 3461 grad_norm: 0.0649 loss: 0.1603 loss_sem_seg: 0.1603 2023/04/25 21:44:36 - mmengine - INFO - Epoch(train) [29][1150/1196] lr: 8.0000e-04 eta: 1:50:58 time: 0.7871 data_time: 0.0037 memory: 3273 grad_norm: 0.0640 loss: 0.1619 loss_sem_seg: 0.1619 2023/04/25 21:45:13 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 21:45:13 - mmengine - INFO - Saving checkpoint at 29 epochs 2023/04/25 21:45:30 - mmengine - INFO - Epoch(val) [29][ 50/509] eta: 0:01:52 time: 0.2442 data_time: 0.0048 memory: 3164 2023/04/25 21:45:42 - mmengine - INFO - Epoch(val) [29][100/509] eta: 0:01:37 time: 0.2329 data_time: 0.0045 memory: 840 2023/04/25 21:45:53 - mmengine - INFO - Epoch(val) [29][150/509] eta: 0:01:23 time: 0.2232 data_time: 0.0045 memory: 843 2023/04/25 21:46:04 - mmengine - INFO - Epoch(val) [29][200/509] eta: 0:01:10 time: 0.2169 data_time: 0.0044 memory: 834 2023/04/25 21:46:14 - mmengine - INFO - Epoch(val) [29][250/509] eta: 0:00:57 time: 0.2009 data_time: 0.0046 memory: 850 2023/04/25 21:46:25 - mmengine - INFO - Epoch(val) [29][300/509] eta: 0:00:46 time: 0.2242 data_time: 0.0044 memory: 812 2023/04/25 21:46:37 - mmengine - INFO - Epoch(val) [29][350/509] eta: 0:00:36 time: 0.2437 data_time: 0.0046 memory: 825 2023/04/25 21:46:49 - mmengine - INFO - Epoch(val) [29][400/509] eta: 0:00:24 time: 0.2323 data_time: 0.0044 memory: 827 2023/04/25 21:47:05 - mmengine - INFO - Epoch(val) [29][450/509] eta: 0:00:14 time: 0.3315 data_time: 0.0047 memory: 845 2023/04/25 21:47:22 - mmengine - INFO - Epoch(val) [29][500/509] eta: 0:00:02 time: 0.3431 data_time: 0.0040 memory: 832 2023/04/25 21:48:05 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9687 | 0.5647 | 0.8012 | 0.7759 | 0.7038 | 0.8073 | 0.9062 | 0.0344 | 0.9469 | 0.5015 | 0.8284 | 0.0014 | 0.9164 | 0.6689 | 0.8808 | 0.7007 | 0.7394 | 0.6642 | 0.5321 | 0.6812 | 0.9245 | 0.7534 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 21:48:05 - mmengine - INFO - Epoch(val) [29][509/509] car: 0.9687 bicycle: 0.5647 motorcycle: 0.8012 truck: 0.7759 bus: 0.7038 person: 0.8073 bicyclist: 0.9062 motorcyclist: 0.0344 road: 0.9469 parking: 0.5015 sidewalk: 0.8284 other-ground: 0.0014 building: 0.9164 fence: 0.6689 vegetation: 0.8808 trunck: 0.7007 terrian: 0.7394 pole: 0.6642 traffic-sign: 0.5321 miou: 0.6812 acc: 0.9245 acc_cls: 0.7534 data_time: 0.0039 time: 0.3277 2023/04/25 21:48:45 - mmengine - INFO - Epoch(train) [30][ 50/1196] lr: 8.0000e-04 eta: 1:49:42 time: 0.8146 data_time: 0.0047 memory: 3131 grad_norm: 0.0644 loss: 0.1588 loss_sem_seg: 0.1588 2023/04/25 21:49:26 - mmengine - INFO - Epoch(train) [30][ 100/1196] lr: 8.0000e-04 eta: 1:49:03 time: 0.8192 data_time: 0.0037 memory: 3463 grad_norm: 0.0664 loss: 0.1550 loss_sem_seg: 0.1550 2023/04/25 21:50:08 - mmengine - INFO - Epoch(train) [30][ 150/1196] lr: 8.0000e-04 eta: 1:48:24 time: 0.8325 data_time: 0.0038 memory: 3019 grad_norm: 0.0609 loss: 0.1568 loss_sem_seg: 0.1568 2023/04/25 21:50:47 - mmengine - INFO - Epoch(train) [30][ 200/1196] lr: 8.0000e-04 eta: 1:47:44 time: 0.7824 data_time: 0.0036 memory: 3285 grad_norm: 0.0643 loss: 0.1593 loss_sem_seg: 0.1593 2023/04/25 21:51:26 - mmengine - INFO - Epoch(train) [30][ 250/1196] lr: 8.0000e-04 eta: 1:47:04 time: 0.7826 data_time: 0.0036 memory: 3116 grad_norm: 0.0682 loss: 0.1727 loss_sem_seg: 0.1727 2023/04/25 21:52:07 - mmengine - INFO - Epoch(train) [30][ 300/1196] lr: 8.0000e-04 eta: 1:46:25 time: 0.8086 data_time: 0.0035 memory: 3345 grad_norm: 0.0691 loss: 0.1611 loss_sem_seg: 0.1611 2023/04/25 21:52:19 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 21:52:46 - mmengine - INFO - Epoch(train) [30][ 350/1196] lr: 8.0000e-04 eta: 1:45:45 time: 0.7826 data_time: 0.0037 memory: 3386 grad_norm: 0.0670 loss: 0.1632 loss_sem_seg: 0.1632 2023/04/25 21:53:24 - mmengine - INFO - Epoch(train) [30][ 400/1196] lr: 8.0000e-04 eta: 1:45:06 time: 0.7693 data_time: 0.0036 memory: 3279 grad_norm: 0.0655 loss: 0.1688 loss_sem_seg: 0.1688 2023/04/25 21:54:04 - mmengine - INFO - Epoch(train) [30][ 450/1196] lr: 8.0000e-04 eta: 1:44:26 time: 0.7858 data_time: 0.0037 memory: 3189 grad_norm: inf loss: 0.1700 loss_sem_seg: 0.1700 2023/04/25 21:54:44 - mmengine - INFO - Epoch(train) [30][ 500/1196] lr: 8.0000e-04 eta: 1:43:47 time: 0.8044 data_time: 0.0038 memory: 3151 grad_norm: 0.0683 loss: 0.1635 loss_sem_seg: 0.1635 2023/04/25 21:55:23 - mmengine - INFO - Epoch(train) [30][ 550/1196] lr: 8.0000e-04 eta: 1:43:07 time: 0.7874 data_time: 0.0036 memory: 3426 grad_norm: 0.0700 loss: 0.1662 loss_sem_seg: 0.1662 2023/04/25 21:56:03 - mmengine - INFO - Epoch(train) [30][ 600/1196] lr: 8.0000e-04 eta: 1:42:27 time: 0.7935 data_time: 0.0038 memory: 3338 grad_norm: 0.0654 loss: 0.1600 loss_sem_seg: 0.1600 2023/04/25 21:56:43 - mmengine - INFO - Epoch(train) [30][ 650/1196] lr: 8.0000e-04 eta: 1:41:48 time: 0.7997 data_time: 0.0038 memory: 3158 grad_norm: 0.0657 loss: 0.1684 loss_sem_seg: 0.1684 2023/04/25 21:57:24 - mmengine - INFO - Epoch(train) [30][ 700/1196] lr: 8.0000e-04 eta: 1:41:09 time: 0.8155 data_time: 0.0035 memory: 3193 grad_norm: 0.0679 loss: 0.1612 loss_sem_seg: 0.1612 2023/04/25 21:58:04 - mmengine - INFO - Epoch(train) [30][ 750/1196] lr: 8.0000e-04 eta: 1:40:29 time: 0.8035 data_time: 0.0036 memory: 3208 grad_norm: 0.0660 loss: 0.1586 loss_sem_seg: 0.1586 2023/04/25 21:58:43 - mmengine - INFO - Epoch(train) [30][ 800/1196] lr: 8.0000e-04 eta: 1:39:50 time: 0.7830 data_time: 0.0035 memory: 3170 grad_norm: 0.0722 loss: 0.1663 loss_sem_seg: 0.1663 2023/04/25 21:59:24 - mmengine - INFO - Epoch(train) [30][ 850/1196] lr: 8.0000e-04 eta: 1:39:10 time: 0.8212 data_time: 0.0036 memory: 3252 grad_norm: 0.0669 loss: 0.1722 loss_sem_seg: 0.1722 2023/04/25 22:00:03 - mmengine - INFO - Epoch(train) [30][ 900/1196] lr: 8.0000e-04 eta: 1:38:31 time: 0.7761 data_time: 0.0037 memory: 3193 grad_norm: 0.0688 loss: 0.1633 loss_sem_seg: 0.1633 2023/04/25 22:00:43 - mmengine - INFO - Epoch(train) [30][ 950/1196] lr: 8.0000e-04 eta: 1:37:51 time: 0.7987 data_time: 0.0037 memory: 3222 grad_norm: 0.0624 loss: 0.1578 loss_sem_seg: 0.1578 2023/04/25 22:01:23 - mmengine - INFO - Epoch(train) [30][1000/1196] lr: 8.0000e-04 eta: 1:37:12 time: 0.8056 data_time: 0.0036 memory: 3231 grad_norm: 0.0717 loss: 0.1543 loss_sem_seg: 0.1543 2023/04/25 22:02:04 - mmengine - INFO - Epoch(train) [30][1050/1196] lr: 8.0000e-04 eta: 1:36:33 time: 0.8218 data_time: 0.0038 memory: 3439 grad_norm: 0.0652 loss: 0.1567 loss_sem_seg: 0.1567 2023/04/25 22:02:42 - mmengine - INFO - Epoch(train) [30][1100/1196] lr: 8.0000e-04 eta: 1:35:53 time: 0.7495 data_time: 0.0037 memory: 3060 grad_norm: 0.0679 loss: 0.1568 loss_sem_seg: 0.1568 2023/04/25 22:03:22 - mmengine - INFO - Epoch(train) [30][1150/1196] lr: 8.0000e-04 eta: 1:35:13 time: 0.8042 data_time: 0.0036 memory: 3268 grad_norm: 0.0746 loss: 0.1682 loss_sem_seg: 0.1682 2023/04/25 22:03:57 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 22:03:57 - mmengine - INFO - Saving checkpoint at 30 epochs 2023/04/25 22:04:12 - mmengine - INFO - Epoch(val) [30][ 50/509] eta: 0:01:29 time: 0.1957 data_time: 0.0048 memory: 3194 2023/04/25 22:04:23 - mmengine - INFO - Epoch(val) [30][100/509] eta: 0:01:26 time: 0.2252 data_time: 0.0045 memory: 840 2023/04/25 22:04:34 - mmengine - INFO - Epoch(val) [30][150/509] eta: 0:01:17 time: 0.2284 data_time: 0.0046 memory: 843 2023/04/25 22:04:46 - mmengine - INFO - Epoch(val) [30][200/509] eta: 0:01:08 time: 0.2338 data_time: 0.0045 memory: 834 2023/04/25 22:04:56 - mmengine - INFO - Epoch(val) [30][250/509] eta: 0:00:56 time: 0.1998 data_time: 0.0047 memory: 850 2023/04/25 22:05:07 - mmengine - INFO - Epoch(val) [30][300/509] eta: 0:00:45 time: 0.2240 data_time: 0.0044 memory: 812 2023/04/25 22:05:19 - mmengine - INFO - Epoch(val) [30][350/509] eta: 0:00:34 time: 0.2320 data_time: 0.0047 memory: 825 2023/04/25 22:05:29 - mmengine - INFO - Epoch(val) [30][400/509] eta: 0:00:23 time: 0.2033 data_time: 0.0044 memory: 827 2023/04/25 22:05:39 - mmengine - INFO - Epoch(val) [30][450/509] eta: 0:00:12 time: 0.1944 data_time: 0.0046 memory: 845 2023/04/25 22:05:56 - mmengine - INFO - Epoch(val) [30][500/509] eta: 0:00:02 time: 0.3485 data_time: 0.0041 memory: 832 2023/04/25 22:06:39 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9704 | 0.5607 | 0.8226 | 0.8139 | 0.7281 | 0.8039 | 0.9003 | 0.0487 | 0.9467 | 0.4897 | 0.8258 | 0.0049 | 0.9136 | 0.6629 | 0.8790 | 0.7009 | 0.7345 | 0.6602 | 0.5255 | 0.6838 | 0.9233 | 0.7519 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 22:06:39 - mmengine - INFO - Epoch(val) [30][509/509] car: 0.9704 bicycle: 0.5607 motorcycle: 0.8226 truck: 0.8139 bus: 0.7281 person: 0.8039 bicyclist: 0.9003 motorcyclist: 0.0487 road: 0.9467 parking: 0.4897 sidewalk: 0.8258 other-ground: 0.0049 building: 0.9136 fence: 0.6629 vegetation: 0.8790 trunck: 0.7009 terrian: 0.7345 pole: 0.6602 traffic-sign: 0.5255 miou: 0.6838 acc: 0.9233 acc_cls: 0.7519 data_time: 0.0039 time: 0.3921 2023/04/25 22:07:19 - mmengine - INFO - Epoch(train) [31][ 50/1196] lr: 8.0000e-04 eta: 1:33:57 time: 0.7923 data_time: 0.0046 memory: 3269 grad_norm: 0.0654 loss: 0.1479 loss_sem_seg: 0.1479 2023/04/25 22:07:57 - mmengine - INFO - Epoch(train) [31][ 100/1196] lr: 8.0000e-04 eta: 1:33:17 time: 0.7682 data_time: 0.0035 memory: 3359 grad_norm: 0.0679 loss: 0.1599 loss_sem_seg: 0.1599 2023/04/25 22:08:12 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 22:08:37 - mmengine - INFO - Epoch(train) [31][ 150/1196] lr: 8.0000e-04 eta: 1:32:38 time: 0.7873 data_time: 0.0036 memory: 3106 grad_norm: 0.0658 loss: 0.1612 loss_sem_seg: 0.1612 2023/04/25 22:09:18 - mmengine - INFO - Epoch(train) [31][ 200/1196] lr: 8.0000e-04 eta: 1:31:58 time: 0.8240 data_time: 0.0036 memory: 3221 grad_norm: 0.0654 loss: 0.1625 loss_sem_seg: 0.1625 2023/04/25 22:09:57 - mmengine - INFO - Epoch(train) [31][ 250/1196] lr: 8.0000e-04 eta: 1:31:19 time: 0.7859 data_time: 0.0036 memory: 3341 grad_norm: 0.0707 loss: 0.1574 loss_sem_seg: 0.1574 2023/04/25 22:10:39 - mmengine - INFO - Epoch(train) [31][ 300/1196] lr: 8.0000e-04 eta: 1:30:40 time: 0.8310 data_time: 0.0035 memory: 3183 grad_norm: 0.0660 loss: 0.1716 loss_sem_seg: 0.1716 2023/04/25 22:11:18 - mmengine - INFO - Epoch(train) [31][ 350/1196] lr: 8.0000e-04 eta: 1:30:00 time: 0.7842 data_time: 0.0036 memory: 3102 grad_norm: 0.0691 loss: 0.1576 loss_sem_seg: 0.1576 2023/04/25 22:11:57 - mmengine - INFO - Epoch(train) [31][ 400/1196] lr: 8.0000e-04 eta: 1:29:21 time: 0.7897 data_time: 0.0034 memory: 3237 grad_norm: 0.0705 loss: 0.1591 loss_sem_seg: 0.1591 2023/04/25 22:12:38 - mmengine - INFO - Epoch(train) [31][ 450/1196] lr: 8.0000e-04 eta: 1:28:41 time: 0.8224 data_time: 0.0037 memory: 3243 grad_norm: 0.0622 loss: 0.1612 loss_sem_seg: 0.1612 2023/04/25 22:13:17 - mmengine - INFO - Epoch(train) [31][ 500/1196] lr: 8.0000e-04 eta: 1:28:01 time: 0.7621 data_time: 0.0035 memory: 3616 grad_norm: 0.0702 loss: 0.1602 loss_sem_seg: 0.1602 2023/04/25 22:13:57 - mmengine - INFO - Epoch(train) [31][ 550/1196] lr: 8.0000e-04 eta: 1:27:22 time: 0.8172 data_time: 0.0036 memory: 3182 grad_norm: 0.0692 loss: 0.1651 loss_sem_seg: 0.1651 2023/04/25 22:14:37 - mmengine - INFO - Epoch(train) [31][ 600/1196] lr: 8.0000e-04 eta: 1:26:43 time: 0.7921 data_time: 0.0036 memory: 3275 grad_norm: 0.0683 loss: 0.1611 loss_sem_seg: 0.1611 2023/04/25 22:15:15 - mmengine - INFO - Epoch(train) [31][ 650/1196] lr: 8.0000e-04 eta: 1:26:03 time: 0.7649 data_time: 0.0036 memory: 3163 grad_norm: 0.0664 loss: 0.1707 loss_sem_seg: 0.1707 2023/04/25 22:15:56 - mmengine - INFO - Epoch(train) [31][ 700/1196] lr: 8.0000e-04 eta: 1:25:23 time: 0.8064 data_time: 0.0035 memory: 3208 grad_norm: 0.0672 loss: 0.1540 loss_sem_seg: 0.1540 2023/04/25 22:16:36 - mmengine - INFO - Epoch(train) [31][ 750/1196] lr: 8.0000e-04 eta: 1:24:44 time: 0.7994 data_time: 0.0037 memory: 3165 grad_norm: 0.0703 loss: 0.1706 loss_sem_seg: 0.1706 2023/04/25 22:17:16 - mmengine - INFO - Epoch(train) [31][ 800/1196] lr: 8.0000e-04 eta: 1:24:04 time: 0.8042 data_time: 0.0036 memory: 3308 grad_norm: 0.0680 loss: 0.1627 loss_sem_seg: 0.1627 2023/04/25 22:17:56 - mmengine - INFO - Epoch(train) [31][ 850/1196] lr: 8.0000e-04 eta: 1:23:25 time: 0.8083 data_time: 0.0035 memory: 3182 grad_norm: 0.0637 loss: 0.1674 loss_sem_seg: 0.1674 2023/04/25 22:18:35 - mmengine - INFO - Epoch(train) [31][ 900/1196] lr: 8.0000e-04 eta: 1:22:45 time: 0.7731 data_time: 0.0035 memory: 3476 grad_norm: 0.0666 loss: 0.1659 loss_sem_seg: 0.1659 2023/04/25 22:19:15 - mmengine - INFO - Epoch(train) [31][ 950/1196] lr: 8.0000e-04 eta: 1:22:06 time: 0.8110 data_time: 0.0036 memory: 3259 grad_norm: 0.0731 loss: 0.1670 loss_sem_seg: 0.1670 2023/04/25 22:19:54 - mmengine - INFO - Epoch(train) [31][1000/1196] lr: 8.0000e-04 eta: 1:21:26 time: 0.7789 data_time: 0.0037 memory: 3470 grad_norm: 0.0648 loss: 0.1578 loss_sem_seg: 0.1578 2023/04/25 22:20:33 - mmengine - INFO - Epoch(train) [31][1050/1196] lr: 8.0000e-04 eta: 1:20:46 time: 0.7655 data_time: 0.0037 memory: 3189 grad_norm: 0.0707 loss: 0.1698 loss_sem_seg: 0.1698 2023/04/25 22:21:12 - mmengine - INFO - Epoch(train) [31][1100/1196] lr: 8.0000e-04 eta: 1:20:07 time: 0.7953 data_time: 0.0037 memory: 3166 grad_norm: 0.0662 loss: 0.1612 loss_sem_seg: 0.1612 2023/04/25 22:21:29 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 22:21:53 - mmengine - INFO - Epoch(train) [31][1150/1196] lr: 8.0000e-04 eta: 1:19:27 time: 0.8017 data_time: 0.0037 memory: 3465 grad_norm: 0.0644 loss: 0.1584 loss_sem_seg: 0.1584 2023/04/25 22:22:28 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 22:22:28 - mmengine - INFO - Saving checkpoint at 31 epochs 2023/04/25 22:22:43 - mmengine - INFO - Epoch(val) [31][ 50/509] eta: 0:01:41 time: 0.2214 data_time: 0.0047 memory: 3218 2023/04/25 22:22:54 - mmengine - INFO - Epoch(val) [31][100/509] eta: 0:01:26 time: 0.2038 data_time: 0.0046 memory: 840 2023/04/25 22:23:05 - mmengine - INFO - Epoch(val) [31][150/509] eta: 0:01:19 time: 0.2354 data_time: 0.0047 memory: 843 2023/04/25 22:23:17 - mmengine - INFO - Epoch(val) [31][200/509] eta: 0:01:09 time: 0.2346 data_time: 0.0046 memory: 834 2023/04/25 22:23:27 - mmengine - INFO - Epoch(val) [31][250/509] eta: 0:00:56 time: 0.1946 data_time: 0.0048 memory: 850 2023/04/25 22:23:37 - mmengine - INFO - Epoch(val) [31][300/509] eta: 0:00:44 time: 0.1955 data_time: 0.0046 memory: 812 2023/04/25 22:23:47 - mmengine - INFO - Epoch(val) [31][350/509] eta: 0:00:33 time: 0.2009 data_time: 0.0046 memory: 825 2023/04/25 22:23:56 - mmengine - INFO - Epoch(val) [31][400/509] eta: 0:00:22 time: 0.1817 data_time: 0.0043 memory: 827 2023/04/25 22:24:08 - mmengine - INFO - Epoch(val) [31][450/509] eta: 0:00:12 time: 0.2545 data_time: 0.0047 memory: 845 2023/04/25 22:24:28 - mmengine - INFO - Epoch(val) [31][500/509] eta: 0:00:02 time: 0.3931 data_time: 0.0043 memory: 832 2023/04/25 22:25:03 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9695 | 0.5408 | 0.8072 | 0.7977 | 0.7091 | 0.7995 | 0.9034 | 0.0288 | 0.9462 | 0.5014 | 0.8247 | 0.0014 | 0.9181 | 0.6773 | 0.8801 | 0.7020 | 0.7370 | 0.6603 | 0.5245 | 0.6805 | 0.9240 | 0.7498 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 22:25:03 - mmengine - INFO - Epoch(val) [31][509/509] car: 0.9695 bicycle: 0.5408 motorcycle: 0.8072 truck: 0.7977 bus: 0.7091 person: 0.7995 bicyclist: 0.9034 motorcyclist: 0.0288 road: 0.9462 parking: 0.5014 sidewalk: 0.8247 other-ground: 0.0014 building: 0.9181 fence: 0.6773 vegetation: 0.8801 trunck: 0.7020 terrian: 0.7370 pole: 0.6603 traffic-sign: 0.5245 miou: 0.6805 acc: 0.9240 acc_cls: 0.7498 data_time: 0.0042 time: 0.3742 2023/04/25 22:25:42 - mmengine - INFO - Epoch(train) [32][ 50/1196] lr: 8.0000e-04 eta: 1:18:11 time: 0.7664 data_time: 0.0047 memory: 3147 grad_norm: 0.0662 loss: 0.1507 loss_sem_seg: 0.1507 2023/04/25 22:26:21 - mmengine - INFO - Epoch(train) [32][ 100/1196] lr: 8.0000e-04 eta: 1:17:31 time: 0.7852 data_time: 0.0035 memory: 3121 grad_norm: 0.0707 loss: 0.1724 loss_sem_seg: 0.1724 2023/04/25 22:27:00 - mmengine - INFO - Epoch(train) [32][ 150/1196] lr: 8.0000e-04 eta: 1:16:52 time: 0.7804 data_time: 0.0035 memory: 3387 grad_norm: 0.0680 loss: 0.1578 loss_sem_seg: 0.1578 2023/04/25 22:27:39 - mmengine - INFO - Epoch(train) [32][ 200/1196] lr: 8.0000e-04 eta: 1:16:12 time: 0.7777 data_time: 0.0036 memory: 3234 grad_norm: 0.0662 loss: 0.1523 loss_sem_seg: 0.1523 2023/04/25 22:28:18 - mmengine - INFO - Epoch(train) [32][ 250/1196] lr: 8.0000e-04 eta: 1:15:33 time: 0.7940 data_time: 0.0037 memory: 3121 grad_norm: 0.0669 loss: 0.1578 loss_sem_seg: 0.1578 2023/04/25 22:29:00 - mmengine - INFO - Epoch(train) [32][ 300/1196] lr: 8.0000e-04 eta: 1:14:53 time: 0.8259 data_time: 0.0037 memory: 3180 grad_norm: 0.0667 loss: 0.1674 loss_sem_seg: 0.1674 2023/04/25 22:29:39 - mmengine - INFO - Epoch(train) [32][ 350/1196] lr: 8.0000e-04 eta: 1:14:14 time: 0.7879 data_time: 0.0035 memory: 3024 grad_norm: 0.0674 loss: 0.1576 loss_sem_seg: 0.1576 2023/04/25 22:30:18 - mmengine - INFO - Epoch(train) [32][ 400/1196] lr: 8.0000e-04 eta: 1:13:34 time: 0.7840 data_time: 0.0035 memory: 3101 grad_norm: 0.0691 loss: 0.1641 loss_sem_seg: 0.1641 2023/04/25 22:30:59 - mmengine - INFO - Epoch(train) [32][ 450/1196] lr: 8.0000e-04 eta: 1:12:55 time: 0.8079 data_time: 0.0036 memory: 3488 grad_norm: 0.0644 loss: 0.1605 loss_sem_seg: 0.1605 2023/04/25 22:31:38 - mmengine - INFO - Epoch(train) [32][ 500/1196] lr: 8.0000e-04 eta: 1:12:15 time: 0.7743 data_time: 0.0036 memory: 3229 grad_norm: 0.0697 loss: 0.1550 loss_sem_seg: 0.1550 2023/04/25 22:32:18 - mmengine - INFO - Epoch(train) [32][ 550/1196] lr: 8.0000e-04 eta: 1:11:36 time: 0.8069 data_time: 0.0037 memory: 3073 grad_norm: inf loss: 0.1560 loss_sem_seg: 0.1560 2023/04/25 22:32:57 - mmengine - INFO - Epoch(train) [32][ 600/1196] lr: 8.0000e-04 eta: 1:10:56 time: 0.7736 data_time: 0.0035 memory: 3155 grad_norm: 0.0704 loss: 0.1596 loss_sem_seg: 0.1596 2023/04/25 22:33:35 - mmengine - INFO - Epoch(train) [32][ 650/1196] lr: 8.0000e-04 eta: 1:10:16 time: 0.7714 data_time: 0.0037 memory: 3157 grad_norm: 0.0669 loss: 0.1626 loss_sem_seg: 0.1626 2023/04/25 22:34:15 - mmengine - INFO - Epoch(train) [32][ 700/1196] lr: 8.0000e-04 eta: 1:09:37 time: 0.8034 data_time: 0.0034 memory: 3146 grad_norm: 0.0685 loss: 0.1648 loss_sem_seg: 0.1648 2023/04/25 22:34:55 - mmengine - INFO - Epoch(train) [32][ 750/1196] lr: 8.0000e-04 eta: 1:08:57 time: 0.7996 data_time: 0.0036 memory: 3166 grad_norm: 0.0649 loss: 0.1572 loss_sem_seg: 0.1572 2023/04/25 22:35:35 - mmengine - INFO - Epoch(train) [32][ 800/1196] lr: 8.0000e-04 eta: 1:08:18 time: 0.7879 data_time: 0.0035 memory: 3506 grad_norm: 0.0677 loss: 0.1524 loss_sem_seg: 0.1524 2023/04/25 22:36:15 - mmengine - INFO - Epoch(train) [32][ 850/1196] lr: 8.0000e-04 eta: 1:07:38 time: 0.8061 data_time: 0.0035 memory: 3098 grad_norm: 0.0661 loss: 0.1695 loss_sem_seg: 0.1695 2023/04/25 22:36:56 - mmengine - INFO - Epoch(train) [32][ 900/1196] lr: 8.0000e-04 eta: 1:06:59 time: 0.8162 data_time: 0.0035 memory: 3544 grad_norm: 0.0674 loss: 0.1611 loss_sem_seg: 0.1611 2023/04/25 22:37:15 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 22:37:34 - mmengine - INFO - Epoch(train) [32][ 950/1196] lr: 8.0000e-04 eta: 1:06:19 time: 0.7730 data_time: 0.0036 memory: 3207 grad_norm: 0.0670 loss: 0.1620 loss_sem_seg: 0.1620 2023/04/25 22:38:15 - mmengine - INFO - Epoch(train) [32][1000/1196] lr: 8.0000e-04 eta: 1:05:40 time: 0.8008 data_time: 0.0034 memory: 3076 grad_norm: 0.0647 loss: 0.1535 loss_sem_seg: 0.1535 2023/04/25 22:38:55 - mmengine - INFO - Epoch(train) [32][1050/1196] lr: 8.0000e-04 eta: 1:05:00 time: 0.8045 data_time: 0.0036 memory: 3170 grad_norm: 0.0696 loss: 0.1542 loss_sem_seg: 0.1542 2023/04/25 22:39:33 - mmengine - INFO - Epoch(train) [32][1100/1196] lr: 8.0000e-04 eta: 1:04:20 time: 0.7716 data_time: 0.0035 memory: 3472 grad_norm: 0.0709 loss: 0.1667 loss_sem_seg: 0.1667 2023/04/25 22:40:13 - mmengine - INFO - Epoch(train) [32][1150/1196] lr: 8.0000e-04 eta: 1:03:41 time: 0.7861 data_time: 0.0035 memory: 3180 grad_norm: 0.0679 loss: 0.1661 loss_sem_seg: 0.1661 2023/04/25 22:40:49 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 22:40:49 - mmengine - INFO - Saving checkpoint at 32 epochs 2023/04/25 22:41:05 - mmengine - INFO - Epoch(val) [32][ 50/509] eta: 0:01:50 time: 0.2405 data_time: 0.0046 memory: 3278 2023/04/25 22:41:14 - mmengine - INFO - Epoch(val) [32][100/509] eta: 0:01:26 time: 0.1822 data_time: 0.0044 memory: 840 2023/04/25 22:41:25 - mmengine - INFO - Epoch(val) [32][150/509] eta: 0:01:15 time: 0.2112 data_time: 0.0044 memory: 843 2023/04/25 22:41:36 - mmengine - INFO - Epoch(val) [32][200/509] eta: 0:01:06 time: 0.2229 data_time: 0.0044 memory: 834 2023/04/25 22:41:47 - mmengine - INFO - Epoch(val) [32][250/509] eta: 0:00:55 time: 0.2171 data_time: 0.0046 memory: 850 2023/04/25 22:41:59 - mmengine - INFO - Epoch(val) [32][300/509] eta: 0:00:45 time: 0.2411 data_time: 0.0045 memory: 812 2023/04/25 22:42:08 - mmengine - INFO - Epoch(val) [32][350/509] eta: 0:00:34 time: 0.1958 data_time: 0.0045 memory: 825 2023/04/25 22:42:19 - mmengine - INFO - Epoch(val) [32][400/509] eta: 0:00:23 time: 0.2060 data_time: 0.0041 memory: 827 2023/04/25 22:42:32 - mmengine - INFO - Epoch(val) [32][450/509] eta: 0:00:12 time: 0.2624 data_time: 0.0047 memory: 845 2023/04/25 22:42:51 - mmengine - INFO - Epoch(val) [32][500/509] eta: 0:00:02 time: 0.3838 data_time: 0.0039 memory: 832 2023/04/25 22:43:32 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9737 | 0.5756 | 0.8038 | 0.8505 | 0.7733 | 0.7983 | 0.9066 | 0.0352 | 0.9468 | 0.4812 | 0.8248 | 0.0075 | 0.9105 | 0.6424 | 0.8801 | 0.6840 | 0.7390 | 0.6596 | 0.5270 | 0.6853 | 0.9232 | 0.7550 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 22:43:32 - mmengine - INFO - Epoch(val) [32][509/509] car: 0.9737 bicycle: 0.5756 motorcycle: 0.8038 truck: 0.8505 bus: 0.7733 person: 0.7983 bicyclist: 0.9066 motorcyclist: 0.0352 road: 0.9468 parking: 0.4812 sidewalk: 0.8248 other-ground: 0.0075 building: 0.9105 fence: 0.6424 vegetation: 0.8801 trunck: 0.6840 terrian: 0.7390 pole: 0.6596 traffic-sign: 0.5270 miou: 0.6853 acc: 0.9232 acc_cls: 0.7550 data_time: 0.0038 time: 0.3587 2023/04/25 22:44:12 - mmengine - INFO - Epoch(train) [33][ 50/1196] lr: 8.0000e-05 eta: 1:02:25 time: 0.7836 data_time: 0.0049 memory: 3528 grad_norm: 0.0670 loss: 0.1547 loss_sem_seg: 0.1547 2023/04/25 22:44:52 - mmengine - INFO - Epoch(train) [33][ 100/1196] lr: 8.0000e-05 eta: 1:01:45 time: 0.8138 data_time: 0.0036 memory: 3040 grad_norm: 0.0605 loss: 0.1618 loss_sem_seg: 0.1618 2023/04/25 22:45:33 - mmengine - INFO - Epoch(train) [33][ 150/1196] lr: 8.0000e-05 eta: 1:01:06 time: 0.8092 data_time: 0.0035 memory: 3167 grad_norm: 0.0628 loss: 0.1570 loss_sem_seg: 0.1570 2023/04/25 22:46:12 - mmengine - INFO - Epoch(train) [33][ 200/1196] lr: 8.0000e-05 eta: 1:00:26 time: 0.7869 data_time: 0.0035 memory: 3157 grad_norm: 0.0637 loss: 0.1627 loss_sem_seg: 0.1627 2023/04/25 22:46:50 - mmengine - INFO - Epoch(train) [33][ 250/1196] lr: 8.0000e-05 eta: 0:59:47 time: 0.7654 data_time: 0.0038 memory: 3310 grad_norm: 0.0648 loss: 0.1585 loss_sem_seg: 0.1585 2023/04/25 22:47:31 - mmengine - INFO - Epoch(train) [33][ 300/1196] lr: 8.0000e-05 eta: 0:59:07 time: 0.8073 data_time: 0.0035 memory: 3310 grad_norm: 0.0677 loss: 0.1567 loss_sem_seg: 0.1567 2023/04/25 22:48:10 - mmengine - INFO - Epoch(train) [33][ 350/1196] lr: 8.0000e-05 eta: 0:58:28 time: 0.7871 data_time: 0.0035 memory: 3297 grad_norm: 0.0577 loss: 0.1487 loss_sem_seg: 0.1487 2023/04/25 22:48:52 - mmengine - INFO - Epoch(train) [33][ 400/1196] lr: 8.0000e-05 eta: 0:57:48 time: 0.8319 data_time: 0.0035 memory: 3229 grad_norm: 0.0598 loss: 0.1563 loss_sem_seg: 0.1563 2023/04/25 22:49:33 - mmengine - INFO - Epoch(train) [33][ 450/1196] lr: 8.0000e-05 eta: 0:57:09 time: 0.8179 data_time: 0.0035 memory: 3182 grad_norm: 0.0591 loss: 0.1463 loss_sem_seg: 0.1463 2023/04/25 22:50:10 - mmengine - INFO - Epoch(train) [33][ 500/1196] lr: 8.0000e-05 eta: 0:56:29 time: 0.7523 data_time: 0.0037 memory: 3187 grad_norm: 0.0641 loss: 0.1520 loss_sem_seg: 0.1520 2023/04/25 22:50:51 - mmengine - INFO - Epoch(train) [33][ 550/1196] lr: 8.0000e-05 eta: 0:55:50 time: 0.8115 data_time: 0.0036 memory: 3164 grad_norm: 0.0641 loss: 0.1667 loss_sem_seg: 0.1667 2023/04/25 22:51:29 - mmengine - INFO - Epoch(train) [33][ 600/1196] lr: 8.0000e-05 eta: 0:55:10 time: 0.7728 data_time: 0.0035 memory: 3383 grad_norm: 0.0629 loss: 0.1546 loss_sem_seg: 0.1546 2023/04/25 22:52:09 - mmengine - INFO - Epoch(train) [33][ 650/1196] lr: 8.0000e-05 eta: 0:54:30 time: 0.7903 data_time: 0.0037 memory: 3287 grad_norm: 0.0644 loss: 0.1609 loss_sem_seg: 0.1609 2023/04/25 22:52:51 - mmengine - INFO - Epoch(train) [33][ 700/1196] lr: 8.0000e-05 eta: 0:53:51 time: 0.8366 data_time: 0.0036 memory: 3563 grad_norm: 0.0626 loss: 0.1558 loss_sem_seg: 0.1558 2023/04/25 22:53:13 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 22:53:29 - mmengine - INFO - Epoch(train) [33][ 750/1196] lr: 8.0000e-05 eta: 0:53:11 time: 0.7662 data_time: 0.0037 memory: 3502 grad_norm: 0.0621 loss: 0.1553 loss_sem_seg: 0.1553 2023/04/25 22:54:09 - mmengine - INFO - Epoch(train) [33][ 800/1196] lr: 8.0000e-05 eta: 0:52:32 time: 0.8008 data_time: 0.0037 memory: 3460 grad_norm: 0.0615 loss: 0.1548 loss_sem_seg: 0.1548 2023/04/25 22:54:49 - mmengine - INFO - Epoch(train) [33][ 850/1196] lr: 8.0000e-05 eta: 0:51:52 time: 0.8058 data_time: 0.0036 memory: 3308 grad_norm: 0.0663 loss: 0.1575 loss_sem_seg: 0.1575 2023/04/25 22:55:29 - mmengine - INFO - Epoch(train) [33][ 900/1196] lr: 8.0000e-05 eta: 0:51:13 time: 0.7883 data_time: 0.0037 memory: 3172 grad_norm: 0.0677 loss: 0.1640 loss_sem_seg: 0.1640 2023/04/25 22:56:09 - mmengine - INFO - Epoch(train) [33][ 950/1196] lr: 8.0000e-05 eta: 0:50:33 time: 0.7978 data_time: 0.0036 memory: 3395 grad_norm: 0.0622 loss: 0.1528 loss_sem_seg: 0.1528 2023/04/25 22:56:50 - mmengine - INFO - Epoch(train) [33][1000/1196] lr: 8.0000e-05 eta: 0:49:54 time: 0.8188 data_time: 0.0037 memory: 3236 grad_norm: 0.0605 loss: 0.1505 loss_sem_seg: 0.1505 2023/04/25 22:57:28 - mmengine - INFO - Epoch(train) [33][1050/1196] lr: 8.0000e-05 eta: 0:49:14 time: 0.7671 data_time: 0.0036 memory: 3147 grad_norm: 0.0607 loss: 0.1549 loss_sem_seg: 0.1549 2023/04/25 22:58:08 - mmengine - INFO - Epoch(train) [33][1100/1196] lr: 8.0000e-05 eta: 0:48:35 time: 0.8038 data_time: 0.0037 memory: 3368 grad_norm: 0.0656 loss: 0.1592 loss_sem_seg: 0.1592 2023/04/25 22:58:49 - mmengine - INFO - Epoch(train) [33][1150/1196] lr: 8.0000e-05 eta: 0:47:55 time: 0.8120 data_time: 0.0036 memory: 3231 grad_norm: 0.0646 loss: 0.1580 loss_sem_seg: 0.1580 2023/04/25 22:59:25 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 22:59:25 - mmengine - INFO - Saving checkpoint at 33 epochs 2023/04/25 22:59:39 - mmengine - INFO - Epoch(val) [33][ 50/509] eta: 0:01:33 time: 0.2040 data_time: 0.0047 memory: 3192 2023/04/25 22:59:50 - mmengine - INFO - Epoch(val) [33][100/509] eta: 0:01:23 time: 0.2055 data_time: 0.0044 memory: 840 2023/04/25 22:59:59 - mmengine - INFO - Epoch(val) [33][150/509] eta: 0:01:11 time: 0.1851 data_time: 0.0044 memory: 843 2023/04/25 23:00:10 - mmengine - INFO - Epoch(val) [33][200/509] eta: 0:01:02 time: 0.2155 data_time: 0.0045 memory: 834 2023/04/25 23:00:19 - mmengine - INFO - Epoch(val) [33][250/509] eta: 0:00:51 time: 0.1914 data_time: 0.0045 memory: 850 2023/04/25 23:00:28 - mmengine - INFO - Epoch(val) [33][300/509] eta: 0:00:40 time: 0.1700 data_time: 0.0044 memory: 812 2023/04/25 23:00:39 - mmengine - INFO - Epoch(val) [33][350/509] eta: 0:00:31 time: 0.2181 data_time: 0.0046 memory: 825 2023/04/25 23:00:50 - mmengine - INFO - Epoch(val) [33][400/509] eta: 0:00:21 time: 0.2248 data_time: 0.0044 memory: 827 2023/04/25 23:01:00 - mmengine - INFO - Epoch(val) [33][450/509] eta: 0:00:11 time: 0.2017 data_time: 0.0050 memory: 845 2023/04/25 23:01:19 - mmengine - INFO - Epoch(val) [33][500/509] eta: 0:00:01 time: 0.3797 data_time: 0.0041 memory: 832 2023/04/25 23:01:50 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9720 | 0.5642 | 0.8104 | 0.8030 | 0.7562 | 0.8058 | 0.9021 | 0.0500 | 0.9484 | 0.4975 | 0.8271 | 0.0050 | 0.9156 | 0.6672 | 0.8795 | 0.6898 | 0.7374 | 0.6617 | 0.5290 | 0.6854 | 0.9241 | 0.7565 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 23:01:50 - mmengine - INFO - Epoch(val) [33][509/509] car: 0.9720 bicycle: 0.5642 motorcycle: 0.8104 truck: 0.8030 bus: 0.7562 person: 0.8058 bicyclist: 0.9021 motorcyclist: 0.0500 road: 0.9484 parking: 0.4975 sidewalk: 0.8271 other-ground: 0.0050 building: 0.9156 fence: 0.6672 vegetation: 0.8795 trunck: 0.6898 terrian: 0.7374 pole: 0.6617 traffic-sign: 0.5290 miou: 0.6854 acc: 0.9241 acc_cls: 0.7565 data_time: 0.0040 time: 0.3834 2023/04/25 23:02:29 - mmengine - INFO - Epoch(train) [34][ 50/1196] lr: 8.0000e-05 eta: 0:46:39 time: 0.7844 data_time: 0.0046 memory: 3129 grad_norm: 0.0634 loss: 0.1497 loss_sem_seg: 0.1497 2023/04/25 23:03:09 - mmengine - INFO - Epoch(train) [34][ 100/1196] lr: 8.0000e-05 eta: 0:46:00 time: 0.7881 data_time: 0.0037 memory: 3236 grad_norm: 0.0609 loss: 0.1647 loss_sem_seg: 0.1647 2023/04/25 23:03:47 - mmengine - INFO - Epoch(train) [34][ 150/1196] lr: 8.0000e-05 eta: 0:45:20 time: 0.7716 data_time: 0.0035 memory: 3161 grad_norm: 0.0641 loss: 0.1575 loss_sem_seg: 0.1575 2023/04/25 23:04:27 - mmengine - INFO - Epoch(train) [34][ 200/1196] lr: 8.0000e-05 eta: 0:44:40 time: 0.7911 data_time: 0.0037 memory: 3107 grad_norm: 0.0678 loss: 0.1619 loss_sem_seg: 0.1619 2023/04/25 23:05:05 - mmengine - INFO - Epoch(train) [34][ 250/1196] lr: 8.0000e-05 eta: 0:44:01 time: 0.7684 data_time: 0.0035 memory: 3231 grad_norm: 0.0635 loss: 0.1483 loss_sem_seg: 0.1483 2023/04/25 23:05:44 - mmengine - INFO - Epoch(train) [34][ 300/1196] lr: 8.0000e-05 eta: 0:43:21 time: 0.7754 data_time: 0.0037 memory: 3119 grad_norm: 0.0650 loss: 0.1506 loss_sem_seg: 0.1506 2023/04/25 23:06:22 - mmengine - INFO - Epoch(train) [34][ 350/1196] lr: 8.0000e-05 eta: 0:42:41 time: 0.7555 data_time: 0.0037 memory: 3166 grad_norm: 0.0626 loss: 0.1565 loss_sem_seg: 0.1565 2023/04/25 23:07:01 - mmengine - INFO - Epoch(train) [34][ 400/1196] lr: 8.0000e-05 eta: 0:42:02 time: 0.7855 data_time: 0.0037 memory: 2994 grad_norm: 0.0576 loss: 0.1565 loss_sem_seg: 0.1565 2023/04/25 23:07:41 - mmengine - INFO - Epoch(train) [34][ 450/1196] lr: 8.0000e-05 eta: 0:41:22 time: 0.7942 data_time: 0.0037 memory: 3225 grad_norm: 0.0626 loss: 0.1481 loss_sem_seg: 0.1481 2023/04/25 23:08:20 - mmengine - INFO - Epoch(train) [34][ 500/1196] lr: 8.0000e-05 eta: 0:40:43 time: 0.7793 data_time: 0.0035 memory: 3475 grad_norm: 0.0606 loss: 0.1502 loss_sem_seg: 0.1502 2023/04/25 23:08:44 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 23:08:58 - mmengine - INFO - Epoch(train) [34][ 550/1196] lr: 8.0000e-05 eta: 0:40:03 time: 0.7743 data_time: 0.0038 memory: 3424 grad_norm: 0.0609 loss: 0.1552 loss_sem_seg: 0.1552 2023/04/25 23:09:37 - mmengine - INFO - Epoch(train) [34][ 600/1196] lr: 8.0000e-05 eta: 0:39:23 time: 0.7716 data_time: 0.0036 memory: 3333 grad_norm: 0.0609 loss: 0.1514 loss_sem_seg: 0.1514 2023/04/25 23:10:18 - mmengine - INFO - Epoch(train) [34][ 650/1196] lr: 8.0000e-05 eta: 0:38:44 time: 0.8157 data_time: 0.0036 memory: 3157 grad_norm: 0.0663 loss: 0.1656 loss_sem_seg: 0.1656 2023/04/25 23:10:57 - mmengine - INFO - Epoch(train) [34][ 700/1196] lr: 8.0000e-05 eta: 0:38:04 time: 0.7857 data_time: 0.0037 memory: 3194 grad_norm: 0.0647 loss: 0.1528 loss_sem_seg: 0.1528 2023/04/25 23:11:37 - mmengine - INFO - Epoch(train) [34][ 750/1196] lr: 8.0000e-05 eta: 0:37:25 time: 0.7919 data_time: 0.0035 memory: 3164 grad_norm: 0.0652 loss: 0.1481 loss_sem_seg: 0.1481 2023/04/25 23:12:18 - mmengine - INFO - Epoch(train) [34][ 800/1196] lr: 8.0000e-05 eta: 0:36:45 time: 0.8234 data_time: 0.0038 memory: 3193 grad_norm: 0.0682 loss: 0.1487 loss_sem_seg: 0.1487 2023/04/25 23:12:59 - mmengine - INFO - Epoch(train) [34][ 850/1196] lr: 8.0000e-05 eta: 0:36:06 time: 0.8149 data_time: 0.0036 memory: 3263 grad_norm: 0.0671 loss: 0.1532 loss_sem_seg: 0.1532 2023/04/25 23:13:39 - mmengine - INFO - Epoch(train) [34][ 900/1196] lr: 8.0000e-05 eta: 0:35:26 time: 0.8009 data_time: 0.0039 memory: 3462 grad_norm: 0.0612 loss: 0.1539 loss_sem_seg: 0.1539 2023/04/25 23:14:19 - mmengine - INFO - Epoch(train) [34][ 950/1196] lr: 8.0000e-05 eta: 0:34:47 time: 0.8086 data_time: 0.0037 memory: 3167 grad_norm: 0.0646 loss: 0.1634 loss_sem_seg: 0.1634 2023/04/25 23:15:00 - mmengine - INFO - Epoch(train) [34][1000/1196] lr: 8.0000e-05 eta: 0:34:07 time: 0.8104 data_time: 0.0035 memory: 3519 grad_norm: 0.0634 loss: 0.1596 loss_sem_seg: 0.1596 2023/04/25 23:15:40 - mmengine - INFO - Epoch(train) [34][1050/1196] lr: 8.0000e-05 eta: 0:33:28 time: 0.8011 data_time: 0.0035 memory: 3222 grad_norm: 0.0588 loss: 0.1598 loss_sem_seg: 0.1598 2023/04/25 23:16:19 - mmengine - INFO - Epoch(train) [34][1100/1196] lr: 8.0000e-05 eta: 0:32:48 time: 0.7812 data_time: 0.0037 memory: 3093 grad_norm: 0.0637 loss: 0.1627 loss_sem_seg: 0.1627 2023/04/25 23:16:58 - mmengine - INFO - Epoch(train) [34][1150/1196] lr: 8.0000e-05 eta: 0:32:09 time: 0.7850 data_time: 0.0036 memory: 3276 grad_norm: 0.0610 loss: 0.1544 loss_sem_seg: 0.1544 2023/04/25 23:17:33 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 23:17:33 - mmengine - INFO - Saving checkpoint at 34 epochs 2023/04/25 23:17:48 - mmengine - INFO - Epoch(val) [34][ 50/509] eta: 0:01:37 time: 0.2123 data_time: 0.0047 memory: 3210 2023/04/25 23:17:57 - mmengine - INFO - Epoch(val) [34][100/509] eta: 0:01:20 time: 0.1815 data_time: 0.0047 memory: 840 2023/04/25 23:18:08 - mmengine - INFO - Epoch(val) [34][150/509] eta: 0:01:12 time: 0.2161 data_time: 0.0047 memory: 843 2023/04/25 23:18:19 - mmengine - INFO - Epoch(val) [34][200/509] eta: 0:01:03 time: 0.2143 data_time: 0.0047 memory: 834 2023/04/25 23:18:29 - mmengine - INFO - Epoch(val) [34][250/509] eta: 0:00:53 time: 0.2047 data_time: 0.0046 memory: 850 2023/04/25 23:18:40 - mmengine - INFO - Epoch(val) [34][300/509] eta: 0:00:43 time: 0.2125 data_time: 0.0047 memory: 812 2023/04/25 23:18:51 - mmengine - INFO - Epoch(val) [34][350/509] eta: 0:00:33 time: 0.2244 data_time: 0.0047 memory: 825 2023/04/25 23:19:00 - mmengine - INFO - Epoch(val) [34][400/509] eta: 0:00:22 time: 0.1799 data_time: 0.0048 memory: 827 2023/04/25 23:19:09 - mmengine - INFO - Epoch(val) [34][450/509] eta: 0:00:12 time: 0.1872 data_time: 0.0048 memory: 845 2023/04/25 23:19:26 - mmengine - INFO - Epoch(val) [34][500/509] eta: 0:00:01 time: 0.3276 data_time: 0.0046 memory: 832 2023/04/25 23:20:01 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9726 | 0.5634 | 0.8156 | 0.7938 | 0.7549 | 0.8061 | 0.9025 | 0.0494 | 0.9483 | 0.4882 | 0.8267 | 0.0030 | 0.9157 | 0.6673 | 0.8770 | 0.6923 | 0.7295 | 0.6605 | 0.5260 | 0.6838 | 0.9231 | 0.7543 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 23:20:01 - mmengine - INFO - Epoch(val) [34][509/509] car: 0.9726 bicycle: 0.5634 motorcycle: 0.8156 truck: 0.7938 bus: 0.7549 person: 0.8061 bicyclist: 0.9025 motorcyclist: 0.0494 road: 0.9483 parking: 0.4882 sidewalk: 0.8267 other-ground: 0.0030 building: 0.9157 fence: 0.6673 vegetation: 0.8770 trunck: 0.6923 terrian: 0.7295 pole: 0.6605 traffic-sign: 0.5260 miou: 0.6838 acc: 0.9231 acc_cls: 0.7543 data_time: 0.0043 time: 0.3577 2023/04/25 23:20:40 - mmengine - INFO - Epoch(train) [35][ 50/1196] lr: 8.0000e-05 eta: 0:30:53 time: 0.7825 data_time: 0.0047 memory: 3613 grad_norm: 0.0648 loss: 0.1536 loss_sem_seg: 0.1536 2023/04/25 23:21:19 - mmengine - INFO - Epoch(train) [35][ 100/1196] lr: 8.0000e-05 eta: 0:30:13 time: 0.7860 data_time: 0.0036 memory: 3237 grad_norm: 0.0625 loss: 0.1545 loss_sem_seg: 0.1545 2023/04/25 23:21:59 - mmengine - INFO - Epoch(train) [35][ 150/1196] lr: 8.0000e-05 eta: 0:29:33 time: 0.7983 data_time: 0.0038 memory: 3556 grad_norm: 0.0660 loss: 0.1587 loss_sem_seg: 0.1587 2023/04/25 23:22:39 - mmengine - INFO - Epoch(train) [35][ 200/1196] lr: 8.0000e-05 eta: 0:28:54 time: 0.7993 data_time: 0.0037 memory: 3161 grad_norm: 0.0609 loss: 0.1625 loss_sem_seg: 0.1625 2023/04/25 23:23:19 - mmengine - INFO - Epoch(train) [35][ 250/1196] lr: 8.0000e-05 eta: 0:28:14 time: 0.8005 data_time: 0.0036 memory: 3116 grad_norm: 0.0632 loss: 0.1552 loss_sem_seg: 0.1552 2023/04/25 23:23:59 - mmengine - INFO - Epoch(train) [35][ 300/1196] lr: 8.0000e-05 eta: 0:27:35 time: 0.7912 data_time: 0.0036 memory: 3202 grad_norm: inf loss: 0.1525 loss_sem_seg: 0.1525 2023/04/25 23:24:26 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 23:24:37 - mmengine - INFO - Epoch(train) [35][ 350/1196] lr: 8.0000e-05 eta: 0:26:55 time: 0.7674 data_time: 0.0036 memory: 3241 grad_norm: 0.0662 loss: 0.1504 loss_sem_seg: 0.1504 2023/04/25 23:25:16 - mmengine - INFO - Epoch(train) [35][ 400/1196] lr: 8.0000e-05 eta: 0:26:16 time: 0.7830 data_time: 0.0036 memory: 3298 grad_norm: 0.0617 loss: 0.1564 loss_sem_seg: 0.1564 2023/04/25 23:25:53 - mmengine - INFO - Epoch(train) [35][ 450/1196] lr: 8.0000e-05 eta: 0:25:36 time: 0.7454 data_time: 0.0036 memory: 3353 grad_norm: 0.0669 loss: 0.1484 loss_sem_seg: 0.1484 2023/04/25 23:26:33 - mmengine - INFO - Epoch(train) [35][ 500/1196] lr: 8.0000e-05 eta: 0:24:56 time: 0.7952 data_time: 0.0038 memory: 3333 grad_norm: 0.0648 loss: 0.1533 loss_sem_seg: 0.1533 2023/04/25 23:27:12 - mmengine - INFO - Epoch(train) [35][ 550/1196] lr: 8.0000e-05 eta: 0:24:17 time: 0.7737 data_time: 0.0037 memory: 3478 grad_norm: 0.0666 loss: 0.1684 loss_sem_seg: 0.1684 2023/04/25 23:27:52 - mmengine - INFO - Epoch(train) [35][ 600/1196] lr: 8.0000e-05 eta: 0:23:37 time: 0.8012 data_time: 0.0037 memory: 3117 grad_norm: 0.0612 loss: 0.1430 loss_sem_seg: 0.1430 2023/04/25 23:28:33 - mmengine - INFO - Epoch(train) [35][ 650/1196] lr: 8.0000e-05 eta: 0:22:58 time: 0.8270 data_time: 0.0036 memory: 3204 grad_norm: 0.0605 loss: 0.1538 loss_sem_seg: 0.1538 2023/04/25 23:29:12 - mmengine - INFO - Epoch(train) [35][ 700/1196] lr: 8.0000e-05 eta: 0:22:18 time: 0.7832 data_time: 0.0038 memory: 3211 grad_norm: 0.0627 loss: 0.1488 loss_sem_seg: 0.1488 2023/04/25 23:29:51 - mmengine - INFO - Epoch(train) [35][ 750/1196] lr: 8.0000e-05 eta: 0:21:39 time: 0.7782 data_time: 0.0037 memory: 3733 grad_norm: 0.0608 loss: 0.1540 loss_sem_seg: 0.1540 2023/04/25 23:30:32 - mmengine - INFO - Epoch(train) [35][ 800/1196] lr: 8.0000e-05 eta: 0:20:59 time: 0.8131 data_time: 0.0038 memory: 3321 grad_norm: 0.0665 loss: 0.1498 loss_sem_seg: 0.1498 2023/04/25 23:31:13 - mmengine - INFO - Epoch(train) [35][ 850/1196] lr: 8.0000e-05 eta: 0:20:20 time: 0.8216 data_time: 0.0037 memory: 3228 grad_norm: 0.0600 loss: 0.1502 loss_sem_seg: 0.1502 2023/04/25 23:31:52 - mmengine - INFO - Epoch(train) [35][ 900/1196] lr: 8.0000e-05 eta: 0:19:40 time: 0.7833 data_time: 0.0037 memory: 3234 grad_norm: 0.0659 loss: 0.1545 loss_sem_seg: 0.1545 2023/04/25 23:32:33 - mmengine - INFO - Epoch(train) [35][ 950/1196] lr: 8.0000e-05 eta: 0:19:01 time: 0.8166 data_time: 0.0037 memory: 3240 grad_norm: 0.0599 loss: 0.1531 loss_sem_seg: 0.1531 2023/04/25 23:33:14 - mmengine - INFO - Epoch(train) [35][1000/1196] lr: 8.0000e-05 eta: 0:18:21 time: 0.8245 data_time: 0.0037 memory: 3173 grad_norm: 0.0654 loss: 0.1580 loss_sem_seg: 0.1580 2023/04/25 23:33:54 - mmengine - INFO - Epoch(train) [35][1050/1196] lr: 8.0000e-05 eta: 0:17:41 time: 0.7986 data_time: 0.0036 memory: 3281 grad_norm: 0.0676 loss: 0.1661 loss_sem_seg: 0.1661 2023/04/25 23:34:34 - mmengine - INFO - Epoch(train) [35][1100/1196] lr: 8.0000e-05 eta: 0:17:02 time: 0.8017 data_time: 0.0035 memory: 3339 grad_norm: 0.0644 loss: 0.1593 loss_sem_seg: 0.1593 2023/04/25 23:35:14 - mmengine - INFO - Epoch(train) [35][1150/1196] lr: 8.0000e-05 eta: 0:16:22 time: 0.8016 data_time: 0.0036 memory: 3128 grad_norm: 0.0634 loss: 0.1618 loss_sem_seg: 0.1618 2023/04/25 23:35:51 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 23:35:51 - mmengine - INFO - Saving checkpoint at 35 epochs 2023/04/25 23:36:05 - mmengine - INFO - Epoch(val) [35][ 50/509] eta: 0:01:34 time: 0.2066 data_time: 0.0048 memory: 3378 2023/04/25 23:36:16 - mmengine - INFO - Epoch(val) [35][100/509] eta: 0:01:25 time: 0.2092 data_time: 0.0045 memory: 840 2023/04/25 23:36:24 - mmengine - INFO - Epoch(val) [35][150/509] eta: 0:01:10 time: 0.1720 data_time: 0.0047 memory: 843 2023/04/25 23:36:35 - mmengine - INFO - Epoch(val) [35][200/509] eta: 0:01:01 time: 0.2116 data_time: 0.0044 memory: 834 2023/04/25 23:36:44 - mmengine - INFO - Epoch(val) [35][250/509] eta: 0:00:51 time: 0.1853 data_time: 0.0045 memory: 850 2023/04/25 23:36:55 - mmengine - INFO - Epoch(val) [35][300/509] eta: 0:00:42 time: 0.2231 data_time: 0.0044 memory: 812 2023/04/25 23:37:06 - mmengine - INFO - Epoch(val) [35][350/509] eta: 0:00:32 time: 0.2089 data_time: 0.0047 memory: 825 2023/04/25 23:37:16 - mmengine - INFO - Epoch(val) [35][400/509] eta: 0:00:22 time: 0.2001 data_time: 0.0044 memory: 827 2023/04/25 23:37:25 - mmengine - INFO - Epoch(val) [35][450/509] eta: 0:00:11 time: 0.1895 data_time: 0.0050 memory: 845 2023/04/25 23:37:39 - mmengine - INFO - Epoch(val) [35][500/509] eta: 0:00:01 time: 0.2853 data_time: 0.0043 memory: 832 2023/04/25 23:38:18 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9734 | 0.5593 | 0.8151 | 0.8151 | 0.7663 | 0.8084 | 0.9016 | 0.0430 | 0.9487 | 0.5033 | 0.8275 | 0.0033 | 0.9159 | 0.6692 | 0.8802 | 0.6935 | 0.7380 | 0.6602 | 0.5251 | 0.6867 | 0.9246 | 0.7560 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 23:38:18 - mmengine - INFO - Epoch(val) [35][509/509] car: 0.9734 bicycle: 0.5593 motorcycle: 0.8151 truck: 0.8151 bus: 0.7663 person: 0.8084 bicyclist: 0.9016 motorcyclist: 0.0430 road: 0.9487 parking: 0.5033 sidewalk: 0.8275 other-ground: 0.0033 building: 0.9159 fence: 0.6692 vegetation: 0.8802 trunck: 0.6935 terrian: 0.7380 pole: 0.6602 traffic-sign: 0.5251 miou: 0.6867 acc: 0.9246 acc_cls: 0.7560 data_time: 0.0041 time: 0.3218 2023/04/25 23:38:58 - mmengine - INFO - Epoch(train) [36][ 50/1196] lr: 8.0000e-05 eta: 0:15:06 time: 0.8122 data_time: 0.0046 memory: 3407 grad_norm: 0.0611 loss: 0.1534 loss_sem_seg: 0.1534 2023/04/25 23:39:39 - mmengine - INFO - Epoch(train) [36][ 100/1196] lr: 8.0000e-05 eta: 0:14:27 time: 0.8107 data_time: 0.0038 memory: 3364 grad_norm: 0.0645 loss: 0.1659 loss_sem_seg: 0.1659 2023/04/25 23:40:11 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 23:40:19 - mmengine - INFO - Epoch(train) [36][ 150/1196] lr: 8.0000e-05 eta: 0:13:47 time: 0.7984 data_time: 0.0037 memory: 3353 grad_norm: 0.0640 loss: 0.1609 loss_sem_seg: 0.1609 2023/04/25 23:40:59 - mmengine - INFO - Epoch(train) [36][ 200/1196] lr: 8.0000e-05 eta: 0:13:08 time: 0.8083 data_time: 0.0035 memory: 3141 grad_norm: 0.0587 loss: 0.1517 loss_sem_seg: 0.1517 2023/04/25 23:41:40 - mmengine - INFO - Epoch(train) [36][ 250/1196] lr: 8.0000e-05 eta: 0:12:28 time: 0.8197 data_time: 0.0036 memory: 3438 grad_norm: 0.0637 loss: 0.1466 loss_sem_seg: 0.1466 2023/04/25 23:42:20 - mmengine - INFO - Epoch(train) [36][ 300/1196] lr: 8.0000e-05 eta: 0:11:49 time: 0.8046 data_time: 0.0037 memory: 3299 grad_norm: 0.0560 loss: 0.1566 loss_sem_seg: 0.1566 2023/04/25 23:43:00 - mmengine - INFO - Epoch(train) [36][ 350/1196] lr: 8.0000e-05 eta: 0:11:09 time: 0.7978 data_time: 0.0038 memory: 3178 grad_norm: 0.0661 loss: 0.1644 loss_sem_seg: 0.1644 2023/04/25 23:43:40 - mmengine - INFO - Epoch(train) [36][ 400/1196] lr: 8.0000e-05 eta: 0:10:30 time: 0.8024 data_time: 0.0036 memory: 3158 grad_norm: 0.0607 loss: 0.1523 loss_sem_seg: 0.1523 2023/04/25 23:44:18 - mmengine - INFO - Epoch(train) [36][ 450/1196] lr: 8.0000e-05 eta: 0:09:50 time: 0.7502 data_time: 0.0037 memory: 3231 grad_norm: 0.0640 loss: 0.1581 loss_sem_seg: 0.1581 2023/04/25 23:44:59 - mmengine - INFO - Epoch(train) [36][ 500/1196] lr: 8.0000e-05 eta: 0:09:10 time: 0.8286 data_time: 0.0035 memory: 3330 grad_norm: 0.0602 loss: 0.1566 loss_sem_seg: 0.1566 2023/04/25 23:45:39 - mmengine - INFO - Epoch(train) [36][ 550/1196] lr: 8.0000e-05 eta: 0:08:31 time: 0.7842 data_time: 0.0038 memory: 3357 grad_norm: 0.0634 loss: 0.1563 loss_sem_seg: 0.1563 2023/04/25 23:46:18 - mmengine - INFO - Epoch(train) [36][ 600/1196] lr: 8.0000e-05 eta: 0:07:51 time: 0.7852 data_time: 0.0038 memory: 3172 grad_norm: 0.0708 loss: 0.1561 loss_sem_seg: 0.1561 2023/04/25 23:46:59 - mmengine - INFO - Epoch(train) [36][ 650/1196] lr: 8.0000e-05 eta: 0:07:12 time: 0.8316 data_time: 0.0036 memory: 3058 grad_norm: 0.0642 loss: 0.1529 loss_sem_seg: 0.1529 2023/04/25 23:47:39 - mmengine - INFO - Epoch(train) [36][ 700/1196] lr: 8.0000e-05 eta: 0:06:32 time: 0.7879 data_time: 0.0037 memory: 3168 grad_norm: 0.0646 loss: 0.1627 loss_sem_seg: 0.1627 2023/04/25 23:48:19 - mmengine - INFO - Epoch(train) [36][ 750/1196] lr: 8.0000e-05 eta: 0:05:53 time: 0.8034 data_time: 0.0037 memory: 3228 grad_norm: 0.0594 loss: 0.1540 loss_sem_seg: 0.1540 2023/04/25 23:48:59 - mmengine - INFO - Epoch(train) [36][ 800/1196] lr: 8.0000e-05 eta: 0:05:13 time: 0.7940 data_time: 0.0036 memory: 3295 grad_norm: 0.0632 loss: 0.1625 loss_sem_seg: 0.1625 2023/04/25 23:49:39 - mmengine - INFO - Epoch(train) [36][ 850/1196] lr: 8.0000e-05 eta: 0:04:33 time: 0.8069 data_time: 0.0037 memory: 3278 grad_norm: 0.0646 loss: 0.1504 loss_sem_seg: 0.1504 2023/04/25 23:50:18 - mmengine - INFO - Epoch(train) [36][ 900/1196] lr: 8.0000e-05 eta: 0:03:54 time: 0.7861 data_time: 0.0038 memory: 3338 grad_norm: 0.0604 loss: 0.1591 loss_sem_seg: 0.1591 2023/04/25 23:50:58 - mmengine - INFO - Epoch(train) [36][ 950/1196] lr: 8.0000e-05 eta: 0:03:14 time: 0.7840 data_time: 0.0036 memory: 3231 grad_norm: 0.0605 loss: 0.1585 loss_sem_seg: 0.1585 2023/04/25 23:51:38 - mmengine - INFO - Epoch(train) [36][1000/1196] lr: 8.0000e-05 eta: 0:02:35 time: 0.8170 data_time: 0.0038 memory: 3236 grad_norm: 0.0648 loss: 0.1589 loss_sem_seg: 0.1589 2023/04/25 23:52:19 - mmengine - INFO - Epoch(train) [36][1050/1196] lr: 8.0000e-05 eta: 0:01:55 time: 0.8132 data_time: 0.0037 memory: 3251 grad_norm: 0.0622 loss: 0.1526 loss_sem_seg: 0.1526 2023/04/25 23:52:59 - mmengine - INFO - Epoch(train) [36][1100/1196] lr: 8.0000e-05 eta: 0:01:15 time: 0.7995 data_time: 0.0036 memory: 3384 grad_norm: 0.0613 loss: 0.1475 loss_sem_seg: 0.1475 2023/04/25 23:53:31 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 23:53:39 - mmengine - INFO - Epoch(train) [36][1150/1196] lr: 8.0000e-05 eta: 0:00:36 time: 0.7986 data_time: 0.0039 memory: 3426 grad_norm: 0.0676 loss: 0.1528 loss_sem_seg: 0.1528 2023/04/25 23:54:15 - mmengine - INFO - Exp name: spvcnn_w32_8xb2-amp-3x_lpmix_semantickitti_20230425_125908 2023/04/25 23:54:15 - mmengine - INFO - Saving checkpoint at 36 epochs 2023/04/25 23:54:33 - mmengine - INFO - Epoch(val) [36][ 50/509] eta: 0:02:02 time: 0.2668 data_time: 0.0048 memory: 3276 2023/04/25 23:54:42 - mmengine - INFO - Epoch(val) [36][100/509] eta: 0:01:31 time: 0.1817 data_time: 0.0046 memory: 840 2023/04/25 23:54:53 - mmengine - INFO - Epoch(val) [36][150/509] eta: 0:01:18 time: 0.2112 data_time: 0.0046 memory: 843 2023/04/25 23:55:02 - mmengine - INFO - Epoch(val) [36][200/509] eta: 0:01:05 time: 0.1888 data_time: 0.0046 memory: 834 2023/04/25 23:55:12 - mmengine - INFO - Epoch(val) [36][250/509] eta: 0:00:54 time: 0.1953 data_time: 0.0048 memory: 850 2023/04/25 23:55:21 - mmengine - INFO - Epoch(val) [36][300/509] eta: 0:00:42 time: 0.1823 data_time: 0.0046 memory: 812 2023/04/25 23:55:33 - mmengine - INFO - Epoch(val) [36][350/509] eta: 0:00:33 time: 0.2462 data_time: 0.0047 memory: 825 2023/04/25 23:55:42 - mmengine - INFO - Epoch(val) [36][400/509] eta: 0:00:22 time: 0.1809 data_time: 0.0044 memory: 827 2023/04/25 23:55:56 - mmengine - INFO - Epoch(val) [36][450/509] eta: 0:00:12 time: 0.2650 data_time: 0.0047 memory: 845 2023/04/25 23:56:15 - mmengine - INFO - Epoch(val) [36][500/509] eta: 0:00:02 time: 0.3800 data_time: 0.0043 memory: 832 2023/04/25 23:56:55 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9726 | 0.5615 | 0.8134 | 0.8171 | 0.7597 | 0.8054 | 0.8983 | 0.0521 | 0.9484 | 0.4912 | 0.8277 | 0.0035 | 0.9157 | 0.6696 | 0.8800 | 0.6875 | 0.7381 | 0.6611 | 0.5238 | 0.6856 | 0.9244 | 0.7544 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/04/25 23:56:55 - mmengine - INFO - Epoch(val) [36][509/509] car: 0.9726 bicycle: 0.5615 motorcycle: 0.8134 truck: 0.8171 bus: 0.7597 person: 0.8054 bicyclist: 0.8983 motorcyclist: 0.0521 road: 0.9484 parking: 0.4912 sidewalk: 0.8277 other-ground: 0.0035 building: 0.9157 fence: 0.6696 vegetation: 0.8800 trunck: 0.6875 terrian: 0.7381 pole: 0.6611 traffic-sign: 0.5238 miou: 0.6856 acc: 0.9244 acc_cls: 0.7544 data_time: 0.0042 time: 0.3781