2023/05/12 23:32:04 - 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: 419298009 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /nvme/share/cuda-11.7 NVCC: Cuda compilation tools, release 11.7, V11.7.64 GCC: gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44) PyTorch: 2.0.0+cu117 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201703 - Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.7.3 (Git Hash 6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.7 - 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 8.5 - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.7, CUDNN_VERSION=8.5.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -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_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.0.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.15.1+cu117 OpenCV: 4.7.0 MMEngine: 0.7.2 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: pytorch Distributed training: True GPU number: 8 ------------------------------------------------------------ 2023/05/12 23:32:08 - 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']) ] eval_pipeline = [ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=4, use_dim=4, backend_args=None), dict(type='Pack3DDetInputs', keys=['points']) ] tta_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='TestTimeAug', transforms=[[{ 'type': 'RandomFlip3D', 'sync_2d': False, 'flip_ratio_bev_horizontal': 0.0, 'flip_ratio_bev_vertical': 0.0 }, { 'type': 'RandomFlip3D', 'sync_2d': False, 'flip_ratio_bev_horizontal': 0.0, 'flip_ratio_bev_vertical': 1.0 }, { 'type': 'RandomFlip3D', 'sync_2d': False, 'flip_ratio_bev_horizontal': 1.0, 'flip_ratio_bev_vertical': 0.0 }, { 'type': 'RandomFlip3D', 'sync_2d': False, 'flip_ratio_bev_horizontal': 1.0, 'flip_ratio_bev_vertical': 1.0 }], [{ 'type': 'GlobalRotScaleTrans', 'rot_range': [-0.78539816, -0.78539816], 'scale_ratio_range': [0.95, 0.95], 'translation_std': [0, 0, 0] }, { 'type': 'GlobalRotScaleTrans', 'rot_range': [-0.78539816, -0.78539816], 'scale_ratio_range': [1.0, 1.0], 'translation_std': [0, 0, 0] }, { 'type': 'GlobalRotScaleTrans', 'rot_range': [-0.78539816, -0.78539816], 'scale_ratio_range': [1.05, 1.05], 'translation_std': [0, 0, 0] }, { 'type': 'GlobalRotScaleTrans', 'rot_range': [0.0, 0.0], 'scale_ratio_range': [0.95, 0.95], 'translation_std': [0, 0, 0] }, { 'type': 'GlobalRotScaleTrans', 'rot_range': [0.0, 0.0], 'scale_ratio_range': [1.0, 1.0], 'translation_std': [0, 0, 0] }, { 'type': 'GlobalRotScaleTrans', 'rot_range': [0.0, 0.0], 'scale_ratio_range': [1.05, 1.05], 'translation_std': [0, 0, 0] }, { 'type': 'GlobalRotScaleTrans', 'rot_range': [0.78539816, 0.78539816], 'scale_ratio_range': [0.95, 0.95], 'translation_std': [0, 0, 0] }, { 'type': 'GlobalRotScaleTrans', 'rot_range': [0.78539816, 0.78539816], 'scale_ratio_range': [1.0, 1.0], 'translation_std': [0, 0, 0] }, { 'type': 'GlobalRotScaleTrans', 'rot_range': [0.78539816, 0.78539816], 'scale_ratio_range': [1.05, 1.05], 'translation_std': [0, 0, 0] }], [{ 'type': 'Pack3DDetInputs', 'keys': ['points'] }]]) ] train_dataloader = dict( batch_size=2, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), 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=1, persistent_workers=True, drop_last=False, 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']) ], 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=1, persistent_workers=True, drop_last=False, 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']) ], 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') tta_model = dict(type='Seg3DTTAModel') model = dict( type='MinkUNet', data_preprocessor=dict( type='Det3DDataPreprocessor', voxel=True, voxel_type='minkunet', batch_first=True, max_voxels=None, 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='MinkUNetBackbone', in_channels=4, num_stages=4, base_channels=32, encoder_channels=[32, 64, 128, 256], encoder_blocks=[2, 3, 4, 6], decoder_channels=[256, 128, 96, 96], decoder_blocks=[2, 2, 2, 2], sparseconv_backends='spconv'), 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()) lr = 0.008 optim_wrapper = dict( type='AmpOptimWrapper', optimizer=dict(type='AdamW', lr=0.008, weight_decay=0.01), clip_grad=dict(max_norm=10, norm_type=2), loss_scale='dynamic') train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=36, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='MultiStepLR', begin=0, end=36, by_epoch=True, milestones=[24, 32], gamma=0.1) ] auto_scale_lr = dict(enable=False, base_batch_size=32) 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=False, 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 launcher = 'pytorch' work_dir = './work_dirs/minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti' 2023/05/12 23:32:14 - 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 -------------------- 2023/05/12 23:32:19 - mmengine - WARNING - The prefix is not set in metric class SegMetric. Name of parameter - Initialization information backbone.conv_input.0.0.weight - torch.Size([32, 3, 3, 3, 4]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.0.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.0.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.0.weight - torch.Size([32, 3, 3, 3, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.0.weight - torch.Size([32, 2, 2, 2, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.conv1.weight - torch.Size([32, 3, 3, 3, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.bn1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.bn1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.conv2.weight - torch.Size([32, 3, 3, 3, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.bn2.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.bn2.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.conv1.weight - torch.Size([32, 3, 3, 3, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.bn1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.bn1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.conv2.weight - torch.Size([32, 3, 3, 3, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.bn2.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.bn2.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.0.weight - torch.Size([32, 2, 2, 2, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.1.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.conv1.weight - torch.Size([64, 3, 3, 3, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.conv2.weight - torch.Size([64, 3, 3, 3, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.downsample.0.weight - torch.Size([64, 1, 1, 1, 32]): 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.conv1.weight - torch.Size([64, 3, 3, 3, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.conv2.weight - torch.Size([64, 3, 3, 3, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.conv1.weight - torch.Size([64, 3, 3, 3, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.conv2.weight - torch.Size([64, 3, 3, 3, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.0.weight - torch.Size([64, 2, 2, 2, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.conv1.weight - torch.Size([128, 3, 3, 3, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.conv2.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.downsample.0.weight - torch.Size([128, 1, 1, 1, 64]): 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.conv1.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.conv2.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.conv1.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.conv2.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.conv1.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.conv2.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.0.weight - torch.Size([128, 2, 2, 2, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.conv1.weight - torch.Size([256, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.conv2.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.downsample.0.weight - torch.Size([256, 1, 1, 1, 128]): 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.conv1.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.conv2.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.conv1.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.conv2.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.conv1.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.conv2.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.conv1.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.conv2.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.conv1.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.conv2.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.0.weight - torch.Size([256, 2, 2, 2, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.conv1.weight - torch.Size([256, 3, 3, 3, 384]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.conv2.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.downsample.0.weight - torch.Size([256, 1, 1, 1, 384]): 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.conv1.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.conv2.weight - torch.Size([256, 3, 3, 3, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.0.weight - torch.Size([128, 2, 2, 2, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.conv1.weight - torch.Size([128, 3, 3, 3, 192]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.conv2.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.downsample.0.weight - torch.Size([128, 1, 1, 1, 192]): 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.conv1.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.conv2.weight - torch.Size([128, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.0.weight - torch.Size([96, 2, 2, 2, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.conv1.weight - torch.Size([96, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.bn1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.bn1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.conv2.weight - torch.Size([96, 3, 3, 3, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.bn2.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.bn2.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.downsample.0.weight - torch.Size([96, 1, 1, 1, 128]): 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.conv1.weight - torch.Size([96, 3, 3, 3, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.bn1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.bn1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.conv2.weight - torch.Size([96, 3, 3, 3, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.bn2.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.bn2.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.0.weight - torch.Size([96, 2, 2, 2, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.conv1.weight - torch.Size([96, 3, 3, 3, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.bn1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.bn1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.conv2.weight - torch.Size([96, 3, 3, 3, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.bn2.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.bn2.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.downsample.0.weight - torch.Size([96, 1, 1, 1, 128]): 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.conv1.weight - torch.Size([96, 3, 3, 3, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.bn1.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.bn1.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.conv2.weight - torch.Size([96, 3, 3, 3, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.bn2.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.bn2.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 2023/05/12 23:32:24 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/05/12 23:32:24 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/05/12 23:32:24 - mmengine - INFO - Checkpoints will be saved to /nvme/sunjiahao/projects/mmdetection3d/work_dirs/minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti. 2023/05/12 23:32:54 - mmengine - INFO - Epoch(train) [1][ 50/1196] lr: 8.0000e-03 eta: 7:16:02 time: 0.6083 data_time: 0.0063 memory: 2838 grad_norm: 0.7356 loss: 1.5125 loss_sem_seg: 1.5125 2023/05/12 23:33:07 - mmengine - INFO - Epoch(train) [1][ 100/1196] lr: 8.0000e-03 eta: 5:04:30 time: 0.2423 data_time: 0.0033 memory: 2763 grad_norm: 0.6169 loss: 1.0238 loss_sem_seg: 1.0238 2023/05/12 23:33:19 - mmengine - INFO - Epoch(train) [1][ 150/1196] lr: 8.0000e-03 eta: 4:20:28 time: 0.2421 data_time: 0.0035 memory: 2993 grad_norm: 0.6083 loss: 0.8840 loss_sem_seg: 0.8840 2023/05/12 23:33:30 - mmengine - INFO - Epoch(train) [1][ 200/1196] lr: 8.0000e-03 eta: 3:56:22 time: 0.2310 data_time: 0.0033 memory: 3066 grad_norm: inf loss: 0.8104 loss_sem_seg: 0.8104 2023/05/12 23:33:44 - mmengine - INFO - Epoch(train) [1][ 250/1196] lr: 8.0000e-03 eta: 3:49:06 time: 0.2820 data_time: 0.0032 memory: 2651 grad_norm: 0.7366 loss: 0.7549 loss_sem_seg: 0.7549 2023/05/12 23:33:59 - mmengine - INFO - Epoch(train) [1][ 300/1196] lr: 8.0000e-03 eta: 3:46:24 time: 0.3005 data_time: 0.0031 memory: 2911 grad_norm: 0.6788 loss: 0.7355 loss_sem_seg: 0.7355 2023/05/12 23:34:16 - mmengine - INFO - Epoch(train) [1][ 350/1196] lr: 8.0000e-03 eta: 3:48:24 time: 0.3400 data_time: 0.0030 memory: 3149 grad_norm: inf loss: 0.7167 loss_sem_seg: 0.7167 2023/05/12 23:34:32 - mmengine - INFO - Epoch(train) [1][ 400/1196] lr: 8.0000e-03 eta: 3:48:02 time: 0.3199 data_time: 0.0032 memory: 2975 grad_norm: 0.5932 loss: 0.6240 loss_sem_seg: 0.6240 2023/05/12 23:34:49 - mmengine - INFO - Epoch(train) [1][ 450/1196] lr: 8.0000e-03 eta: 3:49:27 time: 0.3420 data_time: 0.0031 memory: 2744 grad_norm: 0.5871 loss: 0.6203 loss_sem_seg: 0.6203 2023/05/12 23:35:07 - mmengine - INFO - Epoch(train) [1][ 500/1196] lr: 8.0000e-03 eta: 3:50:44 time: 0.3451 data_time: 0.0031 memory: 2914 grad_norm: 0.5002 loss: 0.5848 loss_sem_seg: 0.5848 2023/05/12 23:35:25 - mmengine - INFO - Epoch(train) [1][ 550/1196] lr: 8.0000e-03 eta: 3:53:09 time: 0.3670 data_time: 0.0036 memory: 2726 grad_norm: 0.5612 loss: 0.5838 loss_sem_seg: 0.5838 2023/05/12 23:35:46 - mmengine - INFO - Epoch(train) [1][ 600/1196] lr: 8.0000e-03 eta: 3:57:58 time: 0.4154 data_time: 0.0038 memory: 3023 grad_norm: 0.4812 loss: 0.5622 loss_sem_seg: 0.5622 2023/05/12 23:36:09 - mmengine - INFO - Epoch(train) [1][ 650/1196] lr: 8.0000e-03 eta: 4:04:15 time: 0.4572 data_time: 0.0039 memory: 2965 grad_norm: 0.4621 loss: 0.5194 loss_sem_seg: 0.5194 2023/05/12 23:36:34 - mmengine - INFO - Epoch(train) [1][ 700/1196] lr: 8.0000e-03 eta: 4:11:40 time: 0.4983 data_time: 0.0041 memory: 2864 grad_norm: 0.4675 loss: 0.5134 loss_sem_seg: 0.5134 2023/05/12 23:37:01 - mmengine - INFO - Epoch(train) [1][ 750/1196] lr: 8.0000e-03 eta: 4:20:49 time: 0.5576 data_time: 0.0037 memory: 2768 grad_norm: 0.4147 loss: 0.5068 loss_sem_seg: 0.5068 2023/05/12 23:37:30 - mmengine - INFO - Epoch(train) [1][ 800/1196] lr: 8.0000e-03 eta: 4:29:38 time: 0.5771 data_time: 0.0039 memory: 3059 grad_norm: 0.4092 loss: 0.5415 loss_sem_seg: 0.5415 2023/05/12 23:37:59 - mmengine - INFO - Epoch(train) [1][ 850/1196] lr: 8.0000e-03 eta: 4:36:52 time: 0.5653 data_time: 0.0037 memory: 2850 grad_norm: 0.4425 loss: 0.5066 loss_sem_seg: 0.5066 2023/05/12 23:38:22 - mmengine - INFO - Epoch(train) [1][ 900/1196] lr: 8.0000e-03 eta: 4:39:19 time: 0.4650 data_time: 0.0036 memory: 2927 grad_norm: 0.4090 loss: 0.5071 loss_sem_seg: 0.5071 2023/05/12 23:38:45 - mmengine - INFO - Epoch(train) [1][ 950/1196] lr: 8.0000e-03 eta: 4:41:31 time: 0.4657 data_time: 0.0034 memory: 2767 grad_norm: 0.4151 loss: 0.4750 loss_sem_seg: 0.4750 2023/05/12 23:39:12 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/12 23:39:12 - mmengine - INFO - Epoch(train) [1][1000/1196] lr: 8.0000e-03 eta: 4:45:52 time: 0.5348 data_time: 0.0031 memory: 2779 grad_norm: 0.3955 loss: 0.4743 loss_sem_seg: 0.4743 2023/05/12 23:39:42 - mmengine - INFO - Epoch(train) [1][1050/1196] lr: 8.0000e-03 eta: 4:52:16 time: 0.6101 data_time: 0.0033 memory: 2821 grad_norm: 0.3608 loss: 0.4623 loss_sem_seg: 0.4623 2023/05/12 23:40:12 - mmengine - INFO - Epoch(train) [1][1100/1196] lr: 8.0000e-03 eta: 4:57:11 time: 0.5833 data_time: 0.0034 memory: 2822 grad_norm: 0.3812 loss: 0.4890 loss_sem_seg: 0.4890 2023/05/12 23:40:40 - mmengine - INFO - Epoch(train) [1][1150/1196] lr: 8.0000e-03 eta: 5:01:26 time: 0.5763 data_time: 0.0032 memory: 2952 grad_norm: 0.3354 loss: 0.4478 loss_sem_seg: 0.4478 2023/05/12 23:41:08 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/12 23:41:08 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/05/12 23:41:34 - mmengine - INFO - Epoch(val) [1][ 50/509] eta: 0:03:11 time: 0.4182 data_time: 0.0032 memory: 2686 2023/05/12 23:41:51 - mmengine - INFO - Epoch(val) [1][100/509] eta: 0:02:35 time: 0.3442 data_time: 0.0022 memory: 920 2023/05/12 23:42:08 - mmengine - INFO - Epoch(val) [1][150/509] eta: 0:02:10 time: 0.3270 data_time: 0.0022 memory: 918 2023/05/12 23:42:24 - mmengine - INFO - Epoch(val) [1][200/509] eta: 0:01:49 time: 0.3298 data_time: 0.0022 memory: 906 2023/05/12 23:42:43 - mmengine - INFO - Epoch(val) [1][250/509] eta: 0:01:32 time: 0.3716 data_time: 0.0022 memory: 931 2023/05/12 23:42:57 - mmengine - INFO - Epoch(val) [1][300/509] eta: 0:01:12 time: 0.2860 data_time: 0.0021 memory: 868 2023/05/12 23:43:13 - mmengine - INFO - Epoch(val) [1][350/509] eta: 0:00:54 time: 0.3113 data_time: 0.0021 memory: 893 2023/05/12 23:43:30 - mmengine - INFO - Epoch(val) [1][400/509] eta: 0:00:37 time: 0.3475 data_time: 0.0023 memory: 901 2023/05/12 23:43:48 - mmengine - INFO - Epoch(val) [1][450/509] eta: 0:00:20 time: 0.3513 data_time: 0.0023 memory: 915 2023/05/12 23:44:04 - mmengine - INFO - Epoch(val) [1][500/509] eta: 0:00:03 time: 0.3154 data_time: 0.0022 memory: 898 2023/05/12 23:44:22 - 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 | 0.8934 | 0.0026 | 0.0660 | 0.0632 | 0.0022 | 0.0549 | 0.0393 | 0.0001 | 0.8909 | 0.2217 | 0.7422 | 0.0000 | 0.8645 | 0.4861 | 0.8573 | 0.5699 | 0.7336 | 0.5344 | 0.2926 | 0.3850 | 0.8883 | 0.4432 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/12 23:44:22 - mmengine - INFO - Epoch(val) [1][509/509] car: 0.8934 bicycle: 0.0026 motorcycle: 0.0660 truck: 0.0632 bus: 0.0022 person: 0.0549 bicyclist: 0.0393 motorcyclist: 0.0001 road: 0.8909 parking: 0.2217 sidewalk: 0.7422 other-ground: 0.0000 building: 0.8645 fence: 0.4861 vegetation: 0.8573 trunck: 0.5699 terrian: 0.7336 pole: 0.5344 traffic-sign: 0.2926 miou: 0.3850 acc: 0.8883 acc_cls: 0.4432 data_time: 0.0021 time: 0.3258 2023/05/12 23:44:53 - mmengine - INFO - Epoch(train) [2][ 50/1196] lr: 8.0000e-03 eta: 5:10:34 time: 0.6216 data_time: 0.0044 memory: 2864 grad_norm: 0.3492 loss: 0.4332 loss_sem_seg: 0.4332 2023/05/12 23:45:23 - mmengine - INFO - Epoch(train) [2][ 100/1196] lr: 8.0000e-03 eta: 5:14:03 time: 0.5895 data_time: 0.0033 memory: 2860 grad_norm: 0.3488 loss: 0.4276 loss_sem_seg: 0.4276 2023/05/12 23:45:53 - mmengine - INFO - Epoch(train) [2][ 150/1196] lr: 8.0000e-03 eta: 5:17:41 time: 0.6064 data_time: 0.0035 memory: 2886 grad_norm: 0.3656 loss: 0.4325 loss_sem_seg: 0.4325 2023/05/12 23:46:24 - mmengine - INFO - Epoch(train) [2][ 200/1196] lr: 8.0000e-03 eta: 5:21:18 time: 0.6175 data_time: 0.0033 memory: 2809 grad_norm: 0.3595 loss: 0.4352 loss_sem_seg: 0.4352 2023/05/12 23:46:54 - mmengine - INFO - Epoch(train) [2][ 250/1196] lr: 8.0000e-03 eta: 5:24:19 time: 0.6047 data_time: 0.0032 memory: 3129 grad_norm: 0.3499 loss: 0.4245 loss_sem_seg: 0.4245 2023/05/12 23:47:25 - mmengine - INFO - Epoch(train) [2][ 300/1196] lr: 8.0000e-03 eta: 5:27:30 time: 0.6224 data_time: 0.0034 memory: 2835 grad_norm: 0.3287 loss: 0.4099 loss_sem_seg: 0.4099 2023/05/12 23:47:56 - mmengine - INFO - Epoch(train) [2][ 350/1196] lr: 8.0000e-03 eta: 5:30:14 time: 0.6127 data_time: 0.0034 memory: 2726 grad_norm: 0.2807 loss: 0.3889 loss_sem_seg: 0.3889 2023/05/12 23:48:26 - mmengine - INFO - Epoch(train) [2][ 400/1196] lr: 8.0000e-03 eta: 5:32:38 time: 0.6063 data_time: 0.0034 memory: 2755 grad_norm: 0.3172 loss: 0.4320 loss_sem_seg: 0.4320 2023/05/12 23:48:57 - mmengine - INFO - Epoch(train) [2][ 450/1196] lr: 8.0000e-03 eta: 5:35:15 time: 0.6250 data_time: 0.0032 memory: 2922 grad_norm: 0.2948 loss: 0.3924 loss_sem_seg: 0.3924 2023/05/12 23:49:28 - mmengine - INFO - Epoch(train) [2][ 500/1196] lr: 8.0000e-03 eta: 5:37:26 time: 0.6136 data_time: 0.0033 memory: 2973 grad_norm: 0.2810 loss: 0.3834 loss_sem_seg: 0.3834 2023/05/12 23:49:59 - mmengine - INFO - Epoch(train) [2][ 550/1196] lr: 8.0000e-03 eta: 5:39:31 time: 0.6155 data_time: 0.0034 memory: 2914 grad_norm: 0.3220 loss: 0.4092 loss_sem_seg: 0.4092 2023/05/12 23:50:29 - mmengine - INFO - Epoch(train) [2][ 600/1196] lr: 8.0000e-03 eta: 5:41:17 time: 0.6071 data_time: 0.0033 memory: 3257 grad_norm: 0.2932 loss: 0.4059 loss_sem_seg: 0.4059 2023/05/12 23:50:59 - mmengine - INFO - Epoch(train) [2][ 650/1196] lr: 8.0000e-03 eta: 5:42:53 time: 0.6041 data_time: 0.0032 memory: 2775 grad_norm: 0.2799 loss: 0.4095 loss_sem_seg: 0.4095 2023/05/12 23:51:30 - mmengine - INFO - Epoch(train) [2][ 700/1196] lr: 8.0000e-03 eta: 5:44:32 time: 0.6141 data_time: 0.0031 memory: 2934 grad_norm: 0.3547 loss: 0.4378 loss_sem_seg: 0.4378 2023/05/12 23:52:01 - mmengine - INFO - Epoch(train) [2][ 750/1196] lr: 8.0000e-03 eta: 5:46:00 time: 0.6093 data_time: 0.0031 memory: 2665 grad_norm: 0.2944 loss: 0.4035 loss_sem_seg: 0.4035 2023/05/12 23:52:31 - mmengine - INFO - Epoch(train) [2][ 800/1196] lr: 8.0000e-03 eta: 5:47:26 time: 0.6129 data_time: 0.0033 memory: 2868 grad_norm: 0.2575 loss: 0.4088 loss_sem_seg: 0.4088 2023/05/12 23:52:34 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/12 23:53:01 - mmengine - INFO - Epoch(train) [2][ 850/1196] lr: 8.0000e-03 eta: 5:48:35 time: 0.6016 data_time: 0.0032 memory: 2770 grad_norm: 0.2832 loss: 0.3981 loss_sem_seg: 0.3981 2023/05/12 23:53:32 - mmengine - INFO - Epoch(train) [2][ 900/1196] lr: 8.0000e-03 eta: 5:49:44 time: 0.6073 data_time: 0.0034 memory: 2913 grad_norm: 0.2664 loss: 0.3647 loss_sem_seg: 0.3647 2023/05/12 23:54:02 - mmengine - INFO - Epoch(train) [2][ 950/1196] lr: 8.0000e-03 eta: 5:50:47 time: 0.6049 data_time: 0.0032 memory: 2952 grad_norm: 0.2582 loss: 0.3758 loss_sem_seg: 0.3758 2023/05/12 23:54:33 - mmengine - INFO - Epoch(train) [2][1000/1196] lr: 8.0000e-03 eta: 5:51:57 time: 0.6173 data_time: 0.0033 memory: 2768 grad_norm: 0.2941 loss: 0.3747 loss_sem_seg: 0.3747 2023/05/12 23:55:03 - mmengine - INFO - Epoch(train) [2][1050/1196] lr: 8.0000e-03 eta: 5:52:55 time: 0.6097 data_time: 0.0034 memory: 2850 grad_norm: 0.2703 loss: 0.3639 loss_sem_seg: 0.3639 2023/05/12 23:55:34 - mmengine - INFO - Epoch(train) [2][1100/1196] lr: 8.0000e-03 eta: 5:53:54 time: 0.6142 data_time: 0.0034 memory: 2919 grad_norm: 0.2466 loss: 0.3604 loss_sem_seg: 0.3604 2023/05/12 23:56:04 - mmengine - INFO - Epoch(train) [2][1150/1196] lr: 8.0000e-03 eta: 5:54:44 time: 0.6085 data_time: 0.0034 memory: 3064 grad_norm: 0.2563 loss: 0.3979 loss_sem_seg: 0.3979 2023/05/12 23:56:32 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/12 23:56:32 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/05/12 23:56:57 - mmengine - INFO - Epoch(val) [2][ 50/509] eta: 0:02:50 time: 0.3713 data_time: 0.0022 memory: 2981 2023/05/12 23:57:14 - mmengine - INFO - Epoch(val) [2][100/509] eta: 0:02:25 time: 0.3399 data_time: 0.0023 memory: 920 2023/05/12 23:57:31 - mmengine - INFO - Epoch(val) [2][150/509] eta: 0:02:05 time: 0.3345 data_time: 0.0027 memory: 918 2023/05/12 23:57:48 - mmengine - INFO - Epoch(val) [2][200/509] eta: 0:01:47 time: 0.3500 data_time: 0.0027 memory: 906 2023/05/12 23:58:07 - mmengine - INFO - Epoch(val) [2][250/509] eta: 0:01:31 time: 0.3792 data_time: 0.0026 memory: 931 2023/05/12 23:58:23 - mmengine - INFO - Epoch(val) [2][300/509] eta: 0:01:12 time: 0.3067 data_time: 0.0025 memory: 868 2023/05/12 23:58:38 - mmengine - INFO - Epoch(val) [2][350/509] eta: 0:00:54 time: 0.3133 data_time: 0.0021 memory: 893 2023/05/12 23:58:56 - mmengine - INFO - Epoch(val) [2][400/509] eta: 0:00:37 time: 0.3569 data_time: 0.0021 memory: 901 2023/05/12 23:59:13 - mmengine - INFO - Epoch(val) [2][450/509] eta: 0:00:20 time: 0.3307 data_time: 0.0021 memory: 915 2023/05/12 23:59:28 - mmengine - INFO - Epoch(val) [2][500/509] eta: 0:00:03 time: 0.3148 data_time: 0.0021 memory: 898 2023/05/12 23:59:48 - 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 | 0.9136 | 0.0485 | 0.3486 | 0.2451 | 0.0593 | 0.4094 | 0.4256 | 0.0026 | 0.9185 | 0.3290 | 0.7785 | 0.0000 | 0.8611 | 0.5017 | 0.8849 | 0.6197 | 0.7540 | 0.6020 | 0.4133 | 0.4798 | 0.9056 | 0.5647 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/12 23:59:48 - mmengine - INFO - Epoch(val) [2][509/509] car: 0.9136 bicycle: 0.0485 motorcycle: 0.3486 truck: 0.2451 bus: 0.0593 person: 0.4094 bicyclist: 0.4256 motorcyclist: 0.0026 road: 0.9185 parking: 0.3290 sidewalk: 0.7785 other-ground: 0.0000 building: 0.8611 fence: 0.5017 vegetation: 0.8849 trunck: 0.6197 terrian: 0.7540 pole: 0.6020 traffic-sign: 0.4133 miou: 0.4798 acc: 0.9056 acc_cls: 0.5647 data_time: 0.0020 time: 0.3260 2023/05/13 00:00:19 - mmengine - INFO - Epoch(train) [3][ 50/1196] lr: 8.0000e-03 eta: 5:56:13 time: 0.6107 data_time: 0.0043 memory: 2812 grad_norm: 0.2888 loss: 0.3585 loss_sem_seg: 0.3585 2023/05/13 00:00:49 - mmengine - INFO - Epoch(train) [3][ 100/1196] lr: 8.0000e-03 eta: 5:56:52 time: 0.6072 data_time: 0.0033 memory: 2714 grad_norm: 0.2705 loss: 0.3720 loss_sem_seg: 0.3720 2023/05/13 00:01:20 - mmengine - INFO - Epoch(train) [3][ 150/1196] lr: 8.0000e-03 eta: 5:57:38 time: 0.6191 data_time: 0.0033 memory: 2977 grad_norm: 0.2167 loss: 0.3639 loss_sem_seg: 0.3639 2023/05/13 00:01:51 - mmengine - INFO - Epoch(train) [3][ 200/1196] lr: 8.0000e-03 eta: 5:58:21 time: 0.6183 data_time: 0.0034 memory: 2856 grad_norm: 0.2291 loss: 0.3448 loss_sem_seg: 0.3448 2023/05/13 00:02:23 - mmengine - INFO - Epoch(train) [3][ 250/1196] lr: 8.0000e-03 eta: 5:59:09 time: 0.6285 data_time: 0.0033 memory: 2922 grad_norm: 0.2460 loss: 0.3529 loss_sem_seg: 0.3529 2023/05/13 00:02:53 - mmengine - INFO - Epoch(train) [3][ 300/1196] lr: 8.0000e-03 eta: 5:59:41 time: 0.6111 data_time: 0.0034 memory: 2879 grad_norm: 0.2268 loss: 0.3484 loss_sem_seg: 0.3484 2023/05/13 00:03:24 - mmengine - INFO - Epoch(train) [3][ 350/1196] lr: 8.0000e-03 eta: 6:00:14 time: 0.6169 data_time: 0.0032 memory: 2893 grad_norm: 0.2300 loss: 0.3386 loss_sem_seg: 0.3386 2023/05/13 00:03:54 - mmengine - INFO - Epoch(train) [3][ 400/1196] lr: 8.0000e-03 eta: 6:00:36 time: 0.6038 data_time: 0.0032 memory: 2891 grad_norm: 0.2296 loss: 0.3600 loss_sem_seg: 0.3600 2023/05/13 00:04:25 - mmengine - INFO - Epoch(train) [3][ 450/1196] lr: 8.0000e-03 eta: 6:01:03 time: 0.6125 data_time: 0.0033 memory: 3124 grad_norm: 0.2538 loss: 0.3691 loss_sem_seg: 0.3691 2023/05/13 00:04:54 - mmengine - INFO - Epoch(train) [3][ 500/1196] lr: 8.0000e-03 eta: 6:01:09 time: 0.5872 data_time: 0.0032 memory: 2691 grad_norm: 0.2531 loss: 0.3643 loss_sem_seg: 0.3643 2023/05/13 00:05:25 - mmengine - INFO - Epoch(train) [3][ 550/1196] lr: 8.0000e-03 eta: 6:01:34 time: 0.6151 data_time: 0.0034 memory: 2719 grad_norm: 0.2144 loss: 0.3268 loss_sem_seg: 0.3268 2023/05/13 00:05:56 - mmengine - INFO - Epoch(train) [3][ 600/1196] lr: 8.0000e-03 eta: 6:02:01 time: 0.6213 data_time: 0.0034 memory: 2831 grad_norm: 0.2210 loss: 0.3596 loss_sem_seg: 0.3596 2023/05/13 00:06:01 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:06:27 - mmengine - INFO - Epoch(train) [3][ 650/1196] lr: 8.0000e-03 eta: 6:02:20 time: 0.6128 data_time: 0.0035 memory: 3016 grad_norm: 0.2407 loss: 0.3563 loss_sem_seg: 0.3563 2023/05/13 00:06:58 - mmengine - INFO - Epoch(train) [3][ 700/1196] lr: 8.0000e-03 eta: 6:02:43 time: 0.6209 data_time: 0.0033 memory: 2723 grad_norm: 0.2304 loss: 0.3488 loss_sem_seg: 0.3488 2023/05/13 00:07:28 - mmengine - INFO - Epoch(train) [3][ 750/1196] lr: 8.0000e-03 eta: 6:02:54 time: 0.6046 data_time: 0.0035 memory: 2702 grad_norm: 0.2298 loss: 0.3403 loss_sem_seg: 0.3403 2023/05/13 00:07:59 - mmengine - INFO - Epoch(train) [3][ 800/1196] lr: 8.0000e-03 eta: 6:03:11 time: 0.6162 data_time: 0.0034 memory: 2928 grad_norm: 0.2561 loss: 0.3545 loss_sem_seg: 0.3545 2023/05/13 00:08:29 - mmengine - INFO - Epoch(train) [3][ 850/1196] lr: 8.0000e-03 eta: 6:03:23 time: 0.6109 data_time: 0.0034 memory: 2865 grad_norm: 0.2320 loss: 0.3482 loss_sem_seg: 0.3482 2023/05/13 00:08:59 - mmengine - INFO - Epoch(train) [3][ 900/1196] lr: 8.0000e-03 eta: 6:03:27 time: 0.5991 data_time: 0.0034 memory: 2664 grad_norm: 0.2085 loss: 0.3256 loss_sem_seg: 0.3256 2023/05/13 00:09:30 - mmengine - INFO - Epoch(train) [3][ 950/1196] lr: 8.0000e-03 eta: 6:03:43 time: 0.6219 data_time: 0.0035 memory: 2861 grad_norm: 0.2210 loss: 0.3442 loss_sem_seg: 0.3442 2023/05/13 00:10:00 - mmengine - INFO - Epoch(train) [3][1000/1196] lr: 8.0000e-03 eta: 6:03:37 time: 0.5856 data_time: 0.0033 memory: 2649 grad_norm: inf loss: 0.3440 loss_sem_seg: 0.3440 2023/05/13 00:10:27 - mmengine - INFO - Epoch(train) [3][1050/1196] lr: 8.0000e-03 eta: 6:03:13 time: 0.5560 data_time: 0.0032 memory: 2763 grad_norm: 0.2320 loss: 0.3379 loss_sem_seg: 0.3379 2023/05/13 00:10:56 - mmengine - INFO - Epoch(train) [3][1100/1196] lr: 8.0000e-03 eta: 6:02:54 time: 0.5665 data_time: 0.0031 memory: 2822 grad_norm: 0.1970 loss: 0.3186 loss_sem_seg: 0.3186 2023/05/13 00:11:24 - mmengine - INFO - Epoch(train) [3][1150/1196] lr: 8.0000e-03 eta: 6:02:39 time: 0.5722 data_time: 0.0033 memory: 2715 grad_norm: 0.2000 loss: 0.3151 loss_sem_seg: 0.3151 2023/05/13 00:11:50 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:11:50 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/05/13 00:12:14 - mmengine - INFO - Epoch(val) [3][ 50/509] eta: 0:02:47 time: 0.3643 data_time: 0.0021 memory: 2818 2023/05/13 00:12:28 - mmengine - INFO - Epoch(val) [3][100/509] eta: 0:02:12 time: 0.2840 data_time: 0.0021 memory: 920 2023/05/13 00:12:44 - mmengine - INFO - Epoch(val) [3][150/509] eta: 0:01:54 time: 0.3080 data_time: 0.0021 memory: 918 2023/05/13 00:13:00 - mmengine - INFO - Epoch(val) [3][200/509] eta: 0:01:38 time: 0.3223 data_time: 0.0021 memory: 906 2023/05/13 00:13:18 - mmengine - INFO - Epoch(val) [3][250/509] eta: 0:01:24 time: 0.3548 data_time: 0.0021 memory: 931 2023/05/13 00:13:31 - mmengine - INFO - Epoch(val) [3][300/509] eta: 0:01:06 time: 0.2693 data_time: 0.0021 memory: 868 2023/05/13 00:13:46 - mmengine - INFO - Epoch(val) [3][350/509] eta: 0:00:50 time: 0.3010 data_time: 0.0021 memory: 893 2023/05/13 00:14:02 - mmengine - INFO - Epoch(val) [3][400/509] eta: 0:00:34 time: 0.3105 data_time: 0.0020 memory: 901 2023/05/13 00:14:16 - mmengine - INFO - Epoch(val) [3][450/509] eta: 0:00:18 time: 0.2950 data_time: 0.0021 memory: 915 2023/05/13 00:14:30 - mmengine - INFO - Epoch(val) [3][500/509] eta: 0:00:02 time: 0.2809 data_time: 0.0021 memory: 898 2023/05/13 00:14:51 - 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 | 0.9414 | 0.0751 | 0.4430 | 0.3570 | 0.2522 | 0.3767 | 0.0062 | 0.0089 | 0.9176 | 0.3969 | 0.7944 | 0.0040 | 0.8863 | 0.5579 | 0.8824 | 0.6572 | 0.7519 | 0.6269 | 0.4783 | 0.4955 | 0.9109 | 0.5952 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 00:14:51 - mmengine - INFO - Epoch(val) [3][509/509] car: 0.9414 bicycle: 0.0751 motorcycle: 0.4430 truck: 0.3570 bus: 0.2522 person: 0.3767 bicyclist: 0.0062 motorcyclist: 0.0089 road: 0.9176 parking: 0.3969 sidewalk: 0.7944 other-ground: 0.0040 building: 0.8863 fence: 0.5579 vegetation: 0.8824 trunck: 0.6572 terrian: 0.7519 pole: 0.6269 traffic-sign: 0.4783 miou: 0.4955 acc: 0.9109 acc_cls: 0.5952 data_time: 0.0021 time: 0.2920 2023/05/13 00:15:19 - mmengine - INFO - Epoch(train) [4][ 50/1196] lr: 8.0000e-03 eta: 6:01:59 time: 0.5678 data_time: 0.0043 memory: 2889 grad_norm: 0.2121 loss: 0.3350 loss_sem_seg: 0.3350 2023/05/13 00:15:48 - mmengine - INFO - Epoch(train) [4][ 100/1196] lr: 8.0000e-03 eta: 6:01:42 time: 0.5723 data_time: 0.0033 memory: 2920 grad_norm: 0.2049 loss: 0.3209 loss_sem_seg: 0.3209 2023/05/13 00:16:15 - mmengine - INFO - Epoch(train) [4][ 150/1196] lr: 8.0000e-03 eta: 6:01:18 time: 0.5564 data_time: 0.0032 memory: 2859 grad_norm: 0.2173 loss: 0.3308 loss_sem_seg: 0.3308 2023/05/13 00:16:44 - mmengine - INFO - Epoch(train) [4][ 200/1196] lr: 8.0000e-03 eta: 6:00:57 time: 0.5652 data_time: 0.0033 memory: 2926 grad_norm: 0.2046 loss: 0.3270 loss_sem_seg: 0.3270 2023/05/13 00:17:12 - mmengine - INFO - Epoch(train) [4][ 250/1196] lr: 8.0000e-03 eta: 6:00:35 time: 0.5618 data_time: 0.0032 memory: 2880 grad_norm: 0.1984 loss: 0.3194 loss_sem_seg: 0.3194 2023/05/13 00:17:43 - mmengine - INFO - Epoch(train) [4][ 300/1196] lr: 8.0000e-03 eta: 6:00:40 time: 0.6165 data_time: 0.0032 memory: 2732 grad_norm: 0.2203 loss: 0.3380 loss_sem_seg: 0.3380 2023/05/13 00:18:12 - mmengine - INFO - Epoch(train) [4][ 350/1196] lr: 8.0000e-03 eta: 6:00:32 time: 0.5923 data_time: 0.0033 memory: 2645 grad_norm: 0.2291 loss: 0.3213 loss_sem_seg: 0.3213 2023/05/13 00:18:40 - mmengine - INFO - Epoch(train) [4][ 400/1196] lr: 8.0000e-03 eta: 6:00:10 time: 0.5638 data_time: 0.0036 memory: 2912 grad_norm: 0.2040 loss: 0.3169 loss_sem_seg: 0.3169 2023/05/13 00:18:47 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:19:09 - mmengine - INFO - Epoch(train) [4][ 450/1196] lr: 8.0000e-03 eta: 5:59:50 time: 0.5687 data_time: 0.0034 memory: 2867 grad_norm: 0.2029 loss: 0.3252 loss_sem_seg: 0.3252 2023/05/13 00:19:36 - mmengine - INFO - Epoch(train) [4][ 500/1196] lr: 8.0000e-03 eta: 5:59:19 time: 0.5463 data_time: 0.0033 memory: 3038 grad_norm: 0.1911 loss: 0.3098 loss_sem_seg: 0.3098 2023/05/13 00:20:04 - mmengine - INFO - Epoch(train) [4][ 550/1196] lr: 8.0000e-03 eta: 5:58:48 time: 0.5464 data_time: 0.0033 memory: 2855 grad_norm: 0.1899 loss: 0.3005 loss_sem_seg: 0.3005 2023/05/13 00:20:32 - mmengine - INFO - Epoch(train) [4][ 600/1196] lr: 8.0000e-03 eta: 5:58:24 time: 0.5626 data_time: 0.0032 memory: 2921 grad_norm: 0.1874 loss: 0.3196 loss_sem_seg: 0.3196 2023/05/13 00:21:02 - mmengine - INFO - Epoch(train) [4][ 650/1196] lr: 8.0000e-03 eta: 5:58:18 time: 0.5997 data_time: 0.0033 memory: 2867 grad_norm: 0.2032 loss: 0.3079 loss_sem_seg: 0.3079 2023/05/13 00:21:31 - mmengine - INFO - Epoch(train) [4][ 700/1196] lr: 8.0000e-03 eta: 5:58:06 time: 0.5877 data_time: 0.0033 memory: 2838 grad_norm: 0.1764 loss: 0.3047 loss_sem_seg: 0.3047 2023/05/13 00:22:01 - mmengine - INFO - Epoch(train) [4][ 750/1196] lr: 8.0000e-03 eta: 5:57:59 time: 0.6017 data_time: 0.0033 memory: 3101 grad_norm: 0.1800 loss: 0.3014 loss_sem_seg: 0.3014 2023/05/13 00:22:31 - mmengine - INFO - Epoch(train) [4][ 800/1196] lr: 8.0000e-03 eta: 5:57:52 time: 0.6023 data_time: 0.0033 memory: 3127 grad_norm: 0.1982 loss: 0.3278 loss_sem_seg: 0.3278 2023/05/13 00:23:02 - mmengine - INFO - Epoch(train) [4][ 850/1196] lr: 8.0000e-03 eta: 5:57:49 time: 0.6109 data_time: 0.0032 memory: 3303 grad_norm: 0.1903 loss: 0.3302 loss_sem_seg: 0.3302 2023/05/13 00:23:31 - mmengine - INFO - Epoch(train) [4][ 900/1196] lr: 8.0000e-03 eta: 5:57:31 time: 0.5791 data_time: 0.0032 memory: 2839 grad_norm: 0.1923 loss: 0.3147 loss_sem_seg: 0.3147 2023/05/13 00:23:58 - mmengine - INFO - Epoch(train) [4][ 950/1196] lr: 8.0000e-03 eta: 5:56:58 time: 0.5453 data_time: 0.0033 memory: 3023 grad_norm: 0.2115 loss: 0.3043 loss_sem_seg: 0.3043 2023/05/13 00:24:26 - mmengine - INFO - Epoch(train) [4][1000/1196] lr: 8.0000e-03 eta: 5:56:31 time: 0.5570 data_time: 0.0032 memory: 2936 grad_norm: 0.1752 loss: 0.3218 loss_sem_seg: 0.3218 2023/05/13 00:24:52 - mmengine - INFO - Epoch(train) [4][1050/1196] lr: 8.0000e-03 eta: 5:55:51 time: 0.5267 data_time: 0.0033 memory: 2832 grad_norm: 0.1764 loss: 0.3191 loss_sem_seg: 0.3191 2023/05/13 00:25:20 - mmengine - INFO - Epoch(train) [4][1100/1196] lr: 8.0000e-03 eta: 5:55:26 time: 0.5616 data_time: 0.0031 memory: 2854 grad_norm: 0.1649 loss: 0.3009 loss_sem_seg: 0.3009 2023/05/13 00:25:48 - mmengine - INFO - Epoch(train) [4][1150/1196] lr: 8.0000e-03 eta: 5:54:53 time: 0.5450 data_time: 0.0032 memory: 2858 grad_norm: 0.1637 loss: 0.3072 loss_sem_seg: 0.3072 2023/05/13 00:26:13 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:26:13 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/05/13 00:26:35 - mmengine - INFO - Epoch(val) [4][ 50/509] eta: 0:02:30 time: 0.3289 data_time: 0.0021 memory: 2788 2023/05/13 00:26:50 - mmengine - INFO - Epoch(val) [4][100/509] eta: 0:02:07 time: 0.2947 data_time: 0.0021 memory: 920 2023/05/13 00:27:05 - mmengine - INFO - Epoch(val) [4][150/509] eta: 0:01:50 time: 0.2961 data_time: 0.0020 memory: 918 2023/05/13 00:27:20 - mmengine - INFO - Epoch(val) [4][200/509] eta: 0:01:34 time: 0.2997 data_time: 0.0021 memory: 906 2023/05/13 00:27:37 - mmengine - INFO - Epoch(val) [4][250/509] eta: 0:01:20 time: 0.3335 data_time: 0.0021 memory: 931 2023/05/13 00:27:49 - mmengine - INFO - Epoch(val) [4][300/509] eta: 0:01:02 time: 0.2491 data_time: 0.0021 memory: 868 2023/05/13 00:28:03 - mmengine - INFO - Epoch(val) [4][350/509] eta: 0:00:47 time: 0.2750 data_time: 0.0020 memory: 893 2023/05/13 00:28:19 - mmengine - INFO - Epoch(val) [4][400/509] eta: 0:00:32 time: 0.3171 data_time: 0.0021 memory: 901 2023/05/13 00:28:34 - mmengine - INFO - Epoch(val) [4][450/509] eta: 0:00:17 time: 0.2995 data_time: 0.0021 memory: 915 2023/05/13 00:28:47 - mmengine - INFO - Epoch(val) [4][500/509] eta: 0:00:02 time: 0.2599 data_time: 0.0020 memory: 898 2023/05/13 00:29:07 - 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 | 0.9269 | 0.3244 | 0.4985 | 0.4912 | 0.1502 | 0.4659 | 0.6571 | 0.0215 | 0.9289 | 0.4480 | 0.8021 | 0.0037 | 0.8941 | 0.5916 | 0.8862 | 0.6584 | 0.7580 | 0.6232 | 0.3010 | 0.5490 | 0.9151 | 0.6275 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 00:29:07 - mmengine - INFO - Epoch(val) [4][509/509] car: 0.9269 bicycle: 0.3244 motorcycle: 0.4985 truck: 0.4912 bus: 0.1502 person: 0.4659 bicyclist: 0.6571 motorcyclist: 0.0215 road: 0.9289 parking: 0.4480 sidewalk: 0.8021 other-ground: 0.0037 building: 0.8941 fence: 0.5916 vegetation: 0.8862 trunck: 0.6584 terrian: 0.7580 pole: 0.6232 traffic-sign: 0.3010 miou: 0.5490 acc: 0.9151 acc_cls: 0.6275 data_time: 0.0020 time: 0.2776 2023/05/13 00:29:34 - mmengine - INFO - Epoch(train) [5][ 50/1196] lr: 8.0000e-03 eta: 5:53:51 time: 0.5376 data_time: 0.0042 memory: 3048 grad_norm: 0.1529 loss: 0.3023 loss_sem_seg: 0.3023 2023/05/13 00:30:01 - mmengine - INFO - Epoch(train) [5][ 100/1196] lr: 8.0000e-03 eta: 5:53:22 time: 0.5508 data_time: 0.0032 memory: 2950 grad_norm: 0.2049 loss: 0.3240 loss_sem_seg: 0.3240 2023/05/13 00:30:28 - mmengine - INFO - Epoch(train) [5][ 150/1196] lr: 8.0000e-03 eta: 5:52:42 time: 0.5257 data_time: 0.0033 memory: 2843 grad_norm: 0.1801 loss: 0.2905 loss_sem_seg: 0.2905 2023/05/13 00:30:54 - mmengine - INFO - Epoch(train) [5][ 200/1196] lr: 8.0000e-03 eta: 5:52:04 time: 0.5282 data_time: 0.0032 memory: 2829 grad_norm: 0.1763 loss: 0.3007 loss_sem_seg: 0.3007 2023/05/13 00:31:04 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:31:25 - mmengine - INFO - Epoch(train) [5][ 250/1196] lr: 8.0000e-03 eta: 5:52:00 time: 0.6170 data_time: 0.0032 memory: 2642 grad_norm: 0.1718 loss: 0.2953 loss_sem_seg: 0.2953 2023/05/13 00:31:55 - mmengine - INFO - Epoch(train) [5][ 300/1196] lr: 8.0000e-03 eta: 5:51:52 time: 0.6088 data_time: 0.0032 memory: 2766 grad_norm: 0.1721 loss: 0.2899 loss_sem_seg: 0.2899 2023/05/13 00:32:25 - mmengine - INFO - Epoch(train) [5][ 350/1196] lr: 8.0000e-03 eta: 5:51:39 time: 0.5966 data_time: 0.0033 memory: 2947 grad_norm: 0.2223 loss: 0.3085 loss_sem_seg: 0.3085 2023/05/13 00:32:55 - mmengine - INFO - Epoch(train) [5][ 400/1196] lr: 8.0000e-03 eta: 5:51:30 time: 0.6081 data_time: 0.0034 memory: 2965 grad_norm: 0.1648 loss: 0.3098 loss_sem_seg: 0.3098 2023/05/13 00:33:25 - mmengine - INFO - Epoch(train) [5][ 450/1196] lr: 8.0000e-03 eta: 5:51:16 time: 0.5944 data_time: 0.0033 memory: 2918 grad_norm: 0.1665 loss: 0.3079 loss_sem_seg: 0.3079 2023/05/13 00:33:56 - mmengine - INFO - Epoch(train) [5][ 500/1196] lr: 8.0000e-03 eta: 5:51:06 time: 0.6068 data_time: 0.0032 memory: 2669 grad_norm: 0.1681 loss: 0.3063 loss_sem_seg: 0.3063 2023/05/13 00:34:26 - mmengine - INFO - Epoch(train) [5][ 550/1196] lr: 8.0000e-03 eta: 5:50:54 time: 0.6016 data_time: 0.0034 memory: 2879 grad_norm: 0.1928 loss: 0.2953 loss_sem_seg: 0.2953 2023/05/13 00:34:56 - mmengine - INFO - Epoch(train) [5][ 600/1196] lr: 8.0000e-03 eta: 5:50:44 time: 0.6113 data_time: 0.0034 memory: 2877 grad_norm: 0.1607 loss: 0.2939 loss_sem_seg: 0.2939 2023/05/13 00:35:26 - mmengine - INFO - Epoch(train) [5][ 650/1196] lr: 8.0000e-03 eta: 5:50:32 time: 0.6038 data_time: 0.0032 memory: 2693 grad_norm: 0.1718 loss: 0.2964 loss_sem_seg: 0.2964 2023/05/13 00:35:56 - mmengine - INFO - Epoch(train) [5][ 700/1196] lr: 8.0000e-03 eta: 5:50:16 time: 0.5940 data_time: 0.0033 memory: 2884 grad_norm: 0.1632 loss: 0.2877 loss_sem_seg: 0.2877 2023/05/13 00:36:27 - mmengine - INFO - Epoch(train) [5][ 750/1196] lr: 8.0000e-03 eta: 5:50:06 time: 0.6127 data_time: 0.0033 memory: 2846 grad_norm: 0.1753 loss: 0.2957 loss_sem_seg: 0.2957 2023/05/13 00:36:57 - mmengine - INFO - Epoch(train) [5][ 800/1196] lr: 8.0000e-03 eta: 5:49:53 time: 0.6029 data_time: 0.0035 memory: 2730 grad_norm: 0.1741 loss: 0.2972 loss_sem_seg: 0.2972 2023/05/13 00:37:27 - mmengine - INFO - Epoch(train) [5][ 850/1196] lr: 8.0000e-03 eta: 5:49:36 time: 0.5955 data_time: 0.0035 memory: 2801 grad_norm: 0.1662 loss: 0.3069 loss_sem_seg: 0.3069 2023/05/13 00:37:57 - mmengine - INFO - Epoch(train) [5][ 900/1196] lr: 8.0000e-03 eta: 5:49:26 time: 0.6146 data_time: 0.0033 memory: 2815 grad_norm: 0.1497 loss: 0.2969 loss_sem_seg: 0.2969 2023/05/13 00:38:28 - mmengine - INFO - Epoch(train) [5][ 950/1196] lr: 8.0000e-03 eta: 5:49:12 time: 0.6037 data_time: 0.0032 memory: 2685 grad_norm: 0.1859 loss: 0.3166 loss_sem_seg: 0.3166 2023/05/13 00:38:58 - mmengine - INFO - Epoch(train) [5][1000/1196] lr: 8.0000e-03 eta: 5:49:00 time: 0.6129 data_time: 0.0034 memory: 2786 grad_norm: 0.1768 loss: 0.2937 loss_sem_seg: 0.2937 2023/05/13 00:39:29 - mmengine - INFO - Epoch(train) [5][1050/1196] lr: 8.0000e-03 eta: 5:48:51 time: 0.6202 data_time: 0.0033 memory: 2941 grad_norm: 0.1536 loss: 0.2865 loss_sem_seg: 0.2865 2023/05/13 00:39:59 - mmengine - INFO - Epoch(train) [5][1100/1196] lr: 8.0000e-03 eta: 5:48:33 time: 0.5951 data_time: 0.0034 memory: 2742 grad_norm: 0.1644 loss: 0.2873 loss_sem_seg: 0.2873 2023/05/13 00:40:30 - mmengine - INFO - Epoch(train) [5][1150/1196] lr: 8.0000e-03 eta: 5:48:21 time: 0.6130 data_time: 0.0035 memory: 2705 grad_norm: inf loss: 0.2841 loss_sem_seg: 0.2841 2023/05/13 00:40:57 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:40:57 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/05/13 00:41:23 - mmengine - INFO - Epoch(val) [5][ 50/509] eta: 0:03:00 time: 0.3940 data_time: 0.0023 memory: 2906 2023/05/13 00:41:40 - mmengine - INFO - Epoch(val) [5][100/509] eta: 0:02:31 time: 0.3448 data_time: 0.0022 memory: 920 2023/05/13 00:41:55 - mmengine - INFO - Epoch(val) [5][150/509] eta: 0:02:03 time: 0.2974 data_time: 0.0021 memory: 918 2023/05/13 00:42:12 - mmengine - INFO - Epoch(val) [5][200/509] eta: 0:01:45 time: 0.3275 data_time: 0.0021 memory: 906 2023/05/13 00:42:30 - mmengine - INFO - Epoch(val) [5][250/509] eta: 0:01:29 time: 0.3585 data_time: 0.0021 memory: 931 2023/05/13 00:42:44 - mmengine - INFO - Epoch(val) [5][300/509] eta: 0:01:10 time: 0.2880 data_time: 0.0022 memory: 868 2023/05/13 00:43:01 - mmengine - INFO - Epoch(val) [5][350/509] eta: 0:00:53 time: 0.3325 data_time: 0.0021 memory: 893 2023/05/13 00:43:17 - mmengine - INFO - Epoch(val) [5][400/509] eta: 0:00:36 time: 0.3357 data_time: 0.0022 memory: 901 2023/05/13 00:43:34 - mmengine - INFO - Epoch(val) [5][450/509] eta: 0:00:19 time: 0.3260 data_time: 0.0022 memory: 915 2023/05/13 00:43:50 - mmengine - INFO - Epoch(val) [5][500/509] eta: 0:00:02 time: 0.3264 data_time: 0.0021 memory: 898 2023/05/13 00:44:11 - 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 | 0.9444 | 0.1366 | 0.3753 | 0.5197 | 0.2691 | 0.4565 | 0.6928 | 0.0318 | 0.9304 | 0.3740 | 0.8088 | 0.0107 | 0.8972 | 0.5676 | 0.8848 | 0.5639 | 0.7825 | 0.6399 | 0.4569 | 0.5444 | 0.9170 | 0.6185 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 00:44:11 - mmengine - INFO - Epoch(val) [5][509/509] car: 0.9444 bicycle: 0.1366 motorcycle: 0.3753 truck: 0.5197 bus: 0.2691 person: 0.4565 bicyclist: 0.6928 motorcyclist: 0.0318 road: 0.9304 parking: 0.3740 sidewalk: 0.8088 other-ground: 0.0107 building: 0.8972 fence: 0.5676 vegetation: 0.8848 trunck: 0.5639 terrian: 0.7825 pole: 0.6399 traffic-sign: 0.4569 miou: 0.5444 acc: 0.9170 acc_cls: 0.6185 data_time: 0.0021 time: 0.3425 2023/05/13 00:44:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:44:42 - mmengine - INFO - Epoch(train) [6][ 50/1196] lr: 8.0000e-03 eta: 5:47:56 time: 0.6248 data_time: 0.0042 memory: 2821 grad_norm: 0.1644 loss: 0.3006 loss_sem_seg: 0.3006 2023/05/13 00:45:12 - mmengine - INFO - Epoch(train) [6][ 100/1196] lr: 8.0000e-03 eta: 5:47:40 time: 0.6019 data_time: 0.0034 memory: 2982 grad_norm: 0.1526 loss: 0.2774 loss_sem_seg: 0.2774 2023/05/13 00:45:43 - mmengine - INFO - Epoch(train) [6][ 150/1196] lr: 8.0000e-03 eta: 5:47:28 time: 0.6192 data_time: 0.0036 memory: 2704 grad_norm: 0.1503 loss: 0.2902 loss_sem_seg: 0.2902 2023/05/13 00:46:14 - mmengine - INFO - Epoch(train) [6][ 200/1196] lr: 8.0000e-03 eta: 5:47:13 time: 0.6095 data_time: 0.0034 memory: 2818 grad_norm: 0.1708 loss: 0.2961 loss_sem_seg: 0.2961 2023/05/13 00:46:43 - mmengine - INFO - Epoch(train) [6][ 250/1196] lr: 8.0000e-03 eta: 5:46:53 time: 0.5914 data_time: 0.0035 memory: 2759 grad_norm: 0.1560 loss: 0.2892 loss_sem_seg: 0.2892 2023/05/13 00:47:12 - mmengine - INFO - Epoch(train) [6][ 300/1196] lr: 8.0000e-03 eta: 5:46:31 time: 0.5858 data_time: 0.0033 memory: 2799 grad_norm: 0.1366 loss: 0.2721 loss_sem_seg: 0.2721 2023/05/13 00:47:43 - mmengine - INFO - Epoch(train) [6][ 350/1196] lr: 8.0000e-03 eta: 5:46:17 time: 0.6148 data_time: 0.0035 memory: 2790 grad_norm: 0.1441 loss: 0.2662 loss_sem_seg: 0.2662 2023/05/13 00:48:14 - mmengine - INFO - Epoch(train) [6][ 400/1196] lr: 8.0000e-03 eta: 5:46:01 time: 0.6110 data_time: 0.0034 memory: 2851 grad_norm: 0.1351 loss: 0.2907 loss_sem_seg: 0.2907 2023/05/13 00:48:44 - mmengine - INFO - Epoch(train) [6][ 450/1196] lr: 8.0000e-03 eta: 5:45:46 time: 0.6122 data_time: 0.0036 memory: 2572 grad_norm: 0.1568 loss: 0.3151 loss_sem_seg: 0.3151 2023/05/13 00:49:15 - mmengine - INFO - Epoch(train) [6][ 500/1196] lr: 8.0000e-03 eta: 5:45:32 time: 0.6152 data_time: 0.0037 memory: 2724 grad_norm: 0.1700 loss: 0.2899 loss_sem_seg: 0.2899 2023/05/13 00:49:46 - mmengine - INFO - Epoch(train) [6][ 550/1196] lr: 8.0000e-03 eta: 5:45:16 time: 0.6131 data_time: 0.0034 memory: 2729 grad_norm: 0.1521 loss: 0.3129 loss_sem_seg: 0.3129 2023/05/13 00:50:16 - mmengine - INFO - Epoch(train) [6][ 600/1196] lr: 8.0000e-03 eta: 5:44:59 time: 0.6061 data_time: 0.0034 memory: 2842 grad_norm: 0.1462 loss: 0.2806 loss_sem_seg: 0.2806 2023/05/13 00:50:45 - mmengine - INFO - Epoch(train) [6][ 650/1196] lr: 8.0000e-03 eta: 5:44:33 time: 0.5760 data_time: 0.0032 memory: 2741 grad_norm: 0.1648 loss: 0.2878 loss_sem_seg: 0.2878 2023/05/13 00:51:14 - mmengine - INFO - Epoch(train) [6][ 700/1196] lr: 8.0000e-03 eta: 5:44:10 time: 0.5885 data_time: 0.0032 memory: 2778 grad_norm: 0.1586 loss: 0.2980 loss_sem_seg: 0.2980 2023/05/13 00:51:43 - mmengine - INFO - Epoch(train) [6][ 750/1196] lr: 8.0000e-03 eta: 5:43:45 time: 0.5800 data_time: 0.0033 memory: 2729 grad_norm: 0.1356 loss: 0.2747 loss_sem_seg: 0.2747 2023/05/13 00:52:12 - mmengine - INFO - Epoch(train) [6][ 800/1196] lr: 8.0000e-03 eta: 5:43:17 time: 0.5708 data_time: 0.0032 memory: 2798 grad_norm: 0.1584 loss: 0.2665 loss_sem_seg: 0.2665 2023/05/13 00:52:39 - mmengine - INFO - Epoch(train) [6][ 850/1196] lr: 8.0000e-03 eta: 5:42:45 time: 0.5518 data_time: 0.0033 memory: 2675 grad_norm: 0.1545 loss: 0.3030 loss_sem_seg: 0.3030 2023/05/13 00:53:08 - mmengine - INFO - Epoch(train) [6][ 900/1196] lr: 8.0000e-03 eta: 5:42:16 time: 0.5646 data_time: 0.0038 memory: 2788 grad_norm: 0.1578 loss: 0.2774 loss_sem_seg: 0.2774 2023/05/13 00:53:35 - mmengine - INFO - Epoch(train) [6][ 950/1196] lr: 8.0000e-03 eta: 5:41:44 time: 0.5561 data_time: 0.0035 memory: 2767 grad_norm: 0.1525 loss: 0.2817 loss_sem_seg: 0.2817 2023/05/13 00:54:04 - mmengine - INFO - Epoch(train) [6][1000/1196] lr: 8.0000e-03 eta: 5:41:17 time: 0.5727 data_time: 0.0032 memory: 2990 grad_norm: 0.1522 loss: 0.2716 loss_sem_seg: 0.2716 2023/05/13 00:54:15 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:54:33 - mmengine - INFO - Epoch(train) [6][1050/1196] lr: 8.0000e-03 eta: 5:40:49 time: 0.5693 data_time: 0.0033 memory: 3006 grad_norm: 0.1306 loss: 0.2787 loss_sem_seg: 0.2787 2023/05/13 00:55:01 - mmengine - INFO - Epoch(train) [6][1100/1196] lr: 8.0000e-03 eta: 5:40:21 time: 0.5695 data_time: 0.0033 memory: 2752 grad_norm: 0.1481 loss: 0.2678 loss_sem_seg: 0.2678 2023/05/13 00:55:29 - mmengine - INFO - Epoch(train) [6][1150/1196] lr: 8.0000e-03 eta: 5:39:52 time: 0.5659 data_time: 0.0033 memory: 2759 grad_norm: 0.1432 loss: 0.2846 loss_sem_seg: 0.2846 2023/05/13 00:55:55 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 00:55:55 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/05/13 00:56:17 - mmengine - INFO - Epoch(val) [6][ 50/509] eta: 0:02:29 time: 0.3268 data_time: 0.0021 memory: 2801 2023/05/13 00:56:32 - mmengine - INFO - Epoch(val) [6][100/509] eta: 0:02:06 time: 0.2934 data_time: 0.0021 memory: 920 2023/05/13 00:56:45 - mmengine - INFO - Epoch(val) [6][150/509] eta: 0:01:46 time: 0.2666 data_time: 0.0020 memory: 918 2023/05/13 00:56:59 - mmengine - INFO - Epoch(val) [6][200/509] eta: 0:01:30 time: 0.2823 data_time: 0.0021 memory: 906 2023/05/13 00:57:14 - mmengine - INFO - Epoch(val) [6][250/509] eta: 0:01:15 time: 0.2893 data_time: 0.0021 memory: 931 2023/05/13 00:57:25 - mmengine - INFO - Epoch(val) [6][300/509] eta: 0:00:58 time: 0.2257 data_time: 0.0021 memory: 868 2023/05/13 00:57:38 - mmengine - INFO - Epoch(val) [6][350/509] eta: 0:00:44 time: 0.2649 data_time: 0.0021 memory: 893 2023/05/13 00:57:53 - mmengine - INFO - Epoch(val) [6][400/509] eta: 0:00:30 time: 0.2869 data_time: 0.0020 memory: 901 2023/05/13 00:58:06 - mmengine - INFO - Epoch(val) [6][450/509] eta: 0:00:16 time: 0.2622 data_time: 0.0021 memory: 915 2023/05/13 00:58:19 - mmengine - INFO - Epoch(val) [6][500/509] eta: 0:00:02 time: 0.2667 data_time: 0.0021 memory: 898 2023/05/13 00:58:40 - 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 | 0.9086 | 0.2938 | 0.5425 | 0.2976 | 0.0896 | 0.5987 | 0.6011 | 0.0365 | 0.9248 | 0.4545 | 0.8015 | 0.0330 | 0.8715 | 0.4905 | 0.8864 | 0.6227 | 0.7574 | 0.6335 | 0.3555 | 0.5368 | 0.9113 | 0.6162 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 00:58:40 - mmengine - INFO - Epoch(val) [6][509/509] car: 0.9086 bicycle: 0.2938 motorcycle: 0.5425 truck: 0.2976 bus: 0.0896 person: 0.5987 bicyclist: 0.6011 motorcyclist: 0.0365 road: 0.9248 parking: 0.4545 sidewalk: 0.8015 other-ground: 0.0330 building: 0.8715 fence: 0.4905 vegetation: 0.8864 trunck: 0.6227 terrian: 0.7574 pole: 0.6335 traffic-sign: 0.3555 miou: 0.5368 acc: 0.9113 acc_cls: 0.6162 data_time: 0.0021 time: 0.2825 2023/05/13 00:59:11 - mmengine - INFO - Epoch(train) [7][ 50/1196] lr: 8.0000e-03 eta: 5:39:08 time: 0.6205 data_time: 0.0043 memory: 2659 grad_norm: 0.1501 loss: 0.2802 loss_sem_seg: 0.2802 2023/05/13 00:59:42 - mmengine - INFO - Epoch(train) [7][ 100/1196] lr: 8.0000e-03 eta: 5:38:51 time: 0.6153 data_time: 0.0032 memory: 3030 grad_norm: 0.1458 loss: 0.2564 loss_sem_seg: 0.2564 2023/05/13 01:00:12 - mmengine - INFO - Epoch(train) [7][ 150/1196] lr: 8.0000e-03 eta: 5:38:34 time: 0.6151 data_time: 0.0034 memory: 2807 grad_norm: 0.1472 loss: 0.2715 loss_sem_seg: 0.2715 2023/05/13 01:00:43 - mmengine - INFO - Epoch(train) [7][ 200/1196] lr: 8.0000e-03 eta: 5:38:17 time: 0.6126 data_time: 0.0033 memory: 2853 grad_norm: 0.1419 loss: 0.2488 loss_sem_seg: 0.2488 2023/05/13 01:01:11 - mmengine - INFO - Epoch(train) [7][ 250/1196] lr: 8.0000e-03 eta: 5:37:46 time: 0.5616 data_time: 0.0035 memory: 2775 grad_norm: 0.1368 loss: 0.2766 loss_sem_seg: 0.2766 2023/05/13 01:01:38 - mmengine - INFO - Epoch(train) [7][ 300/1196] lr: 8.0000e-03 eta: 5:37:09 time: 0.5308 data_time: 0.0034 memory: 2780 grad_norm: 0.1507 loss: 0.2974 loss_sem_seg: 0.2974 2023/05/13 01:02:04 - mmengine - INFO - Epoch(train) [7][ 350/1196] lr: 8.0000e-03 eta: 5:36:32 time: 0.5323 data_time: 0.0032 memory: 2861 grad_norm: 0.1503 loss: 0.2724 loss_sem_seg: 0.2724 2023/05/13 01:02:31 - mmengine - INFO - Epoch(train) [7][ 400/1196] lr: 8.0000e-03 eta: 5:35:54 time: 0.5284 data_time: 0.0033 memory: 2780 grad_norm: 0.1375 loss: 0.2530 loss_sem_seg: 0.2530 2023/05/13 01:02:57 - mmengine - INFO - Epoch(train) [7][ 450/1196] lr: 8.0000e-03 eta: 5:35:17 time: 0.5301 data_time: 0.0033 memory: 2718 grad_norm: 0.1338 loss: 0.2580 loss_sem_seg: 0.2580 2023/05/13 01:03:24 - mmengine - INFO - Epoch(train) [7][ 500/1196] lr: 8.0000e-03 eta: 5:34:42 time: 0.5393 data_time: 0.0035 memory: 2948 grad_norm: 0.1390 loss: 0.2715 loss_sem_seg: 0.2715 2023/05/13 01:03:51 - mmengine - INFO - Epoch(train) [7][ 550/1196] lr: 8.0000e-03 eta: 5:34:05 time: 0.5310 data_time: 0.0032 memory: 2929 grad_norm: 0.1281 loss: 0.2782 loss_sem_seg: 0.2782 2023/05/13 01:04:17 - mmengine - INFO - Epoch(train) [7][ 600/1196] lr: 8.0000e-03 eta: 5:33:28 time: 0.5300 data_time: 0.0031 memory: 2930 grad_norm: 0.1551 loss: 0.2648 loss_sem_seg: 0.2648 2023/05/13 01:04:44 - mmengine - INFO - Epoch(train) [7][ 650/1196] lr: 8.0000e-03 eta: 5:32:52 time: 0.5307 data_time: 0.0033 memory: 2919 grad_norm: 0.1446 loss: 0.2582 loss_sem_seg: 0.2582 2023/05/13 01:05:11 - mmengine - INFO - Epoch(train) [7][ 700/1196] lr: 8.0000e-03 eta: 5:32:18 time: 0.5415 data_time: 0.0033 memory: 2961 grad_norm: 0.1294 loss: 0.2642 loss_sem_seg: 0.2642 2023/05/13 01:05:37 - mmengine - INFO - Epoch(train) [7][ 750/1196] lr: 8.0000e-03 eta: 5:31:42 time: 0.5318 data_time: 0.0033 memory: 2851 grad_norm: 0.1495 loss: 0.2739 loss_sem_seg: 0.2739 2023/05/13 01:06:04 - mmengine - INFO - Epoch(train) [7][ 800/1196] lr: 8.0000e-03 eta: 5:31:05 time: 0.5268 data_time: 0.0032 memory: 2931 grad_norm: 0.1469 loss: 0.2484 loss_sem_seg: 0.2484 2023/05/13 01:06:16 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:06:30 - mmengine - INFO - Epoch(train) [7][ 850/1196] lr: 8.0000e-03 eta: 5:30:26 time: 0.5195 data_time: 0.0034 memory: 2871 grad_norm: inf loss: 0.2672 loss_sem_seg: 0.2672 2023/05/13 01:06:56 - mmengine - INFO - Epoch(train) [7][ 900/1196] lr: 8.0000e-03 eta: 5:29:51 time: 0.5348 data_time: 0.0033 memory: 2790 grad_norm: 0.1347 loss: 0.2576 loss_sem_seg: 0.2576 2023/05/13 01:07:23 - mmengine - INFO - Epoch(train) [7][ 950/1196] lr: 8.0000e-03 eta: 5:29:14 time: 0.5270 data_time: 0.0032 memory: 2694 grad_norm: 0.1517 loss: 0.2722 loss_sem_seg: 0.2722 2023/05/13 01:07:49 - mmengine - INFO - Epoch(train) [7][1000/1196] lr: 8.0000e-03 eta: 5:28:38 time: 0.5260 data_time: 0.0033 memory: 2784 grad_norm: 0.1333 loss: 0.2615 loss_sem_seg: 0.2615 2023/05/13 01:08:16 - mmengine - INFO - Epoch(train) [7][1050/1196] lr: 8.0000e-03 eta: 5:28:04 time: 0.5374 data_time: 0.0033 memory: 2764 grad_norm: 0.1481 loss: 0.2560 loss_sem_seg: 0.2560 2023/05/13 01:08:43 - mmengine - INFO - Epoch(train) [7][1100/1196] lr: 8.0000e-03 eta: 5:27:29 time: 0.5338 data_time: 0.0033 memory: 2680 grad_norm: 0.1463 loss: 0.2692 loss_sem_seg: 0.2692 2023/05/13 01:09:09 - mmengine - INFO - Epoch(train) [7][1150/1196] lr: 8.0000e-03 eta: 5:26:55 time: 0.5364 data_time: 0.0032 memory: 3013 grad_norm: 0.1366 loss: 0.2606 loss_sem_seg: 0.2606 2023/05/13 01:09:34 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:09:34 - mmengine - INFO - Saving checkpoint at 7 epochs 2023/05/13 01:09:57 - mmengine - INFO - Epoch(val) [7][ 50/509] eta: 0:02:36 time: 0.3414 data_time: 0.0023 memory: 2734 2023/05/13 01:10:13 - mmengine - INFO - Epoch(val) [7][100/509] eta: 0:02:16 time: 0.3246 data_time: 0.0026 memory: 920 2023/05/13 01:10:29 - mmengine - INFO - Epoch(val) [7][150/509] eta: 0:01:57 time: 0.3149 data_time: 0.0025 memory: 918 2023/05/13 01:10:44 - mmengine - INFO - Epoch(val) [7][200/509] eta: 0:01:39 time: 0.3079 data_time: 0.0026 memory: 906 2023/05/13 01:11:03 - mmengine - INFO - Epoch(val) [7][250/509] eta: 0:01:26 time: 0.3748 data_time: 0.0025 memory: 931 2023/05/13 01:11:17 - mmengine - INFO - Epoch(val) [7][300/509] eta: 0:01:07 time: 0.2871 data_time: 0.0026 memory: 868 2023/05/13 01:11:33 - mmengine - INFO - Epoch(val) [7][350/509] eta: 0:00:51 time: 0.3087 data_time: 0.0025 memory: 893 2023/05/13 01:11:50 - mmengine - INFO - Epoch(val) [7][400/509] eta: 0:00:35 time: 0.3497 data_time: 0.0025 memory: 901 2023/05/13 01:12:06 - mmengine - INFO - Epoch(val) [7][450/509] eta: 0:00:19 time: 0.3255 data_time: 0.0027 memory: 915 2023/05/13 01:12:22 - mmengine - INFO - Epoch(val) [7][500/509] eta: 0:00:02 time: 0.3055 data_time: 0.0023 memory: 898 2023/05/13 01:12:43 - 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 | 0.9360 | 0.4029 | 0.5892 | 0.4672 | 0.4650 | 0.6621 | 0.7158 | 0.0860 | 0.9197 | 0.3132 | 0.8060 | 0.0146 | 0.9011 | 0.6069 | 0.8940 | 0.6636 | 0.7706 | 0.6513 | 0.4577 | 0.5959 | 0.9186 | 0.6853 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 01:12:43 - mmengine - INFO - Epoch(val) [7][509/509] car: 0.9360 bicycle: 0.4029 motorcycle: 0.5892 truck: 0.4672 bus: 0.4650 person: 0.6621 bicyclist: 0.7158 motorcyclist: 0.0860 road: 0.9197 parking: 0.3132 sidewalk: 0.8060 other-ground: 0.0146 building: 0.9011 fence: 0.6069 vegetation: 0.8940 trunck: 0.6636 terrian: 0.7706 pole: 0.6513 traffic-sign: 0.4577 miou: 0.5959 acc: 0.9186 acc_cls: 0.6853 data_time: 0.0022 time: 0.3240 2023/05/13 01:13:14 - mmengine - INFO - Epoch(train) [8][ 50/1196] lr: 8.0000e-03 eta: 5:26:05 time: 0.6217 data_time: 0.0041 memory: 2865 grad_norm: 0.1282 loss: 0.2758 loss_sem_seg: 0.2758 2023/05/13 01:13:43 - mmengine - INFO - Epoch(train) [8][ 100/1196] lr: 8.0000e-03 eta: 5:25:39 time: 0.5763 data_time: 0.0034 memory: 2759 grad_norm: 0.1275 loss: 0.2773 loss_sem_seg: 0.2773 2023/05/13 01:14:14 - mmengine - INFO - Epoch(train) [8][ 150/1196] lr: 8.0000e-03 eta: 5:25:20 time: 0.6131 data_time: 0.0033 memory: 2804 grad_norm: 0.1480 loss: 0.2754 loss_sem_seg: 0.2754 2023/05/13 01:14:44 - mmengine - INFO - Epoch(train) [8][ 200/1196] lr: 8.0000e-03 eta: 5:25:00 time: 0.6038 data_time: 0.0033 memory: 3033 grad_norm: 0.1206 loss: 0.2516 loss_sem_seg: 0.2516 2023/05/13 01:15:15 - mmengine - INFO - Epoch(train) [8][ 250/1196] lr: 8.0000e-03 eta: 5:24:42 time: 0.6160 data_time: 0.0033 memory: 2767 grad_norm: 0.1355 loss: 0.2520 loss_sem_seg: 0.2520 2023/05/13 01:15:45 - mmengine - INFO - Epoch(train) [8][ 300/1196] lr: 8.0000e-03 eta: 5:24:23 time: 0.6130 data_time: 0.0032 memory: 2692 grad_norm: 0.1286 loss: 0.2620 loss_sem_seg: 0.2620 2023/05/13 01:16:15 - mmengine - INFO - Epoch(train) [8][ 350/1196] lr: 8.0000e-03 eta: 5:24:00 time: 0.5924 data_time: 0.0033 memory: 2711 grad_norm: 0.1313 loss: 0.2396 loss_sem_seg: 0.2396 2023/05/13 01:16:46 - mmengine - INFO - Epoch(train) [8][ 400/1196] lr: 8.0000e-03 eta: 5:23:40 time: 0.6116 data_time: 0.0032 memory: 2915 grad_norm: 0.1394 loss: 0.2740 loss_sem_seg: 0.2740 2023/05/13 01:17:14 - mmengine - INFO - Epoch(train) [8][ 450/1196] lr: 8.0000e-03 eta: 5:23:13 time: 0.5704 data_time: 0.0033 memory: 2919 grad_norm: 0.1465 loss: 0.2677 loss_sem_seg: 0.2677 2023/05/13 01:17:42 - mmengine - INFO - Epoch(train) [8][ 500/1196] lr: 8.0000e-03 eta: 5:22:41 time: 0.5496 data_time: 0.0034 memory: 2621 grad_norm: 0.1306 loss: 0.2561 loss_sem_seg: 0.2561 2023/05/13 01:18:09 - mmengine - INFO - Epoch(train) [8][ 550/1196] lr: 8.0000e-03 eta: 5:22:09 time: 0.5450 data_time: 0.0033 memory: 2947 grad_norm: 0.1306 loss: 0.2733 loss_sem_seg: 0.2733 2023/05/13 01:18:36 - mmengine - INFO - Epoch(train) [8][ 600/1196] lr: 8.0000e-03 eta: 5:21:34 time: 0.5326 data_time: 0.0035 memory: 2788 grad_norm: 0.1233 loss: 0.2481 loss_sem_seg: 0.2481 2023/05/13 01:18:50 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:19:03 - mmengine - INFO - Epoch(train) [8][ 650/1196] lr: 8.0000e-03 eta: 5:21:01 time: 0.5408 data_time: 0.0032 memory: 2787 grad_norm: 0.1289 loss: 0.2449 loss_sem_seg: 0.2449 2023/05/13 01:19:29 - mmengine - INFO - Epoch(train) [8][ 700/1196] lr: 8.0000e-03 eta: 5:20:26 time: 0.5289 data_time: 0.0032 memory: 2768 grad_norm: 0.1399 loss: 0.2610 loss_sem_seg: 0.2610 2023/05/13 01:19:56 - mmengine - INFO - Epoch(train) [8][ 750/1196] lr: 8.0000e-03 eta: 5:19:51 time: 0.5328 data_time: 0.0035 memory: 3049 grad_norm: 0.1255 loss: 0.2543 loss_sem_seg: 0.2543 2023/05/13 01:20:23 - mmengine - INFO - Epoch(train) [8][ 800/1196] lr: 8.0000e-03 eta: 5:19:19 time: 0.5426 data_time: 0.0033 memory: 2767 grad_norm: 0.1168 loss: 0.2489 loss_sem_seg: 0.2489 2023/05/13 01:20:49 - mmengine - INFO - Epoch(train) [8][ 850/1196] lr: 8.0000e-03 eta: 5:18:45 time: 0.5333 data_time: 0.0032 memory: 2881 grad_norm: 0.1535 loss: 0.2795 loss_sem_seg: 0.2795 2023/05/13 01:21:16 - mmengine - INFO - Epoch(train) [8][ 900/1196] lr: 8.0000e-03 eta: 5:18:09 time: 0.5261 data_time: 0.0034 memory: 2807 grad_norm: 0.1478 loss: 0.2677 loss_sem_seg: 0.2677 2023/05/13 01:21:43 - mmengine - INFO - Epoch(train) [8][ 950/1196] lr: 8.0000e-03 eta: 5:17:36 time: 0.5388 data_time: 0.0033 memory: 2749 grad_norm: 0.1276 loss: 0.2467 loss_sem_seg: 0.2467 2023/05/13 01:22:09 - mmengine - INFO - Epoch(train) [8][1000/1196] lr: 8.0000e-03 eta: 5:17:02 time: 0.5298 data_time: 0.0034 memory: 2845 grad_norm: 0.1254 loss: 0.2463 loss_sem_seg: 0.2463 2023/05/13 01:22:36 - mmengine - INFO - Epoch(train) [8][1050/1196] lr: 8.0000e-03 eta: 5:16:30 time: 0.5435 data_time: 0.0033 memory: 2854 grad_norm: 0.1330 loss: 0.2747 loss_sem_seg: 0.2747 2023/05/13 01:23:03 - mmengine - INFO - Epoch(train) [8][1100/1196] lr: 8.0000e-03 eta: 5:15:56 time: 0.5360 data_time: 0.0033 memory: 2890 grad_norm: 0.1411 loss: 0.2475 loss_sem_seg: 0.2475 2023/05/13 01:23:30 - mmengine - INFO - Epoch(train) [8][1150/1196] lr: 8.0000e-03 eta: 5:15:24 time: 0.5440 data_time: 0.0033 memory: 2839 grad_norm: 0.1157 loss: 0.2457 loss_sem_seg: 0.2457 2023/05/13 01:23:55 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:23:55 - mmengine - INFO - Saving checkpoint at 8 epochs 2023/05/13 01:24:18 - mmengine - INFO - Epoch(val) [8][ 50/509] eta: 0:02:32 time: 0.3316 data_time: 0.0021 memory: 2935 2023/05/13 01:24:33 - mmengine - INFO - Epoch(val) [8][100/509] eta: 0:02:09 time: 0.3022 data_time: 0.0021 memory: 920 2023/05/13 01:24:47 - mmengine - INFO - Epoch(val) [8][150/509] eta: 0:01:50 time: 0.2901 data_time: 0.0021 memory: 918 2023/05/13 01:25:03 - mmengine - INFO - Epoch(val) [8][200/509] eta: 0:01:35 time: 0.3132 data_time: 0.0021 memory: 906 2023/05/13 01:25:20 - mmengine - INFO - Epoch(val) [8][250/509] eta: 0:01:21 time: 0.3406 data_time: 0.0022 memory: 931 2023/05/13 01:25:34 - mmengine - INFO - Epoch(val) [8][300/509] eta: 0:01:04 time: 0.2858 data_time: 0.0021 memory: 868 2023/05/13 01:25:51 - mmengine - INFO - Epoch(val) [8][350/509] eta: 0:00:49 time: 0.3269 data_time: 0.0021 memory: 893 2023/05/13 01:26:07 - mmengine - INFO - Epoch(val) [8][400/509] eta: 0:00:34 time: 0.3349 data_time: 0.0021 memory: 901 2023/05/13 01:26:23 - mmengine - INFO - Epoch(val) [8][450/509] eta: 0:00:18 time: 0.3136 data_time: 0.0021 memory: 915 2023/05/13 01:26:38 - mmengine - INFO - Epoch(val) [8][500/509] eta: 0:00:02 time: 0.2985 data_time: 0.0021 memory: 898 2023/05/13 01:27:00 - 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 | 0.9262 | 0.4015 | 0.4162 | 0.6581 | 0.3252 | 0.6348 | 0.5841 | 0.0133 | 0.9376 | 0.4328 | 0.8149 | 0.0628 | 0.9031 | 0.6161 | 0.8834 | 0.6953 | 0.7569 | 0.6490 | 0.4857 | 0.5893 | 0.9184 | 0.6648 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 01:27:00 - mmengine - INFO - Epoch(val) [8][509/509] car: 0.9262 bicycle: 0.4015 motorcycle: 0.4162 truck: 0.6581 bus: 0.3252 person: 0.6348 bicyclist: 0.5841 motorcyclist: 0.0133 road: 0.9376 parking: 0.4328 sidewalk: 0.8149 other-ground: 0.0628 building: 0.9031 fence: 0.6161 vegetation: 0.8834 trunck: 0.6953 terrian: 0.7569 pole: 0.6490 traffic-sign: 0.4857 miou: 0.5893 acc: 0.9184 acc_cls: 0.6648 data_time: 0.0021 time: 0.3180 2023/05/13 01:27:29 - mmengine - INFO - Epoch(train) [9][ 50/1196] lr: 8.0000e-03 eta: 5:14:31 time: 0.5922 data_time: 0.0042 memory: 2808 grad_norm: 0.1253 loss: 0.2526 loss_sem_seg: 0.2526 2023/05/13 01:28:00 - mmengine - INFO - Epoch(train) [9][ 100/1196] lr: 8.0000e-03 eta: 5:14:11 time: 0.6159 data_time: 0.0034 memory: 2805 grad_norm: 0.1196 loss: 0.2689 loss_sem_seg: 0.2689 2023/05/13 01:28:30 - mmengine - INFO - Epoch(train) [9][ 150/1196] lr: 8.0000e-03 eta: 5:13:49 time: 0.5980 data_time: 0.0036 memory: 2795 grad_norm: 0.1213 loss: 0.2450 loss_sem_seg: 0.2450 2023/05/13 01:29:00 - mmengine - INFO - Epoch(train) [9][ 200/1196] lr: 8.0000e-03 eta: 5:13:26 time: 0.5981 data_time: 0.0036 memory: 2801 grad_norm: 0.1447 loss: 0.2724 loss_sem_seg: 0.2724 2023/05/13 01:29:31 - mmengine - INFO - Epoch(train) [9][ 250/1196] lr: 8.0000e-03 eta: 5:13:08 time: 0.6253 data_time: 0.0034 memory: 2771 grad_norm: 0.1307 loss: 0.2693 loss_sem_seg: 0.2693 2023/05/13 01:30:02 - mmengine - INFO - Epoch(train) [9][ 300/1196] lr: 8.0000e-03 eta: 5:12:47 time: 0.6090 data_time: 0.0034 memory: 3101 grad_norm: 0.1342 loss: 0.2592 loss_sem_seg: 0.2592 2023/05/13 01:30:33 - mmengine - INFO - Epoch(train) [9][ 350/1196] lr: 8.0000e-03 eta: 5:12:28 time: 0.6191 data_time: 0.0034 memory: 2956 grad_norm: 0.1315 loss: 0.2772 loss_sem_seg: 0.2772 2023/05/13 01:31:03 - mmengine - INFO - Epoch(train) [9][ 400/1196] lr: 8.0000e-03 eta: 5:12:06 time: 0.6027 data_time: 0.0035 memory: 3086 grad_norm: 0.1238 loss: 0.2529 loss_sem_seg: 0.2529 2023/05/13 01:31:21 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:31:31 - mmengine - INFO - Epoch(train) [9][ 450/1196] lr: 8.0000e-03 eta: 5:11:39 time: 0.5715 data_time: 0.0033 memory: 2581 grad_norm: 0.1246 loss: 0.2419 loss_sem_seg: 0.2419 2023/05/13 01:32:00 - mmengine - INFO - Epoch(train) [9][ 500/1196] lr: 8.0000e-03 eta: 5:11:10 time: 0.5674 data_time: 0.0033 memory: 2759 grad_norm: 0.1205 loss: 0.2339 loss_sem_seg: 0.2339 2023/05/13 01:32:29 - mmengine - INFO - Epoch(train) [9][ 550/1196] lr: 8.0000e-03 eta: 5:10:44 time: 0.5757 data_time: 0.0035 memory: 2782 grad_norm: 0.1466 loss: 0.2646 loss_sem_seg: 0.2646 2023/05/13 01:32:57 - mmengine - INFO - Epoch(train) [9][ 600/1196] lr: 8.0000e-03 eta: 5:10:16 time: 0.5720 data_time: 0.0034 memory: 3189 grad_norm: 0.1222 loss: 0.2414 loss_sem_seg: 0.2414 2023/05/13 01:33:26 - mmengine - INFO - Epoch(train) [9][ 650/1196] lr: 8.0000e-03 eta: 5:09:48 time: 0.5665 data_time: 0.0036 memory: 2690 grad_norm: 0.1348 loss: 0.2600 loss_sem_seg: 0.2600 2023/05/13 01:33:54 - mmengine - INFO - Epoch(train) [9][ 700/1196] lr: 8.0000e-03 eta: 5:09:19 time: 0.5602 data_time: 0.0035 memory: 2742 grad_norm: 0.1340 loss: 0.2549 loss_sem_seg: 0.2549 2023/05/13 01:34:20 - mmengine - INFO - Epoch(train) [9][ 750/1196] lr: 8.0000e-03 eta: 5:08:45 time: 0.5318 data_time: 0.0034 memory: 2821 grad_norm: 0.1169 loss: 0.2557 loss_sem_seg: 0.2557 2023/05/13 01:34:45 - mmengine - INFO - Epoch(train) [9][ 800/1196] lr: 8.0000e-03 eta: 5:08:07 time: 0.5042 data_time: 0.0036 memory: 2691 grad_norm: 0.1291 loss: 0.2690 loss_sem_seg: 0.2690 2023/05/13 01:35:11 - mmengine - INFO - Epoch(train) [9][ 850/1196] lr: 8.0000e-03 eta: 5:07:31 time: 0.5124 data_time: 0.0036 memory: 2807 grad_norm: 0.1231 loss: 0.2436 loss_sem_seg: 0.2436 2023/05/13 01:35:37 - mmengine - INFO - Epoch(train) [9][ 900/1196] lr: 8.0000e-03 eta: 5:06:54 time: 0.5125 data_time: 0.0033 memory: 2763 grad_norm: 0.1321 loss: 0.2551 loss_sem_seg: 0.2551 2023/05/13 01:36:03 - mmengine - INFO - Epoch(train) [9][ 950/1196] lr: 8.0000e-03 eta: 5:06:19 time: 0.5204 data_time: 0.0034 memory: 2776 grad_norm: 0.1153 loss: 0.2498 loss_sem_seg: 0.2498 2023/05/13 01:36:29 - mmengine - INFO - Epoch(train) [9][1000/1196] lr: 8.0000e-03 eta: 5:05:45 time: 0.5301 data_time: 0.0033 memory: 2704 grad_norm: 0.1201 loss: 0.2562 loss_sem_seg: 0.2562 2023/05/13 01:36:57 - mmengine - INFO - Epoch(train) [9][1050/1196] lr: 8.0000e-03 eta: 5:05:15 time: 0.5537 data_time: 0.0034 memory: 2870 grad_norm: 0.1295 loss: 0.2468 loss_sem_seg: 0.2468 2023/05/13 01:37:26 - mmengine - INFO - Epoch(train) [9][1100/1196] lr: 8.0000e-03 eta: 5:04:49 time: 0.5783 data_time: 0.0033 memory: 2885 grad_norm: 0.1387 loss: 0.2571 loss_sem_seg: 0.2571 2023/05/13 01:37:54 - mmengine - INFO - Epoch(train) [9][1150/1196] lr: 8.0000e-03 eta: 5:04:21 time: 0.5645 data_time: 0.0035 memory: 3129 grad_norm: 0.1236 loss: 0.2330 loss_sem_seg: 0.2330 2023/05/13 01:38:20 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:38:20 - mmengine - INFO - Saving checkpoint at 9 epochs 2023/05/13 01:38:44 - mmengine - INFO - Epoch(val) [9][ 50/509] eta: 0:02:44 time: 0.3580 data_time: 0.0022 memory: 2842 2023/05/13 01:39:01 - mmengine - INFO - Epoch(val) [9][100/509] eta: 0:02:22 time: 0.3382 data_time: 0.0022 memory: 920 2023/05/13 01:39:17 - mmengine - INFO - Epoch(val) [9][150/509] eta: 0:02:01 time: 0.3187 data_time: 0.0021 memory: 918 2023/05/13 01:39:33 - mmengine - INFO - Epoch(val) [9][200/509] eta: 0:01:43 time: 0.3233 data_time: 0.0022 memory: 906 2023/05/13 01:39:51 - mmengine - INFO - Epoch(val) [9][250/509] eta: 0:01:27 time: 0.3536 data_time: 0.0022 memory: 931 2023/05/13 01:40:06 - mmengine - INFO - Epoch(val) [9][300/509] eta: 0:01:09 time: 0.3069 data_time: 0.0021 memory: 868 2023/05/13 01:40:22 - mmengine - INFO - Epoch(val) [9][350/509] eta: 0:00:52 time: 0.3017 data_time: 0.0021 memory: 893 2023/05/13 01:40:39 - mmengine - INFO - Epoch(val) [9][400/509] eta: 0:00:36 time: 0.3525 data_time: 0.0021 memory: 901 2023/05/13 01:40:56 - mmengine - INFO - Epoch(val) [9][450/509] eta: 0:00:19 time: 0.3427 data_time: 0.0021 memory: 915 2023/05/13 01:41:13 - mmengine - INFO - Epoch(val) [9][500/509] eta: 0:00:02 time: 0.3256 data_time: 0.0022 memory: 898 2023/05/13 01:41:34 - 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 | 0.3649 | 0.6456 | 0.3931 | 0.4931 | 0.6883 | 0.6695 | 0.1032 | 0.9288 | 0.4584 | 0.8117 | 0.0400 | 0.9108 | 0.6706 | 0.8927 | 0.6762 | 0.7725 | 0.6420 | 0.5012 | 0.6118 | 0.9228 | 0.7305 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 01:41:34 - mmengine - INFO - Epoch(val) [9][509/509] car: 0.9621 bicycle: 0.3649 motorcycle: 0.6456 truck: 0.3931 bus: 0.4931 person: 0.6883 bicyclist: 0.6695 motorcyclist: 0.1032 road: 0.9288 parking: 0.4584 sidewalk: 0.8117 other-ground: 0.0400 building: 0.9108 fence: 0.6706 vegetation: 0.8927 trunck: 0.6762 terrian: 0.7725 pole: 0.6420 traffic-sign: 0.5012 miou: 0.6118 acc: 0.9228 acc_cls: 0.7305 data_time: 0.0021 time: 0.3447 2023/05/13 01:42:04 - mmengine - INFO - Epoch(train) [10][ 50/1196] lr: 8.0000e-03 eta: 5:03:32 time: 0.6003 data_time: 0.0046 memory: 2902 grad_norm: 0.1249 loss: 0.2604 loss_sem_seg: 0.2604 2023/05/13 01:42:35 - mmengine - INFO - Epoch(train) [10][ 100/1196] lr: 8.0000e-03 eta: 5:03:12 time: 0.6177 data_time: 0.0034 memory: 3016 grad_norm: 0.1254 loss: 0.2429 loss_sem_seg: 0.2429 2023/05/13 01:43:05 - mmengine - INFO - Epoch(train) [10][ 150/1196] lr: 8.0000e-03 eta: 5:02:50 time: 0.6074 data_time: 0.0035 memory: 2751 grad_norm: 0.1236 loss: 0.2445 loss_sem_seg: 0.2445 2023/05/13 01:43:35 - mmengine - INFO - Epoch(train) [10][ 200/1196] lr: 8.0000e-03 eta: 5:02:28 time: 0.6057 data_time: 0.0035 memory: 2847 grad_norm: 0.1310 loss: 0.2501 loss_sem_seg: 0.2501 2023/05/13 01:43:57 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:44:06 - mmengine - INFO - Epoch(train) [10][ 250/1196] lr: 8.0000e-03 eta: 5:02:05 time: 0.6074 data_time: 0.0033 memory: 2676 grad_norm: 0.1178 loss: 0.2610 loss_sem_seg: 0.2610 2023/05/13 01:44:36 - mmengine - INFO - Epoch(train) [10][ 300/1196] lr: 8.0000e-03 eta: 5:01:44 time: 0.6164 data_time: 0.0034 memory: 2934 grad_norm: 0.1259 loss: 0.2589 loss_sem_seg: 0.2589 2023/05/13 01:45:07 - mmengine - INFO - Epoch(train) [10][ 350/1196] lr: 8.0000e-03 eta: 5:01:24 time: 0.6185 data_time: 0.0033 memory: 2811 grad_norm: 0.1251 loss: 0.2630 loss_sem_seg: 0.2630 2023/05/13 01:45:37 - mmengine - INFO - Epoch(train) [10][ 400/1196] lr: 8.0000e-03 eta: 5:01:01 time: 0.6023 data_time: 0.0033 memory: 2930 grad_norm: 0.1214 loss: 0.2500 loss_sem_seg: 0.2500 2023/05/13 01:46:07 - mmengine - INFO - Epoch(train) [10][ 450/1196] lr: 8.0000e-03 eta: 5:00:36 time: 0.5910 data_time: 0.0033 memory: 2745 grad_norm: 0.1248 loss: 0.2589 loss_sem_seg: 0.2589 2023/05/13 01:46:37 - mmengine - INFO - Epoch(train) [10][ 500/1196] lr: 8.0000e-03 eta: 5:00:14 time: 0.6096 data_time: 0.0034 memory: 3068 grad_norm: 0.1295 loss: 0.2337 loss_sem_seg: 0.2337 2023/05/13 01:47:08 - mmengine - INFO - Epoch(train) [10][ 550/1196] lr: 8.0000e-03 eta: 4:59:50 time: 0.6035 data_time: 0.0035 memory: 2731 grad_norm: 0.1181 loss: 0.2503 loss_sem_seg: 0.2503 2023/05/13 01:47:38 - mmengine - INFO - Epoch(train) [10][ 600/1196] lr: 8.0000e-03 eta: 4:59:28 time: 0.6083 data_time: 0.0033 memory: 2748 grad_norm: 0.1238 loss: 0.2547 loss_sem_seg: 0.2547 2023/05/13 01:48:09 - mmengine - INFO - Epoch(train) [10][ 650/1196] lr: 8.0000e-03 eta: 4:59:05 time: 0.6089 data_time: 0.0034 memory: 3000 grad_norm: 0.1179 loss: 0.2491 loss_sem_seg: 0.2491 2023/05/13 01:48:39 - mmengine - INFO - Epoch(train) [10][ 700/1196] lr: 8.0000e-03 eta: 4:58:42 time: 0.6062 data_time: 0.0033 memory: 2767 grad_norm: 0.1201 loss: 0.2427 loss_sem_seg: 0.2427 2023/05/13 01:49:10 - mmengine - INFO - Epoch(train) [10][ 750/1196] lr: 8.0000e-03 eta: 4:58:21 time: 0.6197 data_time: 0.0034 memory: 2890 grad_norm: 0.1304 loss: 0.2615 loss_sem_seg: 0.2615 2023/05/13 01:49:41 - mmengine - INFO - Epoch(train) [10][ 800/1196] lr: 8.0000e-03 eta: 4:57:59 time: 0.6139 data_time: 0.0035 memory: 3070 grad_norm: 0.1200 loss: 0.2609 loss_sem_seg: 0.2609 2023/05/13 01:50:11 - mmengine - INFO - Epoch(train) [10][ 850/1196] lr: 8.0000e-03 eta: 4:57:37 time: 0.6154 data_time: 0.0034 memory: 2897 grad_norm: 0.1423 loss: 0.2487 loss_sem_seg: 0.2487 2023/05/13 01:50:42 - mmengine - INFO - Epoch(train) [10][ 900/1196] lr: 8.0000e-03 eta: 4:57:14 time: 0.6053 data_time: 0.0033 memory: 2815 grad_norm: 0.1106 loss: 0.2392 loss_sem_seg: 0.2392 2023/05/13 01:51:12 - mmengine - INFO - Epoch(train) [10][ 950/1196] lr: 8.0000e-03 eta: 4:56:52 time: 0.6187 data_time: 0.0034 memory: 2823 grad_norm: 0.1301 loss: 0.2437 loss_sem_seg: 0.2437 2023/05/13 01:51:43 - mmengine - INFO - Epoch(train) [10][1000/1196] lr: 8.0000e-03 eta: 4:56:29 time: 0.6106 data_time: 0.0034 memory: 3027 grad_norm: 0.1162 loss: 0.2598 loss_sem_seg: 0.2598 2023/05/13 01:52:14 - mmengine - INFO - Epoch(train) [10][1050/1196] lr: 8.0000e-03 eta: 4:56:07 time: 0.6119 data_time: 0.0035 memory: 2880 grad_norm: 0.1184 loss: 0.2405 loss_sem_seg: 0.2405 2023/05/13 01:52:44 - mmengine - INFO - Epoch(train) [10][1100/1196] lr: 8.0000e-03 eta: 4:55:43 time: 0.6029 data_time: 0.0034 memory: 2795 grad_norm: 0.1286 loss: 0.2432 loss_sem_seg: 0.2432 2023/05/13 01:53:14 - mmengine - INFO - Epoch(train) [10][1150/1196] lr: 8.0000e-03 eta: 4:55:20 time: 0.6111 data_time: 0.0036 memory: 2887 grad_norm: 0.1345 loss: 0.2474 loss_sem_seg: 0.2474 2023/05/13 01:53:42 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:53:42 - mmengine - INFO - Saving checkpoint at 10 epochs 2023/05/13 01:54:07 - mmengine - INFO - Epoch(val) [10][ 50/509] eta: 0:02:47 time: 0.3645 data_time: 0.0021 memory: 3024 2023/05/13 01:54:23 - mmengine - INFO - Epoch(val) [10][100/509] eta: 0:02:21 time: 0.3260 data_time: 0.0021 memory: 920 2023/05/13 01:54:40 - mmengine - INFO - Epoch(val) [10][150/509] eta: 0:02:02 time: 0.3300 data_time: 0.0021 memory: 918 2023/05/13 01:54:57 - mmengine - INFO - Epoch(val) [10][200/509] eta: 0:01:44 time: 0.3375 data_time: 0.0021 memory: 906 2023/05/13 01:55:15 - mmengine - INFO - Epoch(val) [10][250/509] eta: 0:01:29 time: 0.3658 data_time: 0.0021 memory: 931 2023/05/13 01:55:30 - mmengine - INFO - Epoch(val) [10][300/509] eta: 0:01:10 time: 0.2921 data_time: 0.0021 memory: 868 2023/05/13 01:55:45 - mmengine - INFO - Epoch(val) [10][350/509] eta: 0:00:52 time: 0.3015 data_time: 0.0021 memory: 893 2023/05/13 01:56:02 - mmengine - INFO - Epoch(val) [10][400/509] eta: 0:00:36 time: 0.3465 data_time: 0.0021 memory: 901 2023/05/13 01:56:18 - mmengine - INFO - Epoch(val) [10][450/509] eta: 0:00:19 time: 0.3208 data_time: 0.0021 memory: 915 2023/05/13 01:56:34 - mmengine - INFO - Epoch(val) [10][500/509] eta: 0:00:02 time: 0.3204 data_time: 0.0020 memory: 898 2023/05/13 01:56:55 - 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 | 0.9454 | 0.4354 | 0.6909 | 0.5660 | 0.3916 | 0.5685 | 0.7764 | 0.0568 | 0.9296 | 0.4526 | 0.8024 | 0.0128 | 0.9114 | 0.6367 | 0.8875 | 0.6484 | 0.7635 | 0.6267 | 0.5055 | 0.6110 | 0.9197 | 0.6835 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 01:56:55 - mmengine - INFO - Epoch(val) [10][509/509] car: 0.9454 bicycle: 0.4354 motorcycle: 0.6909 truck: 0.5660 bus: 0.3916 person: 0.5685 bicyclist: 0.7764 motorcyclist: 0.0568 road: 0.9296 parking: 0.4526 sidewalk: 0.8024 other-ground: 0.0128 building: 0.9114 fence: 0.6367 vegetation: 0.8875 trunck: 0.6484 terrian: 0.7635 pole: 0.6267 traffic-sign: 0.5055 miou: 0.6110 acc: 0.9197 acc_cls: 0.6835 data_time: 0.0021 time: 0.3357 2023/05/13 01:57:19 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 01:57:25 - mmengine - INFO - Epoch(train) [11][ 50/1196] lr: 8.0000e-03 eta: 4:54:36 time: 0.6133 data_time: 0.0045 memory: 2812 grad_norm: 0.1225 loss: 0.2435 loss_sem_seg: 0.2435 2023/05/13 01:57:55 - mmengine - INFO - Epoch(train) [11][ 100/1196] lr: 8.0000e-03 eta: 4:54:10 time: 0.5880 data_time: 0.0033 memory: 2656 grad_norm: 0.1168 loss: 0.2601 loss_sem_seg: 0.2601 2023/05/13 01:58:25 - mmengine - INFO - Epoch(train) [11][ 150/1196] lr: 8.0000e-03 eta: 4:53:46 time: 0.6019 data_time: 0.0035 memory: 2877 grad_norm: 0.1203 loss: 0.2445 loss_sem_seg: 0.2445 2023/05/13 01:58:55 - mmengine - INFO - Epoch(train) [11][ 200/1196] lr: 8.0000e-03 eta: 4:53:22 time: 0.6060 data_time: 0.0034 memory: 2946 grad_norm: 0.1342 loss: 0.2699 loss_sem_seg: 0.2699 2023/05/13 01:59:25 - mmengine - INFO - Epoch(train) [11][ 250/1196] lr: 8.0000e-03 eta: 4:52:58 time: 0.6047 data_time: 0.0034 memory: 2730 grad_norm: 0.1159 loss: 0.2503 loss_sem_seg: 0.2503 2023/05/13 01:59:56 - mmengine - INFO - Epoch(train) [11][ 300/1196] lr: 8.0000e-03 eta: 4:52:33 time: 0.6011 data_time: 0.0034 memory: 2923 grad_norm: 0.1089 loss: 0.2350 loss_sem_seg: 0.2350 2023/05/13 02:00:25 - mmengine - INFO - Epoch(train) [11][ 350/1196] lr: 8.0000e-03 eta: 4:52:08 time: 0.5966 data_time: 0.0034 memory: 2926 grad_norm: 0.1139 loss: 0.2294 loss_sem_seg: 0.2294 2023/05/13 02:00:56 - mmengine - INFO - Epoch(train) [11][ 400/1196] lr: 8.0000e-03 eta: 4:51:44 time: 0.6100 data_time: 0.0034 memory: 2648 grad_norm: 0.1260 loss: 0.2440 loss_sem_seg: 0.2440 2023/05/13 02:01:26 - mmengine - INFO - Epoch(train) [11][ 450/1196] lr: 8.0000e-03 eta: 4:51:19 time: 0.5988 data_time: 0.0034 memory: 2737 grad_norm: 0.1158 loss: 0.2489 loss_sem_seg: 0.2489 2023/05/13 02:01:56 - mmengine - INFO - Epoch(train) [11][ 500/1196] lr: 8.0000e-03 eta: 4:50:56 time: 0.6118 data_time: 0.0034 memory: 2853 grad_norm: 0.1036 loss: 0.2373 loss_sem_seg: 0.2373 2023/05/13 02:02:27 - mmengine - INFO - Epoch(train) [11][ 550/1196] lr: 8.0000e-03 eta: 4:50:33 time: 0.6149 data_time: 0.0034 memory: 3086 grad_norm: 0.1041 loss: 0.2399 loss_sem_seg: 0.2399 2023/05/13 02:02:58 - mmengine - INFO - Epoch(train) [11][ 600/1196] lr: 8.0000e-03 eta: 4:50:09 time: 0.6090 data_time: 0.0033 memory: 2813 grad_norm: 0.1216 loss: 0.2351 loss_sem_seg: 0.2351 2023/05/13 02:03:28 - mmengine - INFO - Epoch(train) [11][ 650/1196] lr: 8.0000e-03 eta: 4:49:45 time: 0.6109 data_time: 0.0034 memory: 2978 grad_norm: 0.1135 loss: 0.2350 loss_sem_seg: 0.2350 2023/05/13 02:03:58 - mmengine - INFO - Epoch(train) [11][ 700/1196] lr: 8.0000e-03 eta: 4:49:20 time: 0.5986 data_time: 0.0034 memory: 2703 grad_norm: inf loss: 0.2343 loss_sem_seg: 0.2343 2023/05/13 02:04:29 - mmengine - INFO - Epoch(train) [11][ 750/1196] lr: 8.0000e-03 eta: 4:48:57 time: 0.6190 data_time: 0.0034 memory: 2922 grad_norm: 0.1221 loss: 0.2558 loss_sem_seg: 0.2558 2023/05/13 02:04:59 - mmengine - INFO - Epoch(train) [11][ 800/1196] lr: 8.0000e-03 eta: 4:48:33 time: 0.6064 data_time: 0.0035 memory: 2844 grad_norm: 0.1209 loss: 0.2481 loss_sem_seg: 0.2481 2023/05/13 02:05:30 - mmengine - INFO - Epoch(train) [11][ 850/1196] lr: 8.0000e-03 eta: 4:48:09 time: 0.6135 data_time: 0.0034 memory: 2846 grad_norm: 0.1183 loss: 0.2260 loss_sem_seg: 0.2260 2023/05/13 02:06:00 - mmengine - INFO - Epoch(train) [11][ 900/1196] lr: 8.0000e-03 eta: 4:47:45 time: 0.6072 data_time: 0.0034 memory: 2908 grad_norm: 0.1113 loss: 0.2391 loss_sem_seg: 0.2391 2023/05/13 02:06:31 - mmengine - INFO - Epoch(train) [11][ 950/1196] lr: 8.0000e-03 eta: 4:47:21 time: 0.6113 data_time: 0.0034 memory: 3055 grad_norm: 0.1186 loss: 0.2485 loss_sem_seg: 0.2485 2023/05/13 02:07:01 - mmengine - INFO - Epoch(train) [11][1000/1196] lr: 8.0000e-03 eta: 4:46:56 time: 0.6058 data_time: 0.0034 memory: 2841 grad_norm: 0.1310 loss: 0.2505 loss_sem_seg: 0.2505 2023/05/13 02:07:25 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:07:31 - mmengine - INFO - Epoch(train) [11][1050/1196] lr: 8.0000e-03 eta: 4:46:31 time: 0.6003 data_time: 0.0034 memory: 2718 grad_norm: 0.1177 loss: 0.2438 loss_sem_seg: 0.2438 2023/05/13 02:08:02 - mmengine - INFO - Epoch(train) [11][1100/1196] lr: 8.0000e-03 eta: 4:46:06 time: 0.6068 data_time: 0.0035 memory: 2897 grad_norm: 0.1144 loss: 0.2196 loss_sem_seg: 0.2196 2023/05/13 02:08:32 - mmengine - INFO - Epoch(train) [11][1150/1196] lr: 8.0000e-03 eta: 4:45:42 time: 0.6138 data_time: 0.0035 memory: 2649 grad_norm: 0.1262 loss: 0.2548 loss_sem_seg: 0.2548 2023/05/13 02:09:00 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:09:00 - mmengine - INFO - Saving checkpoint at 11 epochs 2023/05/13 02:09:25 - mmengine - INFO - Epoch(val) [11][ 50/509] eta: 0:02:49 time: 0.3687 data_time: 0.0021 memory: 2821 2023/05/13 02:09:43 - mmengine - INFO - Epoch(val) [11][100/509] eta: 0:02:26 time: 0.3498 data_time: 0.0022 memory: 920 2023/05/13 02:09:59 - mmengine - INFO - Epoch(val) [11][150/509] eta: 0:02:05 time: 0.3291 data_time: 0.0021 memory: 918 2023/05/13 02:10:16 - mmengine - INFO - Epoch(val) [11][200/509] eta: 0:01:47 time: 0.3411 data_time: 0.0022 memory: 906 2023/05/13 02:10:33 - mmengine - INFO - Epoch(val) [11][250/509] eta: 0:01:29 time: 0.3458 data_time: 0.0021 memory: 931 2023/05/13 02:10:47 - mmengine - INFO - Epoch(val) [11][300/509] eta: 0:01:10 time: 0.2811 data_time: 0.0021 memory: 868 2023/05/13 02:11:03 - mmengine - INFO - Epoch(val) [11][350/509] eta: 0:00:53 time: 0.3179 data_time: 0.0022 memory: 893 2023/05/13 02:11:21 - mmengine - INFO - Epoch(val) [11][400/509] eta: 0:00:36 time: 0.3502 data_time: 0.0021 memory: 901 2023/05/13 02:11:37 - mmengine - INFO - Epoch(val) [11][450/509] eta: 0:00:19 time: 0.3291 data_time: 0.0021 memory: 915 2023/05/13 02:11:52 - mmengine - INFO - Epoch(val) [11][500/509] eta: 0:00:02 time: 0.3001 data_time: 0.0021 memory: 898 2023/05/13 02:12:11 - 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 | 0.9587 | 0.5002 | 0.7634 | 0.6924 | 0.5784 | 0.6871 | 0.8051 | 0.0667 | 0.9410 | 0.4535 | 0.8198 | 0.0880 | 0.9147 | 0.6278 | 0.8813 | 0.6288 | 0.7541 | 0.6429 | 0.4899 | 0.6470 | 0.9219 | 0.7193 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 02:12:11 - mmengine - INFO - Epoch(val) [11][509/509] car: 0.9587 bicycle: 0.5002 motorcycle: 0.7634 truck: 0.6924 bus: 0.5784 person: 0.6871 bicyclist: 0.8051 motorcyclist: 0.0667 road: 0.9410 parking: 0.4535 sidewalk: 0.8198 other-ground: 0.0880 building: 0.9147 fence: 0.6278 vegetation: 0.8813 trunck: 0.6288 terrian: 0.7541 pole: 0.6429 traffic-sign: 0.4899 miou: 0.6470 acc: 0.9219 acc_cls: 0.7193 data_time: 0.0021 time: 0.3083 2023/05/13 02:12:38 - mmengine - INFO - Epoch(train) [12][ 50/1196] lr: 8.0000e-03 eta: 4:44:48 time: 0.5465 data_time: 0.0041 memory: 2877 grad_norm: 0.1102 loss: 0.2229 loss_sem_seg: 0.2229 2023/05/13 02:13:05 - mmengine - INFO - Epoch(train) [12][ 100/1196] lr: 8.0000e-03 eta: 4:44:14 time: 0.5288 data_time: 0.0032 memory: 2906 grad_norm: 0.1182 loss: 0.2338 loss_sem_seg: 0.2338 2023/05/13 02:13:29 - mmengine - INFO - Epoch(train) [12][ 150/1196] lr: 8.0000e-03 eta: 4:43:36 time: 0.4838 data_time: 0.0033 memory: 2873 grad_norm: 0.1233 loss: 0.2432 loss_sem_seg: 0.2432 2023/05/13 02:13:52 - mmengine - INFO - Epoch(train) [12][ 200/1196] lr: 8.0000e-03 eta: 4:42:54 time: 0.4532 data_time: 0.0034 memory: 2900 grad_norm: 0.1243 loss: 0.2316 loss_sem_seg: 0.2316 2023/05/13 02:14:14 - mmengine - INFO - Epoch(train) [12][ 250/1196] lr: 8.0000e-03 eta: 4:42:10 time: 0.4376 data_time: 0.0033 memory: 2711 grad_norm: 0.1193 loss: 0.2470 loss_sem_seg: 0.2470 2023/05/13 02:14:35 - mmengine - INFO - Epoch(train) [12][ 300/1196] lr: 8.0000e-03 eta: 4:41:27 time: 0.4353 data_time: 0.0033 memory: 2933 grad_norm: 0.1263 loss: 0.2459 loss_sem_seg: 0.2459 2023/05/13 02:14:58 - mmengine - INFO - Epoch(train) [12][ 350/1196] lr: 8.0000e-03 eta: 4:40:46 time: 0.4529 data_time: 0.0033 memory: 2801 grad_norm: 0.1093 loss: 0.2304 loss_sem_seg: 0.2304 2023/05/13 02:15:20 - mmengine - INFO - Epoch(train) [12][ 400/1196] lr: 8.0000e-03 eta: 4:40:04 time: 0.4488 data_time: 0.0035 memory: 2856 grad_norm: 0.1194 loss: 0.2555 loss_sem_seg: 0.2555 2023/05/13 02:15:44 - mmengine - INFO - Epoch(train) [12][ 450/1196] lr: 8.0000e-03 eta: 4:39:24 time: 0.4692 data_time: 0.0034 memory: 2960 grad_norm: 0.1172 loss: 0.2381 loss_sem_seg: 0.2381 2023/05/13 02:16:09 - mmengine - INFO - Epoch(train) [12][ 500/1196] lr: 8.0000e-03 eta: 4:38:48 time: 0.4931 data_time: 0.0031 memory: 2719 grad_norm: 0.1305 loss: 0.2513 loss_sem_seg: 0.2513 2023/05/13 02:16:33 - mmengine - INFO - Epoch(train) [12][ 550/1196] lr: 8.0000e-03 eta: 4:38:11 time: 0.4898 data_time: 0.0033 memory: 2875 grad_norm: 0.1175 loss: 0.2577 loss_sem_seg: 0.2577 2023/05/13 02:16:58 - mmengine - INFO - Epoch(train) [12][ 600/1196] lr: 8.0000e-03 eta: 4:37:36 time: 0.5038 data_time: 0.0035 memory: 2795 grad_norm: 0.1386 loss: 0.2383 loss_sem_seg: 0.2383 2023/05/13 02:17:23 - mmengine - INFO - Epoch(train) [12][ 650/1196] lr: 8.0000e-03 eta: 4:37:00 time: 0.5020 data_time: 0.0037 memory: 3028 grad_norm: 0.1268 loss: 0.2522 loss_sem_seg: 0.2522 2023/05/13 02:17:48 - mmengine - INFO - Epoch(train) [12][ 700/1196] lr: 8.0000e-03 eta: 4:36:24 time: 0.4986 data_time: 0.0035 memory: 2716 grad_norm: 0.1066 loss: 0.2497 loss_sem_seg: 0.2497 2023/05/13 02:18:13 - mmengine - INFO - Epoch(train) [12][ 750/1196] lr: 8.0000e-03 eta: 4:35:48 time: 0.4964 data_time: 0.0034 memory: 2751 grad_norm: 0.1106 loss: 0.2381 loss_sem_seg: 0.2381 2023/05/13 02:18:43 - mmengine - INFO - Epoch(train) [12][ 800/1196] lr: 8.0000e-03 eta: 4:35:23 time: 0.5946 data_time: 0.0032 memory: 2805 grad_norm: 0.1058 loss: 0.2382 loss_sem_seg: 0.2382 2023/05/13 02:19:08 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:19:12 - mmengine - INFO - Epoch(train) [12][ 850/1196] lr: 8.0000e-03 eta: 4:34:56 time: 0.5812 data_time: 0.0033 memory: 2836 grad_norm: 0.1130 loss: 0.2402 loss_sem_seg: 0.2402 2023/05/13 02:19:41 - mmengine - INFO - Epoch(train) [12][ 900/1196] lr: 8.0000e-03 eta: 4:34:28 time: 0.5774 data_time: 0.0035 memory: 2935 grad_norm: 0.1201 loss: 0.2417 loss_sem_seg: 0.2417 2023/05/13 02:20:13 - mmengine - INFO - Epoch(train) [12][ 950/1196] lr: 8.0000e-03 eta: 4:34:07 time: 0.6379 data_time: 0.0034 memory: 2866 grad_norm: 0.1122 loss: 0.2290 loss_sem_seg: 0.2290 2023/05/13 02:20:43 - mmengine - INFO - Epoch(train) [12][1000/1196] lr: 8.0000e-03 eta: 4:33:42 time: 0.5957 data_time: 0.0034 memory: 2905 grad_norm: 0.1072 loss: 0.2352 loss_sem_seg: 0.2352 2023/05/13 02:21:13 - mmengine - INFO - Epoch(train) [12][1050/1196] lr: 8.0000e-03 eta: 4:33:18 time: 0.6189 data_time: 0.0035 memory: 2725 grad_norm: 0.1000 loss: 0.2327 loss_sem_seg: 0.2327 2023/05/13 02:21:44 - mmengine - INFO - Epoch(train) [12][1100/1196] lr: 8.0000e-03 eta: 4:32:55 time: 0.6138 data_time: 0.0033 memory: 2888 grad_norm: 0.1099 loss: 0.2411 loss_sem_seg: 0.2411 2023/05/13 02:22:15 - mmengine - INFO - Epoch(train) [12][1150/1196] lr: 8.0000e-03 eta: 4:32:31 time: 0.6128 data_time: 0.0033 memory: 2891 grad_norm: 0.1173 loss: 0.2354 loss_sem_seg: 0.2354 2023/05/13 02:22:42 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:22:42 - mmengine - INFO - Saving checkpoint at 12 epochs 2023/05/13 02:23:07 - mmengine - INFO - Epoch(val) [12][ 50/509] eta: 0:02:48 time: 0.3673 data_time: 0.0021 memory: 2791 2023/05/13 02:23:24 - mmengine - INFO - Epoch(val) [12][100/509] eta: 0:02:26 time: 0.3474 data_time: 0.0021 memory: 920 2023/05/13 02:23:41 - mmengine - INFO - Epoch(val) [12][150/509] eta: 0:02:06 time: 0.3400 data_time: 0.0021 memory: 918 2023/05/13 02:23:57 - mmengine - INFO - Epoch(val) [12][200/509] eta: 0:01:46 time: 0.3265 data_time: 0.0021 memory: 906 2023/05/13 02:24:16 - mmengine - INFO - Epoch(val) [12][250/509] eta: 0:01:30 time: 0.3668 data_time: 0.0021 memory: 931 2023/05/13 02:24:30 - mmengine - INFO - Epoch(val) [12][300/509] eta: 0:01:10 time: 0.2847 data_time: 0.0021 memory: 868 2023/05/13 02:24:46 - mmengine - INFO - Epoch(val) [12][350/509] eta: 0:00:53 time: 0.3210 data_time: 0.0022 memory: 893 2023/05/13 02:25:03 - mmengine - INFO - Epoch(val) [12][400/509] eta: 0:00:36 time: 0.3379 data_time: 0.0021 memory: 901 2023/05/13 02:25:20 - mmengine - INFO - Epoch(val) [12][450/509] eta: 0:00:19 time: 0.3323 data_time: 0.0021 memory: 915 2023/05/13 02:25:36 - mmengine - INFO - Epoch(val) [12][500/509] eta: 0:00:03 time: 0.3287 data_time: 0.0021 memory: 898 2023/05/13 02:25:56 - 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 | 0.9651 | 0.4452 | 0.6709 | 0.2994 | 0.3937 | 0.7042 | 0.7934 | 0.0467 | 0.9319 | 0.4232 | 0.8025 | 0.0298 | 0.9030 | 0.6312 | 0.8970 | 0.7103 | 0.7745 | 0.6574 | 0.5042 | 0.6097 | 0.9221 | 0.7132 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 02:25:56 - mmengine - INFO - Epoch(val) [12][509/509] car: 0.9651 bicycle: 0.4452 motorcycle: 0.6709 truck: 0.2994 bus: 0.3937 person: 0.7042 bicyclist: 0.7934 motorcyclist: 0.0467 road: 0.9319 parking: 0.4232 sidewalk: 0.8025 other-ground: 0.0298 building: 0.9030 fence: 0.6312 vegetation: 0.8970 trunck: 0.7103 terrian: 0.7745 pole: 0.6574 traffic-sign: 0.5042 miou: 0.6097 acc: 0.9221 acc_cls: 0.7132 data_time: 0.0020 time: 0.3441 2023/05/13 02:26:27 - mmengine - INFO - Epoch(train) [13][ 50/1196] lr: 8.0000e-03 eta: 4:31:43 time: 0.6195 data_time: 0.0044 memory: 2929 grad_norm: 0.1146 loss: 0.2427 loss_sem_seg: 0.2427 2023/05/13 02:26:58 - mmengine - INFO - Epoch(train) [13][ 100/1196] lr: 8.0000e-03 eta: 4:31:19 time: 0.6166 data_time: 0.0035 memory: 2802 grad_norm: 0.1111 loss: 0.2320 loss_sem_seg: 0.2320 2023/05/13 02:27:29 - mmengine - INFO - Epoch(train) [13][ 150/1196] lr: 8.0000e-03 eta: 4:30:56 time: 0.6154 data_time: 0.0034 memory: 3128 grad_norm: 0.1168 loss: 0.2417 loss_sem_seg: 0.2417 2023/05/13 02:27:59 - mmengine - INFO - Epoch(train) [13][ 200/1196] lr: 8.0000e-03 eta: 4:30:31 time: 0.6120 data_time: 0.0033 memory: 2967 grad_norm: 0.1054 loss: 0.2382 loss_sem_seg: 0.2382 2023/05/13 02:28:29 - mmengine - INFO - Epoch(train) [13][ 250/1196] lr: 8.0000e-03 eta: 4:30:06 time: 0.6056 data_time: 0.0034 memory: 2745 grad_norm: 0.1062 loss: 0.2356 loss_sem_seg: 0.2356 2023/05/13 02:28:59 - mmengine - INFO - Epoch(train) [13][ 300/1196] lr: 8.0000e-03 eta: 4:29:40 time: 0.5912 data_time: 0.0034 memory: 2949 grad_norm: 0.1022 loss: 0.2370 loss_sem_seg: 0.2370 2023/05/13 02:29:29 - mmengine - INFO - Epoch(train) [13][ 350/1196] lr: 8.0000e-03 eta: 4:29:15 time: 0.6016 data_time: 0.0036 memory: 2872 grad_norm: 0.1174 loss: 0.2360 loss_sem_seg: 0.2360 2023/05/13 02:29:58 - mmengine - INFO - Epoch(train) [13][ 400/1196] lr: 8.0000e-03 eta: 4:28:47 time: 0.5772 data_time: 0.0033 memory: 2777 grad_norm: 0.1088 loss: 0.2374 loss_sem_seg: 0.2374 2023/05/13 02:30:28 - mmengine - INFO - Epoch(train) [13][ 450/1196] lr: 8.0000e-03 eta: 4:28:22 time: 0.6039 data_time: 0.0034 memory: 2820 grad_norm: 0.1269 loss: 0.2441 loss_sem_seg: 0.2441 2023/05/13 02:30:59 - mmengine - INFO - Epoch(train) [13][ 500/1196] lr: 8.0000e-03 eta: 4:27:57 time: 0.6100 data_time: 0.0034 memory: 2730 grad_norm: 0.1074 loss: 0.2295 loss_sem_seg: 0.2295 2023/05/13 02:31:29 - mmengine - INFO - Epoch(train) [13][ 550/1196] lr: 8.0000e-03 eta: 4:27:32 time: 0.6070 data_time: 0.0033 memory: 2844 grad_norm: 0.1227 loss: 0.2555 loss_sem_seg: 0.2555 2023/05/13 02:31:59 - mmengine - INFO - Epoch(train) [13][ 600/1196] lr: 8.0000e-03 eta: 4:27:06 time: 0.5976 data_time: 0.0034 memory: 3064 grad_norm: 0.1157 loss: 0.2398 loss_sem_seg: 0.2398 2023/05/13 02:32:29 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:32:30 - mmengine - INFO - Epoch(train) [13][ 650/1196] lr: 8.0000e-03 eta: 4:26:42 time: 0.6233 data_time: 0.0034 memory: 2973 grad_norm: 0.1093 loss: 0.2224 loss_sem_seg: 0.2224 2023/05/13 02:33:00 - mmengine - INFO - Epoch(train) [13][ 700/1196] lr: 8.0000e-03 eta: 4:26:17 time: 0.6078 data_time: 0.0035 memory: 2689 grad_norm: 0.1024 loss: 0.2370 loss_sem_seg: 0.2370 2023/05/13 02:33:31 - mmengine - INFO - Epoch(train) [13][ 750/1196] lr: 8.0000e-03 eta: 4:25:53 time: 0.6207 data_time: 0.0035 memory: 2900 grad_norm: 0.1157 loss: 0.2272 loss_sem_seg: 0.2272 2023/05/13 02:34:02 - mmengine - INFO - Epoch(train) [13][ 800/1196] lr: 8.0000e-03 eta: 4:25:29 time: 0.6164 data_time: 0.0035 memory: 3102 grad_norm: 0.1172 loss: 0.2394 loss_sem_seg: 0.2394 2023/05/13 02:34:33 - mmengine - INFO - Epoch(train) [13][ 850/1196] lr: 8.0000e-03 eta: 4:25:04 time: 0.6052 data_time: 0.0035 memory: 2742 grad_norm: 0.1276 loss: 0.2483 loss_sem_seg: 0.2483 2023/05/13 02:35:04 - mmengine - INFO - Epoch(train) [13][ 900/1196] lr: 8.0000e-03 eta: 4:24:40 time: 0.6213 data_time: 0.0034 memory: 3051 grad_norm: 0.1099 loss: 0.2297 loss_sem_seg: 0.2297 2023/05/13 02:35:33 - mmengine - INFO - Epoch(train) [13][ 950/1196] lr: 8.0000e-03 eta: 4:24:12 time: 0.5806 data_time: 0.0034 memory: 2929 grad_norm: inf loss: 0.2367 loss_sem_seg: 0.2367 2023/05/13 02:36:02 - mmengine - INFO - Epoch(train) [13][1000/1196] lr: 8.0000e-03 eta: 4:23:46 time: 0.5954 data_time: 0.0036 memory: 2913 grad_norm: 0.1003 loss: 0.2335 loss_sem_seg: 0.2335 2023/05/13 02:36:33 - mmengine - INFO - Epoch(train) [13][1050/1196] lr: 8.0000e-03 eta: 4:23:21 time: 0.6109 data_time: 0.0036 memory: 2963 grad_norm: 0.0977 loss: 0.2329 loss_sem_seg: 0.2329 2023/05/13 02:37:03 - mmengine - INFO - Epoch(train) [13][1100/1196] lr: 8.0000e-03 eta: 4:22:55 time: 0.6086 data_time: 0.0036 memory: 2867 grad_norm: 0.1210 loss: 0.2261 loss_sem_seg: 0.2261 2023/05/13 02:37:34 - mmengine - INFO - Epoch(train) [13][1150/1196] lr: 8.0000e-03 eta: 4:22:30 time: 0.6124 data_time: 0.0035 memory: 2841 grad_norm: 0.1244 loss: 0.2483 loss_sem_seg: 0.2483 2023/05/13 02:38:02 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:38:02 - mmengine - INFO - Saving checkpoint at 13 epochs 2023/05/13 02:38:27 - mmengine - INFO - Epoch(val) [13][ 50/509] eta: 0:02:50 time: 0.3717 data_time: 0.0022 memory: 2931 2023/05/13 02:38:44 - mmengine - INFO - Epoch(val) [13][100/509] eta: 0:02:25 time: 0.3419 data_time: 0.0021 memory: 920 2023/05/13 02:39:01 - mmengine - INFO - Epoch(val) [13][150/509] eta: 0:02:05 time: 0.3374 data_time: 0.0021 memory: 918 2023/05/13 02:39:18 - mmengine - INFO - Epoch(val) [13][200/509] eta: 0:01:46 time: 0.3335 data_time: 0.0021 memory: 906 2023/05/13 02:39:36 - mmengine - INFO - Epoch(val) [13][250/509] eta: 0:01:30 time: 0.3684 data_time: 0.0021 memory: 931 2023/05/13 02:39:52 - mmengine - INFO - Epoch(val) [13][300/509] eta: 0:01:11 time: 0.3086 data_time: 0.0021 memory: 868 2023/05/13 02:40:08 - mmengine - INFO - Epoch(val) [13][350/509] eta: 0:00:54 time: 0.3257 data_time: 0.0021 memory: 893 2023/05/13 02:40:25 - mmengine - INFO - Epoch(val) [13][400/509] eta: 0:00:37 time: 0.3433 data_time: 0.0021 memory: 901 2023/05/13 02:40:42 - mmengine - INFO - Epoch(val) [13][450/509] eta: 0:00:20 time: 0.3416 data_time: 0.0021 memory: 915 2023/05/13 02:40:59 - mmengine - INFO - Epoch(val) [13][500/509] eta: 0:00:03 time: 0.3316 data_time: 0.0021 memory: 898 2023/05/13 02:41:20 - 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 | 0.9450 | 0.4335 | 0.6875 | 0.6677 | 0.3705 | 0.7601 | 0.7969 | 0.0359 | 0.9401 | 0.4711 | 0.8275 | 0.0622 | 0.9100 | 0.6561 | 0.8937 | 0.7002 | 0.7781 | 0.6557 | 0.4871 | 0.6357 | 0.9258 | 0.7139 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 02:41:20 - mmengine - INFO - Epoch(val) [13][509/509] car: 0.9450 bicycle: 0.4335 motorcycle: 0.6875 truck: 0.6677 bus: 0.3705 person: 0.7601 bicyclist: 0.7969 motorcyclist: 0.0359 road: 0.9401 parking: 0.4711 sidewalk: 0.8275 other-ground: 0.0622 building: 0.9100 fence: 0.6561 vegetation: 0.8937 trunck: 0.7002 terrian: 0.7781 pole: 0.6557 traffic-sign: 0.4871 miou: 0.6357 acc: 0.9258 acc_cls: 0.7139 data_time: 0.0020 time: 0.3459 2023/05/13 02:41:50 - mmengine - INFO - Epoch(train) [14][ 50/1196] lr: 8.0000e-03 eta: 4:21:43 time: 0.6130 data_time: 0.0042 memory: 2786 grad_norm: 0.1117 loss: 0.2383 loss_sem_seg: 0.2383 2023/05/13 02:42:21 - mmengine - INFO - Epoch(train) [14][ 100/1196] lr: 8.0000e-03 eta: 4:21:18 time: 0.6129 data_time: 0.0035 memory: 2869 grad_norm: 0.1175 loss: 0.2409 loss_sem_seg: 0.2409 2023/05/13 02:42:51 - mmengine - INFO - Epoch(train) [14][ 150/1196] lr: 8.0000e-03 eta: 4:20:52 time: 0.6011 data_time: 0.0036 memory: 2709 grad_norm: 0.1082 loss: 0.2278 loss_sem_seg: 0.2278 2023/05/13 02:43:21 - mmengine - INFO - Epoch(train) [14][ 200/1196] lr: 8.0000e-03 eta: 4:20:25 time: 0.5916 data_time: 0.0035 memory: 2742 grad_norm: 0.1146 loss: 0.2361 loss_sem_seg: 0.2361 2023/05/13 02:43:51 - mmengine - INFO - Epoch(train) [14][ 250/1196] lr: 8.0000e-03 eta: 4:19:59 time: 0.6030 data_time: 0.0034 memory: 2602 grad_norm: 0.1164 loss: 0.2343 loss_sem_seg: 0.2343 2023/05/13 02:44:21 - mmengine - INFO - Epoch(train) [14][ 300/1196] lr: 8.0000e-03 eta: 4:19:33 time: 0.6059 data_time: 0.0034 memory: 2587 grad_norm: 0.1008 loss: 0.2313 loss_sem_seg: 0.2313 2023/05/13 02:44:52 - mmengine - INFO - Epoch(train) [14][ 350/1196] lr: 8.0000e-03 eta: 4:19:08 time: 0.6142 data_time: 0.0035 memory: 3128 grad_norm: 0.1058 loss: 0.2250 loss_sem_seg: 0.2250 2023/05/13 02:45:21 - mmengine - INFO - Epoch(train) [14][ 400/1196] lr: 8.0000e-03 eta: 4:18:41 time: 0.5908 data_time: 0.0034 memory: 2932 grad_norm: 0.1240 loss: 0.2302 loss_sem_seg: 0.2302 2023/05/13 02:45:52 - mmengine - INFO - Epoch(train) [14][ 450/1196] lr: 8.0000e-03 eta: 4:18:16 time: 0.6183 data_time: 0.0034 memory: 2779 grad_norm: 0.1115 loss: 0.2426 loss_sem_seg: 0.2426 2023/05/13 02:45:54 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:46:23 - mmengine - INFO - Epoch(train) [14][ 500/1196] lr: 8.0000e-03 eta: 4:17:52 time: 0.6200 data_time: 0.0033 memory: 2913 grad_norm: 0.1055 loss: 0.2489 loss_sem_seg: 0.2489 2023/05/13 02:46:53 - mmengine - INFO - Epoch(train) [14][ 550/1196] lr: 8.0000e-03 eta: 4:17:25 time: 0.6007 data_time: 0.0034 memory: 2673 grad_norm: 0.0966 loss: 0.2290 loss_sem_seg: 0.2290 2023/05/13 02:47:24 - mmengine - INFO - Epoch(train) [14][ 600/1196] lr: 8.0000e-03 eta: 4:17:00 time: 0.6081 data_time: 0.0033 memory: 2992 grad_norm: 0.0983 loss: 0.2229 loss_sem_seg: 0.2229 2023/05/13 02:47:54 - mmengine - INFO - Epoch(train) [14][ 650/1196] lr: 8.0000e-03 eta: 4:16:34 time: 0.6081 data_time: 0.0033 memory: 2766 grad_norm: 0.1038 loss: 0.2245 loss_sem_seg: 0.2245 2023/05/13 02:48:24 - mmengine - INFO - Epoch(train) [14][ 700/1196] lr: 8.0000e-03 eta: 4:16:08 time: 0.6063 data_time: 0.0035 memory: 2849 grad_norm: 0.1125 loss: 0.2323 loss_sem_seg: 0.2323 2023/05/13 02:48:55 - mmengine - INFO - Epoch(train) [14][ 750/1196] lr: 8.0000e-03 eta: 4:15:42 time: 0.6083 data_time: 0.0033 memory: 2745 grad_norm: 0.1176 loss: 0.2517 loss_sem_seg: 0.2517 2023/05/13 02:49:26 - mmengine - INFO - Epoch(train) [14][ 800/1196] lr: 8.0000e-03 eta: 4:15:17 time: 0.6224 data_time: 0.0034 memory: 2986 grad_norm: 0.1144 loss: 0.2467 loss_sem_seg: 0.2467 2023/05/13 02:49:57 - mmengine - INFO - Epoch(train) [14][ 850/1196] lr: 8.0000e-03 eta: 4:14:52 time: 0.6177 data_time: 0.0037 memory: 2732 grad_norm: 0.1200 loss: 0.2259 loss_sem_seg: 0.2259 2023/05/13 02:50:28 - mmengine - INFO - Epoch(train) [14][ 900/1196] lr: 8.0000e-03 eta: 4:14:27 time: 0.6142 data_time: 0.0036 memory: 2992 grad_norm: 0.1139 loss: 0.2437 loss_sem_seg: 0.2437 2023/05/13 02:50:58 - mmengine - INFO - Epoch(train) [14][ 950/1196] lr: 8.0000e-03 eta: 4:14:01 time: 0.6102 data_time: 0.0034 memory: 2698 grad_norm: 0.1207 loss: 0.2198 loss_sem_seg: 0.2198 2023/05/13 02:51:28 - mmengine - INFO - Epoch(train) [14][1000/1196] lr: 8.0000e-03 eta: 4:13:35 time: 0.6056 data_time: 0.0034 memory: 2826 grad_norm: 0.1100 loss: 0.2357 loss_sem_seg: 0.2357 2023/05/13 02:51:59 - mmengine - INFO - Epoch(train) [14][1050/1196] lr: 8.0000e-03 eta: 4:13:09 time: 0.6123 data_time: 0.0035 memory: 2791 grad_norm: 0.1095 loss: 0.2170 loss_sem_seg: 0.2170 2023/05/13 02:52:28 - mmengine - INFO - Epoch(train) [14][1100/1196] lr: 8.0000e-03 eta: 4:12:42 time: 0.5865 data_time: 0.0036 memory: 2776 grad_norm: 0.1096 loss: 0.2202 loss_sem_seg: 0.2202 2023/05/13 02:52:57 - mmengine - INFO - Epoch(train) [14][1150/1196] lr: 8.0000e-03 eta: 4:12:12 time: 0.5677 data_time: 0.0035 memory: 2757 grad_norm: 0.0973 loss: 0.2320 loss_sem_seg: 0.2320 2023/05/13 02:53:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:53:23 - mmengine - INFO - Saving checkpoint at 14 epochs 2023/05/13 02:53:46 - mmengine - INFO - Epoch(val) [14][ 50/509] eta: 0:02:36 time: 0.3418 data_time: 0.0021 memory: 3070 2023/05/13 02:54:02 - mmengine - INFO - Epoch(val) [14][100/509] eta: 0:02:12 time: 0.3078 data_time: 0.0022 memory: 920 2023/05/13 02:54:16 - mmengine - INFO - Epoch(val) [14][150/509] eta: 0:01:51 time: 0.2820 data_time: 0.0021 memory: 918 2023/05/13 02:54:29 - mmengine - INFO - Epoch(val) [14][200/509] eta: 0:01:33 time: 0.2727 data_time: 0.0021 memory: 906 2023/05/13 02:54:44 - mmengine - INFO - Epoch(val) [14][250/509] eta: 0:01:17 time: 0.2962 data_time: 0.0021 memory: 931 2023/05/13 02:54:55 - mmengine - INFO - Epoch(val) [14][300/509] eta: 0:00:59 time: 0.2189 data_time: 0.0020 memory: 868 2023/05/13 02:55:07 - mmengine - INFO - Epoch(val) [14][350/509] eta: 0:00:44 time: 0.2330 data_time: 0.0020 memory: 893 2023/05/13 02:55:20 - mmengine - INFO - Epoch(val) [14][400/509] eta: 0:00:30 time: 0.2673 data_time: 0.0020 memory: 901 2023/05/13 02:55:35 - mmengine - INFO - Epoch(val) [14][450/509] eta: 0:00:16 time: 0.3037 data_time: 0.0020 memory: 915 2023/05/13 02:55:50 - mmengine - INFO - Epoch(val) [14][500/509] eta: 0:00:02 time: 0.2985 data_time: 0.0021 memory: 898 2023/05/13 02:56:11 - 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 | 0.9526 | 0.4789 | 0.6386 | 0.1093 | 0.4624 | 0.6555 | 0.6541 | 0.0010 | 0.9282 | 0.3403 | 0.7982 | 0.0386 | 0.9088 | 0.6146 | 0.8893 | 0.6992 | 0.7667 | 0.6377 | 0.4954 | 0.5826 | 0.9188 | 0.6545 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 02:56:11 - mmengine - INFO - Epoch(val) [14][509/509] car: 0.9526 bicycle: 0.4789 motorcycle: 0.6386 truck: 0.1093 bus: 0.4624 person: 0.6555 bicyclist: 0.6541 motorcyclist: 0.0010 road: 0.9282 parking: 0.3403 sidewalk: 0.7982 other-ground: 0.0386 building: 0.9088 fence: 0.6146 vegetation: 0.8893 trunck: 0.6992 terrian: 0.7667 pole: 0.6377 traffic-sign: 0.4954 miou: 0.5826 acc: 0.9188 acc_cls: 0.6545 data_time: 0.0021 time: 0.3090 2023/05/13 02:56:40 - mmengine - INFO - Epoch(train) [15][ 50/1196] lr: 8.0000e-03 eta: 4:11:16 time: 0.5636 data_time: 0.0044 memory: 2850 grad_norm: 0.1085 loss: 0.2333 loss_sem_seg: 0.2333 2023/05/13 02:57:08 - mmengine - INFO - Epoch(train) [15][ 100/1196] lr: 8.0000e-03 eta: 4:10:47 time: 0.5756 data_time: 0.0034 memory: 2757 grad_norm: 0.0938 loss: 0.2219 loss_sem_seg: 0.2219 2023/05/13 02:57:37 - mmengine - INFO - Epoch(train) [15][ 150/1196] lr: 8.0000e-03 eta: 4:10:19 time: 0.5748 data_time: 0.0034 memory: 2774 grad_norm: 0.1100 loss: 0.2307 loss_sem_seg: 0.2307 2023/05/13 02:58:05 - mmengine - INFO - Epoch(train) [15][ 200/1196] lr: 8.0000e-03 eta: 4:09:48 time: 0.5487 data_time: 0.0033 memory: 2606 grad_norm: 0.1144 loss: 0.2258 loss_sem_seg: 0.2258 2023/05/13 02:58:33 - mmengine - INFO - Epoch(train) [15][ 250/1196] lr: 8.0000e-03 eta: 4:09:19 time: 0.5637 data_time: 0.0035 memory: 2991 grad_norm: 0.1085 loss: 0.2306 loss_sem_seg: 0.2306 2023/05/13 02:58:36 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 02:59:01 - mmengine - INFO - Epoch(train) [15][ 300/1196] lr: 8.0000e-03 eta: 4:08:49 time: 0.5580 data_time: 0.0036 memory: 2708 grad_norm: 0.1086 loss: 0.2284 loss_sem_seg: 0.2284 2023/05/13 02:59:29 - mmengine - INFO - Epoch(train) [15][ 350/1196] lr: 8.0000e-03 eta: 4:08:20 time: 0.5694 data_time: 0.0035 memory: 2840 grad_norm: 0.0949 loss: 0.2236 loss_sem_seg: 0.2236 2023/05/13 02:59:57 - mmengine - INFO - Epoch(train) [15][ 400/1196] lr: 8.0000e-03 eta: 4:07:49 time: 0.5528 data_time: 0.0033 memory: 2735 grad_norm: 0.1120 loss: 0.2142 loss_sem_seg: 0.2142 2023/05/13 03:00:26 - mmengine - INFO - Epoch(train) [15][ 450/1196] lr: 8.0000e-03 eta: 4:07:21 time: 0.5763 data_time: 0.0034 memory: 2965 grad_norm: 0.1005 loss: 0.2357 loss_sem_seg: 0.2357 2023/05/13 03:00:53 - mmengine - INFO - Epoch(train) [15][ 500/1196] lr: 8.0000e-03 eta: 4:06:51 time: 0.5580 data_time: 0.0034 memory: 2917 grad_norm: 0.0970 loss: 0.2124 loss_sem_seg: 0.2124 2023/05/13 03:01:21 - mmengine - INFO - Epoch(train) [15][ 550/1196] lr: 8.0000e-03 eta: 4:06:20 time: 0.5512 data_time: 0.0034 memory: 2596 grad_norm: 0.1110 loss: 0.2304 loss_sem_seg: 0.2304 2023/05/13 03:01:49 - mmengine - INFO - Epoch(train) [15][ 600/1196] lr: 8.0000e-03 eta: 4:05:50 time: 0.5544 data_time: 0.0033 memory: 2884 grad_norm: 0.0978 loss: 0.2210 loss_sem_seg: 0.2210 2023/05/13 03:02:21 - mmengine - INFO - Epoch(train) [15][ 650/1196] lr: 8.0000e-03 eta: 4:05:26 time: 0.6379 data_time: 0.0034 memory: 2854 grad_norm: 0.1219 loss: 0.2154 loss_sem_seg: 0.2154 2023/05/13 03:02:50 - mmengine - INFO - Epoch(train) [15][ 700/1196] lr: 8.0000e-03 eta: 4:04:59 time: 0.5961 data_time: 0.0034 memory: 2893 grad_norm: 0.1006 loss: 0.2148 loss_sem_seg: 0.2148 2023/05/13 03:03:22 - mmengine - INFO - Epoch(train) [15][ 750/1196] lr: 8.0000e-03 eta: 4:04:35 time: 0.6303 data_time: 0.0034 memory: 2834 grad_norm: 0.1026 loss: 0.2241 loss_sem_seg: 0.2241 2023/05/13 03:03:53 - mmengine - INFO - Epoch(train) [15][ 800/1196] lr: 8.0000e-03 eta: 4:04:09 time: 0.6168 data_time: 0.0035 memory: 2808 grad_norm: 0.1069 loss: 0.2134 loss_sem_seg: 0.2134 2023/05/13 03:04:23 - mmengine - INFO - Epoch(train) [15][ 850/1196] lr: 8.0000e-03 eta: 4:03:43 time: 0.6110 data_time: 0.0035 memory: 2757 grad_norm: 0.0980 loss: 0.2099 loss_sem_seg: 0.2099 2023/05/13 03:04:54 - mmengine - INFO - Epoch(train) [15][ 900/1196] lr: 8.0000e-03 eta: 4:03:17 time: 0.6137 data_time: 0.0034 memory: 2784 grad_norm: 0.1043 loss: 0.2209 loss_sem_seg: 0.2209 2023/05/13 03:05:24 - mmengine - INFO - Epoch(train) [15][ 950/1196] lr: 8.0000e-03 eta: 4:02:50 time: 0.5907 data_time: 0.0035 memory: 2852 grad_norm: 0.1095 loss: 0.2292 loss_sem_seg: 0.2292 2023/05/13 03:05:52 - mmengine - INFO - Epoch(train) [15][1000/1196] lr: 8.0000e-03 eta: 4:02:21 time: 0.5750 data_time: 0.0035 memory: 2825 grad_norm: 0.1081 loss: 0.2151 loss_sem_seg: 0.2151 2023/05/13 03:06:19 - mmengine - INFO - Epoch(train) [15][1050/1196] lr: 8.0000e-03 eta: 4:01:49 time: 0.5325 data_time: 0.0034 memory: 2881 grad_norm: 0.1020 loss: 0.2299 loss_sem_seg: 0.2299 2023/05/13 03:06:46 - mmengine - INFO - Epoch(train) [15][1100/1196] lr: 8.0000e-03 eta: 4:01:19 time: 0.5463 data_time: 0.0035 memory: 2775 grad_norm: 0.1314 loss: 0.2408 loss_sem_seg: 0.2408 2023/05/13 03:07:14 - mmengine - INFO - Epoch(train) [15][1150/1196] lr: 8.0000e-03 eta: 4:00:48 time: 0.5504 data_time: 0.0035 memory: 2694 grad_norm: 0.1133 loss: 0.2144 loss_sem_seg: 0.2144 2023/05/13 03:07:38 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:07:38 - mmengine - INFO - Saving checkpoint at 15 epochs 2023/05/13 03:08:01 - mmengine - INFO - Epoch(val) [15][ 50/509] eta: 0:02:30 time: 0.3283 data_time: 0.0021 memory: 2779 2023/05/13 03:08:16 - mmengine - INFO - Epoch(val) [15][100/509] eta: 0:02:05 time: 0.2842 data_time: 0.0021 memory: 920 2023/05/13 03:08:29 - mmengine - INFO - Epoch(val) [15][150/509] eta: 0:01:45 time: 0.2687 data_time: 0.0021 memory: 918 2023/05/13 03:08:44 - mmengine - INFO - Epoch(val) [15][200/509] eta: 0:01:30 time: 0.2955 data_time: 0.0021 memory: 906 2023/05/13 03:08:59 - mmengine - INFO - Epoch(val) [15][250/509] eta: 0:01:17 time: 0.3105 data_time: 0.0021 memory: 931 2023/05/13 03:09:12 - mmengine - INFO - Epoch(val) [15][300/509] eta: 0:01:00 time: 0.2614 data_time: 0.0021 memory: 868 2023/05/13 03:09:26 - mmengine - INFO - Epoch(val) [15][350/509] eta: 0:00:45 time: 0.2751 data_time: 0.0021 memory: 893 2023/05/13 03:09:41 - mmengine - INFO - Epoch(val) [15][400/509] eta: 0:00:31 time: 0.2936 data_time: 0.0021 memory: 901 2023/05/13 03:09:55 - mmengine - INFO - Epoch(val) [15][450/509] eta: 0:00:17 time: 0.2861 data_time: 0.0020 memory: 915 2023/05/13 03:10:09 - mmengine - INFO - Epoch(val) [15][500/509] eta: 0:00:02 time: 0.2826 data_time: 0.0021 memory: 898 2023/05/13 03:10:29 - 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 | 0.9506 | 0.3887 | 0.7613 | 0.4970 | 0.4490 | 0.7647 | 0.8694 | 0.0974 | 0.9462 | 0.5101 | 0.8280 | 0.0801 | 0.9191 | 0.6726 | 0.8935 | 0.7000 | 0.7751 | 0.6359 | 0.5046 | 0.6444 | 0.9278 | 0.7315 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 03:10:29 - mmengine - INFO - Epoch(val) [15][509/509] car: 0.9506 bicycle: 0.3887 motorcycle: 0.7613 truck: 0.4970 bus: 0.4490 person: 0.7647 bicyclist: 0.8694 motorcyclist: 0.0974 road: 0.9462 parking: 0.5101 sidewalk: 0.8280 other-ground: 0.0801 building: 0.9191 fence: 0.6726 vegetation: 0.8935 trunck: 0.7000 terrian: 0.7751 pole: 0.6359 traffic-sign: 0.5046 miou: 0.6444 acc: 0.9278 acc_cls: 0.7315 data_time: 0.0021 time: 0.2969 2023/05/13 03:10:56 - mmengine - INFO - Epoch(train) [16][ 50/1196] lr: 8.0000e-03 eta: 3:59:48 time: 0.5408 data_time: 0.0047 memory: 2909 grad_norm: 0.1045 loss: 0.2233 loss_sem_seg: 0.2233 2023/05/13 03:11:01 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:11:23 - mmengine - INFO - Epoch(train) [16][ 100/1196] lr: 8.0000e-03 eta: 3:59:18 time: 0.5453 data_time: 0.0034 memory: 2836 grad_norm: 0.0987 loss: 0.2380 loss_sem_seg: 0.2380 2023/05/13 03:11:50 - mmengine - INFO - Epoch(train) [16][ 150/1196] lr: 8.0000e-03 eta: 3:58:47 time: 0.5430 data_time: 0.0034 memory: 2903 grad_norm: 0.0941 loss: 0.2256 loss_sem_seg: 0.2256 2023/05/13 03:12:17 - mmengine - INFO - Epoch(train) [16][ 200/1196] lr: 8.0000e-03 eta: 3:58:16 time: 0.5374 data_time: 0.0035 memory: 2774 grad_norm: 0.1061 loss: 0.2155 loss_sem_seg: 0.2155 2023/05/13 03:12:43 - mmengine - INFO - Epoch(train) [16][ 250/1196] lr: 8.0000e-03 eta: 3:57:44 time: 0.5287 data_time: 0.0033 memory: 2640 grad_norm: 0.0967 loss: 0.2322 loss_sem_seg: 0.2322 2023/05/13 03:13:12 - mmengine - INFO - Epoch(train) [16][ 300/1196] lr: 8.0000e-03 eta: 3:57:15 time: 0.5799 data_time: 0.0034 memory: 2973 grad_norm: 0.0942 loss: 0.2227 loss_sem_seg: 0.2227 2023/05/13 03:13:44 - mmengine - INFO - Epoch(train) [16][ 350/1196] lr: 8.0000e-03 eta: 3:56:50 time: 0.6272 data_time: 0.0034 memory: 2780 grad_norm: 0.1044 loss: 0.2214 loss_sem_seg: 0.2214 2023/05/13 03:14:14 - mmengine - INFO - Epoch(train) [16][ 400/1196] lr: 8.0000e-03 eta: 3:56:24 time: 0.6138 data_time: 0.0035 memory: 2893 grad_norm: 0.1246 loss: 0.2264 loss_sem_seg: 0.2264 2023/05/13 03:14:46 - mmengine - INFO - Epoch(train) [16][ 450/1196] lr: 8.0000e-03 eta: 3:56:00 time: 0.6314 data_time: 0.0035 memory: 2921 grad_norm: 0.1056 loss: 0.2207 loss_sem_seg: 0.2207 2023/05/13 03:15:17 - mmengine - INFO - Epoch(train) [16][ 500/1196] lr: 8.0000e-03 eta: 3:55:34 time: 0.6172 data_time: 0.0036 memory: 2724 grad_norm: 0.1263 loss: 0.2346 loss_sem_seg: 0.2346 2023/05/13 03:15:47 - mmengine - INFO - Epoch(train) [16][ 550/1196] lr: 8.0000e-03 eta: 3:55:07 time: 0.6049 data_time: 0.0034 memory: 2855 grad_norm: 0.1122 loss: 0.2284 loss_sem_seg: 0.2284 2023/05/13 03:16:17 - mmengine - INFO - Epoch(train) [16][ 600/1196] lr: 8.0000e-03 eta: 3:54:40 time: 0.6047 data_time: 0.0035 memory: 2902 grad_norm: 0.0984 loss: 0.2207 loss_sem_seg: 0.2207 2023/05/13 03:16:47 - mmengine - INFO - Epoch(train) [16][ 650/1196] lr: 8.0000e-03 eta: 3:54:13 time: 0.5904 data_time: 0.0037 memory: 2909 grad_norm: 0.0989 loss: 0.2118 loss_sem_seg: 0.2118 2023/05/13 03:17:17 - mmengine - INFO - Epoch(train) [16][ 700/1196] lr: 8.0000e-03 eta: 3:53:46 time: 0.6019 data_time: 0.0035 memory: 2732 grad_norm: 0.1159 loss: 0.2239 loss_sem_seg: 0.2239 2023/05/13 03:17:48 - mmengine - INFO - Epoch(train) [16][ 750/1196] lr: 8.0000e-03 eta: 3:53:20 time: 0.6121 data_time: 0.0036 memory: 2700 grad_norm: 0.1118 loss: 0.2177 loss_sem_seg: 0.2177 2023/05/13 03:18:18 - mmengine - INFO - Epoch(train) [16][ 800/1196] lr: 8.0000e-03 eta: 3:52:53 time: 0.6145 data_time: 0.0033 memory: 2756 grad_norm: 0.1099 loss: 0.2502 loss_sem_seg: 0.2502 2023/05/13 03:18:49 - mmengine - INFO - Epoch(train) [16][ 850/1196] lr: 8.0000e-03 eta: 3:52:27 time: 0.6126 data_time: 0.0033 memory: 2768 grad_norm: 0.1020 loss: 0.2103 loss_sem_seg: 0.2103 2023/05/13 03:19:19 - mmengine - INFO - Epoch(train) [16][ 900/1196] lr: 8.0000e-03 eta: 3:52:01 time: 0.6108 data_time: 0.0034 memory: 2963 grad_norm: 0.1076 loss: 0.2114 loss_sem_seg: 0.2114 2023/05/13 03:19:49 - mmengine - INFO - Epoch(train) [16][ 950/1196] lr: 8.0000e-03 eta: 3:51:33 time: 0.5930 data_time: 0.0034 memory: 2718 grad_norm: 0.1043 loss: 0.2416 loss_sem_seg: 0.2416 2023/05/13 03:20:20 - mmengine - INFO - Epoch(train) [16][1000/1196] lr: 8.0000e-03 eta: 3:51:07 time: 0.6180 data_time: 0.0035 memory: 2855 grad_norm: 0.1043 loss: 0.2194 loss_sem_seg: 0.2194 2023/05/13 03:20:51 - mmengine - INFO - Epoch(train) [16][1050/1196] lr: 8.0000e-03 eta: 3:50:41 time: 0.6121 data_time: 0.0035 memory: 2684 grad_norm: 0.1081 loss: 0.2215 loss_sem_seg: 0.2215 2023/05/13 03:20:57 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:21:21 - mmengine - INFO - Epoch(train) [16][1100/1196] lr: 8.0000e-03 eta: 3:50:14 time: 0.6111 data_time: 0.0033 memory: 2834 grad_norm: 0.1075 loss: 0.2195 loss_sem_seg: 0.2195 2023/05/13 03:21:51 - mmengine - INFO - Epoch(train) [16][1150/1196] lr: 8.0000e-03 eta: 3:49:47 time: 0.6061 data_time: 0.0035 memory: 3030 grad_norm: 0.1019 loss: 0.2097 loss_sem_seg: 0.2097 2023/05/13 03:22:20 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:22:20 - mmengine - INFO - Saving checkpoint at 16 epochs 2023/05/13 03:22:45 - mmengine - INFO - Epoch(val) [16][ 50/509] eta: 0:02:50 time: 0.3719 data_time: 0.0021 memory: 2782 2023/05/13 03:23:02 - mmengine - INFO - Epoch(val) [16][100/509] eta: 0:02:28 time: 0.3540 data_time: 0.0022 memory: 920 2023/05/13 03:23:19 - mmengine - INFO - Epoch(val) [16][150/509] eta: 0:02:06 time: 0.3308 data_time: 0.0022 memory: 918 2023/05/13 03:23:36 - mmengine - INFO - Epoch(val) [16][200/509] eta: 0:01:48 time: 0.3425 data_time: 0.0022 memory: 906 2023/05/13 03:23:54 - mmengine - INFO - Epoch(val) [16][250/509] eta: 0:01:30 time: 0.3539 data_time: 0.0020 memory: 931 2023/05/13 03:24:08 - mmengine - INFO - Epoch(val) [16][300/509] eta: 0:01:11 time: 0.2983 data_time: 0.0021 memory: 868 2023/05/13 03:24:24 - mmengine - INFO - Epoch(val) [16][350/509] eta: 0:00:53 time: 0.3151 data_time: 0.0021 memory: 893 2023/05/13 03:24:41 - mmengine - INFO - Epoch(val) [16][400/509] eta: 0:00:36 time: 0.3410 data_time: 0.0021 memory: 901 2023/05/13 03:24:59 - mmengine - INFO - Epoch(val) [16][450/509] eta: 0:00:20 time: 0.3442 data_time: 0.0020 memory: 915 2023/05/13 03:25:15 - mmengine - INFO - Epoch(val) [16][500/509] eta: 0:00:03 time: 0.3299 data_time: 0.0021 memory: 898 2023/05/13 03:25:35 - 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 | 0.9514 | 0.5035 | 0.6389 | 0.5905 | 0.4606 | 0.6921 | 0.8815 | 0.0273 | 0.9368 | 0.4799 | 0.8118 | 0.0160 | 0.9133 | 0.6351 | 0.8909 | 0.6463 | 0.7760 | 0.6467 | 0.5068 | 0.6319 | 0.9237 | 0.7175 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 03:25:35 - mmengine - INFO - Epoch(val) [16][509/509] car: 0.9514 bicycle: 0.5035 motorcycle: 0.6389 truck: 0.5905 bus: 0.4606 person: 0.6921 bicyclist: 0.8815 motorcyclist: 0.0273 road: 0.9368 parking: 0.4799 sidewalk: 0.8118 other-ground: 0.0160 building: 0.9133 fence: 0.6351 vegetation: 0.8909 trunck: 0.6463 terrian: 0.7760 pole: 0.6467 traffic-sign: 0.5068 miou: 0.6319 acc: 0.9237 acc_cls: 0.7175 data_time: 0.0020 time: 0.3336 2023/05/13 03:26:05 - mmengine - INFO - Epoch(train) [17][ 50/1196] lr: 8.0000e-03 eta: 3:48:56 time: 0.5995 data_time: 0.0040 memory: 2761 grad_norm: 0.0935 loss: 0.2172 loss_sem_seg: 0.2172 2023/05/13 03:26:34 - mmengine - INFO - Epoch(train) [17][ 100/1196] lr: 8.0000e-03 eta: 3:48:27 time: 0.5836 data_time: 0.0035 memory: 2770 grad_norm: 0.1129 loss: 0.2289 loss_sem_seg: 0.2289 2023/05/13 03:27:04 - mmengine - INFO - Epoch(train) [17][ 150/1196] lr: 8.0000e-03 eta: 3:48:00 time: 0.5914 data_time: 0.0034 memory: 2708 grad_norm: 0.0967 loss: 0.2255 loss_sem_seg: 0.2255 2023/05/13 03:27:34 - mmengine - INFO - Epoch(train) [17][ 200/1196] lr: 8.0000e-03 eta: 3:47:33 time: 0.6177 data_time: 0.0033 memory: 3189 grad_norm: 0.1123 loss: 0.2372 loss_sem_seg: 0.2372 2023/05/13 03:28:04 - mmengine - INFO - Epoch(train) [17][ 250/1196] lr: 8.0000e-03 eta: 3:47:06 time: 0.5983 data_time: 0.0034 memory: 2780 grad_norm: inf loss: 0.2443 loss_sem_seg: 0.2443 2023/05/13 03:28:35 - mmengine - INFO - Epoch(train) [17][ 300/1196] lr: 8.0000e-03 eta: 3:46:39 time: 0.6111 data_time: 0.0033 memory: 2760 grad_norm: 0.1137 loss: 0.2307 loss_sem_seg: 0.2307 2023/05/13 03:29:06 - mmengine - INFO - Epoch(train) [17][ 350/1196] lr: 8.0000e-03 eta: 3:46:13 time: 0.6169 data_time: 0.0036 memory: 2805 grad_norm: 0.1067 loss: 0.2445 loss_sem_seg: 0.2445 2023/05/13 03:29:35 - mmengine - INFO - Epoch(train) [17][ 400/1196] lr: 8.0000e-03 eta: 3:45:45 time: 0.5887 data_time: 0.0034 memory: 2794 grad_norm: 0.1057 loss: 0.2458 loss_sem_seg: 0.2458 2023/05/13 03:30:06 - mmengine - INFO - Epoch(train) [17][ 450/1196] lr: 8.0000e-03 eta: 3:45:18 time: 0.6092 data_time: 0.0034 memory: 2689 grad_norm: 0.0982 loss: 0.2213 loss_sem_seg: 0.2213 2023/05/13 03:30:36 - mmengine - INFO - Epoch(train) [17][ 500/1196] lr: 8.0000e-03 eta: 3:44:51 time: 0.6075 data_time: 0.0033 memory: 2830 grad_norm: 0.1167 loss: 0.2114 loss_sem_seg: 0.2114 2023/05/13 03:31:06 - mmengine - INFO - Epoch(train) [17][ 550/1196] lr: 8.0000e-03 eta: 3:44:24 time: 0.5962 data_time: 0.0034 memory: 2785 grad_norm: 0.1009 loss: 0.2336 loss_sem_seg: 0.2336 2023/05/13 03:31:34 - mmengine - INFO - Epoch(train) [17][ 600/1196] lr: 8.0000e-03 eta: 3:43:54 time: 0.5691 data_time: 0.0036 memory: 3052 grad_norm: 0.1015 loss: 0.2207 loss_sem_seg: 0.2207 2023/05/13 03:32:02 - mmengine - INFO - Epoch(train) [17][ 650/1196] lr: 8.0000e-03 eta: 3:43:24 time: 0.5432 data_time: 0.0035 memory: 2695 grad_norm: inf loss: 0.2262 loss_sem_seg: 0.2262 2023/05/13 03:32:29 - mmengine - INFO - Epoch(train) [17][ 700/1196] lr: 8.0000e-03 eta: 3:42:54 time: 0.5561 data_time: 0.0034 memory: 2754 grad_norm: 0.1097 loss: 0.2314 loss_sem_seg: 0.2314 2023/05/13 03:32:57 - mmengine - INFO - Epoch(train) [17][ 750/1196] lr: 8.0000e-03 eta: 3:42:23 time: 0.5500 data_time: 0.0033 memory: 2622 grad_norm: 0.1083 loss: 0.2327 loss_sem_seg: 0.2327 2023/05/13 03:33:24 - mmengine - INFO - Epoch(train) [17][ 800/1196] lr: 8.0000e-03 eta: 3:41:53 time: 0.5477 data_time: 0.0035 memory: 2899 grad_norm: 0.1078 loss: 0.2276 loss_sem_seg: 0.2276 2023/05/13 03:33:53 - mmengine - INFO - Epoch(train) [17][ 850/1196] lr: 8.0000e-03 eta: 3:41:25 time: 0.5847 data_time: 0.0035 memory: 2792 grad_norm: 0.1108 loss: 0.2191 loss_sem_seg: 0.2191 2023/05/13 03:34:02 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:34:24 - mmengine - INFO - Epoch(train) [17][ 900/1196] lr: 8.0000e-03 eta: 3:40:58 time: 0.6126 data_time: 0.0033 memory: 2696 grad_norm: 0.0961 loss: 0.2335 loss_sem_seg: 0.2335 2023/05/13 03:34:55 - mmengine - INFO - Epoch(train) [17][ 950/1196] lr: 8.0000e-03 eta: 3:40:31 time: 0.6085 data_time: 0.0034 memory: 2836 grad_norm: 0.1048 loss: 0.2204 loss_sem_seg: 0.2204 2023/05/13 03:35:25 - mmengine - INFO - Epoch(train) [17][1000/1196] lr: 8.0000e-03 eta: 3:40:05 time: 0.6156 data_time: 0.0038 memory: 2876 grad_norm: 0.1196 loss: 0.2236 loss_sem_seg: 0.2236 2023/05/13 03:35:54 - mmengine - INFO - Epoch(train) [17][1050/1196] lr: 8.0000e-03 eta: 3:39:36 time: 0.5751 data_time: 0.0033 memory: 2827 grad_norm: 0.0906 loss: 0.2178 loss_sem_seg: 0.2178 2023/05/13 03:36:22 - mmengine - INFO - Epoch(train) [17][1100/1196] lr: 8.0000e-03 eta: 3:39:06 time: 0.5664 data_time: 0.0033 memory: 2728 grad_norm: 0.0971 loss: 0.2196 loss_sem_seg: 0.2196 2023/05/13 03:36:48 - mmengine - INFO - Epoch(train) [17][1150/1196] lr: 8.0000e-03 eta: 3:38:34 time: 0.5157 data_time: 0.0033 memory: 2918 grad_norm: 0.1077 loss: 0.2308 loss_sem_seg: 0.2308 2023/05/13 03:37:11 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:37:11 - mmengine - INFO - Saving checkpoint at 17 epochs 2023/05/13 03:37:33 - mmengine - INFO - Epoch(val) [17][ 50/509] eta: 0:02:22 time: 0.3100 data_time: 0.0021 memory: 2750 2023/05/13 03:37:47 - mmengine - INFO - Epoch(val) [17][100/509] eta: 0:01:58 time: 0.2709 data_time: 0.0021 memory: 920 2023/05/13 03:38:00 - mmengine - INFO - Epoch(val) [17][150/509] eta: 0:01:40 time: 0.2629 data_time: 0.0020 memory: 918 2023/05/13 03:38:13 - mmengine - INFO - Epoch(val) [17][200/509] eta: 0:01:26 time: 0.2698 data_time: 0.0021 memory: 906 2023/05/13 03:38:28 - mmengine - INFO - Epoch(val) [17][250/509] eta: 0:01:13 time: 0.2958 data_time: 0.0021 memory: 931 2023/05/13 03:38:41 - mmengine - INFO - Epoch(val) [17][300/509] eta: 0:00:57 time: 0.2482 data_time: 0.0020 memory: 868 2023/05/13 03:38:53 - mmengine - INFO - Epoch(val) [17][350/509] eta: 0:00:43 time: 0.2585 data_time: 0.0021 memory: 893 2023/05/13 03:39:07 - mmengine - INFO - Epoch(val) [17][400/509] eta: 0:00:29 time: 0.2748 data_time: 0.0020 memory: 901 2023/05/13 03:39:21 - mmengine - INFO - Epoch(val) [17][450/509] eta: 0:00:16 time: 0.2701 data_time: 0.0020 memory: 915 2023/05/13 03:39:34 - mmengine - INFO - Epoch(val) [17][500/509] eta: 0:00:02 time: 0.2565 data_time: 0.0020 memory: 898 2023/05/13 03:39:52 - 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 | 0.9682 | 0.4412 | 0.7455 | 0.6945 | 0.7037 | 0.7268 | 0.8728 | 0.0112 | 0.9398 | 0.5387 | 0.8177 | 0.0280 | 0.9031 | 0.5782 | 0.8873 | 0.6236 | 0.7689 | 0.6514 | 0.5240 | 0.6539 | 0.9231 | 0.7269 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 03:39:52 - mmengine - INFO - Epoch(val) [17][509/509] car: 0.9682 bicycle: 0.4412 motorcycle: 0.7455 truck: 0.6945 bus: 0.7037 person: 0.7268 bicyclist: 0.8728 motorcyclist: 0.0112 road: 0.9398 parking: 0.5387 sidewalk: 0.8177 other-ground: 0.0280 building: 0.9031 fence: 0.5782 vegetation: 0.8873 trunck: 0.6236 terrian: 0.7689 pole: 0.6514 traffic-sign: 0.5240 miou: 0.6539 acc: 0.9231 acc_cls: 0.7269 data_time: 0.0020 time: 0.2635 2023/05/13 03:40:16 - mmengine - INFO - Epoch(train) [18][ 50/1196] lr: 8.0000e-03 eta: 3:37:30 time: 0.4933 data_time: 0.0044 memory: 2848 grad_norm: 0.1044 loss: 0.2255 loss_sem_seg: 0.2255 2023/05/13 03:40:41 - mmengine - INFO - Epoch(train) [18][ 100/1196] lr: 8.0000e-03 eta: 3:36:56 time: 0.4821 data_time: 0.0034 memory: 2882 grad_norm: 0.1036 loss: 0.2242 loss_sem_seg: 0.2242 2023/05/13 03:41:05 - mmengine - INFO - Epoch(train) [18][ 150/1196] lr: 8.0000e-03 eta: 3:36:23 time: 0.4923 data_time: 0.0033 memory: 2935 grad_norm: 0.1000 loss: 0.2093 loss_sem_seg: 0.2093 2023/05/13 03:41:30 - mmengine - INFO - Epoch(train) [18][ 200/1196] lr: 8.0000e-03 eta: 3:35:49 time: 0.4929 data_time: 0.0034 memory: 2807 grad_norm: 0.0979 loss: 0.2186 loss_sem_seg: 0.2186 2023/05/13 03:41:54 - mmengine - INFO - Epoch(train) [18][ 250/1196] lr: 8.0000e-03 eta: 3:35:16 time: 0.4913 data_time: 0.0036 memory: 2833 grad_norm: 0.1137 loss: 0.2108 loss_sem_seg: 0.2108 2023/05/13 03:42:19 - mmengine - INFO - Epoch(train) [18][ 300/1196] lr: 8.0000e-03 eta: 3:34:43 time: 0.4945 data_time: 0.0034 memory: 2905 grad_norm: 0.0982 loss: 0.2122 loss_sem_seg: 0.2122 2023/05/13 03:42:47 - mmengine - INFO - Epoch(train) [18][ 350/1196] lr: 8.0000e-03 eta: 3:34:14 time: 0.5626 data_time: 0.0033 memory: 2729 grad_norm: 0.0972 loss: 0.2313 loss_sem_seg: 0.2313 2023/05/13 03:43:14 - mmengine - INFO - Epoch(train) [18][ 400/1196] lr: 8.0000e-03 eta: 3:33:43 time: 0.5364 data_time: 0.0035 memory: 2901 grad_norm: 0.0967 loss: 0.2122 loss_sem_seg: 0.2122 2023/05/13 03:43:41 - mmengine - INFO - Epoch(train) [18][ 450/1196] lr: 8.0000e-03 eta: 3:33:12 time: 0.5379 data_time: 0.0034 memory: 2804 grad_norm: 0.1095 loss: 0.2078 loss_sem_seg: 0.2078 2023/05/13 03:44:08 - mmengine - INFO - Epoch(train) [18][ 500/1196] lr: 8.0000e-03 eta: 3:32:41 time: 0.5364 data_time: 0.0033 memory: 3185 grad_norm: 0.1059 loss: 0.2113 loss_sem_seg: 0.2113 2023/05/13 03:44:35 - mmengine - INFO - Epoch(train) [18][ 550/1196] lr: 8.0000e-03 eta: 3:32:11 time: 0.5491 data_time: 0.0035 memory: 2798 grad_norm: 0.0959 loss: 0.2206 loss_sem_seg: 0.2206 2023/05/13 03:45:07 - mmengine - INFO - Epoch(train) [18][ 600/1196] lr: 8.0000e-03 eta: 3:31:46 time: 0.6367 data_time: 0.0033 memory: 2969 grad_norm: 0.0961 loss: 0.2206 loss_sem_seg: 0.2206 2023/05/13 03:45:38 - mmengine - INFO - Epoch(train) [18][ 650/1196] lr: 8.0000e-03 eta: 3:31:19 time: 0.6152 data_time: 0.0033 memory: 2865 grad_norm: 0.1015 loss: 0.2200 loss_sem_seg: 0.2200 2023/05/13 03:45:48 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:46:09 - mmengine - INFO - Epoch(train) [18][ 700/1196] lr: 8.0000e-03 eta: 3:30:53 time: 0.6138 data_time: 0.0034 memory: 2794 grad_norm: 0.1087 loss: 0.2468 loss_sem_seg: 0.2468 2023/05/13 03:46:39 - mmengine - INFO - Epoch(train) [18][ 750/1196] lr: 8.0000e-03 eta: 3:30:26 time: 0.6177 data_time: 0.0035 memory: 2875 grad_norm: 0.1013 loss: 0.2092 loss_sem_seg: 0.2092 2023/05/13 03:47:10 - mmengine - INFO - Epoch(train) [18][ 800/1196] lr: 8.0000e-03 eta: 3:29:59 time: 0.6012 data_time: 0.0033 memory: 2762 grad_norm: 0.0981 loss: 0.2178 loss_sem_seg: 0.2178 2023/05/13 03:47:40 - mmengine - INFO - Epoch(train) [18][ 850/1196] lr: 8.0000e-03 eta: 3:29:32 time: 0.6133 data_time: 0.0033 memory: 2843 grad_norm: 0.1083 loss: 0.2229 loss_sem_seg: 0.2229 2023/05/13 03:48:10 - mmengine - INFO - Epoch(train) [18][ 900/1196] lr: 8.0000e-03 eta: 3:29:05 time: 0.6018 data_time: 0.0034 memory: 2682 grad_norm: 0.1048 loss: 0.2228 loss_sem_seg: 0.2228 2023/05/13 03:48:41 - mmengine - INFO - Epoch(train) [18][ 950/1196] lr: 8.0000e-03 eta: 3:28:38 time: 0.6071 data_time: 0.0034 memory: 2862 grad_norm: 0.0969 loss: 0.2167 loss_sem_seg: 0.2167 2023/05/13 03:49:10 - mmengine - INFO - Epoch(train) [18][1000/1196] lr: 8.0000e-03 eta: 3:28:10 time: 0.5913 data_time: 0.0034 memory: 2921 grad_norm: 0.0964 loss: 0.2254 loss_sem_seg: 0.2254 2023/05/13 03:49:39 - mmengine - INFO - Epoch(train) [18][1050/1196] lr: 8.0000e-03 eta: 3:27:41 time: 0.5825 data_time: 0.0035 memory: 2826 grad_norm: 0.1160 loss: 0.2216 loss_sem_seg: 0.2216 2023/05/13 03:50:09 - mmengine - INFO - Epoch(train) [18][1100/1196] lr: 8.0000e-03 eta: 3:27:14 time: 0.5935 data_time: 0.0034 memory: 2733 grad_norm: 0.1077 loss: 0.2302 loss_sem_seg: 0.2302 2023/05/13 03:50:39 - mmengine - INFO - Epoch(train) [18][1150/1196] lr: 8.0000e-03 eta: 3:26:46 time: 0.6061 data_time: 0.0033 memory: 2864 grad_norm: 0.0958 loss: 0.2114 loss_sem_seg: 0.2114 2023/05/13 03:51:07 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:51:07 - mmengine - INFO - Saving checkpoint at 18 epochs 2023/05/13 03:51:33 - mmengine - INFO - Epoch(val) [18][ 50/509] eta: 0:02:55 time: 0.3824 data_time: 0.0021 memory: 2921 2023/05/13 03:51:49 - mmengine - INFO - Epoch(val) [18][100/509] eta: 0:02:24 time: 0.3220 data_time: 0.0021 memory: 920 2023/05/13 03:52:06 - mmengine - INFO - Epoch(val) [18][150/509] eta: 0:02:03 time: 0.3316 data_time: 0.0021 memory: 918 2023/05/13 03:52:22 - mmengine - INFO - Epoch(val) [18][200/509] eta: 0:01:45 time: 0.3277 data_time: 0.0021 memory: 906 2023/05/13 03:52:40 - mmengine - INFO - Epoch(val) [18][250/509] eta: 0:01:29 time: 0.3613 data_time: 0.0021 memory: 931 2023/05/13 03:52:55 - mmengine - INFO - Epoch(val) [18][300/509] eta: 0:01:10 time: 0.2901 data_time: 0.0021 memory: 868 2023/05/13 03:53:09 - mmengine - INFO - Epoch(val) [18][350/509] eta: 0:00:52 time: 0.2982 data_time: 0.0021 memory: 893 2023/05/13 03:53:26 - mmengine - INFO - Epoch(val) [18][400/509] eta: 0:00:36 time: 0.3344 data_time: 0.0021 memory: 901 2023/05/13 03:53:43 - mmengine - INFO - Epoch(val) [18][450/509] eta: 0:00:19 time: 0.3409 data_time: 0.0021 memory: 915 2023/05/13 03:53:59 - mmengine - INFO - Epoch(val) [18][500/509] eta: 0:00:02 time: 0.3107 data_time: 0.0021 memory: 898 2023/05/13 03:54:18 - 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 | 0.9646 | 0.5285 | 0.7024 | 0.6929 | 0.6806 | 0.6692 | 0.8296 | 0.0194 | 0.9395 | 0.4708 | 0.8156 | 0.0229 | 0.9060 | 0.6269 | 0.8748 | 0.7008 | 0.7219 | 0.6505 | 0.4949 | 0.6480 | 0.9181 | 0.7177 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 03:54:18 - mmengine - INFO - Epoch(val) [18][509/509] car: 0.9646 bicycle: 0.5285 motorcycle: 0.7024 truck: 0.6929 bus: 0.6806 person: 0.6692 bicyclist: 0.8296 motorcyclist: 0.0194 road: 0.9395 parking: 0.4708 sidewalk: 0.8156 other-ground: 0.0229 building: 0.9060 fence: 0.6269 vegetation: 0.8748 trunck: 0.7008 terrian: 0.7219 pole: 0.6505 traffic-sign: 0.4949 miou: 0.6480 acc: 0.9181 acc_cls: 0.7177 data_time: 0.0021 time: 0.3298 2023/05/13 03:54:49 - mmengine - INFO - Epoch(train) [19][ 50/1196] lr: 8.0000e-03 eta: 3:25:55 time: 0.6129 data_time: 0.0039 memory: 2622 grad_norm: 0.1118 loss: 0.2221 loss_sem_seg: 0.2221 2023/05/13 03:55:19 - mmengine - INFO - Epoch(train) [19][ 100/1196] lr: 8.0000e-03 eta: 3:25:27 time: 0.5989 data_time: 0.0034 memory: 2811 grad_norm: 0.1182 loss: 0.2315 loss_sem_seg: 0.2315 2023/05/13 03:55:48 - mmengine - INFO - Epoch(train) [19][ 150/1196] lr: 8.0000e-03 eta: 3:24:58 time: 0.5789 data_time: 0.0035 memory: 2832 grad_norm: 0.1052 loss: 0.2174 loss_sem_seg: 0.2174 2023/05/13 03:56:18 - mmengine - INFO - Epoch(train) [19][ 200/1196] lr: 8.0000e-03 eta: 3:24:31 time: 0.6087 data_time: 0.0034 memory: 2673 grad_norm: 0.0952 loss: 0.2029 loss_sem_seg: 0.2029 2023/05/13 03:56:48 - mmengine - INFO - Epoch(train) [19][ 250/1196] lr: 8.0000e-03 eta: 3:24:04 time: 0.6044 data_time: 0.0036 memory: 2880 grad_norm: 0.0971 loss: 0.2148 loss_sem_seg: 0.2148 2023/05/13 03:57:19 - mmengine - INFO - Epoch(train) [19][ 300/1196] lr: 8.0000e-03 eta: 3:23:37 time: 0.6160 data_time: 0.0034 memory: 2777 grad_norm: 0.1071 loss: 0.2212 loss_sem_seg: 0.2212 2023/05/13 03:57:49 - mmengine - INFO - Epoch(train) [19][ 350/1196] lr: 8.0000e-03 eta: 3:23:10 time: 0.6050 data_time: 0.0035 memory: 2986 grad_norm: 0.1064 loss: 0.2158 loss_sem_seg: 0.2158 2023/05/13 03:58:20 - mmengine - INFO - Epoch(train) [19][ 400/1196] lr: 8.0000e-03 eta: 3:22:43 time: 0.6153 data_time: 0.0034 memory: 2759 grad_norm: 0.1020 loss: 0.2201 loss_sem_seg: 0.2201 2023/05/13 03:58:51 - mmengine - INFO - Epoch(train) [19][ 450/1196] lr: 8.0000e-03 eta: 3:22:16 time: 0.6154 data_time: 0.0035 memory: 2840 grad_norm: 0.0890 loss: 0.2011 loss_sem_seg: 0.2011 2023/05/13 03:59:05 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 03:59:21 - mmengine - INFO - Epoch(train) [19][ 500/1196] lr: 8.0000e-03 eta: 3:21:48 time: 0.5947 data_time: 0.0033 memory: 2811 grad_norm: 0.1005 loss: 0.2246 loss_sem_seg: 0.2246 2023/05/13 03:59:48 - mmengine - INFO - Epoch(train) [19][ 550/1196] lr: 8.0000e-03 eta: 3:21:18 time: 0.5434 data_time: 0.0033 memory: 2868 grad_norm: 0.1087 loss: 0.2268 loss_sem_seg: 0.2268 2023/05/13 04:00:15 - mmengine - INFO - Epoch(train) [19][ 600/1196] lr: 8.0000e-03 eta: 3:20:48 time: 0.5454 data_time: 0.0035 memory: 2708 grad_norm: 0.1243 loss: 0.2430 loss_sem_seg: 0.2430 2023/05/13 04:00:42 - mmengine - INFO - Epoch(train) [19][ 650/1196] lr: 8.0000e-03 eta: 3:20:17 time: 0.5342 data_time: 0.0035 memory: 2914 grad_norm: 0.1044 loss: 0.2140 loss_sem_seg: 0.2140 2023/05/13 04:01:07 - mmengine - INFO - Epoch(train) [19][ 700/1196] lr: 8.0000e-03 eta: 3:19:45 time: 0.5115 data_time: 0.0033 memory: 2944 grad_norm: 0.1029 loss: 0.2157 loss_sem_seg: 0.2157 2023/05/13 04:01:34 - mmengine - INFO - Epoch(train) [19][ 750/1196] lr: 8.0000e-03 eta: 3:19:15 time: 0.5430 data_time: 0.0034 memory: 2728 grad_norm: 0.1089 loss: 0.2231 loss_sem_seg: 0.2231 2023/05/13 04:02:01 - mmengine - INFO - Epoch(train) [19][ 800/1196] lr: 8.0000e-03 eta: 3:18:44 time: 0.5361 data_time: 0.0033 memory: 2670 grad_norm: 0.0995 loss: 0.2168 loss_sem_seg: 0.2168 2023/05/13 04:02:28 - mmengine - INFO - Epoch(train) [19][ 850/1196] lr: 8.0000e-03 eta: 3:18:14 time: 0.5433 data_time: 0.0034 memory: 2769 grad_norm: 0.1006 loss: 0.2192 loss_sem_seg: 0.2192 2023/05/13 04:02:55 - mmengine - INFO - Epoch(train) [19][ 900/1196] lr: 8.0000e-03 eta: 3:17:43 time: 0.5353 data_time: 0.0035 memory: 2768 grad_norm: 0.0967 loss: 0.2142 loss_sem_seg: 0.2142 2023/05/13 04:03:22 - mmengine - INFO - Epoch(train) [19][ 950/1196] lr: 8.0000e-03 eta: 3:17:13 time: 0.5433 data_time: 0.0034 memory: 2880 grad_norm: 0.0989 loss: 0.1932 loss_sem_seg: 0.1932 2023/05/13 04:03:49 - mmengine - INFO - Epoch(train) [19][1000/1196] lr: 8.0000e-03 eta: 3:16:42 time: 0.5290 data_time: 0.0034 memory: 2863 grad_norm: 0.0989 loss: 0.2101 loss_sem_seg: 0.2101 2023/05/13 04:04:16 - mmengine - INFO - Epoch(train) [19][1050/1196] lr: 8.0000e-03 eta: 3:16:12 time: 0.5392 data_time: 0.0033 memory: 2673 grad_norm: 0.0951 loss: 0.2048 loss_sem_seg: 0.2048 2023/05/13 04:04:43 - mmengine - INFO - Epoch(train) [19][1100/1196] lr: 8.0000e-03 eta: 3:15:42 time: 0.5450 data_time: 0.0034 memory: 2847 grad_norm: 0.0921 loss: 0.1995 loss_sem_seg: 0.1995 2023/05/13 04:05:11 - mmengine - INFO - Epoch(train) [19][1150/1196] lr: 8.0000e-03 eta: 3:15:12 time: 0.5522 data_time: 0.0034 memory: 3020 grad_norm: 0.0983 loss: 0.2279 loss_sem_seg: 0.2279 2023/05/13 04:05:36 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:05:36 - mmengine - INFO - Saving checkpoint at 19 epochs 2023/05/13 04:05:59 - mmengine - INFO - Epoch(val) [19][ 50/509] eta: 0:02:32 time: 0.3314 data_time: 0.0022 memory: 3175 2023/05/13 04:06:13 - mmengine - INFO - Epoch(val) [19][100/509] eta: 0:02:06 time: 0.2875 data_time: 0.0021 memory: 920 2023/05/13 04:06:27 - mmengine - INFO - Epoch(val) [19][150/509] eta: 0:01:46 time: 0.2741 data_time: 0.0020 memory: 918 2023/05/13 04:06:41 - mmengine - INFO - Epoch(val) [19][200/509] eta: 0:01:30 time: 0.2841 data_time: 0.0021 memory: 906 2023/05/13 04:06:59 - mmengine - INFO - Epoch(val) [19][250/509] eta: 0:01:19 time: 0.3551 data_time: 0.0021 memory: 931 2023/05/13 04:07:12 - mmengine - INFO - Epoch(val) [19][300/509] eta: 0:01:02 time: 0.2733 data_time: 0.0021 memory: 868 2023/05/13 04:07:29 - mmengine - INFO - Epoch(val) [19][350/509] eta: 0:00:48 time: 0.3340 data_time: 0.0021 memory: 893 2023/05/13 04:07:47 - mmengine - INFO - Epoch(val) [19][400/509] eta: 0:00:34 time: 0.3560 data_time: 0.0021 memory: 901 2023/05/13 04:08:03 - mmengine - INFO - Epoch(val) [19][450/509] eta: 0:00:18 time: 0.3238 data_time: 0.0020 memory: 915 2023/05/13 04:08:18 - mmengine - INFO - Epoch(val) [19][500/509] eta: 0:00:02 time: 0.2963 data_time: 0.0021 memory: 898 2023/05/13 04:08:39 - 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 | 0.9499 | 0.4764 | 0.7746 | 0.7140 | 0.4061 | 0.7397 | 0.8566 | 0.0309 | 0.9382 | 0.4274 | 0.8125 | 0.1014 | 0.9138 | 0.6464 | 0.8816 | 0.6311 | 0.7486 | 0.6448 | 0.5201 | 0.6428 | 0.9200 | 0.7114 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 04:08:39 - mmengine - INFO - Epoch(val) [19][509/509] car: 0.9499 bicycle: 0.4764 motorcycle: 0.7746 truck: 0.7140 bus: 0.4061 person: 0.7397 bicyclist: 0.8566 motorcyclist: 0.0309 road: 0.9382 parking: 0.4274 sidewalk: 0.8125 other-ground: 0.1014 building: 0.9138 fence: 0.6464 vegetation: 0.8816 trunck: 0.6311 terrian: 0.7486 pole: 0.6448 traffic-sign: 0.5201 miou: 0.6428 acc: 0.9200 acc_cls: 0.7114 data_time: 0.0021 time: 0.3133 2023/05/13 04:09:06 - mmengine - INFO - Epoch(train) [20][ 50/1196] lr: 8.0000e-03 eta: 3:14:14 time: 0.5396 data_time: 0.0041 memory: 2796 grad_norm: 0.1188 loss: 0.2246 loss_sem_seg: 0.2246 2023/05/13 04:09:34 - mmengine - INFO - Epoch(train) [20][ 100/1196] lr: 8.0000e-03 eta: 3:13:45 time: 0.5634 data_time: 0.0033 memory: 2964 grad_norm: 0.1032 loss: 0.2369 loss_sem_seg: 0.2369 2023/05/13 04:10:02 - mmengine - INFO - Epoch(train) [20][ 150/1196] lr: 8.0000e-03 eta: 3:13:16 time: 0.5597 data_time: 0.0035 memory: 2894 grad_norm: 0.0966 loss: 0.2110 loss_sem_seg: 0.2110 2023/05/13 04:10:31 - mmengine - INFO - Epoch(train) [20][ 200/1196] lr: 8.0000e-03 eta: 3:12:47 time: 0.5675 data_time: 0.0035 memory: 2829 grad_norm: 0.1062 loss: 0.2213 loss_sem_seg: 0.2213 2023/05/13 04:10:59 - mmengine - INFO - Epoch(train) [20][ 250/1196] lr: 8.0000e-03 eta: 3:12:17 time: 0.5647 data_time: 0.0033 memory: 2711 grad_norm: 0.0917 loss: 0.1950 loss_sem_seg: 0.1950 2023/05/13 04:11:14 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:11:28 - mmengine - INFO - Epoch(train) [20][ 300/1196] lr: 8.0000e-03 eta: 3:11:49 time: 0.5869 data_time: 0.0033 memory: 2663 grad_norm: 0.1010 loss: 0.2001 loss_sem_seg: 0.2001 2023/05/13 04:11:59 - mmengine - INFO - Epoch(train) [20][ 350/1196] lr: 8.0000e-03 eta: 3:11:22 time: 0.6106 data_time: 0.0033 memory: 2625 grad_norm: 0.1069 loss: 0.2197 loss_sem_seg: 0.2197 2023/05/13 04:12:29 - mmengine - INFO - Epoch(train) [20][ 400/1196] lr: 8.0000e-03 eta: 3:10:55 time: 0.6062 data_time: 0.0034 memory: 2745 grad_norm: 0.1002 loss: 0.2166 loss_sem_seg: 0.2166 2023/05/13 04:12:59 - mmengine - INFO - Epoch(train) [20][ 450/1196] lr: 8.0000e-03 eta: 3:10:27 time: 0.6028 data_time: 0.0036 memory: 2911 grad_norm: 0.1126 loss: 0.1958 loss_sem_seg: 0.1958 2023/05/13 04:13:31 - mmengine - INFO - Epoch(train) [20][ 500/1196] lr: 8.0000e-03 eta: 3:10:01 time: 0.6234 data_time: 0.0035 memory: 2796 grad_norm: 0.1005 loss: 0.2122 loss_sem_seg: 0.2122 2023/05/13 04:14:01 - mmengine - INFO - Epoch(train) [20][ 550/1196] lr: 8.0000e-03 eta: 3:09:34 time: 0.6169 data_time: 0.0034 memory: 2826 grad_norm: 0.1071 loss: 0.2278 loss_sem_seg: 0.2278 2023/05/13 04:14:32 - mmengine - INFO - Epoch(train) [20][ 600/1196] lr: 8.0000e-03 eta: 3:09:06 time: 0.6010 data_time: 0.0036 memory: 2731 grad_norm: 0.0980 loss: 0.2117 loss_sem_seg: 0.2117 2023/05/13 04:15:02 - mmengine - INFO - Epoch(train) [20][ 650/1196] lr: 8.0000e-03 eta: 3:08:38 time: 0.6060 data_time: 0.0034 memory: 2755 grad_norm: 0.1001 loss: 0.2095 loss_sem_seg: 0.2095 2023/05/13 04:15:32 - mmengine - INFO - Epoch(train) [20][ 700/1196] lr: 8.0000e-03 eta: 3:08:11 time: 0.6131 data_time: 0.0035 memory: 2827 grad_norm: 0.0957 loss: 0.2082 loss_sem_seg: 0.2082 2023/05/13 04:16:01 - mmengine - INFO - Epoch(train) [20][ 750/1196] lr: 8.0000e-03 eta: 3:07:42 time: 0.5647 data_time: 0.0034 memory: 2966 grad_norm: 0.1107 loss: 0.2162 loss_sem_seg: 0.2162 2023/05/13 04:16:29 - mmengine - INFO - Epoch(train) [20][ 800/1196] lr: 8.0000e-03 eta: 3:07:13 time: 0.5715 data_time: 0.0033 memory: 2834 grad_norm: 0.0939 loss: 0.2164 loss_sem_seg: 0.2164 2023/05/13 04:16:59 - mmengine - INFO - Epoch(train) [20][ 850/1196] lr: 8.0000e-03 eta: 3:06:45 time: 0.5845 data_time: 0.0034 memory: 2829 grad_norm: 0.1095 loss: 0.2255 loss_sem_seg: 0.2255 2023/05/13 04:17:27 - mmengine - INFO - Epoch(train) [20][ 900/1196] lr: 8.0000e-03 eta: 3:06:16 time: 0.5704 data_time: 0.0033 memory: 3141 grad_norm: 0.1014 loss: 0.2094 loss_sem_seg: 0.2094 2023/05/13 04:17:55 - mmengine - INFO - Epoch(train) [20][ 950/1196] lr: 8.0000e-03 eta: 3:05:46 time: 0.5533 data_time: 0.0034 memory: 2855 grad_norm: 0.0979 loss: 0.2229 loss_sem_seg: 0.2229 2023/05/13 04:18:23 - mmengine - INFO - Epoch(train) [20][1000/1196] lr: 8.0000e-03 eta: 3:05:17 time: 0.5646 data_time: 0.0033 memory: 2685 grad_norm: inf loss: 0.2156 loss_sem_seg: 0.2156 2023/05/13 04:18:52 - mmengine - INFO - Epoch(train) [20][1050/1196] lr: 8.0000e-03 eta: 3:04:48 time: 0.5718 data_time: 0.0034 memory: 2881 grad_norm: 0.0997 loss: 0.2154 loss_sem_seg: 0.2154 2023/05/13 04:19:21 - mmengine - INFO - Epoch(train) [20][1100/1196] lr: 8.0000e-03 eta: 3:04:20 time: 0.5855 data_time: 0.0038 memory: 2791 grad_norm: 0.1076 loss: 0.2242 loss_sem_seg: 0.2242 2023/05/13 04:19:49 - mmengine - INFO - Epoch(train) [20][1150/1196] lr: 8.0000e-03 eta: 3:03:51 time: 0.5639 data_time: 0.0034 memory: 2669 grad_norm: 0.0998 loss: 0.2077 loss_sem_seg: 0.2077 2023/05/13 04:20:15 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:20:15 - mmengine - INFO - Saving checkpoint at 20 epochs 2023/05/13 04:20:39 - mmengine - INFO - Epoch(val) [20][ 50/509] eta: 0:02:41 time: 0.3512 data_time: 0.0021 memory: 2658 2023/05/13 04:20:55 - mmengine - INFO - Epoch(val) [20][100/509] eta: 0:02:15 time: 0.3115 data_time: 0.0021 memory: 920 2023/05/13 04:21:10 - mmengine - INFO - Epoch(val) [20][150/509] eta: 0:01:55 time: 0.3025 data_time: 0.0020 memory: 918 2023/05/13 04:21:26 - mmengine - INFO - Epoch(val) [20][200/509] eta: 0:01:39 time: 0.3231 data_time: 0.0020 memory: 906 2023/05/13 04:21:44 - mmengine - INFO - Epoch(val) [20][250/509] eta: 0:01:24 time: 0.3516 data_time: 0.0021 memory: 931 2023/05/13 04:21:58 - mmengine - INFO - Epoch(val) [20][300/509] eta: 0:01:07 time: 0.2869 data_time: 0.0020 memory: 868 2023/05/13 04:22:13 - mmengine - INFO - Epoch(val) [20][350/509] eta: 0:00:50 time: 0.2990 data_time: 0.0021 memory: 893 2023/05/13 04:22:28 - mmengine - INFO - Epoch(val) [20][400/509] eta: 0:00:34 time: 0.3057 data_time: 0.0021 memory: 901 2023/05/13 04:22:43 - mmengine - INFO - Epoch(val) [20][450/509] eta: 0:00:18 time: 0.2972 data_time: 0.0020 memory: 915 2023/05/13 04:22:58 - mmengine - INFO - Epoch(val) [20][500/509] eta: 0:00:02 time: 0.2924 data_time: 0.0020 memory: 898 2023/05/13 04:23:17 - 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 | 0.9520 | 0.4817 | 0.7192 | 0.8347 | 0.5157 | 0.6320 | 0.7832 | 0.0234 | 0.9310 | 0.3815 | 0.8077 | 0.0103 | 0.9140 | 0.6543 | 0.8887 | 0.6916 | 0.7588 | 0.6471 | 0.5217 | 0.6394 | 0.9215 | 0.7006 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 04:23:17 - mmengine - INFO - Epoch(val) [20][509/509] car: 0.9520 bicycle: 0.4817 motorcycle: 0.7192 truck: 0.8347 bus: 0.5157 person: 0.6320 bicyclist: 0.7832 motorcyclist: 0.0234 road: 0.9310 parking: 0.3815 sidewalk: 0.8077 other-ground: 0.0103 building: 0.9140 fence: 0.6543 vegetation: 0.8887 trunck: 0.6916 terrian: 0.7588 pole: 0.6471 traffic-sign: 0.5217 miou: 0.6394 acc: 0.9215 acc_cls: 0.7006 data_time: 0.0020 time: 0.3010 2023/05/13 04:23:48 - mmengine - INFO - Epoch(train) [21][ 50/1196] lr: 8.0000e-03 eta: 3:02:57 time: 0.6218 data_time: 0.0044 memory: 3026 grad_norm: 0.1018 loss: 0.2048 loss_sem_seg: 0.2048 2023/05/13 04:24:06 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:24:19 - mmengine - INFO - Epoch(train) [21][ 100/1196] lr: 8.0000e-03 eta: 3:02:30 time: 0.6182 data_time: 0.0035 memory: 2769 grad_norm: 0.0977 loss: 0.2133 loss_sem_seg: 0.2133 2023/05/13 04:24:49 - mmengine - INFO - Epoch(train) [21][ 150/1196] lr: 8.0000e-03 eta: 3:02:03 time: 0.6102 data_time: 0.0035 memory: 2818 grad_norm: 0.1046 loss: 0.2105 loss_sem_seg: 0.2105 2023/05/13 04:25:20 - mmengine - INFO - Epoch(train) [21][ 200/1196] lr: 8.0000e-03 eta: 3:01:35 time: 0.6081 data_time: 0.0034 memory: 2753 grad_norm: 0.0980 loss: 0.2163 loss_sem_seg: 0.2163 2023/05/13 04:25:50 - mmengine - INFO - Epoch(train) [21][ 250/1196] lr: 8.0000e-03 eta: 3:01:08 time: 0.6047 data_time: 0.0035 memory: 2920 grad_norm: 0.1088 loss: 0.2210 loss_sem_seg: 0.2210 2023/05/13 04:26:19 - mmengine - INFO - Epoch(train) [21][ 300/1196] lr: 8.0000e-03 eta: 3:00:39 time: 0.5870 data_time: 0.0034 memory: 2763 grad_norm: 0.1066 loss: 0.2097 loss_sem_seg: 0.2097 2023/05/13 04:26:50 - mmengine - INFO - Epoch(train) [21][ 350/1196] lr: 8.0000e-03 eta: 3:00:12 time: 0.6100 data_time: 0.0034 memory: 2866 grad_norm: 0.0974 loss: 0.2318 loss_sem_seg: 0.2318 2023/05/13 04:27:21 - mmengine - INFO - Epoch(train) [21][ 400/1196] lr: 8.0000e-03 eta: 2:59:45 time: 0.6240 data_time: 0.0034 memory: 2850 grad_norm: 0.1129 loss: 0.2196 loss_sem_seg: 0.2196 2023/05/13 04:27:51 - mmengine - INFO - Epoch(train) [21][ 450/1196] lr: 8.0000e-03 eta: 2:59:17 time: 0.6063 data_time: 0.0036 memory: 2800 grad_norm: 0.1073 loss: 0.2238 loss_sem_seg: 0.2238 2023/05/13 04:28:22 - mmengine - INFO - Epoch(train) [21][ 500/1196] lr: 8.0000e-03 eta: 2:58:50 time: 0.6137 data_time: 0.0034 memory: 2815 grad_norm: 0.0872 loss: 0.2022 loss_sem_seg: 0.2022 2023/05/13 04:28:53 - mmengine - INFO - Epoch(train) [21][ 550/1196] lr: 8.0000e-03 eta: 2:58:23 time: 0.6187 data_time: 0.0034 memory: 2678 grad_norm: 0.0866 loss: 0.1954 loss_sem_seg: 0.1954 2023/05/13 04:29:23 - mmengine - INFO - Epoch(train) [21][ 600/1196] lr: 8.0000e-03 eta: 2:57:55 time: 0.6091 data_time: 0.0034 memory: 2917 grad_norm: 0.1014 loss: 0.2209 loss_sem_seg: 0.2209 2023/05/13 04:29:53 - mmengine - INFO - Epoch(train) [21][ 650/1196] lr: 8.0000e-03 eta: 2:57:27 time: 0.5932 data_time: 0.0034 memory: 2839 grad_norm: 0.1062 loss: 0.2155 loss_sem_seg: 0.2155 2023/05/13 04:30:24 - mmengine - INFO - Epoch(train) [21][ 700/1196] lr: 8.0000e-03 eta: 2:57:00 time: 0.6104 data_time: 0.0035 memory: 2909 grad_norm: 0.1055 loss: 0.1997 loss_sem_seg: 0.1997 2023/05/13 04:30:54 - mmengine - INFO - Epoch(train) [21][ 750/1196] lr: 8.0000e-03 eta: 2:56:32 time: 0.6108 data_time: 0.0036 memory: 2975 grad_norm: 0.0968 loss: 0.2259 loss_sem_seg: 0.2259 2023/05/13 04:31:24 - mmengine - INFO - Epoch(train) [21][ 800/1196] lr: 8.0000e-03 eta: 2:56:04 time: 0.6048 data_time: 0.0036 memory: 2807 grad_norm: 0.0965 loss: 0.2105 loss_sem_seg: 0.2105 2023/05/13 04:31:55 - mmengine - INFO - Epoch(train) [21][ 850/1196] lr: 8.0000e-03 eta: 2:55:37 time: 0.6222 data_time: 0.0035 memory: 2914 grad_norm: 0.0961 loss: 0.2054 loss_sem_seg: 0.2054 2023/05/13 04:32:26 - mmengine - INFO - Epoch(train) [21][ 900/1196] lr: 8.0000e-03 eta: 2:55:10 time: 0.6092 data_time: 0.0035 memory: 2621 grad_norm: 0.1042 loss: 0.2077 loss_sem_seg: 0.2077 2023/05/13 04:32:56 - mmengine - INFO - Epoch(train) [21][ 950/1196] lr: 8.0000e-03 eta: 2:54:41 time: 0.5955 data_time: 0.0034 memory: 2893 grad_norm: 0.0963 loss: 0.2126 loss_sem_seg: 0.2126 2023/05/13 04:33:27 - mmengine - INFO - Epoch(train) [21][1000/1196] lr: 8.0000e-03 eta: 2:54:14 time: 0.6178 data_time: 0.0034 memory: 2916 grad_norm: 0.0985 loss: 0.2209 loss_sem_seg: 0.2209 2023/05/13 04:33:57 - mmengine - INFO - Epoch(train) [21][1050/1196] lr: 8.0000e-03 eta: 2:53:47 time: 0.6096 data_time: 0.0036 memory: 2717 grad_norm: 0.1078 loss: 0.1980 loss_sem_seg: 0.1980 2023/05/13 04:34:15 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:34:28 - mmengine - INFO - Epoch(train) [21][1100/1196] lr: 8.0000e-03 eta: 2:53:19 time: 0.6161 data_time: 0.0035 memory: 2957 grad_norm: 0.1084 loss: 0.2253 loss_sem_seg: 0.2253 2023/05/13 04:34:56 - mmengine - INFO - Epoch(train) [21][1150/1196] lr: 8.0000e-03 eta: 2:52:50 time: 0.5626 data_time: 0.0034 memory: 2779 grad_norm: 0.1166 loss: 0.2240 loss_sem_seg: 0.2240 2023/05/13 04:35:25 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:35:25 - mmengine - INFO - Saving checkpoint at 21 epochs 2023/05/13 04:35:49 - mmengine - INFO - Epoch(val) [21][ 50/509] eta: 0:02:43 time: 0.3564 data_time: 0.0022 memory: 2997 2023/05/13 04:36:05 - mmengine - INFO - Epoch(val) [21][100/509] eta: 0:02:18 time: 0.3190 data_time: 0.0021 memory: 920 2023/05/13 04:36:21 - mmengine - INFO - Epoch(val) [21][150/509] eta: 0:01:59 time: 0.3203 data_time: 0.0021 memory: 918 2023/05/13 04:36:37 - mmengine - INFO - Epoch(val) [21][200/509] eta: 0:01:41 time: 0.3228 data_time: 0.0021 memory: 906 2023/05/13 04:36:55 - mmengine - INFO - Epoch(val) [21][250/509] eta: 0:01:27 time: 0.3653 data_time: 0.0020 memory: 931 2023/05/13 04:37:10 - mmengine - INFO - Epoch(val) [21][300/509] eta: 0:01:08 time: 0.2908 data_time: 0.0021 memory: 868 2023/05/13 04:37:26 - mmengine - INFO - Epoch(val) [21][350/509] eta: 0:00:52 time: 0.3310 data_time: 0.0021 memory: 893 2023/05/13 04:37:43 - mmengine - INFO - Epoch(val) [21][400/509] eta: 0:00:35 time: 0.3312 data_time: 0.0021 memory: 901 2023/05/13 04:38:00 - mmengine - INFO - Epoch(val) [21][450/509] eta: 0:00:19 time: 0.3447 data_time: 0.0021 memory: 915 2023/05/13 04:38:16 - mmengine - INFO - Epoch(val) [21][500/509] eta: 0:00:02 time: 0.3101 data_time: 0.0021 memory: 898 2023/05/13 04:38:36 - 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 | 0.9583 | 0.3862 | 0.6454 | 0.4631 | 0.6185 | 0.6888 | 0.7783 | 0.0319 | 0.9413 | 0.4666 | 0.8118 | 0.0079 | 0.9068 | 0.6264 | 0.8891 | 0.6765 | 0.7648 | 0.6313 | 0.4833 | 0.6198 | 0.9228 | 0.6855 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 04:38:36 - mmengine - INFO - Epoch(val) [21][509/509] car: 0.9583 bicycle: 0.3862 motorcycle: 0.6454 truck: 0.4631 bus: 0.6185 person: 0.6888 bicyclist: 0.7783 motorcyclist: 0.0319 road: 0.9413 parking: 0.4666 sidewalk: 0.8118 other-ground: 0.0079 building: 0.9068 fence: 0.6264 vegetation: 0.8891 trunck: 0.6765 terrian: 0.7648 pole: 0.6313 traffic-sign: 0.4833 miou: 0.6198 acc: 0.9228 acc_cls: 0.6855 data_time: 0.0020 time: 0.3266 2023/05/13 04:39:06 - mmengine - INFO - Epoch(train) [22][ 50/1196] lr: 8.0000e-03 eta: 2:51:57 time: 0.6139 data_time: 0.0038 memory: 2933 grad_norm: 0.0934 loss: 0.1961 loss_sem_seg: 0.1961 2023/05/13 04:39:36 - mmengine - INFO - Epoch(train) [22][ 100/1196] lr: 8.0000e-03 eta: 2:51:29 time: 0.6030 data_time: 0.0035 memory: 2798 grad_norm: 0.0952 loss: 0.2048 loss_sem_seg: 0.2048 2023/05/13 04:40:08 - mmengine - INFO - Epoch(train) [22][ 150/1196] lr: 8.0000e-03 eta: 2:51:03 time: 0.6355 data_time: 0.0034 memory: 2932 grad_norm: 0.1092 loss: 0.2144 loss_sem_seg: 0.2144 2023/05/13 04:40:39 - mmengine - INFO - Epoch(train) [22][ 200/1196] lr: 8.0000e-03 eta: 2:50:35 time: 0.6084 data_time: 0.0036 memory: 2754 grad_norm: 0.0960 loss: 0.2124 loss_sem_seg: 0.2124 2023/05/13 04:41:08 - mmengine - INFO - Epoch(train) [22][ 250/1196] lr: 8.0000e-03 eta: 2:50:06 time: 0.5887 data_time: 0.0035 memory: 2935 grad_norm: 0.1146 loss: 0.2059 loss_sem_seg: 0.2059 2023/05/13 04:41:39 - mmengine - INFO - Epoch(train) [22][ 300/1196] lr: 8.0000e-03 eta: 2:49:39 time: 0.6114 data_time: 0.0034 memory: 2892 grad_norm: 0.0968 loss: 0.2146 loss_sem_seg: 0.2146 2023/05/13 04:42:09 - mmengine - INFO - Epoch(train) [22][ 350/1196] lr: 8.0000e-03 eta: 2:49:11 time: 0.6004 data_time: 0.0036 memory: 2606 grad_norm: 0.0981 loss: 0.2179 loss_sem_seg: 0.2179 2023/05/13 04:42:39 - mmengine - INFO - Epoch(train) [22][ 400/1196] lr: 8.0000e-03 eta: 2:48:43 time: 0.6078 data_time: 0.0034 memory: 2727 grad_norm: 0.1063 loss: 0.2195 loss_sem_seg: 0.2195 2023/05/13 04:43:09 - mmengine - INFO - Epoch(train) [22][ 450/1196] lr: 8.0000e-03 eta: 2:48:15 time: 0.6047 data_time: 0.0033 memory: 2831 grad_norm: 0.0972 loss: 0.2126 loss_sem_seg: 0.2126 2023/05/13 04:43:40 - mmengine - INFO - Epoch(train) [22][ 500/1196] lr: 8.0000e-03 eta: 2:47:47 time: 0.6148 data_time: 0.0035 memory: 2736 grad_norm: 0.0849 loss: 0.2027 loss_sem_seg: 0.2027 2023/05/13 04:44:11 - mmengine - INFO - Epoch(train) [22][ 550/1196] lr: 8.0000e-03 eta: 2:47:20 time: 0.6150 data_time: 0.0035 memory: 2728 grad_norm: 0.0902 loss: 0.2160 loss_sem_seg: 0.2160 2023/05/13 04:44:41 - mmengine - INFO - Epoch(train) [22][ 600/1196] lr: 8.0000e-03 eta: 2:46:52 time: 0.6115 data_time: 0.0034 memory: 3027 grad_norm: 0.1010 loss: 0.1985 loss_sem_seg: 0.1985 2023/05/13 04:45:12 - mmengine - INFO - Epoch(train) [22][ 650/1196] lr: 8.0000e-03 eta: 2:46:24 time: 0.6116 data_time: 0.0036 memory: 2999 grad_norm: 0.0937 loss: 0.2044 loss_sem_seg: 0.2044 2023/05/13 04:45:42 - mmengine - INFO - Epoch(train) [22][ 700/1196] lr: 8.0000e-03 eta: 2:45:57 time: 0.6068 data_time: 0.0035 memory: 2658 grad_norm: 0.1027 loss: 0.2123 loss_sem_seg: 0.2123 2023/05/13 04:46:13 - mmengine - INFO - Epoch(train) [22][ 750/1196] lr: 8.0000e-03 eta: 2:45:29 time: 0.6181 data_time: 0.0035 memory: 2939 grad_norm: 0.1034 loss: 0.2141 loss_sem_seg: 0.2141 2023/05/13 04:46:43 - mmengine - INFO - Epoch(train) [22][ 800/1196] lr: 8.0000e-03 eta: 2:45:01 time: 0.5929 data_time: 0.0033 memory: 2788 grad_norm: 0.1086 loss: 0.2056 loss_sem_seg: 0.2056 2023/05/13 04:47:13 - mmengine - INFO - Epoch(train) [22][ 850/1196] lr: 8.0000e-03 eta: 2:44:33 time: 0.6094 data_time: 0.0034 memory: 2792 grad_norm: 0.1014 loss: 0.2148 loss_sem_seg: 0.2148 2023/05/13 04:47:35 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:47:44 - mmengine - INFO - Epoch(train) [22][ 900/1196] lr: 8.0000e-03 eta: 2:44:05 time: 0.6152 data_time: 0.0034 memory: 2880 grad_norm: 0.1062 loss: 0.2184 loss_sem_seg: 0.2184 2023/05/13 04:48:14 - mmengine - INFO - Epoch(train) [22][ 950/1196] lr: 8.0000e-03 eta: 2:43:37 time: 0.5875 data_time: 0.0034 memory: 3106 grad_norm: 0.1144 loss: 0.2082 loss_sem_seg: 0.2082 2023/05/13 04:48:41 - mmengine - INFO - Epoch(train) [22][1000/1196] lr: 8.0000e-03 eta: 2:43:07 time: 0.5566 data_time: 0.0033 memory: 2976 grad_norm: 0.0971 loss: 0.2147 loss_sem_seg: 0.2147 2023/05/13 04:49:08 - mmengine - INFO - Epoch(train) [22][1050/1196] lr: 8.0000e-03 eta: 2:42:37 time: 0.5385 data_time: 0.0033 memory: 2754 grad_norm: 0.1026 loss: 0.1995 loss_sem_seg: 0.1995 2023/05/13 04:49:36 - mmengine - INFO - Epoch(train) [22][1100/1196] lr: 8.0000e-03 eta: 2:42:07 time: 0.5553 data_time: 0.0035 memory: 2654 grad_norm: 0.1164 loss: 0.2177 loss_sem_seg: 0.2177 2023/05/13 04:50:05 - mmengine - INFO - Epoch(train) [22][1150/1196] lr: 8.0000e-03 eta: 2:41:38 time: 0.5698 data_time: 0.0035 memory: 3136 grad_norm: 0.0979 loss: 0.2205 loss_sem_seg: 0.2205 2023/05/13 04:50:30 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:50:30 - mmengine - INFO - Saving checkpoint at 22 epochs 2023/05/13 04:50:54 - mmengine - INFO - Epoch(val) [22][ 50/509] eta: 0:02:32 time: 0.3319 data_time: 0.0022 memory: 2897 2023/05/13 04:51:10 - mmengine - INFO - Epoch(val) [22][100/509] eta: 0:02:13 time: 0.3191 data_time: 0.0022 memory: 920 2023/05/13 04:51:26 - mmengine - INFO - Epoch(val) [22][150/509] eta: 0:01:56 time: 0.3197 data_time: 0.0021 memory: 918 2023/05/13 04:51:42 - mmengine - INFO - Epoch(val) [22][200/509] eta: 0:01:40 time: 0.3250 data_time: 0.0021 memory: 906 2023/05/13 04:52:00 - mmengine - INFO - Epoch(val) [22][250/509] eta: 0:01:25 time: 0.3634 data_time: 0.0021 memory: 931 2023/05/13 04:52:15 - mmengine - INFO - Epoch(val) [22][300/509] eta: 0:01:08 time: 0.3031 data_time: 0.0020 memory: 868 2023/05/13 04:52:32 - mmengine - INFO - Epoch(val) [22][350/509] eta: 0:00:52 time: 0.3312 data_time: 0.0021 memory: 893 2023/05/13 04:52:49 - mmengine - INFO - Epoch(val) [22][400/509] eta: 0:00:35 time: 0.3431 data_time: 0.0021 memory: 901 2023/05/13 04:53:06 - mmengine - INFO - Epoch(val) [22][450/509] eta: 0:00:19 time: 0.3412 data_time: 0.0022 memory: 915 2023/05/13 04:53:21 - mmengine - INFO - Epoch(val) [22][500/509] eta: 0:00:02 time: 0.2936 data_time: 0.0020 memory: 898 2023/05/13 04:53:41 - 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 | 0.9613 | 0.4982 | 0.7911 | 0.8466 | 0.6951 | 0.7762 | 0.8715 | 0.0530 | 0.9377 | 0.5396 | 0.8205 | 0.0128 | 0.9128 | 0.6300 | 0.8901 | 0.6740 | 0.7698 | 0.6385 | 0.5088 | 0.6751 | 0.9252 | 0.7561 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 04:53:41 - mmengine - INFO - Epoch(val) [22][509/509] car: 0.9613 bicycle: 0.4982 motorcycle: 0.7911 truck: 0.8466 bus: 0.6951 person: 0.7762 bicyclist: 0.8715 motorcyclist: 0.0530 road: 0.9377 parking: 0.5396 sidewalk: 0.8205 other-ground: 0.0128 building: 0.9128 fence: 0.6300 vegetation: 0.8901 trunck: 0.6740 terrian: 0.7698 pole: 0.6385 traffic-sign: 0.5088 miou: 0.6751 acc: 0.9252 acc_cls: 0.7561 data_time: 0.0020 time: 0.3140 2023/05/13 04:54:10 - mmengine - INFO - Epoch(train) [23][ 50/1196] lr: 8.0000e-03 eta: 2:40:42 time: 0.5838 data_time: 0.0047 memory: 2993 grad_norm: 0.0948 loss: 0.2155 loss_sem_seg: 0.2155 2023/05/13 04:54:38 - mmengine - INFO - Epoch(train) [23][ 100/1196] lr: 8.0000e-03 eta: 2:40:13 time: 0.5538 data_time: 0.0035 memory: 2716 grad_norm: 0.0914 loss: 0.2091 loss_sem_seg: 0.2091 2023/05/13 04:55:05 - mmengine - INFO - Epoch(train) [23][ 150/1196] lr: 8.0000e-03 eta: 2:39:43 time: 0.5401 data_time: 0.0034 memory: 2778 grad_norm: 0.0984 loss: 0.2004 loss_sem_seg: 0.2004 2023/05/13 04:55:31 - mmengine - INFO - Epoch(train) [23][ 200/1196] lr: 8.0000e-03 eta: 2:39:12 time: 0.5338 data_time: 0.0036 memory: 2887 grad_norm: 0.0982 loss: 0.2071 loss_sem_seg: 0.2071 2023/05/13 04:55:58 - mmengine - INFO - Epoch(train) [23][ 250/1196] lr: 8.0000e-03 eta: 2:38:42 time: 0.5314 data_time: 0.0034 memory: 2660 grad_norm: 0.0933 loss: 0.2170 loss_sem_seg: 0.2170 2023/05/13 04:56:25 - mmengine - INFO - Epoch(train) [23][ 300/1196] lr: 8.0000e-03 eta: 2:38:12 time: 0.5484 data_time: 0.0034 memory: 2773 grad_norm: 0.0991 loss: 0.2110 loss_sem_seg: 0.2110 2023/05/13 04:56:53 - mmengine - INFO - Epoch(train) [23][ 350/1196] lr: 8.0000e-03 eta: 2:37:43 time: 0.5476 data_time: 0.0034 memory: 2916 grad_norm: 0.1047 loss: 0.2138 loss_sem_seg: 0.2138 2023/05/13 04:57:20 - mmengine - INFO - Epoch(train) [23][ 400/1196] lr: 8.0000e-03 eta: 2:37:13 time: 0.5534 data_time: 0.0034 memory: 3096 grad_norm: 0.0971 loss: 0.1961 loss_sem_seg: 0.1961 2023/05/13 04:57:46 - mmengine - INFO - Epoch(train) [23][ 450/1196] lr: 8.0000e-03 eta: 2:36:42 time: 0.5137 data_time: 0.0034 memory: 2982 grad_norm: 0.1039 loss: 0.2087 loss_sem_seg: 0.2087 2023/05/13 04:58:11 - mmengine - INFO - Epoch(train) [23][ 500/1196] lr: 8.0000e-03 eta: 2:36:11 time: 0.4932 data_time: 0.0033 memory: 2592 grad_norm: 0.0946 loss: 0.1989 loss_sem_seg: 0.1989 2023/05/13 04:58:35 - mmengine - INFO - Epoch(train) [23][ 550/1196] lr: 8.0000e-03 eta: 2:35:39 time: 0.4929 data_time: 0.0034 memory: 2661 grad_norm: 0.0992 loss: 0.2122 loss_sem_seg: 0.2122 2023/05/13 04:59:00 - mmengine - INFO - Epoch(train) [23][ 600/1196] lr: 8.0000e-03 eta: 2:35:08 time: 0.4916 data_time: 0.0035 memory: 2856 grad_norm: 0.0860 loss: 0.2022 loss_sem_seg: 0.2022 2023/05/13 04:59:25 - mmengine - INFO - Epoch(train) [23][ 650/1196] lr: 8.0000e-03 eta: 2:34:37 time: 0.5077 data_time: 0.0036 memory: 2886 grad_norm: 0.0942 loss: 0.2022 loss_sem_seg: 0.2022 2023/05/13 04:59:44 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 04:59:50 - mmengine - INFO - Epoch(train) [23][ 700/1196] lr: 8.0000e-03 eta: 2:34:06 time: 0.4972 data_time: 0.0036 memory: 2832 grad_norm: 0.0878 loss: 0.1909 loss_sem_seg: 0.1909 2023/05/13 05:00:15 - mmengine - INFO - Epoch(train) [23][ 750/1196] lr: 8.0000e-03 eta: 2:33:35 time: 0.5015 data_time: 0.0035 memory: 2708 grad_norm: 0.0936 loss: 0.2208 loss_sem_seg: 0.2208 2023/05/13 05:00:40 - mmengine - INFO - Epoch(train) [23][ 800/1196] lr: 8.0000e-03 eta: 2:33:04 time: 0.4932 data_time: 0.0034 memory: 2796 grad_norm: 0.0977 loss: 0.2056 loss_sem_seg: 0.2056 2023/05/13 05:01:06 - mmengine - INFO - Epoch(train) [23][ 850/1196] lr: 8.0000e-03 eta: 2:32:33 time: 0.5170 data_time: 0.0033 memory: 2819 grad_norm: 0.0980 loss: 0.2079 loss_sem_seg: 0.2079 2023/05/13 05:01:34 - mmengine - INFO - Epoch(train) [23][ 900/1196] lr: 8.0000e-03 eta: 2:32:04 time: 0.5735 data_time: 0.0034 memory: 2720 grad_norm: 0.0926 loss: 0.2064 loss_sem_seg: 0.2064 2023/05/13 05:02:03 - mmengine - INFO - Epoch(train) [23][ 950/1196] lr: 8.0000e-03 eta: 2:31:35 time: 0.5673 data_time: 0.0034 memory: 2745 grad_norm: 0.1030 loss: 0.2101 loss_sem_seg: 0.2101 2023/05/13 05:02:31 - mmengine - INFO - Epoch(train) [23][1000/1196] lr: 8.0000e-03 eta: 2:31:06 time: 0.5628 data_time: 0.0034 memory: 3062 grad_norm: 0.1064 loss: 0.2067 loss_sem_seg: 0.2067 2023/05/13 05:02:59 - mmengine - INFO - Epoch(train) [23][1050/1196] lr: 8.0000e-03 eta: 2:30:37 time: 0.5695 data_time: 0.0033 memory: 3001 grad_norm: 0.1032 loss: 0.2266 loss_sem_seg: 0.2266 2023/05/13 05:03:27 - mmengine - INFO - Epoch(train) [23][1100/1196] lr: 8.0000e-03 eta: 2:30:08 time: 0.5563 data_time: 0.0033 memory: 2661 grad_norm: 0.0970 loss: 0.2243 loss_sem_seg: 0.2243 2023/05/13 05:03:56 - mmengine - INFO - Epoch(train) [23][1150/1196] lr: 8.0000e-03 eta: 2:29:39 time: 0.5656 data_time: 0.0034 memory: 2669 grad_norm: 0.1056 loss: 0.2207 loss_sem_seg: 0.2207 2023/05/13 05:04:21 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 05:04:21 - mmengine - INFO - Saving checkpoint at 23 epochs 2023/05/13 05:04:46 - mmengine - INFO - Epoch(val) [23][ 50/509] eta: 0:02:45 time: 0.3608 data_time: 0.0021 memory: 2771 2023/05/13 05:05:04 - mmengine - INFO - Epoch(val) [23][100/509] eta: 0:02:29 time: 0.3713 data_time: 0.0020 memory: 920 2023/05/13 05:05:20 - mmengine - INFO - Epoch(val) [23][150/509] eta: 0:02:05 time: 0.3152 data_time: 0.0021 memory: 918 2023/05/13 05:05:35 - mmengine - INFO - Epoch(val) [23][200/509] eta: 0:01:44 time: 0.3069 data_time: 0.0022 memory: 906 2023/05/13 05:05:52 - mmengine - INFO - Epoch(val) [23][250/509] eta: 0:01:27 time: 0.3402 data_time: 0.0022 memory: 931 2023/05/13 05:06:07 - mmengine - INFO - Epoch(val) [23][300/509] eta: 0:01:09 time: 0.2988 data_time: 0.0021 memory: 868 2023/05/13 05:06:23 - mmengine - INFO - Epoch(val) [23][350/509] eta: 0:00:52 time: 0.3208 data_time: 0.0022 memory: 893 2023/05/13 05:06:39 - mmengine - INFO - Epoch(val) [23][400/509] eta: 0:00:35 time: 0.3157 data_time: 0.0022 memory: 901 2023/05/13 05:06:56 - mmengine - INFO - Epoch(val) [23][450/509] eta: 0:00:19 time: 0.3278 data_time: 0.0022 memory: 915 2023/05/13 05:07:11 - mmengine - INFO - Epoch(val) [23][500/509] eta: 0:00:02 time: 0.3156 data_time: 0.0021 memory: 898 2023/05/13 05:07:31 - 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 | 0.9536 | 0.5319 | 0.7238 | 0.4109 | 0.6082 | 0.7473 | 0.8747 | 0.0862 | 0.9394 | 0.4276 | 0.8180 | 0.0055 | 0.9036 | 0.6075 | 0.8845 | 0.7206 | 0.7524 | 0.6450 | 0.4786 | 0.6379 | 0.9211 | 0.7038 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 05:07:31 - mmengine - INFO - Epoch(val) [23][509/509] car: 0.9536 bicycle: 0.5319 motorcycle: 0.7238 truck: 0.4109 bus: 0.6082 person: 0.7473 bicyclist: 0.8747 motorcyclist: 0.0862 road: 0.9394 parking: 0.4276 sidewalk: 0.8180 other-ground: 0.0055 building: 0.9036 fence: 0.6075 vegetation: 0.8845 trunck: 0.7206 terrian: 0.7524 pole: 0.6450 traffic-sign: 0.4786 miou: 0.6379 acc: 0.9211 acc_cls: 0.7038 data_time: 0.0021 time: 0.3352 2023/05/13 05:08:01 - mmengine - INFO - Epoch(train) [24][ 50/1196] lr: 8.0000e-03 eta: 2:28:44 time: 0.6007 data_time: 0.0042 memory: 3137 grad_norm: 0.0872 loss: 0.2029 loss_sem_seg: 0.2029 2023/05/13 05:08:32 - mmengine - INFO - Epoch(train) [24][ 100/1196] lr: 8.0000e-03 eta: 2:28:16 time: 0.6210 data_time: 0.0033 memory: 2769 grad_norm: 0.1007 loss: 0.2196 loss_sem_seg: 0.2196 2023/05/13 05:09:02 - mmengine - INFO - Epoch(train) [24][ 150/1196] lr: 8.0000e-03 eta: 2:27:48 time: 0.5978 data_time: 0.0036 memory: 2855 grad_norm: 0.0927 loss: 0.2070 loss_sem_seg: 0.2070 2023/05/13 05:09:31 - mmengine - INFO - Epoch(train) [24][ 200/1196] lr: 8.0000e-03 eta: 2:27:19 time: 0.5936 data_time: 0.0035 memory: 2768 grad_norm: 0.0960 loss: 0.2094 loss_sem_seg: 0.2094 2023/05/13 05:10:02 - mmengine - INFO - Epoch(train) [24][ 250/1196] lr: 8.0000e-03 eta: 2:26:52 time: 0.6207 data_time: 0.0035 memory: 2904 grad_norm: 0.0967 loss: 0.2039 loss_sem_seg: 0.2039 2023/05/13 05:10:33 - mmengine - INFO - Epoch(train) [24][ 300/1196] lr: 8.0000e-03 eta: 2:26:24 time: 0.6031 data_time: 0.0035 memory: 2779 grad_norm: inf loss: 0.2090 loss_sem_seg: 0.2090 2023/05/13 05:11:03 - mmengine - INFO - Epoch(train) [24][ 350/1196] lr: 8.0000e-03 eta: 2:25:56 time: 0.6058 data_time: 0.0035 memory: 2717 grad_norm: 0.0934 loss: 0.2072 loss_sem_seg: 0.2072 2023/05/13 05:11:33 - mmengine - INFO - Epoch(train) [24][ 400/1196] lr: 8.0000e-03 eta: 2:25:28 time: 0.6054 data_time: 0.0035 memory: 2714 grad_norm: 0.1010 loss: 0.2083 loss_sem_seg: 0.2083 2023/05/13 05:12:04 - mmengine - INFO - Epoch(train) [24][ 450/1196] lr: 8.0000e-03 eta: 2:25:00 time: 0.6211 data_time: 0.0036 memory: 3011 grad_norm: 0.0904 loss: 0.1911 loss_sem_seg: 0.1911 2023/05/13 05:12:29 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 05:12:34 - mmengine - INFO - Epoch(train) [24][ 500/1196] lr: 8.0000e-03 eta: 2:24:32 time: 0.6034 data_time: 0.0036 memory: 2781 grad_norm: 0.0911 loss: 0.2102 loss_sem_seg: 0.2102 2023/05/13 05:13:04 - mmengine - INFO - Epoch(train) [24][ 550/1196] lr: 8.0000e-03 eta: 2:24:04 time: 0.5905 data_time: 0.0034 memory: 2829 grad_norm: 0.1062 loss: 0.2056 loss_sem_seg: 0.2056 2023/05/13 05:13:35 - mmengine - INFO - Epoch(train) [24][ 600/1196] lr: 8.0000e-03 eta: 2:23:36 time: 0.6113 data_time: 0.0034 memory: 2756 grad_norm: 0.1054 loss: 0.2041 loss_sem_seg: 0.2041 2023/05/13 05:14:05 - mmengine - INFO - Epoch(train) [24][ 650/1196] lr: 8.0000e-03 eta: 2:23:08 time: 0.6143 data_time: 0.0036 memory: 2837 grad_norm: 0.1040 loss: 0.2061 loss_sem_seg: 0.2061 2023/05/13 05:14:36 - mmengine - INFO - Epoch(train) [24][ 700/1196] lr: 8.0000e-03 eta: 2:22:40 time: 0.6185 data_time: 0.0035 memory: 2983 grad_norm: 0.1068 loss: 0.2112 loss_sem_seg: 0.2112 2023/05/13 05:15:07 - mmengine - INFO - Epoch(train) [24][ 750/1196] lr: 8.0000e-03 eta: 2:22:12 time: 0.6120 data_time: 0.0035 memory: 2894 grad_norm: 0.0965 loss: 0.2135 loss_sem_seg: 0.2135 2023/05/13 05:15:37 - mmengine - INFO - Epoch(train) [24][ 800/1196] lr: 8.0000e-03 eta: 2:21:44 time: 0.6013 data_time: 0.0037 memory: 2809 grad_norm: 0.0940 loss: 0.2178 loss_sem_seg: 0.2178 2023/05/13 05:16:08 - mmengine - INFO - Epoch(train) [24][ 850/1196] lr: 8.0000e-03 eta: 2:21:17 time: 0.6196 data_time: 0.0034 memory: 3085 grad_norm: 0.0932 loss: 0.2102 loss_sem_seg: 0.2102 2023/05/13 05:16:39 - mmengine - INFO - Epoch(train) [24][ 900/1196] lr: 8.0000e-03 eta: 2:20:49 time: 0.6163 data_time: 0.0034 memory: 2868 grad_norm: 0.0960 loss: 0.2205 loss_sem_seg: 0.2205 2023/05/13 05:17:09 - mmengine - INFO - Epoch(train) [24][ 950/1196] lr: 8.0000e-03 eta: 2:20:20 time: 0.5993 data_time: 0.0036 memory: 2738 grad_norm: 0.0969 loss: 0.2084 loss_sem_seg: 0.2084 2023/05/13 05:17:40 - mmengine - INFO - Epoch(train) [24][1000/1196] lr: 8.0000e-03 eta: 2:19:53 time: 0.6185 data_time: 0.0035 memory: 2743 grad_norm: 0.1050 loss: 0.1955 loss_sem_seg: 0.1955 2023/05/13 05:18:10 - mmengine - INFO - Epoch(train) [24][1050/1196] lr: 8.0000e-03 eta: 2:19:25 time: 0.6055 data_time: 0.0035 memory: 2812 grad_norm: 0.0932 loss: 0.2015 loss_sem_seg: 0.2015 2023/05/13 05:18:41 - mmengine - INFO - Epoch(train) [24][1100/1196] lr: 8.0000e-03 eta: 2:18:57 time: 0.6180 data_time: 0.0035 memory: 2823 grad_norm: 0.0968 loss: 0.2100 loss_sem_seg: 0.2100 2023/05/13 05:19:11 - mmengine - INFO - Epoch(train) [24][1150/1196] lr: 8.0000e-03 eta: 2:18:29 time: 0.6094 data_time: 0.0035 memory: 2786 grad_norm: 0.0955 loss: 0.2028 loss_sem_seg: 0.2028 2023/05/13 05:19:39 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 05:19:39 - mmengine - INFO - Saving checkpoint at 24 epochs 2023/05/13 05:20:06 - mmengine - INFO - Epoch(val) [24][ 50/509] eta: 0:02:59 time: 0.3911 data_time: 0.0021 memory: 2807 2023/05/13 05:20:23 - mmengine - INFO - Epoch(val) [24][100/509] eta: 0:02:28 time: 0.3364 data_time: 0.0021 memory: 920 2023/05/13 05:20:39 - mmengine - INFO - Epoch(val) [24][150/509] eta: 0:02:06 time: 0.3301 data_time: 0.0022 memory: 918 2023/05/13 05:20:56 - mmengine - INFO - Epoch(val) [24][200/509] eta: 0:01:47 time: 0.3357 data_time: 0.0021 memory: 906 2023/05/13 05:21:14 - mmengine - INFO - Epoch(val) [24][250/509] eta: 0:01:31 time: 0.3656 data_time: 0.0021 memory: 931 2023/05/13 05:21:29 - mmengine - INFO - Epoch(val) [24][300/509] eta: 0:01:11 time: 0.2966 data_time: 0.0022 memory: 868 2023/05/13 05:21:45 - mmengine - INFO - Epoch(val) [24][350/509] eta: 0:00:53 time: 0.3191 data_time: 0.0021 memory: 893 2023/05/13 05:22:02 - mmengine - INFO - Epoch(val) [24][400/509] eta: 0:00:37 time: 0.3468 data_time: 0.0021 memory: 901 2023/05/13 05:22:20 - mmengine - INFO - Epoch(val) [24][450/509] eta: 0:00:20 time: 0.3439 data_time: 0.0021 memory: 915 2023/05/13 05:22:36 - mmengine - INFO - Epoch(val) [24][500/509] eta: 0:00:03 time: 0.3274 data_time: 0.0021 memory: 898 2023/05/13 05:22:57 - 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 | 0.9543 | 0.4892 | 0.7685 | 0.4470 | 0.5733 | 0.7227 | 0.8450 | 0.0733 | 0.9385 | 0.5416 | 0.8241 | 0.0088 | 0.9200 | 0.6372 | 0.8717 | 0.6790 | 0.7271 | 0.6478 | 0.5101 | 0.6410 | 0.9191 | 0.7108 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 05:22:57 - mmengine - INFO - Epoch(val) [24][509/509] car: 0.9543 bicycle: 0.4892 motorcycle: 0.7685 truck: 0.4470 bus: 0.5733 person: 0.7227 bicyclist: 0.8450 motorcyclist: 0.0733 road: 0.9385 parking: 0.5416 sidewalk: 0.8241 other-ground: 0.0088 building: 0.9200 fence: 0.6372 vegetation: 0.8717 trunck: 0.6790 terrian: 0.7271 pole: 0.6478 traffic-sign: 0.5101 miou: 0.6410 acc: 0.9191 acc_cls: 0.7108 data_time: 0.0021 time: 0.3463 2023/05/13 05:23:28 - mmengine - INFO - Epoch(train) [25][ 50/1196] lr: 8.0000e-04 eta: 2:17:35 time: 0.6272 data_time: 0.0039 memory: 3028 grad_norm: 0.0708 loss: 0.1984 loss_sem_seg: 0.1984 2023/05/13 05:23:59 - mmengine - INFO - Epoch(train) [25][ 100/1196] lr: 8.0000e-04 eta: 2:17:07 time: 0.6059 data_time: 0.0036 memory: 2983 grad_norm: 0.0633 loss: 0.1868 loss_sem_seg: 0.1868 2023/05/13 05:24:29 - mmengine - INFO - Epoch(train) [25][ 150/1196] lr: 8.0000e-04 eta: 2:16:39 time: 0.6045 data_time: 0.0034 memory: 2798 grad_norm: 0.0635 loss: 0.1854 loss_sem_seg: 0.1854 2023/05/13 05:24:59 - mmengine - INFO - Epoch(train) [25][ 200/1196] lr: 8.0000e-04 eta: 2:16:11 time: 0.6052 data_time: 0.0036 memory: 2826 grad_norm: 0.0595 loss: 0.1815 loss_sem_seg: 0.1815 2023/05/13 05:25:30 - mmengine - INFO - Epoch(train) [25][ 250/1196] lr: 8.0000e-04 eta: 2:15:43 time: 0.6197 data_time: 0.0038 memory: 2849 grad_norm: 0.0614 loss: 0.1710 loss_sem_seg: 0.1710 2023/05/13 05:25:58 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 05:26:01 - mmengine - INFO - Epoch(train) [25][ 300/1196] lr: 8.0000e-04 eta: 2:15:15 time: 0.6109 data_time: 0.0038 memory: 2777 grad_norm: 0.0568 loss: 0.1777 loss_sem_seg: 0.1777 2023/05/13 05:26:31 - mmengine - INFO - Epoch(train) [25][ 350/1196] lr: 8.0000e-04 eta: 2:14:47 time: 0.6118 data_time: 0.0035 memory: 2889 grad_norm: 0.0580 loss: 0.1721 loss_sem_seg: 0.1721 2023/05/13 05:27:00 - mmengine - INFO - Epoch(train) [25][ 400/1196] lr: 8.0000e-04 eta: 2:14:18 time: 0.5709 data_time: 0.0036 memory: 2693 grad_norm: 0.0622 loss: 0.1743 loss_sem_seg: 0.1743 2023/05/13 05:27:27 - mmengine - INFO - Epoch(train) [25][ 450/1196] lr: 8.0000e-04 eta: 2:13:48 time: 0.5519 data_time: 0.0033 memory: 3083 grad_norm: 0.0602 loss: 0.1545 loss_sem_seg: 0.1545 2023/05/13 05:27:56 - mmengine - INFO - Epoch(train) [25][ 500/1196] lr: 8.0000e-04 eta: 2:13:19 time: 0.5700 data_time: 0.0035 memory: 2751 grad_norm: 0.0623 loss: 0.1625 loss_sem_seg: 0.1625 2023/05/13 05:28:24 - mmengine - INFO - Epoch(train) [25][ 550/1196] lr: 8.0000e-04 eta: 2:12:50 time: 0.5646 data_time: 0.0035 memory: 2792 grad_norm: 0.0591 loss: 0.1709 loss_sem_seg: 0.1709 2023/05/13 05:28:52 - mmengine - INFO - Epoch(train) [25][ 600/1196] lr: 8.0000e-04 eta: 2:12:21 time: 0.5494 data_time: 0.0034 memory: 2821 grad_norm: 0.0654 loss: 0.1813 loss_sem_seg: 0.1813 2023/05/13 05:29:19 - mmengine - INFO - Epoch(train) [25][ 650/1196] lr: 8.0000e-04 eta: 2:11:51 time: 0.5406 data_time: 0.0035 memory: 2676 grad_norm: 0.0620 loss: 0.1886 loss_sem_seg: 0.1886 2023/05/13 05:29:48 - mmengine - INFO - Epoch(train) [25][ 700/1196] lr: 8.0000e-04 eta: 2:11:22 time: 0.5948 data_time: 0.0036 memory: 2782 grad_norm: 0.0585 loss: 0.1714 loss_sem_seg: 0.1714 2023/05/13 05:30:19 - mmengine - INFO - Epoch(train) [25][ 750/1196] lr: 8.0000e-04 eta: 2:10:54 time: 0.6136 data_time: 0.0036 memory: 2761 grad_norm: 0.0569 loss: 0.1624 loss_sem_seg: 0.1624 2023/05/13 05:30:49 - mmengine - INFO - Epoch(train) [25][ 800/1196] lr: 8.0000e-04 eta: 2:10:26 time: 0.6055 data_time: 0.0036 memory: 2797 grad_norm: 0.0621 loss: 0.1734 loss_sem_seg: 0.1734 2023/05/13 05:31:19 - mmengine - INFO - Epoch(train) [25][ 850/1196] lr: 8.0000e-04 eta: 2:09:58 time: 0.5994 data_time: 0.0035 memory: 2772 grad_norm: 0.0634 loss: 0.1711 loss_sem_seg: 0.1711 2023/05/13 05:31:50 - mmengine - INFO - Epoch(train) [25][ 900/1196] lr: 8.0000e-04 eta: 2:09:30 time: 0.6132 data_time: 0.0035 memory: 3042 grad_norm: 0.0596 loss: 0.1672 loss_sem_seg: 0.1672 2023/05/13 05:32:21 - mmengine - INFO - Epoch(train) [25][ 950/1196] lr: 8.0000e-04 eta: 2:09:02 time: 0.6116 data_time: 0.0036 memory: 2746 grad_norm: 0.0623 loss: 0.1699 loss_sem_seg: 0.1699 2023/05/13 05:32:51 - mmengine - INFO - Epoch(train) [25][1000/1196] lr: 8.0000e-04 eta: 2:08:34 time: 0.6160 data_time: 0.0034 memory: 2716 grad_norm: 0.0611 loss: 0.1593 loss_sem_seg: 0.1593 2023/05/13 05:33:22 - mmengine - INFO - Epoch(train) [25][1050/1196] lr: 8.0000e-04 eta: 2:08:05 time: 0.6134 data_time: 0.0035 memory: 2858 grad_norm: 0.0575 loss: 0.1631 loss_sem_seg: 0.1631 2023/05/13 05:33:53 - mmengine - INFO - Epoch(train) [25][1100/1196] lr: 8.0000e-04 eta: 2:07:37 time: 0.6201 data_time: 0.0037 memory: 3066 grad_norm: 0.0619 loss: 0.1694 loss_sem_seg: 0.1694 2023/05/13 05:34:24 - mmengine - INFO - Epoch(train) [25][1150/1196] lr: 8.0000e-04 eta: 2:07:09 time: 0.6098 data_time: 0.0037 memory: 2716 grad_norm: 0.0594 loss: 0.1682 loss_sem_seg: 0.1682 2023/05/13 05:34:52 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 05:34:52 - mmengine - INFO - Saving checkpoint at 25 epochs 2023/05/13 05:35:17 - mmengine - INFO - Epoch(val) [25][ 50/509] eta: 0:02:48 time: 0.3681 data_time: 0.0022 memory: 2914 2023/05/13 05:35:33 - mmengine - INFO - Epoch(val) [25][100/509] eta: 0:02:23 time: 0.3322 data_time: 0.0022 memory: 920 2023/05/13 05:35:49 - mmengine - INFO - Epoch(val) [25][150/509] eta: 0:02:01 time: 0.3124 data_time: 0.0023 memory: 918 2023/05/13 05:36:05 - mmengine - INFO - Epoch(val) [25][200/509] eta: 0:01:42 time: 0.3138 data_time: 0.0021 memory: 906 2023/05/13 05:36:22 - mmengine - INFO - Epoch(val) [25][250/509] eta: 0:01:26 time: 0.3512 data_time: 0.0022 memory: 931 2023/05/13 05:36:36 - mmengine - INFO - Epoch(val) [25][300/509] eta: 0:01:08 time: 0.2805 data_time: 0.0022 memory: 868 2023/05/13 05:36:51 - mmengine - INFO - Epoch(val) [25][350/509] eta: 0:00:51 time: 0.2971 data_time: 0.0022 memory: 893 2023/05/13 05:37:09 - mmengine - INFO - Epoch(val) [25][400/509] eta: 0:00:35 time: 0.3481 data_time: 0.0023 memory: 901 2023/05/13 05:37:24 - mmengine - INFO - Epoch(val) [25][450/509] eta: 0:00:19 time: 0.3115 data_time: 0.0021 memory: 915 2023/05/13 05:37:39 - mmengine - INFO - Epoch(val) [25][500/509] eta: 0:00:02 time: 0.3009 data_time: 0.0021 memory: 898 2023/05/13 05:38:00 - 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 | 0.9612 | 0.5473 | 0.8097 | 0.8289 | 0.5958 | 0.7808 | 0.8933 | 0.0620 | 0.9449 | 0.5285 | 0.8260 | 0.0181 | 0.9201 | 0.6864 | 0.8728 | 0.6953 | 0.7165 | 0.6594 | 0.5159 | 0.6770 | 0.9210 | 0.7449 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 05:38:00 - mmengine - INFO - Epoch(val) [25][509/509] car: 0.9612 bicycle: 0.5473 motorcycle: 0.8097 truck: 0.8289 bus: 0.5958 person: 0.7808 bicyclist: 0.8933 motorcyclist: 0.0620 road: 0.9449 parking: 0.5285 sidewalk: 0.8260 other-ground: 0.0181 building: 0.9201 fence: 0.6864 vegetation: 0.8728 trunck: 0.6953 terrian: 0.7165 pole: 0.6594 traffic-sign: 0.5159 miou: 0.6770 acc: 0.9210 acc_cls: 0.7449 data_time: 0.0022 time: 0.3072 2023/05/13 05:38:31 - mmengine - INFO - Epoch(train) [26][ 50/1196] lr: 8.0000e-04 eta: 2:06:15 time: 0.6094 data_time: 0.0044 memory: 2718 grad_norm: 0.0659 loss: 0.1651 loss_sem_seg: 0.1651 2023/05/13 05:39:02 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 05:39:02 - mmengine - INFO - Epoch(train) [26][ 100/1196] lr: 8.0000e-04 eta: 2:05:47 time: 0.6192 data_time: 0.0034 memory: 2837 grad_norm: 0.0614 loss: 0.1641 loss_sem_seg: 0.1641 2023/05/13 05:39:31 - mmengine - INFO - Epoch(train) [26][ 150/1196] lr: 8.0000e-04 eta: 2:05:18 time: 0.5713 data_time: 0.0035 memory: 2773 grad_norm: 0.0615 loss: 0.1638 loss_sem_seg: 0.1638 2023/05/13 05:40:00 - mmengine - INFO - Epoch(train) [26][ 200/1196] lr: 8.0000e-04 eta: 2:04:49 time: 0.5859 data_time: 0.0035 memory: 3099 grad_norm: 0.0644 loss: 0.1652 loss_sem_seg: 0.1652 2023/05/13 05:40:28 - mmengine - INFO - Epoch(train) [26][ 250/1196] lr: 8.0000e-04 eta: 2:04:20 time: 0.5617 data_time: 0.0037 memory: 2972 grad_norm: 0.0643 loss: 0.1819 loss_sem_seg: 0.1819 2023/05/13 05:40:56 - mmengine - INFO - Epoch(train) [26][ 300/1196] lr: 8.0000e-04 eta: 2:03:51 time: 0.5640 data_time: 0.0036 memory: 2861 grad_norm: 0.0611 loss: 0.1770 loss_sem_seg: 0.1770 2023/05/13 05:41:23 - mmengine - INFO - Epoch(train) [26][ 350/1196] lr: 8.0000e-04 eta: 2:03:21 time: 0.5453 data_time: 0.0035 memory: 2845 grad_norm: 0.0614 loss: 0.1702 loss_sem_seg: 0.1702 2023/05/13 05:41:51 - mmengine - INFO - Epoch(train) [26][ 400/1196] lr: 8.0000e-04 eta: 2:02:52 time: 0.5559 data_time: 0.0035 memory: 2790 grad_norm: 0.0579 loss: 0.1511 loss_sem_seg: 0.1511 2023/05/13 05:42:20 - mmengine - INFO - Epoch(train) [26][ 450/1196] lr: 8.0000e-04 eta: 2:02:23 time: 0.5771 data_time: 0.0036 memory: 2806 grad_norm: 0.0580 loss: 0.1693 loss_sem_seg: 0.1693 2023/05/13 05:42:49 - mmengine - INFO - Epoch(train) [26][ 500/1196] lr: 8.0000e-04 eta: 2:01:54 time: 0.5766 data_time: 0.0036 memory: 2681 grad_norm: 0.0589 loss: 0.1729 loss_sem_seg: 0.1729 2023/05/13 05:43:17 - mmengine - INFO - Epoch(train) [26][ 550/1196] lr: 8.0000e-04 eta: 2:01:25 time: 0.5592 data_time: 0.0034 memory: 2619 grad_norm: 0.0560 loss: 0.1594 loss_sem_seg: 0.1594 2023/05/13 05:43:45 - mmengine - INFO - Epoch(train) [26][ 600/1196] lr: 8.0000e-04 eta: 2:00:56 time: 0.5706 data_time: 0.0037 memory: 2804 grad_norm: 0.0588 loss: 0.1694 loss_sem_seg: 0.1694 2023/05/13 05:44:14 - mmengine - INFO - Epoch(train) [26][ 650/1196] lr: 8.0000e-04 eta: 2:00:27 time: 0.5711 data_time: 0.0037 memory: 2899 grad_norm: 0.0588 loss: 0.1629 loss_sem_seg: 0.1629 2023/05/13 05:44:43 - mmengine - INFO - Epoch(train) [26][ 700/1196] lr: 8.0000e-04 eta: 1:59:58 time: 0.5733 data_time: 0.0034 memory: 3008 grad_norm: 0.0641 loss: 0.1648 loss_sem_seg: 0.1648 2023/05/13 05:45:12 - mmengine - INFO - Epoch(train) [26][ 750/1196] lr: 8.0000e-04 eta: 1:59:29 time: 0.5796 data_time: 0.0035 memory: 2850 grad_norm: 0.0573 loss: 0.1575 loss_sem_seg: 0.1575 2023/05/13 05:45:40 - mmengine - INFO - Epoch(train) [26][ 800/1196] lr: 8.0000e-04 eta: 1:59:00 time: 0.5689 data_time: 0.0036 memory: 3231 grad_norm: 0.0586 loss: 0.1724 loss_sem_seg: 0.1724 2023/05/13 05:46:09 - mmengine - INFO - Epoch(train) [26][ 850/1196] lr: 8.0000e-04 eta: 1:58:31 time: 0.5706 data_time: 0.0034 memory: 2746 grad_norm: 0.0584 loss: 0.1646 loss_sem_seg: 0.1646 2023/05/13 05:46:37 - mmengine - INFO - Epoch(train) [26][ 900/1196] lr: 8.0000e-04 eta: 1:58:02 time: 0.5656 data_time: 0.0037 memory: 2910 grad_norm: 0.0612 loss: 0.1671 loss_sem_seg: 0.1671 2023/05/13 05:47:06 - mmengine - INFO - Epoch(train) [26][ 950/1196] lr: 8.0000e-04 eta: 1:57:33 time: 0.5747 data_time: 0.0035 memory: 2833 grad_norm: 0.0580 loss: 0.1701 loss_sem_seg: 0.1701 2023/05/13 05:47:37 - mmengine - INFO - Epoch(train) [26][1000/1196] lr: 8.0000e-04 eta: 1:57:05 time: 0.6312 data_time: 0.0035 memory: 2817 grad_norm: 0.0539 loss: 0.1537 loss_sem_seg: 0.1537 2023/05/13 05:48:09 - mmengine - INFO - Epoch(train) [26][1050/1196] lr: 8.0000e-04 eta: 1:56:37 time: 0.6275 data_time: 0.0035 memory: 2829 grad_norm: 0.0623 loss: 0.1719 loss_sem_seg: 0.1719 2023/05/13 05:48:37 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 05:48:37 - mmengine - INFO - Epoch(train) [26][1100/1196] lr: 8.0000e-04 eta: 1:56:08 time: 0.5649 data_time: 0.0035 memory: 2911 grad_norm: 0.0643 loss: 0.1573 loss_sem_seg: 0.1573 2023/05/13 05:49:04 - mmengine - INFO - Epoch(train) [26][1150/1196] lr: 8.0000e-04 eta: 1:55:38 time: 0.5339 data_time: 0.0035 memory: 2644 grad_norm: 0.0614 loss: 0.1660 loss_sem_seg: 0.1660 2023/05/13 05:49:28 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 05:49:28 - mmengine - INFO - Saving checkpoint at 26 epochs 2023/05/13 05:49:53 - mmengine - INFO - Epoch(val) [26][ 50/509] eta: 0:02:40 time: 0.3502 data_time: 0.0021 memory: 2856 2023/05/13 05:50:07 - mmengine - INFO - Epoch(val) [26][100/509] eta: 0:02:08 time: 0.2783 data_time: 0.0021 memory: 920 2023/05/13 05:50:20 - mmengine - INFO - Epoch(val) [26][150/509] eta: 0:01:47 time: 0.2693 data_time: 0.0021 memory: 918 2023/05/13 05:50:35 - mmengine - INFO - Epoch(val) [26][200/509] eta: 0:01:31 time: 0.2908 data_time: 0.0021 memory: 906 2023/05/13 05:50:50 - mmengine - INFO - Epoch(val) [26][250/509] eta: 0:01:17 time: 0.3137 data_time: 0.0021 memory: 931 2023/05/13 05:51:03 - mmengine - INFO - Epoch(val) [26][300/509] eta: 0:01:01 time: 0.2574 data_time: 0.0021 memory: 868 2023/05/13 05:51:18 - mmengine - INFO - Epoch(val) [26][350/509] eta: 0:00:46 time: 0.2889 data_time: 0.0021 memory: 893 2023/05/13 05:51:32 - mmengine - INFO - Epoch(val) [26][400/509] eta: 0:00:31 time: 0.2779 data_time: 0.0021 memory: 901 2023/05/13 05:51:46 - mmengine - INFO - Epoch(val) [26][450/509] eta: 0:00:17 time: 0.2860 data_time: 0.0021 memory: 915 2023/05/13 05:52:01 - mmengine - INFO - Epoch(val) [26][500/509] eta: 0:00:02 time: 0.2911 data_time: 0.0021 memory: 898 2023/05/13 05:52:19 - 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 | 0.9647 | 0.5140 | 0.7955 | 0.8355 | 0.6595 | 0.7801 | 0.8843 | 0.0715 | 0.9422 | 0.5160 | 0.8264 | 0.0123 | 0.9181 | 0.6810 | 0.8796 | 0.6768 | 0.7356 | 0.6574 | 0.5086 | 0.6768 | 0.9234 | 0.7435 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 05:52:19 - mmengine - INFO - Epoch(val) [26][509/509] car: 0.9647 bicycle: 0.5140 motorcycle: 0.7955 truck: 0.8355 bus: 0.6595 person: 0.7801 bicyclist: 0.8843 motorcyclist: 0.0715 road: 0.9422 parking: 0.5160 sidewalk: 0.8264 other-ground: 0.0123 building: 0.9181 fence: 0.6810 vegetation: 0.8796 trunck: 0.6768 terrian: 0.7356 pole: 0.6574 traffic-sign: 0.5086 miou: 0.6768 acc: 0.9234 acc_cls: 0.7435 data_time: 0.0021 time: 0.2959 2023/05/13 05:52:46 - mmengine - INFO - Epoch(train) [27][ 50/1196] lr: 8.0000e-04 eta: 1:54:41 time: 0.5308 data_time: 0.0046 memory: 3055 grad_norm: 0.0642 loss: 0.1720 loss_sem_seg: 0.1720 2023/05/13 05:53:13 - mmengine - INFO - Epoch(train) [27][ 100/1196] lr: 8.0000e-04 eta: 1:54:11 time: 0.5436 data_time: 0.0036 memory: 2758 grad_norm: 0.0607 loss: 0.1639 loss_sem_seg: 0.1639 2023/05/13 05:53:40 - mmengine - INFO - Epoch(train) [27][ 150/1196] lr: 8.0000e-04 eta: 1:53:42 time: 0.5415 data_time: 0.0036 memory: 2697 grad_norm: 0.0610 loss: 0.1751 loss_sem_seg: 0.1751 2023/05/13 05:54:07 - mmengine - INFO - Epoch(train) [27][ 200/1196] lr: 8.0000e-04 eta: 1:53:12 time: 0.5461 data_time: 0.0034 memory: 2814 grad_norm: 0.0585 loss: 0.1574 loss_sem_seg: 0.1574 2023/05/13 05:54:34 - mmengine - INFO - Epoch(train) [27][ 250/1196] lr: 8.0000e-04 eta: 1:52:43 time: 0.5440 data_time: 0.0035 memory: 2874 grad_norm: 0.0586 loss: 0.1626 loss_sem_seg: 0.1626 2023/05/13 05:55:01 - mmengine - INFO - Epoch(train) [27][ 300/1196] lr: 8.0000e-04 eta: 1:52:13 time: 0.5381 data_time: 0.0034 memory: 2723 grad_norm: 0.0619 loss: 0.1640 loss_sem_seg: 0.1640 2023/05/13 05:55:29 - mmengine - INFO - Epoch(train) [27][ 350/1196] lr: 8.0000e-04 eta: 1:51:44 time: 0.5475 data_time: 0.0035 memory: 2900 grad_norm: 0.0591 loss: 0.1549 loss_sem_seg: 0.1549 2023/05/13 05:55:58 - mmengine - INFO - Epoch(train) [27][ 400/1196] lr: 8.0000e-04 eta: 1:51:15 time: 0.5836 data_time: 0.0034 memory: 2723 grad_norm: 0.0599 loss: 0.1706 loss_sem_seg: 0.1706 2023/05/13 05:56:30 - mmengine - INFO - Epoch(train) [27][ 450/1196] lr: 8.0000e-04 eta: 1:50:47 time: 0.6343 data_time: 0.0035 memory: 2731 grad_norm: 0.0578 loss: 0.1701 loss_sem_seg: 0.1701 2023/05/13 05:57:00 - mmengine - INFO - Epoch(train) [27][ 500/1196] lr: 8.0000e-04 eta: 1:50:19 time: 0.6104 data_time: 0.0035 memory: 2696 grad_norm: 0.0693 loss: 0.1740 loss_sem_seg: 0.1740 2023/05/13 05:57:31 - mmengine - INFO - Epoch(train) [27][ 550/1196] lr: 8.0000e-04 eta: 1:49:51 time: 0.6122 data_time: 0.0035 memory: 2664 grad_norm: 0.0588 loss: 0.1542 loss_sem_seg: 0.1542 2023/05/13 05:58:02 - mmengine - INFO - Epoch(train) [27][ 600/1196] lr: 8.0000e-04 eta: 1:49:23 time: 0.6186 data_time: 0.0036 memory: 3132 grad_norm: 0.0599 loss: 0.1656 loss_sem_seg: 0.1656 2023/05/13 05:58:32 - mmengine - INFO - Epoch(train) [27][ 650/1196] lr: 8.0000e-04 eta: 1:48:54 time: 0.6139 data_time: 0.0036 memory: 2745 grad_norm: 0.0579 loss: 0.1605 loss_sem_seg: 0.1605 2023/05/13 05:59:03 - mmengine - INFO - Epoch(train) [27][ 700/1196] lr: 8.0000e-04 eta: 1:48:26 time: 0.6179 data_time: 0.0035 memory: 2746 grad_norm: 0.0608 loss: 0.1575 loss_sem_seg: 0.1575 2023/05/13 05:59:34 - mmengine - INFO - Epoch(train) [27][ 750/1196] lr: 8.0000e-04 eta: 1:47:58 time: 0.6106 data_time: 0.0035 memory: 2585 grad_norm: inf loss: 0.1554 loss_sem_seg: 0.1554 2023/05/13 06:00:04 - mmengine - INFO - Epoch(train) [27][ 800/1196] lr: 8.0000e-04 eta: 1:47:29 time: 0.5956 data_time: 0.0035 memory: 2667 grad_norm: 0.0631 loss: 0.1675 loss_sem_seg: 0.1675 2023/05/13 06:00:34 - mmengine - INFO - Epoch(train) [27][ 850/1196] lr: 8.0000e-04 eta: 1:47:01 time: 0.6118 data_time: 0.0036 memory: 2706 grad_norm: 0.0618 loss: 0.1655 loss_sem_seg: 0.1655 2023/05/13 06:01:04 - mmengine - INFO - Epoch(train) [27][ 900/1196] lr: 8.0000e-04 eta: 1:46:32 time: 0.5985 data_time: 0.0035 memory: 3116 grad_norm: 0.0605 loss: 0.1679 loss_sem_seg: 0.1679 2023/05/13 06:01:07 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:01:35 - mmengine - INFO - Epoch(train) [27][ 950/1196] lr: 8.0000e-04 eta: 1:46:04 time: 0.6166 data_time: 0.0035 memory: 3119 grad_norm: 0.0591 loss: 0.1641 loss_sem_seg: 0.1641 2023/05/13 06:02:05 - mmengine - INFO - Epoch(train) [27][1000/1196] lr: 8.0000e-04 eta: 1:45:36 time: 0.5975 data_time: 0.0035 memory: 2691 grad_norm: 0.0623 loss: 0.1600 loss_sem_seg: 0.1600 2023/05/13 06:02:36 - mmengine - INFO - Epoch(train) [27][1050/1196] lr: 8.0000e-04 eta: 1:45:07 time: 0.6228 data_time: 0.0036 memory: 2644 grad_norm: 0.0647 loss: 0.1576 loss_sem_seg: 0.1576 2023/05/13 06:03:06 - mmengine - INFO - Epoch(train) [27][1100/1196] lr: 8.0000e-04 eta: 1:44:39 time: 0.6028 data_time: 0.0036 memory: 2922 grad_norm: 0.0601 loss: 0.1672 loss_sem_seg: 0.1672 2023/05/13 06:03:37 - mmengine - INFO - Epoch(train) [27][1150/1196] lr: 8.0000e-04 eta: 1:44:11 time: 0.6136 data_time: 0.0035 memory: 2793 grad_norm: 0.0588 loss: 0.1650 loss_sem_seg: 0.1650 2023/05/13 06:04:05 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:04:05 - mmengine - INFO - Saving checkpoint at 27 epochs 2023/05/13 06:04:31 - mmengine - INFO - Epoch(val) [27][ 50/509] eta: 0:02:54 time: 0.3794 data_time: 0.0021 memory: 2860 2023/05/13 06:04:47 - mmengine - INFO - Epoch(val) [27][100/509] eta: 0:02:23 time: 0.3233 data_time: 0.0021 memory: 920 2023/05/13 06:05:03 - mmengine - INFO - Epoch(val) [27][150/509] eta: 0:02:01 time: 0.3143 data_time: 0.0021 memory: 918 2023/05/13 06:05:19 - mmengine - INFO - Epoch(val) [27][200/509] eta: 0:01:44 time: 0.3310 data_time: 0.0021 memory: 906 2023/05/13 06:05:35 - mmengine - INFO - Epoch(val) [27][250/509] eta: 0:01:26 time: 0.3190 data_time: 0.0021 memory: 931 2023/05/13 06:05:48 - mmengine - INFO - Epoch(val) [27][300/509] eta: 0:01:06 time: 0.2526 data_time: 0.0022 memory: 868 2023/05/13 06:06:02 - mmengine - INFO - Epoch(val) [27][350/509] eta: 0:00:49 time: 0.2775 data_time: 0.0021 memory: 893 2023/05/13 06:06:17 - mmengine - INFO - Epoch(val) [27][400/509] eta: 0:00:34 time: 0.3053 data_time: 0.0020 memory: 901 2023/05/13 06:06:32 - mmengine - INFO - Epoch(val) [27][450/509] eta: 0:00:18 time: 0.3063 data_time: 0.0021 memory: 915 2023/05/13 06:06:47 - mmengine - INFO - Epoch(val) [27][500/509] eta: 0:00:02 time: 0.2945 data_time: 0.0020 memory: 898 2023/05/13 06:07:05 - 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 | 0.9588 | 0.5210 | 0.7748 | 0.7377 | 0.5935 | 0.7830 | 0.8965 | 0.0718 | 0.9459 | 0.5124 | 0.8288 | 0.0164 | 0.9204 | 0.6850 | 0.8840 | 0.7008 | 0.7451 | 0.6587 | 0.5212 | 0.6714 | 0.9253 | 0.7370 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 06:07:05 - mmengine - INFO - Epoch(val) [27][509/509] car: 0.9588 bicycle: 0.5210 motorcycle: 0.7748 truck: 0.7377 bus: 0.5935 person: 0.7830 bicyclist: 0.8965 motorcyclist: 0.0718 road: 0.9459 parking: 0.5124 sidewalk: 0.8288 other-ground: 0.0164 building: 0.9204 fence: 0.6850 vegetation: 0.8840 trunck: 0.7008 terrian: 0.7451 pole: 0.6587 traffic-sign: 0.5212 miou: 0.6714 acc: 0.9253 acc_cls: 0.7370 data_time: 0.0020 time: 0.2999 2023/05/13 06:07:33 - mmengine - INFO - Epoch(train) [28][ 50/1196] lr: 8.0000e-04 eta: 1:43:15 time: 0.5491 data_time: 0.0043 memory: 2877 grad_norm: 0.0625 loss: 0.1652 loss_sem_seg: 0.1652 2023/05/13 06:08:01 - mmengine - INFO - Epoch(train) [28][ 100/1196] lr: 8.0000e-04 eta: 1:42:46 time: 0.5624 data_time: 0.0038 memory: 2719 grad_norm: 0.0591 loss: 0.1595 loss_sem_seg: 0.1595 2023/05/13 06:08:32 - mmengine - INFO - Epoch(train) [28][ 150/1196] lr: 8.0000e-04 eta: 1:42:18 time: 0.6230 data_time: 0.0035 memory: 2833 grad_norm: 0.0596 loss: 0.1477 loss_sem_seg: 0.1477 2023/05/13 06:09:03 - mmengine - INFO - Epoch(train) [28][ 200/1196] lr: 8.0000e-04 eta: 1:41:49 time: 0.6149 data_time: 0.0036 memory: 2969 grad_norm: 0.0614 loss: 0.1667 loss_sem_seg: 0.1667 2023/05/13 06:09:34 - mmengine - INFO - Epoch(train) [28][ 250/1196] lr: 8.0000e-04 eta: 1:41:21 time: 0.6168 data_time: 0.0037 memory: 2863 grad_norm: 0.0631 loss: 0.1695 loss_sem_seg: 0.1695 2023/05/13 06:10:04 - mmengine - INFO - Epoch(train) [28][ 300/1196] lr: 8.0000e-04 eta: 1:40:53 time: 0.6151 data_time: 0.0035 memory: 3020 grad_norm: 0.0610 loss: 0.1592 loss_sem_seg: 0.1592 2023/05/13 06:10:34 - mmengine - INFO - Epoch(train) [28][ 350/1196] lr: 8.0000e-04 eta: 1:40:24 time: 0.6024 data_time: 0.0038 memory: 2739 grad_norm: inf loss: 0.1596 loss_sem_seg: 0.1596 2023/05/13 06:11:05 - mmengine - INFO - Epoch(train) [28][ 400/1196] lr: 8.0000e-04 eta: 1:39:56 time: 0.6044 data_time: 0.0036 memory: 2684 grad_norm: 0.0629 loss: 0.1497 loss_sem_seg: 0.1497 2023/05/13 06:11:35 - mmengine - INFO - Epoch(train) [28][ 450/1196] lr: 8.0000e-04 eta: 1:39:27 time: 0.5997 data_time: 0.0035 memory: 2873 grad_norm: 0.0621 loss: 0.1538 loss_sem_seg: 0.1538 2023/05/13 06:12:02 - mmengine - INFO - Epoch(train) [28][ 500/1196] lr: 8.0000e-04 eta: 1:38:58 time: 0.5492 data_time: 0.0035 memory: 3021 grad_norm: 0.0592 loss: 0.1650 loss_sem_seg: 0.1650 2023/05/13 06:12:29 - mmengine - INFO - Epoch(train) [28][ 550/1196] lr: 8.0000e-04 eta: 1:38:28 time: 0.5289 data_time: 0.0037 memory: 2813 grad_norm: 0.0648 loss: 0.1618 loss_sem_seg: 0.1618 2023/05/13 06:12:55 - mmengine - INFO - Epoch(train) [28][ 600/1196] lr: 8.0000e-04 eta: 1:37:58 time: 0.5265 data_time: 0.0036 memory: 2689 grad_norm: 0.0595 loss: 0.1626 loss_sem_seg: 0.1626 2023/05/13 06:13:22 - mmengine - INFO - Epoch(train) [28][ 650/1196] lr: 8.0000e-04 eta: 1:37:29 time: 0.5350 data_time: 0.0035 memory: 2866 grad_norm: 0.0623 loss: 0.1610 loss_sem_seg: 0.1610 2023/05/13 06:13:48 - mmengine - INFO - Epoch(train) [28][ 700/1196] lr: 8.0000e-04 eta: 1:36:59 time: 0.5298 data_time: 0.0033 memory: 2785 grad_norm: 0.0564 loss: 0.1664 loss_sem_seg: 0.1664 2023/05/13 06:13:52 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:14:15 - mmengine - INFO - Epoch(train) [28][ 750/1196] lr: 8.0000e-04 eta: 1:36:29 time: 0.5336 data_time: 0.0035 memory: 2795 grad_norm: 0.0607 loss: 0.1588 loss_sem_seg: 0.1588 2023/05/13 06:14:42 - mmengine - INFO - Epoch(train) [28][ 800/1196] lr: 8.0000e-04 eta: 1:36:00 time: 0.5371 data_time: 0.0035 memory: 2715 grad_norm: 0.0595 loss: 0.1578 loss_sem_seg: 0.1578 2023/05/13 06:15:08 - mmengine - INFO - Epoch(train) [28][ 850/1196] lr: 8.0000e-04 eta: 1:35:30 time: 0.5313 data_time: 0.0034 memory: 2672 grad_norm: 0.0611 loss: 0.1532 loss_sem_seg: 0.1532 2023/05/13 06:15:35 - mmengine - INFO - Epoch(train) [28][ 900/1196] lr: 8.0000e-04 eta: 1:35:01 time: 0.5368 data_time: 0.0034 memory: 2743 grad_norm: 0.0617 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/13 06:16:02 - mmengine - INFO - Epoch(train) [28][ 950/1196] lr: 8.0000e-04 eta: 1:34:31 time: 0.5394 data_time: 0.0035 memory: 2939 grad_norm: 0.0608 loss: 0.1496 loss_sem_seg: 0.1496 2023/05/13 06:16:29 - mmengine - INFO - Epoch(train) [28][1000/1196] lr: 8.0000e-04 eta: 1:34:02 time: 0.5307 data_time: 0.0034 memory: 3182 grad_norm: 0.0593 loss: 0.1550 loss_sem_seg: 0.1550 2023/05/13 06:16:55 - mmengine - INFO - Epoch(train) [28][1050/1196] lr: 8.0000e-04 eta: 1:33:32 time: 0.5231 data_time: 0.0036 memory: 2805 grad_norm: 0.0603 loss: 0.1579 loss_sem_seg: 0.1579 2023/05/13 06:17:21 - mmengine - INFO - Epoch(train) [28][1100/1196] lr: 8.0000e-04 eta: 1:33:03 time: 0.5317 data_time: 0.0034 memory: 2839 grad_norm: 0.0604 loss: 0.1661 loss_sem_seg: 0.1661 2023/05/13 06:17:48 - mmengine - INFO - Epoch(train) [28][1150/1196] lr: 8.0000e-04 eta: 1:32:33 time: 0.5291 data_time: 0.0034 memory: 2723 grad_norm: 0.0630 loss: 0.1668 loss_sem_seg: 0.1668 2023/05/13 06:18:13 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:18:13 - mmengine - INFO - Saving checkpoint at 28 epochs 2023/05/13 06:18:36 - mmengine - INFO - Epoch(val) [28][ 50/509] eta: 0:02:31 time: 0.3308 data_time: 0.0022 memory: 2819 2023/05/13 06:18:51 - mmengine - INFO - Epoch(val) [28][100/509] eta: 0:02:07 time: 0.2951 data_time: 0.0021 memory: 920 2023/05/13 06:19:05 - mmengine - INFO - Epoch(val) [28][150/509] eta: 0:01:49 time: 0.2869 data_time: 0.0021 memory: 918 2023/05/13 06:19:19 - mmengine - INFO - Epoch(val) [28][200/509] eta: 0:01:33 time: 0.2912 data_time: 0.0021 memory: 906 2023/05/13 06:19:36 - mmengine - INFO - Epoch(val) [28][250/509] eta: 0:01:18 time: 0.3211 data_time: 0.0021 memory: 931 2023/05/13 06:19:47 - mmengine - INFO - Epoch(val) [28][300/509] eta: 0:01:01 time: 0.2374 data_time: 0.0021 memory: 868 2023/05/13 06:20:00 - mmengine - INFO - Epoch(val) [28][350/509] eta: 0:00:45 time: 0.2600 data_time: 0.0020 memory: 893 2023/05/13 06:20:14 - mmengine - INFO - Epoch(val) [28][400/509] eta: 0:00:31 time: 0.2792 data_time: 0.0020 memory: 901 2023/05/13 06:20:28 - mmengine - INFO - Epoch(val) [28][450/509] eta: 0:00:16 time: 0.2692 data_time: 0.0021 memory: 915 2023/05/13 06:20:42 - mmengine - INFO - Epoch(val) [28][500/509] eta: 0:00:02 time: 0.2759 data_time: 0.0021 memory: 898 2023/05/13 06:21:01 - 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 | 0.9703 | 0.5040 | 0.7901 | 0.7852 | 0.6982 | 0.7852 | 0.8920 | 0.1123 | 0.9428 | 0.4822 | 0.8236 | 0.0237 | 0.9199 | 0.6824 | 0.8806 | 0.6762 | 0.7381 | 0.6581 | 0.5182 | 0.6781 | 0.9236 | 0.7522 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 06:21:01 - mmengine - INFO - Epoch(val) [28][509/509] car: 0.9703 bicycle: 0.5040 motorcycle: 0.7901 truck: 0.7852 bus: 0.6982 person: 0.7852 bicyclist: 0.8920 motorcyclist: 0.1123 road: 0.9428 parking: 0.4822 sidewalk: 0.8236 other-ground: 0.0237 building: 0.9199 fence: 0.6824 vegetation: 0.8806 trunck: 0.6762 terrian: 0.7381 pole: 0.6581 traffic-sign: 0.5182 miou: 0.6781 acc: 0.9236 acc_cls: 0.7522 data_time: 0.0020 time: 0.3016 2023/05/13 06:21:30 - mmengine - INFO - Epoch(train) [29][ 50/1196] lr: 8.0000e-04 eta: 1:31:37 time: 0.5730 data_time: 0.0042 memory: 2681 grad_norm: 0.0595 loss: 0.1615 loss_sem_seg: 0.1615 2023/05/13 06:21:59 - mmengine - INFO - Epoch(train) [29][ 100/1196] lr: 8.0000e-04 eta: 1:31:08 time: 0.5790 data_time: 0.0033 memory: 2867 grad_norm: 0.0639 loss: 0.1446 loss_sem_seg: 0.1446 2023/05/13 06:22:27 - mmengine - INFO - Epoch(train) [29][ 150/1196] lr: 8.0000e-04 eta: 1:30:39 time: 0.5747 data_time: 0.0033 memory: 2801 grad_norm: 0.0637 loss: 0.1601 loss_sem_seg: 0.1601 2023/05/13 06:22:56 - mmengine - INFO - Epoch(train) [29][ 200/1196] lr: 8.0000e-04 eta: 1:30:10 time: 0.5716 data_time: 0.0034 memory: 2947 grad_norm: 0.0591 loss: 0.1580 loss_sem_seg: 0.1580 2023/05/13 06:23:24 - mmengine - INFO - Epoch(train) [29][ 250/1196] lr: 8.0000e-04 eta: 1:29:41 time: 0.5591 data_time: 0.0035 memory: 2746 grad_norm: 0.0627 loss: 0.1664 loss_sem_seg: 0.1664 2023/05/13 06:23:52 - mmengine - INFO - Epoch(train) [29][ 300/1196] lr: 8.0000e-04 eta: 1:29:12 time: 0.5535 data_time: 0.0034 memory: 2857 grad_norm: 0.0603 loss: 0.1457 loss_sem_seg: 0.1457 2023/05/13 06:24:20 - mmengine - INFO - Epoch(train) [29][ 350/1196] lr: 8.0000e-04 eta: 1:28:43 time: 0.5658 data_time: 0.0034 memory: 2765 grad_norm: 0.0587 loss: 0.1539 loss_sem_seg: 0.1539 2023/05/13 06:24:48 - mmengine - INFO - Epoch(train) [29][ 400/1196] lr: 8.0000e-04 eta: 1:28:14 time: 0.5691 data_time: 0.0035 memory: 2786 grad_norm: 0.0657 loss: 0.1590 loss_sem_seg: 0.1590 2023/05/13 06:25:17 - mmengine - INFO - Epoch(train) [29][ 450/1196] lr: 8.0000e-04 eta: 1:27:45 time: 0.5645 data_time: 0.0034 memory: 2932 grad_norm: 0.0665 loss: 0.1694 loss_sem_seg: 0.1694 2023/05/13 06:25:45 - mmengine - INFO - Epoch(train) [29][ 500/1196] lr: 8.0000e-04 eta: 1:27:16 time: 0.5621 data_time: 0.0033 memory: 2834 grad_norm: 0.0665 loss: 0.1603 loss_sem_seg: 0.1603 2023/05/13 06:25:52 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:26:14 - mmengine - INFO - Epoch(train) [29][ 550/1196] lr: 8.0000e-04 eta: 1:26:47 time: 0.5790 data_time: 0.0034 memory: 2810 grad_norm: 0.0586 loss: 0.1558 loss_sem_seg: 0.1558 2023/05/13 06:26:42 - mmengine - INFO - Epoch(train) [29][ 600/1196] lr: 8.0000e-04 eta: 1:26:18 time: 0.5564 data_time: 0.0033 memory: 2977 grad_norm: 0.0604 loss: 0.1599 loss_sem_seg: 0.1599 2023/05/13 06:27:09 - mmengine - INFO - Epoch(train) [29][ 650/1196] lr: 8.0000e-04 eta: 1:25:49 time: 0.5567 data_time: 0.0035 memory: 2904 grad_norm: 0.0616 loss: 0.1509 loss_sem_seg: 0.1509 2023/05/13 06:27:40 - mmengine - INFO - Epoch(train) [29][ 700/1196] lr: 8.0000e-04 eta: 1:25:20 time: 0.6117 data_time: 0.0035 memory: 2774 grad_norm: 0.0585 loss: 0.1571 loss_sem_seg: 0.1571 2023/05/13 06:28:11 - mmengine - INFO - Epoch(train) [29][ 750/1196] lr: 8.0000e-04 eta: 1:24:52 time: 0.6223 data_time: 0.0035 memory: 2937 grad_norm: 0.0620 loss: 0.1500 loss_sem_seg: 0.1500 2023/05/13 06:28:41 - mmengine - INFO - Epoch(train) [29][ 800/1196] lr: 8.0000e-04 eta: 1:24:23 time: 0.5984 data_time: 0.0035 memory: 2901 grad_norm: 0.0639 loss: 0.1611 loss_sem_seg: 0.1611 2023/05/13 06:29:11 - mmengine - INFO - Epoch(train) [29][ 850/1196] lr: 8.0000e-04 eta: 1:23:55 time: 0.6066 data_time: 0.0035 memory: 2839 grad_norm: 0.0604 loss: 0.1650 loss_sem_seg: 0.1650 2023/05/13 06:29:42 - mmengine - INFO - Epoch(train) [29][ 900/1196] lr: 8.0000e-04 eta: 1:23:26 time: 0.6155 data_time: 0.0040 memory: 2932 grad_norm: 0.0619 loss: 0.1664 loss_sem_seg: 0.1664 2023/05/13 06:30:12 - mmengine - INFO - Epoch(train) [29][ 950/1196] lr: 8.0000e-04 eta: 1:22:58 time: 0.6066 data_time: 0.0036 memory: 2759 grad_norm: 0.0597 loss: 0.1578 loss_sem_seg: 0.1578 2023/05/13 06:30:43 - mmengine - INFO - Epoch(train) [29][1000/1196] lr: 8.0000e-04 eta: 1:22:29 time: 0.6019 data_time: 0.0034 memory: 2872 grad_norm: 0.0548 loss: 0.1546 loss_sem_seg: 0.1546 2023/05/13 06:31:13 - mmengine - INFO - Epoch(train) [29][1050/1196] lr: 8.0000e-04 eta: 1:22:01 time: 0.6018 data_time: 0.0035 memory: 2691 grad_norm: 0.0602 loss: 0.1623 loss_sem_seg: 0.1623 2023/05/13 06:31:43 - mmengine - INFO - Epoch(train) [29][1100/1196] lr: 8.0000e-04 eta: 1:21:32 time: 0.6131 data_time: 0.0036 memory: 2866 grad_norm: 0.0614 loss: 0.1556 loss_sem_seg: 0.1556 2023/05/13 06:32:14 - mmengine - INFO - Epoch(train) [29][1150/1196] lr: 8.0000e-04 eta: 1:21:04 time: 0.6121 data_time: 0.0035 memory: 3087 grad_norm: 0.0661 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/13 06:32:42 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:32:42 - mmengine - INFO - Saving checkpoint at 29 epochs 2023/05/13 06:33:08 - mmengine - INFO - Epoch(val) [29][ 50/509] eta: 0:02:59 time: 0.3902 data_time: 0.0021 memory: 2785 2023/05/13 06:33:24 - mmengine - INFO - Epoch(val) [29][100/509] eta: 0:02:27 time: 0.3301 data_time: 0.0021 memory: 920 2023/05/13 06:33:41 - mmengine - INFO - Epoch(val) [29][150/509] eta: 0:02:05 time: 0.3322 data_time: 0.0022 memory: 918 2023/05/13 06:33:57 - mmengine - INFO - Epoch(val) [29][200/509] eta: 0:01:46 time: 0.3265 data_time: 0.0022 memory: 906 2023/05/13 06:34:15 - mmengine - INFO - Epoch(val) [29][250/509] eta: 0:01:30 time: 0.3635 data_time: 0.0020 memory: 931 2023/05/13 06:34:30 - mmengine - INFO - Epoch(val) [29][300/509] eta: 0:01:10 time: 0.2901 data_time: 0.0021 memory: 868 2023/05/13 06:34:46 - mmengine - INFO - Epoch(val) [29][350/509] eta: 0:00:53 time: 0.3320 data_time: 0.0022 memory: 893 2023/05/13 06:35:03 - mmengine - INFO - Epoch(val) [29][400/509] eta: 0:00:36 time: 0.3317 data_time: 0.0021 memory: 901 2023/05/13 06:35:20 - mmengine - INFO - Epoch(val) [29][450/509] eta: 0:00:19 time: 0.3419 data_time: 0.0020 memory: 915 2023/05/13 06:35:36 - mmengine - INFO - Epoch(val) [29][500/509] eta: 0:00:03 time: 0.3260 data_time: 0.0020 memory: 898 2023/05/13 06:35:56 - 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 | 0.9636 | 0.5171 | 0.7990 | 0.8312 | 0.6350 | 0.7809 | 0.9005 | 0.0647 | 0.9447 | 0.5154 | 0.8275 | 0.0152 | 0.9194 | 0.6846 | 0.8799 | 0.6787 | 0.7343 | 0.6586 | 0.5069 | 0.6767 | 0.9237 | 0.7411 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 06:35:56 - mmengine - INFO - Epoch(val) [29][509/509] car: 0.9636 bicycle: 0.5171 motorcycle: 0.7990 truck: 0.8312 bus: 0.6350 person: 0.7809 bicyclist: 0.9005 motorcyclist: 0.0647 road: 0.9447 parking: 0.5154 sidewalk: 0.8275 other-ground: 0.0152 building: 0.9194 fence: 0.6846 vegetation: 0.8799 trunck: 0.6787 terrian: 0.7343 pole: 0.6586 traffic-sign: 0.5069 miou: 0.6767 acc: 0.9237 acc_cls: 0.7411 data_time: 0.0021 time: 0.3353 2023/05/13 06:36:27 - mmengine - INFO - Epoch(train) [30][ 50/1196] lr: 8.0000e-04 eta: 1:20:09 time: 0.6055 data_time: 0.0041 memory: 3083 grad_norm: 0.0590 loss: 0.1621 loss_sem_seg: 0.1621 2023/05/13 06:36:57 - mmengine - INFO - Epoch(train) [30][ 100/1196] lr: 8.0000e-04 eta: 1:19:40 time: 0.6053 data_time: 0.0036 memory: 2743 grad_norm: 0.0585 loss: 0.1572 loss_sem_seg: 0.1572 2023/05/13 06:37:27 - mmengine - INFO - Epoch(train) [30][ 150/1196] lr: 8.0000e-04 eta: 1:19:12 time: 0.5921 data_time: 0.0035 memory: 2817 grad_norm: 0.0615 loss: 0.1549 loss_sem_seg: 0.1549 2023/05/13 06:37:57 - mmengine - INFO - Epoch(train) [30][ 200/1196] lr: 8.0000e-04 eta: 1:18:43 time: 0.6057 data_time: 0.0036 memory: 2674 grad_norm: 0.0641 loss: 0.1546 loss_sem_seg: 0.1546 2023/05/13 06:38:27 - mmengine - INFO - Epoch(train) [30][ 250/1196] lr: 8.0000e-04 eta: 1:18:14 time: 0.6076 data_time: 0.0034 memory: 2686 grad_norm: 0.0598 loss: 0.1583 loss_sem_seg: 0.1583 2023/05/13 06:38:58 - mmengine - INFO - Epoch(train) [30][ 300/1196] lr: 8.0000e-04 eta: 1:17:46 time: 0.6200 data_time: 0.0037 memory: 2976 grad_norm: 0.0604 loss: 0.1601 loss_sem_seg: 0.1601 2023/05/13 06:39:08 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:39:29 - mmengine - INFO - Epoch(train) [30][ 350/1196] lr: 8.0000e-04 eta: 1:17:17 time: 0.6075 data_time: 0.0035 memory: 2775 grad_norm: 0.0610 loss: 0.1538 loss_sem_seg: 0.1538 2023/05/13 06:40:00 - mmengine - INFO - Epoch(train) [30][ 400/1196] lr: 8.0000e-04 eta: 1:16:49 time: 0.6198 data_time: 0.0034 memory: 2888 grad_norm: 0.0628 loss: 0.1529 loss_sem_seg: 0.1529 2023/05/13 06:40:29 - mmengine - INFO - Epoch(train) [30][ 450/1196] lr: 8.0000e-04 eta: 1:16:20 time: 0.5940 data_time: 0.0034 memory: 2930 grad_norm: 0.0577 loss: 0.1575 loss_sem_seg: 0.1575 2023/05/13 06:41:00 - mmengine - INFO - Epoch(train) [30][ 500/1196] lr: 8.0000e-04 eta: 1:15:52 time: 0.6091 data_time: 0.0036 memory: 2920 grad_norm: 0.0608 loss: 0.1499 loss_sem_seg: 0.1499 2023/05/13 06:41:30 - mmengine - INFO - Epoch(train) [30][ 550/1196] lr: 8.0000e-04 eta: 1:15:23 time: 0.6111 data_time: 0.0035 memory: 2748 grad_norm: 0.0630 loss: 0.1610 loss_sem_seg: 0.1610 2023/05/13 06:42:01 - mmengine - INFO - Epoch(train) [30][ 600/1196] lr: 8.0000e-04 eta: 1:14:55 time: 0.6084 data_time: 0.0034 memory: 2967 grad_norm: 0.0592 loss: 0.1510 loss_sem_seg: 0.1510 2023/05/13 06:42:28 - mmengine - INFO - Epoch(train) [30][ 650/1196] lr: 8.0000e-04 eta: 1:14:25 time: 0.5439 data_time: 0.0035 memory: 2834 grad_norm: 0.0599 loss: 0.1593 loss_sem_seg: 0.1593 2023/05/13 06:42:56 - mmengine - INFO - Epoch(train) [30][ 700/1196] lr: 8.0000e-04 eta: 1:13:56 time: 0.5547 data_time: 0.0035 memory: 2924 grad_norm: 0.0568 loss: 0.1612 loss_sem_seg: 0.1612 2023/05/13 06:43:22 - mmengine - INFO - Epoch(train) [30][ 750/1196] lr: 8.0000e-04 eta: 1:13:27 time: 0.5342 data_time: 0.0037 memory: 2774 grad_norm: 0.0621 loss: 0.1526 loss_sem_seg: 0.1526 2023/05/13 06:43:48 - mmengine - INFO - Epoch(train) [30][ 800/1196] lr: 8.0000e-04 eta: 1:12:57 time: 0.5019 data_time: 0.0038 memory: 2823 grad_norm: 0.0609 loss: 0.1553 loss_sem_seg: 0.1553 2023/05/13 06:44:12 - mmengine - INFO - Epoch(train) [30][ 850/1196] lr: 8.0000e-04 eta: 1:12:27 time: 0.4950 data_time: 0.0035 memory: 2910 grad_norm: 0.0628 loss: 0.1433 loss_sem_seg: 0.1433 2023/05/13 06:44:38 - mmengine - INFO - Epoch(train) [30][ 900/1196] lr: 8.0000e-04 eta: 1:11:58 time: 0.5062 data_time: 0.0034 memory: 2845 grad_norm: 0.0644 loss: 0.1552 loss_sem_seg: 0.1552 2023/05/13 06:45:02 - mmengine - INFO - Epoch(train) [30][ 950/1196] lr: 8.0000e-04 eta: 1:11:28 time: 0.4950 data_time: 0.0034 memory: 2877 grad_norm: 0.0617 loss: 0.1566 loss_sem_seg: 0.1566 2023/05/13 06:45:27 - mmengine - INFO - Epoch(train) [30][1000/1196] lr: 8.0000e-04 eta: 1:10:58 time: 0.4957 data_time: 0.0035 memory: 2806 grad_norm: 0.0593 loss: 0.1510 loss_sem_seg: 0.1510 2023/05/13 06:45:52 - mmengine - INFO - Epoch(train) [30][1050/1196] lr: 8.0000e-04 eta: 1:10:28 time: 0.4888 data_time: 0.0035 memory: 3003 grad_norm: 0.0595 loss: 0.1594 loss_sem_seg: 0.1594 2023/05/13 06:46:17 - mmengine - INFO - Epoch(train) [30][1100/1196] lr: 8.0000e-04 eta: 1:09:59 time: 0.5160 data_time: 0.0036 memory: 2660 grad_norm: 0.0564 loss: 0.1478 loss_sem_seg: 0.1478 2023/05/13 06:46:44 - mmengine - INFO - Epoch(train) [30][1150/1196] lr: 8.0000e-04 eta: 1:09:29 time: 0.5383 data_time: 0.0034 memory: 2717 grad_norm: 0.0599 loss: 0.1453 loss_sem_seg: 0.1453 2023/05/13 06:47:09 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:47:09 - mmengine - INFO - Saving checkpoint at 30 epochs 2023/05/13 06:47:32 - mmengine - INFO - Epoch(val) [30][ 50/509] eta: 0:02:34 time: 0.3362 data_time: 0.0021 memory: 2837 2023/05/13 06:47:46 - mmengine - INFO - Epoch(val) [30][100/509] eta: 0:02:04 time: 0.2750 data_time: 0.0021 memory: 920 2023/05/13 06:48:00 - mmengine - INFO - Epoch(val) [30][150/509] eta: 0:01:46 time: 0.2788 data_time: 0.0020 memory: 918 2023/05/13 06:48:15 - mmengine - INFO - Epoch(val) [30][200/509] eta: 0:01:32 time: 0.3055 data_time: 0.0021 memory: 906 2023/05/13 06:48:31 - mmengine - INFO - Epoch(val) [30][250/509] eta: 0:01:18 time: 0.3296 data_time: 0.0021 memory: 931 2023/05/13 06:48:44 - mmengine - INFO - Epoch(val) [30][300/509] eta: 0:01:01 time: 0.2519 data_time: 0.0021 memory: 868 2023/05/13 06:48:58 - mmengine - INFO - Epoch(val) [30][350/509] eta: 0:00:46 time: 0.2716 data_time: 0.0020 memory: 893 2023/05/13 06:49:13 - mmengine - INFO - Epoch(val) [30][400/509] eta: 0:00:32 time: 0.3049 data_time: 0.0020 memory: 901 2023/05/13 06:49:29 - mmengine - INFO - Epoch(val) [30][450/509] eta: 0:00:17 time: 0.3191 data_time: 0.0021 memory: 915 2023/05/13 06:49:44 - mmengine - INFO - Epoch(val) [30][500/509] eta: 0:00:02 time: 0.2985 data_time: 0.0021 memory: 898 2023/05/13 06:50:04 - 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 | 0.9673 | 0.5201 | 0.8069 | 0.7599 | 0.6949 | 0.7889 | 0.8929 | 0.0492 | 0.9444 | 0.4995 | 0.8253 | 0.0086 | 0.9162 | 0.6706 | 0.8752 | 0.6846 | 0.7208 | 0.6608 | 0.5194 | 0.6740 | 0.9213 | 0.7405 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 06:50:04 - mmengine - INFO - Epoch(val) [30][509/509] car: 0.9673 bicycle: 0.5201 motorcycle: 0.8069 truck: 0.7599 bus: 0.6949 person: 0.7889 bicyclist: 0.8929 motorcyclist: 0.0492 road: 0.9444 parking: 0.4995 sidewalk: 0.8253 other-ground: 0.0086 building: 0.9162 fence: 0.6706 vegetation: 0.8752 trunck: 0.6846 terrian: 0.7208 pole: 0.6608 traffic-sign: 0.5194 miou: 0.6740 acc: 0.9213 acc_cls: 0.7405 data_time: 0.0021 time: 0.3163 2023/05/13 06:50:35 - mmengine - INFO - Epoch(train) [31][ 50/1196] lr: 8.0000e-04 eta: 1:08:34 time: 0.6308 data_time: 0.0043 memory: 2691 grad_norm: 0.0635 loss: 0.1626 loss_sem_seg: 0.1626 2023/05/13 06:51:06 - mmengine - INFO - Epoch(train) [31][ 100/1196] lr: 8.0000e-04 eta: 1:08:06 time: 0.6065 data_time: 0.0035 memory: 2838 grad_norm: 0.0616 loss: 0.1499 loss_sem_seg: 0.1499 2023/05/13 06:51:18 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 06:51:36 - mmengine - INFO - Epoch(train) [31][ 150/1196] lr: 8.0000e-04 eta: 1:07:37 time: 0.6136 data_time: 0.0037 memory: 3133 grad_norm: 0.0582 loss: 0.1511 loss_sem_seg: 0.1511 2023/05/13 06:52:07 - mmengine - INFO - Epoch(train) [31][ 200/1196] lr: 8.0000e-04 eta: 1:07:09 time: 0.6124 data_time: 0.0036 memory: 2962 grad_norm: 0.0587 loss: 0.1456 loss_sem_seg: 0.1456 2023/05/13 06:52:37 - mmengine - INFO - Epoch(train) [31][ 250/1196] lr: 8.0000e-04 eta: 1:06:40 time: 0.6053 data_time: 0.0036 memory: 2800 grad_norm: 0.0587 loss: 0.1559 loss_sem_seg: 0.1559 2023/05/13 06:53:07 - mmengine - INFO - Epoch(train) [31][ 300/1196] lr: 8.0000e-04 eta: 1:06:11 time: 0.6021 data_time: 0.0036 memory: 2688 grad_norm: 0.0609 loss: 0.1569 loss_sem_seg: 0.1569 2023/05/13 06:53:38 - mmengine - INFO - Epoch(train) [31][ 350/1196] lr: 8.0000e-04 eta: 1:05:43 time: 0.6095 data_time: 0.0037 memory: 2711 grad_norm: 0.0671 loss: 0.1610 loss_sem_seg: 0.1610 2023/05/13 06:54:07 - mmengine - INFO - Epoch(train) [31][ 400/1196] lr: 8.0000e-04 eta: 1:05:14 time: 0.5879 data_time: 0.0036 memory: 2814 grad_norm: 0.0611 loss: 0.1481 loss_sem_seg: 0.1481 2023/05/13 06:54:37 - mmengine - INFO - Epoch(train) [31][ 450/1196] lr: 8.0000e-04 eta: 1:04:45 time: 0.5961 data_time: 0.0037 memory: 2921 grad_norm: 0.0604 loss: 0.1511 loss_sem_seg: 0.1511 2023/05/13 06:55:08 - mmengine - INFO - Epoch(train) [31][ 500/1196] lr: 8.0000e-04 eta: 1:04:17 time: 0.6098 data_time: 0.0034 memory: 2883 grad_norm: 0.0664 loss: 0.1612 loss_sem_seg: 0.1612 2023/05/13 06:55:38 - mmengine - INFO - Epoch(train) [31][ 550/1196] lr: 8.0000e-04 eta: 1:03:48 time: 0.6035 data_time: 0.0035 memory: 2838 grad_norm: 0.0649 loss: 0.1559 loss_sem_seg: 0.1559 2023/05/13 06:56:08 - mmengine - INFO - Epoch(train) [31][ 600/1196] lr: 8.0000e-04 eta: 1:03:19 time: 0.6100 data_time: 0.0035 memory: 2803 grad_norm: 0.0609 loss: 0.1469 loss_sem_seg: 0.1469 2023/05/13 06:56:39 - mmengine - INFO - Epoch(train) [31][ 650/1196] lr: 8.0000e-04 eta: 1:02:51 time: 0.6095 data_time: 0.0035 memory: 2842 grad_norm: 0.0586 loss: 0.1513 loss_sem_seg: 0.1513 2023/05/13 06:57:09 - mmengine - INFO - Epoch(train) [31][ 700/1196] lr: 8.0000e-04 eta: 1:02:22 time: 0.6113 data_time: 0.0035 memory: 2747 grad_norm: 0.0620 loss: 0.1522 loss_sem_seg: 0.1522 2023/05/13 06:57:40 - mmengine - INFO - Epoch(train) [31][ 750/1196] lr: 8.0000e-04 eta: 1:01:53 time: 0.6069 data_time: 0.0035 memory: 2739 grad_norm: 0.0653 loss: 0.1551 loss_sem_seg: 0.1551 2023/05/13 06:58:10 - mmengine - INFO - Epoch(train) [31][ 800/1196] lr: 8.0000e-04 eta: 1:01:25 time: 0.6153 data_time: 0.0036 memory: 2735 grad_norm: 0.0623 loss: 0.1541 loss_sem_seg: 0.1541 2023/05/13 06:58:41 - mmengine - INFO - Epoch(train) [31][ 850/1196] lr: 8.0000e-04 eta: 1:00:56 time: 0.6126 data_time: 0.0036 memory: 2919 grad_norm: 0.0634 loss: 0.1563 loss_sem_seg: 0.1563 2023/05/13 06:59:11 - mmengine - INFO - Epoch(train) [31][ 900/1196] lr: 8.0000e-04 eta: 1:00:28 time: 0.6081 data_time: 0.0034 memory: 2726 grad_norm: inf loss: 0.1545 loss_sem_seg: 0.1545 2023/05/13 06:59:41 - mmengine - INFO - Epoch(train) [31][ 950/1196] lr: 8.0000e-04 eta: 0:59:59 time: 0.5994 data_time: 0.0035 memory: 2866 grad_norm: 0.0602 loss: 0.1472 loss_sem_seg: 0.1472 2023/05/13 07:00:12 - mmengine - INFO - Epoch(train) [31][1000/1196] lr: 8.0000e-04 eta: 0:59:30 time: 0.6169 data_time: 0.0035 memory: 2926 grad_norm: 0.0602 loss: 0.1471 loss_sem_seg: 0.1471 2023/05/13 07:00:43 - mmengine - INFO - Epoch(train) [31][1050/1196] lr: 8.0000e-04 eta: 0:59:02 time: 0.6203 data_time: 0.0037 memory: 2844 grad_norm: 0.0589 loss: 0.1435 loss_sem_seg: 0.1435 2023/05/13 07:01:13 - mmengine - INFO - Epoch(train) [31][1100/1196] lr: 8.0000e-04 eta: 0:58:33 time: 0.5946 data_time: 0.0035 memory: 2906 grad_norm: 0.0582 loss: 0.1469 loss_sem_seg: 0.1469 2023/05/13 07:01:24 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:01:41 - mmengine - INFO - Epoch(train) [31][1150/1196] lr: 8.0000e-04 eta: 0:58:04 time: 0.5597 data_time: 0.0037 memory: 2982 grad_norm: 0.0589 loss: 0.1431 loss_sem_seg: 0.1431 2023/05/13 07:02:07 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:02:07 - mmengine - INFO - Saving checkpoint at 31 epochs 2023/05/13 07:02:31 - mmengine - INFO - Epoch(val) [31][ 50/509] eta: 0:02:45 time: 0.3607 data_time: 0.0021 memory: 2874 2023/05/13 07:02:46 - mmengine - INFO - Epoch(val) [31][100/509] eta: 0:02:15 time: 0.3003 data_time: 0.0021 memory: 920 2023/05/13 07:03:01 - mmengine - INFO - Epoch(val) [31][150/509] eta: 0:01:53 time: 0.2898 data_time: 0.0021 memory: 918 2023/05/13 07:03:15 - mmengine - INFO - Epoch(val) [31][200/509] eta: 0:01:35 time: 0.2917 data_time: 0.0021 memory: 906 2023/05/13 07:03:32 - mmengine - INFO - Epoch(val) [31][250/509] eta: 0:01:21 time: 0.3378 data_time: 0.0020 memory: 931 2023/05/13 07:03:45 - mmengine - INFO - Epoch(val) [31][300/509] eta: 0:01:04 time: 0.2660 data_time: 0.0020 memory: 868 2023/05/13 07:04:00 - mmengine - INFO - Epoch(val) [31][350/509] eta: 0:00:48 time: 0.2882 data_time: 0.0021 memory: 893 2023/05/13 07:04:15 - mmengine - INFO - Epoch(val) [31][400/509] eta: 0:00:33 time: 0.3096 data_time: 0.0021 memory: 901 2023/05/13 07:04:30 - mmengine - INFO - Epoch(val) [31][450/509] eta: 0:00:17 time: 0.2950 data_time: 0.0021 memory: 915 2023/05/13 07:04:44 - mmengine - INFO - Epoch(val) [31][500/509] eta: 0:00:02 time: 0.2794 data_time: 0.0021 memory: 898 2023/05/13 07:05:04 - 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 | 0.5098 | 0.8137 | 0.8066 | 0.7622 | 0.7845 | 0.8706 | 0.0855 | 0.9459 | 0.5124 | 0.8266 | 0.0101 | 0.9192 | 0.6850 | 0.8728 | 0.6628 | 0.7175 | 0.6603 | 0.5100 | 0.6804 | 0.9217 | 0.7467 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 07:05:04 - mmengine - INFO - Epoch(val) [31][509/509] car: 0.9727 bicycle: 0.5098 motorcycle: 0.8137 truck: 0.8066 bus: 0.7622 person: 0.7845 bicyclist: 0.8706 motorcyclist: 0.0855 road: 0.9459 parking: 0.5124 sidewalk: 0.8266 other-ground: 0.0101 building: 0.9192 fence: 0.6850 vegetation: 0.8728 trunck: 0.6628 terrian: 0.7175 pole: 0.6603 traffic-sign: 0.5100 miou: 0.6804 acc: 0.9217 acc_cls: 0.7467 data_time: 0.0020 time: 0.2963 2023/05/13 07:05:32 - mmengine - INFO - Epoch(train) [32][ 50/1196] lr: 8.0000e-04 eta: 0:57:08 time: 0.5558 data_time: 0.0040 memory: 2847 grad_norm: 0.0633 loss: 0.1444 loss_sem_seg: 0.1444 2023/05/13 07:06:00 - mmengine - INFO - Epoch(train) [32][ 100/1196] lr: 8.0000e-04 eta: 0:56:39 time: 0.5648 data_time: 0.0036 memory: 2792 grad_norm: 0.0614 loss: 0.1527 loss_sem_seg: 0.1527 2023/05/13 07:06:29 - mmengine - INFO - Epoch(train) [32][ 150/1196] lr: 8.0000e-04 eta: 0:56:10 time: 0.5698 data_time: 0.0035 memory: 2800 grad_norm: 0.0617 loss: 0.1463 loss_sem_seg: 0.1463 2023/05/13 07:06:58 - mmengine - INFO - Epoch(train) [32][ 200/1196] lr: 8.0000e-04 eta: 0:55:41 time: 0.5915 data_time: 0.0035 memory: 2674 grad_norm: 0.0617 loss: 0.1543 loss_sem_seg: 0.1543 2023/05/13 07:07:27 - mmengine - INFO - Epoch(train) [32][ 250/1196] lr: 8.0000e-04 eta: 0:55:12 time: 0.5677 data_time: 0.0035 memory: 2901 grad_norm: 0.0638 loss: 0.1486 loss_sem_seg: 0.1486 2023/05/13 07:07:55 - mmengine - INFO - Epoch(train) [32][ 300/1196] lr: 8.0000e-04 eta: 0:54:43 time: 0.5685 data_time: 0.0034 memory: 2721 grad_norm: 0.0594 loss: 0.1555 loss_sem_seg: 0.1555 2023/05/13 07:08:23 - mmengine - INFO - Epoch(train) [32][ 350/1196] lr: 8.0000e-04 eta: 0:54:14 time: 0.5688 data_time: 0.0033 memory: 2896 grad_norm: 0.0631 loss: 0.1496 loss_sem_seg: 0.1496 2023/05/13 07:08:53 - mmengine - INFO - Epoch(train) [32][ 400/1196] lr: 8.0000e-04 eta: 0:53:46 time: 0.5877 data_time: 0.0035 memory: 2819 grad_norm: 0.0580 loss: 0.1460 loss_sem_seg: 0.1460 2023/05/13 07:09:24 - mmengine - INFO - Epoch(train) [32][ 450/1196] lr: 8.0000e-04 eta: 0:53:17 time: 0.6327 data_time: 0.0035 memory: 2770 grad_norm: 0.0651 loss: 0.1559 loss_sem_seg: 0.1559 2023/05/13 07:09:55 - mmengine - INFO - Epoch(train) [32][ 500/1196] lr: 8.0000e-04 eta: 0:52:48 time: 0.6128 data_time: 0.0036 memory: 2870 grad_norm: 0.0595 loss: 0.1520 loss_sem_seg: 0.1520 2023/05/13 07:10:25 - mmengine - INFO - Epoch(train) [32][ 550/1196] lr: 8.0000e-04 eta: 0:52:20 time: 0.6036 data_time: 0.0035 memory: 2798 grad_norm: 0.0611 loss: 0.1479 loss_sem_seg: 0.1479 2023/05/13 07:10:56 - mmengine - INFO - Epoch(train) [32][ 600/1196] lr: 8.0000e-04 eta: 0:51:51 time: 0.6236 data_time: 0.0035 memory: 3255 grad_norm: 0.0594 loss: 0.1569 loss_sem_seg: 0.1569 2023/05/13 07:11:27 - mmengine - INFO - Epoch(train) [32][ 650/1196] lr: 8.0000e-04 eta: 0:51:22 time: 0.6087 data_time: 0.0035 memory: 2752 grad_norm: 0.0600 loss: 0.1517 loss_sem_seg: 0.1517 2023/05/13 07:11:57 - mmengine - INFO - Epoch(train) [32][ 700/1196] lr: 8.0000e-04 eta: 0:50:54 time: 0.5984 data_time: 0.0035 memory: 2864 grad_norm: 0.0603 loss: 0.1586 loss_sem_seg: 0.1586 2023/05/13 07:12:28 - mmengine - INFO - Epoch(train) [32][ 750/1196] lr: 8.0000e-04 eta: 0:50:25 time: 0.6192 data_time: 0.0034 memory: 2759 grad_norm: 0.0618 loss: 0.1499 loss_sem_seg: 0.1499 2023/05/13 07:12:58 - mmengine - INFO - Epoch(train) [32][ 800/1196] lr: 8.0000e-04 eta: 0:49:56 time: 0.6030 data_time: 0.0035 memory: 2744 grad_norm: 0.0604 loss: 0.1518 loss_sem_seg: 0.1518 2023/05/13 07:13:28 - mmengine - INFO - Epoch(train) [32][ 850/1196] lr: 8.0000e-04 eta: 0:49:27 time: 0.6022 data_time: 0.0034 memory: 2743 grad_norm: 0.0646 loss: 0.1491 loss_sem_seg: 0.1491 2023/05/13 07:13:59 - mmengine - INFO - Epoch(train) [32][ 900/1196] lr: 8.0000e-04 eta: 0:48:59 time: 0.6145 data_time: 0.0035 memory: 2884 grad_norm: 0.0615 loss: 0.1514 loss_sem_seg: 0.1514 2023/05/13 07:14:13 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:14:29 - mmengine - INFO - Epoch(train) [32][ 950/1196] lr: 8.0000e-04 eta: 0:48:30 time: 0.6108 data_time: 0.0036 memory: 2791 grad_norm: 0.0637 loss: 0.1509 loss_sem_seg: 0.1509 2023/05/13 07:15:01 - mmengine - INFO - Epoch(train) [32][1000/1196] lr: 8.0000e-04 eta: 0:48:01 time: 0.6287 data_time: 0.0036 memory: 3027 grad_norm: 0.0598 loss: 0.1550 loss_sem_seg: 0.1550 2023/05/13 07:15:31 - mmengine - INFO - Epoch(train) [32][1050/1196] lr: 8.0000e-04 eta: 0:47:33 time: 0.6046 data_time: 0.0036 memory: 2793 grad_norm: 0.0626 loss: 0.1574 loss_sem_seg: 0.1574 2023/05/13 07:16:02 - mmengine - INFO - Epoch(train) [32][1100/1196] lr: 8.0000e-04 eta: 0:47:04 time: 0.6141 data_time: 0.0035 memory: 2807 grad_norm: 0.0620 loss: 0.1508 loss_sem_seg: 0.1508 2023/05/13 07:16:32 - mmengine - INFO - Epoch(train) [32][1150/1196] lr: 8.0000e-04 eta: 0:46:35 time: 0.6154 data_time: 0.0035 memory: 2751 grad_norm: 0.0668 loss: 0.1519 loss_sem_seg: 0.1519 2023/05/13 07:17:00 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:17:00 - mmengine - INFO - Saving checkpoint at 32 epochs 2023/05/13 07:17:25 - mmengine - INFO - Epoch(val) [32][ 50/509] eta: 0:02:49 time: 0.3703 data_time: 0.0021 memory: 3001 2023/05/13 07:17:42 - mmengine - INFO - Epoch(val) [32][100/509] eta: 0:02:23 time: 0.3295 data_time: 0.0021 memory: 920 2023/05/13 07:17:59 - mmengine - INFO - Epoch(val) [32][150/509] eta: 0:02:04 time: 0.3381 data_time: 0.0021 memory: 918 2023/05/13 07:18:16 - mmengine - INFO - Epoch(val) [32][200/509] eta: 0:01:45 time: 0.3338 data_time: 0.0021 memory: 906 2023/05/13 07:18:33 - mmengine - INFO - Epoch(val) [32][250/509] eta: 0:01:28 time: 0.3436 data_time: 0.0022 memory: 931 2023/05/13 07:18:48 - mmengine - INFO - Epoch(val) [32][300/509] eta: 0:01:10 time: 0.3015 data_time: 0.0021 memory: 868 2023/05/13 07:19:03 - mmengine - INFO - Epoch(val) [32][350/509] eta: 0:00:52 time: 0.3009 data_time: 0.0020 memory: 893 2023/05/13 07:19:19 - mmengine - INFO - Epoch(val) [32][400/509] eta: 0:00:36 time: 0.3272 data_time: 0.0021 memory: 901 2023/05/13 07:19:36 - mmengine - INFO - Epoch(val) [32][450/509] eta: 0:00:19 time: 0.3332 data_time: 0.0021 memory: 915 2023/05/13 07:19:52 - mmengine - INFO - Epoch(val) [32][500/509] eta: 0:00:02 time: 0.3221 data_time: 0.0021 memory: 898 2023/05/13 07:20:12 - 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 | 0.9689 | 0.5318 | 0.8026 | 0.8313 | 0.7121 | 0.7943 | 0.8969 | 0.0334 | 0.9448 | 0.5087 | 0.8277 | 0.0167 | 0.9241 | 0.6871 | 0.8722 | 0.6876 | 0.7180 | 0.6607 | 0.5206 | 0.6810 | 0.9217 | 0.7464 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 07:20:12 - mmengine - INFO - Epoch(val) [32][509/509] car: 0.9689 bicycle: 0.5318 motorcycle: 0.8026 truck: 0.8313 bus: 0.7121 person: 0.7943 bicyclist: 0.8969 motorcyclist: 0.0334 road: 0.9448 parking: 0.5087 sidewalk: 0.8277 other-ground: 0.0167 building: 0.9241 fence: 0.6871 vegetation: 0.8722 trunck: 0.6876 terrian: 0.7180 pole: 0.6607 traffic-sign: 0.5206 miou: 0.6810 acc: 0.9217 acc_cls: 0.7464 data_time: 0.0022 time: 0.3280 2023/05/13 07:20:43 - mmengine - INFO - Epoch(train) [33][ 50/1196] lr: 8.0000e-05 eta: 0:45:40 time: 0.6080 data_time: 0.0044 memory: 2871 grad_norm: 0.0588 loss: 0.1498 loss_sem_seg: 0.1498 2023/05/13 07:21:13 - mmengine - INFO - Epoch(train) [33][ 100/1196] lr: 8.0000e-05 eta: 0:45:11 time: 0.6082 data_time: 0.0035 memory: 2887 grad_norm: 0.0591 loss: 0.1457 loss_sem_seg: 0.1457 2023/05/13 07:21:43 - mmengine - INFO - Epoch(train) [33][ 150/1196] lr: 8.0000e-05 eta: 0:44:42 time: 0.5954 data_time: 0.0034 memory: 3095 grad_norm: 0.0561 loss: 0.1479 loss_sem_seg: 0.1479 2023/05/13 07:22:14 - mmengine - INFO - Epoch(train) [33][ 200/1196] lr: 8.0000e-05 eta: 0:44:14 time: 0.6300 data_time: 0.0040 memory: 2911 grad_norm: 0.0583 loss: 0.1557 loss_sem_seg: 0.1557 2023/05/13 07:22:43 - mmengine - INFO - Epoch(train) [33][ 250/1196] lr: 8.0000e-05 eta: 0:43:45 time: 0.5732 data_time: 0.0035 memory: 2756 grad_norm: 0.0574 loss: 0.1491 loss_sem_seg: 0.1491 2023/05/13 07:23:11 - mmengine - INFO - Epoch(train) [33][ 300/1196] lr: 8.0000e-05 eta: 0:43:16 time: 0.5570 data_time: 0.0034 memory: 3017 grad_norm: 0.0580 loss: 0.1551 loss_sem_seg: 0.1551 2023/05/13 07:23:40 - mmengine - INFO - Epoch(train) [33][ 350/1196] lr: 8.0000e-05 eta: 0:42:47 time: 0.5733 data_time: 0.0035 memory: 2871 grad_norm: 0.0584 loss: 0.1506 loss_sem_seg: 0.1506 2023/05/13 07:24:08 - mmengine - INFO - Epoch(train) [33][ 400/1196] lr: 8.0000e-05 eta: 0:42:18 time: 0.5683 data_time: 0.0035 memory: 3124 grad_norm: 0.0572 loss: 0.1607 loss_sem_seg: 0.1607 2023/05/13 07:24:36 - mmengine - INFO - Epoch(train) [33][ 450/1196] lr: 8.0000e-05 eta: 0:41:49 time: 0.5628 data_time: 0.0035 memory: 2705 grad_norm: 0.0621 loss: 0.1508 loss_sem_seg: 0.1508 2023/05/13 07:25:04 - mmengine - INFO - Epoch(train) [33][ 500/1196] lr: 8.0000e-05 eta: 0:41:20 time: 0.5568 data_time: 0.0034 memory: 2912 grad_norm: 0.0558 loss: 0.1459 loss_sem_seg: 0.1459 2023/05/13 07:25:34 - mmengine - INFO - Epoch(train) [33][ 550/1196] lr: 8.0000e-05 eta: 0:40:51 time: 0.6051 data_time: 0.0035 memory: 3245 grad_norm: 0.0598 loss: 0.1477 loss_sem_seg: 0.1477 2023/05/13 07:26:05 - mmengine - INFO - Epoch(train) [33][ 600/1196] lr: 8.0000e-05 eta: 0:40:22 time: 0.6095 data_time: 0.0035 memory: 2763 grad_norm: 0.0557 loss: 0.1545 loss_sem_seg: 0.1545 2023/05/13 07:26:35 - mmengine - INFO - Epoch(train) [33][ 650/1196] lr: 8.0000e-05 eta: 0:39:53 time: 0.6026 data_time: 0.0035 memory: 2826 grad_norm: 0.0562 loss: 0.1411 loss_sem_seg: 0.1411 2023/05/13 07:27:05 - mmengine - INFO - Epoch(train) [33][ 700/1196] lr: 8.0000e-05 eta: 0:39:24 time: 0.6055 data_time: 0.0038 memory: 2869 grad_norm: 0.0602 loss: 0.1531 loss_sem_seg: 0.1531 2023/05/13 07:27:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:27:37 - mmengine - INFO - Epoch(train) [33][ 750/1196] lr: 8.0000e-05 eta: 0:38:56 time: 0.6288 data_time: 0.0036 memory: 2729 grad_norm: 0.0528 loss: 0.1581 loss_sem_seg: 0.1581 2023/05/13 07:28:08 - mmengine - INFO - Epoch(train) [33][ 800/1196] lr: 8.0000e-05 eta: 0:38:27 time: 0.6226 data_time: 0.0038 memory: 2714 grad_norm: 0.0601 loss: 0.1541 loss_sem_seg: 0.1541 2023/05/13 07:28:39 - mmengine - INFO - Epoch(train) [33][ 850/1196] lr: 8.0000e-05 eta: 0:37:58 time: 0.6159 data_time: 0.0037 memory: 2687 grad_norm: 0.0594 loss: 0.1515 loss_sem_seg: 0.1515 2023/05/13 07:29:09 - mmengine - INFO - Epoch(train) [33][ 900/1196] lr: 8.0000e-05 eta: 0:37:29 time: 0.6126 data_time: 0.0035 memory: 2991 grad_norm: inf loss: 0.1567 loss_sem_seg: 0.1567 2023/05/13 07:29:40 - mmengine - INFO - Epoch(train) [33][ 950/1196] lr: 8.0000e-05 eta: 0:37:01 time: 0.6086 data_time: 0.0035 memory: 2780 grad_norm: 0.0523 loss: 0.1481 loss_sem_seg: 0.1481 2023/05/13 07:30:11 - mmengine - INFO - Epoch(train) [33][1000/1196] lr: 8.0000e-05 eta: 0:36:32 time: 0.6186 data_time: 0.0035 memory: 2922 grad_norm: 0.0603 loss: 0.1568 loss_sem_seg: 0.1568 2023/05/13 07:30:41 - mmengine - INFO - Epoch(train) [33][1050/1196] lr: 8.0000e-05 eta: 0:36:03 time: 0.6076 data_time: 0.0037 memory: 2857 grad_norm: 0.0544 loss: 0.1443 loss_sem_seg: 0.1443 2023/05/13 07:31:11 - mmengine - INFO - Epoch(train) [33][1100/1196] lr: 8.0000e-05 eta: 0:35:34 time: 0.6024 data_time: 0.0037 memory: 2827 grad_norm: 0.0542 loss: 0.1516 loss_sem_seg: 0.1516 2023/05/13 07:31:42 - mmengine - INFO - Epoch(train) [33][1150/1196] lr: 8.0000e-05 eta: 0:35:05 time: 0.6130 data_time: 0.0035 memory: 2717 grad_norm: 0.0598 loss: 0.1479 loss_sem_seg: 0.1479 2023/05/13 07:32:09 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:32:09 - mmengine - INFO - Saving checkpoint at 33 epochs 2023/05/13 07:32:35 - mmengine - INFO - Epoch(val) [33][ 50/509] eta: 0:02:53 time: 0.3780 data_time: 0.0021 memory: 2722 2023/05/13 07:32:52 - mmengine - INFO - Epoch(val) [33][100/509] eta: 0:02:26 time: 0.3392 data_time: 0.0021 memory: 920 2023/05/13 07:33:08 - mmengine - INFO - Epoch(val) [33][150/509] eta: 0:02:05 time: 0.3293 data_time: 0.0021 memory: 918 2023/05/13 07:33:24 - mmengine - INFO - Epoch(val) [33][200/509] eta: 0:01:45 time: 0.3206 data_time: 0.0021 memory: 906 2023/05/13 07:33:43 - mmengine - INFO - Epoch(val) [33][250/509] eta: 0:01:30 time: 0.3748 data_time: 0.0022 memory: 931 2023/05/13 07:33:57 - mmengine - INFO - Epoch(val) [33][300/509] eta: 0:01:10 time: 0.2797 data_time: 0.0021 memory: 868 2023/05/13 07:34:12 - mmengine - INFO - Epoch(val) [33][350/509] eta: 0:00:53 time: 0.3119 data_time: 0.0021 memory: 893 2023/05/13 07:34:30 - mmengine - INFO - Epoch(val) [33][400/509] eta: 0:00:36 time: 0.3502 data_time: 0.0021 memory: 901 2023/05/13 07:34:47 - mmengine - INFO - Epoch(val) [33][450/509] eta: 0:00:19 time: 0.3307 data_time: 0.0022 memory: 915 2023/05/13 07:35:01 - mmengine - INFO - Epoch(val) [33][500/509] eta: 0:00:02 time: 0.2978 data_time: 0.0020 memory: 898 2023/05/13 07:35:21 - 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 | 0.9693 | 0.5257 | 0.8018 | 0.8188 | 0.7225 | 0.7872 | 0.8962 | 0.0450 | 0.9457 | 0.5085 | 0.8282 | 0.0171 | 0.9213 | 0.6907 | 0.8742 | 0.6817 | 0.7201 | 0.6622 | 0.5183 | 0.6808 | 0.9224 | 0.7465 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 07:35:21 - mmengine - INFO - Epoch(val) [33][509/509] car: 0.9693 bicycle: 0.5257 motorcycle: 0.8018 truck: 0.8188 bus: 0.7225 person: 0.7872 bicyclist: 0.8962 motorcyclist: 0.0450 road: 0.9457 parking: 0.5085 sidewalk: 0.8282 other-ground: 0.0171 building: 0.9213 fence: 0.6907 vegetation: 0.8742 trunck: 0.6817 terrian: 0.7201 pole: 0.6622 traffic-sign: 0.5183 miou: 0.6808 acc: 0.9224 acc_cls: 0.7465 data_time: 0.0020 time: 0.3059 2023/05/13 07:35:52 - mmengine - INFO - Epoch(train) [34][ 50/1196] lr: 8.0000e-05 eta: 0:34:10 time: 0.6143 data_time: 0.0047 memory: 2827 grad_norm: 0.0629 loss: 0.1531 loss_sem_seg: 0.1531 2023/05/13 07:36:22 - mmengine - INFO - Epoch(train) [34][ 100/1196] lr: 8.0000e-05 eta: 0:33:41 time: 0.5984 data_time: 0.0035 memory: 3167 grad_norm: 0.0584 loss: 0.1500 loss_sem_seg: 0.1500 2023/05/13 07:36:50 - mmengine - INFO - Epoch(train) [34][ 150/1196] lr: 8.0000e-05 eta: 0:33:12 time: 0.5663 data_time: 0.0038 memory: 3012 grad_norm: 0.0634 loss: 0.1464 loss_sem_seg: 0.1464 2023/05/13 07:37:18 - mmengine - INFO - Epoch(train) [34][ 200/1196] lr: 8.0000e-05 eta: 0:32:43 time: 0.5473 data_time: 0.0038 memory: 2893 grad_norm: 0.0566 loss: 0.1513 loss_sem_seg: 0.1513 2023/05/13 07:37:45 - mmengine - INFO - Epoch(train) [34][ 250/1196] lr: 8.0000e-05 eta: 0:32:14 time: 0.5349 data_time: 0.0037 memory: 2612 grad_norm: 0.0576 loss: 0.1598 loss_sem_seg: 0.1598 2023/05/13 07:38:12 - mmengine - INFO - Epoch(train) [34][ 300/1196] lr: 8.0000e-05 eta: 0:31:45 time: 0.5408 data_time: 0.0036 memory: 3258 grad_norm: 0.0578 loss: 0.1470 loss_sem_seg: 0.1470 2023/05/13 07:38:39 - mmengine - INFO - Epoch(train) [34][ 350/1196] lr: 8.0000e-05 eta: 0:31:15 time: 0.5558 data_time: 0.0035 memory: 2902 grad_norm: 0.0572 loss: 0.1490 loss_sem_seg: 0.1490 2023/05/13 07:39:07 - mmengine - INFO - Epoch(train) [34][ 400/1196] lr: 8.0000e-05 eta: 0:30:46 time: 0.5451 data_time: 0.0035 memory: 3453 grad_norm: 0.0551 loss: 0.1458 loss_sem_seg: 0.1458 2023/05/13 07:39:34 - mmengine - INFO - Epoch(train) [34][ 450/1196] lr: 8.0000e-05 eta: 0:30:17 time: 0.5394 data_time: 0.0035 memory: 2771 grad_norm: 0.0568 loss: 0.1523 loss_sem_seg: 0.1523 2023/05/13 07:40:01 - mmengine - INFO - Epoch(train) [34][ 500/1196] lr: 8.0000e-05 eta: 0:29:48 time: 0.5561 data_time: 0.0036 memory: 2827 grad_norm: 0.0564 loss: 0.1482 loss_sem_seg: 0.1482 2023/05/13 07:40:19 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:40:29 - mmengine - INFO - Epoch(train) [34][ 550/1196] lr: 8.0000e-05 eta: 0:29:19 time: 0.5498 data_time: 0.0037 memory: 2818 grad_norm: 0.0556 loss: 0.1502 loss_sem_seg: 0.1502 2023/05/13 07:40:56 - mmengine - INFO - Epoch(train) [34][ 600/1196] lr: 8.0000e-05 eta: 0:28:50 time: 0.5353 data_time: 0.0037 memory: 2735 grad_norm: 0.0551 loss: 0.1445 loss_sem_seg: 0.1445 2023/05/13 07:41:23 - mmengine - INFO - Epoch(train) [34][ 650/1196] lr: 8.0000e-05 eta: 0:28:21 time: 0.5416 data_time: 0.0035 memory: 2778 grad_norm: 0.0573 loss: 0.1469 loss_sem_seg: 0.1469 2023/05/13 07:41:50 - mmengine - INFO - Epoch(train) [34][ 700/1196] lr: 8.0000e-05 eta: 0:27:52 time: 0.5426 data_time: 0.0037 memory: 2883 grad_norm: 0.0573 loss: 0.1579 loss_sem_seg: 0.1579 2023/05/13 07:42:17 - mmengine - INFO - Epoch(train) [34][ 750/1196] lr: 8.0000e-05 eta: 0:27:23 time: 0.5420 data_time: 0.0036 memory: 2791 grad_norm: 0.0587 loss: 0.1502 loss_sem_seg: 0.1502 2023/05/13 07:42:43 - mmengine - INFO - Epoch(train) [34][ 800/1196] lr: 8.0000e-05 eta: 0:26:54 time: 0.5204 data_time: 0.0039 memory: 2970 grad_norm: 0.0549 loss: 0.1408 loss_sem_seg: 0.1408 2023/05/13 07:43:09 - mmengine - INFO - Epoch(train) [34][ 850/1196] lr: 8.0000e-05 eta: 0:26:24 time: 0.5096 data_time: 0.0036 memory: 2985 grad_norm: 0.0588 loss: 0.1547 loss_sem_seg: 0.1547 2023/05/13 07:43:33 - mmengine - INFO - Epoch(train) [34][ 900/1196] lr: 8.0000e-05 eta: 0:25:55 time: 0.4927 data_time: 0.0036 memory: 2712 grad_norm: 0.0619 loss: 0.1538 loss_sem_seg: 0.1538 2023/05/13 07:44:00 - mmengine - INFO - Epoch(train) [34][ 950/1196] lr: 8.0000e-05 eta: 0:25:26 time: 0.5334 data_time: 0.0035 memory: 2626 grad_norm: 0.0546 loss: 0.1485 loss_sem_seg: 0.1485 2023/05/13 07:44:29 - mmengine - INFO - Epoch(train) [34][1000/1196] lr: 8.0000e-05 eta: 0:24:57 time: 0.5756 data_time: 0.0036 memory: 2750 grad_norm: 0.0535 loss: 0.1449 loss_sem_seg: 0.1449 2023/05/13 07:44:57 - mmengine - INFO - Epoch(train) [34][1050/1196] lr: 8.0000e-05 eta: 0:24:28 time: 0.5634 data_time: 0.0035 memory: 2783 grad_norm: 0.0557 loss: 0.1572 loss_sem_seg: 0.1572 2023/05/13 07:45:25 - mmengine - INFO - Epoch(train) [34][1100/1196] lr: 8.0000e-05 eta: 0:23:59 time: 0.5638 data_time: 0.0035 memory: 2664 grad_norm: 0.0575 loss: 0.1482 loss_sem_seg: 0.1482 2023/05/13 07:45:53 - mmengine - INFO - Epoch(train) [34][1150/1196] lr: 8.0000e-05 eta: 0:23:30 time: 0.5656 data_time: 0.0035 memory: 2733 grad_norm: 0.0550 loss: 0.1514 loss_sem_seg: 0.1514 2023/05/13 07:46:19 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:46:19 - mmengine - INFO - Saving checkpoint at 34 epochs 2023/05/13 07:46:43 - mmengine - INFO - Epoch(val) [34][ 50/509] eta: 0:02:42 time: 0.3550 data_time: 0.0021 memory: 2737 2023/05/13 07:46:59 - mmengine - INFO - Epoch(val) [34][100/509] eta: 0:02:17 time: 0.3182 data_time: 0.0022 memory: 920 2023/05/13 07:47:13 - mmengine - INFO - Epoch(val) [34][150/509] eta: 0:01:54 time: 0.2873 data_time: 0.0021 memory: 918 2023/05/13 07:47:29 - mmengine - INFO - Epoch(val) [34][200/509] eta: 0:01:38 time: 0.3108 data_time: 0.0021 memory: 906 2023/05/13 07:47:46 - mmengine - INFO - Epoch(val) [34][250/509] eta: 0:01:23 time: 0.3409 data_time: 0.0021 memory: 931 2023/05/13 07:48:00 - mmengine - INFO - Epoch(val) [34][300/509] eta: 0:01:06 time: 0.2849 data_time: 0.0021 memory: 868 2023/05/13 07:48:15 - mmengine - INFO - Epoch(val) [34][350/509] eta: 0:00:50 time: 0.3058 data_time: 0.0021 memory: 893 2023/05/13 07:48:32 - mmengine - INFO - Epoch(val) [34][400/509] eta: 0:00:34 time: 0.3302 data_time: 0.0021 memory: 901 2023/05/13 07:48:46 - mmengine - INFO - Epoch(val) [34][450/509] eta: 0:00:18 time: 0.2876 data_time: 0.0020 memory: 915 2023/05/13 07:49:01 - mmengine - INFO - Epoch(val) [34][500/509] eta: 0:00:02 time: 0.2880 data_time: 0.0021 memory: 898 2023/05/13 07:49:22 - 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 | 0.5299 | 0.8059 | 0.8302 | 0.7243 | 0.7906 | 0.8930 | 0.0498 | 0.9462 | 0.5027 | 0.8281 | 0.0144 | 0.9227 | 0.6978 | 0.8744 | 0.6816 | 0.7192 | 0.6614 | 0.5162 | 0.6820 | 0.9226 | 0.7480 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 07:49:22 - mmengine - INFO - Epoch(val) [34][509/509] car: 0.9695 bicycle: 0.5299 motorcycle: 0.8059 truck: 0.8302 bus: 0.7243 person: 0.7906 bicyclist: 0.8930 motorcyclist: 0.0498 road: 0.9462 parking: 0.5027 sidewalk: 0.8281 other-ground: 0.0144 building: 0.9227 fence: 0.6978 vegetation: 0.8744 trunck: 0.6816 terrian: 0.7192 pole: 0.6614 traffic-sign: 0.5162 miou: 0.6820 acc: 0.9226 acc_cls: 0.7480 data_time: 0.0020 time: 0.3085 2023/05/13 07:49:51 - mmengine - INFO - Epoch(train) [35][ 50/1196] lr: 8.0000e-05 eta: 0:22:35 time: 0.5789 data_time: 0.0042 memory: 2878 grad_norm: 0.0525 loss: 0.1402 loss_sem_seg: 0.1402 2023/05/13 07:50:23 - mmengine - INFO - Epoch(train) [35][ 100/1196] lr: 8.0000e-05 eta: 0:22:06 time: 0.6432 data_time: 0.0037 memory: 2969 grad_norm: 0.0551 loss: 0.1427 loss_sem_seg: 0.1427 2023/05/13 07:50:54 - mmengine - INFO - Epoch(train) [35][ 150/1196] lr: 8.0000e-05 eta: 0:21:37 time: 0.6065 data_time: 0.0035 memory: 2707 grad_norm: 0.0576 loss: 0.1501 loss_sem_seg: 0.1501 2023/05/13 07:51:23 - mmengine - INFO - Epoch(train) [35][ 200/1196] lr: 8.0000e-05 eta: 0:21:08 time: 0.5968 data_time: 0.0036 memory: 2766 grad_norm: 0.0576 loss: 0.1461 loss_sem_seg: 0.1461 2023/05/13 07:51:53 - mmengine - INFO - Epoch(train) [35][ 250/1196] lr: 8.0000e-05 eta: 0:20:39 time: 0.5879 data_time: 0.0034 memory: 2690 grad_norm: 0.0525 loss: 0.1342 loss_sem_seg: 0.1342 2023/05/13 07:52:23 - mmengine - INFO - Epoch(train) [35][ 300/1196] lr: 8.0000e-05 eta: 0:20:10 time: 0.6022 data_time: 0.0037 memory: 2893 grad_norm: 0.0596 loss: 0.1551 loss_sem_seg: 0.1551 2023/05/13 07:52:45 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 07:52:54 - mmengine - INFO - Epoch(train) [35][ 350/1196] lr: 8.0000e-05 eta: 0:19:41 time: 0.6147 data_time: 0.0036 memory: 2932 grad_norm: 0.0615 loss: 0.1500 loss_sem_seg: 0.1500 2023/05/13 07:53:24 - mmengine - INFO - Epoch(train) [35][ 400/1196] lr: 8.0000e-05 eta: 0:19:13 time: 0.6031 data_time: 0.0036 memory: 2736 grad_norm: 0.0546 loss: 0.1525 loss_sem_seg: 0.1525 2023/05/13 07:53:54 - mmengine - INFO - Epoch(train) [35][ 450/1196] lr: 8.0000e-05 eta: 0:18:44 time: 0.6044 data_time: 0.0035 memory: 2906 grad_norm: 0.0621 loss: 0.1482 loss_sem_seg: 0.1482 2023/05/13 07:54:24 - mmengine - INFO - Epoch(train) [35][ 500/1196] lr: 8.0000e-05 eta: 0:18:15 time: 0.6058 data_time: 0.0036 memory: 2916 grad_norm: 0.0562 loss: 0.1506 loss_sem_seg: 0.1506 2023/05/13 07:54:55 - mmengine - INFO - Epoch(train) [35][ 550/1196] lr: 8.0000e-05 eta: 0:17:46 time: 0.6070 data_time: 0.0036 memory: 2782 grad_norm: 0.0625 loss: 0.1422 loss_sem_seg: 0.1422 2023/05/13 07:55:26 - mmengine - INFO - Epoch(train) [35][ 600/1196] lr: 8.0000e-05 eta: 0:17:17 time: 0.6184 data_time: 0.0035 memory: 2769 grad_norm: inf loss: 0.1586 loss_sem_seg: 0.1586 2023/05/13 07:55:56 - mmengine - INFO - Epoch(train) [35][ 650/1196] lr: 8.0000e-05 eta: 0:16:48 time: 0.6050 data_time: 0.0036 memory: 2864 grad_norm: 0.0557 loss: 0.1450 loss_sem_seg: 0.1450 2023/05/13 07:56:27 - mmengine - INFO - Epoch(train) [35][ 700/1196] lr: 8.0000e-05 eta: 0:16:19 time: 0.6149 data_time: 0.0035 memory: 2734 grad_norm: 0.0586 loss: 0.1462 loss_sem_seg: 0.1462 2023/05/13 07:56:58 - mmengine - INFO - Epoch(train) [35][ 750/1196] lr: 8.0000e-05 eta: 0:15:50 time: 0.6182 data_time: 0.0035 memory: 2756 grad_norm: 0.0590 loss: 0.1499 loss_sem_seg: 0.1499 2023/05/13 07:57:28 - mmengine - INFO - Epoch(train) [35][ 800/1196] lr: 8.0000e-05 eta: 0:15:22 time: 0.6152 data_time: 0.0035 memory: 3040 grad_norm: 0.0548 loss: 0.1396 loss_sem_seg: 0.1396 2023/05/13 07:57:59 - mmengine - INFO - Epoch(train) [35][ 850/1196] lr: 8.0000e-05 eta: 0:14:53 time: 0.6159 data_time: 0.0036 memory: 2778 grad_norm: 0.0587 loss: 0.1419 loss_sem_seg: 0.1419 2023/05/13 07:58:30 - mmengine - INFO - Epoch(train) [35][ 900/1196] lr: 8.0000e-05 eta: 0:14:24 time: 0.6165 data_time: 0.0035 memory: 3042 grad_norm: 0.0591 loss: 0.1520 loss_sem_seg: 0.1520 2023/05/13 07:58:59 - mmengine - INFO - Epoch(train) [35][ 950/1196] lr: 8.0000e-05 eta: 0:13:55 time: 0.5767 data_time: 0.0036 memory: 3229 grad_norm: 0.0599 loss: 0.1517 loss_sem_seg: 0.1517 2023/05/13 07:59:29 - mmengine - INFO - Epoch(train) [35][1000/1196] lr: 8.0000e-05 eta: 0:13:26 time: 0.6112 data_time: 0.0037 memory: 2781 grad_norm: 0.0558 loss: 0.1514 loss_sem_seg: 0.1514 2023/05/13 08:00:00 - mmengine - INFO - Epoch(train) [35][1050/1196] lr: 8.0000e-05 eta: 0:12:57 time: 0.6137 data_time: 0.0038 memory: 2696 grad_norm: 0.0534 loss: 0.1479 loss_sem_seg: 0.1479 2023/05/13 08:00:30 - mmengine - INFO - Epoch(train) [35][1100/1196] lr: 8.0000e-05 eta: 0:12:28 time: 0.5993 data_time: 0.0035 memory: 2858 grad_norm: 0.0587 loss: 0.1478 loss_sem_seg: 0.1478 2023/05/13 08:01:01 - mmengine - INFO - Epoch(train) [35][1150/1196] lr: 8.0000e-05 eta: 0:11:59 time: 0.6170 data_time: 0.0038 memory: 2900 grad_norm: 0.0580 loss: 0.1543 loss_sem_seg: 0.1543 2023/05/13 08:01:28 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 08:01:28 - mmengine - INFO - Saving checkpoint at 35 epochs 2023/05/13 08:01:50 - mmengine - INFO - Epoch(val) [35][ 50/509] eta: 0:02:22 time: 0.3102 data_time: 0.0021 memory: 2867 2023/05/13 08:02:04 - mmengine - INFO - Epoch(val) [35][100/509] eta: 0:02:04 time: 0.2964 data_time: 0.0021 memory: 920 2023/05/13 08:02:20 - mmengine - INFO - Epoch(val) [35][150/509] eta: 0:01:49 time: 0.3092 data_time: 0.0022 memory: 918 2023/05/13 08:02:35 - mmengine - INFO - Epoch(val) [35][200/509] eta: 0:01:34 time: 0.3058 data_time: 0.0021 memory: 906 2023/05/13 08:02:52 - mmengine - INFO - Epoch(val) [35][250/509] eta: 0:01:20 time: 0.3393 data_time: 0.0022 memory: 931 2023/05/13 08:03:06 - mmengine - INFO - Epoch(val) [35][300/509] eta: 0:01:04 time: 0.2816 data_time: 0.0021 memory: 868 2023/05/13 08:03:20 - mmengine - INFO - Epoch(val) [35][350/509] eta: 0:00:48 time: 0.2843 data_time: 0.0021 memory: 893 2023/05/13 08:03:36 - mmengine - INFO - Epoch(val) [35][400/509] eta: 0:00:33 time: 0.3069 data_time: 0.0021 memory: 901 2023/05/13 08:03:51 - mmengine - INFO - Epoch(val) [35][450/509] eta: 0:00:17 time: 0.3054 data_time: 0.0021 memory: 915 2023/05/13 08:04:05 - mmengine - INFO - Epoch(val) [35][500/509] eta: 0:00:02 time: 0.2765 data_time: 0.0020 memory: 898 2023/05/13 08:04:23 - 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 | 0.9699 | 0.5254 | 0.8057 | 0.8073 | 0.7370 | 0.7910 | 0.8960 | 0.0503 | 0.9462 | 0.5099 | 0.8293 | 0.0120 | 0.9212 | 0.6917 | 0.8737 | 0.6787 | 0.7181 | 0.6622 | 0.5177 | 0.6812 | 0.9223 | 0.7460 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 08:04:23 - mmengine - INFO - Epoch(val) [35][509/509] car: 0.9699 bicycle: 0.5254 motorcycle: 0.8057 truck: 0.8073 bus: 0.7370 person: 0.7910 bicyclist: 0.8960 motorcyclist: 0.0503 road: 0.9462 parking: 0.5099 sidewalk: 0.8293 other-ground: 0.0120 building: 0.9212 fence: 0.6917 vegetation: 0.8737 trunck: 0.6787 terrian: 0.7181 pole: 0.6622 traffic-sign: 0.5177 miou: 0.6812 acc: 0.9223 acc_cls: 0.7460 data_time: 0.0020 time: 0.2806 2023/05/13 08:04:54 - mmengine - INFO - Epoch(train) [36][ 50/1196] lr: 8.0000e-05 eta: 0:11:04 time: 0.6084 data_time: 0.0048 memory: 2792 grad_norm: 0.0543 loss: 0.1459 loss_sem_seg: 0.1459 2023/05/13 08:05:24 - mmengine - INFO - Epoch(train) [36][ 100/1196] lr: 8.0000e-05 eta: 0:10:35 time: 0.6049 data_time: 0.0034 memory: 2893 grad_norm: 0.0558 loss: 0.1423 loss_sem_seg: 0.1423 2023/05/13 08:05:49 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 08:05:55 - mmengine - INFO - Epoch(train) [36][ 150/1196] lr: 8.0000e-05 eta: 0:10:06 time: 0.6151 data_time: 0.0034 memory: 2704 grad_norm: 0.0636 loss: 0.1522 loss_sem_seg: 0.1522 2023/05/13 08:06:26 - mmengine - INFO - Epoch(train) [36][ 200/1196] lr: 8.0000e-05 eta: 0:09:37 time: 0.6255 data_time: 0.0036 memory: 3118 grad_norm: 0.0591 loss: 0.1450 loss_sem_seg: 0.1450 2023/05/13 08:06:57 - mmengine - INFO - Epoch(train) [36][ 250/1196] lr: 8.0000e-05 eta: 0:09:08 time: 0.6185 data_time: 0.0034 memory: 2723 grad_norm: 0.0546 loss: 0.1452 loss_sem_seg: 0.1452 2023/05/13 08:07:26 - mmengine - INFO - Epoch(train) [36][ 300/1196] lr: 8.0000e-05 eta: 0:08:39 time: 0.5870 data_time: 0.0035 memory: 2874 grad_norm: inf loss: 0.1490 loss_sem_seg: 0.1490 2023/05/13 08:07:57 - mmengine - INFO - Epoch(train) [36][ 350/1196] lr: 8.0000e-05 eta: 0:08:10 time: 0.6163 data_time: 0.0035 memory: 2786 grad_norm: 0.0559 loss: 0.1499 loss_sem_seg: 0.1499 2023/05/13 08:08:28 - mmengine - INFO - Epoch(train) [36][ 400/1196] lr: 8.0000e-05 eta: 0:07:41 time: 0.6127 data_time: 0.0035 memory: 2744 grad_norm: 0.0605 loss: 0.1451 loss_sem_seg: 0.1451 2023/05/13 08:08:58 - mmengine - INFO - Epoch(train) [36][ 450/1196] lr: 8.0000e-05 eta: 0:07:12 time: 0.6100 data_time: 0.0036 memory: 2775 grad_norm: 0.0535 loss: 0.1369 loss_sem_seg: 0.1369 2023/05/13 08:09:29 - mmengine - INFO - Epoch(train) [36][ 500/1196] lr: 8.0000e-05 eta: 0:06:43 time: 0.6223 data_time: 0.0036 memory: 3103 grad_norm: 0.0607 loss: 0.1445 loss_sem_seg: 0.1445 2023/05/13 08:10:00 - mmengine - INFO - Epoch(train) [36][ 550/1196] lr: 8.0000e-05 eta: 0:06:14 time: 0.6161 data_time: 0.0036 memory: 2784 grad_norm: 0.0562 loss: 0.1485 loss_sem_seg: 0.1485 2023/05/13 08:10:31 - mmengine - INFO - Epoch(train) [36][ 600/1196] lr: 8.0000e-05 eta: 0:05:45 time: 0.6146 data_time: 0.0036 memory: 2701 grad_norm: 0.0594 loss: 0.1493 loss_sem_seg: 0.1493 2023/05/13 08:11:01 - mmengine - INFO - Epoch(train) [36][ 650/1196] lr: 8.0000e-05 eta: 0:05:16 time: 0.6074 data_time: 0.0036 memory: 2734 grad_norm: 0.0563 loss: 0.1490 loss_sem_seg: 0.1490 2023/05/13 08:11:32 - mmengine - INFO - Epoch(train) [36][ 700/1196] lr: 8.0000e-05 eta: 0:04:47 time: 0.6034 data_time: 0.0036 memory: 2814 grad_norm: 0.0581 loss: 0.1408 loss_sem_seg: 0.1408 2023/05/13 08:12:01 - mmengine - INFO - Epoch(train) [36][ 750/1196] lr: 8.0000e-05 eta: 0:04:18 time: 0.5858 data_time: 0.0035 memory: 2558 grad_norm: 0.0575 loss: 0.1389 loss_sem_seg: 0.1389 2023/05/13 08:12:32 - mmengine - INFO - Epoch(train) [36][ 800/1196] lr: 8.0000e-05 eta: 0:03:49 time: 0.6167 data_time: 0.0036 memory: 2912 grad_norm: 0.0604 loss: 0.1641 loss_sem_seg: 0.1641 2023/05/13 08:13:02 - mmengine - INFO - Epoch(train) [36][ 850/1196] lr: 8.0000e-05 eta: 0:03:20 time: 0.5974 data_time: 0.0035 memory: 3145 grad_norm: 0.0563 loss: 0.1500 loss_sem_seg: 0.1500 2023/05/13 08:13:32 - mmengine - INFO - Epoch(train) [36][ 900/1196] lr: 8.0000e-05 eta: 0:02:51 time: 0.6131 data_time: 0.0035 memory: 2828 grad_norm: 0.0554 loss: 0.1533 loss_sem_seg: 0.1533 2023/05/13 08:14:03 - mmengine - INFO - Epoch(train) [36][ 950/1196] lr: 8.0000e-05 eta: 0:02:22 time: 0.6156 data_time: 0.0036 memory: 2949 grad_norm: 0.0570 loss: 0.1548 loss_sem_seg: 0.1548 2023/05/13 08:14:34 - mmengine - INFO - Epoch(train) [36][1000/1196] lr: 8.0000e-05 eta: 0:01:53 time: 0.6141 data_time: 0.0035 memory: 2813 grad_norm: 0.0559 loss: 0.1556 loss_sem_seg: 0.1556 2023/05/13 08:15:05 - mmengine - INFO - Epoch(train) [36][1050/1196] lr: 8.0000e-05 eta: 0:01:24 time: 0.6193 data_time: 0.0034 memory: 2915 grad_norm: 0.0555 loss: 0.1499 loss_sem_seg: 0.1499 2023/05/13 08:15:35 - mmengine - INFO - Epoch(train) [36][1100/1196] lr: 8.0000e-05 eta: 0:00:55 time: 0.6036 data_time: 0.0035 memory: 3031 grad_norm: 0.0646 loss: 0.1516 loss_sem_seg: 0.1516 2023/05/13 08:15:59 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 08:16:06 - mmengine - INFO - Epoch(train) [36][1150/1196] lr: 8.0000e-05 eta: 0:00:26 time: 0.6132 data_time: 0.0037 memory: 2891 grad_norm: 0.0599 loss: 0.1460 loss_sem_seg: 0.1460 2023/05/13 08:16:33 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-amp-lpmix-3x_semantickitti_20230512_233152 2023/05/13 08:16:33 - mmengine - INFO - Saving checkpoint at 36 epochs 2023/05/13 08:16:59 - mmengine - INFO - Epoch(val) [36][ 50/509] eta: 0:02:54 time: 0.3804 data_time: 0.0022 memory: 2737 2023/05/13 08:17:14 - mmengine - INFO - Epoch(val) [36][100/509] eta: 0:02:21 time: 0.3097 data_time: 0.0021 memory: 920 2023/05/13 08:17:30 - mmengine - INFO - Epoch(val) [36][150/509] eta: 0:02:00 time: 0.3171 data_time: 0.0022 memory: 918 2023/05/13 08:17:47 - mmengine - INFO - Epoch(val) [36][200/509] eta: 0:01:44 time: 0.3436 data_time: 0.0021 memory: 906 2023/05/13 08:18:06 - mmengine - INFO - Epoch(val) [36][250/509] eta: 0:01:29 time: 0.3814 data_time: 0.0022 memory: 931 2023/05/13 08:18:20 - mmengine - INFO - Epoch(val) [36][300/509] eta: 0:01:09 time: 0.2764 data_time: 0.0021 memory: 868 2023/05/13 08:18:36 - mmengine - INFO - Epoch(val) [36][350/509] eta: 0:00:52 time: 0.3088 data_time: 0.0021 memory: 893 2023/05/13 08:18:52 - mmengine - INFO - Epoch(val) [36][400/509] eta: 0:00:36 time: 0.3333 data_time: 0.0020 memory: 901 2023/05/13 08:19:10 - mmengine - INFO - Epoch(val) [36][450/509] eta: 0:00:19 time: 0.3442 data_time: 0.0021 memory: 915 2023/05/13 08:19:25 - mmengine - INFO - Epoch(val) [36][500/509] eta: 0:00:02 time: 0.3053 data_time: 0.0021 memory: 898 2023/05/13 08:19:44 - 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 | 0.5280 | 0.8038 | 0.8017 | 0.7344 | 0.7934 | 0.8975 | 0.0498 | 0.9472 | 0.5149 | 0.8308 | 0.0212 | 0.9230 | 0.6978 | 0.8783 | 0.6828 | 0.7305 | 0.6617 | 0.5186 | 0.6834 | 0.9245 | 0.7492 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 08:19:44 - mmengine - INFO - Epoch(val) [36][509/509] car: 0.9695 bicycle: 0.5280 motorcycle: 0.8038 truck: 0.8017 bus: 0.7344 person: 0.7934 bicyclist: 0.8975 motorcyclist: 0.0498 road: 0.9472 parking: 0.5149 sidewalk: 0.8308 other-ground: 0.0212 building: 0.9230 fence: 0.6978 vegetation: 0.8783 trunck: 0.6828 terrian: 0.7305 pole: 0.6617 traffic-sign: 0.5186 miou: 0.6834 acc: 0.9245 acc_cls: 0.7492 data_time: 0.0021 time: 0.3042