2023/05/12 23:38:32 - 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: 848936903 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) 9.4.0 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 23:38:36 - 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='OptimWrapper', optimizer=dict(type='AdamW', lr=0.008, weight_decay=0.01), clip_grad=dict(max_norm=10, norm_type=2)) 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-lpmix-3x_semantickitti' 2023/05/12 23:38:44 - 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 23:38:49 - 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 23:38:57 - 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 23:38:57 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/05/12 23:38:57 - mmengine - INFO - Checkpoints will be saved to /nvme/sunjiahao/projects/mmdetection3d/work_dirs/minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti. 2023/05/12 23:42:35 - mmengine - INFO - Epoch(train) [1][ 50/1196] lr: 8.0000e-03 eta: 2 days, 4:18:24 time: 4.3786 data_time: 0.0069 memory: 4903 grad_norm: 0.7125 loss: 1.5338 loss_sem_seg: 1.5338 2023/05/12 23:44:07 - mmengine - INFO - Epoch(train) [1][ 100/1196] lr: 8.0000e-03 eta: 1 day, 13:05:35 time: 1.8388 data_time: 0.0032 memory: 5026 grad_norm: 0.5683 loss: 1.0943 loss_sem_seg: 1.0943 2023/05/12 23:45:40 - mmengine - INFO - Epoch(train) [1][ 150/1196] lr: 8.0000e-03 eta: 1 day, 8:02:16 time: 1.8471 data_time: 0.0032 memory: 4903 grad_norm: 0.6521 loss: 0.9098 loss_sem_seg: 0.9098 2023/05/12 23:47:14 - mmengine - INFO - Epoch(train) [1][ 200/1196] lr: 8.0000e-03 eta: 1 day, 5:37:27 time: 1.8897 data_time: 0.0032 memory: 4509 grad_norm: 0.6910 loss: 0.8371 loss_sem_seg: 0.8371 2023/05/12 23:48:47 - mmengine - INFO - Epoch(train) [1][ 250/1196] lr: 8.0000e-03 eta: 1 day, 4:05:45 time: 1.8603 data_time: 0.0033 memory: 4931 grad_norm: 0.8400 loss: 0.7520 loss_sem_seg: 0.7520 2023/05/12 23:50:22 - mmengine - INFO - Epoch(train) [1][ 300/1196] lr: 8.0000e-03 eta: 1 day, 3:09:19 time: 1.9043 data_time: 0.0033 memory: 4633 grad_norm: 0.8953 loss: 0.7430 loss_sem_seg: 0.7430 2023/05/12 23:51:57 - mmengine - INFO - Epoch(train) [1][ 350/1196] lr: 8.0000e-03 eta: 1 day, 2:26:15 time: 1.8816 data_time: 0.0032 memory: 4546 grad_norm: 0.7747 loss: 0.6944 loss_sem_seg: 0.6944 2023/05/12 23:53:30 - mmengine - INFO - Epoch(train) [1][ 400/1196] lr: 8.0000e-03 eta: 1 day, 1:52:20 time: 1.8680 data_time: 0.0033 memory: 5812 grad_norm: 1.0442 loss: 0.6782 loss_sem_seg: 0.6782 2023/05/12 23:55:05 - mmengine - INFO - Epoch(train) [1][ 450/1196] lr: 8.0000e-03 eta: 1 day, 1:28:20 time: 1.9022 data_time: 0.0033 memory: 4759 grad_norm: 0.7837 loss: 0.6269 loss_sem_seg: 0.6269 2023/05/12 23:56:39 - mmengine - INFO - Epoch(train) [1][ 500/1196] lr: 8.0000e-03 eta: 1 day, 1:07:03 time: 1.8775 data_time: 0.0032 memory: 4772 grad_norm: 0.8459 loss: 0.6166 loss_sem_seg: 0.6166 2023/05/12 23:58:10 - mmengine - INFO - Epoch(train) [1][ 550/1196] lr: 8.0000e-03 eta: 1 day, 0:45:12 time: 1.8131 data_time: 0.0033 memory: 5298 grad_norm: 0.7055 loss: 0.6540 loss_sem_seg: 0.6540 2023/05/12 23:59:41 - mmengine - INFO - Epoch(train) [1][ 600/1196] lr: 8.0000e-03 eta: 1 day, 0:28:02 time: 1.8349 data_time: 0.0032 memory: 4466 grad_norm: 0.6344 loss: 0.5413 loss_sem_seg: 0.5413 2023/05/13 00:01:16 - mmengine - INFO - Epoch(train) [1][ 650/1196] lr: 8.0000e-03 eta: 1 day, 0:16:38 time: 1.8968 data_time: 0.0032 memory: 5230 grad_norm: 0.6703 loss: 0.6028 loss_sem_seg: 0.6028 2023/05/13 00:02:51 - mmengine - INFO - Epoch(train) [1][ 700/1196] lr: 8.0000e-03 eta: 1 day, 0:06:41 time: 1.8977 data_time: 0.0034 memory: 5163 grad_norm: 0.5192 loss: 0.5458 loss_sem_seg: 0.5458 2023/05/13 00:04:25 - mmengine - INFO - Epoch(train) [1][ 750/1196] lr: 8.0000e-03 eta: 23:57:21 time: 1.8872 data_time: 0.0034 memory: 4437 grad_norm: 0.5617 loss: 0.5079 loss_sem_seg: 0.5079 2023/05/13 00:05:57 - mmengine - INFO - Epoch(train) [1][ 800/1196] lr: 8.0000e-03 eta: 23:46:33 time: 1.8317 data_time: 0.0032 memory: 4330 grad_norm: 0.5766 loss: 0.5148 loss_sem_seg: 0.5148 2023/05/13 00:07:31 - mmengine - INFO - Epoch(train) [1][ 850/1196] lr: 8.0000e-03 eta: 23:38:29 time: 1.8715 data_time: 0.0032 memory: 4903 grad_norm: 0.4787 loss: 0.4939 loss_sem_seg: 0.4939 2023/05/13 00:09:06 - mmengine - INFO - Epoch(train) [1][ 900/1196] lr: 8.0000e-03 eta: 23:32:51 time: 1.9151 data_time: 0.0033 memory: 4733 grad_norm: 0.5094 loss: 0.4945 loss_sem_seg: 0.4945 2023/05/13 00:10:37 - mmengine - INFO - Epoch(train) [1][ 950/1196] lr: 8.0000e-03 eta: 23:23:47 time: 1.8109 data_time: 0.0033 memory: 4605 grad_norm: 0.5385 loss: 0.4877 loss_sem_seg: 0.4877 2023/05/13 00:12:04 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 00:12:04 - mmengine - INFO - Epoch(train) [1][1000/1196] lr: 8.0000e-03 eta: 23:12:45 time: 1.7332 data_time: 0.0033 memory: 4938 grad_norm: 0.4744 loss: 0.5041 loss_sem_seg: 0.5041 2023/05/13 00:13:30 - mmengine - INFO - Epoch(train) [1][1050/1196] lr: 8.0000e-03 eta: 23:02:41 time: 1.7347 data_time: 0.0033 memory: 4649 grad_norm: 0.5229 loss: 0.4878 loss_sem_seg: 0.4878 2023/05/13 00:14:57 - mmengine - INFO - Epoch(train) [1][1100/1196] lr: 8.0000e-03 eta: 22:53:07 time: 1.7258 data_time: 0.0032 memory: 4697 grad_norm: 0.4752 loss: 0.4950 loss_sem_seg: 0.4950 2023/05/13 00:16:22 - mmengine - INFO - Epoch(train) [1][1150/1196] lr: 8.0000e-03 eta: 22:43:42 time: 1.7070 data_time: 0.0033 memory: 4610 grad_norm: 0.4974 loss: 0.4644 loss_sem_seg: 0.4644 2023/05/13 00:17:44 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 00:17:44 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/05/13 00:18:07 - mmengine - INFO - Epoch(val) [1][ 50/509] eta: 0:02:37 time: 0.3434 data_time: 0.0029 memory: 5005 2023/05/13 00:18:23 - mmengine - INFO - Epoch(val) [1][100/509] eta: 0:02:15 time: 0.3198 data_time: 0.0021 memory: 914 2023/05/13 00:18:38 - mmengine - INFO - Epoch(val) [1][150/509] eta: 0:01:56 time: 0.3105 data_time: 0.0020 memory: 915 2023/05/13 00:18:54 - mmengine - INFO - Epoch(val) [1][200/509] eta: 0:01:40 time: 0.3218 data_time: 0.0020 memory: 901 2023/05/13 00:19:11 - mmengine - INFO - Epoch(val) [1][250/509] eta: 0:01:24 time: 0.3326 data_time: 0.0020 memory: 929 2023/05/13 00:19:24 - mmengine - INFO - Epoch(val) [1][300/509] eta: 0:01:05 time: 0.2587 data_time: 0.0020 memory: 867 2023/05/13 00:19:39 - mmengine - INFO - Epoch(val) [1][350/509] eta: 0:00:49 time: 0.2907 data_time: 0.0020 memory: 891 2023/05/13 00:19:53 - mmengine - INFO - Epoch(val) [1][400/509] eta: 0:00:33 time: 0.2927 data_time: 0.0020 memory: 899 2023/05/13 00:20:08 - mmengine - INFO - Epoch(val) [1][450/509] eta: 0:00:18 time: 0.3048 data_time: 0.0020 memory: 911 2023/05/13 00:20:22 - mmengine - INFO - Epoch(val) [1][500/509] eta: 0:00:02 time: 0.2808 data_time: 0.0019 memory: 893 2023/05/13 00:20:45 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9095 | 0.0000 | 0.2436 | 0.1682 | 0.0043 | 0.0027 | 0.0087 | 0.0000 | 0.8931 | 0.0009 | 0.7192 | 0.0000 | 0.8639 | 0.4986 | 0.8781 | 0.5399 | 0.7124 | 0.5329 | 0.2706 | 0.3814 | 0.8898 | 0.4419 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 00:20:45 - mmengine - INFO - Epoch(val) [1][509/509] car: 0.9095 bicycle: 0.0000 motorcycle: 0.2436 truck: 0.1682 bus: 0.0043 person: 0.0027 bicyclist: 0.0087 motorcyclist: 0.0000 road: 0.8931 parking: 0.0009 sidewalk: 0.7192 other-ground: 0.0000 building: 0.8639 fence: 0.4986 vegetation: 0.8781 trunck: 0.5399 terrian: 0.7124 pole: 0.5329 traffic-sign: 0.2706 miou: 0.3814 acc: 0.8898 acc_cls: 0.4419 data_time: 0.0020 time: 0.2852 2023/05/13 00:22:19 - mmengine - INFO - Epoch(train) [2][ 50/1196] lr: 8.0000e-03 eta: 22:34:14 time: 1.8749 data_time: 0.0045 memory: 4677 grad_norm: 0.5513 loss: 0.4536 loss_sem_seg: 0.4536 2023/05/13 00:23:47 - mmengine - INFO - Epoch(train) [2][ 100/1196] lr: 8.0000e-03 eta: 22:27:56 time: 1.7690 data_time: 0.0032 memory: 4501 grad_norm: 0.4942 loss: 0.4332 loss_sem_seg: 0.4332 2023/05/13 00:25:10 - mmengine - INFO - Epoch(train) [2][ 150/1196] lr: 8.0000e-03 eta: 22:19:21 time: 1.6665 data_time: 0.0032 memory: 4645 grad_norm: 0.4515 loss: 0.4584 loss_sem_seg: 0.4584 2023/05/13 00:26:32 - mmengine - INFO - Epoch(train) [2][ 200/1196] lr: 8.0000e-03 eta: 22:10:17 time: 1.6271 data_time: 0.0031 memory: 4560 grad_norm: 0.4106 loss: 0.4216 loss_sem_seg: 0.4216 2023/05/13 00:27:50 - mmengine - INFO - Epoch(train) [2][ 250/1196] lr: 8.0000e-03 eta: 22:00:09 time: 1.5600 data_time: 0.0032 memory: 5130 grad_norm: 0.4264 loss: 0.4277 loss_sem_seg: 0.4277 2023/05/13 00:29:13 - mmengine - INFO - Epoch(train) [2][ 300/1196] lr: 8.0000e-03 eta: 21:53:14 time: 1.6734 data_time: 0.0031 memory: 4622 grad_norm: 0.4430 loss: 0.4286 loss_sem_seg: 0.4286 2023/05/13 00:30:35 - mmengine - INFO - Epoch(train) [2][ 350/1196] lr: 8.0000e-03 eta: 21:45:56 time: 1.6399 data_time: 0.0031 memory: 4790 grad_norm: 0.4193 loss: 0.4563 loss_sem_seg: 0.4563 2023/05/13 00:32:07 - mmengine - INFO - Epoch(train) [2][ 400/1196] lr: 8.0000e-03 eta: 21:43:16 time: 1.8373 data_time: 0.0031 memory: 4573 grad_norm: 0.5218 loss: 0.4584 loss_sem_seg: 0.4584 2023/05/13 00:33:40 - mmengine - INFO - Epoch(train) [2][ 450/1196] lr: 8.0000e-03 eta: 21:41:08 time: 1.8593 data_time: 0.0033 memory: 4822 grad_norm: 0.4070 loss: 0.4379 loss_sem_seg: 0.4379 2023/05/13 00:35:15 - mmengine - INFO - Epoch(train) [2][ 500/1196] lr: 8.0000e-03 eta: 21:39:45 time: 1.8946 data_time: 0.0032 memory: 4696 grad_norm: 0.3840 loss: 0.4277 loss_sem_seg: 0.4277 2023/05/13 00:36:47 - mmengine - INFO - Epoch(train) [2][ 550/1196] lr: 8.0000e-03 eta: 21:37:23 time: 1.8446 data_time: 0.0031 memory: 4665 grad_norm: 0.4635 loss: 0.4248 loss_sem_seg: 0.4248 2023/05/13 00:38:20 - mmengine - INFO - Epoch(train) [2][ 600/1196] lr: 8.0000e-03 eta: 21:35:17 time: 1.8569 data_time: 0.0032 memory: 4717 grad_norm: 0.4084 loss: 0.4022 loss_sem_seg: 0.4022 2023/05/13 00:39:55 - mmengine - INFO - Epoch(train) [2][ 650/1196] lr: 8.0000e-03 eta: 21:33:59 time: 1.8987 data_time: 0.0032 memory: 4965 grad_norm: 0.3824 loss: 0.4095 loss_sem_seg: 0.4095 2023/05/13 00:41:28 - mmengine - INFO - Epoch(train) [2][ 700/1196] lr: 8.0000e-03 eta: 21:32:06 time: 1.8660 data_time: 0.0031 memory: 4857 grad_norm: 0.4410 loss: 0.4120 loss_sem_seg: 0.4120 2023/05/13 00:43:00 - mmengine - INFO - Epoch(train) [2][ 750/1196] lr: 8.0000e-03 eta: 21:29:42 time: 1.8368 data_time: 0.0032 memory: 4549 grad_norm: 0.3834 loss: 0.3825 loss_sem_seg: 0.3825 2023/05/13 00:44:33 - mmengine - INFO - Epoch(train) [2][ 800/1196] lr: 8.0000e-03 eta: 21:27:45 time: 1.8599 data_time: 0.0032 memory: 4819 grad_norm: 0.3766 loss: 0.3826 loss_sem_seg: 0.3826 2023/05/13 00:44:41 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 00:46:07 - mmengine - INFO - Epoch(train) [2][ 850/1196] lr: 8.0000e-03 eta: 21:26:10 time: 1.8813 data_time: 0.0033 memory: 4691 grad_norm: 0.3192 loss: 0.3884 loss_sem_seg: 0.3884 2023/05/13 00:47:40 - mmengine - INFO - Epoch(train) [2][ 900/1196] lr: 8.0000e-03 eta: 21:24:12 time: 1.8568 data_time: 0.0033 memory: 5349 grad_norm: 0.3853 loss: 0.3837 loss_sem_seg: 0.3837 2023/05/13 00:49:14 - mmengine - INFO - Epoch(train) [2][ 950/1196] lr: 8.0000e-03 eta: 21:22:40 time: 1.8833 data_time: 0.0032 memory: 4467 grad_norm: 0.3164 loss: 0.3962 loss_sem_seg: 0.3962 2023/05/13 00:50:46 - mmengine - INFO - Epoch(train) [2][1000/1196] lr: 8.0000e-03 eta: 21:20:26 time: 1.8382 data_time: 0.0032 memory: 4431 grad_norm: 0.3514 loss: 0.3934 loss_sem_seg: 0.3934 2023/05/13 00:52:16 - mmengine - INFO - Epoch(train) [2][1050/1196] lr: 8.0000e-03 eta: 21:17:39 time: 1.8007 data_time: 0.0033 memory: 4666 grad_norm: 0.3766 loss: 0.3789 loss_sem_seg: 0.3789 2023/05/13 00:53:43 - mmengine - INFO - Epoch(train) [2][1100/1196] lr: 8.0000e-03 eta: 21:14:00 time: 1.7368 data_time: 0.0031 memory: 4476 grad_norm: 0.3846 loss: 0.3949 loss_sem_seg: 0.3949 2023/05/13 00:55:09 - mmengine - INFO - Epoch(train) [2][1150/1196] lr: 8.0000e-03 eta: 21:10:14 time: 1.7229 data_time: 0.0033 memory: 4954 grad_norm: 0.3119 loss: 0.3649 loss_sem_seg: 0.3649 2023/05/13 00:56:28 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 00:56:28 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/05/13 00:56:51 - mmengine - INFO - Epoch(val) [2][ 50/509] eta: 0:02:29 time: 0.3253 data_time: 0.0021 memory: 5138 2023/05/13 00:57:04 - mmengine - INFO - Epoch(val) [2][100/509] eta: 0:02:02 time: 0.2740 data_time: 0.0021 memory: 914 2023/05/13 00:57:17 - mmengine - INFO - Epoch(val) [2][150/509] eta: 0:01:42 time: 0.2610 data_time: 0.0020 memory: 915 2023/05/13 00:57:31 - mmengine - INFO - Epoch(val) [2][200/509] eta: 0:01:26 time: 0.2648 data_time: 0.0021 memory: 901 2023/05/13 00:57:45 - mmengine - INFO - Epoch(val) [2][250/509] eta: 0:01:13 time: 0.2923 data_time: 0.0021 memory: 929 2023/05/13 00:57:58 - mmengine - INFO - Epoch(val) [2][300/509] eta: 0:00:58 time: 0.2505 data_time: 0.0021 memory: 867 2023/05/13 00:58:11 - mmengine - INFO - Epoch(val) [2][350/509] eta: 0:00:43 time: 0.2543 data_time: 0.0021 memory: 891 2023/05/13 00:58:25 - mmengine - INFO - Epoch(val) [2][400/509] eta: 0:00:30 time: 0.2876 data_time: 0.0020 memory: 899 2023/05/13 00:58:38 - mmengine - INFO - Epoch(val) [2][450/509] eta: 0:00:16 time: 0.2670 data_time: 0.0020 memory: 911 2023/05/13 00:58:52 - mmengine - INFO - Epoch(val) [2][500/509] eta: 0:00:02 time: 0.2823 data_time: 0.0020 memory: 893 2023/05/13 00:59:13 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9403 | 0.0016 | 0.4440 | 0.2101 | 0.2629 | 0.1560 | 0.4306 | 0.0245 | 0.9027 | 0.1552 | 0.7489 | 0.0000 | 0.8862 | 0.5489 | 0.8822 | 0.6324 | 0.7527 | 0.6033 | 0.4346 | 0.4746 | 0.9029 | 0.5590 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 00:59:13 - mmengine - INFO - Epoch(val) [2][509/509] car: 0.9403 bicycle: 0.0016 motorcycle: 0.4440 truck: 0.2101 bus: 0.2629 person: 0.1560 bicyclist: 0.4306 motorcyclist: 0.0245 road: 0.9027 parking: 0.1552 sidewalk: 0.7489 other-ground: 0.0000 building: 0.8862 fence: 0.5489 vegetation: 0.8822 trunck: 0.6324 terrian: 0.7527 pole: 0.6033 traffic-sign: 0.4346 miou: 0.4746 acc: 0.9029 acc_cls: 0.5590 data_time: 0.0020 time: 0.2977 2023/05/13 01:00:48 - mmengine - INFO - Epoch(train) [3][ 50/1196] lr: 8.0000e-03 eta: 21:05:37 time: 1.8922 data_time: 0.0041 memory: 5357 grad_norm: 0.2911 loss: 0.3610 loss_sem_seg: 0.3610 2023/05/13 01:02:12 - mmengine - INFO - Epoch(train) [3][ 100/1196] lr: 8.0000e-03 eta: 21:01:31 time: 1.6814 data_time: 0.0035 memory: 4927 grad_norm: 0.3269 loss: 0.3447 loss_sem_seg: 0.3447 2023/05/13 01:03:34 - mmengine - INFO - Epoch(train) [3][ 150/1196] lr: 8.0000e-03 eta: 20:56:54 time: 1.6366 data_time: 0.0034 memory: 5068 grad_norm: 0.3588 loss: 0.3692 loss_sem_seg: 0.3692 2023/05/13 01:04:57 - mmengine - INFO - Epoch(train) [3][ 200/1196] lr: 8.0000e-03 eta: 20:52:43 time: 1.6582 data_time: 0.0033 memory: 4458 grad_norm: 0.3347 loss: 0.4001 loss_sem_seg: 0.4001 2023/05/13 01:06:17 - mmengine - INFO - Epoch(train) [3][ 250/1196] lr: 8.0000e-03 eta: 20:48:02 time: 1.6126 data_time: 0.0031 memory: 4468 grad_norm: 0.3154 loss: 0.3846 loss_sem_seg: 0.3846 2023/05/13 01:07:38 - mmengine - INFO - Epoch(train) [3][ 300/1196] lr: 8.0000e-03 eta: 20:43:34 time: 1.6179 data_time: 0.0033 memory: 4975 grad_norm: 0.3576 loss: 0.3862 loss_sem_seg: 0.3862 2023/05/13 01:09:01 - mmengine - INFO - Epoch(train) [3][ 350/1196] lr: 8.0000e-03 eta: 20:39:35 time: 1.6503 data_time: 0.0032 memory: 4563 grad_norm: 0.2970 loss: 0.3786 loss_sem_seg: 0.3786 2023/05/13 01:10:29 - mmengine - INFO - Epoch(train) [3][ 400/1196] lr: 8.0000e-03 eta: 20:37:05 time: 1.7636 data_time: 0.0032 memory: 4576 grad_norm: 0.2772 loss: 0.3654 loss_sem_seg: 0.3654 2023/05/13 01:12:00 - mmengine - INFO - Epoch(train) [3][ 450/1196] lr: 8.0000e-03 eta: 20:35:18 time: 1.8226 data_time: 0.0033 memory: 4814 grad_norm: 0.3040 loss: 0.3553 loss_sem_seg: 0.3553 2023/05/13 01:13:34 - mmengine - INFO - Epoch(train) [3][ 500/1196] lr: 8.0000e-03 eta: 20:34:09 time: 1.8772 data_time: 0.0033 memory: 4693 grad_norm: 0.2992 loss: 0.3812 loss_sem_seg: 0.3812 2023/05/13 01:15:07 - mmengine - INFO - Epoch(train) [3][ 550/1196] lr: 8.0000e-03 eta: 20:32:53 time: 1.8676 data_time: 0.0033 memory: 4324 grad_norm: 0.3037 loss: 0.3615 loss_sem_seg: 0.3615 2023/05/13 01:16:41 - mmengine - INFO - Epoch(train) [3][ 600/1196] lr: 8.0000e-03 eta: 20:31:40 time: 1.8723 data_time: 0.0034 memory: 4814 grad_norm: 0.2634 loss: 0.3943 loss_sem_seg: 0.3943 2023/05/13 01:16:56 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 01:18:06 - mmengine - INFO - Epoch(train) [3][ 650/1196] lr: 8.0000e-03 eta: 20:28:35 time: 1.7034 data_time: 0.0033 memory: 4463 grad_norm: 0.3069 loss: 0.3317 loss_sem_seg: 0.3317 2023/05/13 01:19:30 - mmengine - INFO - Epoch(train) [3][ 700/1196] lr: 8.0000e-03 eta: 20:25:09 time: 1.6662 data_time: 0.0034 memory: 4666 grad_norm: 0.2416 loss: 0.3309 loss_sem_seg: 0.3309 2023/05/13 01:20:52 - mmengine - INFO - Epoch(train) [3][ 750/1196] lr: 8.0000e-03 eta: 20:21:34 time: 1.6457 data_time: 0.0034 memory: 5276 grad_norm: 0.2506 loss: 0.3175 loss_sem_seg: 0.3175 2023/05/13 01:22:13 - mmengine - INFO - Epoch(train) [3][ 800/1196] lr: 8.0000e-03 eta: 20:17:55 time: 1.6323 data_time: 0.0033 memory: 4414 grad_norm: 0.2465 loss: 0.3382 loss_sem_seg: 0.3382 2023/05/13 01:23:35 - mmengine - INFO - Epoch(train) [3][ 850/1196] lr: 8.0000e-03 eta: 20:14:22 time: 1.6350 data_time: 0.0032 memory: 4603 grad_norm: 0.2577 loss: 0.3414 loss_sem_seg: 0.3414 2023/05/13 01:25:00 - mmengine - INFO - Epoch(train) [3][ 900/1196] lr: 8.0000e-03 eta: 20:11:32 time: 1.7006 data_time: 0.0034 memory: 4598 grad_norm: 0.3259 loss: 0.3488 loss_sem_seg: 0.3488 2023/05/13 01:26:31 - mmengine - INFO - Epoch(train) [3][ 950/1196] lr: 8.0000e-03 eta: 20:09:48 time: 1.8063 data_time: 0.0033 memory: 4921 grad_norm: 0.2654 loss: 0.3261 loss_sem_seg: 0.3261 2023/05/13 01:28:04 - mmengine - INFO - Epoch(train) [3][1000/1196] lr: 8.0000e-03 eta: 20:08:37 time: 1.8632 data_time: 0.0032 memory: 4784 grad_norm: 0.2319 loss: 0.3331 loss_sem_seg: 0.3331 2023/05/13 01:29:37 - mmengine - INFO - Epoch(train) [3][1050/1196] lr: 8.0000e-03 eta: 20:07:30 time: 1.8711 data_time: 0.0032 memory: 4609 grad_norm: 0.2446 loss: 0.3231 loss_sem_seg: 0.3231 2023/05/13 01:31:09 - mmengine - INFO - Epoch(train) [3][1100/1196] lr: 8.0000e-03 eta: 20:06:08 time: 1.8447 data_time: 0.0033 memory: 4841 grad_norm: 0.2804 loss: 0.3422 loss_sem_seg: 0.3422 2023/05/13 01:32:36 - mmengine - INFO - Epoch(train) [3][1150/1196] lr: 8.0000e-03 eta: 20:03:39 time: 1.7260 data_time: 0.0033 memory: 4597 grad_norm: 0.2410 loss: 0.3247 loss_sem_seg: 0.3247 2023/05/13 01:33:56 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 01:33:56 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/05/13 01:34:19 - mmengine - INFO - Epoch(val) [3][ 50/509] eta: 0:02:31 time: 0.3299 data_time: 0.0021 memory: 4768 2023/05/13 01:34:34 - mmengine - INFO - Epoch(val) [3][100/509] eta: 0:02:07 time: 0.2938 data_time: 0.0021 memory: 914 2023/05/13 01:34:47 - mmengine - INFO - Epoch(val) [3][150/509] eta: 0:01:46 time: 0.2701 data_time: 0.0020 memory: 915 2023/05/13 01:35:01 - mmengine - INFO - Epoch(val) [3][200/509] eta: 0:01:30 time: 0.2762 data_time: 0.0020 memory: 901 2023/05/13 01:35:17 - mmengine - INFO - Epoch(val) [3][250/509] eta: 0:01:16 time: 0.3147 data_time: 0.0021 memory: 929 2023/05/13 01:35:29 - mmengine - INFO - Epoch(val) [3][300/509] eta: 0:01:00 time: 0.2517 data_time: 0.0021 memory: 867 2023/05/13 01:35:43 - mmengine - INFO - Epoch(val) [3][350/509] eta: 0:00:45 time: 0.2753 data_time: 0.0020 memory: 891 2023/05/13 01:35:57 - mmengine - INFO - Epoch(val) [3][400/509] eta: 0:00:31 time: 0.2794 data_time: 0.0020 memory: 899 2023/05/13 01:36:12 - mmengine - INFO - Epoch(val) [3][450/509] eta: 0:00:16 time: 0.2869 data_time: 0.0022 memory: 911 2023/05/13 01:36:25 - mmengine - INFO - Epoch(val) [3][500/509] eta: 0:00:02 time: 0.2726 data_time: 0.0021 memory: 893 2023/05/13 01:36:44 - 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 | 0.9044 | 0.1291 | 0.3374 | 0.2710 | 0.0282 | 0.5028 | 0.6988 | 0.0026 | 0.8926 | 0.2468 | 0.7726 | 0.0003 | 0.8916 | 0.6044 | 0.8901 | 0.5930 | 0.7721 | 0.6280 | 0.4660 | 0.5069 | 0.9086 | 0.5750 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 01:36:44 - mmengine - INFO - Epoch(val) [3][509/509] car: 0.9044 bicycle: 0.1291 motorcycle: 0.3374 truck: 0.2710 bus: 0.0282 person: 0.5028 bicyclist: 0.6988 motorcyclist: 0.0026 road: 0.8926 parking: 0.2468 sidewalk: 0.7726 other-ground: 0.0003 building: 0.8916 fence: 0.6044 vegetation: 0.8901 trunck: 0.5930 terrian: 0.7721 pole: 0.6280 traffic-sign: 0.4660 miou: 0.5069 acc: 0.9086 acc_cls: 0.5750 data_time: 0.0020 time: 0.2822 2023/05/13 01:38:11 - mmengine - INFO - Epoch(train) [4][ 50/1196] lr: 8.0000e-03 eta: 19:59:18 time: 1.7464 data_time: 0.0040 memory: 4570 grad_norm: 0.2327 loss: 0.3161 loss_sem_seg: 0.3161 2023/05/13 01:39:43 - mmengine - INFO - Epoch(train) [4][ 100/1196] lr: 8.0000e-03 eta: 19:57:51 time: 1.8335 data_time: 0.0033 memory: 5155 grad_norm: 0.2084 loss: 0.3175 loss_sem_seg: 0.3175 2023/05/13 01:41:13 - mmengine - INFO - Epoch(train) [4][ 150/1196] lr: 8.0000e-03 eta: 19:56:15 time: 1.8158 data_time: 0.0033 memory: 4684 grad_norm: 0.2442 loss: 0.3320 loss_sem_seg: 0.3320 2023/05/13 01:42:48 - mmengine - INFO - Epoch(train) [4][ 200/1196] lr: 8.0000e-03 eta: 19:55:15 time: 1.8863 data_time: 0.0032 memory: 5003 grad_norm: 0.2567 loss: 0.3483 loss_sem_seg: 0.3483 2023/05/13 01:44:21 - mmengine - INFO - Epoch(train) [4][ 250/1196] lr: 8.0000e-03 eta: 19:54:05 time: 1.8684 data_time: 0.0033 memory: 4992 grad_norm: 0.2140 loss: 0.3368 loss_sem_seg: 0.3368 2023/05/13 01:45:53 - mmengine - INFO - Epoch(train) [4][ 300/1196] lr: 8.0000e-03 eta: 19:52:40 time: 1.8398 data_time: 0.0034 memory: 4601 grad_norm: 0.2285 loss: 0.3318 loss_sem_seg: 0.3318 2023/05/13 01:47:27 - mmengine - INFO - Epoch(train) [4][ 350/1196] lr: 8.0000e-03 eta: 19:51:29 time: 1.8680 data_time: 0.0034 memory: 4993 grad_norm: 0.2142 loss: 0.3293 loss_sem_seg: 0.3293 2023/05/13 01:49:01 - mmengine - INFO - Epoch(train) [4][ 400/1196] lr: 8.0000e-03 eta: 19:50:28 time: 1.8895 data_time: 0.0032 memory: 4726 grad_norm: 0.2435 loss: 0.3449 loss_sem_seg: 0.3449 2023/05/13 01:49:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 01:50:36 - mmengine - INFO - Epoch(train) [4][ 450/1196] lr: 8.0000e-03 eta: 19:49:28 time: 1.8922 data_time: 0.0033 memory: 4828 grad_norm: 0.2409 loss: 0.3251 loss_sem_seg: 0.3251 2023/05/13 01:52:09 - mmengine - INFO - Epoch(train) [4][ 500/1196] lr: 8.0000e-03 eta: 19:48:18 time: 1.8744 data_time: 0.0032 memory: 4929 grad_norm: 0.2252 loss: 0.3050 loss_sem_seg: 0.3050 2023/05/13 01:53:43 - mmengine - INFO - Epoch(train) [4][ 550/1196] lr: 8.0000e-03 eta: 19:47:08 time: 1.8756 data_time: 0.0034 memory: 4611 grad_norm: 0.2219 loss: 0.3380 loss_sem_seg: 0.3380 2023/05/13 01:55:14 - mmengine - INFO - Epoch(train) [4][ 600/1196] lr: 8.0000e-03 eta: 19:45:32 time: 1.8199 data_time: 0.0034 memory: 4715 grad_norm: 0.2290 loss: 0.3256 loss_sem_seg: 0.3256 2023/05/13 01:56:46 - mmengine - INFO - Epoch(train) [4][ 650/1196] lr: 8.0000e-03 eta: 19:44:00 time: 1.8304 data_time: 0.0033 memory: 4629 grad_norm: 0.1989 loss: 0.3349 loss_sem_seg: 0.3349 2023/05/13 01:58:18 - mmengine - INFO - Epoch(train) [4][ 700/1196] lr: 8.0000e-03 eta: 19:42:34 time: 1.8414 data_time: 0.0032 memory: 4641 grad_norm: 0.2485 loss: 0.3313 loss_sem_seg: 0.3313 2023/05/13 01:59:50 - mmengine - INFO - Epoch(train) [4][ 750/1196] lr: 8.0000e-03 eta: 19:41:11 time: 1.8482 data_time: 0.0033 memory: 4914 grad_norm: 0.2037 loss: 0.3176 loss_sem_seg: 0.3176 2023/05/13 02:01:24 - mmengine - INFO - Epoch(train) [4][ 800/1196] lr: 8.0000e-03 eta: 19:39:57 time: 1.8712 data_time: 0.0033 memory: 5016 grad_norm: 0.2206 loss: 0.3306 loss_sem_seg: 0.3306 2023/05/13 02:02:57 - mmengine - INFO - Epoch(train) [4][ 850/1196] lr: 8.0000e-03 eta: 19:38:43 time: 1.8716 data_time: 0.0033 memory: 4755 grad_norm: 0.2040 loss: 0.3253 loss_sem_seg: 0.3253 2023/05/13 02:04:32 - mmengine - INFO - Epoch(train) [4][ 900/1196] lr: 8.0000e-03 eta: 19:37:41 time: 1.8990 data_time: 0.0032 memory: 4482 grad_norm: 0.1967 loss: 0.2917 loss_sem_seg: 0.2917 2023/05/13 02:06:06 - mmengine - INFO - Epoch(train) [4][ 950/1196] lr: 8.0000e-03 eta: 19:36:23 time: 1.8648 data_time: 0.0032 memory: 4552 grad_norm: 0.1937 loss: 0.3066 loss_sem_seg: 0.3066 2023/05/13 02:07:40 - mmengine - INFO - Epoch(train) [4][1000/1196] lr: 8.0000e-03 eta: 19:35:12 time: 1.8826 data_time: 0.0033 memory: 4496 grad_norm: 0.1843 loss: 0.3017 loss_sem_seg: 0.3017 2023/05/13 02:09:11 - mmengine - INFO - Epoch(train) [4][1050/1196] lr: 8.0000e-03 eta: 19:33:38 time: 1.8257 data_time: 0.0032 memory: 4444 grad_norm: 0.1987 loss: 0.3102 loss_sem_seg: 0.3102 2023/05/13 02:10:41 - mmengine - INFO - Epoch(train) [4][1100/1196] lr: 8.0000e-03 eta: 19:31:50 time: 1.7935 data_time: 0.0033 memory: 4731 grad_norm: 0.2177 loss: 0.2919 loss_sem_seg: 0.2919 2023/05/13 02:12:12 - mmengine - INFO - Epoch(train) [4][1150/1196] lr: 8.0000e-03 eta: 19:30:17 time: 1.8292 data_time: 0.0032 memory: 5187 grad_norm: 0.2014 loss: 0.2902 loss_sem_seg: 0.2902 2023/05/13 02:13:25 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 02:13:25 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/05/13 02:13:45 - mmengine - INFO - Epoch(val) [4][ 50/509] eta: 0:02:04 time: 0.2719 data_time: 0.0021 memory: 4767 2023/05/13 02:13:57 - mmengine - INFO - Epoch(val) [4][100/509] eta: 0:01:43 time: 0.2343 data_time: 0.0021 memory: 914 2023/05/13 02:14:08 - mmengine - INFO - Epoch(val) [4][150/509] eta: 0:01:27 time: 0.2243 data_time: 0.0021 memory: 915 2023/05/13 02:14:20 - mmengine - INFO - Epoch(val) [4][200/509] eta: 0:01:14 time: 0.2309 data_time: 0.0021 memory: 901 2023/05/13 02:14:32 - mmengine - INFO - Epoch(val) [4][250/509] eta: 0:01:02 time: 0.2515 data_time: 0.0021 memory: 929 2023/05/13 02:14:43 - mmengine - INFO - Epoch(val) [4][300/509] eta: 0:00:49 time: 0.2157 data_time: 0.0020 memory: 867 2023/05/13 02:14:55 - mmengine - INFO - Epoch(val) [4][350/509] eta: 0:00:37 time: 0.2377 data_time: 0.0020 memory: 891 2023/05/13 02:15:08 - mmengine - INFO - Epoch(val) [4][400/509] eta: 0:00:26 time: 0.2539 data_time: 0.0021 memory: 899 2023/05/13 02:15:20 - mmengine - INFO - Epoch(val) [4][450/509] eta: 0:00:14 time: 0.2471 data_time: 0.0020 memory: 911 2023/05/13 02:15:32 - mmengine - INFO - Epoch(val) [4][500/509] eta: 0:00:02 time: 0.2377 data_time: 0.0020 memory: 893 2023/05/13 02:15:50 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9606 | 0.2927 | 0.5678 | 0.4301 | 0.4805 | 0.6403 | 0.7200 | 0.0079 | 0.9277 | 0.3593 | 0.7982 | 0.0017 | 0.8895 | 0.5904 | 0.8972 | 0.6654 | 0.7823 | 0.6333 | 0.4859 | 0.5858 | 0.9202 | 0.6863 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 02:15:50 - mmengine - INFO - Epoch(val) [4][509/509] car: 0.9606 bicycle: 0.2927 motorcycle: 0.5678 truck: 0.4301 bus: 0.4805 person: 0.6403 bicyclist: 0.7200 motorcyclist: 0.0079 road: 0.9277 parking: 0.3593 sidewalk: 0.7982 other-ground: 0.0017 building: 0.8895 fence: 0.5904 vegetation: 0.8972 trunck: 0.6654 terrian: 0.7823 pole: 0.6333 traffic-sign: 0.4859 miou: 0.5858 acc: 0.9202 acc_cls: 0.6863 data_time: 0.0021 time: 0.2514 2023/05/13 02:17:05 - mmengine - INFO - Epoch(train) [5][ 50/1196] lr: 8.0000e-03 eta: 19:23:39 time: 1.4991 data_time: 0.0043 memory: 4538 grad_norm: 0.2017 loss: 0.3227 loss_sem_seg: 0.3227 2023/05/13 02:18:22 - mmengine - INFO - Epoch(train) [5][ 100/1196] lr: 8.0000e-03 eta: 19:20:12 time: 1.5322 data_time: 0.0031 memory: 4791 grad_norm: 0.2016 loss: 0.3140 loss_sem_seg: 0.3140 2023/05/13 02:19:52 - mmengine - INFO - Epoch(train) [5][ 150/1196] lr: 8.0000e-03 eta: 19:18:31 time: 1.7968 data_time: 0.0033 memory: 4984 grad_norm: 0.2265 loss: 0.3122 loss_sem_seg: 0.3122 2023/05/13 02:21:25 - mmengine - INFO - Epoch(train) [5][ 200/1196] lr: 8.0000e-03 eta: 19:17:17 time: 1.8693 data_time: 0.0033 memory: 4696 grad_norm: 0.2441 loss: 0.3211 loss_sem_seg: 0.3211 2023/05/13 02:21:55 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 02:22:58 - mmengine - INFO - Epoch(train) [5][ 250/1196] lr: 8.0000e-03 eta: 19:15:59 time: 1.8598 data_time: 0.0034 memory: 4560 grad_norm: 0.1948 loss: 0.2859 loss_sem_seg: 0.2859 2023/05/13 02:24:29 - mmengine - INFO - Epoch(train) [5][ 300/1196] lr: 8.0000e-03 eta: 19:14:23 time: 1.8112 data_time: 0.0034 memory: 5066 grad_norm: 0.1920 loss: 0.2990 loss_sem_seg: 0.2990 2023/05/13 02:26:02 - mmengine - INFO - Epoch(train) [5][ 350/1196] lr: 8.0000e-03 eta: 19:13:07 time: 1.8641 data_time: 0.0037 memory: 4847 grad_norm: 0.1915 loss: 0.2982 loss_sem_seg: 0.2982 2023/05/13 02:27:38 - mmengine - INFO - Epoch(train) [5][ 400/1196] lr: 8.0000e-03 eta: 19:12:16 time: 1.9347 data_time: 0.0033 memory: 4683 grad_norm: 0.2228 loss: 0.3237 loss_sem_seg: 0.3237 2023/05/13 02:29:10 - mmengine - INFO - Epoch(train) [5][ 450/1196] lr: 8.0000e-03 eta: 19:10:46 time: 1.8284 data_time: 0.0033 memory: 4361 grad_norm: 0.1857 loss: 0.2917 loss_sem_seg: 0.2917 2023/05/13 02:30:43 - mmengine - INFO - Epoch(train) [5][ 500/1196] lr: 8.0000e-03 eta: 19:09:24 time: 1.8533 data_time: 0.0033 memory: 5017 grad_norm: 0.1870 loss: 0.2985 loss_sem_seg: 0.2985 2023/05/13 02:32:17 - mmengine - INFO - Epoch(train) [5][ 550/1196] lr: 8.0000e-03 eta: 19:08:13 time: 1.8831 data_time: 0.0034 memory: 4555 grad_norm: 0.1883 loss: 0.3118 loss_sem_seg: 0.3118 2023/05/13 02:33:51 - mmengine - INFO - Epoch(train) [5][ 600/1196] lr: 8.0000e-03 eta: 19:07:05 time: 1.8926 data_time: 0.0033 memory: 4805 grad_norm: 0.1836 loss: 0.3082 loss_sem_seg: 0.3082 2023/05/13 02:35:25 - mmengine - INFO - Epoch(train) [5][ 650/1196] lr: 8.0000e-03 eta: 19:05:53 time: 1.8826 data_time: 0.0033 memory: 4604 grad_norm: 0.1932 loss: 0.2983 loss_sem_seg: 0.2983 2023/05/13 02:36:58 - mmengine - INFO - Epoch(train) [5][ 700/1196] lr: 8.0000e-03 eta: 19:04:28 time: 1.8458 data_time: 0.0034 memory: 4384 grad_norm: 0.2050 loss: 0.2806 loss_sem_seg: 0.2806 2023/05/13 02:38:32 - mmengine - INFO - Epoch(train) [5][ 750/1196] lr: 8.0000e-03 eta: 19:03:14 time: 1.8791 data_time: 0.0034 memory: 4808 grad_norm: 0.1930 loss: 0.2852 loss_sem_seg: 0.2852 2023/05/13 02:40:03 - mmengine - INFO - Epoch(train) [5][ 800/1196] lr: 8.0000e-03 eta: 19:01:45 time: 1.8341 data_time: 0.0033 memory: 4635 grad_norm: 0.1839 loss: 0.2934 loss_sem_seg: 0.2934 2023/05/13 02:41:37 - mmengine - INFO - Epoch(train) [5][ 850/1196] lr: 8.0000e-03 eta: 19:00:26 time: 1.8668 data_time: 0.0033 memory: 4598 grad_norm: 0.1670 loss: 0.3031 loss_sem_seg: 0.3031 2023/05/13 02:43:10 - mmengine - INFO - Epoch(train) [5][ 900/1196] lr: 8.0000e-03 eta: 18:59:03 time: 1.8552 data_time: 0.0034 memory: 4599 grad_norm: 0.1853 loss: 0.2879 loss_sem_seg: 0.2879 2023/05/13 02:44:44 - mmengine - INFO - Epoch(train) [5][ 950/1196] lr: 8.0000e-03 eta: 18:57:51 time: 1.8863 data_time: 0.0032 memory: 4973 grad_norm: 0.1959 loss: 0.3103 loss_sem_seg: 0.3103 2023/05/13 02:46:17 - mmengine - INFO - Epoch(train) [5][1000/1196] lr: 8.0000e-03 eta: 18:56:33 time: 1.8715 data_time: 0.0033 memory: 4566 grad_norm: 0.2020 loss: 0.2946 loss_sem_seg: 0.2946 2023/05/13 02:47:52 - mmengine - INFO - Epoch(train) [5][1050/1196] lr: 8.0000e-03 eta: 18:55:20 time: 1.8872 data_time: 0.0033 memory: 4675 grad_norm: 0.1870 loss: 0.3104 loss_sem_seg: 0.3104 2023/05/13 02:49:26 - mmengine - INFO - Epoch(train) [5][1100/1196] lr: 8.0000e-03 eta: 18:54:04 time: 1.8799 data_time: 0.0034 memory: 4721 grad_norm: 0.1836 loss: 0.3027 loss_sem_seg: 0.3027 2023/05/13 02:51:00 - mmengine - INFO - Epoch(train) [5][1150/1196] lr: 8.0000e-03 eta: 18:52:46 time: 1.8754 data_time: 0.0034 memory: 4829 grad_norm: 0.2092 loss: 0.2884 loss_sem_seg: 0.2884 2023/05/13 02:52:25 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 02:52:25 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/05/13 02:52:48 - mmengine - INFO - Epoch(val) [5][ 50/509] eta: 0:02:36 time: 0.3419 data_time: 0.0021 memory: 4803 2023/05/13 02:53:04 - mmengine - INFO - Epoch(val) [5][100/509] eta: 0:02:13 time: 0.3119 data_time: 0.0021 memory: 914 2023/05/13 02:53:19 - mmengine - INFO - Epoch(val) [5][150/509] eta: 0:01:54 time: 0.2989 data_time: 0.0021 memory: 915 2023/05/13 02:53:33 - mmengine - INFO - Epoch(val) [5][200/509] eta: 0:01:35 time: 0.2853 data_time: 0.0020 memory: 901 2023/05/13 02:53:49 - mmengine - INFO - Epoch(val) [5][250/509] eta: 0:01:20 time: 0.3235 data_time: 0.0021 memory: 929 2023/05/13 02:54:03 - mmengine - INFO - Epoch(val) [5][300/509] eta: 0:01:04 time: 0.2806 data_time: 0.0021 memory: 867 2023/05/13 02:54:17 - mmengine - INFO - Epoch(val) [5][350/509] eta: 0:00:48 time: 0.2791 data_time: 0.0021 memory: 891 2023/05/13 02:54:31 - mmengine - INFO - Epoch(val) [5][400/509] eta: 0:00:32 time: 0.2768 data_time: 0.0020 memory: 899 2023/05/13 02:54:44 - mmengine - INFO - Epoch(val) [5][450/509] eta: 0:00:17 time: 0.2702 data_time: 0.0021 memory: 911 2023/05/13 02:54:56 - mmengine - INFO - Epoch(val) [5][500/509] eta: 0:00:02 time: 0.2333 data_time: 0.0020 memory: 893 2023/05/13 02:55:16 - 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 | 0.9218 | 0.1161 | 0.5279 | 0.6952 | 0.2531 | 0.5720 | 0.7666 | 0.0290 | 0.9244 | 0.3622 | 0.7874 | 0.0218 | 0.8905 | 0.5827 | 0.8707 | 0.6528 | 0.7180 | 0.6237 | 0.4656 | 0.5674 | 0.9077 | 0.6440 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 02:55:16 - mmengine - INFO - Epoch(val) [5][509/509] car: 0.9218 bicycle: 0.1161 motorcycle: 0.5279 truck: 0.6952 bus: 0.2531 person: 0.5720 bicyclist: 0.7666 motorcyclist: 0.0290 road: 0.9244 parking: 0.3622 sidewalk: 0.7874 other-ground: 0.0218 building: 0.8905 fence: 0.5827 vegetation: 0.8707 trunck: 0.6528 terrian: 0.7180 pole: 0.6237 traffic-sign: 0.4656 miou: 0.5674 acc: 0.9077 acc_cls: 0.6440 data_time: 0.0020 time: 0.2419 2023/05/13 02:55:51 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 02:56:45 - mmengine - INFO - Epoch(train) [6][ 50/1196] lr: 8.0000e-03 eta: 18:49:41 time: 1.7805 data_time: 0.0041 memory: 4749 grad_norm: 0.1649 loss: 0.2619 loss_sem_seg: 0.2619 2023/05/13 02:58:12 - mmengine - INFO - Epoch(train) [6][ 100/1196] lr: 8.0000e-03 eta: 18:47:41 time: 1.7383 data_time: 0.0032 memory: 4557 grad_norm: 0.1590 loss: 0.2794 loss_sem_seg: 0.2794 2023/05/13 02:59:38 - mmengine - INFO - Epoch(train) [6][ 150/1196] lr: 8.0000e-03 eta: 18:45:34 time: 1.7108 data_time: 0.0034 memory: 4494 grad_norm: 0.1822 loss: 0.2982 loss_sem_seg: 0.2982 2023/05/13 03:01:03 - mmengine - INFO - Epoch(train) [6][ 200/1196] lr: 8.0000e-03 eta: 18:43:27 time: 1.7093 data_time: 0.0033 memory: 4784 grad_norm: 0.1857 loss: 0.2894 loss_sem_seg: 0.2894 2023/05/13 03:02:33 - mmengine - INFO - Epoch(train) [6][ 250/1196] lr: 8.0000e-03 eta: 18:41:49 time: 1.8051 data_time: 0.0033 memory: 4816 grad_norm: 0.1830 loss: 0.2891 loss_sem_seg: 0.2891 2023/05/13 03:04:09 - mmengine - INFO - Epoch(train) [6][ 300/1196] lr: 8.0000e-03 eta: 18:40:40 time: 1.9059 data_time: 0.0033 memory: 4529 grad_norm: 0.1641 loss: 0.2789 loss_sem_seg: 0.2789 2023/05/13 03:05:41 - mmengine - INFO - Epoch(train) [6][ 350/1196] lr: 8.0000e-03 eta: 18:39:13 time: 1.8432 data_time: 0.0034 memory: 4512 grad_norm: 0.1684 loss: 0.2975 loss_sem_seg: 0.2975 2023/05/13 03:07:04 - mmengine - INFO - Epoch(train) [6][ 400/1196] lr: 8.0000e-03 eta: 18:36:54 time: 1.6634 data_time: 0.0033 memory: 5059 grad_norm: 0.1450 loss: 0.2716 loss_sem_seg: 0.2716 2023/05/13 03:08:22 - mmengine - INFO - Epoch(train) [6][ 450/1196] lr: 8.0000e-03 eta: 18:34:09 time: 1.5670 data_time: 0.0033 memory: 4494 grad_norm: 0.1694 loss: 0.2924 loss_sem_seg: 0.2924 2023/05/13 03:09:42 - mmengine - INFO - Epoch(train) [6][ 500/1196] lr: 8.0000e-03 eta: 18:31:33 time: 1.5974 data_time: 0.0033 memory: 4966 grad_norm: 0.1782 loss: 0.2776 loss_sem_seg: 0.2776 2023/05/13 03:11:03 - mmengine - INFO - Epoch(train) [6][ 550/1196] lr: 8.0000e-03 eta: 18:29:05 time: 1.6190 data_time: 0.0032 memory: 4540 grad_norm: 0.1664 loss: 0.2902 loss_sem_seg: 0.2902 2023/05/13 03:12:25 - mmengine - INFO - Epoch(train) [6][ 600/1196] lr: 8.0000e-03 eta: 18:26:46 time: 1.6484 data_time: 0.0032 memory: 4499 grad_norm: 0.1755 loss: 0.2912 loss_sem_seg: 0.2912 2023/05/13 03:13:55 - mmengine - INFO - Epoch(train) [6][ 650/1196] lr: 8.0000e-03 eta: 18:25:06 time: 1.7897 data_time: 0.0033 memory: 4972 grad_norm: 0.1874 loss: 0.2840 loss_sem_seg: 0.2840 2023/05/13 03:15:29 - mmengine - INFO - Epoch(train) [6][ 700/1196] lr: 8.0000e-03 eta: 18:23:49 time: 1.8708 data_time: 0.0034 memory: 4821 grad_norm: 0.1644 loss: 0.3003 loss_sem_seg: 0.3003 2023/05/13 03:16:59 - mmengine - INFO - Epoch(train) [6][ 750/1196] lr: 8.0000e-03 eta: 18:22:17 time: 1.8172 data_time: 0.0034 memory: 4625 grad_norm: 0.1537 loss: 0.2991 loss_sem_seg: 0.2991 2023/05/13 03:18:33 - mmengine - INFO - Epoch(train) [6][ 800/1196] lr: 8.0000e-03 eta: 18:21:01 time: 1.8775 data_time: 0.0033 memory: 4611 grad_norm: 0.1609 loss: 0.2736 loss_sem_seg: 0.2736 2023/05/13 03:20:06 - mmengine - INFO - Epoch(train) [6][ 850/1196] lr: 8.0000e-03 eta: 18:19:39 time: 1.8556 data_time: 0.0033 memory: 4787 grad_norm: 0.1839 loss: 0.2814 loss_sem_seg: 0.2814 2023/05/13 03:21:41 - mmengine - INFO - Epoch(train) [6][ 900/1196] lr: 8.0000e-03 eta: 18:18:28 time: 1.8986 data_time: 0.0036 memory: 5033 grad_norm: 0.1625 loss: 0.2767 loss_sem_seg: 0.2767 2023/05/13 03:23:14 - mmengine - INFO - Epoch(train) [6][ 950/1196] lr: 8.0000e-03 eta: 18:17:05 time: 1.8527 data_time: 0.0035 memory: 4788 grad_norm: 0.1505 loss: 0.2622 loss_sem_seg: 0.2622 2023/05/13 03:24:44 - mmengine - INFO - Epoch(train) [6][1000/1196] lr: 8.0000e-03 eta: 18:15:32 time: 1.8145 data_time: 0.0035 memory: 4763 grad_norm: 0.1499 loss: 0.2710 loss_sem_seg: 0.2710 2023/05/13 03:25:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 03:26:19 - mmengine - INFO - Epoch(train) [6][1050/1196] lr: 8.0000e-03 eta: 18:14:19 time: 1.8932 data_time: 0.0033 memory: 4656 grad_norm: 0.1694 loss: 0.2702 loss_sem_seg: 0.2702 2023/05/13 03:27:54 - mmengine - INFO - Epoch(train) [6][1100/1196] lr: 8.0000e-03 eta: 18:13:08 time: 1.8985 data_time: 0.0035 memory: 4584 grad_norm: 0.1436 loss: 0.2798 loss_sem_seg: 0.2798 2023/05/13 03:29:29 - mmengine - INFO - Epoch(train) [6][1150/1196] lr: 8.0000e-03 eta: 18:11:55 time: 1.8948 data_time: 0.0033 memory: 4486 grad_norm: 0.1515 loss: 0.2812 loss_sem_seg: 0.2812 2023/05/13 03:30:56 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 03:30:56 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/05/13 03:31:21 - mmengine - INFO - Epoch(val) [6][ 50/509] eta: 0:02:50 time: 0.3718 data_time: 0.0021 memory: 4600 2023/05/13 03:31:37 - mmengine - INFO - Epoch(val) [6][100/509] eta: 0:02:21 time: 0.3182 data_time: 0.0020 memory: 914 2023/05/13 03:31:52 - mmengine - INFO - Epoch(val) [6][150/509] eta: 0:02:00 time: 0.3167 data_time: 0.0021 memory: 915 2023/05/13 03:32:08 - mmengine - INFO - Epoch(val) [6][200/509] eta: 0:01:41 time: 0.3115 data_time: 0.0022 memory: 901 2023/05/13 03:32:25 - mmengine - INFO - Epoch(val) [6][250/509] eta: 0:01:26 time: 0.3425 data_time: 0.0021 memory: 929 2023/05/13 03:32:38 - mmengine - INFO - Epoch(val) [6][300/509] eta: 0:01:07 time: 0.2630 data_time: 0.0021 memory: 867 2023/05/13 03:32:53 - mmengine - INFO - Epoch(val) [6][350/509] eta: 0:00:50 time: 0.2931 data_time: 0.0021 memory: 891 2023/05/13 03:33:09 - mmengine - INFO - Epoch(val) [6][400/509] eta: 0:00:34 time: 0.3147 data_time: 0.0022 memory: 899 2023/05/13 03:33:24 - mmengine - INFO - Epoch(val) [6][450/509] eta: 0:00:18 time: 0.3099 data_time: 0.0021 memory: 911 2023/05/13 03:33:39 - mmengine - INFO - Epoch(val) [6][500/509] eta: 0:00:02 time: 0.3015 data_time: 0.0021 memory: 893 2023/05/13 03:33:59 - 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 | 0.9336 | 0.3277 | 0.5762 | 0.7059 | 0.2839 | 0.6528 | 0.4008 | 0.0678 | 0.9227 | 0.3274 | 0.8069 | 0.0774 | 0.8931 | 0.5871 | 0.9001 | 0.6759 | 0.7912 | 0.6448 | 0.4785 | 0.5818 | 0.9206 | 0.6817 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 03:33:59 - mmengine - INFO - Epoch(val) [6][509/509] car: 0.9336 bicycle: 0.3277 motorcycle: 0.5762 truck: 0.7059 bus: 0.2839 person: 0.6528 bicyclist: 0.4008 motorcyclist: 0.0678 road: 0.9227 parking: 0.3274 sidewalk: 0.8069 other-ground: 0.0774 building: 0.8931 fence: 0.5871 vegetation: 0.9001 trunck: 0.6759 terrian: 0.7912 pole: 0.6448 traffic-sign: 0.4785 miou: 0.5818 acc: 0.9206 acc_cls: 0.6817 data_time: 0.0021 time: 0.3112 2023/05/13 03:35:32 - mmengine - INFO - Epoch(train) [7][ 50/1196] lr: 8.0000e-03 eta: 18:09:24 time: 1.8614 data_time: 0.0041 memory: 5015 grad_norm: 0.1624 loss: 0.2828 loss_sem_seg: 0.2828 2023/05/13 03:36:56 - mmengine - INFO - Epoch(train) [7][ 100/1196] lr: 8.0000e-03 eta: 18:07:16 time: 1.6770 data_time: 0.0033 memory: 4831 grad_norm: 0.1556 loss: 0.2800 loss_sem_seg: 0.2800 2023/05/13 03:38:10 - mmengine - INFO - Epoch(train) [7][ 150/1196] lr: 8.0000e-03 eta: 18:04:25 time: 1.4947 data_time: 0.0032 memory: 4646 grad_norm: 0.1365 loss: 0.2732 loss_sem_seg: 0.2732 2023/05/13 03:39:25 - mmengine - INFO - Epoch(train) [7][ 200/1196] lr: 8.0000e-03 eta: 18:01:33 time: 1.4863 data_time: 0.0032 memory: 4460 grad_norm: 0.1348 loss: 0.2641 loss_sem_seg: 0.2641 2023/05/13 03:40:40 - mmengine - INFO - Epoch(train) [7][ 250/1196] lr: 8.0000e-03 eta: 17:58:49 time: 1.5125 data_time: 0.0035 memory: 4403 grad_norm: 0.1513 loss: 0.2663 loss_sem_seg: 0.2663 2023/05/13 03:41:56 - mmengine - INFO - Epoch(train) [7][ 300/1196] lr: 8.0000e-03 eta: 17:56:03 time: 1.5037 data_time: 0.0035 memory: 4736 grad_norm: 0.1768 loss: 0.2908 loss_sem_seg: 0.2908 2023/05/13 03:43:17 - mmengine - INFO - Epoch(train) [7][ 350/1196] lr: 8.0000e-03 eta: 17:53:50 time: 1.6324 data_time: 0.0038 memory: 4709 grad_norm: 0.1478 loss: 0.2726 loss_sem_seg: 0.2726 2023/05/13 03:44:41 - mmengine - INFO - Epoch(train) [7][ 400/1196] lr: 8.0000e-03 eta: 17:51:48 time: 1.6819 data_time: 0.0037 memory: 4513 grad_norm: 0.1470 loss: 0.2734 loss_sem_seg: 0.2734 2023/05/13 03:46:18 - mmengine - INFO - Epoch(train) [7][ 450/1196] lr: 8.0000e-03 eta: 17:50:45 time: 1.9306 data_time: 0.0035 memory: 4831 grad_norm: 0.1552 loss: 0.2699 loss_sem_seg: 0.2699 2023/05/13 03:47:51 - mmengine - INFO - Epoch(train) [7][ 500/1196] lr: 8.0000e-03 eta: 17:49:27 time: 1.8706 data_time: 0.0036 memory: 5101 grad_norm: 0.1489 loss: 0.2755 loss_sem_seg: 0.2755 2023/05/13 03:49:23 - mmengine - INFO - Epoch(train) [7][ 550/1196] lr: 8.0000e-03 eta: 17:48:01 time: 1.8322 data_time: 0.0035 memory: 4593 grad_norm: 0.1707 loss: 0.2951 loss_sem_seg: 0.2951 2023/05/13 03:50:57 - mmengine - INFO - Epoch(train) [7][ 600/1196] lr: 8.0000e-03 eta: 17:46:46 time: 1.8846 data_time: 0.0033 memory: 4673 grad_norm: 0.1623 loss: 0.2759 loss_sem_seg: 0.2759 2023/05/13 03:52:29 - mmengine - INFO - Epoch(train) [7][ 650/1196] lr: 8.0000e-03 eta: 17:45:21 time: 1.8383 data_time: 0.0035 memory: 4812 grad_norm: 0.1458 loss: 0.2702 loss_sem_seg: 0.2702 2023/05/13 03:54:00 - mmengine - INFO - Epoch(train) [7][ 700/1196] lr: 8.0000e-03 eta: 17:43:53 time: 1.8245 data_time: 0.0034 memory: 5138 grad_norm: 0.1559 loss: 0.2826 loss_sem_seg: 0.2826 2023/05/13 03:55:34 - mmengine - INFO - Epoch(train) [7][ 750/1196] lr: 8.0000e-03 eta: 17:42:35 time: 1.8737 data_time: 0.0033 memory: 4601 grad_norm: 0.1683 loss: 0.2666 loss_sem_seg: 0.2666 2023/05/13 03:57:07 - mmengine - INFO - Epoch(train) [7][ 800/1196] lr: 8.0000e-03 eta: 17:41:15 time: 1.8657 data_time: 0.0033 memory: 4851 grad_norm: 0.1654 loss: 0.2561 loss_sem_seg: 0.2561 2023/05/13 03:57:52 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 03:58:40 - mmengine - INFO - Epoch(train) [7][ 850/1196] lr: 8.0000e-03 eta: 17:39:53 time: 1.8520 data_time: 0.0035 memory: 4483 grad_norm: 0.1489 loss: 0.2659 loss_sem_seg: 0.2659 2023/05/13 04:00:08 - mmengine - INFO - Epoch(train) [7][ 900/1196] lr: 8.0000e-03 eta: 17:38:11 time: 1.7665 data_time: 0.0035 memory: 4422 grad_norm: 0.1529 loss: 0.2677 loss_sem_seg: 0.2677 2023/05/13 04:01:29 - mmengine - INFO - Epoch(train) [7][ 950/1196] lr: 8.0000e-03 eta: 17:35:59 time: 1.6200 data_time: 0.0034 memory: 4654 grad_norm: 0.1616 loss: 0.2531 loss_sem_seg: 0.2531 2023/05/13 04:02:51 - mmengine - INFO - Epoch(train) [7][1000/1196] lr: 8.0000e-03 eta: 17:33:48 time: 1.6280 data_time: 0.0034 memory: 4423 grad_norm: 0.1497 loss: 0.2716 loss_sem_seg: 0.2716 2023/05/13 04:04:14 - mmengine - INFO - Epoch(train) [7][1050/1196] lr: 8.0000e-03 eta: 17:31:49 time: 1.6758 data_time: 0.0035 memory: 4998 grad_norm: 0.1532 loss: 0.2476 loss_sem_seg: 0.2476 2023/05/13 04:05:38 - mmengine - INFO - Epoch(train) [7][1100/1196] lr: 8.0000e-03 eta: 17:29:48 time: 1.6701 data_time: 0.0035 memory: 5135 grad_norm: 0.1533 loss: 0.2809 loss_sem_seg: 0.2809 2023/05/13 04:07:01 - mmengine - INFO - Epoch(train) [7][1150/1196] lr: 8.0000e-03 eta: 17:27:46 time: 1.6604 data_time: 0.0035 memory: 4802 grad_norm: 0.1491 loss: 0.2617 loss_sem_seg: 0.2617 2023/05/13 04:08:24 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 04:08:24 - mmengine - INFO - Saving checkpoint at 7 epochs 2023/05/13 04:08:48 - mmengine - INFO - Epoch(val) [7][ 50/509] eta: 0:02:36 time: 0.3400 data_time: 0.0021 memory: 4661 2023/05/13 04:09:02 - mmengine - INFO - Epoch(val) [7][100/509] eta: 0:02:08 time: 0.2877 data_time: 0.0021 memory: 914 2023/05/13 04:09:16 - mmengine - INFO - Epoch(val) [7][150/509] eta: 0:01:49 time: 0.2864 data_time: 0.0020 memory: 915 2023/05/13 04:09:33 - mmengine - INFO - Epoch(val) [7][200/509] eta: 0:01:35 time: 0.3280 data_time: 0.0021 memory: 901 2023/05/13 04:09:50 - mmengine - INFO - Epoch(val) [7][250/509] eta: 0:01:21 time: 0.3408 data_time: 0.0021 memory: 929 2023/05/13 04:10:04 - mmengine - INFO - Epoch(val) [7][300/509] eta: 0:01:05 time: 0.2838 data_time: 0.0021 memory: 867 2023/05/13 04:10:19 - mmengine - INFO - Epoch(val) [7][350/509] eta: 0:00:49 time: 0.2977 data_time: 0.0021 memory: 891 2023/05/13 04:10:36 - mmengine - INFO - Epoch(val) [7][400/509] eta: 0:00:34 time: 0.3349 data_time: 0.0021 memory: 899 2023/05/13 04:10:51 - mmengine - INFO - Epoch(val) [7][450/509] eta: 0:00:18 time: 0.3155 data_time: 0.0021 memory: 911 2023/05/13 04:11:06 - mmengine - INFO - Epoch(val) [7][500/509] eta: 0:00:02 time: 0.3017 data_time: 0.0021 memory: 893 2023/05/13 04:11:28 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9554 | 0.3448 | 0.6819 | 0.7504 | 0.5128 | 0.6612 | 0.7286 | 0.0668 | 0.9311 | 0.4717 | 0.8061 | 0.0198 | 0.8890 | 0.5766 | 0.8756 | 0.6613 | 0.7302 | 0.6512 | 0.4966 | 0.6216 | 0.9143 | 0.6992 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 04:11:28 - mmengine - INFO - Epoch(val) [7][509/509] car: 0.9554 bicycle: 0.3448 motorcycle: 0.6819 truck: 0.7504 bus: 0.5128 person: 0.6612 bicyclist: 0.7286 motorcyclist: 0.0668 road: 0.9311 parking: 0.4717 sidewalk: 0.8061 other-ground: 0.0198 building: 0.8890 fence: 0.5766 vegetation: 0.8756 trunck: 0.6613 terrian: 0.7302 pole: 0.6512 traffic-sign: 0.4966 miou: 0.6216 acc: 0.9143 acc_cls: 0.6992 data_time: 0.0021 time: 0.3223 2023/05/13 04:13:02 - mmengine - INFO - Epoch(train) [8][ 50/1196] lr: 8.0000e-03 eta: 17:25:07 time: 1.8827 data_time: 0.0039 memory: 4727 grad_norm: 0.1517 loss: 0.2637 loss_sem_seg: 0.2637 2023/05/13 04:14:36 - mmengine - INFO - Epoch(train) [8][ 100/1196] lr: 8.0000e-03 eta: 17:23:51 time: 1.8800 data_time: 0.0037 memory: 4645 grad_norm: 0.1330 loss: 0.2808 loss_sem_seg: 0.2808 2023/05/13 04:16:07 - mmengine - INFO - Epoch(train) [8][ 150/1196] lr: 8.0000e-03 eta: 17:22:22 time: 1.8222 data_time: 0.0034 memory: 4617 grad_norm: 0.1461 loss: 0.2641 loss_sem_seg: 0.2641 2023/05/13 04:17:34 - mmengine - INFO - Epoch(train) [8][ 200/1196] lr: 8.0000e-03 eta: 17:20:37 time: 1.7399 data_time: 0.0035 memory: 4682 grad_norm: 0.1429 loss: 0.2833 loss_sem_seg: 0.2833 2023/05/13 04:19:01 - mmengine - INFO - Epoch(train) [8][ 250/1196] lr: 8.0000e-03 eta: 17:18:53 time: 1.7406 data_time: 0.0037 memory: 4684 grad_norm: 0.1373 loss: 0.2710 loss_sem_seg: 0.2710 2023/05/13 04:20:28 - mmengine - INFO - Epoch(train) [8][ 300/1196] lr: 8.0000e-03 eta: 17:17:06 time: 1.7293 data_time: 0.0034 memory: 4764 grad_norm: 0.1463 loss: 0.2713 loss_sem_seg: 0.2713 2023/05/13 04:21:52 - mmengine - INFO - Epoch(train) [8][ 350/1196] lr: 8.0000e-03 eta: 17:15:12 time: 1.6903 data_time: 0.0033 memory: 4782 grad_norm: 0.1496 loss: 0.2551 loss_sem_seg: 0.2551 2023/05/13 04:23:17 - mmengine - INFO - Epoch(train) [8][ 400/1196] lr: 8.0000e-03 eta: 17:13:18 time: 1.6873 data_time: 0.0032 memory: 4895 grad_norm: 0.1659 loss: 0.2480 loss_sem_seg: 0.2480 2023/05/13 04:24:52 - mmengine - INFO - Epoch(train) [8][ 450/1196] lr: 8.0000e-03 eta: 17:12:08 time: 1.9130 data_time: 0.0033 memory: 4707 grad_norm: 0.1710 loss: 0.2797 loss_sem_seg: 0.2797 2023/05/13 04:26:24 - mmengine - INFO - Epoch(train) [8][ 500/1196] lr: 8.0000e-03 eta: 17:10:43 time: 1.8391 data_time: 0.0036 memory: 4518 grad_norm: 0.1339 loss: 0.2497 loss_sem_seg: 0.2497 2023/05/13 04:27:59 - mmengine - INFO - Epoch(train) [8][ 550/1196] lr: 8.0000e-03 eta: 17:09:29 time: 1.8940 data_time: 0.0034 memory: 4349 grad_norm: 0.1450 loss: 0.2662 loss_sem_seg: 0.2662 2023/05/13 04:29:31 - mmengine - INFO - Epoch(train) [8][ 600/1196] lr: 8.0000e-03 eta: 17:08:07 time: 1.8511 data_time: 0.0033 memory: 4415 grad_norm: 0.1366 loss: 0.2629 loss_sem_seg: 0.2629 2023/05/13 04:30:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 04:31:04 - mmengine - INFO - Epoch(train) [8][ 650/1196] lr: 8.0000e-03 eta: 17:06:43 time: 1.8485 data_time: 0.0034 memory: 4633 grad_norm: 0.1473 loss: 0.2719 loss_sem_seg: 0.2719 2023/05/13 04:32:39 - mmengine - INFO - Epoch(train) [8][ 700/1196] lr: 8.0000e-03 eta: 17:05:29 time: 1.8983 data_time: 0.0034 memory: 4466 grad_norm: 0.1432 loss: 0.2546 loss_sem_seg: 0.2546 2023/05/13 04:34:11 - mmengine - INFO - Epoch(train) [8][ 750/1196] lr: 8.0000e-03 eta: 17:04:06 time: 1.8483 data_time: 0.0034 memory: 4560 grad_norm: 0.1607 loss: 0.2788 loss_sem_seg: 0.2788 2023/05/13 04:35:41 - mmengine - INFO - Epoch(train) [8][ 800/1196] lr: 8.0000e-03 eta: 17:02:33 time: 1.7992 data_time: 0.0032 memory: 4577 grad_norm: 0.1305 loss: 0.2733 loss_sem_seg: 0.2733 2023/05/13 04:37:12 - mmengine - INFO - Epoch(train) [8][ 850/1196] lr: 8.0000e-03 eta: 17:01:03 time: 1.8114 data_time: 0.0033 memory: 4536 grad_norm: 0.1350 loss: 0.2593 loss_sem_seg: 0.2593 2023/05/13 04:38:45 - mmengine - INFO - Epoch(train) [8][ 900/1196] lr: 8.0000e-03 eta: 16:59:42 time: 1.8653 data_time: 0.0037 memory: 4814 grad_norm: 0.1354 loss: 0.2800 loss_sem_seg: 0.2800 2023/05/13 04:40:18 - mmengine - INFO - Epoch(train) [8][ 950/1196] lr: 8.0000e-03 eta: 16:58:19 time: 1.8507 data_time: 0.0034 memory: 4493 grad_norm: 0.1381 loss: 0.2490 loss_sem_seg: 0.2490 2023/05/13 04:41:50 - mmengine - INFO - Epoch(train) [8][1000/1196] lr: 8.0000e-03 eta: 16:56:57 time: 1.8572 data_time: 0.0034 memory: 4894 grad_norm: 0.1335 loss: 0.2550 loss_sem_seg: 0.2550 2023/05/13 04:43:24 - mmengine - INFO - Epoch(train) [8][1050/1196] lr: 8.0000e-03 eta: 16:55:36 time: 1.8670 data_time: 0.0034 memory: 4460 grad_norm: 0.1353 loss: 0.2526 loss_sem_seg: 0.2526 2023/05/13 04:44:59 - mmengine - INFO - Epoch(train) [8][1100/1196] lr: 8.0000e-03 eta: 16:54:22 time: 1.9079 data_time: 0.0033 memory: 4691 grad_norm: 0.1277 loss: 0.2524 loss_sem_seg: 0.2524 2023/05/13 04:46:33 - mmengine - INFO - Epoch(train) [8][1150/1196] lr: 8.0000e-03 eta: 16:53:03 time: 1.8785 data_time: 0.0035 memory: 4718 grad_norm: 0.1891 loss: 0.2829 loss_sem_seg: 0.2829 2023/05/13 04:47:59 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 04:47:59 - mmengine - INFO - Saving checkpoint at 8 epochs 2023/05/13 04:48:24 - mmengine - INFO - Epoch(val) [8][ 50/509] eta: 0:02:43 time: 0.3557 data_time: 0.0021 memory: 4852 2023/05/13 04:48:39 - mmengine - INFO - Epoch(val) [8][100/509] eta: 0:02:15 time: 0.3078 data_time: 0.0021 memory: 914 2023/05/13 04:48:54 - mmengine - INFO - Epoch(val) [8][150/509] eta: 0:01:54 time: 0.2934 data_time: 0.0021 memory: 915 2023/05/13 04:49:08 - mmengine - INFO - Epoch(val) [8][200/509] eta: 0:01:36 time: 0.2900 data_time: 0.0020 memory: 901 2023/05/13 04:49:25 - mmengine - INFO - Epoch(val) [8][250/509] eta: 0:01:21 time: 0.3282 data_time: 0.0021 memory: 929 2023/05/13 04:49:39 - mmengine - INFO - Epoch(val) [8][300/509] eta: 0:01:04 time: 0.2902 data_time: 0.0021 memory: 867 2023/05/13 04:49:54 - mmengine - INFO - Epoch(val) [8][350/509] eta: 0:00:48 time: 0.2853 data_time: 0.0021 memory: 891 2023/05/13 04:50:10 - mmengine - INFO - Epoch(val) [8][400/509] eta: 0:00:33 time: 0.3193 data_time: 0.0021 memory: 899 2023/05/13 04:50:24 - mmengine - INFO - Epoch(val) [8][450/509] eta: 0:00:18 time: 0.2962 data_time: 0.0020 memory: 911 2023/05/13 04:50:38 - mmengine - INFO - Epoch(val) [8][500/509] eta: 0:00:02 time: 0.2765 data_time: 0.0021 memory: 893 2023/05/13 04:51:00 - 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 | 0.9589 | 0.4793 | 0.7420 | 0.5621 | 0.5422 | 0.7085 | 0.8066 | 0.0120 | 0.9330 | 0.4577 | 0.8129 | 0.0674 | 0.9016 | 0.6071 | 0.8794 | 0.7136 | 0.7296 | 0.6434 | 0.4850 | 0.6338 | 0.9174 | 0.7187 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 04:51:00 - mmengine - INFO - Epoch(val) [8][509/509] car: 0.9589 bicycle: 0.4793 motorcycle: 0.7420 truck: 0.5621 bus: 0.5422 person: 0.7085 bicyclist: 0.8066 motorcyclist: 0.0120 road: 0.9330 parking: 0.4577 sidewalk: 0.8129 other-ground: 0.0674 building: 0.9016 fence: 0.6071 vegetation: 0.8794 trunck: 0.7136 terrian: 0.7296 pole: 0.6434 traffic-sign: 0.4850 miou: 0.6338 acc: 0.9174 acc_cls: 0.7187 data_time: 0.0020 time: 0.2899 2023/05/13 04:52:30 - mmengine - INFO - Epoch(train) [9][ 50/1196] lr: 8.0000e-03 eta: 16:50:17 time: 1.7973 data_time: 0.0045 memory: 4815 grad_norm: 0.1346 loss: 0.2526 loss_sem_seg: 0.2526 2023/05/13 04:54:04 - mmengine - INFO - Epoch(train) [9][ 100/1196] lr: 8.0000e-03 eta: 16:48:58 time: 1.8798 data_time: 0.0035 memory: 4672 grad_norm: 0.1292 loss: 0.2591 loss_sem_seg: 0.2591 2023/05/13 04:55:27 - mmengine - INFO - Epoch(train) [9][ 150/1196] lr: 8.0000e-03 eta: 16:47:00 time: 1.6528 data_time: 0.0034 memory: 4765 grad_norm: 0.1347 loss: 0.2639 loss_sem_seg: 0.2639 2023/05/13 04:56:51 - mmengine - INFO - Epoch(train) [9][ 200/1196] lr: 8.0000e-03 eta: 16:45:07 time: 1.6803 data_time: 0.0034 memory: 4697 grad_norm: 0.1266 loss: 0.2549 loss_sem_seg: 0.2549 2023/05/13 04:58:10 - mmengine - INFO - Epoch(train) [9][ 250/1196] lr: 8.0000e-03 eta: 16:42:59 time: 1.5896 data_time: 0.0033 memory: 4787 grad_norm: 0.1309 loss: 0.2504 loss_sem_seg: 0.2504 2023/05/13 04:59:27 - mmengine - INFO - Epoch(train) [9][ 300/1196] lr: 8.0000e-03 eta: 16:40:40 time: 1.5259 data_time: 0.0034 memory: 4932 grad_norm: 0.1286 loss: 0.2586 loss_sem_seg: 0.2586 2023/05/13 05:00:42 - mmengine - INFO - Epoch(train) [9][ 350/1196] lr: 8.0000e-03 eta: 16:38:20 time: 1.5131 data_time: 0.0034 memory: 4587 grad_norm: 0.1344 loss: 0.2481 loss_sem_seg: 0.2481 2023/05/13 05:02:06 - mmengine - INFO - Epoch(train) [9][ 400/1196] lr: 8.0000e-03 eta: 16:36:26 time: 1.6659 data_time: 0.0033 memory: 4536 grad_norm: 0.1270 loss: 0.2463 loss_sem_seg: 0.2463 2023/05/13 05:03:01 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 05:03:32 - mmengine - INFO - Epoch(train) [9][ 450/1196] lr: 8.0000e-03 eta: 16:34:44 time: 1.7352 data_time: 0.0032 memory: 4623 grad_norm: 0.1196 loss: 0.2308 loss_sem_seg: 0.2308 2023/05/13 05:05:01 - mmengine - INFO - Epoch(train) [9][ 500/1196] lr: 8.0000e-03 eta: 16:33:10 time: 1.7800 data_time: 0.0035 memory: 4909 grad_norm: 0.1367 loss: 0.2667 loss_sem_seg: 0.2667 2023/05/13 05:06:34 - mmengine - INFO - Epoch(train) [9][ 550/1196] lr: 8.0000e-03 eta: 16:31:46 time: 1.8505 data_time: 0.0033 memory: 5066 grad_norm: 0.1628 loss: 0.2511 loss_sem_seg: 0.2511 2023/05/13 05:08:06 - mmengine - INFO - Epoch(train) [9][ 600/1196] lr: 8.0000e-03 eta: 16:30:23 time: 1.8507 data_time: 0.0032 memory: 4545 grad_norm: 0.1544 loss: 0.2479 loss_sem_seg: 0.2479 2023/05/13 05:09:38 - mmengine - INFO - Epoch(train) [9][ 650/1196] lr: 8.0000e-03 eta: 16:28:57 time: 1.8329 data_time: 0.0033 memory: 4832 grad_norm: 0.1462 loss: 0.2555 loss_sem_seg: 0.2555 2023/05/13 05:11:14 - mmengine - INFO - Epoch(train) [9][ 700/1196] lr: 8.0000e-03 eta: 16:27:45 time: 1.9187 data_time: 0.0032 memory: 4795 grad_norm: 0.1491 loss: 0.2645 loss_sem_seg: 0.2645 2023/05/13 05:12:47 - mmengine - INFO - Epoch(train) [9][ 750/1196] lr: 8.0000e-03 eta: 16:26:24 time: 1.8687 data_time: 0.0035 memory: 4543 grad_norm: 0.1373 loss: 0.2500 loss_sem_seg: 0.2500 2023/05/13 05:14:19 - mmengine - INFO - Epoch(train) [9][ 800/1196] lr: 8.0000e-03 eta: 16:24:59 time: 1.8403 data_time: 0.0036 memory: 4512 grad_norm: 0.1291 loss: 0.2538 loss_sem_seg: 0.2538 2023/05/13 05:15:54 - mmengine - INFO - Epoch(train) [9][ 850/1196] lr: 8.0000e-03 eta: 16:23:40 time: 1.8863 data_time: 0.0032 memory: 4628 grad_norm: 0.1303 loss: 0.2709 loss_sem_seg: 0.2709 2023/05/13 05:17:28 - mmengine - INFO - Epoch(train) [9][ 900/1196] lr: 8.0000e-03 eta: 16:22:23 time: 1.8900 data_time: 0.0032 memory: 4612 grad_norm: 0.1195 loss: 0.2482 loss_sem_seg: 0.2482 2023/05/13 05:19:03 - mmengine - INFO - Epoch(train) [9][ 950/1196] lr: 8.0000e-03 eta: 16:21:06 time: 1.8992 data_time: 0.0032 memory: 4702 grad_norm: 0.1410 loss: 0.2425 loss_sem_seg: 0.2425 2023/05/13 05:20:37 - mmengine - INFO - Epoch(train) [9][1000/1196] lr: 8.0000e-03 eta: 16:19:46 time: 1.8747 data_time: 0.0034 memory: 5161 grad_norm: 0.1274 loss: 0.2579 loss_sem_seg: 0.2579 2023/05/13 05:22:09 - mmengine - INFO - Epoch(train) [9][1050/1196] lr: 8.0000e-03 eta: 16:18:20 time: 1.8396 data_time: 0.0034 memory: 4655 grad_norm: 0.1299 loss: 0.2568 loss_sem_seg: 0.2568 2023/05/13 05:23:42 - mmengine - INFO - Epoch(train) [9][1100/1196] lr: 8.0000e-03 eta: 16:16:58 time: 1.8644 data_time: 0.0034 memory: 4649 grad_norm: 0.1317 loss: 0.2522 loss_sem_seg: 0.2522 2023/05/13 05:25:16 - mmengine - INFO - Epoch(train) [9][1150/1196] lr: 8.0000e-03 eta: 16:15:38 time: 1.8803 data_time: 0.0034 memory: 5175 grad_norm: 0.1233 loss: 0.2630 loss_sem_seg: 0.2630 2023/05/13 05:26:42 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 05:26:42 - mmengine - INFO - Saving checkpoint at 9 epochs 2023/05/13 05:27:05 - mmengine - INFO - Epoch(val) [9][ 50/509] eta: 0:02:35 time: 0.3398 data_time: 0.0021 memory: 4776 2023/05/13 05:27:20 - mmengine - INFO - Epoch(val) [9][100/509] eta: 0:02:11 time: 0.3039 data_time: 0.0021 memory: 914 2023/05/13 05:27:34 - mmengine - INFO - Epoch(val) [9][150/509] eta: 0:01:50 time: 0.2830 data_time: 0.0021 memory: 915 2023/05/13 05:27:49 - mmengine - INFO - Epoch(val) [9][200/509] eta: 0:01:34 time: 0.2951 data_time: 0.0021 memory: 901 2023/05/13 05:28:07 - mmengine - INFO - Epoch(val) [9][250/509] eta: 0:01:21 time: 0.3599 data_time: 0.0021 memory: 929 2023/05/13 05:28:21 - mmengine - INFO - Epoch(val) [9][300/509] eta: 0:01:04 time: 0.2770 data_time: 0.0021 memory: 867 2023/05/13 05:28:36 - mmengine - INFO - Epoch(val) [9][350/509] eta: 0:00:48 time: 0.2930 data_time: 0.0021 memory: 891 2023/05/13 05:28:51 - mmengine - INFO - Epoch(val) [9][400/509] eta: 0:00:33 time: 0.3080 data_time: 0.0021 memory: 899 2023/05/13 05:29:07 - mmengine - INFO - Epoch(val) [9][450/509] eta: 0:00:18 time: 0.3154 data_time: 0.0021 memory: 911 2023/05/13 05:29:21 - mmengine - INFO - Epoch(val) [9][500/509] eta: 0:00:02 time: 0.2768 data_time: 0.0020 memory: 893 2023/05/13 05:29:40 - 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 | 0.9647 | 0.3388 | 0.6543 | 0.6163 | 0.6285 | 0.7115 | 0.7852 | 0.0815 | 0.9408 | 0.4838 | 0.8217 | 0.0378 | 0.9038 | 0.6057 | 0.8914 | 0.6633 | 0.7693 | 0.6461 | 0.4317 | 0.6303 | 0.9244 | 0.7169 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 05:29:40 - mmengine - INFO - Epoch(val) [9][509/509] car: 0.9647 bicycle: 0.3388 motorcycle: 0.6543 truck: 0.6163 bus: 0.6285 person: 0.7115 bicyclist: 0.7852 motorcyclist: 0.0815 road: 0.9408 parking: 0.4838 sidewalk: 0.8217 other-ground: 0.0378 building: 0.9038 fence: 0.6057 vegetation: 0.8914 trunck: 0.6633 terrian: 0.7693 pole: 0.6461 traffic-sign: 0.4317 miou: 0.6303 acc: 0.9244 acc_cls: 0.7169 data_time: 0.0020 time: 0.2934 2023/05/13 05:31:13 - mmengine - INFO - Epoch(train) [10][ 50/1196] lr: 8.0000e-03 eta: 16:13:00 time: 1.8725 data_time: 0.0038 memory: 5196 grad_norm: 0.1273 loss: 0.2390 loss_sem_seg: 0.2390 2023/05/13 05:32:48 - mmengine - INFO - Epoch(train) [10][ 100/1196] lr: 8.0000e-03 eta: 16:11:42 time: 1.8929 data_time: 0.0033 memory: 4917 grad_norm: 0.1400 loss: 0.2335 loss_sem_seg: 0.2335 2023/05/13 05:34:22 - mmengine - INFO - Epoch(train) [10][ 150/1196] lr: 8.0000e-03 eta: 16:10:23 time: 1.8884 data_time: 0.0034 memory: 4469 grad_norm: 0.1422 loss: 0.2432 loss_sem_seg: 0.2432 2023/05/13 05:35:54 - mmengine - INFO - Epoch(train) [10][ 200/1196] lr: 8.0000e-03 eta: 16:08:54 time: 1.8257 data_time: 0.0033 memory: 4548 grad_norm: 0.1260 loss: 0.2527 loss_sem_seg: 0.2527 2023/05/13 05:36:59 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 05:37:24 - mmengine - INFO - Epoch(train) [10][ 250/1196] lr: 8.0000e-03 eta: 16:07:24 time: 1.8142 data_time: 0.0033 memory: 4768 grad_norm: 0.1390 loss: 0.2501 loss_sem_seg: 0.2501 2023/05/13 05:38:59 - mmengine - INFO - Epoch(train) [10][ 300/1196] lr: 8.0000e-03 eta: 16:06:06 time: 1.8962 data_time: 0.0033 memory: 4988 grad_norm: 0.1430 loss: 0.2570 loss_sem_seg: 0.2570 2023/05/13 05:40:28 - mmengine - INFO - Epoch(train) [10][ 350/1196] lr: 8.0000e-03 eta: 16:04:31 time: 1.7807 data_time: 0.0032 memory: 4834 grad_norm: 0.1212 loss: 0.2561 loss_sem_seg: 0.2561 2023/05/13 05:41:52 - mmengine - INFO - Epoch(train) [10][ 400/1196] lr: 8.0000e-03 eta: 16:02:41 time: 1.6806 data_time: 0.0033 memory: 4686 grad_norm: 0.1429 loss: 0.2539 loss_sem_seg: 0.2539 2023/05/13 05:43:19 - mmengine - INFO - Epoch(train) [10][ 450/1196] lr: 8.0000e-03 eta: 16:01:01 time: 1.7415 data_time: 0.0033 memory: 4956 grad_norm: 0.1434 loss: 0.2532 loss_sem_seg: 0.2532 2023/05/13 05:44:47 - mmengine - INFO - Epoch(train) [10][ 500/1196] lr: 8.0000e-03 eta: 15:59:23 time: 1.7583 data_time: 0.0034 memory: 4683 grad_norm: 0.1190 loss: 0.2441 loss_sem_seg: 0.2441 2023/05/13 05:46:16 - mmengine - INFO - Epoch(train) [10][ 550/1196] lr: 8.0000e-03 eta: 15:57:46 time: 1.7640 data_time: 0.0036 memory: 5075 grad_norm: 0.1258 loss: 0.2638 loss_sem_seg: 0.2638 2023/05/13 05:47:47 - mmengine - INFO - Epoch(train) [10][ 600/1196] lr: 8.0000e-03 eta: 15:56:19 time: 1.8395 data_time: 0.0033 memory: 4708 grad_norm: 0.1268 loss: 0.2464 loss_sem_seg: 0.2464 2023/05/13 05:49:14 - mmengine - INFO - Epoch(train) [10][ 650/1196] lr: 8.0000e-03 eta: 15:54:39 time: 1.7391 data_time: 0.0033 memory: 4978 grad_norm: 0.1155 loss: 0.2347 loss_sem_seg: 0.2347 2023/05/13 05:50:34 - mmengine - INFO - Epoch(train) [10][ 700/1196] lr: 8.0000e-03 eta: 15:52:39 time: 1.5970 data_time: 0.0032 memory: 4673 grad_norm: 0.1289 loss: 0.2600 loss_sem_seg: 0.2600 2023/05/13 05:51:55 - mmengine - INFO - Epoch(train) [10][ 750/1196] lr: 8.0000e-03 eta: 15:50:42 time: 1.6130 data_time: 0.0032 memory: 4883 grad_norm: 0.1265 loss: 0.2497 loss_sem_seg: 0.2497 2023/05/13 05:53:19 - mmengine - INFO - Epoch(train) [10][ 800/1196] lr: 8.0000e-03 eta: 15:48:53 time: 1.6726 data_time: 0.0033 memory: 4938 grad_norm: 0.1143 loss: 0.2443 loss_sem_seg: 0.2443 2023/05/13 05:54:41 - mmengine - INFO - Epoch(train) [10][ 850/1196] lr: 8.0000e-03 eta: 15:47:01 time: 1.6526 data_time: 0.0033 memory: 4684 grad_norm: 0.1327 loss: 0.2422 loss_sem_seg: 0.2422 2023/05/13 05:56:09 - mmengine - INFO - Epoch(train) [10][ 900/1196] lr: 8.0000e-03 eta: 15:45:25 time: 1.7633 data_time: 0.0034 memory: 4715 grad_norm: 0.1243 loss: 0.2317 loss_sem_seg: 0.2317 2023/05/13 05:57:41 - mmengine - INFO - Epoch(train) [10][ 950/1196] lr: 8.0000e-03 eta: 15:43:59 time: 1.8370 data_time: 0.0032 memory: 4664 grad_norm: 0.1273 loss: 0.2374 loss_sem_seg: 0.2374 2023/05/13 05:59:17 - mmengine - INFO - Epoch(train) [10][1000/1196] lr: 8.0000e-03 eta: 15:42:43 time: 1.9164 data_time: 0.0032 memory: 4748 grad_norm: 0.1413 loss: 0.2506 loss_sem_seg: 0.2506 2023/05/13 06:00:49 - mmengine - INFO - Epoch(train) [10][1050/1196] lr: 8.0000e-03 eta: 15:41:18 time: 1.8487 data_time: 0.0033 memory: 4946 grad_norm: 0.1174 loss: 0.2417 loss_sem_seg: 0.2417 2023/05/13 06:02:23 - mmengine - INFO - Epoch(train) [10][1100/1196] lr: 8.0000e-03 eta: 15:39:56 time: 1.8763 data_time: 0.0034 memory: 4461 grad_norm: 0.1180 loss: 0.2384 loss_sem_seg: 0.2384 2023/05/13 06:03:57 - mmengine - INFO - Epoch(train) [10][1150/1196] lr: 8.0000e-03 eta: 15:38:34 time: 1.8676 data_time: 0.0033 memory: 4848 grad_norm: 0.1371 loss: 0.2447 loss_sem_seg: 0.2447 2023/05/13 06:05:18 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 06:05:18 - mmengine - INFO - Saving checkpoint at 10 epochs 2023/05/13 06:05:40 - mmengine - INFO - Epoch(val) [10][ 50/509] eta: 0:02:28 time: 0.3232 data_time: 0.0022 memory: 4783 2023/05/13 06:05:54 - mmengine - INFO - Epoch(val) [10][100/509] eta: 0:02:03 time: 0.2797 data_time: 0.0020 memory: 914 2023/05/13 06:06:09 - mmengine - INFO - Epoch(val) [10][150/509] eta: 0:01:47 time: 0.2920 data_time: 0.0020 memory: 915 2023/05/13 06:06:25 - mmengine - INFO - Epoch(val) [10][200/509] eta: 0:01:33 time: 0.3196 data_time: 0.0021 memory: 901 2023/05/13 06:06:41 - mmengine - INFO - Epoch(val) [10][250/509] eta: 0:01:19 time: 0.3194 data_time: 0.0020 memory: 929 2023/05/13 06:06:54 - mmengine - INFO - Epoch(val) [10][300/509] eta: 0:01:02 time: 0.2658 data_time: 0.0020 memory: 867 2023/05/13 06:07:08 - mmengine - INFO - Epoch(val) [10][350/509] eta: 0:00:47 time: 0.2782 data_time: 0.0021 memory: 891 2023/05/13 06:07:23 - mmengine - INFO - Epoch(val) [10][400/509] eta: 0:00:32 time: 0.3059 data_time: 0.0020 memory: 899 2023/05/13 06:07:39 - mmengine - INFO - Epoch(val) [10][450/509] eta: 0:00:17 time: 0.3205 data_time: 0.0021 memory: 911 2023/05/13 06:07:54 - mmengine - INFO - Epoch(val) [10][500/509] eta: 0:00:02 time: 0.2923 data_time: 0.0021 memory: 893 2023/05/13 06:08:14 - 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 | 0.9611 | 0.4321 | 0.6393 | 0.5470 | 0.5555 | 0.6830 | 0.7903 | 0.0858 | 0.9406 | 0.4945 | 0.8237 | 0.0104 | 0.9058 | 0.6486 | 0.8977 | 0.6532 | 0.7891 | 0.6407 | 0.4809 | 0.6305 | 0.9277 | 0.7348 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 06:08:14 - mmengine - INFO - Epoch(val) [10][509/509] car: 0.9611 bicycle: 0.4321 motorcycle: 0.6393 truck: 0.5470 bus: 0.5555 person: 0.6830 bicyclist: 0.7903 motorcyclist: 0.0858 road: 0.9406 parking: 0.4945 sidewalk: 0.8237 other-ground: 0.0104 building: 0.9058 fence: 0.6486 vegetation: 0.8977 trunck: 0.6532 terrian: 0.7891 pole: 0.6407 traffic-sign: 0.4809 miou: 0.6305 acc: 0.9277 acc_cls: 0.7348 data_time: 0.0021 time: 0.3040 2023/05/13 06:09:31 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 06:09:49 - mmengine - INFO - Epoch(train) [11][ 50/1196] lr: 8.0000e-03 eta: 15:35:48 time: 1.9090 data_time: 0.0040 memory: 4583 grad_norm: 0.1302 loss: 0.2211 loss_sem_seg: 0.2211 2023/05/13 06:11:24 - mmengine - INFO - Epoch(train) [11][ 100/1196] lr: 8.0000e-03 eta: 15:34:27 time: 1.8855 data_time: 0.0033 memory: 4665 grad_norm: 0.1196 loss: 0.2604 loss_sem_seg: 0.2604 2023/05/13 06:12:48 - mmengine - INFO - Epoch(train) [11][ 150/1196] lr: 8.0000e-03 eta: 15:32:42 time: 1.6927 data_time: 0.0033 memory: 4757 grad_norm: 0.1180 loss: 0.2288 loss_sem_seg: 0.2288 2023/05/13 06:14:09 - mmengine - INFO - Epoch(train) [11][ 200/1196] lr: 8.0000e-03 eta: 15:30:47 time: 1.6126 data_time: 0.0033 memory: 4683 grad_norm: 0.1318 loss: 0.2446 loss_sem_seg: 0.2446 2023/05/13 06:15:31 - mmengine - INFO - Epoch(train) [11][ 250/1196] lr: 8.0000e-03 eta: 15:28:56 time: 1.6469 data_time: 0.0035 memory: 4591 grad_norm: 0.1354 loss: 0.2408 loss_sem_seg: 0.2408 2023/05/13 06:16:53 - mmengine - INFO - Epoch(train) [11][ 300/1196] lr: 8.0000e-03 eta: 15:27:04 time: 1.6340 data_time: 0.0033 memory: 4575 grad_norm: 0.1141 loss: 0.2563 loss_sem_seg: 0.2563 2023/05/13 06:18:14 - mmengine - INFO - Epoch(train) [11][ 350/1196] lr: 8.0000e-03 eta: 15:25:12 time: 1.6315 data_time: 0.0037 memory: 4524 grad_norm: 0.1402 loss: 0.2367 loss_sem_seg: 0.2367 2023/05/13 06:19:34 - mmengine - INFO - Epoch(train) [11][ 400/1196] lr: 8.0000e-03 eta: 15:23:15 time: 1.5945 data_time: 0.0032 memory: 5024 grad_norm: 0.1353 loss: 0.2472 loss_sem_seg: 0.2472 2023/05/13 06:20:56 - mmengine - INFO - Epoch(train) [11][ 450/1196] lr: 8.0000e-03 eta: 15:21:24 time: 1.6354 data_time: 0.0033 memory: 5241 grad_norm: 0.1079 loss: 0.2568 loss_sem_seg: 0.2568 2023/05/13 06:22:24 - mmengine - INFO - Epoch(train) [11][ 500/1196] lr: 8.0000e-03 eta: 15:19:49 time: 1.7605 data_time: 0.0034 memory: 5015 grad_norm: 0.1215 loss: 0.2549 loss_sem_seg: 0.2549 2023/05/13 06:23:49 - mmengine - INFO - Epoch(train) [11][ 550/1196] lr: 8.0000e-03 eta: 15:18:07 time: 1.7094 data_time: 0.0033 memory: 4889 grad_norm: 0.1493 loss: 0.2482 loss_sem_seg: 0.2482 2023/05/13 06:25:15 - mmengine - INFO - Epoch(train) [11][ 600/1196] lr: 8.0000e-03 eta: 15:16:27 time: 1.7191 data_time: 0.0034 memory: 4675 grad_norm: 0.1360 loss: 0.2410 loss_sem_seg: 0.2410 2023/05/13 06:26:43 - mmengine - INFO - Epoch(train) [11][ 650/1196] lr: 8.0000e-03 eta: 15:14:51 time: 1.7588 data_time: 0.0036 memory: 4576 grad_norm: 0.1241 loss: 0.2315 loss_sem_seg: 0.2315 2023/05/13 06:28:14 - mmengine - INFO - Epoch(train) [11][ 700/1196] lr: 8.0000e-03 eta: 15:13:23 time: 1.8211 data_time: 0.0034 memory: 4678 grad_norm: 0.1359 loss: 0.2364 loss_sem_seg: 0.2364 2023/05/13 06:29:48 - mmengine - INFO - Epoch(train) [11][ 750/1196] lr: 8.0000e-03 eta: 15:12:02 time: 1.8805 data_time: 0.0035 memory: 4356 grad_norm: 0.1320 loss: 0.2332 loss_sem_seg: 0.2332 2023/05/13 06:31:22 - mmengine - INFO - Epoch(train) [11][ 800/1196] lr: 8.0000e-03 eta: 15:10:39 time: 1.8640 data_time: 0.0034 memory: 4942 grad_norm: 0.1239 loss: 0.2187 loss_sem_seg: 0.2187 2023/05/13 06:32:56 - mmengine - INFO - Epoch(train) [11][ 850/1196] lr: 8.0000e-03 eta: 15:09:20 time: 1.8941 data_time: 0.0035 memory: 4407 grad_norm: 0.1218 loss: 0.2638 loss_sem_seg: 0.2638 2023/05/13 06:34:28 - mmengine - INFO - Epoch(train) [11][ 900/1196] lr: 8.0000e-03 eta: 15:07:53 time: 1.8315 data_time: 0.0035 memory: 5001 grad_norm: 0.1129 loss: 0.2363 loss_sem_seg: 0.2363 2023/05/13 06:36:01 - mmengine - INFO - Epoch(train) [11][ 950/1196] lr: 8.0000e-03 eta: 15:06:29 time: 1.8577 data_time: 0.0036 memory: 4715 grad_norm: 0.1184 loss: 0.2471 loss_sem_seg: 0.2471 2023/05/13 06:37:34 - mmengine - INFO - Epoch(train) [11][1000/1196] lr: 8.0000e-03 eta: 15:05:05 time: 1.8560 data_time: 0.0034 memory: 4714 grad_norm: 0.1153 loss: 0.2426 loss_sem_seg: 0.2426 2023/05/13 06:38:48 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 06:39:06 - mmengine - INFO - Epoch(train) [11][1050/1196] lr: 8.0000e-03 eta: 15:03:39 time: 1.8446 data_time: 0.0037 memory: 4489 grad_norm: 0.1472 loss: 0.2506 loss_sem_seg: 0.2506 2023/05/13 06:40:39 - mmengine - INFO - Epoch(train) [11][1100/1196] lr: 8.0000e-03 eta: 15:02:15 time: 1.8587 data_time: 0.0036 memory: 4684 grad_norm: 0.1249 loss: 0.2321 loss_sem_seg: 0.2321 2023/05/13 06:42:13 - mmengine - INFO - Epoch(train) [11][1150/1196] lr: 8.0000e-03 eta: 15:00:54 time: 1.8870 data_time: 0.0035 memory: 4483 grad_norm: 0.1272 loss: 0.2301 loss_sem_seg: 0.2301 2023/05/13 06:43:30 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 06:43:30 - mmengine - INFO - Saving checkpoint at 11 epochs 2023/05/13 06:43:50 - mmengine - INFO - Epoch(val) [11][ 50/509] eta: 0:02:08 time: 0.2806 data_time: 0.0021 memory: 4397 2023/05/13 06:44:04 - mmengine - INFO - Epoch(val) [11][100/509] eta: 0:01:53 time: 0.2761 data_time: 0.0020 memory: 914 2023/05/13 06:44:17 - mmengine - INFO - Epoch(val) [11][150/509] eta: 0:01:38 time: 0.2685 data_time: 0.0020 memory: 915 2023/05/13 06:44:31 - mmengine - INFO - Epoch(val) [11][200/509] eta: 0:01:25 time: 0.2783 data_time: 0.0024 memory: 901 2023/05/13 06:44:46 - mmengine - INFO - Epoch(val) [11][250/509] eta: 0:01:12 time: 0.2899 data_time: 0.0020 memory: 929 2023/05/13 06:44:58 - mmengine - INFO - Epoch(val) [11][300/509] eta: 0:00:56 time: 0.2349 data_time: 0.0021 memory: 867 2023/05/13 06:45:11 - mmengine - INFO - Epoch(val) [11][350/509] eta: 0:00:43 time: 0.2701 data_time: 0.0020 memory: 891 2023/05/13 06:45:25 - mmengine - INFO - Epoch(val) [11][400/509] eta: 0:00:29 time: 0.2757 data_time: 0.0021 memory: 899 2023/05/13 06:45:39 - mmengine - INFO - Epoch(val) [11][450/509] eta: 0:00:16 time: 0.2740 data_time: 0.0020 memory: 911 2023/05/13 06:45:51 - mmengine - INFO - Epoch(val) [11][500/509] eta: 0:00:02 time: 0.2477 data_time: 0.0020 memory: 893 2023/05/13 06:46:11 - 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 | 0.9640 | 0.3724 | 0.6067 | 0.6571 | 0.6421 | 0.6624 | 0.8532 | 0.0882 | 0.9337 | 0.4041 | 0.8184 | 0.0090 | 0.9106 | 0.6443 | 0.8849 | 0.7161 | 0.7489 | 0.6536 | 0.5032 | 0.6354 | 0.9217 | 0.6973 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 06:46:11 - mmengine - INFO - Epoch(val) [11][509/509] car: 0.9640 bicycle: 0.3724 motorcycle: 0.6067 truck: 0.6571 bus: 0.6421 person: 0.6624 bicyclist: 0.8532 motorcyclist: 0.0882 road: 0.9337 parking: 0.4041 sidewalk: 0.8184 other-ground: 0.0090 building: 0.9106 fence: 0.6443 vegetation: 0.8849 trunck: 0.7161 terrian: 0.7489 pole: 0.6536 traffic-sign: 0.5032 miou: 0.6354 acc: 0.9217 acc_cls: 0.6973 data_time: 0.0021 time: 0.2643 2023/05/13 06:47:33 - mmengine - INFO - Epoch(train) [12][ 50/1196] lr: 8.0000e-03 eta: 14:57:28 time: 1.6426 data_time: 0.0044 memory: 4919 grad_norm: 0.1252 loss: 0.2442 loss_sem_seg: 0.2442 2023/05/13 06:48:53 - mmengine - INFO - Epoch(train) [12][ 100/1196] lr: 8.0000e-03 eta: 14:55:34 time: 1.5896 data_time: 0.0032 memory: 4716 grad_norm: 0.1079 loss: 0.2260 loss_sem_seg: 0.2260 2023/05/13 06:50:28 - mmengine - INFO - Epoch(train) [12][ 150/1196] lr: 8.0000e-03 eta: 14:54:16 time: 1.9080 data_time: 0.0034 memory: 4282 grad_norm: 0.1217 loss: 0.2318 loss_sem_seg: 0.2318 2023/05/13 06:52:01 - mmengine - INFO - Epoch(train) [12][ 200/1196] lr: 8.0000e-03 eta: 14:52:52 time: 1.8653 data_time: 0.0034 memory: 4497 grad_norm: 0.1308 loss: 0.2514 loss_sem_seg: 0.2514 2023/05/13 06:53:34 - mmengine - INFO - Epoch(train) [12][ 250/1196] lr: 8.0000e-03 eta: 14:51:27 time: 1.8447 data_time: 0.0034 memory: 4622 grad_norm: 0.1245 loss: 0.2400 loss_sem_seg: 0.2400 2023/05/13 06:55:05 - mmengine - INFO - Epoch(train) [12][ 300/1196] lr: 8.0000e-03 eta: 14:50:00 time: 1.8358 data_time: 0.0034 memory: 5199 grad_norm: 0.1264 loss: 0.2432 loss_sem_seg: 0.2432 2023/05/13 06:56:37 - mmengine - INFO - Epoch(train) [12][ 350/1196] lr: 8.0000e-03 eta: 14:48:32 time: 1.8257 data_time: 0.0034 memory: 4722 grad_norm: 0.1288 loss: 0.2686 loss_sem_seg: 0.2686 2023/05/13 06:58:11 - mmengine - INFO - Epoch(train) [12][ 400/1196] lr: 8.0000e-03 eta: 14:47:10 time: 1.8782 data_time: 0.0035 memory: 4581 grad_norm: 0.0969 loss: 0.2561 loss_sem_seg: 0.2561 2023/05/13 06:59:45 - mmengine - INFO - Epoch(train) [12][ 450/1196] lr: 8.0000e-03 eta: 14:45:48 time: 1.8834 data_time: 0.0038 memory: 4626 grad_norm: 0.1151 loss: 0.2345 loss_sem_seg: 0.2345 2023/05/13 07:01:18 - mmengine - INFO - Epoch(train) [12][ 500/1196] lr: 8.0000e-03 eta: 14:44:25 time: 1.8702 data_time: 0.0037 memory: 4649 grad_norm: 0.1285 loss: 0.2437 loss_sem_seg: 0.2437 2023/05/13 07:02:43 - mmengine - INFO - Epoch(train) [12][ 550/1196] lr: 8.0000e-03 eta: 14:42:44 time: 1.7020 data_time: 0.0034 memory: 4721 grad_norm: 0.1260 loss: 0.2385 loss_sem_seg: 0.2385 2023/05/13 07:04:07 - mmengine - INFO - Epoch(train) [12][ 600/1196] lr: 8.0000e-03 eta: 14:40:59 time: 1.6646 data_time: 0.0034 memory: 4510 grad_norm: 0.1117 loss: 0.2413 loss_sem_seg: 0.2413 2023/05/13 07:05:32 - mmengine - INFO - Epoch(train) [12][ 650/1196] lr: 8.0000e-03 eta: 14:39:17 time: 1.6991 data_time: 0.0033 memory: 4602 grad_norm: 0.1137 loss: 0.2296 loss_sem_seg: 0.2296 2023/05/13 07:06:58 - mmengine - INFO - Epoch(train) [12][ 700/1196] lr: 8.0000e-03 eta: 14:37:40 time: 1.7357 data_time: 0.0034 memory: 4343 grad_norm: 0.1187 loss: 0.2334 loss_sem_seg: 0.2334 2023/05/13 07:08:26 - mmengine - INFO - Epoch(train) [12][ 750/1196] lr: 8.0000e-03 eta: 14:36:04 time: 1.7462 data_time: 0.0036 memory: 4601 grad_norm: 0.1171 loss: 0.2426 loss_sem_seg: 0.2426 2023/05/13 07:10:00 - mmengine - INFO - Epoch(train) [12][ 800/1196] lr: 8.0000e-03 eta: 14:34:43 time: 1.8877 data_time: 0.0035 memory: 4813 grad_norm: 0.1211 loss: 0.2369 loss_sem_seg: 0.2369 2023/05/13 07:11:25 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 07:11:36 - mmengine - INFO - Epoch(train) [12][ 850/1196] lr: 8.0000e-03 eta: 14:33:25 time: 1.9222 data_time: 0.0033 memory: 4884 grad_norm: 0.1200 loss: 0.2343 loss_sem_seg: 0.2343 2023/05/13 07:13:10 - mmengine - INFO - Epoch(train) [12][ 900/1196] lr: 8.0000e-03 eta: 14:32:01 time: 1.8702 data_time: 0.0034 memory: 4523 grad_norm: 0.1059 loss: 0.2298 loss_sem_seg: 0.2298 2023/05/13 07:14:47 - mmengine - INFO - Epoch(train) [12][ 950/1196] lr: 8.0000e-03 eta: 14:30:46 time: 1.9526 data_time: 0.0035 memory: 4747 grad_norm: 0.1256 loss: 0.2298 loss_sem_seg: 0.2298 2023/05/13 07:16:21 - mmengine - INFO - Epoch(train) [12][1000/1196] lr: 8.0000e-03 eta: 14:29:24 time: 1.8796 data_time: 0.0035 memory: 4603 grad_norm: 0.1176 loss: 0.2393 loss_sem_seg: 0.2393 2023/05/13 07:17:54 - mmengine - INFO - Epoch(train) [12][1050/1196] lr: 8.0000e-03 eta: 14:27:58 time: 1.8535 data_time: 0.0035 memory: 4678 grad_norm: 0.1185 loss: 0.2395 loss_sem_seg: 0.2395 2023/05/13 07:19:25 - mmengine - INFO - Epoch(train) [12][1100/1196] lr: 8.0000e-03 eta: 14:26:30 time: 1.8225 data_time: 0.0035 memory: 4417 grad_norm: 0.1268 loss: 0.2443 loss_sem_seg: 0.2443 2023/05/13 07:20:59 - mmengine - INFO - Epoch(train) [12][1150/1196] lr: 8.0000e-03 eta: 14:25:08 time: 1.8856 data_time: 0.0035 memory: 4411 grad_norm: 0.1188 loss: 0.2329 loss_sem_seg: 0.2329 2023/05/13 07:22:24 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 07:22:24 - mmengine - INFO - Saving checkpoint at 12 epochs 2023/05/13 07:22:48 - mmengine - INFO - Epoch(val) [12][ 50/509] eta: 0:02:42 time: 0.3542 data_time: 0.0021 memory: 4630 2023/05/13 07:23:04 - mmengine - INFO - Epoch(val) [12][100/509] eta: 0:02:16 time: 0.3112 data_time: 0.0021 memory: 914 2023/05/13 07:23:20 - mmengine - INFO - Epoch(val) [12][150/509] eta: 0:01:57 time: 0.3142 data_time: 0.0021 memory: 915 2023/05/13 07:23:36 - mmengine - INFO - Epoch(val) [12][200/509] eta: 0:01:40 time: 0.3206 data_time: 0.0021 memory: 901 2023/05/13 07:23:54 - mmengine - INFO - Epoch(val) [12][250/509] eta: 0:01:26 time: 0.3608 data_time: 0.0021 memory: 929 2023/05/13 07:24:08 - mmengine - INFO - Epoch(val) [12][300/509] eta: 0:01:07 time: 0.2906 data_time: 0.0021 memory: 867 2023/05/13 07:24:24 - mmengine - INFO - Epoch(val) [12][350/509] eta: 0:00:51 time: 0.3098 data_time: 0.0021 memory: 891 2023/05/13 07:24:40 - mmengine - INFO - Epoch(val) [12][400/509] eta: 0:00:35 time: 0.3324 data_time: 0.0020 memory: 899 2023/05/13 07:24:56 - mmengine - INFO - Epoch(val) [12][450/509] eta: 0:00:19 time: 0.3180 data_time: 0.0021 memory: 911 2023/05/13 07:25:12 - mmengine - INFO - Epoch(val) [12][500/509] eta: 0:00:02 time: 0.3132 data_time: 0.0020 memory: 893 2023/05/13 07:25:32 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9555 | 0.4928 | 0.7012 | 0.7586 | 0.5297 | 0.6881 | 0.8388 | 0.1326 | 0.9364 | 0.4954 | 0.8129 | 0.0090 | 0.9025 | 0.6379 | 0.8798 | 0.6132 | 0.7454 | 0.6422 | 0.5118 | 0.6465 | 0.9191 | 0.7304 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 07:25:32 - mmengine - INFO - Epoch(val) [12][509/509] car: 0.9555 bicycle: 0.4928 motorcycle: 0.7012 truck: 0.7586 bus: 0.5297 person: 0.6881 bicyclist: 0.8388 motorcyclist: 0.1326 road: 0.9364 parking: 0.4954 sidewalk: 0.8129 other-ground: 0.0090 building: 0.9025 fence: 0.6379 vegetation: 0.8798 trunck: 0.6132 terrian: 0.7454 pole: 0.6422 traffic-sign: 0.5118 miou: 0.6465 acc: 0.9191 acc_cls: 0.7304 data_time: 0.0021 time: 0.3279 2023/05/13 07:27:05 - mmengine - INFO - Epoch(train) [13][ 50/1196] lr: 8.0000e-03 eta: 14:22:24 time: 1.8658 data_time: 0.0039 memory: 4413 grad_norm: 0.1116 loss: 0.2247 loss_sem_seg: 0.2247 2023/05/13 07:28:41 - mmengine - INFO - Epoch(train) [13][ 100/1196] lr: 8.0000e-03 eta: 14:21:04 time: 1.9095 data_time: 0.0035 memory: 4313 grad_norm: 0.1237 loss: 0.2446 loss_sem_seg: 0.2446 2023/05/13 07:30:15 - mmengine - INFO - Epoch(train) [13][ 150/1196] lr: 8.0000e-03 eta: 14:19:42 time: 1.8904 data_time: 0.0034 memory: 4739 grad_norm: 0.1251 loss: 0.2243 loss_sem_seg: 0.2243 2023/05/13 07:31:49 - mmengine - INFO - Epoch(train) [13][ 200/1196] lr: 8.0000e-03 eta: 14:18:18 time: 1.8681 data_time: 0.0035 memory: 4961 grad_norm: 0.0997 loss: 0.2387 loss_sem_seg: 0.2387 2023/05/13 07:33:20 - mmengine - INFO - Epoch(train) [13][ 250/1196] lr: 8.0000e-03 eta: 14:16:49 time: 1.8273 data_time: 0.0036 memory: 4846 grad_norm: 0.1121 loss: 0.2397 loss_sem_seg: 0.2397 2023/05/13 07:34:50 - mmengine - INFO - Epoch(train) [13][ 300/1196] lr: 8.0000e-03 eta: 14:15:18 time: 1.7949 data_time: 0.0034 memory: 4525 grad_norm: 0.1266 loss: 0.2317 loss_sem_seg: 0.2317 2023/05/13 07:36:24 - mmengine - INFO - Epoch(train) [13][ 350/1196] lr: 8.0000e-03 eta: 14:13:54 time: 1.8748 data_time: 0.0034 memory: 4761 grad_norm: 0.1058 loss: 0.2217 loss_sem_seg: 0.2217 2023/05/13 07:37:47 - mmengine - INFO - Epoch(train) [13][ 400/1196] lr: 8.0000e-03 eta: 14:12:10 time: 1.6678 data_time: 0.0033 memory: 4591 grad_norm: 0.1149 loss: 0.2463 loss_sem_seg: 0.2463 2023/05/13 07:39:11 - mmengine - INFO - Epoch(train) [13][ 450/1196] lr: 8.0000e-03 eta: 14:10:28 time: 1.6801 data_time: 0.0035 memory: 4761 grad_norm: 0.1099 loss: 0.2279 loss_sem_seg: 0.2279 2023/05/13 07:40:34 - mmengine - INFO - Epoch(train) [13][ 500/1196] lr: 8.0000e-03 eta: 14:08:43 time: 1.6541 data_time: 0.0034 memory: 4559 grad_norm: 0.1266 loss: 0.2439 loss_sem_seg: 0.2439 2023/05/13 07:41:57 - mmengine - INFO - Epoch(train) [13][ 550/1196] lr: 8.0000e-03 eta: 14:07:00 time: 1.6685 data_time: 0.0036 memory: 5042 grad_norm: 0.1191 loss: 0.2530 loss_sem_seg: 0.2530 2023/05/13 07:43:15 - mmengine - INFO - Epoch(train) [13][ 600/1196] lr: 8.0000e-03 eta: 14:05:07 time: 1.5602 data_time: 0.0033 memory: 4752 grad_norm: 0.1279 loss: 0.2347 loss_sem_seg: 0.2347 2023/05/13 07:44:34 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 07:44:38 - mmengine - INFO - Epoch(train) [13][ 650/1196] lr: 8.0000e-03 eta: 14:03:22 time: 1.6475 data_time: 0.0033 memory: 4624 grad_norm: 0.1212 loss: 0.2463 loss_sem_seg: 0.2463 2023/05/13 07:46:04 - mmengine - INFO - Epoch(train) [13][ 700/1196] lr: 8.0000e-03 eta: 14:01:45 time: 1.7308 data_time: 0.0033 memory: 4710 grad_norm: 0.1287 loss: 0.2388 loss_sem_seg: 0.2388 2023/05/13 07:47:28 - mmengine - INFO - Epoch(train) [13][ 750/1196] lr: 8.0000e-03 eta: 14:00:04 time: 1.6811 data_time: 0.0034 memory: 4466 grad_norm: 0.1210 loss: 0.2333 loss_sem_seg: 0.2333 2023/05/13 07:48:52 - mmengine - INFO - Epoch(train) [13][ 800/1196] lr: 8.0000e-03 eta: 13:58:22 time: 1.6833 data_time: 0.0033 memory: 4378 grad_norm: 0.1199 loss: 0.2307 loss_sem_seg: 0.2307 2023/05/13 07:50:26 - mmengine - INFO - Epoch(train) [13][ 850/1196] lr: 8.0000e-03 eta: 13:56:58 time: 1.8624 data_time: 0.0033 memory: 4725 grad_norm: 0.1055 loss: 0.2311 loss_sem_seg: 0.2311 2023/05/13 07:51:58 - mmengine - INFO - Epoch(train) [13][ 900/1196] lr: 8.0000e-03 eta: 13:55:32 time: 1.8510 data_time: 0.0036 memory: 4527 grad_norm: 0.1114 loss: 0.2059 loss_sem_seg: 0.2059 2023/05/13 07:53:31 - mmengine - INFO - Epoch(train) [13][ 950/1196] lr: 8.0000e-03 eta: 13:54:07 time: 1.8608 data_time: 0.0034 memory: 4831 grad_norm: 0.1227 loss: 0.2452 loss_sem_seg: 0.2452 2023/05/13 07:55:04 - mmengine - INFO - Epoch(train) [13][1000/1196] lr: 8.0000e-03 eta: 13:52:42 time: 1.8605 data_time: 0.0034 memory: 4675 grad_norm: 0.1206 loss: 0.2391 loss_sem_seg: 0.2391 2023/05/13 07:56:37 - mmengine - INFO - Epoch(train) [13][1050/1196] lr: 8.0000e-03 eta: 13:51:16 time: 1.8544 data_time: 0.0034 memory: 4669 grad_norm: 0.1165 loss: 0.2424 loss_sem_seg: 0.2424 2023/05/13 07:58:10 - mmengine - INFO - Epoch(train) [13][1100/1196] lr: 8.0000e-03 eta: 13:49:52 time: 1.8702 data_time: 0.0034 memory: 4633 grad_norm: 0.1135 loss: 0.2398 loss_sem_seg: 0.2398 2023/05/13 07:59:43 - mmengine - INFO - Epoch(train) [13][1150/1196] lr: 8.0000e-03 eta: 13:48:27 time: 1.8579 data_time: 0.0035 memory: 4506 grad_norm: 0.1099 loss: 0.2178 loss_sem_seg: 0.2178 2023/05/13 08:01:11 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 08:01:11 - mmengine - INFO - Saving checkpoint at 13 epochs 2023/05/13 08:01:35 - mmengine - INFO - Epoch(val) [13][ 50/509] eta: 0:02:39 time: 0.3470 data_time: 0.0021 memory: 4642 2023/05/13 08:01:49 - mmengine - INFO - Epoch(val) [13][100/509] eta: 0:02:10 time: 0.2898 data_time: 0.0022 memory: 914 2023/05/13 08:02:04 - mmengine - INFO - Epoch(val) [13][150/509] eta: 0:01:50 time: 0.2859 data_time: 0.0021 memory: 915 2023/05/13 08:02:20 - mmengine - INFO - Epoch(val) [13][200/509] eta: 0:01:35 time: 0.3193 data_time: 0.0021 memory: 901 2023/05/13 08:02:36 - mmengine - INFO - Epoch(val) [13][250/509] eta: 0:01:21 time: 0.3359 data_time: 0.0021 memory: 929 2023/05/13 08:02:50 - mmengine - INFO - Epoch(val) [13][300/509] eta: 0:01:04 time: 0.2816 data_time: 0.0021 memory: 867 2023/05/13 08:03:05 - mmengine - INFO - Epoch(val) [13][350/509] eta: 0:00:48 time: 0.2967 data_time: 0.0021 memory: 891 2023/05/13 08:03:21 - mmengine - INFO - Epoch(val) [13][400/509] eta: 0:00:33 time: 0.3067 data_time: 0.0020 memory: 899 2023/05/13 08:03:36 - mmengine - INFO - Epoch(val) [13][450/509] eta: 0:00:18 time: 0.3061 data_time: 0.0021 memory: 911 2023/05/13 08:03:50 - mmengine - INFO - Epoch(val) [13][500/509] eta: 0:00:02 time: 0.2893 data_time: 0.0020 memory: 893 2023/05/13 08:04:10 - 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 | 0.9701 | 0.5149 | 0.7041 | 0.6234 | 0.6785 | 0.6940 | 0.8521 | 0.0848 | 0.9299 | 0.4607 | 0.8087 | 0.0109 | 0.8984 | 0.5948 | 0.8982 | 0.6650 | 0.7879 | 0.6547 | 0.5068 | 0.6494 | 0.9243 | 0.7275 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 08:04:10 - mmengine - INFO - Epoch(val) [13][509/509] car: 0.9701 bicycle: 0.5149 motorcycle: 0.7041 truck: 0.6234 bus: 0.6785 person: 0.6940 bicyclist: 0.8521 motorcyclist: 0.0848 road: 0.9299 parking: 0.4607 sidewalk: 0.8087 other-ground: 0.0109 building: 0.8984 fence: 0.5948 vegetation: 0.8982 trunck: 0.6650 terrian: 0.7879 pole: 0.6547 traffic-sign: 0.5068 miou: 0.6494 acc: 0.9243 acc_cls: 0.7275 data_time: 0.0020 time: 0.3059 2023/05/13 08:05:43 - mmengine - INFO - Epoch(train) [14][ 50/1196] lr: 8.0000e-03 eta: 13:45:48 time: 1.8623 data_time: 0.0039 memory: 4412 grad_norm: 0.1119 loss: 0.2420 loss_sem_seg: 0.2420 2023/05/13 08:07:16 - mmengine - INFO - Epoch(train) [14][ 100/1196] lr: 8.0000e-03 eta: 13:44:22 time: 1.8547 data_time: 0.0035 memory: 4480 grad_norm: 0.1158 loss: 0.2151 loss_sem_seg: 0.2151 2023/05/13 08:08:50 - mmengine - INFO - Epoch(train) [14][ 150/1196] lr: 8.0000e-03 eta: 13:42:58 time: 1.8816 data_time: 0.0034 memory: 4580 grad_norm: 0.1354 loss: 0.2373 loss_sem_seg: 0.2373 2023/05/13 08:10:23 - mmengine - INFO - Epoch(train) [14][ 200/1196] lr: 8.0000e-03 eta: 13:41:33 time: 1.8676 data_time: 0.0033 memory: 4597 grad_norm: 0.1296 loss: 0.2318 loss_sem_seg: 0.2318 2023/05/13 08:11:56 - mmengine - INFO - Epoch(train) [14][ 250/1196] lr: 8.0000e-03 eta: 13:40:07 time: 1.8452 data_time: 0.0033 memory: 4472 grad_norm: 0.1226 loss: 0.2372 loss_sem_seg: 0.2372 2023/05/13 08:13:29 - mmengine - INFO - Epoch(train) [14][ 300/1196] lr: 8.0000e-03 eta: 13:38:41 time: 1.8598 data_time: 0.0033 memory: 4964 grad_norm: 0.1101 loss: 0.2395 loss_sem_seg: 0.2395 2023/05/13 08:15:03 - mmengine - INFO - Epoch(train) [14][ 350/1196] lr: 8.0000e-03 eta: 13:37:18 time: 1.8937 data_time: 0.0034 memory: 4527 grad_norm: 0.1173 loss: 0.2303 loss_sem_seg: 0.2303 2023/05/13 08:16:36 - mmengine - INFO - Epoch(train) [14][ 400/1196] lr: 8.0000e-03 eta: 13:35:51 time: 1.8474 data_time: 0.0034 memory: 4950 grad_norm: 0.1113 loss: 0.2374 loss_sem_seg: 0.2374 2023/05/13 08:18:06 - mmengine - INFO - Epoch(train) [14][ 450/1196] lr: 8.0000e-03 eta: 13:34:22 time: 1.8134 data_time: 0.0033 memory: 4590 grad_norm: 0.1069 loss: 0.2321 loss_sem_seg: 0.2321 2023/05/13 08:18:10 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 08:19:37 - mmengine - INFO - Epoch(train) [14][ 500/1196] lr: 8.0000e-03 eta: 13:32:52 time: 1.8121 data_time: 0.0034 memory: 5012 grad_norm: 0.1228 loss: 0.2390 loss_sem_seg: 0.2390 2023/05/13 08:20:54 - mmengine - INFO - Epoch(train) [14][ 550/1196] lr: 8.0000e-03 eta: 13:30:59 time: 1.5298 data_time: 0.0034 memory: 4530 grad_norm: 0.1204 loss: 0.2470 loss_sem_seg: 0.2470 2023/05/13 08:22:08 - mmengine - INFO - Epoch(train) [14][ 600/1196] lr: 8.0000e-03 eta: 13:29:02 time: 1.4862 data_time: 0.0033 memory: 4663 grad_norm: 0.1176 loss: 0.2518 loss_sem_seg: 0.2518 2023/05/13 08:23:23 - mmengine - INFO - Epoch(train) [14][ 650/1196] lr: 8.0000e-03 eta: 13:27:07 time: 1.5046 data_time: 0.0033 memory: 5283 grad_norm: 0.1085 loss: 0.2336 loss_sem_seg: 0.2336 2023/05/13 08:24:30 - mmengine - INFO - Epoch(train) [14][ 700/1196] lr: 8.0000e-03 eta: 13:24:58 time: 1.3322 data_time: 0.0034 memory: 4546 grad_norm: 0.1101 loss: 0.2334 loss_sem_seg: 0.2334 2023/05/13 08:25:38 - mmengine - INFO - Epoch(train) [14][ 750/1196] lr: 8.0000e-03 eta: 13:22:52 time: 1.3664 data_time: 0.0032 memory: 5117 grad_norm: 0.1033 loss: 0.2414 loss_sem_seg: 0.2414 2023/05/13 08:26:45 - mmengine - INFO - Epoch(train) [14][ 800/1196] lr: 8.0000e-03 eta: 13:20:44 time: 1.3393 data_time: 0.0033 memory: 4498 grad_norm: 0.1172 loss: 0.2347 loss_sem_seg: 0.2347 2023/05/13 08:27:52 - mmengine - INFO - Epoch(train) [14][ 850/1196] lr: 8.0000e-03 eta: 13:18:37 time: 1.3362 data_time: 0.0032 memory: 4624 grad_norm: 0.1194 loss: 0.2287 loss_sem_seg: 0.2287 2023/05/13 08:28:55 - mmengine - INFO - Epoch(train) [14][ 900/1196] lr: 8.0000e-03 eta: 13:16:23 time: 1.2598 data_time: 0.0033 memory: 4732 grad_norm: 0.1161 loss: 0.2459 loss_sem_seg: 0.2459 2023/05/13 08:29:59 - mmengine - INFO - Epoch(train) [14][ 950/1196] lr: 8.0000e-03 eta: 13:14:12 time: 1.2809 data_time: 0.0032 memory: 4862 grad_norm: 0.1139 loss: 0.2452 loss_sem_seg: 0.2452 2023/05/13 08:31:02 - mmengine - INFO - Epoch(train) [14][1000/1196] lr: 8.0000e-03 eta: 13:12:00 time: 1.2687 data_time: 0.0035 memory: 4519 grad_norm: 0.1076 loss: 0.2229 loss_sem_seg: 0.2229 2023/05/13 08:32:05 - mmengine - INFO - Epoch(train) [14][1050/1196] lr: 8.0000e-03 eta: 13:09:48 time: 1.2516 data_time: 0.0036 memory: 4906 grad_norm: 0.1224 loss: 0.2192 loss_sem_seg: 0.2192 2023/05/13 08:33:09 - mmengine - INFO - Epoch(train) [14][1100/1196] lr: 8.0000e-03 eta: 13:07:37 time: 1.2754 data_time: 0.0032 memory: 4674 grad_norm: 0.1201 loss: 0.2435 loss_sem_seg: 0.2435 2023/05/13 08:34:12 - mmengine - INFO - Epoch(train) [14][1150/1196] lr: 8.0000e-03 eta: 13:05:26 time: 1.2610 data_time: 0.0033 memory: 4564 grad_norm: 0.1047 loss: 0.2295 loss_sem_seg: 0.2295 2023/05/13 08:35:22 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 08:35:22 - mmengine - INFO - Saving checkpoint at 14 epochs 2023/05/13 08:35:42 - mmengine - INFO - Epoch(val) [14][ 50/509] eta: 0:02:08 time: 0.2790 data_time: 0.0021 memory: 4678 2023/05/13 08:35:54 - mmengine - INFO - Epoch(val) [14][100/509] eta: 0:01:45 time: 0.2366 data_time: 0.0020 memory: 914 2023/05/13 08:36:06 - mmengine - INFO - Epoch(val) [14][150/509] eta: 0:01:29 time: 0.2316 data_time: 0.0020 memory: 915 2023/05/13 08:36:17 - mmengine - INFO - Epoch(val) [14][200/509] eta: 0:01:15 time: 0.2366 data_time: 0.0020 memory: 901 2023/05/13 08:36:31 - mmengine - INFO - Epoch(val) [14][250/509] eta: 0:01:04 time: 0.2694 data_time: 0.0021 memory: 929 2023/05/13 08:36:42 - mmengine - INFO - Epoch(val) [14][300/509] eta: 0:00:51 time: 0.2232 data_time: 0.0020 memory: 867 2023/05/13 08:36:54 - mmengine - INFO - Epoch(val) [14][350/509] eta: 0:00:39 time: 0.2431 data_time: 0.0020 memory: 891 2023/05/13 08:37:07 - mmengine - INFO - Epoch(val) [14][400/509] eta: 0:00:26 time: 0.2607 data_time: 0.0020 memory: 899 2023/05/13 08:37:19 - mmengine - INFO - Epoch(val) [14][450/509] eta: 0:00:14 time: 0.2439 data_time: 0.0021 memory: 911 2023/05/13 08:37:31 - mmengine - INFO - Epoch(val) [14][500/509] eta: 0:00:02 time: 0.2223 data_time: 0.0020 memory: 893 2023/05/13 08:37:51 - 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 | 0.9640 | 0.5031 | 0.7433 | 0.6632 | 0.6403 | 0.7504 | 0.8551 | 0.0852 | 0.9403 | 0.4290 | 0.8090 | 0.0014 | 0.8999 | 0.5980 | 0.9022 | 0.6971 | 0.7865 | 0.6533 | 0.5031 | 0.6539 | 0.9261 | 0.7267 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 08:37:51 - mmengine - INFO - Epoch(val) [14][509/509] car: 0.9640 bicycle: 0.5031 motorcycle: 0.7433 truck: 0.6632 bus: 0.6403 person: 0.7504 bicyclist: 0.8551 motorcyclist: 0.0852 road: 0.9403 parking: 0.4290 sidewalk: 0.8090 other-ground: 0.0014 building: 0.8999 fence: 0.5980 vegetation: 0.9022 trunck: 0.6971 terrian: 0.7865 pole: 0.6533 traffic-sign: 0.5031 miou: 0.6539 acc: 0.9261 acc_cls: 0.7267 data_time: 0.0020 time: 0.2352 2023/05/13 08:39:07 - mmengine - INFO - Epoch(train) [15][ 50/1196] lr: 8.0000e-03 eta: 13:01:53 time: 1.5055 data_time: 0.0041 memory: 5596 grad_norm: 0.1094 loss: 0.2092 loss_sem_seg: 0.2092 2023/05/13 08:40:16 - mmengine - INFO - Epoch(train) [15][ 100/1196] lr: 8.0000e-03 eta: 12:59:53 time: 1.3899 data_time: 0.0034 memory: 4814 grad_norm: 0.1132 loss: 0.2170 loss_sem_seg: 0.2170 2023/05/13 08:41:18 - mmengine - INFO - Epoch(train) [15][ 150/1196] lr: 8.0000e-03 eta: 12:57:42 time: 1.2429 data_time: 0.0033 memory: 4597 grad_norm: 0.1160 loss: 0.2314 loss_sem_seg: 0.2314 2023/05/13 08:42:20 - mmengine - INFO - Epoch(train) [15][ 200/1196] lr: 8.0000e-03 eta: 12:55:31 time: 1.2395 data_time: 0.0032 memory: 4591 grad_norm: 0.1042 loss: 0.2267 loss_sem_seg: 0.2267 2023/05/13 08:43:23 - mmengine - INFO - Epoch(train) [15][ 250/1196] lr: 8.0000e-03 eta: 12:53:21 time: 1.2542 data_time: 0.0033 memory: 4745 grad_norm: 0.1212 loss: 0.2324 loss_sem_seg: 0.2324 2023/05/13 08:43:30 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 08:44:26 - mmengine - INFO - Epoch(train) [15][ 300/1196] lr: 8.0000e-03 eta: 12:51:12 time: 1.2522 data_time: 0.0033 memory: 4812 grad_norm: 0.1148 loss: 0.2218 loss_sem_seg: 0.2218 2023/05/13 08:45:28 - mmengine - INFO - Epoch(train) [15][ 350/1196] lr: 8.0000e-03 eta: 12:49:03 time: 1.2511 data_time: 0.0032 memory: 4683 grad_norm: 0.1225 loss: 0.2405 loss_sem_seg: 0.2405 2023/05/13 08:46:35 - mmengine - INFO - Epoch(train) [15][ 400/1196] lr: 8.0000e-03 eta: 12:47:01 time: 1.3431 data_time: 0.0033 memory: 4557 grad_norm: 0.1085 loss: 0.2363 loss_sem_seg: 0.2363 2023/05/13 08:47:51 - mmengine - INFO - Epoch(train) [15][ 450/1196] lr: 8.0000e-03 eta: 12:45:13 time: 1.5181 data_time: 0.0035 memory: 4788 grad_norm: 0.1122 loss: 0.2346 loss_sem_seg: 0.2346 2023/05/13 08:49:05 - mmengine - INFO - Epoch(train) [15][ 500/1196] lr: 8.0000e-03 eta: 12:43:22 time: 1.4831 data_time: 0.0033 memory: 4549 grad_norm: 0.1070 loss: 0.2261 loss_sem_seg: 0.2261 2023/05/13 08:50:19 - mmengine - INFO - Epoch(train) [15][ 550/1196] lr: 8.0000e-03 eta: 12:41:30 time: 1.4616 data_time: 0.0033 memory: 4688 grad_norm: 0.1089 loss: 0.2164 loss_sem_seg: 0.2164 2023/05/13 08:51:34 - mmengine - INFO - Epoch(train) [15][ 600/1196] lr: 8.0000e-03 eta: 12:39:42 time: 1.5001 data_time: 0.0034 memory: 4661 grad_norm: 0.1016 loss: 0.2181 loss_sem_seg: 0.2181 2023/05/13 08:52:47 - mmengine - INFO - Epoch(train) [15][ 650/1196] lr: 8.0000e-03 eta: 12:37:50 time: 1.4605 data_time: 0.0033 memory: 4969 grad_norm: 0.1001 loss: 0.2167 loss_sem_seg: 0.2167 2023/05/13 08:54:02 - mmengine - INFO - Epoch(train) [15][ 700/1196] lr: 8.0000e-03 eta: 12:36:01 time: 1.5000 data_time: 0.0033 memory: 5177 grad_norm: 0.1132 loss: 0.2336 loss_sem_seg: 0.2336 2023/05/13 08:55:13 - mmengine - INFO - Epoch(train) [15][ 750/1196] lr: 8.0000e-03 eta: 12:34:08 time: 1.4285 data_time: 0.0032 memory: 4592 grad_norm: 0.1164 loss: 0.2192 loss_sem_seg: 0.2192 2023/05/13 08:56:22 - mmengine - INFO - Epoch(train) [15][ 800/1196] lr: 8.0000e-03 eta: 12:32:10 time: 1.3700 data_time: 0.0033 memory: 4992 grad_norm: 0.0998 loss: 0.2179 loss_sem_seg: 0.2179 2023/05/13 08:57:29 - mmengine - INFO - Epoch(train) [15][ 850/1196] lr: 8.0000e-03 eta: 12:30:12 time: 1.3594 data_time: 0.0033 memory: 4306 grad_norm: 0.1047 loss: 0.2400 loss_sem_seg: 0.2400 2023/05/13 08:58:35 - mmengine - INFO - Epoch(train) [15][ 900/1196] lr: 8.0000e-03 eta: 12:28:10 time: 1.3047 data_time: 0.0032 memory: 4309 grad_norm: 0.1117 loss: 0.2290 loss_sem_seg: 0.2290 2023/05/13 08:59:42 - mmengine - INFO - Epoch(train) [15][ 950/1196] lr: 8.0000e-03 eta: 12:26:11 time: 1.3392 data_time: 0.0033 memory: 4995 grad_norm: 0.1082 loss: 0.2286 loss_sem_seg: 0.2286 2023/05/13 09:00:50 - mmengine - INFO - Epoch(train) [15][1000/1196] lr: 8.0000e-03 eta: 12:24:15 time: 1.3737 data_time: 0.0033 memory: 4445 grad_norm: 0.1133 loss: 0.2164 loss_sem_seg: 0.2164 2023/05/13 09:02:08 - mmengine - INFO - Epoch(train) [15][1050/1196] lr: 8.0000e-03 eta: 12:22:32 time: 1.5566 data_time: 0.0036 memory: 4810 grad_norm: 0.1006 loss: 0.2195 loss_sem_seg: 0.2195 2023/05/13 09:03:23 - mmengine - INFO - Epoch(train) [15][1100/1196] lr: 8.0000e-03 eta: 12:20:46 time: 1.5021 data_time: 0.0033 memory: 4495 grad_norm: 0.1186 loss: 0.2237 loss_sem_seg: 0.2237 2023/05/13 09:04:37 - mmengine - INFO - Epoch(train) [15][1150/1196] lr: 8.0000e-03 eta: 12:18:57 time: 1.4673 data_time: 0.0034 memory: 5031 grad_norm: 0.1165 loss: 0.2414 loss_sem_seg: 0.2414 2023/05/13 09:05:44 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 09:05:44 - mmengine - INFO - Saving checkpoint at 15 epochs 2023/05/13 09:06:04 - mmengine - INFO - Epoch(val) [15][ 50/509] eta: 0:02:11 time: 0.2867 data_time: 0.0021 memory: 4421 2023/05/13 09:06:17 - mmengine - INFO - Epoch(val) [15][100/509] eta: 0:01:48 time: 0.2417 data_time: 0.0021 memory: 914 2023/05/13 09:06:28 - mmengine - INFO - Epoch(val) [15][150/509] eta: 0:01:31 time: 0.2331 data_time: 0.0021 memory: 915 2023/05/13 09:06:41 - mmengine - INFO - Epoch(val) [15][200/509] eta: 0:01:18 time: 0.2582 data_time: 0.0020 memory: 901 2023/05/13 09:06:55 - mmengine - INFO - Epoch(val) [15][250/509] eta: 0:01:07 time: 0.2778 data_time: 0.0021 memory: 929 2023/05/13 09:07:06 - mmengine - INFO - Epoch(val) [15][300/509] eta: 0:00:53 time: 0.2291 data_time: 0.0020 memory: 867 2023/05/13 09:07:18 - mmengine - INFO - Epoch(val) [15][350/509] eta: 0:00:40 time: 0.2378 data_time: 0.0021 memory: 891 2023/05/13 09:07:31 - mmengine - INFO - Epoch(val) [15][400/509] eta: 0:00:27 time: 0.2536 data_time: 0.0021 memory: 899 2023/05/13 09:07:42 - mmengine - INFO - Epoch(val) [15][450/509] eta: 0:00:14 time: 0.2284 data_time: 0.0020 memory: 911 2023/05/13 09:07:55 - mmengine - INFO - Epoch(val) [15][500/509] eta: 0:00:02 time: 0.2555 data_time: 0.0019 memory: 893 2023/05/13 09:08:13 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9576 | 0.4905 | 0.7465 | 0.5734 | 0.4195 | 0.7409 | 0.8353 | 0.0472 | 0.9401 | 0.4455 | 0.8138 | 0.0346 | 0.8966 | 0.6001 | 0.8770 | 0.6794 | 0.7300 | 0.6397 | 0.5149 | 0.6307 | 0.9166 | 0.7188 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 09:08:14 - mmengine - INFO - Epoch(val) [15][509/509] car: 0.9576 bicycle: 0.4905 motorcycle: 0.7465 truck: 0.5734 bus: 0.4195 person: 0.7409 bicyclist: 0.8353 motorcyclist: 0.0472 road: 0.9401 parking: 0.4455 sidewalk: 0.8138 other-ground: 0.0346 building: 0.8966 fence: 0.6001 vegetation: 0.8770 trunck: 0.6794 terrian: 0.7300 pole: 0.6397 traffic-sign: 0.5149 miou: 0.6307 acc: 0.9166 acc_cls: 0.7188 data_time: 0.0019 time: 0.2625 2023/05/13 09:09:28 - mmengine - INFO - Epoch(train) [16][ 50/1196] lr: 8.0000e-03 eta: 12:15:29 time: 1.4947 data_time: 0.0041 memory: 5090 grad_norm: 0.1046 loss: 0.2346 loss_sem_seg: 0.2346 2023/05/13 09:09:43 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 09:10:37 - mmengine - INFO - Epoch(train) [16][ 100/1196] lr: 8.0000e-03 eta: 12:13:34 time: 1.3700 data_time: 0.0033 memory: 4619 grad_norm: 0.1034 loss: 0.2307 loss_sem_seg: 0.2307 2023/05/13 09:11:39 - mmengine - INFO - Epoch(train) [16][ 150/1196] lr: 8.0000e-03 eta: 12:11:30 time: 1.2401 data_time: 0.0033 memory: 4654 grad_norm: 0.1180 loss: 0.2141 loss_sem_seg: 0.2141 2023/05/13 09:12:42 - mmengine - INFO - Epoch(train) [16][ 200/1196] lr: 8.0000e-03 eta: 12:09:29 time: 1.2692 data_time: 0.0032 memory: 5361 grad_norm: 0.1107 loss: 0.2145 loss_sem_seg: 0.2145 2023/05/13 09:13:43 - mmengine - INFO - Epoch(train) [16][ 250/1196] lr: 8.0000e-03 eta: 12:07:25 time: 1.2251 data_time: 0.0033 memory: 4678 grad_norm: 0.1019 loss: 0.2315 loss_sem_seg: 0.2315 2023/05/13 09:14:47 - mmengine - INFO - Epoch(train) [16][ 300/1196] lr: 8.0000e-03 eta: 12:05:25 time: 1.2786 data_time: 0.0033 memory: 4555 grad_norm: 0.1012 loss: 0.2253 loss_sem_seg: 0.2253 2023/05/13 09:15:55 - mmengine - INFO - Epoch(train) [16][ 350/1196] lr: 8.0000e-03 eta: 12:03:29 time: 1.3421 data_time: 0.0033 memory: 4913 grad_norm: 0.1093 loss: 0.2453 loss_sem_seg: 0.2453 2023/05/13 09:17:07 - mmengine - INFO - Epoch(train) [16][ 400/1196] lr: 8.0000e-03 eta: 12:01:41 time: 1.4564 data_time: 0.0036 memory: 4749 grad_norm: 0.1069 loss: 0.2285 loss_sem_seg: 0.2285 2023/05/13 09:18:20 - mmengine - INFO - Epoch(train) [16][ 450/1196] lr: 8.0000e-03 eta: 11:59:54 time: 1.4553 data_time: 0.0037 memory: 4709 grad_norm: 0.1298 loss: 0.2293 loss_sem_seg: 0.2293 2023/05/13 09:19:34 - mmengine - INFO - Epoch(train) [16][ 500/1196] lr: 8.0000e-03 eta: 11:58:08 time: 1.4760 data_time: 0.0037 memory: 4867 grad_norm: 0.1055 loss: 0.2313 loss_sem_seg: 0.2313 2023/05/13 09:20:47 - mmengine - INFO - Epoch(train) [16][ 550/1196] lr: 8.0000e-03 eta: 11:56:22 time: 1.4658 data_time: 0.0036 memory: 4847 grad_norm: 0.1138 loss: 0.2455 loss_sem_seg: 0.2455 2023/05/13 09:22:01 - mmengine - INFO - Epoch(train) [16][ 600/1196] lr: 8.0000e-03 eta: 11:54:36 time: 1.4818 data_time: 0.0036 memory: 5492 grad_norm: 0.1138 loss: 0.2250 loss_sem_seg: 0.2250 2023/05/13 09:23:13 - mmengine - INFO - Epoch(train) [16][ 650/1196] lr: 8.0000e-03 eta: 11:52:48 time: 1.4362 data_time: 0.0033 memory: 4883 grad_norm: 0.1049 loss: 0.2449 loss_sem_seg: 0.2449 2023/05/13 09:24:28 - mmengine - INFO - Epoch(train) [16][ 700/1196] lr: 8.0000e-03 eta: 11:51:05 time: 1.4977 data_time: 0.0033 memory: 4701 grad_norm: 0.1053 loss: 0.2165 loss_sem_seg: 0.2165 2023/05/13 09:25:42 - mmengine - INFO - Epoch(train) [16][ 750/1196] lr: 8.0000e-03 eta: 11:49:20 time: 1.4787 data_time: 0.0033 memory: 4905 grad_norm: 0.1246 loss: 0.2291 loss_sem_seg: 0.2291 2023/05/13 09:26:55 - mmengine - INFO - Epoch(train) [16][ 800/1196] lr: 8.0000e-03 eta: 11:47:33 time: 1.4541 data_time: 0.0034 memory: 4689 grad_norm: 0.1037 loss: 0.2277 loss_sem_seg: 0.2277 2023/05/13 09:28:01 - mmengine - INFO - Epoch(train) [16][ 850/1196] lr: 8.0000e-03 eta: 11:45:39 time: 1.3336 data_time: 0.0034 memory: 4589 grad_norm: 0.1016 loss: 0.2272 loss_sem_seg: 0.2272 2023/05/13 09:29:10 - mmengine - INFO - Epoch(train) [16][ 900/1196] lr: 8.0000e-03 eta: 11:43:48 time: 1.3676 data_time: 0.0036 memory: 4867 grad_norm: 0.1213 loss: 0.2319 loss_sem_seg: 0.2319 2023/05/13 09:30:17 - mmengine - INFO - Epoch(train) [16][ 950/1196] lr: 8.0000e-03 eta: 11:41:55 time: 1.3381 data_time: 0.0036 memory: 4904 grad_norm: 0.1135 loss: 0.2082 loss_sem_seg: 0.2082 2023/05/13 09:31:23 - mmengine - INFO - Epoch(train) [16][1000/1196] lr: 8.0000e-03 eta: 11:40:01 time: 1.3283 data_time: 0.0033 memory: 4771 grad_norm: 0.1021 loss: 0.2095 loss_sem_seg: 0.2095 2023/05/13 09:32:32 - mmengine - INFO - Epoch(train) [16][1050/1196] lr: 8.0000e-03 eta: 11:38:11 time: 1.3744 data_time: 0.0035 memory: 4601 grad_norm: 0.1005 loss: 0.2136 loss_sem_seg: 0.2136 2023/05/13 09:32:45 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 09:33:45 - mmengine - INFO - Epoch(train) [16][1100/1196] lr: 8.0000e-03 eta: 11:36:26 time: 1.4558 data_time: 0.0032 memory: 5007 grad_norm: 0.1138 loss: 0.2116 loss_sem_seg: 0.2116 2023/05/13 09:34:57 - mmengine - INFO - Epoch(train) [16][1150/1196] lr: 8.0000e-03 eta: 11:34:41 time: 1.4522 data_time: 0.0033 memory: 4676 grad_norm: 0.1102 loss: 0.2229 loss_sem_seg: 0.2229 2023/05/13 09:36:05 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 09:36:05 - mmengine - INFO - Saving checkpoint at 16 epochs 2023/05/13 09:36:25 - mmengine - INFO - Epoch(val) [16][ 50/509] eta: 0:02:04 time: 0.2719 data_time: 0.0021 memory: 4814 2023/05/13 09:36:37 - mmengine - INFO - Epoch(val) [16][100/509] eta: 0:01:46 time: 0.2507 data_time: 0.0020 memory: 914 2023/05/13 09:36:50 - mmengine - INFO - Epoch(val) [16][150/509] eta: 0:01:31 time: 0.2418 data_time: 0.0020 memory: 915 2023/05/13 09:37:02 - mmengine - INFO - Epoch(val) [16][200/509] eta: 0:01:18 time: 0.2530 data_time: 0.0020 memory: 901 2023/05/13 09:37:16 - mmengine - INFO - Epoch(val) [16][250/509] eta: 0:01:06 time: 0.2660 data_time: 0.0020 memory: 929 2023/05/13 09:37:27 - mmengine - INFO - Epoch(val) [16][300/509] eta: 0:00:52 time: 0.2249 data_time: 0.0020 memory: 867 2023/05/13 09:37:39 - mmengine - INFO - Epoch(val) [16][350/509] eta: 0:00:39 time: 0.2410 data_time: 0.0020 memory: 891 2023/05/13 09:37:51 - mmengine - INFO - Epoch(val) [16][400/509] eta: 0:00:27 time: 0.2421 data_time: 0.0020 memory: 899 2023/05/13 09:38:03 - mmengine - INFO - Epoch(val) [16][450/509] eta: 0:00:14 time: 0.2487 data_time: 0.0021 memory: 911 2023/05/13 09:38:15 - mmengine - INFO - Epoch(val) [16][500/509] eta: 0:00:02 time: 0.2395 data_time: 0.0019 memory: 893 2023/05/13 09:38:35 - 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 | 0.9669 | 0.4763 | 0.7718 | 0.8206 | 0.6608 | 0.7126 | 0.8125 | 0.0414 | 0.9377 | 0.3993 | 0.8156 | 0.0050 | 0.9052 | 0.6025 | 0.8871 | 0.6796 | 0.7635 | 0.6590 | 0.4723 | 0.6521 | 0.9224 | 0.7247 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 09:38:35 - mmengine - INFO - Epoch(val) [16][509/509] car: 0.9669 bicycle: 0.4763 motorcycle: 0.7718 truck: 0.8206 bus: 0.6608 person: 0.7126 bicyclist: 0.8125 motorcyclist: 0.0414 road: 0.9377 parking: 0.3993 sidewalk: 0.8156 other-ground: 0.0050 building: 0.9052 fence: 0.6025 vegetation: 0.8871 trunck: 0.6796 terrian: 0.7635 pole: 0.6590 traffic-sign: 0.4723 miou: 0.6521 acc: 0.9224 acc_cls: 0.7247 data_time: 0.0019 time: 0.2521 2023/05/13 09:39:51 - mmengine - INFO - Epoch(train) [17][ 50/1196] lr: 8.0000e-03 eta: 11:31:24 time: 1.5062 data_time: 0.0042 memory: 5034 grad_norm: 0.1129 loss: 0.2425 loss_sem_seg: 0.2425 2023/05/13 09:41:06 - mmengine - INFO - Epoch(train) [17][ 100/1196] lr: 8.0000e-03 eta: 11:29:43 time: 1.5031 data_time: 0.0033 memory: 4715 grad_norm: 0.1143 loss: 0.2357 loss_sem_seg: 0.2357 2023/05/13 09:42:20 - mmengine - INFO - Epoch(train) [17][ 150/1196] lr: 8.0000e-03 eta: 11:28:00 time: 1.4877 data_time: 0.0034 memory: 4673 grad_norm: 0.1352 loss: 0.2574 loss_sem_seg: 0.2574 2023/05/13 09:43:33 - mmengine - INFO - Epoch(train) [17][ 200/1196] lr: 8.0000e-03 eta: 11:26:17 time: 1.4600 data_time: 0.0033 memory: 5064 grad_norm: 0.1168 loss: 0.2282 loss_sem_seg: 0.2282 2023/05/13 09:44:47 - mmengine - INFO - Epoch(train) [17][ 250/1196] lr: 8.0000e-03 eta: 11:24:34 time: 1.4692 data_time: 0.0032 memory: 4569 grad_norm: 0.1034 loss: 0.2419 loss_sem_seg: 0.2419 2023/05/13 09:46:02 - mmengine - INFO - Epoch(train) [17][ 300/1196] lr: 8.0000e-03 eta: 11:22:53 time: 1.5004 data_time: 0.0033 memory: 4906 grad_norm: 0.1067 loss: 0.2349 loss_sem_seg: 0.2349 2023/05/13 09:47:14 - mmengine - INFO - Epoch(train) [17][ 350/1196] lr: 8.0000e-03 eta: 11:21:09 time: 1.4537 data_time: 0.0033 memory: 4711 grad_norm: 0.1087 loss: 0.2319 loss_sem_seg: 0.2319 2023/05/13 09:48:27 - mmengine - INFO - Epoch(train) [17][ 400/1196] lr: 8.0000e-03 eta: 11:19:26 time: 1.4622 data_time: 0.0033 memory: 4943 grad_norm: 0.1077 loss: 0.2387 loss_sem_seg: 0.2387 2023/05/13 09:49:41 - mmengine - INFO - Epoch(train) [17][ 450/1196] lr: 8.0000e-03 eta: 11:17:43 time: 1.4696 data_time: 0.0034 memory: 4559 grad_norm: 0.0984 loss: 0.2385 loss_sem_seg: 0.2385 2023/05/13 09:50:54 - mmengine - INFO - Epoch(train) [17][ 500/1196] lr: 8.0000e-03 eta: 11:16:01 time: 1.4625 data_time: 0.0034 memory: 4960 grad_norm: 0.0982 loss: 0.2289 loss_sem_seg: 0.2289 2023/05/13 09:52:07 - mmengine - INFO - Epoch(train) [17][ 550/1196] lr: 8.0000e-03 eta: 11:14:18 time: 1.4568 data_time: 0.0033 memory: 4686 grad_norm: 0.1018 loss: 0.2229 loss_sem_seg: 0.2229 2023/05/13 09:53:17 - mmengine - INFO - Epoch(train) [17][ 600/1196] lr: 8.0000e-03 eta: 11:12:31 time: 1.3984 data_time: 0.0034 memory: 4990 grad_norm: 0.1114 loss: 0.2145 loss_sem_seg: 0.2145 2023/05/13 09:54:21 - mmengine - INFO - Epoch(train) [17][ 650/1196] lr: 8.0000e-03 eta: 11:10:38 time: 1.2738 data_time: 0.0037 memory: 4855 grad_norm: 0.1170 loss: 0.2239 loss_sem_seg: 0.2239 2023/05/13 09:55:25 - mmengine - INFO - Epoch(train) [17][ 700/1196] lr: 8.0000e-03 eta: 11:08:46 time: 1.2934 data_time: 0.0037 memory: 4753 grad_norm: 0.1102 loss: 0.2286 loss_sem_seg: 0.2286 2023/05/13 09:56:29 - mmengine - INFO - Epoch(train) [17][ 750/1196] lr: 8.0000e-03 eta: 11:06:54 time: 1.2851 data_time: 0.0034 memory: 4844 grad_norm: 0.1044 loss: 0.2159 loss_sem_seg: 0.2159 2023/05/13 09:57:33 - mmengine - INFO - Epoch(train) [17][ 800/1196] lr: 8.0000e-03 eta: 11:05:01 time: 1.2712 data_time: 0.0035 memory: 4738 grad_norm: 0.1139 loss: 0.2344 loss_sem_seg: 0.2344 2023/05/13 09:58:38 - mmengine - INFO - Epoch(train) [17][ 850/1196] lr: 8.0000e-03 eta: 11:03:10 time: 1.2994 data_time: 0.0034 memory: 4684 grad_norm: 0.1236 loss: 0.2355 loss_sem_seg: 0.2355 2023/05/13 09:59:00 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 09:59:52 - mmengine - INFO - Epoch(train) [17][ 900/1196] lr: 8.0000e-03 eta: 11:01:30 time: 1.4745 data_time: 0.0033 memory: 5238 grad_norm: 0.1108 loss: 0.2104 loss_sem_seg: 0.2104 2023/05/13 10:00:59 - mmengine - INFO - Epoch(train) [17][ 950/1196] lr: 8.0000e-03 eta: 10:59:42 time: 1.3496 data_time: 0.0038 memory: 4522 grad_norm: 0.0928 loss: 0.2179 loss_sem_seg: 0.2179 2023/05/13 10:02:06 - mmengine - INFO - Epoch(train) [17][1000/1196] lr: 8.0000e-03 eta: 10:57:54 time: 1.3401 data_time: 0.0033 memory: 4446 grad_norm: 0.1086 loss: 0.2183 loss_sem_seg: 0.2183 2023/05/13 10:03:13 - mmengine - INFO - Epoch(train) [17][1050/1196] lr: 8.0000e-03 eta: 10:56:06 time: 1.3374 data_time: 0.0033 memory: 4589 grad_norm: 0.1083 loss: 0.2181 loss_sem_seg: 0.2181 2023/05/13 10:04:20 - mmengine - INFO - Epoch(train) [17][1100/1196] lr: 8.0000e-03 eta: 10:54:18 time: 1.3396 data_time: 0.0033 memory: 4847 grad_norm: 0.1114 loss: 0.2189 loss_sem_seg: 0.2189 2023/05/13 10:05:30 - mmengine - INFO - Epoch(train) [17][1150/1196] lr: 8.0000e-03 eta: 10:52:34 time: 1.3978 data_time: 0.0033 memory: 4275 grad_norm: 0.0944 loss: 0.2131 loss_sem_seg: 0.2131 2023/05/13 10:06:39 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 10:06:39 - mmengine - INFO - Saving checkpoint at 17 epochs 2023/05/13 10:06:59 - mmengine - INFO - Epoch(val) [17][ 50/509] eta: 0:02:02 time: 0.2673 data_time: 0.0021 memory: 4290 2023/05/13 10:07:11 - mmengine - INFO - Epoch(val) [17][100/509] eta: 0:01:44 time: 0.2424 data_time: 0.0021 memory: 914 2023/05/13 10:07:23 - mmengine - INFO - Epoch(val) [17][150/509] eta: 0:01:28 time: 0.2326 data_time: 0.0020 memory: 915 2023/05/13 10:07:35 - mmengine - INFO - Epoch(val) [17][200/509] eta: 0:01:16 time: 0.2492 data_time: 0.0021 memory: 901 2023/05/13 10:07:49 - mmengine - INFO - Epoch(val) [17][250/509] eta: 0:01:05 time: 0.2710 data_time: 0.0020 memory: 929 2023/05/13 10:07:59 - mmengine - INFO - Epoch(val) [17][300/509] eta: 0:00:51 time: 0.2024 data_time: 0.0020 memory: 867 2023/05/13 10:08:10 - mmengine - INFO - Epoch(val) [17][350/509] eta: 0:00:38 time: 0.2287 data_time: 0.0020 memory: 891 2023/05/13 10:08:23 - mmengine - INFO - Epoch(val) [17][400/509] eta: 0:00:26 time: 0.2583 data_time: 0.0020 memory: 899 2023/05/13 10:08:34 - mmengine - INFO - Epoch(val) [17][450/509] eta: 0:00:14 time: 0.2234 data_time: 0.0020 memory: 911 2023/05/13 10:08:47 - mmengine - INFO - Epoch(val) [17][500/509] eta: 0:00:02 time: 0.2440 data_time: 0.0020 memory: 893 2023/05/13 10:09:07 - 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 | 0.9381 | 0.5139 | 0.7313 | 0.7169 | 0.3150 | 0.7451 | 0.8224 | 0.0661 | 0.9379 | 0.4126 | 0.8079 | 0.0020 | 0.9069 | 0.6276 | 0.8735 | 0.7201 | 0.7290 | 0.6395 | 0.4976 | 0.6318 | 0.9156 | 0.7135 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 10:09:07 - mmengine - INFO - Epoch(val) [17][509/509] car: 0.9381 bicycle: 0.5139 motorcycle: 0.7313 truck: 0.7169 bus: 0.3150 person: 0.7451 bicyclist: 0.8224 motorcyclist: 0.0661 road: 0.9379 parking: 0.4126 sidewalk: 0.8079 other-ground: 0.0020 building: 0.9069 fence: 0.6276 vegetation: 0.8735 trunck: 0.7201 terrian: 0.7290 pole: 0.6395 traffic-sign: 0.4976 miou: 0.6318 acc: 0.9156 acc_cls: 0.7135 data_time: 0.0020 time: 0.2521 2023/05/13 10:10:21 - mmengine - INFO - Epoch(train) [18][ 50/1196] lr: 8.0000e-03 eta: 10:49:25 time: 1.4742 data_time: 0.0046 memory: 5004 grad_norm: 0.1069 loss: 0.2088 loss_sem_seg: 0.2088 2023/05/13 10:11:36 - mmengine - INFO - Epoch(train) [18][ 100/1196] lr: 8.0000e-03 eta: 10:47:46 time: 1.4926 data_time: 0.0034 memory: 5326 grad_norm: 0.1023 loss: 0.2043 loss_sem_seg: 0.2043 2023/05/13 10:12:50 - mmengine - INFO - Epoch(train) [18][ 150/1196] lr: 8.0000e-03 eta: 10:46:08 time: 1.4874 data_time: 0.0035 memory: 4553 grad_norm: 0.0961 loss: 0.2208 loss_sem_seg: 0.2208 2023/05/13 10:14:05 - mmengine - INFO - Epoch(train) [18][ 200/1196] lr: 8.0000e-03 eta: 10:44:30 time: 1.4966 data_time: 0.0034 memory: 4654 grad_norm: 0.1134 loss: 0.2180 loss_sem_seg: 0.2180 2023/05/13 10:15:20 - mmengine - INFO - Epoch(train) [18][ 250/1196] lr: 8.0000e-03 eta: 10:42:52 time: 1.5078 data_time: 0.0033 memory: 4614 grad_norm: 0.1011 loss: 0.2123 loss_sem_seg: 0.2123 2023/05/13 10:16:34 - mmengine - INFO - Epoch(train) [18][ 300/1196] lr: 8.0000e-03 eta: 10:41:13 time: 1.4739 data_time: 0.0033 memory: 5209 grad_norm: 0.1055 loss: 0.2221 loss_sem_seg: 0.2221 2023/05/13 10:17:47 - mmengine - INFO - Epoch(train) [18][ 350/1196] lr: 8.0000e-03 eta: 10:39:34 time: 1.4647 data_time: 0.0033 memory: 4410 grad_norm: 0.1029 loss: 0.2214 loss_sem_seg: 0.2214 2023/05/13 10:19:01 - mmengine - INFO - Epoch(train) [18][ 400/1196] lr: 8.0000e-03 eta: 10:37:56 time: 1.4839 data_time: 0.0034 memory: 4945 grad_norm: 0.0960 loss: 0.2330 loss_sem_seg: 0.2330 2023/05/13 10:20:15 - mmengine - INFO - Epoch(train) [18][ 450/1196] lr: 8.0000e-03 eta: 10:36:17 time: 1.4644 data_time: 0.0033 memory: 5029 grad_norm: 0.1090 loss: 0.2200 loss_sem_seg: 0.2200 2023/05/13 10:21:29 - mmengine - INFO - Epoch(train) [18][ 500/1196] lr: 8.0000e-03 eta: 10:34:38 time: 1.4786 data_time: 0.0034 memory: 5265 grad_norm: 0.1184 loss: 0.2135 loss_sem_seg: 0.2135 2023/05/13 10:22:42 - mmengine - INFO - Epoch(train) [18][ 550/1196] lr: 8.0000e-03 eta: 10:33:00 time: 1.4654 data_time: 0.0033 memory: 5101 grad_norm: 0.1021 loss: 0.2064 loss_sem_seg: 0.2064 2023/05/13 10:23:56 - mmengine - INFO - Epoch(train) [18][ 600/1196] lr: 8.0000e-03 eta: 10:31:22 time: 1.4812 data_time: 0.0033 memory: 4559 grad_norm: 0.0990 loss: 0.2130 loss_sem_seg: 0.2130 2023/05/13 10:25:08 - mmengine - INFO - Epoch(train) [18][ 650/1196] lr: 8.0000e-03 eta: 10:29:42 time: 1.4429 data_time: 0.0035 memory: 4998 grad_norm: 0.1032 loss: 0.2065 loss_sem_seg: 0.2065 2023/05/13 10:25:36 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 10:26:23 - mmengine - INFO - Epoch(train) [18][ 700/1196] lr: 8.0000e-03 eta: 10:28:05 time: 1.5028 data_time: 0.0034 memory: 5210 grad_norm: 0.0933 loss: 0.2100 loss_sem_seg: 0.2100 2023/05/13 10:27:38 - mmengine - INFO - Epoch(train) [18][ 750/1196] lr: 8.0000e-03 eta: 10:26:29 time: 1.4998 data_time: 0.0033 memory: 5417 grad_norm: 0.1004 loss: 0.2210 loss_sem_seg: 0.2210 2023/05/13 10:28:53 - mmengine - INFO - Epoch(train) [18][ 800/1196] lr: 8.0000e-03 eta: 10:24:53 time: 1.5021 data_time: 0.0033 memory: 4772 grad_norm: 0.1142 loss: 0.2176 loss_sem_seg: 0.2176 2023/05/13 10:30:08 - mmengine - INFO - Epoch(train) [18][ 850/1196] lr: 8.0000e-03 eta: 10:23:16 time: 1.4994 data_time: 0.0033 memory: 4736 grad_norm: 0.1039 loss: 0.2275 loss_sem_seg: 0.2275 2023/05/13 10:31:23 - mmengine - INFO - Epoch(train) [18][ 900/1196] lr: 8.0000e-03 eta: 10:21:39 time: 1.4888 data_time: 0.0034 memory: 5042 grad_norm: 0.1086 loss: 0.2277 loss_sem_seg: 0.2277 2023/05/13 10:32:37 - mmengine - INFO - Epoch(train) [18][ 950/1196] lr: 8.0000e-03 eta: 10:20:02 time: 1.4772 data_time: 0.0033 memory: 4944 grad_norm: 0.1269 loss: 0.2305 loss_sem_seg: 0.2305 2023/05/13 10:33:45 - mmengine - INFO - Epoch(train) [18][1000/1196] lr: 8.0000e-03 eta: 10:18:19 time: 1.3575 data_time: 0.0033 memory: 4492 grad_norm: 0.0969 loss: 0.2302 loss_sem_seg: 0.2302 2023/05/13 10:34:53 - mmengine - INFO - Epoch(train) [18][1050/1196] lr: 8.0000e-03 eta: 10:16:36 time: 1.3602 data_time: 0.0033 memory: 4631 grad_norm: 0.0972 loss: 0.2056 loss_sem_seg: 0.2056 2023/05/13 10:35:57 - mmengine - INFO - Epoch(train) [18][1100/1196] lr: 8.0000e-03 eta: 10:14:49 time: 1.2826 data_time: 0.0033 memory: 4914 grad_norm: 0.0898 loss: 0.2188 loss_sem_seg: 0.2188 2023/05/13 10:36:53 - mmengine - INFO - Epoch(train) [18][1150/1196] lr: 8.0000e-03 eta: 10:12:54 time: 1.1212 data_time: 0.0032 memory: 4651 grad_norm: 0.1016 loss: 0.2212 loss_sem_seg: 0.2212 2023/05/13 10:37:44 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 10:37:44 - mmengine - INFO - Saving checkpoint at 18 epochs 2023/05/13 10:38:02 - mmengine - INFO - Epoch(val) [18][ 50/509] eta: 0:01:41 time: 0.2207 data_time: 0.0021 memory: 4833 2023/05/13 10:38:09 - mmengine - INFO - Epoch(val) [18][100/509] eta: 0:01:12 time: 0.1354 data_time: 0.0020 memory: 914 2023/05/13 10:38:15 - mmengine - INFO - Epoch(val) [18][150/509] eta: 0:00:57 time: 0.1210 data_time: 0.0019 memory: 915 2023/05/13 10:38:22 - mmengine - INFO - Epoch(val) [18][200/509] eta: 0:00:48 time: 0.1463 data_time: 0.0019 memory: 901 2023/05/13 10:38:31 - mmengine - INFO - Epoch(val) [18][250/509] eta: 0:00:41 time: 0.1831 data_time: 0.0020 memory: 929 2023/05/13 10:38:39 - mmengine - INFO - Epoch(val) [18][300/509] eta: 0:00:33 time: 0.1531 data_time: 0.0020 memory: 867 2023/05/13 10:38:47 - mmengine - INFO - Epoch(val) [18][350/509] eta: 0:00:25 time: 0.1620 data_time: 0.0020 memory: 891 2023/05/13 10:38:56 - mmengine - INFO - Epoch(val) [18][400/509] eta: 0:00:17 time: 0.1746 data_time: 0.0020 memory: 899 2023/05/13 10:39:04 - mmengine - INFO - Epoch(val) [18][450/509] eta: 0:00:09 time: 0.1702 data_time: 0.0020 memory: 911 2023/05/13 10:39:12 - mmengine - INFO - Epoch(val) [18][500/509] eta: 0:00:01 time: 0.1639 data_time: 0.0019 memory: 893 2023/05/13 10:39:30 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9486 | 0.5339 | 0.6847 | 0.7120 | 0.4469 | 0.7552 | 0.8128 | 0.0876 | 0.9333 | 0.3548 | 0.8039 | 0.0008 | 0.9094 | 0.6428 | 0.8880 | 0.6504 | 0.7593 | 0.6497 | 0.5071 | 0.6359 | 0.9203 | 0.7088 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 10:39:30 - mmengine - INFO - Epoch(val) [18][509/509] car: 0.9486 bicycle: 0.5339 motorcycle: 0.6847 truck: 0.7120 bus: 0.4469 person: 0.7552 bicyclist: 0.8128 motorcyclist: 0.0876 road: 0.9333 parking: 0.3548 sidewalk: 0.8039 other-ground: 0.0008 building: 0.9094 fence: 0.6428 vegetation: 0.8880 trunck: 0.6504 terrian: 0.7593 pole: 0.6497 traffic-sign: 0.5071 miou: 0.6359 acc: 0.9203 acc_cls: 0.7088 data_time: 0.0019 time: 0.1729 2023/05/13 10:40:35 - mmengine - INFO - Epoch(train) [19][ 50/1196] lr: 8.0000e-03 eta: 10:09:23 time: 1.2919 data_time: 0.0045 memory: 5265 grad_norm: 0.0989 loss: 0.2059 loss_sem_seg: 0.2059 2023/05/13 10:41:38 - mmengine - INFO - Epoch(train) [19][ 100/1196] lr: 8.0000e-03 eta: 10:07:37 time: 1.2696 data_time: 0.0033 memory: 4738 grad_norm: 0.1007 loss: 0.2019 loss_sem_seg: 0.2019 2023/05/13 10:42:40 - mmengine - INFO - Epoch(train) [19][ 150/1196] lr: 8.0000e-03 eta: 10:05:49 time: 1.2449 data_time: 0.0035 memory: 4414 grad_norm: 0.1001 loss: 0.2231 loss_sem_seg: 0.2231 2023/05/13 10:43:51 - mmengine - INFO - Epoch(train) [19][ 200/1196] lr: 8.0000e-03 eta: 10:04:10 time: 1.4100 data_time: 0.0038 memory: 4675 grad_norm: 0.0934 loss: 0.2082 loss_sem_seg: 0.2082 2023/05/13 10:45:07 - mmengine - INFO - Epoch(train) [19][ 250/1196] lr: 8.0000e-03 eta: 10:02:36 time: 1.5141 data_time: 0.0037 memory: 4740 grad_norm: 0.1024 loss: 0.2118 loss_sem_seg: 0.2118 2023/05/13 10:46:22 - mmengine - INFO - Epoch(train) [19][ 300/1196] lr: 8.0000e-03 eta: 10:01:02 time: 1.5189 data_time: 0.0036 memory: 5313 grad_norm: 0.1006 loss: 0.2163 loss_sem_seg: 0.2163 2023/05/13 10:47:38 - mmengine - INFO - Epoch(train) [19][ 350/1196] lr: 8.0000e-03 eta: 9:59:28 time: 1.5090 data_time: 0.0034 memory: 4313 grad_norm: 0.1062 loss: 0.2075 loss_sem_seg: 0.2075 2023/05/13 10:48:52 - mmengine - INFO - Epoch(train) [19][ 400/1196] lr: 8.0000e-03 eta: 9:57:53 time: 1.4814 data_time: 0.0033 memory: 4762 grad_norm: 0.1017 loss: 0.2199 loss_sem_seg: 0.2199 2023/05/13 10:50:06 - mmengine - INFO - Epoch(train) [19][ 450/1196] lr: 8.0000e-03 eta: 9:56:18 time: 1.4870 data_time: 0.0033 memory: 4713 grad_norm: 0.1048 loss: 0.2203 loss_sem_seg: 0.2203 2023/05/13 10:50:40 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 10:51:21 - mmengine - INFO - Epoch(train) [19][ 500/1196] lr: 8.0000e-03 eta: 9:54:43 time: 1.4913 data_time: 0.0034 memory: 4998 grad_norm: 0.0964 loss: 0.2151 loss_sem_seg: 0.2151 2023/05/13 10:52:32 - mmengine - INFO - Epoch(train) [19][ 550/1196] lr: 8.0000e-03 eta: 9:53:05 time: 1.4296 data_time: 0.0033 memory: 4483 grad_norm: 0.0965 loss: 0.2148 loss_sem_seg: 0.2148 2023/05/13 10:53:49 - mmengine - INFO - Epoch(train) [19][ 600/1196] lr: 8.0000e-03 eta: 9:51:33 time: 1.5341 data_time: 0.0034 memory: 5071 grad_norm: 0.0984 loss: 0.2096 loss_sem_seg: 0.2096 2023/05/13 10:55:03 - mmengine - INFO - Epoch(train) [19][ 650/1196] lr: 8.0000e-03 eta: 9:49:58 time: 1.4724 data_time: 0.0034 memory: 4502 grad_norm: 0.1022 loss: 0.2062 loss_sem_seg: 0.2062 2023/05/13 10:56:16 - mmengine - INFO - Epoch(train) [19][ 700/1196] lr: 8.0000e-03 eta: 9:48:22 time: 1.4663 data_time: 0.0033 memory: 5968 grad_norm: 0.1079 loss: 0.2216 loss_sem_seg: 0.2216 2023/05/13 10:57:31 - mmengine - INFO - Epoch(train) [19][ 750/1196] lr: 8.0000e-03 eta: 9:46:48 time: 1.4932 data_time: 0.0033 memory: 5263 grad_norm: 0.1001 loss: 0.2209 loss_sem_seg: 0.2209 2023/05/13 10:58:43 - mmengine - INFO - Epoch(train) [19][ 800/1196] lr: 8.0000e-03 eta: 9:45:12 time: 1.4526 data_time: 0.0034 memory: 4769 grad_norm: 0.1071 loss: 0.2121 loss_sem_seg: 0.2121 2023/05/13 10:59:56 - mmengine - INFO - Epoch(train) [19][ 850/1196] lr: 8.0000e-03 eta: 9:43:36 time: 1.4574 data_time: 0.0034 memory: 5070 grad_norm: 0.1046 loss: 0.2330 loss_sem_seg: 0.2330 2023/05/13 11:01:10 - mmengine - INFO - Epoch(train) [19][ 900/1196] lr: 8.0000e-03 eta: 9:42:02 time: 1.4798 data_time: 0.0035 memory: 4576 grad_norm: 0.1007 loss: 0.2230 loss_sem_seg: 0.2230 2023/05/13 11:02:23 - mmengine - INFO - Epoch(train) [19][ 950/1196] lr: 8.0000e-03 eta: 9:40:26 time: 1.4552 data_time: 0.0033 memory: 4472 grad_norm: 0.0981 loss: 0.2018 loss_sem_seg: 0.2018 2023/05/13 11:03:37 - mmengine - INFO - Epoch(train) [19][1000/1196] lr: 8.0000e-03 eta: 9:38:52 time: 1.4893 data_time: 0.0034 memory: 4648 grad_norm: 0.1206 loss: 0.2157 loss_sem_seg: 0.2157 2023/05/13 11:04:48 - mmengine - INFO - Epoch(train) [19][1050/1196] lr: 8.0000e-03 eta: 9:37:15 time: 1.4013 data_time: 0.0034 memory: 4700 grad_norm: 0.1163 loss: 0.2341 loss_sem_seg: 0.2341 2023/05/13 11:05:55 - mmengine - INFO - Epoch(train) [19][1100/1196] lr: 8.0000e-03 eta: 9:35:35 time: 1.3579 data_time: 0.0033 memory: 5008 grad_norm: 0.0930 loss: 0.2206 loss_sem_seg: 0.2206 2023/05/13 11:07:02 - mmengine - INFO - Epoch(train) [19][1150/1196] lr: 8.0000e-03 eta: 9:33:55 time: 1.3385 data_time: 0.0032 memory: 4526 grad_norm: 0.0969 loss: 0.2250 loss_sem_seg: 0.2250 2023/05/13 11:08:05 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 11:08:05 - mmengine - INFO - Saving checkpoint at 19 epochs 2023/05/13 11:08:24 - mmengine - INFO - Epoch(val) [19][ 50/509] eta: 0:01:52 time: 0.2459 data_time: 0.0021 memory: 4607 2023/05/13 11:08:34 - mmengine - INFO - Epoch(val) [19][100/509] eta: 0:01:32 time: 0.2075 data_time: 0.0020 memory: 914 2023/05/13 11:08:45 - mmengine - INFO - Epoch(val) [19][150/509] eta: 0:01:20 time: 0.2154 data_time: 0.0020 memory: 915 2023/05/13 11:08:56 - mmengine - INFO - Epoch(val) [19][200/509] eta: 0:01:08 time: 0.2210 data_time: 0.0021 memory: 901 2023/05/13 11:09:07 - mmengine - INFO - Epoch(val) [19][250/509] eta: 0:00:57 time: 0.2208 data_time: 0.0020 memory: 929 2023/05/13 11:09:17 - mmengine - INFO - Epoch(val) [19][300/509] eta: 0:00:45 time: 0.1984 data_time: 0.0021 memory: 867 2023/05/13 11:09:28 - mmengine - INFO - Epoch(val) [19][350/509] eta: 0:00:34 time: 0.2201 data_time: 0.0021 memory: 891 2023/05/13 11:09:38 - mmengine - INFO - Epoch(val) [19][400/509] eta: 0:00:23 time: 0.2066 data_time: 0.0020 memory: 899 2023/05/13 11:09:49 - mmengine - INFO - Epoch(val) [19][450/509] eta: 0:00:12 time: 0.2194 data_time: 0.0021 memory: 911 2023/05/13 11:10:00 - mmengine - INFO - Epoch(val) [19][500/509] eta: 0:00:01 time: 0.2199 data_time: 0.0020 memory: 893 2023/05/13 11:10:19 - 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 | 0.9584 | 0.4227 | 0.6619 | 0.7883 | 0.5742 | 0.7622 | 0.8318 | 0.1201 | 0.9328 | 0.5558 | 0.8112 | 0.0070 | 0.9116 | 0.6262 | 0.8905 | 0.6749 | 0.7812 | 0.6626 | 0.5038 | 0.6567 | 0.9243 | 0.7363 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 11:10:19 - mmengine - INFO - Epoch(val) [19][509/509] car: 0.9584 bicycle: 0.4227 motorcycle: 0.6619 truck: 0.7883 bus: 0.5742 person: 0.7622 bicyclist: 0.8318 motorcyclist: 0.1201 road: 0.9328 parking: 0.5558 sidewalk: 0.8112 other-ground: 0.0070 building: 0.9116 fence: 0.6262 vegetation: 0.8905 trunck: 0.6749 terrian: 0.7812 pole: 0.6626 traffic-sign: 0.5038 miou: 0.6567 acc: 0.9243 acc_cls: 0.7363 data_time: 0.0020 time: 0.2302 2023/05/13 11:11:34 - mmengine - INFO - Epoch(train) [20][ 50/1196] lr: 8.0000e-03 eta: 9:30:50 time: 1.4887 data_time: 0.0049 memory: 4693 grad_norm: 0.0981 loss: 0.2092 loss_sem_seg: 0.2092 2023/05/13 11:12:47 - mmengine - INFO - Epoch(train) [20][ 100/1196] lr: 8.0000e-03 eta: 9:29:16 time: 1.4649 data_time: 0.0035 memory: 4695 grad_norm: 0.0942 loss: 0.2017 loss_sem_seg: 0.2017 2023/05/13 11:14:02 - mmengine - INFO - Epoch(train) [20][ 150/1196] lr: 8.0000e-03 eta: 9:27:43 time: 1.4935 data_time: 0.0035 memory: 4533 grad_norm: 0.0951 loss: 0.2221 loss_sem_seg: 0.2221 2023/05/13 11:15:15 - mmengine - INFO - Epoch(train) [20][ 200/1196] lr: 8.0000e-03 eta: 9:26:08 time: 1.4663 data_time: 0.0033 memory: 4477 grad_norm: 0.1097 loss: 0.2248 loss_sem_seg: 0.2248 2023/05/13 11:16:30 - mmengine - INFO - Epoch(train) [20][ 250/1196] lr: 8.0000e-03 eta: 9:24:36 time: 1.4933 data_time: 0.0033 memory: 4954 grad_norm: 0.1054 loss: 0.2147 loss_sem_seg: 0.2147 2023/05/13 11:17:04 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 11:17:34 - mmengine - INFO - Epoch(train) [20][ 300/1196] lr: 8.0000e-03 eta: 9:22:54 time: 1.2940 data_time: 0.0033 memory: 4376 grad_norm: 0.1067 loss: 0.2009 loss_sem_seg: 0.2009 2023/05/13 11:18:38 - mmengine - INFO - Epoch(train) [20][ 350/1196] lr: 8.0000e-03 eta: 9:21:12 time: 1.2704 data_time: 0.0033 memory: 4518 grad_norm: 0.0895 loss: 0.2180 loss_sem_seg: 0.2180 2023/05/13 11:19:41 - mmengine - INFO - Epoch(train) [20][ 400/1196] lr: 8.0000e-03 eta: 9:19:30 time: 1.2684 data_time: 0.0035 memory: 4543 grad_norm: 0.1029 loss: 0.2052 loss_sem_seg: 0.2052 2023/05/13 11:20:45 - mmengine - INFO - Epoch(train) [20][ 450/1196] lr: 8.0000e-03 eta: 9:17:48 time: 1.2803 data_time: 0.0033 memory: 5127 grad_norm: 0.0981 loss: 0.2322 loss_sem_seg: 0.2322 2023/05/13 11:21:49 - mmengine - INFO - Epoch(train) [20][ 500/1196] lr: 8.0000e-03 eta: 9:16:06 time: 1.2706 data_time: 0.0033 memory: 4782 grad_norm: 0.0967 loss: 0.2090 loss_sem_seg: 0.2090 2023/05/13 11:23:01 - mmengine - INFO - Epoch(train) [20][ 550/1196] lr: 8.0000e-03 eta: 9:14:32 time: 1.4408 data_time: 0.0035 memory: 4801 grad_norm: 0.0982 loss: 0.2047 loss_sem_seg: 0.2047 2023/05/13 11:24:15 - mmengine - INFO - Epoch(train) [20][ 600/1196] lr: 8.0000e-03 eta: 9:12:59 time: 1.4841 data_time: 0.0035 memory: 4588 grad_norm: 0.1097 loss: 0.2213 loss_sem_seg: 0.2213 2023/05/13 11:25:29 - mmengine - INFO - Epoch(train) [20][ 650/1196] lr: 8.0000e-03 eta: 9:11:27 time: 1.4750 data_time: 0.0033 memory: 4852 grad_norm: 0.0932 loss: 0.2042 loss_sem_seg: 0.2042 2023/05/13 11:26:43 - mmengine - INFO - Epoch(train) [20][ 700/1196] lr: 8.0000e-03 eta: 9:09:54 time: 1.4748 data_time: 0.0034 memory: 4670 grad_norm: 0.0931 loss: 0.2047 loss_sem_seg: 0.2047 2023/05/13 11:27:57 - mmengine - INFO - Epoch(train) [20][ 750/1196] lr: 8.0000e-03 eta: 9:08:21 time: 1.4787 data_time: 0.0033 memory: 4880 grad_norm: 0.0950 loss: 0.2083 loss_sem_seg: 0.2083 2023/05/13 11:29:13 - mmengine - INFO - Epoch(train) [20][ 800/1196] lr: 8.0000e-03 eta: 9:06:51 time: 1.5180 data_time: 0.0033 memory: 4903 grad_norm: 0.0992 loss: 0.2127 loss_sem_seg: 0.2127 2023/05/13 11:30:28 - mmengine - INFO - Epoch(train) [20][ 850/1196] lr: 8.0000e-03 eta: 9:05:20 time: 1.5092 data_time: 0.0033 memory: 4532 grad_norm: 0.0942 loss: 0.2139 loss_sem_seg: 0.2139 2023/05/13 11:31:43 - mmengine - INFO - Epoch(train) [20][ 900/1196] lr: 8.0000e-03 eta: 9:03:48 time: 1.4972 data_time: 0.0034 memory: 4761 grad_norm: 0.0937 loss: 0.2200 loss_sem_seg: 0.2200 2023/05/13 11:32:57 - mmengine - INFO - Epoch(train) [20][ 950/1196] lr: 8.0000e-03 eta: 9:02:16 time: 1.4771 data_time: 0.0033 memory: 4531 grad_norm: 0.0952 loss: 0.2041 loss_sem_seg: 0.2041 2023/05/13 11:34:10 - mmengine - INFO - Epoch(train) [20][1000/1196] lr: 8.0000e-03 eta: 9:00:43 time: 1.4621 data_time: 0.0034 memory: 4967 grad_norm: 0.1038 loss: 0.2054 loss_sem_seg: 0.2054 2023/05/13 11:35:23 - mmengine - INFO - Epoch(train) [20][1050/1196] lr: 8.0000e-03 eta: 8:59:11 time: 1.4724 data_time: 0.0033 memory: 4559 grad_norm: 0.0884 loss: 0.2108 loss_sem_seg: 0.2108 2023/05/13 11:36:35 - mmengine - INFO - Epoch(train) [20][1100/1196] lr: 8.0000e-03 eta: 8:57:37 time: 1.4304 data_time: 0.0034 memory: 4759 grad_norm: 0.0938 loss: 0.2216 loss_sem_seg: 0.2216 2023/05/13 11:37:44 - mmengine - INFO - Epoch(train) [20][1150/1196] lr: 8.0000e-03 eta: 8:56:01 time: 1.3808 data_time: 0.0034 memory: 5296 grad_norm: 0.0935 loss: 0.2119 loss_sem_seg: 0.2119 2023/05/13 11:38:46 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 11:38:46 - mmengine - INFO - Saving checkpoint at 20 epochs 2023/05/13 11:39:04 - mmengine - INFO - Epoch(val) [20][ 50/509] eta: 0:01:55 time: 0.2512 data_time: 0.0021 memory: 4382 2023/05/13 11:39:14 - mmengine - INFO - Epoch(val) [20][100/509] eta: 0:01:32 time: 0.1998 data_time: 0.0020 memory: 914 2023/05/13 11:39:26 - mmengine - INFO - Epoch(val) [20][150/509] eta: 0:01:20 time: 0.2234 data_time: 0.0020 memory: 915 2023/05/13 11:39:37 - mmengine - INFO - Epoch(val) [20][200/509] eta: 0:01:10 time: 0.2330 data_time: 0.0021 memory: 901 2023/05/13 11:39:49 - mmengine - INFO - Epoch(val) [20][250/509] eta: 0:00:59 time: 0.2378 data_time: 0.0020 memory: 929 2023/05/13 11:39:59 - mmengine - INFO - Epoch(val) [20][300/509] eta: 0:00:46 time: 0.2010 data_time: 0.0020 memory: 867 2023/05/13 11:40:10 - mmengine - INFO - Epoch(val) [20][350/509] eta: 0:00:35 time: 0.2209 data_time: 0.0020 memory: 891 2023/05/13 11:40:21 - mmengine - INFO - Epoch(val) [20][400/509] eta: 0:00:24 time: 0.2180 data_time: 0.0020 memory: 899 2023/05/13 11:40:33 - mmengine - INFO - Epoch(val) [20][450/509] eta: 0:00:13 time: 0.2329 data_time: 0.0021 memory: 911 2023/05/13 11:40:44 - mmengine - INFO - Epoch(val) [20][500/509] eta: 0:00:02 time: 0.2140 data_time: 0.0019 memory: 893 2023/05/13 11:41:02 - 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 | 0.9701 | 0.5234 | 0.7477 | 0.7111 | 0.7080 | 0.7422 | 0.8652 | 0.0397 | 0.9393 | 0.4754 | 0.8156 | 0.0026 | 0.9053 | 0.6484 | 0.8819 | 0.6651 | 0.7421 | 0.6346 | 0.5099 | 0.6594 | 0.9212 | 0.7375 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 11:41:02 - mmengine - INFO - Epoch(val) [20][509/509] car: 0.9701 bicycle: 0.5234 motorcycle: 0.7477 truck: 0.7111 bus: 0.7080 person: 0.7422 bicyclist: 0.8652 motorcyclist: 0.0397 road: 0.9393 parking: 0.4754 sidewalk: 0.8156 other-ground: 0.0026 building: 0.9053 fence: 0.6484 vegetation: 0.8819 trunck: 0.6651 terrian: 0.7421 pole: 0.6346 traffic-sign: 0.5099 miou: 0.6594 acc: 0.9212 acc_cls: 0.7375 data_time: 0.0019 time: 0.2287 2023/05/13 11:42:11 - mmengine - INFO - Epoch(train) [21][ 50/1196] lr: 8.0000e-03 eta: 8:52:56 time: 1.3795 data_time: 0.0043 memory: 5402 grad_norm: 0.1064 loss: 0.2165 loss_sem_seg: 0.2165 2023/05/13 11:43:00 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 11:43:29 - mmengine - INFO - Epoch(train) [21][ 100/1196] lr: 8.0000e-03 eta: 8:51:28 time: 1.5670 data_time: 0.0034 memory: 4385 grad_norm: 0.0980 loss: 0.2141 loss_sem_seg: 0.2141 2023/05/13 11:44:43 - mmengine - INFO - Epoch(train) [21][ 150/1196] lr: 8.0000e-03 eta: 8:49:57 time: 1.4804 data_time: 0.0036 memory: 4752 grad_norm: 0.1111 loss: 0.2121 loss_sem_seg: 0.2121 2023/05/13 11:45:58 - mmengine - INFO - Epoch(train) [21][ 200/1196] lr: 8.0000e-03 eta: 8:48:26 time: 1.4983 data_time: 0.0033 memory: 4635 grad_norm: 0.1034 loss: 0.2110 loss_sem_seg: 0.2110 2023/05/13 11:47:11 - mmengine - INFO - Epoch(train) [21][ 250/1196] lr: 8.0000e-03 eta: 8:46:54 time: 1.4620 data_time: 0.0038 memory: 4580 grad_norm: 0.0946 loss: 0.2137 loss_sem_seg: 0.2137 2023/05/13 11:48:27 - mmengine - INFO - Epoch(train) [21][ 300/1196] lr: 8.0000e-03 eta: 8:45:24 time: 1.5115 data_time: 0.0037 memory: 4396 grad_norm: 0.1039 loss: 0.2231 loss_sem_seg: 0.2231 2023/05/13 11:49:41 - mmengine - INFO - Epoch(train) [21][ 350/1196] lr: 8.0000e-03 eta: 8:43:53 time: 1.4874 data_time: 0.0036 memory: 4818 grad_norm: 0.0971 loss: 0.2213 loss_sem_seg: 0.2213 2023/05/13 11:50:54 - mmengine - INFO - Epoch(train) [21][ 400/1196] lr: 8.0000e-03 eta: 8:42:22 time: 1.4670 data_time: 0.0033 memory: 4784 grad_norm: 0.0934 loss: 0.2148 loss_sem_seg: 0.2148 2023/05/13 11:52:08 - mmengine - INFO - Epoch(train) [21][ 450/1196] lr: 8.0000e-03 eta: 8:40:50 time: 1.4622 data_time: 0.0034 memory: 4722 grad_norm: 0.0932 loss: 0.2007 loss_sem_seg: 0.2007 2023/05/13 11:53:22 - mmengine - INFO - Epoch(train) [21][ 500/1196] lr: 8.0000e-03 eta: 8:39:20 time: 1.4982 data_time: 0.0032 memory: 4769 grad_norm: 0.1065 loss: 0.2148 loss_sem_seg: 0.2148 2023/05/13 11:54:37 - mmengine - INFO - Epoch(train) [21][ 550/1196] lr: 8.0000e-03 eta: 8:37:49 time: 1.4945 data_time: 0.0034 memory: 4683 grad_norm: 0.1127 loss: 0.2236 loss_sem_seg: 0.2236 2023/05/13 11:55:52 - mmengine - INFO - Epoch(train) [21][ 600/1196] lr: 8.0000e-03 eta: 8:36:19 time: 1.4995 data_time: 0.0033 memory: 4929 grad_norm: 0.0900 loss: 0.2085 loss_sem_seg: 0.2085 2023/05/13 11:57:07 - mmengine - INFO - Epoch(train) [21][ 650/1196] lr: 8.0000e-03 eta: 8:34:49 time: 1.4876 data_time: 0.0033 memory: 4720 grad_norm: 0.1131 loss: 0.2197 loss_sem_seg: 0.2197 2023/05/13 11:58:20 - mmengine - INFO - Epoch(train) [21][ 700/1196] lr: 8.0000e-03 eta: 8:33:18 time: 1.4773 data_time: 0.0033 memory: 4689 grad_norm: 0.1027 loss: 0.2131 loss_sem_seg: 0.2131 2023/05/13 11:59:34 - mmengine - INFO - Epoch(train) [21][ 750/1196] lr: 8.0000e-03 eta: 8:31:47 time: 1.4771 data_time: 0.0034 memory: 4624 grad_norm: 0.0974 loss: 0.2054 loss_sem_seg: 0.2054 2023/05/13 12:00:42 - mmengine - INFO - Epoch(train) [21][ 800/1196] lr: 8.0000e-03 eta: 8:30:12 time: 1.3524 data_time: 0.0033 memory: 4855 grad_norm: 0.0976 loss: 0.2048 loss_sem_seg: 0.2048 2023/05/13 12:01:45 - mmengine - INFO - Epoch(train) [21][ 850/1196] lr: 8.0000e-03 eta: 8:28:34 time: 1.2722 data_time: 0.0034 memory: 4493 grad_norm: 0.1017 loss: 0.2092 loss_sem_seg: 0.2092 2023/05/13 12:02:50 - mmengine - INFO - Epoch(train) [21][ 900/1196] lr: 8.0000e-03 eta: 8:26:56 time: 1.2856 data_time: 0.0034 memory: 4823 grad_norm: 0.0976 loss: 0.2119 loss_sem_seg: 0.2119 2023/05/13 12:03:52 - mmengine - INFO - Epoch(train) [21][ 950/1196] lr: 8.0000e-03 eta: 8:25:18 time: 1.2485 data_time: 0.0035 memory: 4799 grad_norm: 0.0939 loss: 0.2058 loss_sem_seg: 0.2058 2023/05/13 12:04:54 - mmengine - INFO - Epoch(train) [21][1000/1196] lr: 8.0000e-03 eta: 8:23:38 time: 1.2300 data_time: 0.0033 memory: 4556 grad_norm: 0.0931 loss: 0.2191 loss_sem_seg: 0.2191 2023/05/13 12:06:06 - mmengine - INFO - Epoch(train) [21][1050/1196] lr: 8.0000e-03 eta: 8:22:07 time: 1.4424 data_time: 0.0033 memory: 5118 grad_norm: 0.0971 loss: 0.2088 loss_sem_seg: 0.2088 2023/05/13 12:06:51 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 12:07:19 - mmengine - INFO - Epoch(train) [21][1100/1196] lr: 8.0000e-03 eta: 8:20:37 time: 1.4730 data_time: 0.0035 memory: 4782 grad_norm: 0.0931 loss: 0.2193 loss_sem_seg: 0.2193 2023/05/13 12:08:33 - mmengine - INFO - Epoch(train) [21][1150/1196] lr: 8.0000e-03 eta: 8:19:06 time: 1.4614 data_time: 0.0035 memory: 5432 grad_norm: 0.0971 loss: 0.2106 loss_sem_seg: 0.2106 2023/05/13 12:09:37 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 12:09:37 - mmengine - INFO - Saving checkpoint at 21 epochs 2023/05/13 12:09:55 - mmengine - INFO - Epoch(val) [21][ 50/509] eta: 0:01:54 time: 0.2486 data_time: 0.0021 memory: 4443 2023/05/13 12:10:06 - mmengine - INFO - Epoch(val) [21][100/509] eta: 0:01:33 time: 0.2070 data_time: 0.0021 memory: 914 2023/05/13 12:10:17 - mmengine - INFO - Epoch(val) [21][150/509] eta: 0:01:20 time: 0.2150 data_time: 0.0020 memory: 915 2023/05/13 12:10:26 - mmengine - INFO - Epoch(val) [21][200/509] eta: 0:01:06 time: 0.1953 data_time: 0.0020 memory: 901 2023/05/13 12:10:38 - mmengine - INFO - Epoch(val) [21][250/509] eta: 0:00:57 time: 0.2403 data_time: 0.0020 memory: 929 2023/05/13 12:10:48 - mmengine - INFO - Epoch(val) [21][300/509] eta: 0:00:45 time: 0.1911 data_time: 0.0021 memory: 867 2023/05/13 12:10:58 - mmengine - INFO - Epoch(val) [21][350/509] eta: 0:00:34 time: 0.1998 data_time: 0.0019 memory: 891 2023/05/13 12:11:09 - mmengine - INFO - Epoch(val) [21][400/509] eta: 0:00:23 time: 0.2178 data_time: 0.0020 memory: 899 2023/05/13 12:11:20 - mmengine - INFO - Epoch(val) [21][450/509] eta: 0:00:12 time: 0.2182 data_time: 0.0020 memory: 911 2023/05/13 12:11:31 - mmengine - INFO - Epoch(val) [21][500/509] eta: 0:00:01 time: 0.2241 data_time: 0.0019 memory: 893 2023/05/13 12:11:49 - 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 | 0.9622 | 0.4750 | 0.7305 | 0.8258 | 0.6224 | 0.7030 | 0.7005 | 0.1255 | 0.9374 | 0.5389 | 0.8022 | 0.0043 | 0.8887 | 0.5683 | 0.8833 | 0.6982 | 0.7376 | 0.6351 | 0.4970 | 0.6493 | 0.9176 | 0.7245 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 12:11:49 - mmengine - INFO - Epoch(val) [21][509/509] car: 0.9622 bicycle: 0.4750 motorcycle: 0.7305 truck: 0.8258 bus: 0.6224 person: 0.7030 bicyclist: 0.7005 motorcyclist: 0.1255 road: 0.9374 parking: 0.5389 sidewalk: 0.8022 other-ground: 0.0043 building: 0.8887 fence: 0.5683 vegetation: 0.8833 trunck: 0.6982 terrian: 0.7376 pole: 0.6351 traffic-sign: 0.4970 miou: 0.6493 acc: 0.9176 acc_cls: 0.7245 data_time: 0.0019 time: 0.2365 2023/05/13 12:12:55 - mmengine - INFO - Epoch(train) [22][ 50/1196] lr: 8.0000e-03 eta: 8:16:05 time: 1.3269 data_time: 0.0042 memory: 4580 grad_norm: 0.1002 loss: 0.2117 loss_sem_seg: 0.2117 2023/05/13 12:14:04 - mmengine - INFO - Epoch(train) [22][ 100/1196] lr: 8.0000e-03 eta: 8:14:31 time: 1.3652 data_time: 0.0035 memory: 4585 grad_norm: 0.1109 loss: 0.2089 loss_sem_seg: 0.2089 2023/05/13 12:15:17 - mmengine - INFO - Epoch(train) [22][ 150/1196] lr: 8.0000e-03 eta: 8:13:02 time: 1.4728 data_time: 0.0036 memory: 5006 grad_norm: 0.0952 loss: 0.2004 loss_sem_seg: 0.2004 2023/05/13 12:16:32 - mmengine - INFO - Epoch(train) [22][ 200/1196] lr: 8.0000e-03 eta: 8:11:32 time: 1.4892 data_time: 0.0036 memory: 4491 grad_norm: 0.1086 loss: 0.2086 loss_sem_seg: 0.2086 2023/05/13 12:17:46 - mmengine - INFO - Epoch(train) [22][ 250/1196] lr: 8.0000e-03 eta: 8:10:03 time: 1.4818 data_time: 0.0033 memory: 4894 grad_norm: 0.1009 loss: 0.2067 loss_sem_seg: 0.2067 2023/05/13 12:19:00 - mmengine - INFO - Epoch(train) [22][ 300/1196] lr: 8.0000e-03 eta: 8:08:34 time: 1.4850 data_time: 0.0033 memory: 4943 grad_norm: 0.0994 loss: 0.2109 loss_sem_seg: 0.2109 2023/05/13 12:20:12 - mmengine - INFO - Epoch(train) [22][ 350/1196] lr: 8.0000e-03 eta: 8:07:03 time: 1.4410 data_time: 0.0034 memory: 5108 grad_norm: 0.1265 loss: 0.2192 loss_sem_seg: 0.2192 2023/05/13 12:21:25 - mmengine - INFO - Epoch(train) [22][ 400/1196] lr: 8.0000e-03 eta: 8:05:33 time: 1.4636 data_time: 0.0034 memory: 4645 grad_norm: 0.1005 loss: 0.1997 loss_sem_seg: 0.1997 2023/05/13 12:22:41 - mmengine - INFO - Epoch(train) [22][ 450/1196] lr: 8.0000e-03 eta: 8:04:05 time: 1.5123 data_time: 0.0033 memory: 4679 grad_norm: 0.0937 loss: 0.2153 loss_sem_seg: 0.2153 2023/05/13 12:23:55 - mmengine - INFO - Epoch(train) [22][ 500/1196] lr: 8.0000e-03 eta: 8:02:36 time: 1.4838 data_time: 0.0035 memory: 4821 grad_norm: 0.0918 loss: 0.2116 loss_sem_seg: 0.2116 2023/05/13 12:25:10 - mmengine - INFO - Epoch(train) [22][ 550/1196] lr: 8.0000e-03 eta: 8:01:07 time: 1.4944 data_time: 0.0034 memory: 4574 grad_norm: 0.0971 loss: 0.2125 loss_sem_seg: 0.2125 2023/05/13 12:26:23 - mmengine - INFO - Epoch(train) [22][ 600/1196] lr: 8.0000e-03 eta: 7:59:38 time: 1.4693 data_time: 0.0033 memory: 4805 grad_norm: 0.0962 loss: 0.2061 loss_sem_seg: 0.2061 2023/05/13 12:27:37 - mmengine - INFO - Epoch(train) [22][ 650/1196] lr: 8.0000e-03 eta: 7:58:08 time: 1.4684 data_time: 0.0035 memory: 4682 grad_norm: 0.0968 loss: 0.2229 loss_sem_seg: 0.2229 2023/05/13 12:28:52 - mmengine - INFO - Epoch(train) [22][ 700/1196] lr: 8.0000e-03 eta: 7:56:40 time: 1.4986 data_time: 0.0033 memory: 4922 grad_norm: 0.0938 loss: 0.2041 loss_sem_seg: 0.2041 2023/05/13 12:30:05 - mmengine - INFO - Epoch(train) [22][ 750/1196] lr: 8.0000e-03 eta: 7:55:11 time: 1.4714 data_time: 0.0034 memory: 5178 grad_norm: 0.0941 loss: 0.2070 loss_sem_seg: 0.2070 2023/05/13 12:31:17 - mmengine - INFO - Epoch(train) [22][ 800/1196] lr: 8.0000e-03 eta: 7:53:41 time: 1.4440 data_time: 0.0035 memory: 4518 grad_norm: 0.0974 loss: 0.1996 loss_sem_seg: 0.1996 2023/05/13 12:32:32 - mmengine - INFO - Epoch(train) [22][ 850/1196] lr: 8.0000e-03 eta: 7:52:12 time: 1.4879 data_time: 0.0033 memory: 4554 grad_norm: 0.0895 loss: 0.2018 loss_sem_seg: 0.2018 2023/05/13 12:33:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 12:33:47 - mmengine - INFO - Epoch(train) [22][ 900/1196] lr: 8.0000e-03 eta: 7:50:45 time: 1.5125 data_time: 0.0036 memory: 4652 grad_norm: 0.0861 loss: 0.1994 loss_sem_seg: 0.1994 2023/05/13 12:35:03 - mmengine - INFO - Epoch(train) [22][ 950/1196] lr: 8.0000e-03 eta: 7:49:17 time: 1.5021 data_time: 0.0035 memory: 4546 grad_norm: 0.0969 loss: 0.2051 loss_sem_seg: 0.2051 2023/05/13 12:36:16 - mmengine - INFO - Epoch(train) [22][1000/1196] lr: 8.0000e-03 eta: 7:47:48 time: 1.4697 data_time: 0.0034 memory: 5139 grad_norm: 0.0997 loss: 0.2126 loss_sem_seg: 0.2126 2023/05/13 12:37:18 - mmengine - INFO - Epoch(train) [22][1050/1196] lr: 8.0000e-03 eta: 7:46:12 time: 1.2449 data_time: 0.0034 memory: 4890 grad_norm: 0.0997 loss: 0.2022 loss_sem_seg: 0.2022 2023/05/13 12:38:22 - mmengine - INFO - Epoch(train) [22][1100/1196] lr: 8.0000e-03 eta: 7:44:37 time: 1.2729 data_time: 0.0033 memory: 4661 grad_norm: 0.0961 loss: 0.2060 loss_sem_seg: 0.2060 2023/05/13 12:39:25 - mmengine - INFO - Epoch(train) [22][1150/1196] lr: 8.0000e-03 eta: 7:43:01 time: 1.2559 data_time: 0.0033 memory: 4459 grad_norm: 0.0902 loss: 0.2041 loss_sem_seg: 0.2041 2023/05/13 12:40:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 12:40:23 - mmengine - INFO - Saving checkpoint at 22 epochs 2023/05/13 12:40:41 - mmengine - INFO - Epoch(val) [22][ 50/509] eta: 0:01:45 time: 0.2293 data_time: 0.0021 memory: 4695 2023/05/13 12:40:52 - mmengine - INFO - Epoch(val) [22][100/509] eta: 0:01:29 time: 0.2087 data_time: 0.0020 memory: 914 2023/05/13 12:41:02 - mmengine - INFO - Epoch(val) [22][150/509] eta: 0:01:16 time: 0.1996 data_time: 0.0020 memory: 915 2023/05/13 12:41:12 - mmengine - INFO - Epoch(val) [22][200/509] eta: 0:01:05 time: 0.2109 data_time: 0.0020 memory: 901 2023/05/13 12:41:22 - mmengine - INFO - Epoch(val) [22][250/509] eta: 0:00:53 time: 0.1932 data_time: 0.0020 memory: 929 2023/05/13 12:41:30 - mmengine - INFO - Epoch(val) [22][300/509] eta: 0:00:42 time: 0.1649 data_time: 0.0020 memory: 867 2023/05/13 12:41:39 - mmengine - INFO - Epoch(val) [22][350/509] eta: 0:00:31 time: 0.1782 data_time: 0.0020 memory: 891 2023/05/13 12:41:46 - mmengine - INFO - Epoch(val) [22][400/509] eta: 0:00:20 time: 0.1402 data_time: 0.0020 memory: 899 2023/05/13 12:41:53 - mmengine - INFO - Epoch(val) [22][450/509] eta: 0:00:10 time: 0.1428 data_time: 0.0020 memory: 911 2023/05/13 12:42:00 - mmengine - INFO - Epoch(val) [22][500/509] eta: 0:00:01 time: 0.1390 data_time: 0.0020 memory: 893 2023/05/13 12:42:18 - 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 | 0.9637 | 0.4041 | 0.7040 | 0.7667 | 0.6903 | 0.7641 | 0.8797 | 0.0145 | 0.9405 | 0.5033 | 0.8157 | 0.0114 | 0.9038 | 0.6155 | 0.8713 | 0.7014 | 0.7250 | 0.6462 | 0.4899 | 0.6532 | 0.9173 | 0.7288 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 12:42:18 - mmengine - INFO - Epoch(val) [22][509/509] car: 0.9637 bicycle: 0.4041 motorcycle: 0.7040 truck: 0.7667 bus: 0.6903 person: 0.7641 bicyclist: 0.8797 motorcyclist: 0.0145 road: 0.9405 parking: 0.5033 sidewalk: 0.8157 other-ground: 0.0114 building: 0.9038 fence: 0.6155 vegetation: 0.8713 trunck: 0.7014 terrian: 0.7250 pole: 0.6462 traffic-sign: 0.4899 miou: 0.6532 acc: 0.9173 acc_cls: 0.7288 data_time: 0.0020 time: 0.1429 2023/05/13 12:43:16 - mmengine - INFO - Epoch(train) [23][ 50/1196] lr: 8.0000e-03 eta: 7:39:55 time: 1.1612 data_time: 0.0041 memory: 4869 grad_norm: 0.1010 loss: 0.2044 loss_sem_seg: 0.2044 2023/05/13 12:44:12 - mmengine - INFO - Epoch(train) [23][ 100/1196] lr: 8.0000e-03 eta: 7:38:16 time: 1.1233 data_time: 0.0034 memory: 5013 grad_norm: 0.1066 loss: 0.2218 loss_sem_seg: 0.2218 2023/05/13 12:45:09 - mmengine - INFO - Epoch(train) [23][ 150/1196] lr: 8.0000e-03 eta: 7:36:37 time: 1.1366 data_time: 0.0033 memory: 4404 grad_norm: 0.1271 loss: 0.2429 loss_sem_seg: 0.2429 2023/05/13 12:46:14 - mmengine - INFO - Epoch(train) [23][ 200/1196] lr: 8.0000e-03 eta: 7:35:04 time: 1.3043 data_time: 0.0033 memory: 4665 grad_norm: 0.1004 loss: 0.2086 loss_sem_seg: 0.2086 2023/05/13 12:47:29 - mmengine - INFO - Epoch(train) [23][ 250/1196] lr: 8.0000e-03 eta: 7:33:37 time: 1.5026 data_time: 0.0033 memory: 5126 grad_norm: 0.0916 loss: 0.2106 loss_sem_seg: 0.2106 2023/05/13 12:48:44 - mmengine - INFO - Epoch(train) [23][ 300/1196] lr: 8.0000e-03 eta: 7:32:10 time: 1.4993 data_time: 0.0034 memory: 4693 grad_norm: 0.0931 loss: 0.2082 loss_sem_seg: 0.2082 2023/05/13 12:49:59 - mmengine - INFO - Epoch(train) [23][ 350/1196] lr: 8.0000e-03 eta: 7:30:42 time: 1.4890 data_time: 0.0033 memory: 5272 grad_norm: 0.0944 loss: 0.2079 loss_sem_seg: 0.2079 2023/05/13 12:51:13 - mmengine - INFO - Epoch(train) [23][ 400/1196] lr: 8.0000e-03 eta: 7:29:15 time: 1.4966 data_time: 0.0034 memory: 4947 grad_norm: 0.0934 loss: 0.1968 loss_sem_seg: 0.1968 2023/05/13 12:52:28 - mmengine - INFO - Epoch(train) [23][ 450/1196] lr: 8.0000e-03 eta: 7:27:48 time: 1.4867 data_time: 0.0035 memory: 4500 grad_norm: 0.0946 loss: 0.2017 loss_sem_seg: 0.2017 2023/05/13 12:53:41 - mmengine - INFO - Epoch(train) [23][ 500/1196] lr: 8.0000e-03 eta: 7:26:19 time: 1.4587 data_time: 0.0033 memory: 4447 grad_norm: 0.0837 loss: 0.2096 loss_sem_seg: 0.2096 2023/05/13 12:54:54 - mmengine - INFO - Epoch(train) [23][ 550/1196] lr: 8.0000e-03 eta: 7:24:52 time: 1.4708 data_time: 0.0033 memory: 4992 grad_norm: 0.0964 loss: 0.2113 loss_sem_seg: 0.2113 2023/05/13 12:56:09 - mmengine - INFO - Epoch(train) [23][ 600/1196] lr: 8.0000e-03 eta: 7:23:24 time: 1.4917 data_time: 0.0033 memory: 4609 grad_norm: 0.1018 loss: 0.2058 loss_sem_seg: 0.2058 2023/05/13 12:57:23 - mmengine - INFO - Epoch(train) [23][ 650/1196] lr: 8.0000e-03 eta: 7:21:57 time: 1.4808 data_time: 0.0033 memory: 4933 grad_norm: 0.0947 loss: 0.1936 loss_sem_seg: 0.1936 2023/05/13 12:58:19 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 12:58:37 - mmengine - INFO - Epoch(train) [23][ 700/1196] lr: 8.0000e-03 eta: 7:20:30 time: 1.4845 data_time: 0.0034 memory: 4552 grad_norm: 0.1022 loss: 0.1962 loss_sem_seg: 0.1962 2023/05/13 12:59:51 - mmengine - INFO - Epoch(train) [23][ 750/1196] lr: 8.0000e-03 eta: 7:19:02 time: 1.4711 data_time: 0.0033 memory: 4771 grad_norm: 0.0927 loss: 0.2031 loss_sem_seg: 0.2031 2023/05/13 13:01:03 - mmengine - INFO - Epoch(train) [23][ 800/1196] lr: 8.0000e-03 eta: 7:17:34 time: 1.4477 data_time: 0.0035 memory: 4798 grad_norm: 0.0923 loss: 0.2004 loss_sem_seg: 0.2004 2023/05/13 13:02:17 - mmengine - INFO - Epoch(train) [23][ 850/1196] lr: 8.0000e-03 eta: 7:16:07 time: 1.4815 data_time: 0.0033 memory: 4970 grad_norm: 0.0978 loss: 0.2001 loss_sem_seg: 0.2001 2023/05/13 13:03:31 - mmengine - INFO - Epoch(train) [23][ 900/1196] lr: 8.0000e-03 eta: 7:14:40 time: 1.4803 data_time: 0.0034 memory: 4419 grad_norm: 0.0952 loss: 0.2103 loss_sem_seg: 0.2103 2023/05/13 13:04:46 - mmengine - INFO - Epoch(train) [23][ 950/1196] lr: 8.0000e-03 eta: 7:13:13 time: 1.4936 data_time: 0.0034 memory: 4732 grad_norm: 0.0997 loss: 0.2198 loss_sem_seg: 0.2198 2023/05/13 13:06:00 - mmengine - INFO - Epoch(train) [23][1000/1196] lr: 8.0000e-03 eta: 7:11:46 time: 1.4882 data_time: 0.0037 memory: 5382 grad_norm: 0.0921 loss: 0.1985 loss_sem_seg: 0.1985 2023/05/13 13:07:15 - mmengine - INFO - Epoch(train) [23][1050/1196] lr: 8.0000e-03 eta: 7:10:19 time: 1.4873 data_time: 0.0033 memory: 4600 grad_norm: 0.0990 loss: 0.1972 loss_sem_seg: 0.1972 2023/05/13 13:08:28 - mmengine - INFO - Epoch(train) [23][1100/1196] lr: 8.0000e-03 eta: 7:08:52 time: 1.4683 data_time: 0.0033 memory: 4386 grad_norm: 0.0918 loss: 0.2024 loss_sem_seg: 0.2024 2023/05/13 13:09:43 - mmengine - INFO - Epoch(train) [23][1150/1196] lr: 8.0000e-03 eta: 7:07:25 time: 1.4911 data_time: 0.0033 memory: 4610 grad_norm: 0.1101 loss: 0.2006 loss_sem_seg: 0.2006 2023/05/13 13:10:52 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 13:10:52 - mmengine - INFO - Saving checkpoint at 23 epochs 2023/05/13 13:11:13 - mmengine - INFO - Epoch(val) [23][ 50/509] eta: 0:02:14 time: 0.2940 data_time: 0.0021 memory: 4502 2023/05/13 13:11:25 - mmengine - INFO - Epoch(val) [23][100/509] eta: 0:01:48 time: 0.2349 data_time: 0.0019 memory: 914 2023/05/13 13:11:37 - mmengine - INFO - Epoch(val) [23][150/509] eta: 0:01:31 time: 0.2325 data_time: 0.0019 memory: 915 2023/05/13 13:11:50 - mmengine - INFO - Epoch(val) [23][200/509] eta: 0:01:19 time: 0.2624 data_time: 0.0020 memory: 901 2023/05/13 13:12:04 - mmengine - INFO - Epoch(val) [23][250/509] eta: 0:01:07 time: 0.2790 data_time: 0.0021 memory: 929 2023/05/13 13:12:15 - mmengine - INFO - Epoch(val) [23][300/509] eta: 0:00:52 time: 0.2120 data_time: 0.0020 memory: 867 2023/05/13 13:12:26 - mmengine - INFO - Epoch(val) [23][350/509] eta: 0:00:39 time: 0.2387 data_time: 0.0020 memory: 891 2023/05/13 13:12:40 - mmengine - INFO - Epoch(val) [23][400/509] eta: 0:00:27 time: 0.2678 data_time: 0.0021 memory: 899 2023/05/13 13:12:52 - mmengine - INFO - Epoch(val) [23][450/509] eta: 0:00:14 time: 0.2441 data_time: 0.0020 memory: 911 2023/05/13 13:13:04 - mmengine - INFO - Epoch(val) [23][500/509] eta: 0:00:02 time: 0.2358 data_time: 0.0019 memory: 893 2023/05/13 13:13:23 - 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 | 0.9691 | 0.4483 | 0.7374 | 0.8092 | 0.7220 | 0.7054 | 0.8741 | 0.0684 | 0.9375 | 0.4619 | 0.8038 | 0.0133 | 0.8861 | 0.5274 | 0.8971 | 0.6159 | 0.7800 | 0.6458 | 0.5050 | 0.6530 | 0.9222 | 0.7139 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 13:13:23 - mmengine - INFO - Epoch(val) [23][509/509] car: 0.9691 bicycle: 0.4483 motorcycle: 0.7374 truck: 0.8092 bus: 0.7220 person: 0.7054 bicyclist: 0.8741 motorcyclist: 0.0684 road: 0.9375 parking: 0.4619 sidewalk: 0.8038 other-ground: 0.0133 building: 0.8861 fence: 0.5274 vegetation: 0.8971 trunck: 0.6159 terrian: 0.7800 pole: 0.6458 traffic-sign: 0.5050 miou: 0.6530 acc: 0.9222 acc_cls: 0.7139 data_time: 0.0019 time: 0.2524 2023/05/13 13:14:30 - mmengine - INFO - Epoch(train) [24][ 50/1196] lr: 8.0000e-03 eta: 7:04:36 time: 1.3412 data_time: 0.0047 memory: 4733 grad_norm: 0.1049 loss: 0.2182 loss_sem_seg: 0.2182 2023/05/13 13:15:40 - mmengine - INFO - Epoch(train) [24][ 100/1196] lr: 8.0000e-03 eta: 7:03:06 time: 1.3947 data_time: 0.0034 memory: 4991 grad_norm: 0.1004 loss: 0.2096 loss_sem_seg: 0.2096 2023/05/13 13:16:48 - mmengine - INFO - Epoch(train) [24][ 150/1196] lr: 8.0000e-03 eta: 7:01:37 time: 1.3781 data_time: 0.0034 memory: 5011 grad_norm: 0.0987 loss: 0.2102 loss_sem_seg: 0.2102 2023/05/13 13:17:56 - mmengine - INFO - Epoch(train) [24][ 200/1196] lr: 8.0000e-03 eta: 7:00:07 time: 1.3477 data_time: 0.0033 memory: 4720 grad_norm: 0.1059 loss: 0.2128 loss_sem_seg: 0.2128 2023/05/13 13:19:04 - mmengine - INFO - Epoch(train) [24][ 250/1196] lr: 8.0000e-03 eta: 6:58:37 time: 1.3612 data_time: 0.0032 memory: 4525 grad_norm: 0.1018 loss: 0.2098 loss_sem_seg: 0.2098 2023/05/13 13:20:20 - mmengine - INFO - Epoch(train) [24][ 300/1196] lr: 8.0000e-03 eta: 6:57:12 time: 1.5301 data_time: 0.0033 memory: 4498 grad_norm: 0.1048 loss: 0.2233 loss_sem_seg: 0.2233 2023/05/13 13:21:38 - mmengine - INFO - Epoch(train) [24][ 350/1196] lr: 8.0000e-03 eta: 6:55:47 time: 1.5543 data_time: 0.0033 memory: 4392 grad_norm: 0.1070 loss: 0.2131 loss_sem_seg: 0.2131 2023/05/13 13:22:53 - mmengine - INFO - Epoch(train) [24][ 400/1196] lr: 8.0000e-03 eta: 6:54:21 time: 1.4962 data_time: 0.0033 memory: 4724 grad_norm: 0.1060 loss: 0.2251 loss_sem_seg: 0.2251 2023/05/13 13:24:09 - mmengine - INFO - Epoch(train) [24][ 450/1196] lr: 8.0000e-03 eta: 6:52:55 time: 1.5103 data_time: 0.0034 memory: 4966 grad_norm: 0.1015 loss: 0.2124 loss_sem_seg: 0.2124 2023/05/13 13:25:04 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 13:25:15 - mmengine - INFO - Epoch(train) [24][ 500/1196] lr: 8.0000e-03 eta: 6:51:25 time: 1.3212 data_time: 0.0034 memory: 4893 grad_norm: 0.0933 loss: 0.2076 loss_sem_seg: 0.2076 2023/05/13 13:26:20 - mmengine - INFO - Epoch(train) [24][ 550/1196] lr: 8.0000e-03 eta: 6:49:54 time: 1.3056 data_time: 0.0033 memory: 4686 grad_norm: 0.0900 loss: 0.1879 loss_sem_seg: 0.1879 2023/05/13 13:27:26 - mmengine - INFO - Epoch(train) [24][ 600/1196] lr: 8.0000e-03 eta: 6:48:23 time: 1.3220 data_time: 0.0033 memory: 4993 grad_norm: 0.0832 loss: 0.2118 loss_sem_seg: 0.2118 2023/05/13 13:28:29 - mmengine - INFO - Epoch(train) [24][ 650/1196] lr: 8.0000e-03 eta: 6:46:52 time: 1.2659 data_time: 0.0033 memory: 4731 grad_norm: 0.0913 loss: 0.2058 loss_sem_seg: 0.2058 2023/05/13 13:29:33 - mmengine - INFO - Epoch(train) [24][ 700/1196] lr: 8.0000e-03 eta: 6:45:20 time: 1.2793 data_time: 0.0033 memory: 4676 grad_norm: 0.1016 loss: 0.2141 loss_sem_seg: 0.2141 2023/05/13 13:30:49 - mmengine - INFO - Epoch(train) [24][ 750/1196] lr: 8.0000e-03 eta: 6:43:55 time: 1.5059 data_time: 0.0033 memory: 4417 grad_norm: 0.0972 loss: 0.2083 loss_sem_seg: 0.2083 2023/05/13 13:32:04 - mmengine - INFO - Epoch(train) [24][ 800/1196] lr: 8.0000e-03 eta: 6:42:29 time: 1.5010 data_time: 0.0036 memory: 4643 grad_norm: 0.1046 loss: 0.2090 loss_sem_seg: 0.2090 2023/05/13 13:33:19 - mmengine - INFO - Epoch(train) [24][ 850/1196] lr: 8.0000e-03 eta: 6:41:04 time: 1.5161 data_time: 0.0034 memory: 4245 grad_norm: 0.0939 loss: 0.2003 loss_sem_seg: 0.2003 2023/05/13 13:34:34 - mmengine - INFO - Epoch(train) [24][ 900/1196] lr: 8.0000e-03 eta: 6:39:39 time: 1.4848 data_time: 0.0034 memory: 5046 grad_norm: 0.0984 loss: 0.2149 loss_sem_seg: 0.2149 2023/05/13 13:35:49 - mmengine - INFO - Epoch(train) [24][ 950/1196] lr: 8.0000e-03 eta: 6:38:13 time: 1.5107 data_time: 0.0033 memory: 4798 grad_norm: 0.0971 loss: 0.2088 loss_sem_seg: 0.2088 2023/05/13 13:37:06 - mmengine - INFO - Epoch(train) [24][1000/1196] lr: 8.0000e-03 eta: 6:36:49 time: 1.5350 data_time: 0.0034 memory: 4941 grad_norm: 0.0915 loss: 0.1965 loss_sem_seg: 0.1965 2023/05/13 13:38:22 - mmengine - INFO - Epoch(train) [24][1050/1196] lr: 8.0000e-03 eta: 6:35:24 time: 1.5219 data_time: 0.0036 memory: 4772 grad_norm: 0.0916 loss: 0.2099 loss_sem_seg: 0.2099 2023/05/13 13:39:39 - mmengine - INFO - Epoch(train) [24][1100/1196] lr: 8.0000e-03 eta: 6:34:00 time: 1.5310 data_time: 0.0034 memory: 4831 grad_norm: 0.1076 loss: 0.2190 loss_sem_seg: 0.2190 2023/05/13 13:40:55 - mmengine - INFO - Epoch(train) [24][1150/1196] lr: 8.0000e-03 eta: 6:32:35 time: 1.5258 data_time: 0.0034 memory: 5048 grad_norm: 0.0980 loss: 0.2112 loss_sem_seg: 0.2112 2023/05/13 13:42:06 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 13:42:06 - mmengine - INFO - Saving checkpoint at 24 epochs 2023/05/13 13:42:27 - mmengine - INFO - Epoch(val) [24][ 50/509] eta: 0:02:15 time: 0.2956 data_time: 0.0021 memory: 4646 2023/05/13 13:42:39 - mmengine - INFO - Epoch(val) [24][100/509] eta: 0:01:51 time: 0.2488 data_time: 0.0020 memory: 914 2023/05/13 13:42:52 - mmengine - INFO - Epoch(val) [24][150/509] eta: 0:01:34 time: 0.2416 data_time: 0.0021 memory: 915 2023/05/13 13:43:04 - mmengine - INFO - Epoch(val) [24][200/509] eta: 0:01:20 time: 0.2554 data_time: 0.0020 memory: 901 2023/05/13 13:43:18 - mmengine - INFO - Epoch(val) [24][250/509] eta: 0:01:08 time: 0.2736 data_time: 0.0020 memory: 929 2023/05/13 13:43:28 - mmengine - INFO - Epoch(val) [24][300/509] eta: 0:00:53 time: 0.2083 data_time: 0.0020 memory: 867 2023/05/13 13:43:41 - mmengine - INFO - Epoch(val) [24][350/509] eta: 0:00:40 time: 0.2420 data_time: 0.0020 memory: 891 2023/05/13 13:43:54 - mmengine - INFO - Epoch(val) [24][400/509] eta: 0:00:27 time: 0.2657 data_time: 0.0021 memory: 899 2023/05/13 13:44:06 - mmengine - INFO - Epoch(val) [24][450/509] eta: 0:00:14 time: 0.2484 data_time: 0.0019 memory: 911 2023/05/13 13:44:19 - mmengine - INFO - Epoch(val) [24][500/509] eta: 0:00:02 time: 0.2545 data_time: 0.0018 memory: 893 2023/05/13 13:44:38 - 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 | 0.9524 | 0.5229 | 0.7244 | 0.6602 | 0.4703 | 0.7181 | 0.8698 | 0.0122 | 0.9454 | 0.5870 | 0.8276 | 0.0070 | 0.9015 | 0.5725 | 0.8749 | 0.6980 | 0.7371 | 0.6483 | 0.4938 | 0.6433 | 0.9190 | 0.7258 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 13:44:38 - mmengine - INFO - Epoch(val) [24][509/509] car: 0.9524 bicycle: 0.5229 motorcycle: 0.7244 truck: 0.6602 bus: 0.4703 person: 0.7181 bicyclist: 0.8698 motorcyclist: 0.0122 road: 0.9454 parking: 0.5870 sidewalk: 0.8276 other-ground: 0.0070 building: 0.9015 fence: 0.5725 vegetation: 0.8749 trunck: 0.6980 terrian: 0.7371 pole: 0.6483 traffic-sign: 0.4938 miou: 0.6433 acc: 0.9190 acc_cls: 0.7258 data_time: 0.0018 time: 0.2728 2023/05/13 13:45:54 - mmengine - INFO - Epoch(train) [25][ 50/1196] lr: 8.0000e-04 eta: 6:29:53 time: 1.5160 data_time: 0.0041 memory: 4892 grad_norm: 0.0733 loss: 0.1960 loss_sem_seg: 0.1960 2023/05/13 13:47:07 - mmengine - INFO - Epoch(train) [25][ 100/1196] lr: 8.0000e-04 eta: 6:28:27 time: 1.4707 data_time: 0.0033 memory: 4481 grad_norm: 0.0654 loss: 0.1957 loss_sem_seg: 0.1957 2023/05/13 13:48:18 - mmengine - INFO - Epoch(train) [25][ 150/1196] lr: 8.0000e-04 eta: 6:27:00 time: 1.4178 data_time: 0.0034 memory: 4665 grad_norm: 0.0633 loss: 0.1942 loss_sem_seg: 0.1942 2023/05/13 13:49:28 - mmengine - INFO - Epoch(train) [25][ 200/1196] lr: 8.0000e-04 eta: 6:25:32 time: 1.3892 data_time: 0.0033 memory: 4626 grad_norm: 0.0636 loss: 0.1825 loss_sem_seg: 0.1825 2023/05/13 13:50:36 - mmengine - INFO - Epoch(train) [25][ 250/1196] lr: 8.0000e-04 eta: 6:24:04 time: 1.3668 data_time: 0.0035 memory: 4627 grad_norm: 0.0642 loss: 0.1756 loss_sem_seg: 0.1756 2023/05/13 13:51:39 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 13:51:45 - mmengine - INFO - Epoch(train) [25][ 300/1196] lr: 8.0000e-04 eta: 6:22:36 time: 1.3799 data_time: 0.0034 memory: 4722 grad_norm: 0.0620 loss: 0.1699 loss_sem_seg: 0.1699 2023/05/13 13:52:55 - mmengine - INFO - Epoch(train) [25][ 350/1196] lr: 8.0000e-04 eta: 6:21:09 time: 1.3997 data_time: 0.0033 memory: 4407 grad_norm: 0.0643 loss: 0.1728 loss_sem_seg: 0.1728 2023/05/13 13:54:15 - mmengine - INFO - Epoch(train) [25][ 400/1196] lr: 8.0000e-04 eta: 6:19:47 time: 1.6116 data_time: 0.0033 memory: 4610 grad_norm: 0.0609 loss: 0.1776 loss_sem_seg: 0.1776 2023/05/13 13:55:29 - mmengine - INFO - Epoch(train) [25][ 450/1196] lr: 8.0000e-04 eta: 6:18:21 time: 1.4621 data_time: 0.0034 memory: 4742 grad_norm: 0.0593 loss: 0.1707 loss_sem_seg: 0.1707 2023/05/13 13:56:44 - mmengine - INFO - Epoch(train) [25][ 500/1196] lr: 8.0000e-04 eta: 6:16:56 time: 1.5062 data_time: 0.0034 memory: 4554 grad_norm: 0.0636 loss: 0.1737 loss_sem_seg: 0.1737 2023/05/13 13:58:01 - mmengine - INFO - Epoch(train) [25][ 550/1196] lr: 8.0000e-04 eta: 6:15:33 time: 1.5473 data_time: 0.0034 memory: 4697 grad_norm: 0.0618 loss: 0.1797 loss_sem_seg: 0.1797 2023/05/13 13:59:15 - mmengine - INFO - Epoch(train) [25][ 600/1196] lr: 8.0000e-04 eta: 6:14:07 time: 1.4832 data_time: 0.0035 memory: 5010 grad_norm: 0.0623 loss: 0.1808 loss_sem_seg: 0.1808 2023/05/13 14:00:33 - mmengine - INFO - Epoch(train) [25][ 650/1196] lr: 8.0000e-04 eta: 6:12:44 time: 1.5439 data_time: 0.0034 memory: 4586 grad_norm: 0.0605 loss: 0.1650 loss_sem_seg: 0.1650 2023/05/13 14:01:48 - mmengine - INFO - Epoch(train) [25][ 700/1196] lr: 8.0000e-04 eta: 6:11:19 time: 1.5065 data_time: 0.0037 memory: 4846 grad_norm: 0.0602 loss: 0.1742 loss_sem_seg: 0.1742 2023/05/13 14:03:06 - mmengine - INFO - Epoch(train) [25][ 750/1196] lr: 8.0000e-04 eta: 6:09:56 time: 1.5668 data_time: 0.0035 memory: 4770 grad_norm: 0.0592 loss: 0.1816 loss_sem_seg: 0.1816 2023/05/13 14:04:23 - mmengine - INFO - Epoch(train) [25][ 800/1196] lr: 8.0000e-04 eta: 6:08:32 time: 1.5296 data_time: 0.0033 memory: 4659 grad_norm: 0.0608 loss: 0.1705 loss_sem_seg: 0.1705 2023/05/13 14:05:39 - mmengine - INFO - Epoch(train) [25][ 850/1196] lr: 8.0000e-04 eta: 6:07:08 time: 1.5154 data_time: 0.0033 memory: 4843 grad_norm: 0.0607 loss: 0.1753 loss_sem_seg: 0.1753 2023/05/13 14:06:53 - mmengine - INFO - Epoch(train) [25][ 900/1196] lr: 8.0000e-04 eta: 6:05:43 time: 1.4851 data_time: 0.0034 memory: 5338 grad_norm: 0.0585 loss: 0.1712 loss_sem_seg: 0.1712 2023/05/13 14:08:07 - mmengine - INFO - Epoch(train) [25][ 950/1196] lr: 8.0000e-04 eta: 6:04:18 time: 1.4929 data_time: 0.0036 memory: 4644 grad_norm: 0.0621 loss: 0.1700 loss_sem_seg: 0.1700 2023/05/13 14:09:17 - mmengine - INFO - Epoch(train) [25][1000/1196] lr: 8.0000e-04 eta: 6:02:52 time: 1.3967 data_time: 0.0033 memory: 4967 grad_norm: 0.0592 loss: 0.1703 loss_sem_seg: 0.1703 2023/05/13 14:10:23 - mmengine - INFO - Epoch(train) [25][1050/1196] lr: 8.0000e-04 eta: 6:01:23 time: 1.3099 data_time: 0.0033 memory: 4784 grad_norm: 0.0575 loss: 0.1756 loss_sem_seg: 0.1756 2023/05/13 14:11:29 - mmengine - INFO - Epoch(train) [25][1100/1196] lr: 8.0000e-04 eta: 5:59:54 time: 1.3192 data_time: 0.0034 memory: 4914 grad_norm: 0.0610 loss: 0.1691 loss_sem_seg: 0.1691 2023/05/13 14:12:35 - mmengine - INFO - Epoch(train) [25][1150/1196] lr: 8.0000e-04 eta: 5:58:26 time: 1.3323 data_time: 0.0034 memory: 4697 grad_norm: 0.0592 loss: 0.1657 loss_sem_seg: 0.1657 2023/05/13 14:13:36 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 14:13:36 - mmengine - INFO - Saving checkpoint at 25 epochs 2023/05/13 14:13:54 - mmengine - INFO - Epoch(val) [25][ 50/509] eta: 0:01:49 time: 0.2392 data_time: 0.0021 memory: 4411 2023/05/13 14:14:05 - mmengine - INFO - Epoch(val) [25][100/509] eta: 0:01:34 time: 0.2232 data_time: 0.0020 memory: 914 2023/05/13 14:14:16 - mmengine - INFO - Epoch(val) [25][150/509] eta: 0:01:19 time: 0.2036 data_time: 0.0020 memory: 915 2023/05/13 14:14:27 - mmengine - INFO - Epoch(val) [25][200/509] eta: 0:01:08 time: 0.2262 data_time: 0.0020 memory: 901 2023/05/13 14:14:41 - mmengine - INFO - Epoch(val) [25][250/509] eta: 0:01:00 time: 0.2784 data_time: 0.0020 memory: 929 2023/05/13 14:14:51 - mmengine - INFO - Epoch(val) [25][300/509] eta: 0:00:47 time: 0.2069 data_time: 0.0021 memory: 867 2023/05/13 14:15:03 - mmengine - INFO - Epoch(val) [25][350/509] eta: 0:00:36 time: 0.2433 data_time: 0.0021 memory: 891 2023/05/13 14:15:17 - mmengine - INFO - Epoch(val) [25][400/509] eta: 0:00:25 time: 0.2627 data_time: 0.0021 memory: 899 2023/05/13 14:15:29 - mmengine - INFO - Epoch(val) [25][450/509] eta: 0:00:13 time: 0.2519 data_time: 0.0020 memory: 911 2023/05/13 14:15:42 - mmengine - INFO - Epoch(val) [25][500/509] eta: 0:00:02 time: 0.2578 data_time: 0.0019 memory: 893 2023/05/13 14:16:00 - 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 | 0.9672 | 0.5227 | 0.8076 | 0.8419 | 0.6616 | 0.7893 | 0.8947 | 0.0369 | 0.9495 | 0.5538 | 0.8322 | 0.0111 | 0.9189 | 0.6804 | 0.8758 | 0.6753 | 0.7267 | 0.6653 | 0.5231 | 0.6807 | 0.9235 | 0.7456 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 14:16:00 - mmengine - INFO - Epoch(val) [25][509/509] car: 0.9672 bicycle: 0.5227 motorcycle: 0.8076 truck: 0.8419 bus: 0.6616 person: 0.7893 bicyclist: 0.8947 motorcyclist: 0.0369 road: 0.9495 parking: 0.5538 sidewalk: 0.8322 other-ground: 0.0111 building: 0.9189 fence: 0.6804 vegetation: 0.8758 trunck: 0.6753 terrian: 0.7267 pole: 0.6653 traffic-sign: 0.5231 miou: 0.6807 acc: 0.9235 acc_cls: 0.7456 data_time: 0.0019 time: 0.2687 2023/05/13 14:17:15 - mmengine - INFO - Epoch(train) [26][ 50/1196] lr: 8.0000e-04 eta: 5:55:41 time: 1.4983 data_time: 0.0042 memory: 4897 grad_norm: 0.0590 loss: 0.1722 loss_sem_seg: 0.1722 2023/05/13 14:18:30 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 14:18:30 - mmengine - INFO - Epoch(train) [26][ 100/1196] lr: 8.0000e-04 eta: 5:54:17 time: 1.5029 data_time: 0.0035 memory: 4920 grad_norm: 0.0590 loss: 0.1746 loss_sem_seg: 0.1746 2023/05/13 14:19:46 - mmengine - INFO - Epoch(train) [26][ 150/1196] lr: 8.0000e-04 eta: 5:52:53 time: 1.5093 data_time: 0.0034 memory: 4798 grad_norm: 0.0656 loss: 0.1698 loss_sem_seg: 0.1698 2023/05/13 14:21:01 - mmengine - INFO - Epoch(train) [26][ 200/1196] lr: 8.0000e-04 eta: 5:51:29 time: 1.5000 data_time: 0.0033 memory: 5426 grad_norm: 0.0581 loss: 0.1638 loss_sem_seg: 0.1638 2023/05/13 14:22:10 - mmengine - INFO - Epoch(train) [26][ 250/1196] lr: 8.0000e-04 eta: 5:50:02 time: 1.3938 data_time: 0.0033 memory: 4567 grad_norm: 0.0550 loss: 0.1573 loss_sem_seg: 0.1573 2023/05/13 14:23:20 - mmengine - INFO - Epoch(train) [26][ 300/1196] lr: 8.0000e-04 eta: 5:48:36 time: 1.3879 data_time: 0.0033 memory: 4563 grad_norm: 0.0568 loss: 0.1724 loss_sem_seg: 0.1724 2023/05/13 14:24:28 - mmengine - INFO - Epoch(train) [26][ 350/1196] lr: 8.0000e-04 eta: 5:47:09 time: 1.3745 data_time: 0.0033 memory: 4420 grad_norm: 0.0560 loss: 0.1620 loss_sem_seg: 0.1620 2023/05/13 14:25:39 - mmengine - INFO - Epoch(train) [26][ 400/1196] lr: 8.0000e-04 eta: 5:45:43 time: 1.4125 data_time: 0.0034 memory: 4659 grad_norm: 0.0580 loss: 0.1659 loss_sem_seg: 0.1659 2023/05/13 14:26:47 - mmengine - INFO - Epoch(train) [26][ 450/1196] lr: 8.0000e-04 eta: 5:44:16 time: 1.3667 data_time: 0.0035 memory: 4347 grad_norm: 0.0601 loss: 0.1745 loss_sem_seg: 0.1745 2023/05/13 14:28:07 - mmengine - INFO - Epoch(train) [26][ 500/1196] lr: 8.0000e-04 eta: 5:42:54 time: 1.5834 data_time: 0.0035 memory: 5118 grad_norm: 0.0597 loss: 0.1592 loss_sem_seg: 0.1592 2023/05/13 14:29:22 - mmengine - INFO - Epoch(train) [26][ 550/1196] lr: 8.0000e-04 eta: 5:41:30 time: 1.4987 data_time: 0.0036 memory: 5136 grad_norm: 0.0563 loss: 0.1587 loss_sem_seg: 0.1587 2023/05/13 14:30:37 - mmengine - INFO - Epoch(train) [26][ 600/1196] lr: 8.0000e-04 eta: 5:40:07 time: 1.5056 data_time: 0.0034 memory: 4571 grad_norm: 0.0603 loss: 0.1748 loss_sem_seg: 0.1748 2023/05/13 14:31:52 - mmengine - INFO - Epoch(train) [26][ 650/1196] lr: 8.0000e-04 eta: 5:38:43 time: 1.5070 data_time: 0.0036 memory: 4664 grad_norm: 0.0579 loss: 0.1725 loss_sem_seg: 0.1725 2023/05/13 14:33:10 - mmengine - INFO - Epoch(train) [26][ 700/1196] lr: 8.0000e-04 eta: 5:37:20 time: 1.5514 data_time: 0.0036 memory: 4754 grad_norm: 0.0587 loss: 0.1624 loss_sem_seg: 0.1624 2023/05/13 14:34:28 - mmengine - INFO - Epoch(train) [26][ 750/1196] lr: 8.0000e-04 eta: 5:35:58 time: 1.5558 data_time: 0.0034 memory: 4241 grad_norm: 0.0593 loss: 0.1660 loss_sem_seg: 0.1660 2023/05/13 14:35:44 - mmengine - INFO - Epoch(train) [26][ 800/1196] lr: 8.0000e-04 eta: 5:34:34 time: 1.5240 data_time: 0.0034 memory: 4467 grad_norm: 0.0615 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/13 14:37:02 - mmengine - INFO - Epoch(train) [26][ 850/1196] lr: 8.0000e-04 eta: 5:33:12 time: 1.5568 data_time: 0.0034 memory: 5118 grad_norm: 0.0603 loss: 0.1676 loss_sem_seg: 0.1676 2023/05/13 14:38:16 - mmengine - INFO - Epoch(train) [26][ 900/1196] lr: 8.0000e-04 eta: 5:31:48 time: 1.4804 data_time: 0.0034 memory: 4639 grad_norm: 0.0581 loss: 0.1791 loss_sem_seg: 0.1791 2023/05/13 14:39:20 - mmengine - INFO - Epoch(train) [26][ 950/1196] lr: 8.0000e-04 eta: 5:30:20 time: 1.2970 data_time: 0.0037 memory: 4840 grad_norm: 0.0608 loss: 0.1677 loss_sem_seg: 0.1677 2023/05/13 14:40:24 - mmengine - INFO - Epoch(train) [26][1000/1196] lr: 8.0000e-04 eta: 5:28:52 time: 1.2740 data_time: 0.0033 memory: 4905 grad_norm: 0.0605 loss: 0.1685 loss_sem_seg: 0.1685 2023/05/13 14:41:29 - mmengine - INFO - Epoch(train) [26][1050/1196] lr: 8.0000e-04 eta: 5:27:24 time: 1.2933 data_time: 0.0036 memory: 4714 grad_norm: 0.0597 loss: 0.1666 loss_sem_seg: 0.1666 2023/05/13 14:42:35 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 14:42:35 - mmengine - INFO - Epoch(train) [26][1100/1196] lr: 8.0000e-04 eta: 5:25:57 time: 1.3158 data_time: 0.0037 memory: 4466 grad_norm: 0.0617 loss: 0.1837 loss_sem_seg: 0.1837 2023/05/13 14:43:40 - mmengine - INFO - Epoch(train) [26][1150/1196] lr: 8.0000e-04 eta: 5:24:30 time: 1.3023 data_time: 0.0035 memory: 4516 grad_norm: 0.0587 loss: 0.1731 loss_sem_seg: 0.1731 2023/05/13 14:44:42 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 14:44:42 - mmengine - INFO - Saving checkpoint at 26 epochs 2023/05/13 14:45:02 - mmengine - INFO - Epoch(val) [26][ 50/509] eta: 0:02:11 time: 0.2865 data_time: 0.0021 memory: 4565 2023/05/13 14:45:14 - mmengine - INFO - Epoch(val) [26][100/509] eta: 0:01:47 time: 0.2398 data_time: 0.0021 memory: 914 2023/05/13 14:45:27 - mmengine - INFO - Epoch(val) [26][150/509] eta: 0:01:32 time: 0.2491 data_time: 0.0021 memory: 915 2023/05/13 14:45:39 - mmengine - INFO - Epoch(val) [26][200/509] eta: 0:01:19 time: 0.2497 data_time: 0.0020 memory: 901 2023/05/13 14:45:54 - mmengine - INFO - Epoch(val) [26][250/509] eta: 0:01:08 time: 0.2906 data_time: 0.0020 memory: 929 2023/05/13 14:46:05 - mmengine - INFO - Epoch(val) [26][300/509] eta: 0:00:53 time: 0.2261 data_time: 0.0020 memory: 867 2023/05/13 14:46:17 - mmengine - INFO - Epoch(val) [26][350/509] eta: 0:00:40 time: 0.2333 data_time: 0.0020 memory: 891 2023/05/13 14:46:30 - mmengine - INFO - Epoch(val) [26][400/509] eta: 0:00:27 time: 0.2724 data_time: 0.0022 memory: 899 2023/05/13 14:46:44 - mmengine - INFO - Epoch(val) [26][450/509] eta: 0:00:15 time: 0.2668 data_time: 0.0021 memory: 911 2023/05/13 14:46:55 - mmengine - INFO - Epoch(val) [26][500/509] eta: 0:00:02 time: 0.2289 data_time: 0.0020 memory: 893 2023/05/13 14:47:14 - 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 | 0.9688 | 0.5304 | 0.8247 | 0.8416 | 0.7094 | 0.7780 | 0.8693 | 0.0380 | 0.9477 | 0.5747 | 0.8327 | 0.0158 | 0.9147 | 0.6678 | 0.8780 | 0.6996 | 0.7279 | 0.6597 | 0.5158 | 0.6839 | 0.9240 | 0.7508 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 14:47:14 - mmengine - INFO - Epoch(val) [26][509/509] car: 0.9688 bicycle: 0.5304 motorcycle: 0.8247 truck: 0.8416 bus: 0.7094 person: 0.7780 bicyclist: 0.8693 motorcyclist: 0.0380 road: 0.9477 parking: 0.5747 sidewalk: 0.8327 other-ground: 0.0158 building: 0.9147 fence: 0.6678 vegetation: 0.8780 trunck: 0.6996 terrian: 0.7279 pole: 0.6597 traffic-sign: 0.5158 miou: 0.6839 acc: 0.9240 acc_cls: 0.7508 data_time: 0.0020 time: 0.2386 2023/05/13 14:48:29 - mmengine - INFO - Epoch(train) [27][ 50/1196] lr: 8.0000e-04 eta: 5:21:47 time: 1.5093 data_time: 0.0039 memory: 4636 grad_norm: 0.0608 loss: 0.1745 loss_sem_seg: 0.1745 2023/05/13 14:49:45 - mmengine - INFO - Epoch(train) [27][ 100/1196] lr: 8.0000e-04 eta: 5:20:24 time: 1.5154 data_time: 0.0033 memory: 5818 grad_norm: 0.0588 loss: 0.1683 loss_sem_seg: 0.1683 2023/05/13 14:51:00 - mmengine - INFO - Epoch(train) [27][ 150/1196] lr: 8.0000e-04 eta: 5:19:01 time: 1.5020 data_time: 0.0033 memory: 4727 grad_norm: 0.0613 loss: 0.1688 loss_sem_seg: 0.1688 2023/05/13 14:52:14 - mmengine - INFO - Epoch(train) [27][ 200/1196] lr: 8.0000e-04 eta: 5:17:37 time: 1.4880 data_time: 0.0033 memory: 4483 grad_norm: 0.0560 loss: 0.1634 loss_sem_seg: 0.1634 2023/05/13 14:53:20 - mmengine - INFO - Epoch(train) [27][ 250/1196] lr: 8.0000e-04 eta: 5:16:10 time: 1.3148 data_time: 0.0033 memory: 4651 grad_norm: 0.0567 loss: 0.1616 loss_sem_seg: 0.1616 2023/05/13 14:54:25 - mmengine - INFO - Epoch(train) [27][ 300/1196] lr: 8.0000e-04 eta: 5:14:43 time: 1.2929 data_time: 0.0033 memory: 4717 grad_norm: 0.0590 loss: 0.1660 loss_sem_seg: 0.1660 2023/05/13 14:55:24 - mmengine - INFO - Epoch(train) [27][ 350/1196] lr: 8.0000e-04 eta: 5:13:14 time: 1.1811 data_time: 0.0036 memory: 4498 grad_norm: 0.0603 loss: 0.1738 loss_sem_seg: 0.1738 2023/05/13 14:56:22 - mmengine - INFO - Epoch(train) [27][ 400/1196] lr: 8.0000e-04 eta: 5:11:45 time: 1.1634 data_time: 0.0037 memory: 4614 grad_norm: 0.0591 loss: 0.1584 loss_sem_seg: 0.1584 2023/05/13 14:57:22 - mmengine - INFO - Epoch(train) [27][ 450/1196] lr: 8.0000e-04 eta: 5:10:16 time: 1.1946 data_time: 0.0037 memory: 5079 grad_norm: 0.0592 loss: 0.1662 loss_sem_seg: 0.1662 2023/05/13 14:58:32 - mmengine - INFO - Epoch(train) [27][ 500/1196] lr: 8.0000e-04 eta: 5:08:52 time: 1.4064 data_time: 0.0034 memory: 4711 grad_norm: 0.0595 loss: 0.1618 loss_sem_seg: 0.1618 2023/05/13 14:59:41 - mmengine - INFO - Epoch(train) [27][ 550/1196] lr: 8.0000e-04 eta: 5:07:27 time: 1.3806 data_time: 0.0035 memory: 4576 grad_norm: 0.0594 loss: 0.1612 loss_sem_seg: 0.1612 2023/05/13 15:01:00 - mmengine - INFO - Epoch(train) [27][ 600/1196] lr: 8.0000e-04 eta: 5:06:05 time: 1.5722 data_time: 0.0035 memory: 4737 grad_norm: 0.0602 loss: 0.1706 loss_sem_seg: 0.1706 2023/05/13 15:02:17 - mmengine - INFO - Epoch(train) [27][ 650/1196] lr: 8.0000e-04 eta: 5:04:43 time: 1.5354 data_time: 0.0034 memory: 4678 grad_norm: 0.0569 loss: 0.1635 loss_sem_seg: 0.1635 2023/05/13 15:03:32 - mmengine - INFO - Epoch(train) [27][ 700/1196] lr: 8.0000e-04 eta: 5:03:20 time: 1.5156 data_time: 0.0033 memory: 4986 grad_norm: 0.0616 loss: 0.1661 loss_sem_seg: 0.1661 2023/05/13 15:04:50 - mmengine - INFO - Epoch(train) [27][ 750/1196] lr: 8.0000e-04 eta: 5:01:58 time: 1.5483 data_time: 0.0040 memory: 4854 grad_norm: 0.0619 loss: 0.1628 loss_sem_seg: 0.1628 2023/05/13 15:06:07 - mmengine - INFO - Epoch(train) [27][ 800/1196] lr: 8.0000e-04 eta: 5:00:36 time: 1.5507 data_time: 0.0034 memory: 4761 grad_norm: 0.0585 loss: 0.1528 loss_sem_seg: 0.1528 2023/05/13 15:07:24 - mmengine - INFO - Epoch(train) [27][ 850/1196] lr: 8.0000e-04 eta: 4:59:14 time: 1.5267 data_time: 0.0034 memory: 4592 grad_norm: 0.0588 loss: 0.1529 loss_sem_seg: 0.1529 2023/05/13 15:08:39 - mmengine - INFO - Epoch(train) [27][ 900/1196] lr: 8.0000e-04 eta: 4:57:51 time: 1.5134 data_time: 0.0034 memory: 4569 grad_norm: 0.0604 loss: 0.1656 loss_sem_seg: 0.1656 2023/05/13 15:08:45 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 15:09:56 - mmengine - INFO - Epoch(train) [27][ 950/1196] lr: 8.0000e-04 eta: 4:56:29 time: 1.5343 data_time: 0.0033 memory: 5170 grad_norm: 0.0607 loss: 0.1730 loss_sem_seg: 0.1730 2023/05/13 15:11:13 - mmengine - INFO - Epoch(train) [27][1000/1196] lr: 8.0000e-04 eta: 4:55:07 time: 1.5324 data_time: 0.0034 memory: 4736 grad_norm: 0.0594 loss: 0.1628 loss_sem_seg: 0.1628 2023/05/13 15:12:28 - mmengine - INFO - Epoch(train) [27][1050/1196] lr: 8.0000e-04 eta: 4:53:44 time: 1.4988 data_time: 0.0034 memory: 4612 grad_norm: 0.0598 loss: 0.1618 loss_sem_seg: 0.1618 2023/05/13 15:13:43 - mmengine - INFO - Epoch(train) [27][1100/1196] lr: 8.0000e-04 eta: 4:52:21 time: 1.5024 data_time: 0.0033 memory: 4701 grad_norm: 0.0571 loss: 0.1651 loss_sem_seg: 0.1651 2023/05/13 15:15:00 - mmengine - INFO - Epoch(train) [27][1150/1196] lr: 8.0000e-04 eta: 4:50:59 time: 1.5441 data_time: 0.0034 memory: 4310 grad_norm: 0.0616 loss: 0.1585 loss_sem_seg: 0.1585 2023/05/13 15:16:10 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 15:16:10 - mmengine - INFO - Saving checkpoint at 27 epochs 2023/05/13 15:16:31 - mmengine - INFO - Epoch(val) [27][ 50/509] eta: 0:02:15 time: 0.2943 data_time: 0.0021 memory: 4853 2023/05/13 15:16:44 - mmengine - INFO - Epoch(val) [27][100/509] eta: 0:01:50 time: 0.2482 data_time: 0.0020 memory: 914 2023/05/13 15:16:57 - mmengine - INFO - Epoch(val) [27][150/509] eta: 0:01:35 time: 0.2586 data_time: 0.0021 memory: 915 2023/05/13 15:17:09 - mmengine - INFO - Epoch(val) [27][200/509] eta: 0:01:20 time: 0.2474 data_time: 0.0020 memory: 901 2023/05/13 15:17:22 - mmengine - INFO - Epoch(val) [27][250/509] eta: 0:01:08 time: 0.2651 data_time: 0.0020 memory: 929 2023/05/13 15:17:34 - mmengine - INFO - Epoch(val) [27][300/509] eta: 0:00:54 time: 0.2429 data_time: 0.0020 memory: 867 2023/05/13 15:17:47 - mmengine - INFO - Epoch(val) [27][350/509] eta: 0:00:40 time: 0.2454 data_time: 0.0020 memory: 891 2023/05/13 15:18:00 - mmengine - INFO - Epoch(val) [27][400/509] eta: 0:00:28 time: 0.2603 data_time: 0.0020 memory: 899 2023/05/13 15:18:13 - mmengine - INFO - Epoch(val) [27][450/509] eta: 0:00:15 time: 0.2627 data_time: 0.0021 memory: 911 2023/05/13 15:18:26 - mmengine - INFO - Epoch(val) [27][500/509] eta: 0:00:02 time: 0.2638 data_time: 0.0020 memory: 893 2023/05/13 15:18:44 - 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 | 0.9676 | 0.5616 | 0.8079 | 0.8897 | 0.6790 | 0.7849 | 0.8785 | 0.0692 | 0.9489 | 0.5737 | 0.8336 | 0.0278 | 0.9161 | 0.6767 | 0.8748 | 0.6860 | 0.7229 | 0.6593 | 0.5175 | 0.6882 | 0.9233 | 0.7539 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 15:18:44 - mmengine - INFO - Epoch(val) [27][509/509] car: 0.9676 bicycle: 0.5616 motorcycle: 0.8079 truck: 0.8897 bus: 0.6790 person: 0.7849 bicyclist: 0.8785 motorcyclist: 0.0692 road: 0.9489 parking: 0.5737 sidewalk: 0.8336 other-ground: 0.0278 building: 0.9161 fence: 0.6767 vegetation: 0.8748 trunck: 0.6860 terrian: 0.7229 pole: 0.6593 traffic-sign: 0.5175 miou: 0.6882 acc: 0.9233 acc_cls: 0.7539 data_time: 0.0020 time: 0.2779 2023/05/13 15:20:02 - mmengine - INFO - Epoch(train) [28][ 50/1196] lr: 8.0000e-04 eta: 4:48:22 time: 1.5543 data_time: 0.0041 memory: 5211 grad_norm: 0.0592 loss: 0.1621 loss_sem_seg: 0.1621 2023/05/13 15:21:19 - mmengine - INFO - Epoch(train) [28][ 100/1196] lr: 8.0000e-04 eta: 4:47:00 time: 1.5414 data_time: 0.0036 memory: 4853 grad_norm: 0.0566 loss: 0.1621 loss_sem_seg: 0.1621 2023/05/13 15:22:34 - mmengine - INFO - Epoch(train) [28][ 150/1196] lr: 8.0000e-04 eta: 4:45:37 time: 1.4936 data_time: 0.0034 memory: 4518 grad_norm: 0.0601 loss: 0.1660 loss_sem_seg: 0.1660 2023/05/13 15:23:48 - mmengine - INFO - Epoch(train) [28][ 200/1196] lr: 8.0000e-04 eta: 4:44:14 time: 1.4916 data_time: 0.0033 memory: 4584 grad_norm: 0.0604 loss: 0.1660 loss_sem_seg: 0.1660 2023/05/13 15:25:05 - mmengine - INFO - Epoch(train) [28][ 250/1196] lr: 8.0000e-04 eta: 4:42:52 time: 1.5295 data_time: 0.0035 memory: 4911 grad_norm: 0.0604 loss: 0.1703 loss_sem_seg: 0.1703 2023/05/13 15:26:19 - mmengine - INFO - Epoch(train) [28][ 300/1196] lr: 8.0000e-04 eta: 4:41:30 time: 1.4907 data_time: 0.0033 memory: 4396 grad_norm: 0.0647 loss: 0.1663 loss_sem_seg: 0.1663 2023/05/13 15:27:36 - mmengine - INFO - Epoch(train) [28][ 350/1196] lr: 8.0000e-04 eta: 4:40:08 time: 1.5366 data_time: 0.0034 memory: 4545 grad_norm: 0.0539 loss: 0.1630 loss_sem_seg: 0.1630 2023/05/13 15:28:51 - mmengine - INFO - Epoch(train) [28][ 400/1196] lr: 8.0000e-04 eta: 4:38:45 time: 1.5043 data_time: 0.0035 memory: 4954 grad_norm: 0.0588 loss: 0.1612 loss_sem_seg: 0.1612 2023/05/13 15:30:02 - mmengine - INFO - Epoch(train) [28][ 450/1196] lr: 8.0000e-04 eta: 4:37:21 time: 1.4096 data_time: 0.0035 memory: 4618 grad_norm: 0.0586 loss: 0.1664 loss_sem_seg: 0.1664 2023/05/13 15:31:12 - mmengine - INFO - Epoch(train) [28][ 500/1196] lr: 8.0000e-04 eta: 4:35:57 time: 1.4080 data_time: 0.0035 memory: 4695 grad_norm: 0.0610 loss: 0.1559 loss_sem_seg: 0.1559 2023/05/13 15:32:21 - mmengine - INFO - Epoch(train) [28][ 550/1196] lr: 8.0000e-04 eta: 4:34:33 time: 1.3689 data_time: 0.0035 memory: 4338 grad_norm: 0.0637 loss: 0.1577 loss_sem_seg: 0.1577 2023/05/13 15:33:29 - mmengine - INFO - Epoch(train) [28][ 600/1196] lr: 8.0000e-04 eta: 4:33:09 time: 1.3762 data_time: 0.0033 memory: 5047 grad_norm: 0.0628 loss: 0.1631 loss_sem_seg: 0.1631 2023/05/13 15:34:39 - mmengine - INFO - Epoch(train) [28][ 650/1196] lr: 8.0000e-04 eta: 4:31:45 time: 1.4005 data_time: 0.0034 memory: 4921 grad_norm: 0.0601 loss: 0.1676 loss_sem_seg: 0.1676 2023/05/13 15:35:59 - mmengine - INFO - Epoch(train) [28][ 700/1196] lr: 8.0000e-04 eta: 4:30:24 time: 1.5849 data_time: 0.0034 memory: 4841 grad_norm: 0.0624 loss: 0.1633 loss_sem_seg: 0.1633 2023/05/13 15:36:10 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 15:37:07 - mmengine - INFO - Epoch(train) [28][ 750/1196] lr: 8.0000e-04 eta: 4:28:59 time: 1.3571 data_time: 0.0034 memory: 4638 grad_norm: 0.0591 loss: 0.1554 loss_sem_seg: 0.1554 2023/05/13 15:38:10 - mmengine - INFO - Epoch(train) [28][ 800/1196] lr: 8.0000e-04 eta: 4:27:34 time: 1.2725 data_time: 0.0033 memory: 4496 grad_norm: 0.0608 loss: 0.1617 loss_sem_seg: 0.1617 2023/05/13 15:39:17 - mmengine - INFO - Epoch(train) [28][ 850/1196] lr: 8.0000e-04 eta: 4:26:09 time: 1.3294 data_time: 0.0034 memory: 4404 grad_norm: 0.0590 loss: 0.1565 loss_sem_seg: 0.1565 2023/05/13 15:40:21 - mmengine - INFO - Epoch(train) [28][ 900/1196] lr: 8.0000e-04 eta: 4:24:44 time: 1.2923 data_time: 0.0033 memory: 4665 grad_norm: 0.0599 loss: 0.1722 loss_sem_seg: 0.1722 2023/05/13 15:41:27 - mmengine - INFO - Epoch(train) [28][ 950/1196] lr: 8.0000e-04 eta: 4:23:19 time: 1.3119 data_time: 0.0033 memory: 4682 grad_norm: 0.0617 loss: 0.1590 loss_sem_seg: 0.1590 2023/05/13 15:42:37 - mmengine - INFO - Epoch(train) [28][1000/1196] lr: 8.0000e-04 eta: 4:21:55 time: 1.4042 data_time: 0.0033 memory: 4813 grad_norm: 0.0604 loss: 0.1574 loss_sem_seg: 0.1574 2023/05/13 15:43:57 - mmengine - INFO - Epoch(train) [28][1050/1196] lr: 8.0000e-04 eta: 4:20:34 time: 1.5911 data_time: 0.0036 memory: 4438 grad_norm: 0.0602 loss: 0.1533 loss_sem_seg: 0.1533 2023/05/13 15:45:12 - mmengine - INFO - Epoch(train) [28][1100/1196] lr: 8.0000e-04 eta: 4:19:12 time: 1.5066 data_time: 0.0036 memory: 4678 grad_norm: 0.0620 loss: 0.1547 loss_sem_seg: 0.1547 2023/05/13 15:46:26 - mmengine - INFO - Epoch(train) [28][1150/1196] lr: 8.0000e-04 eta: 4:17:50 time: 1.4716 data_time: 0.0038 memory: 4799 grad_norm: 0.0623 loss: 0.1603 loss_sem_seg: 0.1603 2023/05/13 15:47:35 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 15:47:35 - mmengine - INFO - Saving checkpoint at 28 epochs 2023/05/13 15:47:55 - mmengine - INFO - Epoch(val) [28][ 50/509] eta: 0:02:05 time: 0.2727 data_time: 0.0020 memory: 4556 2023/05/13 15:48:07 - mmengine - INFO - Epoch(val) [28][100/509] eta: 0:01:44 time: 0.2404 data_time: 0.0020 memory: 914 2023/05/13 15:48:19 - mmengine - INFO - Epoch(val) [28][150/509] eta: 0:01:30 time: 0.2414 data_time: 0.0020 memory: 915 2023/05/13 15:48:32 - mmengine - INFO - Epoch(val) [28][200/509] eta: 0:01:17 time: 0.2466 data_time: 0.0020 memory: 901 2023/05/13 15:48:45 - mmengine - INFO - Epoch(val) [28][250/509] eta: 0:01:06 time: 0.2770 data_time: 0.0020 memory: 929 2023/05/13 15:48:57 - mmengine - INFO - Epoch(val) [28][300/509] eta: 0:00:52 time: 0.2378 data_time: 0.0020 memory: 867 2023/05/13 15:49:09 - mmengine - INFO - Epoch(val) [28][350/509] eta: 0:00:39 time: 0.2390 data_time: 0.0020 memory: 891 2023/05/13 15:49:22 - mmengine - INFO - Epoch(val) [28][400/509] eta: 0:00:27 time: 0.2586 data_time: 0.0019 memory: 899 2023/05/13 15:49:35 - mmengine - INFO - Epoch(val) [28][450/509] eta: 0:00:14 time: 0.2557 data_time: 0.0020 memory: 911 2023/05/13 15:49:48 - mmengine - INFO - Epoch(val) [28][500/509] eta: 0:00:02 time: 0.2579 data_time: 0.0019 memory: 893 2023/05/13 15:50:08 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9736 | 0.5589 | 0.8138 | 0.8136 | 0.7630 | 0.7782 | 0.8728 | 0.0336 | 0.9489 | 0.5845 | 0.8315 | 0.0107 | 0.9158 | 0.6760 | 0.8748 | 0.6774 | 0.7216 | 0.6622 | 0.5157 | 0.6856 | 0.9232 | 0.7551 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 15:50:08 - mmengine - INFO - Epoch(val) [28][509/509] car: 0.9736 bicycle: 0.5589 motorcycle: 0.8138 truck: 0.8136 bus: 0.7630 person: 0.7782 bicyclist: 0.8728 motorcyclist: 0.0336 road: 0.9489 parking: 0.5845 sidewalk: 0.8315 other-ground: 0.0107 building: 0.9158 fence: 0.6760 vegetation: 0.8748 trunck: 0.6774 terrian: 0.7216 pole: 0.6622 traffic-sign: 0.5157 miou: 0.6856 acc: 0.9232 acc_cls: 0.7551 data_time: 0.0020 time: 0.2656 2023/05/13 15:51:24 - mmengine - INFO - Epoch(train) [29][ 50/1196] lr: 8.0000e-04 eta: 4:15:13 time: 1.5198 data_time: 0.0043 memory: 5275 grad_norm: 0.0617 loss: 0.1535 loss_sem_seg: 0.1535 2023/05/13 15:52:41 - mmengine - INFO - Epoch(train) [29][ 100/1196] lr: 8.0000e-04 eta: 4:13:52 time: 1.5481 data_time: 0.0034 memory: 4486 grad_norm: 0.0577 loss: 0.1553 loss_sem_seg: 0.1553 2023/05/13 15:53:58 - mmengine - INFO - Epoch(train) [29][ 150/1196] lr: 8.0000e-04 eta: 4:12:30 time: 1.5339 data_time: 0.0033 memory: 4611 grad_norm: 0.0583 loss: 0.1649 loss_sem_seg: 0.1649 2023/05/13 15:55:14 - mmengine - INFO - Epoch(train) [29][ 200/1196] lr: 8.0000e-04 eta: 4:11:08 time: 1.5277 data_time: 0.0034 memory: 4962 grad_norm: 0.0599 loss: 0.1653 loss_sem_seg: 0.1653 2023/05/13 15:56:30 - mmengine - INFO - Epoch(train) [29][ 250/1196] lr: 8.0000e-04 eta: 4:09:47 time: 1.5148 data_time: 0.0034 memory: 4507 grad_norm: 0.0609 loss: 0.1553 loss_sem_seg: 0.1553 2023/05/13 15:57:44 - mmengine - INFO - Epoch(train) [29][ 300/1196] lr: 8.0000e-04 eta: 4:08:25 time: 1.4921 data_time: 0.0034 memory: 4574 grad_norm: 0.0588 loss: 0.1569 loss_sem_seg: 0.1569 2023/05/13 15:59:00 - mmengine - INFO - Epoch(train) [29][ 350/1196] lr: 8.0000e-04 eta: 4:07:03 time: 1.5102 data_time: 0.0033 memory: 4719 grad_norm: 0.0616 loss: 0.1508 loss_sem_seg: 0.1508 2023/05/13 16:00:17 - mmengine - INFO - Epoch(train) [29][ 400/1196] lr: 8.0000e-04 eta: 4:05:42 time: 1.5458 data_time: 0.0034 memory: 5133 grad_norm: 0.0592 loss: 0.1570 loss_sem_seg: 0.1570 2023/05/13 16:01:35 - mmengine - INFO - Epoch(train) [29][ 450/1196] lr: 8.0000e-04 eta: 4:04:21 time: 1.5441 data_time: 0.0034 memory: 4563 grad_norm: 0.0620 loss: 0.1632 loss_sem_seg: 0.1632 2023/05/13 16:02:51 - mmengine - INFO - Epoch(train) [29][ 500/1196] lr: 8.0000e-04 eta: 4:02:59 time: 1.5236 data_time: 0.0034 memory: 4786 grad_norm: 0.0574 loss: 0.1510 loss_sem_seg: 0.1510 2023/05/13 16:03:08 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 16:04:01 - mmengine - INFO - Epoch(train) [29][ 550/1196] lr: 8.0000e-04 eta: 4:01:36 time: 1.4028 data_time: 0.0033 memory: 4548 grad_norm: 0.0604 loss: 0.1590 loss_sem_seg: 0.1590 2023/05/13 16:05:11 - mmengine - INFO - Epoch(train) [29][ 600/1196] lr: 8.0000e-04 eta: 4:00:13 time: 1.3963 data_time: 0.0034 memory: 4887 grad_norm: 0.0642 loss: 0.1506 loss_sem_seg: 0.1506 2023/05/13 16:06:21 - mmengine - INFO - Epoch(train) [29][ 650/1196] lr: 8.0000e-04 eta: 3:58:50 time: 1.4002 data_time: 0.0034 memory: 4720 grad_norm: 0.0602 loss: 0.1659 loss_sem_seg: 0.1659 2023/05/13 16:07:31 - mmengine - INFO - Epoch(train) [29][ 700/1196] lr: 8.0000e-04 eta: 3:57:27 time: 1.3969 data_time: 0.0034 memory: 4470 grad_norm: 0.0580 loss: 0.1679 loss_sem_seg: 0.1679 2023/05/13 16:08:39 - mmengine - INFO - Epoch(train) [29][ 750/1196] lr: 8.0000e-04 eta: 3:56:03 time: 1.3703 data_time: 0.0034 memory: 4767 grad_norm: 0.0605 loss: 0.1677 loss_sem_seg: 0.1677 2023/05/13 16:09:57 - mmengine - INFO - Epoch(train) [29][ 800/1196] lr: 8.0000e-04 eta: 3:54:42 time: 1.5597 data_time: 0.0034 memory: 4451 grad_norm: 0.0598 loss: 0.1577 loss_sem_seg: 0.1577 2023/05/13 16:11:13 - mmengine - INFO - Epoch(train) [29][ 850/1196] lr: 8.0000e-04 eta: 3:53:21 time: 1.5099 data_time: 0.0034 memory: 4649 grad_norm: 0.0621 loss: 0.1633 loss_sem_seg: 0.1633 2023/05/13 16:12:30 - mmengine - INFO - Epoch(train) [29][ 900/1196] lr: 8.0000e-04 eta: 3:52:00 time: 1.5409 data_time: 0.0034 memory: 4887 grad_norm: 0.0574 loss: 0.1474 loss_sem_seg: 0.1474 2023/05/13 16:13:47 - mmengine - INFO - Epoch(train) [29][ 950/1196] lr: 8.0000e-04 eta: 3:50:39 time: 1.5567 data_time: 0.0034 memory: 4562 grad_norm: 0.0637 loss: 0.1609 loss_sem_seg: 0.1609 2023/05/13 16:15:05 - mmengine - INFO - Epoch(train) [29][1000/1196] lr: 8.0000e-04 eta: 3:49:18 time: 1.5587 data_time: 0.0033 memory: 4813 grad_norm: 0.0596 loss: 0.1512 loss_sem_seg: 0.1512 2023/05/13 16:16:22 - mmengine - INFO - Epoch(train) [29][1050/1196] lr: 8.0000e-04 eta: 3:47:57 time: 1.5253 data_time: 0.0033 memory: 4254 grad_norm: 0.0630 loss: 0.1557 loss_sem_seg: 0.1557 2023/05/13 16:17:39 - mmengine - INFO - Epoch(train) [29][1100/1196] lr: 8.0000e-04 eta: 3:46:36 time: 1.5422 data_time: 0.0034 memory: 5173 grad_norm: 0.0629 loss: 0.1478 loss_sem_seg: 0.1478 2023/05/13 16:18:57 - mmengine - INFO - Epoch(train) [29][1150/1196] lr: 8.0000e-04 eta: 3:45:15 time: 1.5617 data_time: 0.0036 memory: 4954 grad_norm: 0.0577 loss: 0.1482 loss_sem_seg: 0.1482 2023/05/13 16:20:05 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 16:20:05 - mmengine - INFO - Saving checkpoint at 29 epochs 2023/05/13 16:20:26 - mmengine - INFO - Epoch(val) [29][ 50/509] eta: 0:02:11 time: 0.2868 data_time: 0.0021 memory: 4678 2023/05/13 16:20:38 - mmengine - INFO - Epoch(val) [29][100/509] eta: 0:01:47 time: 0.2381 data_time: 0.0021 memory: 914 2023/05/13 16:20:49 - mmengine - INFO - Epoch(val) [29][150/509] eta: 0:01:30 time: 0.2319 data_time: 0.0020 memory: 915 2023/05/13 16:21:02 - mmengine - INFO - Epoch(val) [29][200/509] eta: 0:01:17 time: 0.2471 data_time: 0.0020 memory: 901 2023/05/13 16:21:15 - mmengine - INFO - Epoch(val) [29][250/509] eta: 0:01:05 time: 0.2555 data_time: 0.0021 memory: 929 2023/05/13 16:21:24 - mmengine - INFO - Epoch(val) [29][300/509] eta: 0:00:50 time: 0.1945 data_time: 0.0021 memory: 867 2023/05/13 16:21:34 - mmengine - INFO - Epoch(val) [29][350/509] eta: 0:00:37 time: 0.2021 data_time: 0.0020 memory: 891 2023/05/13 16:21:44 - mmengine - INFO - Epoch(val) [29][400/509] eta: 0:00:25 time: 0.2002 data_time: 0.0020 memory: 899 2023/05/13 16:21:54 - mmengine - INFO - Epoch(val) [29][450/509] eta: 0:00:13 time: 0.2001 data_time: 0.0020 memory: 911 2023/05/13 16:22:05 - mmengine - INFO - Epoch(val) [29][500/509] eta: 0:00:02 time: 0.2018 data_time: 0.0020 memory: 893 2023/05/13 16:22:23 - 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 | 0.9713 | 0.5506 | 0.8094 | 0.8596 | 0.7429 | 0.7986 | 0.8844 | 0.0867 | 0.9497 | 0.5728 | 0.8360 | 0.0182 | 0.9171 | 0.6699 | 0.8771 | 0.7008 | 0.7294 | 0.6629 | 0.5218 | 0.6926 | 0.9246 | 0.7628 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 16:22:23 - mmengine - INFO - Epoch(val) [29][509/509] car: 0.9713 bicycle: 0.5506 motorcycle: 0.8094 truck: 0.8596 bus: 0.7429 person: 0.7986 bicyclist: 0.8844 motorcyclist: 0.0867 road: 0.9497 parking: 0.5728 sidewalk: 0.8360 other-ground: 0.0182 building: 0.9171 fence: 0.6699 vegetation: 0.8771 trunck: 0.7008 terrian: 0.7294 pole: 0.6629 traffic-sign: 0.5218 miou: 0.6926 acc: 0.9246 acc_cls: 0.7628 data_time: 0.0019 time: 0.2149 2023/05/13 16:23:28 - mmengine - INFO - Epoch(train) [30][ 50/1196] lr: 8.0000e-04 eta: 3:42:36 time: 1.2985 data_time: 0.0043 memory: 4928 grad_norm: 0.0578 loss: 0.1549 loss_sem_seg: 0.1549 2023/05/13 16:24:34 - mmengine - INFO - Epoch(train) [30][ 100/1196] lr: 8.0000e-04 eta: 3:41:12 time: 1.3316 data_time: 0.0036 memory: 4706 grad_norm: 0.0583 loss: 0.1539 loss_sem_seg: 0.1539 2023/05/13 16:25:41 - mmengine - INFO - Epoch(train) [30][ 150/1196] lr: 8.0000e-04 eta: 3:39:49 time: 1.3279 data_time: 0.0033 memory: 4745 grad_norm: 0.0585 loss: 0.1518 loss_sem_seg: 0.1518 2023/05/13 16:26:46 - mmengine - INFO - Epoch(train) [30][ 200/1196] lr: 8.0000e-04 eta: 3:38:25 time: 1.3166 data_time: 0.0034 memory: 4450 grad_norm: 0.0641 loss: 0.1534 loss_sem_seg: 0.1534 2023/05/13 16:28:06 - mmengine - INFO - Epoch(train) [30][ 250/1196] lr: 8.0000e-04 eta: 3:37:05 time: 1.5834 data_time: 0.0035 memory: 4642 grad_norm: 0.0567 loss: 0.1500 loss_sem_seg: 0.1500 2023/05/13 16:29:19 - mmengine - INFO - Epoch(train) [30][ 300/1196] lr: 8.0000e-04 eta: 3:35:43 time: 1.4702 data_time: 0.0034 memory: 4532 grad_norm: 0.0606 loss: 0.1525 loss_sem_seg: 0.1525 2023/05/13 16:29:43 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 16:30:33 - mmengine - INFO - Epoch(train) [30][ 350/1196] lr: 8.0000e-04 eta: 3:34:21 time: 1.4779 data_time: 0.0034 memory: 4729 grad_norm: 0.0586 loss: 0.1471 loss_sem_seg: 0.1471 2023/05/13 16:31:46 - mmengine - INFO - Epoch(train) [30][ 400/1196] lr: 8.0000e-04 eta: 3:33:00 time: 1.4698 data_time: 0.0035 memory: 4795 grad_norm: 0.0602 loss: 0.1572 loss_sem_seg: 0.1572 2023/05/13 16:33:03 - mmengine - INFO - Epoch(train) [30][ 450/1196] lr: 8.0000e-04 eta: 3:31:39 time: 1.5251 data_time: 0.0034 memory: 5432 grad_norm: 0.0580 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/13 16:34:19 - mmengine - INFO - Epoch(train) [30][ 500/1196] lr: 8.0000e-04 eta: 3:30:18 time: 1.5272 data_time: 0.0034 memory: 4731 grad_norm: 0.0584 loss: 0.1682 loss_sem_seg: 0.1682 2023/05/13 16:35:36 - mmengine - INFO - Epoch(train) [30][ 550/1196] lr: 8.0000e-04 eta: 3:28:57 time: 1.5373 data_time: 0.0035 memory: 4669 grad_norm: 0.0603 loss: 0.1557 loss_sem_seg: 0.1557 2023/05/13 16:36:50 - mmengine - INFO - Epoch(train) [30][ 600/1196] lr: 8.0000e-04 eta: 3:27:35 time: 1.4872 data_time: 0.0035 memory: 4734 grad_norm: 0.0590 loss: 0.1447 loss_sem_seg: 0.1447 2023/05/13 16:38:00 - mmengine - INFO - Epoch(train) [30][ 650/1196] lr: 8.0000e-04 eta: 3:26:13 time: 1.3941 data_time: 0.0034 memory: 4571 grad_norm: 0.0598 loss: 0.1595 loss_sem_seg: 0.1595 2023/05/13 16:39:09 - mmengine - INFO - Epoch(train) [30][ 700/1196] lr: 8.0000e-04 eta: 3:24:50 time: 1.3708 data_time: 0.0034 memory: 4478 grad_norm: 0.0643 loss: 0.1651 loss_sem_seg: 0.1651 2023/05/13 16:40:17 - mmengine - INFO - Epoch(train) [30][ 750/1196] lr: 8.0000e-04 eta: 3:23:28 time: 1.3707 data_time: 0.0033 memory: 4726 grad_norm: 0.0599 loss: 0.1625 loss_sem_seg: 0.1625 2023/05/13 16:41:24 - mmengine - INFO - Epoch(train) [30][ 800/1196] lr: 8.0000e-04 eta: 3:22:05 time: 1.3307 data_time: 0.0033 memory: 5022 grad_norm: 0.0615 loss: 0.1545 loss_sem_seg: 0.1545 2023/05/13 16:42:31 - mmengine - INFO - Epoch(train) [30][ 850/1196] lr: 8.0000e-04 eta: 3:20:42 time: 1.3512 data_time: 0.0035 memory: 4633 grad_norm: 0.0587 loss: 0.1491 loss_sem_seg: 0.1491 2023/05/13 16:43:40 - mmengine - INFO - Epoch(train) [30][ 900/1196] lr: 8.0000e-04 eta: 3:19:19 time: 1.3659 data_time: 0.0034 memory: 4606 grad_norm: 0.0608 loss: 0.1505 loss_sem_seg: 0.1505 2023/05/13 16:44:46 - mmengine - INFO - Epoch(train) [30][ 950/1196] lr: 8.0000e-04 eta: 3:17:56 time: 1.3231 data_time: 0.0036 memory: 5060 grad_norm: 0.0597 loss: 0.1623 loss_sem_seg: 0.1623 2023/05/13 16:45:53 - mmengine - INFO - Epoch(train) [30][1000/1196] lr: 8.0000e-04 eta: 3:16:34 time: 1.3367 data_time: 0.0035 memory: 4556 grad_norm: 0.0615 loss: 0.1680 loss_sem_seg: 0.1680 2023/05/13 16:46:58 - mmengine - INFO - Epoch(train) [30][1050/1196] lr: 8.0000e-04 eta: 3:15:11 time: 1.3091 data_time: 0.0035 memory: 4512 grad_norm: 0.0604 loss: 0.1601 loss_sem_seg: 0.1601 2023/05/13 16:48:04 - mmengine - INFO - Epoch(train) [30][1100/1196] lr: 8.0000e-04 eta: 3:13:48 time: 1.3276 data_time: 0.0034 memory: 4700 grad_norm: 0.0655 loss: 0.1617 loss_sem_seg: 0.1617 2023/05/13 16:49:12 - mmengine - INFO - Epoch(train) [30][1150/1196] lr: 8.0000e-04 eta: 3:12:26 time: 1.3570 data_time: 0.0034 memory: 4779 grad_norm: 0.0608 loss: 0.1531 loss_sem_seg: 0.1531 2023/05/13 16:50:25 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 16:50:25 - mmengine - INFO - Saving checkpoint at 30 epochs 2023/05/13 16:50:46 - mmengine - INFO - Epoch(val) [30][ 50/509] eta: 0:02:11 time: 0.2867 data_time: 0.0022 memory: 4558 2023/05/13 16:50:58 - mmengine - INFO - Epoch(val) [30][100/509] eta: 0:01:48 time: 0.2461 data_time: 0.0023 memory: 914 2023/05/13 16:51:10 - mmengine - INFO - Epoch(val) [30][150/509] eta: 0:01:31 time: 0.2331 data_time: 0.0024 memory: 915 2023/05/13 16:51:23 - mmengine - INFO - Epoch(val) [30][200/509] eta: 0:01:19 time: 0.2627 data_time: 0.0024 memory: 901 2023/05/13 16:51:36 - mmengine - INFO - Epoch(val) [30][250/509] eta: 0:01:06 time: 0.2616 data_time: 0.0025 memory: 929 2023/05/13 16:51:47 - mmengine - INFO - Epoch(val) [30][300/509] eta: 0:00:52 time: 0.2154 data_time: 0.0025 memory: 867 2023/05/13 16:51:59 - mmengine - INFO - Epoch(val) [30][350/509] eta: 0:00:39 time: 0.2489 data_time: 0.0024 memory: 891 2023/05/13 16:52:13 - mmengine - INFO - Epoch(val) [30][400/509] eta: 0:00:27 time: 0.2644 data_time: 0.0022 memory: 899 2023/05/13 16:52:26 - mmengine - INFO - Epoch(val) [30][450/509] eta: 0:00:14 time: 0.2673 data_time: 0.0020 memory: 911 2023/05/13 16:52:38 - mmengine - INFO - Epoch(val) [30][500/509] eta: 0:00:02 time: 0.2451 data_time: 0.0019 memory: 893 2023/05/13 16:52:56 - 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 | 0.9716 | 0.5732 | 0.8156 | 0.8606 | 0.7295 | 0.7967 | 0.8968 | 0.0484 | 0.9486 | 0.5420 | 0.8314 | 0.0247 | 0.9183 | 0.6833 | 0.8731 | 0.6753 | 0.7188 | 0.6627 | 0.5170 | 0.6888 | 0.9226 | 0.7551 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 16:52:56 - mmengine - INFO - Epoch(val) [30][509/509] car: 0.9716 bicycle: 0.5732 motorcycle: 0.8156 truck: 0.8606 bus: 0.7295 person: 0.7967 bicyclist: 0.8968 motorcyclist: 0.0484 road: 0.9486 parking: 0.5420 sidewalk: 0.8314 other-ground: 0.0247 building: 0.9183 fence: 0.6833 vegetation: 0.8731 trunck: 0.6753 terrian: 0.7188 pole: 0.6627 traffic-sign: 0.5170 miou: 0.6888 acc: 0.9226 acc_cls: 0.7551 data_time: 0.0019 time: 0.2501 2023/05/13 16:54:11 - mmengine - INFO - Epoch(train) [31][ 50/1196] lr: 8.0000e-04 eta: 3:09:51 time: 1.5035 data_time: 0.0045 memory: 4670 grad_norm: 0.0580 loss: 0.1487 loss_sem_seg: 0.1487 2023/05/13 16:55:28 - mmengine - INFO - Epoch(train) [31][ 100/1196] lr: 8.0000e-04 eta: 3:08:30 time: 1.5268 data_time: 0.0036 memory: 4387 grad_norm: 0.0673 loss: 0.1664 loss_sem_seg: 0.1664 2023/05/13 16:55:58 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 16:56:44 - mmengine - INFO - Epoch(train) [31][ 150/1196] lr: 8.0000e-04 eta: 3:07:10 time: 1.5176 data_time: 0.0036 memory: 4432 grad_norm: 0.0602 loss: 0.1445 loss_sem_seg: 0.1445 2023/05/13 16:58:01 - mmengine - INFO - Epoch(train) [31][ 200/1196] lr: 8.0000e-04 eta: 3:05:49 time: 1.5426 data_time: 0.0035 memory: 5017 grad_norm: 0.0625 loss: 0.1655 loss_sem_seg: 0.1655 2023/05/13 16:59:17 - mmengine - INFO - Epoch(train) [31][ 250/1196] lr: 8.0000e-04 eta: 3:04:29 time: 1.5291 data_time: 0.0034 memory: 4791 grad_norm: 0.0608 loss: 0.1501 loss_sem_seg: 0.1501 2023/05/13 17:00:36 - mmengine - INFO - Epoch(train) [31][ 300/1196] lr: 8.0000e-04 eta: 3:03:09 time: 1.5688 data_time: 0.0036 memory: 5375 grad_norm: 0.0594 loss: 0.1555 loss_sem_seg: 0.1555 2023/05/13 17:01:52 - mmengine - INFO - Epoch(train) [31][ 350/1196] lr: 8.0000e-04 eta: 3:01:48 time: 1.5295 data_time: 0.0033 memory: 4678 grad_norm: 0.0563 loss: 0.1529 loss_sem_seg: 0.1529 2023/05/13 17:03:06 - mmengine - INFO - Epoch(train) [31][ 400/1196] lr: 8.0000e-04 eta: 3:00:27 time: 1.4803 data_time: 0.0033 memory: 4709 grad_norm: 0.0619 loss: 0.1558 loss_sem_seg: 0.1558 2023/05/13 17:04:21 - mmengine - INFO - Epoch(train) [31][ 450/1196] lr: 8.0000e-04 eta: 2:59:06 time: 1.4867 data_time: 0.0035 memory: 4741 grad_norm: 0.0654 loss: 0.1557 loss_sem_seg: 0.1557 2023/05/13 17:05:30 - mmengine - INFO - Epoch(train) [31][ 500/1196] lr: 8.0000e-04 eta: 2:57:44 time: 1.3851 data_time: 0.0034 memory: 4664 grad_norm: 0.0623 loss: 0.1473 loss_sem_seg: 0.1473 2023/05/13 17:06:33 - mmengine - INFO - Epoch(train) [31][ 550/1196] lr: 8.0000e-04 eta: 2:56:21 time: 1.2698 data_time: 0.0033 memory: 5151 grad_norm: 0.0601 loss: 0.1553 loss_sem_seg: 0.1553 2023/05/13 17:07:42 - mmengine - INFO - Epoch(train) [31][ 600/1196] lr: 8.0000e-04 eta: 2:54:59 time: 1.3690 data_time: 0.0035 memory: 4894 grad_norm: 0.0617 loss: 0.1498 loss_sem_seg: 0.1498 2023/05/13 17:08:47 - mmengine - INFO - Epoch(train) [31][ 650/1196] lr: 8.0000e-04 eta: 2:53:37 time: 1.2978 data_time: 0.0035 memory: 4642 grad_norm: 0.0570 loss: 0.1549 loss_sem_seg: 0.1549 2023/05/13 17:09:50 - mmengine - INFO - Epoch(train) [31][ 700/1196] lr: 8.0000e-04 eta: 2:52:14 time: 1.2623 data_time: 0.0033 memory: 4493 grad_norm: 0.0634 loss: 0.1538 loss_sem_seg: 0.1538 2023/05/13 17:10:56 - mmengine - INFO - Epoch(train) [31][ 750/1196] lr: 8.0000e-04 eta: 2:50:52 time: 1.3248 data_time: 0.0033 memory: 4839 grad_norm: 0.0696 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/13 17:12:06 - mmengine - INFO - Epoch(train) [31][ 800/1196] lr: 8.0000e-04 eta: 2:49:30 time: 1.3976 data_time: 0.0034 memory: 4655 grad_norm: 0.0599 loss: 0.1680 loss_sem_seg: 0.1680 2023/05/13 17:13:13 - mmengine - INFO - Epoch(train) [31][ 850/1196] lr: 8.0000e-04 eta: 2:48:09 time: 1.3481 data_time: 0.0034 memory: 4845 grad_norm: 0.0610 loss: 0.1434 loss_sem_seg: 0.1434 2023/05/13 17:14:22 - mmengine - INFO - Epoch(train) [31][ 900/1196] lr: 8.0000e-04 eta: 2:46:47 time: 1.3764 data_time: 0.0035 memory: 4518 grad_norm: 0.0572 loss: 0.1693 loss_sem_seg: 0.1693 2023/05/13 17:15:35 - mmengine - INFO - Epoch(train) [31][ 950/1196] lr: 8.0000e-04 eta: 2:45:26 time: 1.4598 data_time: 0.0034 memory: 4811 grad_norm: 0.0626 loss: 0.1454 loss_sem_seg: 0.1454 2023/05/13 17:16:54 - mmengine - INFO - Epoch(train) [31][1000/1196] lr: 8.0000e-04 eta: 2:44:06 time: 1.5683 data_time: 0.0035 memory: 4616 grad_norm: 0.0621 loss: 0.1597 loss_sem_seg: 0.1597 2023/05/13 17:18:12 - mmengine - INFO - Epoch(train) [31][1050/1196] lr: 8.0000e-04 eta: 2:42:46 time: 1.5652 data_time: 0.0034 memory: 5107 grad_norm: 0.0626 loss: 0.1537 loss_sem_seg: 0.1537 2023/05/13 17:19:29 - mmengine - INFO - Epoch(train) [31][1100/1196] lr: 8.0000e-04 eta: 2:41:26 time: 1.5518 data_time: 0.0034 memory: 4897 grad_norm: 0.0613 loss: 0.1505 loss_sem_seg: 0.1505 2023/05/13 17:20:01 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 17:20:46 - mmengine - INFO - Epoch(train) [31][1150/1196] lr: 8.0000e-04 eta: 2:40:06 time: 1.5383 data_time: 0.0035 memory: 4650 grad_norm: 0.0651 loss: 0.1409 loss_sem_seg: 0.1409 2023/05/13 17:21:58 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 17:21:58 - mmengine - INFO - Saving checkpoint at 31 epochs 2023/05/13 17:22:19 - mmengine - INFO - Epoch(val) [31][ 50/509] eta: 0:02:08 time: 0.2808 data_time: 0.0026 memory: 4731 2023/05/13 17:22:32 - mmengine - INFO - Epoch(val) [31][100/509] eta: 0:01:50 time: 0.2593 data_time: 0.0026 memory: 914 2023/05/13 17:22:44 - mmengine - INFO - Epoch(val) [31][150/509] eta: 0:01:34 time: 0.2467 data_time: 0.0024 memory: 915 2023/05/13 17:22:57 - mmengine - INFO - Epoch(val) [31][200/509] eta: 0:01:20 time: 0.2541 data_time: 0.0025 memory: 901 2023/05/13 17:23:11 - mmengine - INFO - Epoch(val) [31][250/509] eta: 0:01:09 time: 0.2918 data_time: 0.0025 memory: 929 2023/05/13 17:23:23 - mmengine - INFO - Epoch(val) [31][300/509] eta: 0:00:54 time: 0.2266 data_time: 0.0025 memory: 867 2023/05/13 17:23:35 - mmengine - INFO - Epoch(val) [31][350/509] eta: 0:00:41 time: 0.2562 data_time: 0.0021 memory: 891 2023/05/13 17:23:49 - mmengine - INFO - Epoch(val) [31][400/509] eta: 0:00:28 time: 0.2766 data_time: 0.0021 memory: 899 2023/05/13 17:24:02 - mmengine - INFO - Epoch(val) [31][450/509] eta: 0:00:15 time: 0.2480 data_time: 0.0022 memory: 911 2023/05/13 17:24:14 - mmengine - INFO - Epoch(val) [31][500/509] eta: 0:00:02 time: 0.2401 data_time: 0.0019 memory: 893 2023/05/13 17:24:32 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9742 | 0.5496 | 0.8150 | 0.8996 | 0.7876 | 0.7981 | 0.8949 | 0.0709 | 0.9504 | 0.5316 | 0.8325 | 0.0093 | 0.9125 | 0.6603 | 0.8768 | 0.6670 | 0.7269 | 0.6626 | 0.5175 | 0.6914 | 0.9236 | 0.7539 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 17:24:32 - mmengine - INFO - Epoch(val) [31][509/509] car: 0.9742 bicycle: 0.5496 motorcycle: 0.8150 truck: 0.8996 bus: 0.7876 person: 0.7981 bicyclist: 0.8949 motorcyclist: 0.0709 road: 0.9504 parking: 0.5316 sidewalk: 0.8325 other-ground: 0.0093 building: 0.9125 fence: 0.6603 vegetation: 0.8768 trunck: 0.6670 terrian: 0.7269 pole: 0.6626 traffic-sign: 0.5175 miou: 0.6914 acc: 0.9236 acc_cls: 0.7539 data_time: 0.0019 time: 0.2507 2023/05/13 17:25:48 - mmengine - INFO - Epoch(train) [32][ 50/1196] lr: 8.0000e-04 eta: 2:37:32 time: 1.5229 data_time: 0.0042 memory: 4998 grad_norm: 0.0641 loss: 0.1512 loss_sem_seg: 0.1512 2023/05/13 17:27:05 - mmengine - INFO - Epoch(train) [32][ 100/1196] lr: 8.0000e-04 eta: 2:36:12 time: 1.5268 data_time: 0.0034 memory: 4993 grad_norm: 0.0592 loss: 0.1515 loss_sem_seg: 0.1515 2023/05/13 17:28:22 - mmengine - INFO - Epoch(train) [32][ 150/1196] lr: 8.0000e-04 eta: 2:34:52 time: 1.5390 data_time: 0.0033 memory: 4719 grad_norm: 0.0585 loss: 0.1509 loss_sem_seg: 0.1509 2023/05/13 17:29:39 - mmengine - INFO - Epoch(train) [32][ 200/1196] lr: 8.0000e-04 eta: 2:33:32 time: 1.5464 data_time: 0.0034 memory: 4889 grad_norm: 0.0629 loss: 0.1494 loss_sem_seg: 0.1494 2023/05/13 17:30:55 - mmengine - INFO - Epoch(train) [32][ 250/1196] lr: 8.0000e-04 eta: 2:32:11 time: 1.5236 data_time: 0.0034 memory: 4669 grad_norm: 0.0599 loss: 0.1519 loss_sem_seg: 0.1519 2023/05/13 17:32:11 - mmengine - INFO - Epoch(train) [32][ 300/1196] lr: 8.0000e-04 eta: 2:30:51 time: 1.5184 data_time: 0.0035 memory: 4559 grad_norm: 0.0602 loss: 0.1440 loss_sem_seg: 0.1440 2023/05/13 17:33:27 - mmengine - INFO - Epoch(train) [32][ 350/1196] lr: 8.0000e-04 eta: 2:29:31 time: 1.5169 data_time: 0.0034 memory: 4976 grad_norm: 0.0613 loss: 0.1567 loss_sem_seg: 0.1567 2023/05/13 17:34:43 - mmengine - INFO - Epoch(train) [32][ 400/1196] lr: 8.0000e-04 eta: 2:28:11 time: 1.5271 data_time: 0.0035 memory: 4886 grad_norm: 0.0565 loss: 0.1496 loss_sem_seg: 0.1496 2023/05/13 17:36:00 - mmengine - INFO - Epoch(train) [32][ 450/1196] lr: 8.0000e-04 eta: 2:26:51 time: 1.5290 data_time: 0.0034 memory: 4726 grad_norm: 0.0683 loss: 0.1622 loss_sem_seg: 0.1622 2023/05/13 17:37:15 - mmengine - INFO - Epoch(train) [32][ 500/1196] lr: 8.0000e-04 eta: 2:25:30 time: 1.4989 data_time: 0.0034 memory: 4983 grad_norm: 0.0636 loss: 0.1572 loss_sem_seg: 0.1572 2023/05/13 17:38:29 - mmengine - INFO - Epoch(train) [32][ 550/1196] lr: 8.0000e-04 eta: 2:24:10 time: 1.4765 data_time: 0.0034 memory: 4529 grad_norm: 0.0639 loss: 0.1435 loss_sem_seg: 0.1435 2023/05/13 17:39:43 - mmengine - INFO - Epoch(train) [32][ 600/1196] lr: 8.0000e-04 eta: 2:22:49 time: 1.4925 data_time: 0.0036 memory: 4451 grad_norm: 0.0598 loss: 0.1526 loss_sem_seg: 0.1526 2023/05/13 17:40:58 - mmengine - INFO - Epoch(train) [32][ 650/1196] lr: 8.0000e-04 eta: 2:21:29 time: 1.5013 data_time: 0.0034 memory: 4399 grad_norm: 0.0624 loss: 0.1536 loss_sem_seg: 0.1536 2023/05/13 17:42:12 - mmengine - INFO - Epoch(train) [32][ 700/1196] lr: 8.0000e-04 eta: 2:20:09 time: 1.4669 data_time: 0.0034 memory: 4590 grad_norm: 0.0640 loss: 0.1568 loss_sem_seg: 0.1568 2023/05/13 17:43:25 - mmengine - INFO - Epoch(train) [32][ 750/1196] lr: 8.0000e-04 eta: 2:18:48 time: 1.4755 data_time: 0.0034 memory: 4841 grad_norm: 0.0670 loss: 0.1491 loss_sem_seg: 0.1491 2023/05/13 17:44:34 - mmengine - INFO - Epoch(train) [32][ 800/1196] lr: 8.0000e-04 eta: 2:17:27 time: 1.3652 data_time: 0.0033 memory: 4815 grad_norm: 0.0626 loss: 0.1482 loss_sem_seg: 0.1482 2023/05/13 17:45:41 - mmengine - INFO - Epoch(train) [32][ 850/1196] lr: 8.0000e-04 eta: 2:16:06 time: 1.3497 data_time: 0.0033 memory: 4475 grad_norm: 0.0625 loss: 0.1549 loss_sem_seg: 0.1549 2023/05/13 17:46:50 - mmengine - INFO - Epoch(train) [32][ 900/1196] lr: 8.0000e-04 eta: 2:14:45 time: 1.3835 data_time: 0.0033 memory: 4386 grad_norm: 0.0652 loss: 0.1553 loss_sem_seg: 0.1553 2023/05/13 17:47:23 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 17:47:58 - mmengine - INFO - Epoch(train) [32][ 950/1196] lr: 8.0000e-04 eta: 2:13:24 time: 1.3599 data_time: 0.0034 memory: 4786 grad_norm: 0.0586 loss: 0.1589 loss_sem_seg: 0.1589 2023/05/13 17:49:03 - mmengine - INFO - Epoch(train) [32][1000/1196] lr: 8.0000e-04 eta: 2:12:02 time: 1.2981 data_time: 0.0034 memory: 4933 grad_norm: 0.0631 loss: 0.1437 loss_sem_seg: 0.1437 2023/05/13 17:50:05 - mmengine - INFO - Epoch(train) [32][1050/1196] lr: 8.0000e-04 eta: 2:10:40 time: 1.2344 data_time: 0.0033 memory: 4748 grad_norm: 0.0621 loss: 0.1495 loss_sem_seg: 0.1495 2023/05/13 17:51:07 - mmengine - INFO - Epoch(train) [32][1100/1196] lr: 8.0000e-04 eta: 2:09:19 time: 1.2414 data_time: 0.0035 memory: 4503 grad_norm: 0.0611 loss: 0.1442 loss_sem_seg: 0.1442 2023/05/13 17:52:09 - mmengine - INFO - Epoch(train) [32][1150/1196] lr: 8.0000e-04 eta: 2:07:57 time: 1.2291 data_time: 0.0038 memory: 4386 grad_norm: 0.0577 loss: 0.1454 loss_sem_seg: 0.1454 2023/05/13 17:53:07 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 17:53:07 - mmengine - INFO - Saving checkpoint at 32 epochs 2023/05/13 17:53:26 - mmengine - INFO - Epoch(val) [32][ 50/509] eta: 0:01:49 time: 0.2387 data_time: 0.0021 memory: 4503 2023/05/13 17:53:36 - mmengine - INFO - Epoch(val) [32][100/509] eta: 0:01:29 time: 0.1988 data_time: 0.0020 memory: 914 2023/05/13 17:53:45 - mmengine - INFO - Epoch(val) [32][150/509] eta: 0:01:15 time: 0.1906 data_time: 0.0020 memory: 915 2023/05/13 17:53:55 - mmengine - INFO - Epoch(val) [32][200/509] eta: 0:01:04 time: 0.2016 data_time: 0.0019 memory: 901 2023/05/13 17:54:08 - mmengine - INFO - Epoch(val) [32][250/509] eta: 0:00:55 time: 0.2482 data_time: 0.0020 memory: 929 2023/05/13 17:54:18 - mmengine - INFO - Epoch(val) [32][300/509] eta: 0:00:44 time: 0.2037 data_time: 0.0020 memory: 867 2023/05/13 17:54:29 - mmengine - INFO - Epoch(val) [32][350/509] eta: 0:00:34 time: 0.2279 data_time: 0.0020 memory: 891 2023/05/13 17:54:42 - mmengine - INFO - Epoch(val) [32][400/509] eta: 0:00:24 time: 0.2590 data_time: 0.0020 memory: 899 2023/05/13 17:54:55 - mmengine - INFO - Epoch(val) [32][450/509] eta: 0:00:13 time: 0.2474 data_time: 0.0021 memory: 911 2023/05/13 17:55:06 - mmengine - INFO - Epoch(val) [32][500/509] eta: 0:00:02 time: 0.2330 data_time: 0.0019 memory: 893 2023/05/13 17:55:24 - 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 | 0.9696 | 0.5748 | 0.8098 | 0.8730 | 0.6968 | 0.7931 | 0.8887 | 0.0883 | 0.9513 | 0.5784 | 0.8353 | 0.0159 | 0.9144 | 0.6634 | 0.8773 | 0.6864 | 0.7301 | 0.6661 | 0.5197 | 0.6912 | 0.9244 | 0.7583 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 17:55:24 - mmengine - INFO - Epoch(val) [32][509/509] car: 0.9696 bicycle: 0.5748 motorcycle: 0.8098 truck: 0.8730 bus: 0.6968 person: 0.7931 bicyclist: 0.8887 motorcyclist: 0.0883 road: 0.9513 parking: 0.5784 sidewalk: 0.8353 other-ground: 0.0159 building: 0.9144 fence: 0.6634 vegetation: 0.8773 trunck: 0.6864 terrian: 0.7301 pole: 0.6661 traffic-sign: 0.5197 miou: 0.6912 acc: 0.9244 acc_cls: 0.7583 data_time: 0.0019 time: 0.2457 2023/05/13 17:56:38 - mmengine - INFO - Epoch(train) [33][ 50/1196] lr: 8.0000e-05 eta: 2:05:22 time: 1.4748 data_time: 0.0040 memory: 4741 grad_norm: 0.0606 loss: 0.1547 loss_sem_seg: 0.1547 2023/05/13 17:57:54 - mmengine - INFO - Epoch(train) [33][ 100/1196] lr: 8.0000e-05 eta: 2:04:02 time: 1.5229 data_time: 0.0034 memory: 4766 grad_norm: 0.0586 loss: 0.1443 loss_sem_seg: 0.1443 2023/05/13 17:59:08 - mmengine - INFO - Epoch(train) [33][ 150/1196] lr: 8.0000e-05 eta: 2:02:42 time: 1.4772 data_time: 0.0033 memory: 4194 grad_norm: 0.0564 loss: 0.1602 loss_sem_seg: 0.1602 2023/05/13 18:00:22 - mmengine - INFO - Epoch(train) [33][ 200/1196] lr: 8.0000e-05 eta: 2:01:22 time: 1.4699 data_time: 0.0034 memory: 4507 grad_norm: 0.0539 loss: 0.1565 loss_sem_seg: 0.1565 2023/05/13 18:01:36 - mmengine - INFO - Epoch(train) [33][ 250/1196] lr: 8.0000e-05 eta: 2:00:02 time: 1.4939 data_time: 0.0034 memory: 4898 grad_norm: 0.0553 loss: 0.1416 loss_sem_seg: 0.1416 2023/05/13 18:02:51 - mmengine - INFO - Epoch(train) [33][ 300/1196] lr: 8.0000e-05 eta: 1:58:42 time: 1.4995 data_time: 0.0035 memory: 4649 grad_norm: 0.0579 loss: 0.1575 loss_sem_seg: 0.1575 2023/05/13 18:04:05 - mmengine - INFO - Epoch(train) [33][ 350/1196] lr: 8.0000e-05 eta: 1:57:22 time: 1.4844 data_time: 0.0035 memory: 4977 grad_norm: 0.0536 loss: 0.1454 loss_sem_seg: 0.1454 2023/05/13 18:05:18 - mmengine - INFO - Epoch(train) [33][ 400/1196] lr: 8.0000e-05 eta: 1:56:01 time: 1.4573 data_time: 0.0035 memory: 4434 grad_norm: 0.0539 loss: 0.1502 loss_sem_seg: 0.1502 2023/05/13 18:06:33 - mmengine - INFO - Epoch(train) [33][ 450/1196] lr: 8.0000e-05 eta: 1:54:42 time: 1.5020 data_time: 0.0034 memory: 4783 grad_norm: 0.0570 loss: 0.1547 loss_sem_seg: 0.1547 2023/05/13 18:07:48 - mmengine - INFO - Epoch(train) [33][ 500/1196] lr: 8.0000e-05 eta: 1:53:22 time: 1.4872 data_time: 0.0035 memory: 5228 grad_norm: 0.0539 loss: 0.1507 loss_sem_seg: 0.1507 2023/05/13 18:09:03 - mmengine - INFO - Epoch(train) [33][ 550/1196] lr: 8.0000e-05 eta: 1:52:02 time: 1.5069 data_time: 0.0034 memory: 5068 grad_norm: 0.0598 loss: 0.1484 loss_sem_seg: 0.1484 2023/05/13 18:10:18 - mmengine - INFO - Epoch(train) [33][ 600/1196] lr: 8.0000e-05 eta: 1:50:42 time: 1.4878 data_time: 0.0035 memory: 4730 grad_norm: 0.0557 loss: 0.1436 loss_sem_seg: 0.1436 2023/05/13 18:11:32 - mmengine - INFO - Epoch(train) [33][ 650/1196] lr: 8.0000e-05 eta: 1:49:22 time: 1.4889 data_time: 0.0035 memory: 4654 grad_norm: 0.0605 loss: 0.1489 loss_sem_seg: 0.1489 2023/05/13 18:12:46 - mmengine - INFO - Epoch(train) [33][ 700/1196] lr: 8.0000e-05 eta: 1:48:02 time: 1.4809 data_time: 0.0035 memory: 5099 grad_norm: 0.0594 loss: 0.1557 loss_sem_seg: 0.1557 2023/05/13 18:13:28 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 18:14:01 - mmengine - INFO - Epoch(train) [33][ 750/1196] lr: 8.0000e-05 eta: 1:46:42 time: 1.4938 data_time: 0.0035 memory: 5029 grad_norm: 0.0550 loss: 0.1447 loss_sem_seg: 0.1447 2023/05/13 18:15:14 - mmengine - INFO - Epoch(train) [33][ 800/1196] lr: 8.0000e-05 eta: 1:45:22 time: 1.4673 data_time: 0.0034 memory: 4940 grad_norm: 0.0590 loss: 0.1485 loss_sem_seg: 0.1485 2023/05/13 18:16:27 - mmengine - INFO - Epoch(train) [33][ 850/1196] lr: 8.0000e-05 eta: 1:44:02 time: 1.4573 data_time: 0.0035 memory: 4389 grad_norm: 0.0557 loss: 0.1563 loss_sem_seg: 0.1563 2023/05/13 18:17:34 - mmengine - INFO - Epoch(train) [33][ 900/1196] lr: 8.0000e-05 eta: 1:42:42 time: 1.3333 data_time: 0.0034 memory: 4468 grad_norm: 0.0581 loss: 0.1587 loss_sem_seg: 0.1587 2023/05/13 18:18:41 - mmengine - INFO - Epoch(train) [33][ 950/1196] lr: 8.0000e-05 eta: 1:41:21 time: 1.3545 data_time: 0.0034 memory: 5170 grad_norm: 0.0566 loss: 0.1503 loss_sem_seg: 0.1503 2023/05/13 18:19:49 - mmengine - INFO - Epoch(train) [33][1000/1196] lr: 8.0000e-05 eta: 1:40:01 time: 1.3446 data_time: 0.0034 memory: 4687 grad_norm: 0.0558 loss: 0.1413 loss_sem_seg: 0.1413 2023/05/13 18:20:57 - mmengine - INFO - Epoch(train) [33][1050/1196] lr: 8.0000e-05 eta: 1:38:40 time: 1.3659 data_time: 0.0037 memory: 4327 grad_norm: 0.0572 loss: 0.1544 loss_sem_seg: 0.1544 2023/05/13 18:22:05 - mmengine - INFO - Epoch(train) [33][1100/1196] lr: 8.0000e-05 eta: 1:37:20 time: 1.3625 data_time: 0.0036 memory: 4656 grad_norm: 0.0593 loss: 0.1405 loss_sem_seg: 0.1405 2023/05/13 18:23:22 - mmengine - INFO - Epoch(train) [33][1150/1196] lr: 8.0000e-05 eta: 1:36:01 time: 1.5412 data_time: 0.0033 memory: 5071 grad_norm: 0.0578 loss: 0.1403 loss_sem_seg: 0.1403 2023/05/13 18:24:29 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 18:24:29 - mmengine - INFO - Saving checkpoint at 33 epochs 2023/05/13 18:24:50 - mmengine - INFO - Epoch(val) [33][ 50/509] eta: 0:02:09 time: 0.2819 data_time: 0.0021 memory: 5435 2023/05/13 18:25:02 - mmengine - INFO - Epoch(val) [33][100/509] eta: 0:01:47 time: 0.2420 data_time: 0.0021 memory: 914 2023/05/13 18:25:14 - mmengine - INFO - Epoch(val) [33][150/509] eta: 0:01:31 time: 0.2369 data_time: 0.0021 memory: 915 2023/05/13 18:25:26 - mmengine - INFO - Epoch(val) [33][200/509] eta: 0:01:17 time: 0.2388 data_time: 0.0020 memory: 901 2023/05/13 18:25:38 - mmengine - INFO - Epoch(val) [33][250/509] eta: 0:01:05 time: 0.2565 data_time: 0.0021 memory: 929 2023/05/13 18:25:50 - mmengine - INFO - Epoch(val) [33][300/509] eta: 0:00:51 time: 0.2259 data_time: 0.0020 memory: 867 2023/05/13 18:26:02 - mmengine - INFO - Epoch(val) [33][350/509] eta: 0:00:39 time: 0.2436 data_time: 0.0020 memory: 891 2023/05/13 18:26:14 - mmengine - INFO - Epoch(val) [33][400/509] eta: 0:00:26 time: 0.2510 data_time: 0.0020 memory: 899 2023/05/13 18:26:27 - mmengine - INFO - Epoch(val) [33][450/509] eta: 0:00:14 time: 0.2504 data_time: 0.0020 memory: 911 2023/05/13 18:26:39 - mmengine - INFO - Epoch(val) [33][500/509] eta: 0:00:02 time: 0.2458 data_time: 0.0020 memory: 893 2023/05/13 18:26:58 - 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 | 0.9711 | 0.5681 | 0.8169 | 0.8903 | 0.7299 | 0.7888 | 0.8854 | 0.0769 | 0.9509 | 0.5454 | 0.8335 | 0.0100 | 0.9165 | 0.6747 | 0.8758 | 0.6802 | 0.7242 | 0.6636 | 0.5185 | 0.6906 | 0.9237 | 0.7574 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 18:26:58 - mmengine - INFO - Epoch(val) [33][509/509] car: 0.9711 bicycle: 0.5681 motorcycle: 0.8169 truck: 0.8903 bus: 0.7299 person: 0.7888 bicyclist: 0.8854 motorcyclist: 0.0769 road: 0.9509 parking: 0.5454 sidewalk: 0.8335 other-ground: 0.0100 building: 0.9165 fence: 0.6747 vegetation: 0.8758 trunck: 0.6802 terrian: 0.7242 pole: 0.6636 traffic-sign: 0.5185 miou: 0.6906 acc: 0.9237 acc_cls: 0.7574 data_time: 0.0019 time: 0.2534 2023/05/13 18:28:14 - mmengine - INFO - Epoch(train) [34][ 50/1196] lr: 8.0000e-05 eta: 1:33:28 time: 1.5142 data_time: 0.0044 memory: 4394 grad_norm: 0.0572 loss: 0.1488 loss_sem_seg: 0.1488 2023/05/13 18:29:28 - mmengine - INFO - Epoch(train) [34][ 100/1196] lr: 8.0000e-05 eta: 1:32:08 time: 1.4877 data_time: 0.0036 memory: 4681 grad_norm: 0.0550 loss: 0.1498 loss_sem_seg: 0.1498 2023/05/13 18:30:41 - mmengine - INFO - Epoch(train) [34][ 150/1196] lr: 8.0000e-05 eta: 1:30:48 time: 1.4585 data_time: 0.0034 memory: 4606 grad_norm: 0.0596 loss: 0.1541 loss_sem_seg: 0.1541 2023/05/13 18:31:51 - mmengine - INFO - Epoch(train) [34][ 200/1196] lr: 8.0000e-05 eta: 1:29:28 time: 1.4020 data_time: 0.0035 memory: 4776 grad_norm: 0.0568 loss: 0.1484 loss_sem_seg: 0.1484 2023/05/13 18:32:55 - mmengine - INFO - Epoch(train) [34][ 250/1196] lr: 8.0000e-05 eta: 1:28:08 time: 1.2844 data_time: 0.0034 memory: 4925 grad_norm: 0.0592 loss: 0.1412 loss_sem_seg: 0.1412 2023/05/13 18:33:57 - mmengine - INFO - Epoch(train) [34][ 300/1196] lr: 8.0000e-05 eta: 1:26:47 time: 1.2371 data_time: 0.0034 memory: 4836 grad_norm: 0.0577 loss: 0.1481 loss_sem_seg: 0.1481 2023/05/13 18:35:02 - mmengine - INFO - Epoch(train) [34][ 350/1196] lr: 8.0000e-05 eta: 1:25:26 time: 1.2858 data_time: 0.0035 memory: 5088 grad_norm: 0.0556 loss: 0.1440 loss_sem_seg: 0.1440 2023/05/13 18:36:06 - mmengine - INFO - Epoch(train) [34][ 400/1196] lr: 8.0000e-05 eta: 1:24:06 time: 1.2808 data_time: 0.0037 memory: 5006 grad_norm: 0.0598 loss: 0.1486 loss_sem_seg: 0.1486 2023/05/13 18:37:11 - mmengine - INFO - Epoch(train) [34][ 450/1196] lr: 8.0000e-05 eta: 1:22:46 time: 1.3107 data_time: 0.0037 memory: 4671 grad_norm: 0.0553 loss: 0.1468 loss_sem_seg: 0.1468 2023/05/13 18:38:28 - mmengine - INFO - Epoch(train) [34][ 500/1196] lr: 8.0000e-05 eta: 1:21:27 time: 1.5363 data_time: 0.0037 memory: 4501 grad_norm: 0.0590 loss: 0.1526 loss_sem_seg: 0.1526 2023/05/13 18:39:15 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 18:39:42 - mmengine - INFO - Epoch(train) [34][ 550/1196] lr: 8.0000e-05 eta: 1:20:07 time: 1.4870 data_time: 0.0036 memory: 4670 grad_norm: 0.0590 loss: 0.1510 loss_sem_seg: 0.1510 2023/05/13 18:40:55 - mmengine - INFO - Epoch(train) [34][ 600/1196] lr: 8.0000e-05 eta: 1:18:47 time: 1.4484 data_time: 0.0035 memory: 4672 grad_norm: 0.0547 loss: 0.1420 loss_sem_seg: 0.1420 2023/05/13 18:42:09 - mmengine - INFO - Epoch(train) [34][ 650/1196] lr: 8.0000e-05 eta: 1:17:28 time: 1.4795 data_time: 0.0033 memory: 4513 grad_norm: 0.0586 loss: 0.1553 loss_sem_seg: 0.1553 2023/05/13 18:43:23 - mmengine - INFO - Epoch(train) [34][ 700/1196] lr: 8.0000e-05 eta: 1:16:09 time: 1.4852 data_time: 0.0034 memory: 4543 grad_norm: 0.0571 loss: 0.1455 loss_sem_seg: 0.1455 2023/05/13 18:44:25 - mmengine - INFO - Epoch(train) [34][ 750/1196] lr: 8.0000e-05 eta: 1:14:48 time: 1.2474 data_time: 0.0034 memory: 4572 grad_norm: 0.0593 loss: 0.1353 loss_sem_seg: 0.1353 2023/05/13 18:45:28 - mmengine - INFO - Epoch(train) [34][ 800/1196] lr: 8.0000e-05 eta: 1:13:28 time: 1.2457 data_time: 0.0037 memory: 5002 grad_norm: 0.0565 loss: 0.1470 loss_sem_seg: 0.1470 2023/05/13 18:46:31 - mmengine - INFO - Epoch(train) [34][ 850/1196] lr: 8.0000e-05 eta: 1:12:08 time: 1.2692 data_time: 0.0038 memory: 4752 grad_norm: 0.0571 loss: 0.1430 loss_sem_seg: 0.1430 2023/05/13 18:47:34 - mmengine - INFO - Epoch(train) [34][ 900/1196] lr: 8.0000e-05 eta: 1:10:48 time: 1.2515 data_time: 0.0037 memory: 4466 grad_norm: 0.0564 loss: 0.1589 loss_sem_seg: 0.1589 2023/05/13 18:48:33 - mmengine - INFO - Epoch(train) [34][ 950/1196] lr: 8.0000e-05 eta: 1:09:27 time: 1.1818 data_time: 0.0036 memory: 5072 grad_norm: 0.0574 loss: 0.1502 loss_sem_seg: 0.1502 2023/05/13 18:49:29 - mmengine - INFO - Epoch(train) [34][1000/1196] lr: 8.0000e-05 eta: 1:08:07 time: 1.1285 data_time: 0.0037 memory: 4775 grad_norm: 0.0570 loss: 0.1540 loss_sem_seg: 0.1540 2023/05/13 18:50:38 - mmengine - INFO - Epoch(train) [34][1050/1196] lr: 8.0000e-05 eta: 1:06:47 time: 1.3779 data_time: 0.0036 memory: 4790 grad_norm: 0.0590 loss: 0.1467 loss_sem_seg: 0.1467 2023/05/13 18:51:47 - mmengine - INFO - Epoch(train) [34][1100/1196] lr: 8.0000e-05 eta: 1:05:28 time: 1.3705 data_time: 0.0041 memory: 4804 grad_norm: 0.0572 loss: 0.1529 loss_sem_seg: 0.1529 2023/05/13 18:52:54 - mmengine - INFO - Epoch(train) [34][1150/1196] lr: 8.0000e-05 eta: 1:04:08 time: 1.3512 data_time: 0.0041 memory: 4582 grad_norm: 0.0540 loss: 0.1433 loss_sem_seg: 0.1433 2023/05/13 18:54:01 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 18:54:01 - mmengine - INFO - Saving checkpoint at 34 epochs 2023/05/13 18:54:21 - mmengine - INFO - Epoch(val) [34][ 50/509] eta: 0:02:05 time: 0.2741 data_time: 0.0021 memory: 5242 2023/05/13 18:54:33 - mmengine - INFO - Epoch(val) [34][100/509] eta: 0:01:47 time: 0.2497 data_time: 0.0021 memory: 914 2023/05/13 18:54:44 - mmengine - INFO - Epoch(val) [34][150/509] eta: 0:01:29 time: 0.2201 data_time: 0.0020 memory: 915 2023/05/13 18:54:56 - mmengine - INFO - Epoch(val) [34][200/509] eta: 0:01:16 time: 0.2431 data_time: 0.0020 memory: 901 2023/05/13 18:55:09 - mmengine - INFO - Epoch(val) [34][250/509] eta: 0:01:04 time: 0.2621 data_time: 0.0021 memory: 929 2023/05/13 18:55:21 - mmengine - INFO - Epoch(val) [34][300/509] eta: 0:00:51 time: 0.2338 data_time: 0.0021 memory: 867 2023/05/13 18:55:33 - mmengine - INFO - Epoch(val) [34][350/509] eta: 0:00:38 time: 0.2330 data_time: 0.0020 memory: 891 2023/05/13 18:55:45 - mmengine - INFO - Epoch(val) [34][400/509] eta: 0:00:26 time: 0.2433 data_time: 0.0020 memory: 899 2023/05/13 18:55:58 - mmengine - INFO - Epoch(val) [34][450/509] eta: 0:00:14 time: 0.2524 data_time: 0.0021 memory: 911 2023/05/13 18:56:10 - mmengine - INFO - Epoch(val) [34][500/509] eta: 0:00:02 time: 0.2402 data_time: 0.0021 memory: 893 2023/05/13 18:56:28 - 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 | 0.9719 | 0.5632 | 0.8173 | 0.8821 | 0.7434 | 0.7943 | 0.8951 | 0.0831 | 0.9499 | 0.5346 | 0.8322 | 0.0132 | 0.9139 | 0.6664 | 0.8740 | 0.6873 | 0.7184 | 0.6630 | 0.5189 | 0.6906 | 0.9226 | 0.7560 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 18:56:28 - mmengine - INFO - Epoch(val) [34][509/509] car: 0.9719 bicycle: 0.5632 motorcycle: 0.8173 truck: 0.8821 bus: 0.7434 person: 0.7943 bicyclist: 0.8951 motorcyclist: 0.0831 road: 0.9499 parking: 0.5346 sidewalk: 0.8322 other-ground: 0.0132 building: 0.9139 fence: 0.6664 vegetation: 0.8740 trunck: 0.6873 terrian: 0.7184 pole: 0.6630 traffic-sign: 0.5189 miou: 0.6906 acc: 0.9226 acc_cls: 0.7560 data_time: 0.0019 time: 0.2431 2023/05/13 18:57:42 - mmengine - INFO - Epoch(train) [35][ 50/1196] lr: 8.0000e-05 eta: 1:01:36 time: 1.4730 data_time: 0.0044 memory: 5066 grad_norm: 0.0627 loss: 0.1491 loss_sem_seg: 0.1491 2023/05/13 18:58:55 - mmengine - INFO - Epoch(train) [35][ 100/1196] lr: 8.0000e-05 eta: 1:00:17 time: 1.4592 data_time: 0.0035 memory: 4711 grad_norm: 0.0554 loss: 0.1398 loss_sem_seg: 0.1398 2023/05/13 19:00:09 - mmengine - INFO - Epoch(train) [35][ 150/1196] lr: 8.0000e-05 eta: 0:58:58 time: 1.4862 data_time: 0.0036 memory: 4601 grad_norm: 0.0562 loss: 0.1560 loss_sem_seg: 0.1560 2023/05/13 19:01:24 - mmengine - INFO - Epoch(train) [35][ 200/1196] lr: 8.0000e-05 eta: 0:57:38 time: 1.5045 data_time: 0.0034 memory: 4854 grad_norm: 0.0575 loss: 0.1515 loss_sem_seg: 0.1515 2023/05/13 19:02:38 - mmengine - INFO - Epoch(train) [35][ 250/1196] lr: 8.0000e-05 eta: 0:56:19 time: 1.4852 data_time: 0.0034 memory: 4657 grad_norm: 0.0547 loss: 0.1461 loss_sem_seg: 0.1461 2023/05/13 19:03:52 - mmengine - INFO - Epoch(train) [35][ 300/1196] lr: 8.0000e-05 eta: 0:55:00 time: 1.4676 data_time: 0.0033 memory: 4793 grad_norm: 0.0565 loss: 0.1527 loss_sem_seg: 0.1527 2023/05/13 19:04:45 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 19:05:06 - mmengine - INFO - Epoch(train) [35][ 350/1196] lr: 8.0000e-05 eta: 0:53:41 time: 1.4791 data_time: 0.0034 memory: 4516 grad_norm: 0.0577 loss: 0.1488 loss_sem_seg: 0.1488 2023/05/13 19:06:20 - mmengine - INFO - Epoch(train) [35][ 400/1196] lr: 8.0000e-05 eta: 0:52:22 time: 1.4775 data_time: 0.0034 memory: 4637 grad_norm: 0.0547 loss: 0.1456 loss_sem_seg: 0.1456 2023/05/13 19:07:34 - mmengine - INFO - Epoch(train) [35][ 450/1196] lr: 8.0000e-05 eta: 0:51:03 time: 1.4846 data_time: 0.0034 memory: 4642 grad_norm: 0.0569 loss: 0.1486 loss_sem_seg: 0.1486 2023/05/13 19:08:47 - mmengine - INFO - Epoch(train) [35][ 500/1196] lr: 8.0000e-05 eta: 0:49:44 time: 1.4620 data_time: 0.0037 memory: 4794 grad_norm: 0.0592 loss: 0.1500 loss_sem_seg: 0.1500 2023/05/13 19:10:00 - mmengine - INFO - Epoch(train) [35][ 550/1196] lr: 8.0000e-05 eta: 0:48:25 time: 1.4704 data_time: 0.0034 memory: 4674 grad_norm: 0.0529 loss: 0.1438 loss_sem_seg: 0.1438 2023/05/13 19:11:14 - mmengine - INFO - Epoch(train) [35][ 600/1196] lr: 8.0000e-05 eta: 0:47:05 time: 1.4609 data_time: 0.0034 memory: 4937 grad_norm: 0.0570 loss: 0.1430 loss_sem_seg: 0.1430 2023/05/13 19:12:28 - mmengine - INFO - Epoch(train) [35][ 650/1196] lr: 8.0000e-05 eta: 0:45:46 time: 1.4955 data_time: 0.0034 memory: 4918 grad_norm: 0.0533 loss: 0.1415 loss_sem_seg: 0.1415 2023/05/13 19:13:38 - mmengine - INFO - Epoch(train) [35][ 700/1196] lr: 8.0000e-05 eta: 0:44:27 time: 1.3995 data_time: 0.0035 memory: 4936 grad_norm: 0.0581 loss: 0.1529 loss_sem_seg: 0.1529 2023/05/13 19:14:42 - mmengine - INFO - Epoch(train) [35][ 750/1196] lr: 8.0000e-05 eta: 0:43:08 time: 1.2674 data_time: 0.0034 memory: 4425 grad_norm: 0.0551 loss: 0.1510 loss_sem_seg: 0.1510 2023/05/13 19:15:45 - mmengine - INFO - Epoch(train) [35][ 800/1196] lr: 8.0000e-05 eta: 0:41:48 time: 1.2641 data_time: 0.0034 memory: 4502 grad_norm: 0.0556 loss: 0.1461 loss_sem_seg: 0.1461 2023/05/13 19:16:47 - mmengine - INFO - Epoch(train) [35][ 850/1196] lr: 8.0000e-05 eta: 0:40:29 time: 1.2412 data_time: 0.0038 memory: 4826 grad_norm: 0.0590 loss: 0.1585 loss_sem_seg: 0.1585 2023/05/13 19:17:52 - mmengine - INFO - Epoch(train) [35][ 900/1196] lr: 8.0000e-05 eta: 0:39:10 time: 1.2947 data_time: 0.0034 memory: 4755 grad_norm: 0.0585 loss: 0.1578 loss_sem_seg: 0.1578 2023/05/13 19:18:58 - mmengine - INFO - Epoch(train) [35][ 950/1196] lr: 8.0000e-05 eta: 0:37:50 time: 1.3350 data_time: 0.0035 memory: 4657 grad_norm: 0.0556 loss: 0.1432 loss_sem_seg: 0.1432 2023/05/13 19:20:14 - mmengine - INFO - Epoch(train) [35][1000/1196] lr: 8.0000e-05 eta: 0:36:32 time: 1.5067 data_time: 0.0036 memory: 5046 grad_norm: 0.0543 loss: 0.1430 loss_sem_seg: 0.1430 2023/05/13 19:21:21 - mmengine - INFO - Epoch(train) [35][1050/1196] lr: 8.0000e-05 eta: 0:35:12 time: 1.3512 data_time: 0.0034 memory: 4671 grad_norm: 0.0567 loss: 0.1445 loss_sem_seg: 0.1445 2023/05/13 19:22:28 - mmengine - INFO - Epoch(train) [35][1100/1196] lr: 8.0000e-05 eta: 0:33:53 time: 1.3414 data_time: 0.0034 memory: 4749 grad_norm: 0.0596 loss: 0.1423 loss_sem_seg: 0.1423 2023/05/13 19:23:36 - mmengine - INFO - Epoch(train) [35][1150/1196] lr: 8.0000e-05 eta: 0:32:34 time: 1.3508 data_time: 0.0034 memory: 4608 grad_norm: 0.0567 loss: 0.1537 loss_sem_seg: 0.1537 2023/05/13 19:24:38 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 19:24:38 - mmengine - INFO - Saving checkpoint at 35 epochs 2023/05/13 19:24:55 - mmengine - INFO - Epoch(val) [35][ 50/509] eta: 0:01:45 time: 0.2288 data_time: 0.0021 memory: 4763 2023/05/13 19:25:06 - mmengine - INFO - Epoch(val) [35][100/509] eta: 0:01:31 time: 0.2204 data_time: 0.0020 memory: 914 2023/05/13 19:25:16 - mmengine - INFO - Epoch(val) [35][150/509] eta: 0:01:18 time: 0.2040 data_time: 0.0020 memory: 915 2023/05/13 19:25:26 - mmengine - INFO - Epoch(val) [35][200/509] eta: 0:01:05 time: 0.1945 data_time: 0.0020 memory: 901 2023/05/13 19:25:37 - mmengine - INFO - Epoch(val) [35][250/509] eta: 0:00:55 time: 0.2221 data_time: 0.0020 memory: 929 2023/05/13 19:25:46 - mmengine - INFO - Epoch(val) [35][300/509] eta: 0:00:43 time: 0.1750 data_time: 0.0021 memory: 867 2023/05/13 19:25:58 - mmengine - INFO - Epoch(val) [35][350/509] eta: 0:00:33 time: 0.2353 data_time: 0.0020 memory: 891 2023/05/13 19:26:10 - mmengine - INFO - Epoch(val) [35][400/509] eta: 0:00:23 time: 0.2445 data_time: 0.0020 memory: 899 2023/05/13 19:26:22 - mmengine - INFO - Epoch(val) [35][450/509] eta: 0:00:12 time: 0.2306 data_time: 0.0021 memory: 911 2023/05/13 19:26:34 - mmengine - INFO - Epoch(val) [35][500/509] eta: 0:00:01 time: 0.2404 data_time: 0.0021 memory: 893 2023/05/13 19:26:54 - 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 | 0.9696 | 0.5635 | 0.8144 | 0.8879 | 0.7084 | 0.7974 | 0.8932 | 0.0759 | 0.9509 | 0.5470 | 0.8337 | 0.0143 | 0.9160 | 0.6735 | 0.8765 | 0.6835 | 0.7256 | 0.6643 | 0.5217 | 0.6904 | 0.9239 | 0.7557 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 19:26:54 - mmengine - INFO - Epoch(val) [35][509/509] car: 0.9696 bicycle: 0.5635 motorcycle: 0.8144 truck: 0.8879 bus: 0.7084 person: 0.7974 bicyclist: 0.8932 motorcyclist: 0.0759 road: 0.9509 parking: 0.5470 sidewalk: 0.8337 other-ground: 0.0143 building: 0.9160 fence: 0.6735 vegetation: 0.8765 trunck: 0.6835 terrian: 0.7256 pole: 0.6643 traffic-sign: 0.5217 miou: 0.6904 acc: 0.9239 acc_cls: 0.7557 data_time: 0.0020 time: 0.2512 2023/05/13 19:28:08 - mmengine - INFO - Epoch(train) [36][ 50/1196] lr: 8.0000e-05 eta: 0:30:03 time: 1.4845 data_time: 0.0045 memory: 4562 grad_norm: 0.0588 loss: 0.1404 loss_sem_seg: 0.1404 2023/05/13 19:29:21 - mmengine - INFO - Epoch(train) [36][ 100/1196] lr: 8.0000e-05 eta: 0:28:44 time: 1.4661 data_time: 0.0036 memory: 4430 grad_norm: 0.0606 loss: 0.1479 loss_sem_seg: 0.1479 2023/05/13 19:30:20 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 19:30:35 - mmengine - INFO - Epoch(train) [36][ 150/1196] lr: 8.0000e-05 eta: 0:27:25 time: 1.4784 data_time: 0.0040 memory: 4932 grad_norm: 0.0576 loss: 0.1539 loss_sem_seg: 0.1539 2023/05/13 19:31:49 - mmengine - INFO - Epoch(train) [36][ 200/1196] lr: 8.0000e-05 eta: 0:26:06 time: 1.4706 data_time: 0.0035 memory: 4621 grad_norm: 0.0552 loss: 0.1510 loss_sem_seg: 0.1510 2023/05/13 19:33:02 - mmengine - INFO - Epoch(train) [36][ 250/1196] lr: 8.0000e-05 eta: 0:24:48 time: 1.4689 data_time: 0.0035 memory: 4546 grad_norm: 0.0588 loss: 0.1482 loss_sem_seg: 0.1482 2023/05/13 19:34:18 - mmengine - INFO - Epoch(train) [36][ 300/1196] lr: 8.0000e-05 eta: 0:23:29 time: 1.5042 data_time: 0.0035 memory: 4947 grad_norm: 0.0579 loss: 0.1522 loss_sem_seg: 0.1522 2023/05/13 19:35:33 - mmengine - INFO - Epoch(train) [36][ 350/1196] lr: 8.0000e-05 eta: 0:22:10 time: 1.4997 data_time: 0.0035 memory: 4670 grad_norm: 0.0554 loss: 0.1452 loss_sem_seg: 0.1452 2023/05/13 19:36:48 - mmengine - INFO - Epoch(train) [36][ 400/1196] lr: 8.0000e-05 eta: 0:20:51 time: 1.4997 data_time: 0.0035 memory: 4620 grad_norm: 0.0553 loss: 0.1453 loss_sem_seg: 0.1453 2023/05/13 19:38:01 - mmengine - INFO - Epoch(train) [36][ 450/1196] lr: 8.0000e-05 eta: 0:19:33 time: 1.4718 data_time: 0.0034 memory: 4777 grad_norm: 0.0560 loss: 0.1450 loss_sem_seg: 0.1450 2023/05/13 19:39:15 - mmengine - INFO - Epoch(train) [36][ 500/1196] lr: 8.0000e-05 eta: 0:18:14 time: 1.4670 data_time: 0.0033 memory: 4711 grad_norm: 0.0596 loss: 0.1516 loss_sem_seg: 0.1516 2023/05/13 19:40:29 - mmengine - INFO - Epoch(train) [36][ 550/1196] lr: 8.0000e-05 eta: 0:16:55 time: 1.4981 data_time: 0.0034 memory: 4769 grad_norm: 0.0562 loss: 0.1593 loss_sem_seg: 0.1593 2023/05/13 19:41:44 - mmengine - INFO - Epoch(train) [36][ 600/1196] lr: 8.0000e-05 eta: 0:15:37 time: 1.4937 data_time: 0.0034 memory: 5440 grad_norm: 0.0606 loss: 0.1330 loss_sem_seg: 0.1330 2023/05/13 19:42:58 - mmengine - INFO - Epoch(train) [36][ 650/1196] lr: 8.0000e-05 eta: 0:14:18 time: 1.4756 data_time: 0.0035 memory: 4898 grad_norm: 0.0544 loss: 0.1488 loss_sem_seg: 0.1488 2023/05/13 19:44:13 - mmengine - INFO - Epoch(train) [36][ 700/1196] lr: 8.0000e-05 eta: 0:12:59 time: 1.5004 data_time: 0.0034 memory: 4901 grad_norm: 0.0582 loss: 0.1489 loss_sem_seg: 0.1489 2023/05/13 19:45:29 - mmengine - INFO - Epoch(train) [36][ 750/1196] lr: 8.0000e-05 eta: 0:11:41 time: 1.5231 data_time: 0.0034 memory: 4724 grad_norm: 0.0582 loss: 0.1642 loss_sem_seg: 0.1642 2023/05/13 19:46:44 - mmengine - INFO - Epoch(train) [36][ 800/1196] lr: 8.0000e-05 eta: 0:10:22 time: 1.5059 data_time: 0.0034 memory: 4648 grad_norm: 0.0546 loss: 0.1372 loss_sem_seg: 0.1372 2023/05/13 19:47:58 - mmengine - INFO - Epoch(train) [36][ 850/1196] lr: 8.0000e-05 eta: 0:09:03 time: 1.4689 data_time: 0.0034 memory: 4304 grad_norm: 0.0558 loss: 0.1472 loss_sem_seg: 0.1472 2023/05/13 19:49:13 - mmengine - INFO - Epoch(train) [36][ 900/1196] lr: 8.0000e-05 eta: 0:07:45 time: 1.4992 data_time: 0.0035 memory: 4418 grad_norm: 0.0593 loss: 0.1582 loss_sem_seg: 0.1582 2023/05/13 19:50:27 - mmengine - INFO - Epoch(train) [36][ 950/1196] lr: 8.0000e-05 eta: 0:06:26 time: 1.4754 data_time: 0.0036 memory: 4489 grad_norm: 0.0558 loss: 0.1472 loss_sem_seg: 0.1472 2023/05/13 19:51:40 - mmengine - INFO - Epoch(train) [36][1000/1196] lr: 8.0000e-05 eta: 0:05:08 time: 1.4675 data_time: 0.0034 memory: 4639 grad_norm: 0.0591 loss: 0.1487 loss_sem_seg: 0.1487 2023/05/13 19:52:54 - mmengine - INFO - Epoch(train) [36][1050/1196] lr: 8.0000e-05 eta: 0:03:49 time: 1.4886 data_time: 0.0035 memory: 4630 grad_norm: 0.0603 loss: 0.1485 loss_sem_seg: 0.1485 2023/05/13 19:54:04 - mmengine - INFO - Epoch(train) [36][1100/1196] lr: 8.0000e-05 eta: 0:02:30 time: 1.4003 data_time: 0.0035 memory: 4809 grad_norm: 0.0568 loss: 0.1463 loss_sem_seg: 0.1463 2023/05/13 19:54:58 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 19:55:12 - mmengine - INFO - Epoch(train) [36][1150/1196] lr: 8.0000e-05 eta: 0:01:12 time: 1.3532 data_time: 0.0034 memory: 4751 grad_norm: 0.0590 loss: 0.1514 loss_sem_seg: 0.1514 2023/05/13 19:56:13 - mmengine - INFO - Exp name: minkunet34_w32_spconv_8xb2-lpmix-3x_semantickitti_20230512_233817 2023/05/13 19:56:13 - mmengine - INFO - Saving checkpoint at 36 epochs 2023/05/13 19:56:29 - mmengine - INFO - Epoch(val) [36][ 50/509] eta: 0:01:25 time: 0.1864 data_time: 0.0020 memory: 4721 2023/05/13 19:56:37 - mmengine - INFO - Epoch(val) [36][100/509] eta: 0:01:11 time: 0.1621 data_time: 0.0019 memory: 914 2023/05/13 19:56:45 - mmengine - INFO - Epoch(val) [36][150/509] eta: 0:00:59 time: 0.1503 data_time: 0.0019 memory: 915 2023/05/13 19:56:52 - mmengine - INFO - Epoch(val) [36][200/509] eta: 0:00:50 time: 0.1554 data_time: 0.0020 memory: 901 2023/05/13 19:57:01 - mmengine - INFO - Epoch(val) [36][250/509] eta: 0:00:42 time: 0.1643 data_time: 0.0020 memory: 929 2023/05/13 19:57:08 - mmengine - INFO - Epoch(val) [36][300/509] eta: 0:00:33 time: 0.1416 data_time: 0.0020 memory: 867 2023/05/13 19:57:16 - mmengine - INFO - Epoch(val) [36][350/509] eta: 0:00:25 time: 0.1766 data_time: 0.0020 memory: 891 2023/05/13 19:57:26 - mmengine - INFO - Epoch(val) [36][400/509] eta: 0:00:18 time: 0.1859 data_time: 0.0020 memory: 899 2023/05/13 19:57:34 - mmengine - INFO - Epoch(val) [36][450/509] eta: 0:00:09 time: 0.1594 data_time: 0.0020 memory: 911 2023/05/13 19:57:43 - mmengine - INFO - Epoch(val) [36][500/509] eta: 0:00:01 time: 0.1904 data_time: 0.0020 memory: 893 2023/05/13 19:58:01 - 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 | 0.9711 | 0.5619 | 0.8178 | 0.8729 | 0.7333 | 0.7925 | 0.8910 | 0.0753 | 0.9503 | 0.5386 | 0.8331 | 0.0055 | 0.9150 | 0.6686 | 0.8755 | 0.6897 | 0.7226 | 0.6645 | 0.5228 | 0.6896 | 0.9233 | 0.7570 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/13 19:58:01 - mmengine - INFO - Epoch(val) [36][509/509] car: 0.9711 bicycle: 0.5619 motorcycle: 0.8178 truck: 0.8729 bus: 0.7333 person: 0.7925 bicyclist: 0.8910 motorcyclist: 0.0753 road: 0.9503 parking: 0.5386 sidewalk: 0.8331 other-ground: 0.0055 building: 0.9150 fence: 0.6686 vegetation: 0.8755 trunck: 0.6897 terrian: 0.7226 pole: 0.6645 traffic-sign: 0.5228 miou: 0.6896 acc: 0.9233 acc_cls: 0.7570 data_time: 0.0019 time: 0.2009