2023/05/14 20:22:46 - 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: 1700996907 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 ------------------------------------------------------------ 2023/05/14 20:22:51 - 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='minkowski'), 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_minkowski_8xb2-lpmix-3x_semantickitti' 2023/05/14 20:22:56 - 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 -------------------- 2023/05/14 20:23:01 - mmengine - WARNING - The prefix is not set in metric class SegMetric. Name of parameter - Initialization information backbone.conv_input.0.net.0.kernel - torch.Size([27, 4, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.0.net.1.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.0.net.1.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.net.0.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.net.1.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.conv_input.1.net.1.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.net.0.kernel - torch.Size([8, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.net.1.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.0.net.1.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.conv1.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.norm1.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.norm1.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.conv2.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.norm2.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.1.norm2.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.conv1.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.norm1.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.norm1.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.conv2.kernel - torch.Size([27, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.norm2.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.0.2.norm2.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.net.0.kernel - torch.Size([8, 32, 32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.net.1.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.0.net.1.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.conv1.kernel - torch.Size([27, 32, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.norm1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.norm1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.conv2.kernel - torch.Size([27, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.norm2.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.norm2.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.downsample.net.0.kernel - torch.Size([32, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.downsample.net.1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.1.downsample.net.1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.conv1.kernel - torch.Size([27, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.norm1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.norm1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.conv2.kernel - torch.Size([27, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.norm2.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.2.norm2.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.conv1.kernel - torch.Size([27, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.norm1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.norm1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.conv2.kernel - torch.Size([27, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.norm2.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.1.3.norm2.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.net.0.kernel - torch.Size([8, 64, 64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.net.1.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.0.net.1.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.conv1.kernel - torch.Size([27, 64, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.norm1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.norm1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.conv2.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.norm2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.norm2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.downsample.net.0.kernel - torch.Size([64, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.downsample.net.1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.1.downsample.net.1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.conv1.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.norm1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.norm1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.conv2.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.norm2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.2.norm2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.conv1.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.norm1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.norm1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.conv2.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.norm2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.3.norm2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.conv1.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.norm1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.norm1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.conv2.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.norm2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.2.4.norm2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.net.0.kernel - torch.Size([8, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.net.1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.0.net.1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.conv1.kernel - torch.Size([27, 128, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.norm1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.norm1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.conv2.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.norm2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.norm2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.downsample.net.0.kernel - torch.Size([128, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.downsample.net.1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.1.downsample.net.1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.conv1.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.norm1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.norm1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.conv2.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.norm2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.2.norm2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.conv1.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.norm1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.norm1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.conv2.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.norm2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.3.norm2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.conv1.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.norm1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.norm1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.conv2.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.norm2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.4.norm2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.conv1.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.norm1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.norm1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.conv2.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.norm2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.5.norm2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.conv1.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.norm1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.norm1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.conv2.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.norm2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.encoder.3.6.norm2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.net.0.kernel - torch.Size([8, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.net.1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.0.net.1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.conv1.kernel - torch.Size([27, 384, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.norm1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.norm1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.conv2.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.norm2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.norm2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.downsample.net.0.kernel - torch.Size([384, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.downsample.net.1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.0.downsample.net.1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.conv1.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.norm1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.norm1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.conv2.kernel - torch.Size([27, 256, 256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.norm2.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.0.1.1.norm2.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.net.0.kernel - torch.Size([8, 256, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.net.1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.0.net.1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.conv1.kernel - torch.Size([27, 192, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.norm1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.norm1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.conv2.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.norm2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.norm2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.downsample.net.0.kernel - torch.Size([192, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.downsample.net.1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.0.downsample.net.1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.conv1.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.norm1.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.norm1.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.conv2.kernel - torch.Size([27, 128, 128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.norm2.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.1.1.1.norm2.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.net.0.kernel - torch.Size([8, 128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.net.1.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.0.net.1.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.conv1.kernel - torch.Size([27, 128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.norm1.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.norm1.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.conv2.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.norm2.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.norm2.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.downsample.net.0.kernel - torch.Size([128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.downsample.net.1.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.0.downsample.net.1.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.conv1.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.norm1.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.norm1.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.conv2.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.norm2.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.2.1.1.norm2.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.net.0.kernel - torch.Size([8, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.net.1.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.0.net.1.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.conv1.kernel - torch.Size([27, 128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.norm1.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.norm1.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.conv2.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.norm2.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.norm2.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.downsample.net.0.kernel - torch.Size([128, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.downsample.net.1.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.0.downsample.net.1.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.conv1.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.norm1.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.norm1.bn.bias - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.conv2.kernel - torch.Size([27, 96, 96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.norm2.bn.weight - torch.Size([96]): The value is the same before and after calling `init_weights` of MinkUNet backbone.decoder.3.1.1.norm2.bn.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 2023/05/14 20:23:06 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/05/14 20:23:06 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/05/14 20:23:06 - mmengine - INFO - Checkpoints will be saved to /nvme/sunjiahao/projects/mmdetection3d/work_dirs/minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti. 2023/05/14 20:24:30 - mmengine - INFO - Epoch(train) [1][ 50/1196] lr: 8.0000e-03 eta: 20:13:11 time: 1.6926 data_time: 0.0066 memory: 5219 grad_norm: 0.7135 loss: 1.5027 loss_sem_seg: 1.5027 2023/05/14 20:25:54 - mmengine - INFO - Epoch(train) [1][ 100/1196] lr: 8.0000e-03 eta: 20:02:50 time: 1.6676 data_time: 0.0033 memory: 4841 grad_norm: 0.6047 loss: 1.0268 loss_sem_seg: 1.0268 2023/05/14 20:27:17 - mmengine - INFO - Epoch(train) [1][ 150/1196] lr: 8.0000e-03 eta: 20:00:13 time: 1.6750 data_time: 0.0034 memory: 4665 grad_norm: 0.6420 loss: 0.9138 loss_sem_seg: 0.9138 2023/05/14 20:28:40 - mmengine - INFO - Epoch(train) [1][ 200/1196] lr: 8.0000e-03 eta: 19:55:57 time: 1.6623 data_time: 0.0033 memory: 4473 grad_norm: 0.7099 loss: 0.8278 loss_sem_seg: 0.8278 2023/05/14 20:30:13 - mmengine - INFO - Epoch(train) [1][ 250/1196] lr: 8.0000e-03 eta: 20:19:31 time: 1.8494 data_time: 0.0035 memory: 4665 grad_norm: 0.8428 loss: 0.7361 loss_sem_seg: 0.7361 2023/05/14 20:31:36 - mmengine - INFO - Epoch(train) [1][ 300/1196] lr: 8.0000e-03 eta: 20:12:42 time: 1.6640 data_time: 0.0034 memory: 4991 grad_norm: 0.9768 loss: 0.7426 loss_sem_seg: 0.7426 2023/05/14 20:33:00 - mmengine - INFO - Epoch(train) [1][ 350/1196] lr: 8.0000e-03 eta: 20:09:02 time: 1.6797 data_time: 0.0034 memory: 4806 grad_norm: 0.8700 loss: 0.6578 loss_sem_seg: 0.6578 2023/05/14 20:34:24 - mmengine - INFO - Epoch(train) [1][ 400/1196] lr: 8.0000e-03 eta: 20:05:16 time: 1.6722 data_time: 0.0032 memory: 5101 grad_norm: 0.7273 loss: 0.6254 loss_sem_seg: 0.6254 2023/05/14 20:35:49 - mmengine - INFO - Epoch(train) [1][ 450/1196] lr: 8.0000e-03 eta: 20:04:16 time: 1.7005 data_time: 0.0032 memory: 4832 grad_norm: 0.7735 loss: 0.6394 loss_sem_seg: 0.6394 2023/05/14 20:37:16 - mmengine - INFO - Epoch(train) [1][ 500/1196] lr: 8.0000e-03 eta: 20:06:49 time: 1.7519 data_time: 0.0035 memory: 4709 grad_norm: 0.6530 loss: 0.5709 loss_sem_seg: 0.5709 2023/05/14 20:38:42 - mmengine - INFO - Epoch(train) [1][ 550/1196] lr: 8.0000e-03 eta: 20:05:38 time: 1.7050 data_time: 0.0032 memory: 4810 grad_norm: 0.6396 loss: 0.5605 loss_sem_seg: 0.5605 2023/05/14 20:40:07 - mmengine - INFO - Epoch(train) [1][ 600/1196] lr: 8.0000e-03 eta: 20:04:44 time: 1.7107 data_time: 0.0033 memory: 4814 grad_norm: 0.6849 loss: 0.5846 loss_sem_seg: 0.5846 2023/05/14 20:41:30 - mmengine - INFO - Epoch(train) [1][ 650/1196] lr: 8.0000e-03 eta: 20:01:14 time: 1.6644 data_time: 0.0034 memory: 4499 grad_norm: 0.5326 loss: 0.5373 loss_sem_seg: 0.5373 2023/05/14 20:42:56 - mmengine - INFO - Epoch(train) [1][ 700/1196] lr: 8.0000e-03 eta: 20:00:29 time: 1.7129 data_time: 0.0035 memory: 5017 grad_norm: 0.5767 loss: 0.5549 loss_sem_seg: 0.5549 2023/05/14 20:44:20 - mmengine - INFO - Epoch(train) [1][ 750/1196] lr: 8.0000e-03 eta: 19:58:03 time: 1.6788 data_time: 0.0032 memory: 5008 grad_norm: 0.5376 loss: 0.5157 loss_sem_seg: 0.5157 2023/05/14 20:45:54 - mmengine - INFO - Epoch(train) [1][ 800/1196] lr: 8.0000e-03 eta: 20:04:41 time: 1.8822 data_time: 0.0033 memory: 4787 grad_norm: 0.6508 loss: 0.5027 loss_sem_seg: 0.5027 2023/05/14 20:47:19 - mmengine - INFO - Epoch(train) [1][ 850/1196] lr: 8.0000e-03 eta: 20:02:57 time: 1.7030 data_time: 0.0033 memory: 4882 grad_norm: 0.5785 loss: 0.5090 loss_sem_seg: 0.5090 2023/05/14 20:48:44 - mmengine - INFO - Epoch(train) [1][ 900/1196] lr: 8.0000e-03 eta: 20:01:02 time: 1.6976 data_time: 0.0032 memory: 4808 grad_norm: 0.5547 loss: 0.4721 loss_sem_seg: 0.4721 2023/05/14 20:50:08 - mmengine - INFO - Epoch(train) [1][ 950/1196] lr: 8.0000e-03 eta: 19:58:38 time: 1.6830 data_time: 0.0031 memory: 4875 grad_norm: 0.4881 loss: 0.4713 loss_sem_seg: 0.4713 2023/05/14 20:51:42 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 20:51:42 - mmengine - INFO - Epoch(train) [1][1000/1196] lr: 8.0000e-03 eta: 20:03:18 time: 1.8818 data_time: 0.0035 memory: 5165 grad_norm: 0.4854 loss: 0.4884 loss_sem_seg: 0.4884 2023/05/14 20:53:16 - mmengine - INFO - Epoch(train) [1][1050/1196] lr: 8.0000e-03 eta: 20:07:02 time: 1.8716 data_time: 0.0032 memory: 4686 grad_norm: 0.6482 loss: 0.4602 loss_sem_seg: 0.4602 2023/05/14 20:54:41 - mmengine - INFO - Epoch(train) [1][1100/1196] lr: 8.0000e-03 eta: 20:05:04 time: 1.7076 data_time: 0.0031 memory: 4829 grad_norm: 0.5184 loss: 0.4450 loss_sem_seg: 0.4450 2023/05/14 20:56:06 - mmengine - INFO - Epoch(train) [1][1150/1196] lr: 8.0000e-03 eta: 20:02:53 time: 1.6985 data_time: 0.0032 memory: 4779 grad_norm: 0.4233 loss: 0.4208 loss_sem_seg: 0.4208 2023/05/14 20:57:24 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 20:57:24 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/05/14 20:57:34 - mmengine - INFO - Epoch(val) [1][ 50/509] eta: 0:00:43 time: 0.0941 data_time: 0.0032 memory: 4832 2023/05/14 20:57:38 - mmengine - INFO - Epoch(val) [1][100/509] eta: 0:00:36 time: 0.0847 data_time: 0.0020 memory: 991 2023/05/14 20:57:42 - mmengine - INFO - Epoch(val) [1][150/509] eta: 0:00:31 time: 0.0827 data_time: 0.0020 memory: 994 2023/05/14 20:57:46 - mmengine - INFO - Epoch(val) [1][200/509] eta: 0:00:26 time: 0.0840 data_time: 0.0020 memory: 979 2023/05/14 20:57:51 - mmengine - INFO - Epoch(val) [1][250/509] eta: 0:00:22 time: 0.0883 data_time: 0.0019 memory: 1004 2023/05/14 20:57:55 - mmengine - INFO - Epoch(val) [1][300/509] eta: 0:00:17 time: 0.0762 data_time: 0.0019 memory: 946 2023/05/14 20:57:58 - mmengine - INFO - Epoch(val) [1][350/509] eta: 0:00:13 time: 0.0790 data_time: 0.0019 memory: 970 2023/05/14 20:58:03 - mmengine - INFO - Epoch(val) [1][400/509] eta: 0:00:09 time: 0.0844 data_time: 0.0019 memory: 978 2023/05/14 20:58:07 - mmengine - INFO - Epoch(val) [1][450/509] eta: 0:00:04 time: 0.0843 data_time: 0.0019 memory: 991 2023/05/14 20:58:11 - mmengine - INFO - Epoch(val) [1][500/509] eta: 0:00:00 time: 0.0779 data_time: 0.0018 memory: 973 2023/05/14 20:59:20 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9040 | 0.0000 | 0.2046 | 0.2352 | 0.1035 | 0.1073 | 0.1859 | 0.0000 | 0.8838 | 0.1309 | 0.7279 | 0.0000 | 0.8547 | 0.4775 | 0.8591 | 0.5757 | 0.6913 | 0.5575 | 0.3040 | 0.4107 | 0.8847 | 0.4777 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/14 20:59:20 - mmengine - INFO - Epoch(val) [1][509/509] car: 0.9040 bicycle: 0.0000 motorcycle: 0.2046 truck: 0.2352 bus: 0.1035 person: 0.1073 bicyclist: 0.1859 motorcyclist: 0.0000 road: 0.8838 parking: 0.1309 sidewalk: 0.7279 other-ground: 0.0000 building: 0.8547 fence: 0.4775 vegetation: 0.8591 trunck: 0.5757 terrian: 0.6913 pole: 0.5575 traffic-sign: 0.3040 miou: 0.4107 acc: 0.8847 acc_cls: 0.4777 data_time: 0.0018 time: 0.0799 2023/05/14 21:00:52 - mmengine - INFO - Epoch(train) [2][ 50/1196] lr: 8.0000e-03 eta: 20:02:19 time: 1.8374 data_time: 0.0043 memory: 5066 grad_norm: 0.4554 loss: 0.4549 loss_sem_seg: 0.4549 2023/05/14 21:02:15 - mmengine - INFO - Epoch(train) [2][ 100/1196] lr: 8.0000e-03 eta: 19:58:59 time: 1.6548 data_time: 0.0032 memory: 4572 grad_norm: 0.5084 loss: 0.4287 loss_sem_seg: 0.4287 2023/05/14 21:03:41 - mmengine - INFO - Epoch(train) [2][ 150/1196] lr: 8.0000e-03 eta: 19:57:35 time: 1.7239 data_time: 0.0033 memory: 4559 grad_norm: 0.4786 loss: 0.4438 loss_sem_seg: 0.4438 2023/05/14 21:05:12 - mmengine - INFO - Epoch(train) [2][ 200/1196] lr: 8.0000e-03 eta: 19:58:42 time: 1.8253 data_time: 0.0033 memory: 4553 grad_norm: 0.4522 loss: 0.4434 loss_sem_seg: 0.4434 2023/05/14 21:06:36 - mmengine - INFO - Epoch(train) [2][ 250/1196] lr: 8.0000e-03 eta: 19:55:56 time: 1.6715 data_time: 0.0034 memory: 4766 grad_norm: 0.5171 loss: 0.4226 loss_sem_seg: 0.4226 2023/05/14 21:08:03 - mmengine - INFO - Epoch(train) [2][ 300/1196] lr: 8.0000e-03 eta: 19:54:44 time: 1.7345 data_time: 0.0032 memory: 5047 grad_norm: 0.4091 loss: 0.4265 loss_sem_seg: 0.4265 2023/05/14 21:09:30 - mmengine - INFO - Epoch(train) [2][ 350/1196] lr: 8.0000e-03 eta: 19:53:58 time: 1.7550 data_time: 0.0033 memory: 4585 grad_norm: 0.4160 loss: 0.4164 loss_sem_seg: 0.4164 2023/05/14 21:10:53 - mmengine - INFO - Epoch(train) [2][ 400/1196] lr: 8.0000e-03 eta: 19:50:50 time: 1.6470 data_time: 0.0033 memory: 5089 grad_norm: 0.3813 loss: 0.4191 loss_sem_seg: 0.4191 2023/05/14 21:12:15 - mmengine - INFO - Epoch(train) [2][ 450/1196] lr: 8.0000e-03 eta: 19:47:41 time: 1.6417 data_time: 0.0034 memory: 4614 grad_norm: 0.4410 loss: 0.4261 loss_sem_seg: 0.4261 2023/05/14 21:13:37 - mmengine - INFO - Epoch(train) [2][ 500/1196] lr: 8.0000e-03 eta: 19:44:36 time: 1.6394 data_time: 0.0033 memory: 5131 grad_norm: 0.3931 loss: 0.4107 loss_sem_seg: 0.4107 2023/05/14 21:14:59 - mmengine - INFO - Epoch(train) [2][ 550/1196] lr: 8.0000e-03 eta: 19:41:47 time: 1.6484 data_time: 0.0034 memory: 4443 grad_norm: 0.3902 loss: 0.4017 loss_sem_seg: 0.4017 2023/05/14 21:16:31 - mmengine - INFO - Epoch(train) [2][ 600/1196] lr: 8.0000e-03 eta: 19:42:44 time: 1.8410 data_time: 0.0034 memory: 4684 grad_norm: 0.3917 loss: 0.3824 loss_sem_seg: 0.3824 2023/05/14 21:17:54 - mmengine - INFO - Epoch(train) [2][ 650/1196] lr: 8.0000e-03 eta: 19:40:15 time: 1.6638 data_time: 0.0033 memory: 5008 grad_norm: 0.4305 loss: 0.4078 loss_sem_seg: 0.4078 2023/05/14 21:19:19 - mmengine - INFO - Epoch(train) [2][ 700/1196] lr: 8.0000e-03 eta: 19:38:11 time: 1.6834 data_time: 0.0033 memory: 4668 grad_norm: 0.3501 loss: 0.4145 loss_sem_seg: 0.4145 2023/05/14 21:20:39 - mmengine - INFO - Epoch(train) [2][ 750/1196] lr: 8.0000e-03 eta: 19:34:53 time: 1.6110 data_time: 0.0034 memory: 4961 grad_norm: 0.4130 loss: 0.3902 loss_sem_seg: 0.3902 2023/05/14 21:22:04 - mmengine - INFO - Epoch(train) [2][ 800/1196] lr: 8.0000e-03 eta: 19:33:07 time: 1.6953 data_time: 0.0034 memory: 5163 grad_norm: 0.2817 loss: 0.3994 loss_sem_seg: 0.3994 2023/05/14 21:22:11 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 21:23:34 - mmengine - INFO - Epoch(train) [2][ 850/1196] lr: 8.0000e-03 eta: 19:33:14 time: 1.8061 data_time: 0.0033 memory: 4816 grad_norm: 0.3368 loss: 0.4065 loss_sem_seg: 0.4065 2023/05/14 21:24:48 - mmengine - INFO - Epoch(train) [2][ 900/1196] lr: 8.0000e-03 eta: 19:28:01 time: 1.4844 data_time: 0.0034 memory: 4449 grad_norm: 0.3044 loss: 0.3558 loss_sem_seg: 0.3558 2023/05/14 21:26:02 - mmengine - INFO - Epoch(train) [2][ 950/1196] lr: 8.0000e-03 eta: 19:22:52 time: 1.4764 data_time: 0.0034 memory: 4925 grad_norm: 0.3376 loss: 0.3734 loss_sem_seg: 0.3734 2023/05/14 21:27:10 - mmengine - INFO - Epoch(train) [2][1000/1196] lr: 8.0000e-03 eta: 19:16:06 time: 1.3606 data_time: 0.0033 memory: 4673 grad_norm: 0.3337 loss: 0.3924 loss_sem_seg: 0.3924 2023/05/14 21:28:20 - mmengine - INFO - Epoch(train) [2][1050/1196] lr: 8.0000e-03 eta: 19:09:59 time: 1.3879 data_time: 0.0034 memory: 4627 grad_norm: 0.3282 loss: 0.3749 loss_sem_seg: 0.3749 2023/05/14 21:29:28 - mmengine - INFO - Epoch(train) [2][1100/1196] lr: 8.0000e-03 eta: 19:03:50 time: 1.3694 data_time: 0.0033 memory: 4729 grad_norm: 0.3111 loss: 0.3911 loss_sem_seg: 0.3911 2023/05/14 21:30:36 - mmengine - INFO - Epoch(train) [2][1150/1196] lr: 8.0000e-03 eta: 18:57:43 time: 1.3577 data_time: 0.0033 memory: 4672 grad_norm: 0.3354 loss: 0.3674 loss_sem_seg: 0.3674 2023/05/14 21:31:39 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 21:31:39 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/05/14 21:31:50 - mmengine - INFO - Epoch(val) [2][ 50/509] eta: 0:00:42 time: 0.0925 data_time: 0.0021 memory: 4847 2023/05/14 21:31:54 - mmengine - INFO - Epoch(val) [2][100/509] eta: 0:00:36 time: 0.0846 data_time: 0.0020 memory: 991 2023/05/14 21:31:58 - mmengine - INFO - Epoch(val) [2][150/509] eta: 0:00:31 time: 0.0832 data_time: 0.0019 memory: 994 2023/05/14 21:32:02 - mmengine - INFO - Epoch(val) [2][200/509] eta: 0:00:26 time: 0.0840 data_time: 0.0020 memory: 979 2023/05/14 21:32:07 - mmengine - INFO - Epoch(val) [2][250/509] eta: 0:00:22 time: 0.0882 data_time: 0.0019 memory: 1004 2023/05/14 21:32:11 - mmengine - INFO - Epoch(val) [2][300/509] eta: 0:00:17 time: 0.0768 data_time: 0.0020 memory: 946 2023/05/14 21:32:15 - mmengine - INFO - Epoch(val) [2][350/509] eta: 0:00:13 time: 0.0792 data_time: 0.0019 memory: 970 2023/05/14 21:32:19 - mmengine - INFO - Epoch(val) [2][400/509] eta: 0:00:09 time: 0.0844 data_time: 0.0019 memory: 978 2023/05/14 21:32:23 - mmengine - INFO - Epoch(val) [2][450/509] eta: 0:00:04 time: 0.0851 data_time: 0.0019 memory: 991 2023/05/14 21:32:27 - mmengine - INFO - Epoch(val) [2][500/509] eta: 0:00:00 time: 0.0795 data_time: 0.0018 memory: 973 2023/05/14 21:33:08 - 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 | 0.9271 | 0.0275 | 0.4192 | 0.3500 | 0.1041 | 0.3452 | 0.0003 | 0.0048 | 0.9155 | 0.3746 | 0.7734 | 0.0002 | 0.8694 | 0.5106 | 0.8704 | 0.6190 | 0.7173 | 0.4771 | 0.4083 | 0.4586 | 0.9008 | 0.5405 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/14 21:33:08 - mmengine - INFO - Epoch(val) [2][509/509] car: 0.9271 bicycle: 0.0275 motorcycle: 0.4192 truck: 0.3500 bus: 0.1041 person: 0.3452 bicyclist: 0.0003 motorcyclist: 0.0048 road: 0.9155 parking: 0.3746 sidewalk: 0.7734 other-ground: 0.0002 building: 0.8694 fence: 0.5106 vegetation: 0.8704 trunck: 0.6190 terrian: 0.7173 pole: 0.4771 traffic-sign: 0.4083 miou: 0.4586 acc: 0.9008 acc_cls: 0.5405 data_time: 0.0018 time: 0.0814 2023/05/14 21:34:17 - mmengine - INFO - Epoch(train) [3][ 50/1196] lr: 8.0000e-03 eta: 18:46:51 time: 1.3712 data_time: 0.0043 memory: 4946 grad_norm: 0.3108 loss: 0.3624 loss_sem_seg: 0.3624 2023/05/14 21:35:26 - mmengine - INFO - Epoch(train) [3][ 100/1196] lr: 8.0000e-03 eta: 18:41:37 time: 1.3810 data_time: 0.0033 memory: 4567 grad_norm: 0.3164 loss: 0.3400 loss_sem_seg: 0.3400 2023/05/14 21:36:36 - mmengine - INFO - Epoch(train) [3][ 150/1196] lr: 8.0000e-03 eta: 18:36:46 time: 1.3980 data_time: 0.0033 memory: 4719 grad_norm: 0.3086 loss: 0.3637 loss_sem_seg: 0.3637 2023/05/14 21:37:45 - mmengine - INFO - Epoch(train) [3][ 200/1196] lr: 8.0000e-03 eta: 18:31:51 time: 1.3813 data_time: 0.0033 memory: 4882 grad_norm: 0.3307 loss: 0.3443 loss_sem_seg: 0.3443 2023/05/14 21:39:00 - mmengine - INFO - Epoch(train) [3][ 250/1196] lr: 8.0000e-03 eta: 18:28:42 time: 1.5103 data_time: 0.0034 memory: 4858 grad_norm: 0.3870 loss: 0.3471 loss_sem_seg: 0.3471 2023/05/14 21:40:23 - mmengine - INFO - Epoch(train) [3][ 300/1196] lr: 8.0000e-03 eta: 18:27:30 time: 1.6593 data_time: 0.0034 memory: 4841 grad_norm: 0.3059 loss: 0.3411 loss_sem_seg: 0.3411 2023/05/14 21:41:34 - mmengine - INFO - Epoch(train) [3][ 350/1196] lr: 8.0000e-03 eta: 18:23:19 time: 1.4161 data_time: 0.0032 memory: 4856 grad_norm: 0.2830 loss: 0.3614 loss_sem_seg: 0.3614 2023/05/14 21:42:41 - mmengine - INFO - Epoch(train) [3][ 400/1196] lr: 8.0000e-03 eta: 18:18:25 time: 1.3493 data_time: 0.0032 memory: 4799 grad_norm: 0.3249 loss: 0.3552 loss_sem_seg: 0.3552 2023/05/14 21:43:50 - mmengine - INFO - Epoch(train) [3][ 450/1196] lr: 8.0000e-03 eta: 18:13:59 time: 1.3767 data_time: 0.0032 memory: 4460 grad_norm: 0.2973 loss: 0.3442 loss_sem_seg: 0.3442 2023/05/14 21:44:58 - mmengine - INFO - Epoch(train) [3][ 500/1196] lr: 8.0000e-03 eta: 18:09:31 time: 1.3637 data_time: 0.0032 memory: 4776 grad_norm: 0.2737 loss: 0.3580 loss_sem_seg: 0.3580 2023/05/14 21:46:08 - mmengine - INFO - Epoch(train) [3][ 550/1196] lr: 8.0000e-03 eta: 18:05:29 time: 1.3919 data_time: 0.0032 memory: 4838 grad_norm: 0.2478 loss: 0.3146 loss_sem_seg: 0.3146 2023/05/14 21:47:16 - mmengine - INFO - Epoch(train) [3][ 600/1196] lr: 8.0000e-03 eta: 18:01:11 time: 1.3584 data_time: 0.0031 memory: 4769 grad_norm: 0.3574 loss: 0.3578 loss_sem_seg: 0.3578 2023/05/14 21:47:27 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 21:48:24 - mmengine - INFO - Epoch(train) [3][ 650/1196] lr: 8.0000e-03 eta: 17:56:57 time: 1.3571 data_time: 0.0031 memory: 4517 grad_norm: 0.2735 loss: 0.3759 loss_sem_seg: 0.3759 2023/05/14 21:49:40 - mmengine - INFO - Epoch(train) [3][ 700/1196] lr: 8.0000e-03 eta: 17:54:44 time: 1.5330 data_time: 0.0031 memory: 4585 grad_norm: 0.2757 loss: 0.3455 loss_sem_seg: 0.3455 2023/05/14 21:51:03 - mmengine - INFO - Epoch(train) [3][ 750/1196] lr: 8.0000e-03 eta: 17:53:52 time: 1.6601 data_time: 0.0031 memory: 4750 grad_norm: 0.2843 loss: 0.3459 loss_sem_seg: 0.3459 2023/05/14 21:52:13 - mmengine - INFO - Epoch(train) [3][ 800/1196] lr: 8.0000e-03 eta: 17:50:12 time: 1.3904 data_time: 0.0030 memory: 4750 grad_norm: 0.2732 loss: 0.3724 loss_sem_seg: 0.3724 2023/05/14 21:53:22 - mmengine - INFO - Epoch(train) [3][ 850/1196] lr: 8.0000e-03 eta: 17:46:28 time: 1.3767 data_time: 0.0031 memory: 4894 grad_norm: 0.2886 loss: 0.3761 loss_sem_seg: 0.3761 2023/05/14 21:54:30 - mmengine - INFO - Epoch(train) [3][ 900/1196] lr: 8.0000e-03 eta: 17:42:45 time: 1.3712 data_time: 0.0031 memory: 4904 grad_norm: 0.2287 loss: 0.3307 loss_sem_seg: 0.3307 2023/05/14 21:55:40 - mmengine - INFO - Epoch(train) [3][ 950/1196] lr: 8.0000e-03 eta: 17:39:16 time: 1.3863 data_time: 0.0031 memory: 5101 grad_norm: 0.2367 loss: 0.3386 loss_sem_seg: 0.3386 2023/05/14 21:56:49 - mmengine - INFO - Epoch(train) [3][1000/1196] lr: 8.0000e-03 eta: 17:35:50 time: 1.3854 data_time: 0.0031 memory: 4606 grad_norm: 0.2298 loss: 0.3343 loss_sem_seg: 0.3343 2023/05/14 21:57:57 - mmengine - INFO - Epoch(train) [3][1050/1196] lr: 8.0000e-03 eta: 17:32:17 time: 1.3666 data_time: 0.0030 memory: 4549 grad_norm: 0.3053 loss: 0.3619 loss_sem_seg: 0.3619 2023/05/14 21:59:07 - mmengine - INFO - Epoch(train) [3][1100/1196] lr: 8.0000e-03 eta: 17:29:00 time: 1.3860 data_time: 0.0030 memory: 4204 grad_norm: 0.2374 loss: 0.3332 loss_sem_seg: 0.3332 2023/05/14 22:00:15 - mmengine - INFO - Epoch(train) [3][1150/1196] lr: 8.0000e-03 eta: 17:25:41 time: 1.3771 data_time: 0.0031 memory: 5085 grad_norm: 0.2705 loss: 0.3304 loss_sem_seg: 0.3304 2023/05/14 22:01:19 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 22:01:19 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/05/14 22:01:30 - mmengine - INFO - Epoch(val) [3][ 50/509] eta: 0:00:42 time: 0.0929 data_time: 0.0021 memory: 4684 2023/05/14 22:01:34 - mmengine - INFO - Epoch(val) [3][100/509] eta: 0:00:36 time: 0.0849 data_time: 0.0020 memory: 991 2023/05/14 22:01:38 - mmengine - INFO - Epoch(val) [3][150/509] eta: 0:00:31 time: 0.0821 data_time: 0.0019 memory: 994 2023/05/14 22:01:42 - mmengine - INFO - Epoch(val) [3][200/509] eta: 0:00:26 time: 0.0835 data_time: 0.0019 memory: 979 2023/05/14 22:01:46 - mmengine - INFO - Epoch(val) [3][250/509] eta: 0:00:22 time: 0.0883 data_time: 0.0019 memory: 1004 2023/05/14 22:01:50 - mmengine - INFO - Epoch(val) [3][300/509] eta: 0:00:17 time: 0.0765 data_time: 0.0019 memory: 946 2023/05/14 22:01:54 - mmengine - INFO - Epoch(val) [3][350/509] eta: 0:00:13 time: 0.0793 data_time: 0.0018 memory: 970 2023/05/14 22:01:59 - mmengine - INFO - Epoch(val) [3][400/509] eta: 0:00:09 time: 0.0843 data_time: 0.0019 memory: 978 2023/05/14 22:02:03 - mmengine - INFO - Epoch(val) [3][450/509] eta: 0:00:04 time: 0.0847 data_time: 0.0018 memory: 991 2023/05/14 22:02:07 - mmengine - INFO - Epoch(val) [3][500/509] eta: 0:00:00 time: 0.0778 data_time: 0.0017 memory: 973 2023/05/14 22:02:47 - 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 | 0.9279 | 0.0625 | 0.2249 | 0.4131 | 0.1625 | 0.4737 | 0.1345 | 0.0004 | 0.9316 | 0.4430 | 0.8032 | 0.0232 | 0.8965 | 0.5651 | 0.8824 | 0.5992 | 0.7650 | 0.6192 | 0.4175 | 0.4919 | 0.9132 | 0.5828 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/14 22:02:47 - mmengine - INFO - Epoch(val) [3][509/509] car: 0.9279 bicycle: 0.0625 motorcycle: 0.2249 truck: 0.4131 bus: 0.1625 person: 0.4737 bicyclist: 0.1345 motorcyclist: 0.0004 road: 0.9316 parking: 0.4430 sidewalk: 0.8032 other-ground: 0.0232 building: 0.8965 fence: 0.5651 vegetation: 0.8824 trunck: 0.5992 terrian: 0.7650 pole: 0.6192 traffic-sign: 0.4175 miou: 0.4919 acc: 0.9132 acc_cls: 0.5828 data_time: 0.0017 time: 0.0796 2023/05/14 22:03:57 - mmengine - INFO - Epoch(train) [4][ 50/1196] lr: 8.0000e-03 eta: 17:19:30 time: 1.3839 data_time: 0.0039 memory: 5009 grad_norm: 0.2321 loss: 0.3081 loss_sem_seg: 0.3081 2023/05/14 22:05:05 - mmengine - INFO - Epoch(train) [4][ 100/1196] lr: 8.0000e-03 eta: 17:16:21 time: 1.3765 data_time: 0.0030 memory: 4906 grad_norm: 0.2287 loss: 0.3304 loss_sem_seg: 0.3304 2023/05/14 22:06:16 - mmengine - INFO - Epoch(train) [4][ 150/1196] lr: 8.0000e-03 eta: 17:13:32 time: 1.4069 data_time: 0.0030 memory: 5108 grad_norm: 0.2524 loss: 0.3201 loss_sem_seg: 0.3201 2023/05/14 22:07:25 - mmengine - INFO - Epoch(train) [4][ 200/1196] lr: 8.0000e-03 eta: 17:10:31 time: 1.3800 data_time: 0.0031 memory: 4661 grad_norm: 0.2524 loss: 0.3195 loss_sem_seg: 0.3195 2023/05/14 22:08:33 - mmengine - INFO - Epoch(train) [4][ 250/1196] lr: 8.0000e-03 eta: 17:07:19 time: 1.3541 data_time: 0.0031 memory: 4567 grad_norm: 0.2215 loss: 0.3259 loss_sem_seg: 0.3259 2023/05/14 22:09:42 - mmengine - INFO - Epoch(train) [4][ 300/1196] lr: 8.0000e-03 eta: 17:04:28 time: 1.3884 data_time: 0.0031 memory: 4541 grad_norm: 0.2484 loss: 0.3345 loss_sem_seg: 0.3345 2023/05/14 22:10:53 - mmengine - INFO - Epoch(train) [4][ 350/1196] lr: 8.0000e-03 eta: 17:01:56 time: 1.4204 data_time: 0.0030 memory: 4909 grad_norm: 0.2385 loss: 0.3375 loss_sem_seg: 0.3375 2023/05/14 22:12:02 - mmengine - INFO - Epoch(train) [4][ 400/1196] lr: 8.0000e-03 eta: 16:59:06 time: 1.3801 data_time: 0.0030 memory: 4680 grad_norm: 0.2138 loss: 0.3437 loss_sem_seg: 0.3437 2023/05/14 22:12:19 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 22:13:11 - mmengine - INFO - Epoch(train) [4][ 450/1196] lr: 8.0000e-03 eta: 16:56:19 time: 1.3825 data_time: 0.0030 memory: 4510 grad_norm: 0.2318 loss: 0.3165 loss_sem_seg: 0.3165 2023/05/14 22:14:20 - mmengine - INFO - Epoch(train) [4][ 500/1196] lr: 8.0000e-03 eta: 16:53:33 time: 1.3780 data_time: 0.0031 memory: 4578 grad_norm: 0.2354 loss: 0.3265 loss_sem_seg: 0.3265 2023/05/14 22:15:30 - mmengine - INFO - Epoch(train) [4][ 550/1196] lr: 8.0000e-03 eta: 16:50:55 time: 1.3906 data_time: 0.0030 memory: 4755 grad_norm: 0.2272 loss: 0.3349 loss_sem_seg: 0.3349 2023/05/14 22:16:39 - mmengine - INFO - Epoch(train) [4][ 600/1196] lr: 8.0000e-03 eta: 16:48:23 time: 1.3995 data_time: 0.0031 memory: 4403 grad_norm: 0.2272 loss: 0.2923 loss_sem_seg: 0.2923 2023/05/14 22:17:49 - mmengine - INFO - Epoch(train) [4][ 650/1196] lr: 8.0000e-03 eta: 16:45:46 time: 1.3822 data_time: 0.0031 memory: 4965 grad_norm: 0.2040 loss: 0.3145 loss_sem_seg: 0.3145 2023/05/14 22:18:58 - mmengine - INFO - Epoch(train) [4][ 700/1196] lr: 8.0000e-03 eta: 16:43:13 time: 1.3889 data_time: 0.0031 memory: 4511 grad_norm: 0.2515 loss: 0.3240 loss_sem_seg: 0.3240 2023/05/14 22:20:08 - mmengine - INFO - Epoch(train) [4][ 750/1196] lr: 8.0000e-03 eta: 16:40:43 time: 1.3903 data_time: 0.0032 memory: 4719 grad_norm: 0.2364 loss: 0.3014 loss_sem_seg: 0.3014 2023/05/14 22:21:29 - mmengine - INFO - Epoch(train) [4][ 800/1196] lr: 8.0000e-03 eta: 16:40:02 time: 1.6347 data_time: 0.0031 memory: 4826 grad_norm: 0.2477 loss: 0.3318 loss_sem_seg: 0.3318 2023/05/14 22:22:48 - mmengine - INFO - Epoch(train) [4][ 850/1196] lr: 8.0000e-03 eta: 16:38:54 time: 1.5743 data_time: 0.0031 memory: 4964 grad_norm: 0.2357 loss: 0.3245 loss_sem_seg: 0.3245 2023/05/14 22:23:56 - mmengine - INFO - Epoch(train) [4][ 900/1196] lr: 8.0000e-03 eta: 16:36:16 time: 1.3644 data_time: 0.0034 memory: 4826 grad_norm: 0.2355 loss: 0.3143 loss_sem_seg: 0.3143 2023/05/14 22:25:04 - mmengine - INFO - Epoch(train) [4][ 950/1196] lr: 8.0000e-03 eta: 16:33:39 time: 1.3611 data_time: 0.0033 memory: 4734 grad_norm: 0.2067 loss: 0.3114 loss_sem_seg: 0.3114 2023/05/14 22:26:13 - mmengine - INFO - Epoch(train) [4][1000/1196] lr: 8.0000e-03 eta: 16:31:09 time: 1.3757 data_time: 0.0033 memory: 5061 grad_norm: 0.1931 loss: 0.2947 loss_sem_seg: 0.2947 2023/05/14 22:27:23 - mmengine - INFO - Epoch(train) [4][1050/1196] lr: 8.0000e-03 eta: 16:28:48 time: 1.3930 data_time: 0.0033 memory: 5043 grad_norm: 0.2113 loss: 0.2999 loss_sem_seg: 0.2999 2023/05/14 22:28:30 - mmengine - INFO - Epoch(train) [4][1100/1196] lr: 8.0000e-03 eta: 16:26:10 time: 1.3445 data_time: 0.0033 memory: 4844 grad_norm: 0.2143 loss: 0.3072 loss_sem_seg: 0.3072 2023/05/14 22:29:39 - mmengine - INFO - Epoch(train) [4][1150/1196] lr: 8.0000e-03 eta: 16:23:47 time: 1.3814 data_time: 0.0032 memory: 4778 grad_norm: 0.1883 loss: 0.2974 loss_sem_seg: 0.2974 2023/05/14 22:30:43 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 22:30:43 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/05/14 22:30:54 - mmengine - INFO - Epoch(val) [4][ 50/509] eta: 0:00:42 time: 0.0923 data_time: 0.0020 memory: 5310 2023/05/14 22:30:59 - mmengine - INFO - Epoch(val) [4][100/509] eta: 0:00:36 time: 0.0844 data_time: 0.0020 memory: 991 2023/05/14 22:31:03 - mmengine - INFO - Epoch(val) [4][150/509] eta: 0:00:31 time: 0.0825 data_time: 0.0019 memory: 994 2023/05/14 22:31:07 - mmengine - INFO - Epoch(val) [4][200/509] eta: 0:00:26 time: 0.0834 data_time: 0.0019 memory: 979 2023/05/14 22:31:11 - mmengine - INFO - Epoch(val) [4][250/509] eta: 0:00:22 time: 0.0879 data_time: 0.0019 memory: 1004 2023/05/14 22:31:15 - mmengine - INFO - Epoch(val) [4][300/509] eta: 0:00:17 time: 0.0761 data_time: 0.0019 memory: 946 2023/05/14 22:31:19 - mmengine - INFO - Epoch(val) [4][350/509] eta: 0:00:13 time: 0.0791 data_time: 0.0019 memory: 970 2023/05/14 22:31:23 - mmengine - INFO - Epoch(val) [4][400/509] eta: 0:00:09 time: 0.0846 data_time: 0.0019 memory: 978 2023/05/14 22:31:27 - mmengine - INFO - Epoch(val) [4][450/509] eta: 0:00:04 time: 0.0850 data_time: 0.0019 memory: 991 2023/05/14 22:31:31 - mmengine - INFO - Epoch(val) [4][500/509] eta: 0:00:00 time: 0.0783 data_time: 0.0018 memory: 973 2023/05/14 22:32:21 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9388 | 0.1946 | 0.5121 | 0.7257 | 0.3298 | 0.5993 | 0.7646 | 0.0038 | 0.9209 | 0.3893 | 0.8065 | 0.0119 | 0.9027 | 0.6379 | 0.8952 | 0.6627 | 0.7823 | 0.6184 | 0.4637 | 0.5874 | 0.9212 | 0.6708 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/14 22:32:21 - mmengine - INFO - Epoch(val) [4][509/509] car: 0.9388 bicycle: 0.1946 motorcycle: 0.5121 truck: 0.7257 bus: 0.3298 person: 0.5993 bicyclist: 0.7646 motorcyclist: 0.0038 road: 0.9209 parking: 0.3893 sidewalk: 0.8065 other-ground: 0.0119 building: 0.9027 fence: 0.6379 vegetation: 0.8952 trunck: 0.6627 terrian: 0.7823 pole: 0.6184 traffic-sign: 0.4637 miou: 0.5874 acc: 0.9212 acc_cls: 0.6708 data_time: 0.0018 time: 0.0799 2023/05/14 22:33:37 - mmengine - INFO - Epoch(train) [5][ 50/1196] lr: 8.0000e-03 eta: 16:20:20 time: 1.5222 data_time: 0.0040 memory: 4333 grad_norm: 0.2096 loss: 0.2992 loss_sem_seg: 0.2992 2023/05/14 22:34:46 - mmengine - INFO - Epoch(train) [5][ 100/1196] lr: 8.0000e-03 eta: 16:18:01 time: 1.3797 data_time: 0.0030 memory: 5020 grad_norm: 0.2149 loss: 0.2978 loss_sem_seg: 0.2978 2023/05/14 22:35:56 - mmengine - INFO - Epoch(train) [5][ 150/1196] lr: 8.0000e-03 eta: 16:15:47 time: 1.3898 data_time: 0.0030 memory: 4753 grad_norm: 0.2618 loss: 0.3100 loss_sem_seg: 0.3100 2023/05/14 22:37:05 - mmengine - INFO - Epoch(train) [5][ 200/1196] lr: 8.0000e-03 eta: 16:13:32 time: 1.3824 data_time: 0.0031 memory: 4742 grad_norm: 0.2001 loss: 0.3031 loss_sem_seg: 0.3031 2023/05/14 22:37:26 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 22:38:13 - mmengine - INFO - Epoch(train) [5][ 250/1196] lr: 8.0000e-03 eta: 16:11:09 time: 1.3585 data_time: 0.0030 memory: 4438 grad_norm: 0.2005 loss: 0.2997 loss_sem_seg: 0.2997 2023/05/14 22:39:21 - mmengine - INFO - Epoch(train) [5][ 300/1196] lr: 8.0000e-03 eta: 16:08:53 time: 1.3737 data_time: 0.0030 memory: 5289 grad_norm: 0.1884 loss: 0.3002 loss_sem_seg: 0.3002 2023/05/14 22:40:30 - mmengine - INFO - Epoch(train) [5][ 350/1196] lr: 8.0000e-03 eta: 16:06:34 time: 1.3634 data_time: 0.0030 memory: 4574 grad_norm: 0.2064 loss: 0.3102 loss_sem_seg: 0.3102 2023/05/14 22:41:39 - mmengine - INFO - Epoch(train) [5][ 400/1196] lr: 8.0000e-03 eta: 16:04:29 time: 1.3952 data_time: 0.0031 memory: 4862 grad_norm: 0.1873 loss: 0.3067 loss_sem_seg: 0.3067 2023/05/14 22:42:49 - mmengine - INFO - Epoch(train) [5][ 450/1196] lr: 8.0000e-03 eta: 16:02:22 time: 1.3877 data_time: 0.0031 memory: 4799 grad_norm: 0.1905 loss: 0.2973 loss_sem_seg: 0.2973 2023/05/14 22:43:58 - mmengine - INFO - Epoch(train) [5][ 500/1196] lr: 8.0000e-03 eta: 16:00:12 time: 1.3763 data_time: 0.0031 memory: 5004 grad_norm: 0.1938 loss: 0.3046 loss_sem_seg: 0.3046 2023/05/14 22:45:06 - mmengine - INFO - Epoch(train) [5][ 550/1196] lr: 8.0000e-03 eta: 15:57:57 time: 1.3594 data_time: 0.0031 memory: 4942 grad_norm: 0.1968 loss: 0.2931 loss_sem_seg: 0.2931 2023/05/14 22:46:14 - mmengine - INFO - Epoch(train) [5][ 600/1196] lr: 8.0000e-03 eta: 15:55:49 time: 1.3752 data_time: 0.0031 memory: 4950 grad_norm: 0.2198 loss: 0.2963 loss_sem_seg: 0.2963 2023/05/14 22:47:24 - mmengine - INFO - Epoch(train) [5][ 650/1196] lr: 8.0000e-03 eta: 15:53:47 time: 1.3917 data_time: 0.0031 memory: 4770 grad_norm: 0.1955 loss: 0.2959 loss_sem_seg: 0.2959 2023/05/14 22:48:32 - mmengine - INFO - Epoch(train) [5][ 700/1196] lr: 8.0000e-03 eta: 15:51:35 time: 1.3570 data_time: 0.0031 memory: 4792 grad_norm: 0.1753 loss: 0.2899 loss_sem_seg: 0.2899 2023/05/14 22:49:41 - mmengine - INFO - Epoch(train) [5][ 750/1196] lr: 8.0000e-03 eta: 15:49:35 time: 1.3895 data_time: 0.0030 memory: 4347 grad_norm: 0.1732 loss: 0.2974 loss_sem_seg: 0.2974 2023/05/14 22:50:50 - mmengine - INFO - Epoch(train) [5][ 800/1196] lr: 8.0000e-03 eta: 15:47:30 time: 1.3722 data_time: 0.0030 memory: 4664 grad_norm: 0.1783 loss: 0.2765 loss_sem_seg: 0.2765 2023/05/14 22:51:58 - mmengine - INFO - Epoch(train) [5][ 850/1196] lr: 8.0000e-03 eta: 15:45:23 time: 1.3642 data_time: 0.0030 memory: 4650 grad_norm: 0.1860 loss: 0.2781 loss_sem_seg: 0.2781 2023/05/14 22:53:07 - mmengine - INFO - Epoch(train) [5][ 900/1196] lr: 8.0000e-03 eta: 15:43:21 time: 1.3737 data_time: 0.0030 memory: 4657 grad_norm: 0.1846 loss: 0.2804 loss_sem_seg: 0.2804 2023/05/14 22:54:15 - mmengine - INFO - Epoch(train) [5][ 950/1196] lr: 8.0000e-03 eta: 15:41:20 time: 1.3752 data_time: 0.0030 memory: 4851 grad_norm: 0.1858 loss: 0.2790 loss_sem_seg: 0.2790 2023/05/14 22:55:23 - mmengine - INFO - Epoch(train) [5][1000/1196] lr: 8.0000e-03 eta: 15:39:14 time: 1.3573 data_time: 0.0031 memory: 4551 grad_norm: 0.1712 loss: 0.2889 loss_sem_seg: 0.2889 2023/05/14 22:56:32 - mmengine - INFO - Epoch(train) [5][1050/1196] lr: 8.0000e-03 eta: 15:37:17 time: 1.3818 data_time: 0.0030 memory: 4454 grad_norm: 0.2034 loss: 0.2989 loss_sem_seg: 0.2989 2023/05/14 22:57:41 - mmengine - INFO - Epoch(train) [5][1100/1196] lr: 8.0000e-03 eta: 15:35:19 time: 1.3785 data_time: 0.0030 memory: 4645 grad_norm: 0.2110 loss: 0.3016 loss_sem_seg: 0.3016 2023/05/14 22:58:49 - mmengine - INFO - Epoch(train) [5][1150/1196] lr: 8.0000e-03 eta: 15:33:15 time: 1.3534 data_time: 0.0030 memory: 4887 grad_norm: 0.1780 loss: 0.2870 loss_sem_seg: 0.2870 2023/05/14 22:59:52 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 22:59:52 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/05/14 23:00:03 - mmengine - INFO - Epoch(val) [5][ 50/509] eta: 0:00:42 time: 0.0916 data_time: 0.0020 memory: 5024 2023/05/14 23:00:07 - mmengine - INFO - Epoch(val) [5][100/509] eta: 0:00:35 time: 0.0842 data_time: 0.0019 memory: 991 2023/05/14 23:00:11 - mmengine - INFO - Epoch(val) [5][150/509] eta: 0:00:30 time: 0.0822 data_time: 0.0019 memory: 994 2023/05/14 23:00:15 - mmengine - INFO - Epoch(val) [5][200/509] eta: 0:00:26 time: 0.0836 data_time: 0.0019 memory: 979 2023/05/14 23:00:20 - mmengine - INFO - Epoch(val) [5][250/509] eta: 0:00:22 time: 0.0884 data_time: 0.0019 memory: 1004 2023/05/14 23:00:24 - mmengine - INFO - Epoch(val) [5][300/509] eta: 0:00:17 time: 0.0767 data_time: 0.0019 memory: 946 2023/05/14 23:00:28 - mmengine - INFO - Epoch(val) [5][350/509] eta: 0:00:13 time: 0.0794 data_time: 0.0018 memory: 970 2023/05/14 23:00:32 - mmengine - INFO - Epoch(val) [5][400/509] eta: 0:00:09 time: 0.0845 data_time: 0.0019 memory: 978 2023/05/14 23:00:36 - mmengine - INFO - Epoch(val) [5][450/509] eta: 0:00:04 time: 0.0849 data_time: 0.0018 memory: 991 2023/05/14 23:00:41 - mmengine - INFO - Epoch(val) [5][500/509] eta: 0:00:00 time: 0.1032 data_time: 0.0018 memory: 973 2023/05/14 23:01:21 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9572 | 0.3584 | 0.4967 | 0.5895 | 0.5383 | 0.6058 | 0.7157 | 0.0186 | 0.9314 | 0.4301 | 0.7987 | 0.0068 | 0.8963 | 0.6058 | 0.9019 | 0.6493 | 0.7883 | 0.6415 | 0.4451 | 0.5987 | 0.9234 | 0.6697 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/14 23:01:21 - mmengine - INFO - Epoch(val) [5][509/509] car: 0.9572 bicycle: 0.3584 motorcycle: 0.4967 truck: 0.5895 bus: 0.5383 person: 0.6058 bicyclist: 0.7157 motorcyclist: 0.0186 road: 0.9314 parking: 0.4301 sidewalk: 0.7987 other-ground: 0.0068 building: 0.8963 fence: 0.6058 vegetation: 0.9019 trunck: 0.6493 terrian: 0.7883 pole: 0.6415 traffic-sign: 0.4451 miou: 0.5987 acc: 0.9234 acc_cls: 0.6697 data_time: 0.0018 time: 0.1058 2023/05/14 23:01:49 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 23:02:31 - mmengine - INFO - Epoch(train) [6][ 50/1196] lr: 8.0000e-03 eta: 15:29:31 time: 1.3852 data_time: 0.0039 memory: 4844 grad_norm: 0.1708 loss: 0.2740 loss_sem_seg: 0.2740 2023/05/14 23:04:01 - mmengine - INFO - Epoch(train) [6][ 100/1196] lr: 8.0000e-03 eta: 15:29:51 time: 1.8178 data_time: 0.0031 memory: 4593 grad_norm: 0.1777 loss: 0.2886 loss_sem_seg: 0.2886 2023/05/14 23:05:09 - mmengine - INFO - Epoch(train) [6][ 150/1196] lr: 8.0000e-03 eta: 15:27:47 time: 1.3490 data_time: 0.0031 memory: 4560 grad_norm: 0.1783 loss: 0.2926 loss_sem_seg: 0.2926 2023/05/14 23:06:18 - mmengine - INFO - Epoch(train) [6][ 200/1196] lr: 8.0000e-03 eta: 15:25:57 time: 1.3908 data_time: 0.0031 memory: 4439 grad_norm: 0.2098 loss: 0.2897 loss_sem_seg: 0.2897 2023/05/14 23:07:27 - mmengine - INFO - Epoch(train) [6][ 250/1196] lr: 8.0000e-03 eta: 15:24:04 time: 1.3808 data_time: 0.0031 memory: 4697 grad_norm: 0.1949 loss: 0.2727 loss_sem_seg: 0.2727 2023/05/14 23:08:37 - mmengine - INFO - Epoch(train) [6][ 300/1196] lr: 8.0000e-03 eta: 15:22:13 time: 1.3825 data_time: 0.0030 memory: 5185 grad_norm: 0.1876 loss: 0.2687 loss_sem_seg: 0.2687 2023/05/14 23:09:44 - mmengine - INFO - Epoch(train) [6][ 350/1196] lr: 8.0000e-03 eta: 15:20:12 time: 1.3462 data_time: 0.0030 memory: 5143 grad_norm: 0.1782 loss: 0.2947 loss_sem_seg: 0.2947 2023/05/14 23:10:54 - mmengine - INFO - Epoch(train) [6][ 400/1196] lr: 8.0000e-03 eta: 15:18:28 time: 1.4050 data_time: 0.0031 memory: 5357 grad_norm: 0.1792 loss: 0.2880 loss_sem_seg: 0.2880 2023/05/14 23:12:03 - mmengine - INFO - Epoch(train) [6][ 450/1196] lr: 8.0000e-03 eta: 15:16:36 time: 1.3703 data_time: 0.0031 memory: 4379 grad_norm: 0.1771 loss: 0.2846 loss_sem_seg: 0.2846 2023/05/14 23:13:11 - mmengine - INFO - Epoch(train) [6][ 500/1196] lr: 8.0000e-03 eta: 15:14:45 time: 1.3740 data_time: 0.0031 memory: 4413 grad_norm: 0.1710 loss: 0.2766 loss_sem_seg: 0.2766 2023/05/14 23:14:38 - mmengine - INFO - Epoch(train) [6][ 550/1196] lr: 8.0000e-03 eta: 15:14:36 time: 1.7373 data_time: 0.0031 memory: 4675 grad_norm: 0.1985 loss: 0.3036 loss_sem_seg: 0.3036 2023/05/14 23:15:50 - mmengine - INFO - Epoch(train) [6][ 600/1196] lr: 8.0000e-03 eta: 15:13:01 time: 1.4326 data_time: 0.0031 memory: 5093 grad_norm: 0.1625 loss: 0.2863 loss_sem_seg: 0.2863 2023/05/14 23:16:59 - mmengine - INFO - Epoch(train) [6][ 650/1196] lr: 8.0000e-03 eta: 15:11:16 time: 1.3918 data_time: 0.0031 memory: 4634 grad_norm: 0.1770 loss: 0.2736 loss_sem_seg: 0.2736 2023/05/14 23:18:08 - mmengine - INFO - Epoch(train) [6][ 700/1196] lr: 8.0000e-03 eta: 15:09:25 time: 1.3696 data_time: 0.0031 memory: 4369 grad_norm: 0.1892 loss: 0.2797 loss_sem_seg: 0.2797 2023/05/14 23:19:17 - mmengine - INFO - Epoch(train) [6][ 750/1196] lr: 8.0000e-03 eta: 15:07:36 time: 1.3747 data_time: 0.0031 memory: 4513 grad_norm: 0.1571 loss: 0.2642 loss_sem_seg: 0.2642 2023/05/14 23:20:25 - mmengine - INFO - Epoch(train) [6][ 800/1196] lr: 8.0000e-03 eta: 15:05:45 time: 1.3622 data_time: 0.0030 memory: 4841 grad_norm: 0.1657 loss: 0.2725 loss_sem_seg: 0.2725 2023/05/14 23:21:34 - mmengine - INFO - Epoch(train) [6][ 850/1196] lr: 8.0000e-03 eta: 15:03:58 time: 1.3775 data_time: 0.0031 memory: 4477 grad_norm: 0.1686 loss: 0.2800 loss_sem_seg: 0.2800 2023/05/14 23:22:43 - mmengine - INFO - Epoch(train) [6][ 900/1196] lr: 8.0000e-03 eta: 15:02:13 time: 1.3826 data_time: 0.0031 memory: 4662 grad_norm: 0.1568 loss: 0.2767 loss_sem_seg: 0.2767 2023/05/14 23:23:52 - mmengine - INFO - Epoch(train) [6][ 950/1196] lr: 8.0000e-03 eta: 15:00:28 time: 1.3821 data_time: 0.0031 memory: 5239 grad_norm: 0.1545 loss: 0.2708 loss_sem_seg: 0.2708 2023/05/14 23:25:00 - mmengine - INFO - Epoch(train) [6][1000/1196] lr: 8.0000e-03 eta: 14:58:40 time: 1.3665 data_time: 0.0031 memory: 4768 grad_norm: 0.1831 loss: 0.2760 loss_sem_seg: 0.2760 2023/05/14 23:25:28 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 23:26:09 - mmengine - INFO - Epoch(train) [6][1050/1196] lr: 8.0000e-03 eta: 14:56:57 time: 1.3836 data_time: 0.0030 memory: 4629 grad_norm: 0.1593 loss: 0.2675 loss_sem_seg: 0.2675 2023/05/14 23:27:19 - mmengine - INFO - Epoch(train) [6][1100/1196] lr: 8.0000e-03 eta: 14:55:15 time: 1.3849 data_time: 0.0030 memory: 4851 grad_norm: 0.1642 loss: 0.2712 loss_sem_seg: 0.2712 2023/05/14 23:28:27 - mmengine - INFO - Epoch(train) [6][1150/1196] lr: 8.0000e-03 eta: 14:53:31 time: 1.3768 data_time: 0.0030 memory: 4882 grad_norm: 0.1742 loss: 0.2784 loss_sem_seg: 0.2784 2023/05/14 23:29:31 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 23:29:31 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/05/14 23:29:42 - mmengine - INFO - Epoch(val) [6][ 50/509] eta: 0:00:42 time: 0.0921 data_time: 0.0021 memory: 4608 2023/05/14 23:29:46 - mmengine - INFO - Epoch(val) [6][100/509] eta: 0:00:35 time: 0.0840 data_time: 0.0019 memory: 991 2023/05/14 23:29:50 - mmengine - INFO - Epoch(val) [6][150/509] eta: 0:00:30 time: 0.0819 data_time: 0.0019 memory: 994 2023/05/14 23:29:54 - mmengine - INFO - Epoch(val) [6][200/509] eta: 0:00:26 time: 0.0833 data_time: 0.0019 memory: 979 2023/05/14 23:29:59 - mmengine - INFO - Epoch(val) [6][250/509] eta: 0:00:22 time: 0.0879 data_time: 0.0019 memory: 1004 2023/05/14 23:30:02 - mmengine - INFO - Epoch(val) [6][300/509] eta: 0:00:17 time: 0.0762 data_time: 0.0019 memory: 946 2023/05/14 23:30:06 - mmengine - INFO - Epoch(val) [6][350/509] eta: 0:00:13 time: 0.0789 data_time: 0.0018 memory: 970 2023/05/14 23:30:11 - mmengine - INFO - Epoch(val) [6][400/509] eta: 0:00:09 time: 0.0845 data_time: 0.0019 memory: 978 2023/05/14 23:30:15 - mmengine - INFO - Epoch(val) [6][450/509] eta: 0:00:04 time: 0.0850 data_time: 0.0018 memory: 991 2023/05/14 23:30:19 - mmengine - INFO - Epoch(val) [6][500/509] eta: 0:00:00 time: 0.0783 data_time: 0.0017 memory: 973 2023/05/14 23:31:00 - 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 | 0.9563 | 0.4178 | 0.6497 | 0.1513 | 0.5344 | 0.6711 | 0.7466 | 0.0124 | 0.9313 | 0.4711 | 0.8134 | 0.0139 | 0.8887 | 0.5846 | 0.8894 | 0.6768 | 0.7699 | 0.6255 | 0.4843 | 0.5941 | 0.9198 | 0.6767 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/14 23:31:00 - mmengine - INFO - Epoch(val) [6][509/509] car: 0.9563 bicycle: 0.4178 motorcycle: 0.6497 truck: 0.1513 bus: 0.5344 person: 0.6711 bicyclist: 0.7466 motorcyclist: 0.0124 road: 0.9313 parking: 0.4711 sidewalk: 0.8134 other-ground: 0.0139 building: 0.8887 fence: 0.5846 vegetation: 0.8894 trunck: 0.6768 terrian: 0.7699 pole: 0.6255 traffic-sign: 0.4843 miou: 0.5941 acc: 0.9198 acc_cls: 0.6767 data_time: 0.0017 time: 0.0800 2023/05/14 23:32:10 - mmengine - INFO - Epoch(train) [7][ 50/1196] lr: 8.0000e-03 eta: 14:50:13 time: 1.3848 data_time: 0.0045 memory: 4595 grad_norm: 0.1805 loss: 0.2583 loss_sem_seg: 0.2583 2023/05/14 23:33:19 - mmengine - INFO - Epoch(train) [7][ 100/1196] lr: 8.0000e-03 eta: 14:48:32 time: 1.3859 data_time: 0.0031 memory: 4575 grad_norm: 0.1676 loss: 0.2683 loss_sem_seg: 0.2683 2023/05/14 23:34:27 - mmengine - INFO - Epoch(train) [7][ 150/1196] lr: 8.0000e-03 eta: 14:46:45 time: 1.3561 data_time: 0.0032 memory: 4411 grad_norm: 0.1591 loss: 0.2597 loss_sem_seg: 0.2597 2023/05/14 23:35:36 - mmengine - INFO - Epoch(train) [7][ 200/1196] lr: 8.0000e-03 eta: 14:45:04 time: 1.3798 data_time: 0.0031 memory: 4772 grad_norm: 0.1552 loss: 0.2778 loss_sem_seg: 0.2778 2023/05/14 23:36:44 - mmengine - INFO - Epoch(train) [7][ 250/1196] lr: 8.0000e-03 eta: 14:43:22 time: 1.3736 data_time: 0.0032 memory: 5528 grad_norm: 0.1574 loss: 0.2704 loss_sem_seg: 0.2704 2023/05/14 23:37:54 - mmengine - INFO - Epoch(train) [7][ 300/1196] lr: 8.0000e-03 eta: 14:41:45 time: 1.3902 data_time: 0.0031 memory: 4989 grad_norm: 0.1564 loss: 0.2980 loss_sem_seg: 0.2980 2023/05/14 23:39:03 - mmengine - INFO - Epoch(train) [7][ 350/1196] lr: 8.0000e-03 eta: 14:40:05 time: 1.3794 data_time: 0.0031 memory: 4389 grad_norm: 0.1548 loss: 0.2821 loss_sem_seg: 0.2821 2023/05/14 23:40:13 - mmengine - INFO - Epoch(train) [7][ 400/1196] lr: 8.0000e-03 eta: 14:38:29 time: 1.3939 data_time: 0.0031 memory: 4710 grad_norm: 0.1817 loss: 0.2783 loss_sem_seg: 0.2783 2023/05/14 23:41:22 - mmengine - INFO - Epoch(train) [7][ 450/1196] lr: 8.0000e-03 eta: 14:36:53 time: 1.3892 data_time: 0.0031 memory: 5129 grad_norm: 0.1459 loss: 0.2729 loss_sem_seg: 0.2729 2023/05/14 23:42:30 - mmengine - INFO - Epoch(train) [7][ 500/1196] lr: 8.0000e-03 eta: 14:35:10 time: 1.3628 data_time: 0.0031 memory: 4782 grad_norm: 0.1529 loss: 0.2734 loss_sem_seg: 0.2734 2023/05/14 23:43:39 - mmengine - INFO - Epoch(train) [7][ 550/1196] lr: 8.0000e-03 eta: 14:33:30 time: 1.3701 data_time: 0.0032 memory: 5125 grad_norm: 0.1453 loss: 0.2623 loss_sem_seg: 0.2623 2023/05/14 23:44:47 - mmengine - INFO - Epoch(train) [7][ 600/1196] lr: 8.0000e-03 eta: 14:31:49 time: 1.3675 data_time: 0.0033 memory: 4709 grad_norm: 0.1565 loss: 0.2551 loss_sem_seg: 0.2551 2023/05/14 23:46:20 - mmengine - INFO - Epoch(train) [7][ 650/1196] lr: 8.0000e-03 eta: 14:31:59 time: 1.8564 data_time: 0.0033 memory: 4659 grad_norm: 0.1664 loss: 0.2487 loss_sem_seg: 0.2487 2023/05/14 23:47:29 - mmengine - INFO - Epoch(train) [7][ 700/1196] lr: 8.0000e-03 eta: 14:30:24 time: 1.3895 data_time: 0.0032 memory: 5237 grad_norm: 0.1508 loss: 0.2700 loss_sem_seg: 0.2700 2023/05/14 23:48:38 - mmengine - INFO - Epoch(train) [7][ 750/1196] lr: 8.0000e-03 eta: 14:28:45 time: 1.3751 data_time: 0.0031 memory: 5095 grad_norm: 0.1549 loss: 0.2835 loss_sem_seg: 0.2835 2023/05/14 23:49:48 - mmengine - INFO - Epoch(train) [7][ 800/1196] lr: 8.0000e-03 eta: 14:27:12 time: 1.3962 data_time: 0.0032 memory: 4635 grad_norm: 0.1580 loss: 0.2581 loss_sem_seg: 0.2581 2023/05/14 23:50:21 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 23:50:57 - mmengine - INFO - Epoch(train) [7][ 850/1196] lr: 8.0000e-03 eta: 14:25:35 time: 1.3780 data_time: 0.0031 memory: 5105 grad_norm: 0.1516 loss: 0.2547 loss_sem_seg: 0.2547 2023/05/14 23:52:05 - mmengine - INFO - Epoch(train) [7][ 900/1196] lr: 8.0000e-03 eta: 14:23:55 time: 1.3661 data_time: 0.0031 memory: 4649 grad_norm: 0.1528 loss: 0.2631 loss_sem_seg: 0.2631 2023/05/14 23:53:14 - mmengine - INFO - Epoch(train) [7][ 950/1196] lr: 8.0000e-03 eta: 14:22:19 time: 1.3772 data_time: 0.0031 memory: 4625 grad_norm: 0.1581 loss: 0.2446 loss_sem_seg: 0.2446 2023/05/14 23:54:24 - mmengine - INFO - Epoch(train) [7][1000/1196] lr: 8.0000e-03 eta: 14:20:47 time: 1.3975 data_time: 0.0033 memory: 4589 grad_norm: 0.1544 loss: 0.2761 loss_sem_seg: 0.2761 2023/05/14 23:55:32 - mmengine - INFO - Epoch(train) [7][1050/1196] lr: 8.0000e-03 eta: 14:19:07 time: 1.3597 data_time: 0.0032 memory: 4775 grad_norm: 0.1586 loss: 0.2586 loss_sem_seg: 0.2586 2023/05/14 23:57:03 - mmengine - INFO - Epoch(train) [7][1100/1196] lr: 8.0000e-03 eta: 14:19:03 time: 1.8143 data_time: 0.0031 memory: 5380 grad_norm: 0.1618 loss: 0.2757 loss_sem_seg: 0.2757 2023/05/14 23:58:11 - mmengine - INFO - Epoch(train) [7][1150/1196] lr: 8.0000e-03 eta: 14:17:24 time: 1.3593 data_time: 0.0031 memory: 4845 grad_norm: 0.1491 loss: 0.2731 loss_sem_seg: 0.2731 2023/05/14 23:59:13 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/14 23:59:13 - mmengine - INFO - Saving checkpoint at 7 epochs 2023/05/14 23:59:24 - mmengine - INFO - Epoch(val) [7][ 50/509] eta: 0:00:42 time: 0.0927 data_time: 0.0021 memory: 4912 2023/05/14 23:59:29 - mmengine - INFO - Epoch(val) [7][100/509] eta: 0:00:36 time: 0.0848 data_time: 0.0019 memory: 991 2023/05/14 23:59:33 - mmengine - INFO - Epoch(val) [7][150/509] eta: 0:00:31 time: 0.0829 data_time: 0.0019 memory: 994 2023/05/14 23:59:37 - mmengine - INFO - Epoch(val) [7][200/509] eta: 0:00:26 time: 0.0838 data_time: 0.0019 memory: 979 2023/05/14 23:59:41 - mmengine - INFO - Epoch(val) [7][250/509] eta: 0:00:22 time: 0.0881 data_time: 0.0020 memory: 1004 2023/05/14 23:59:45 - mmengine - INFO - Epoch(val) [7][300/509] eta: 0:00:17 time: 0.0766 data_time: 0.0019 memory: 946 2023/05/14 23:59:49 - mmengine - INFO - Epoch(val) [7][350/509] eta: 0:00:13 time: 0.0798 data_time: 0.0019 memory: 970 2023/05/14 23:59:53 - mmengine - INFO - Epoch(val) [7][400/509] eta: 0:00:09 time: 0.0843 data_time: 0.0019 memory: 978 2023/05/14 23:59:58 - mmengine - INFO - Epoch(val) [7][450/509] eta: 0:00:04 time: 0.0846 data_time: 0.0018 memory: 991 2023/05/15 00:00:02 - mmengine - INFO - Epoch(val) [7][500/509] eta: 0:00:00 time: 0.0782 data_time: 0.0017 memory: 973 2023/05/15 00:00:43 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9408 | 0.4478 | 0.6417 | 0.8114 | 0.3447 | 0.7019 | 0.7772 | 0.0171 | 0.9388 | 0.4044 | 0.8153 | 0.0190 | 0.9025 | 0.6200 | 0.8890 | 0.6146 | 0.7675 | 0.6450 | 0.4894 | 0.6204 | 0.9215 | 0.6851 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 00:00:43 - mmengine - INFO - Epoch(val) [7][509/509] car: 0.9408 bicycle: 0.4478 motorcycle: 0.6417 truck: 0.8114 bus: 0.3447 person: 0.7019 bicyclist: 0.7772 motorcyclist: 0.0171 road: 0.9388 parking: 0.4044 sidewalk: 0.8153 other-ground: 0.0190 building: 0.9025 fence: 0.6200 vegetation: 0.8890 trunck: 0.6146 terrian: 0.7675 pole: 0.6450 traffic-sign: 0.4894 miou: 0.6204 acc: 0.9215 acc_cls: 0.6851 data_time: 0.0017 time: 0.0800 2023/05/15 00:01:52 - mmengine - INFO - Epoch(train) [8][ 50/1196] lr: 8.0000e-03 eta: 14:14:16 time: 1.3728 data_time: 0.0043 memory: 4691 grad_norm: 0.1498 loss: 0.2876 loss_sem_seg: 0.2876 2023/05/15 00:03:01 - mmengine - INFO - Epoch(train) [8][ 100/1196] lr: 8.0000e-03 eta: 14:12:41 time: 1.3738 data_time: 0.0031 memory: 4916 grad_norm: 0.1614 loss: 0.2637 loss_sem_seg: 0.2637 2023/05/15 00:04:10 - mmengine - INFO - Epoch(train) [8][ 150/1196] lr: 8.0000e-03 eta: 14:11:07 time: 1.3805 data_time: 0.0032 memory: 4841 grad_norm: 0.1605 loss: 0.2584 loss_sem_seg: 0.2584 2023/05/15 00:05:19 - mmengine - INFO - Epoch(train) [8][ 200/1196] lr: 8.0000e-03 eta: 14:09:34 time: 1.3837 data_time: 0.0030 memory: 4428 grad_norm: 0.1431 loss: 0.2716 loss_sem_seg: 0.2716 2023/05/15 00:06:28 - mmengine - INFO - Epoch(train) [8][ 250/1196] lr: 8.0000e-03 eta: 14:08:00 time: 1.3788 data_time: 0.0031 memory: 4864 grad_norm: 0.1703 loss: 0.2673 loss_sem_seg: 0.2673 2023/05/15 00:07:36 - mmengine - INFO - Epoch(train) [8][ 300/1196] lr: 8.0000e-03 eta: 14:06:24 time: 1.3657 data_time: 0.0031 memory: 4909 grad_norm: 0.1474 loss: 0.2505 loss_sem_seg: 0.2505 2023/05/15 00:08:45 - mmengine - INFO - Epoch(train) [8][ 350/1196] lr: 8.0000e-03 eta: 14:04:50 time: 1.3760 data_time: 0.0031 memory: 4675 grad_norm: 0.1700 loss: 0.2651 loss_sem_seg: 0.2651 2023/05/15 00:09:53 - mmengine - INFO - Epoch(train) [8][ 400/1196] lr: 8.0000e-03 eta: 14:03:15 time: 1.3694 data_time: 0.0030 memory: 4660 grad_norm: 0.1601 loss: 0.2719 loss_sem_seg: 0.2719 2023/05/15 00:11:03 - mmengine - INFO - Epoch(train) [8][ 450/1196] lr: 8.0000e-03 eta: 14:01:44 time: 1.3865 data_time: 0.0030 memory: 4833 grad_norm: 0.1523 loss: 0.2444 loss_sem_seg: 0.2444 2023/05/15 00:12:12 - mmengine - INFO - Epoch(train) [8][ 500/1196] lr: 8.0000e-03 eta: 14:00:12 time: 1.3804 data_time: 0.0030 memory: 5032 grad_norm: 0.1418 loss: 0.2551 loss_sem_seg: 0.2551 2023/05/15 00:13:20 - mmengine - INFO - Epoch(train) [8][ 550/1196] lr: 8.0000e-03 eta: 13:58:38 time: 1.3671 data_time: 0.0031 memory: 4545 grad_norm: 0.1403 loss: 0.2691 loss_sem_seg: 0.2691 2023/05/15 00:14:29 - mmengine - INFO - Epoch(train) [8][ 600/1196] lr: 8.0000e-03 eta: 13:57:06 time: 1.3802 data_time: 0.0031 memory: 4721 grad_norm: 0.1446 loss: 0.2635 loss_sem_seg: 0.2635 2023/05/15 00:15:08 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 00:15:37 - mmengine - INFO - Epoch(train) [8][ 650/1196] lr: 8.0000e-03 eta: 13:55:32 time: 1.3650 data_time: 0.0031 memory: 4405 grad_norm: 0.1505 loss: 0.2735 loss_sem_seg: 0.2735 2023/05/15 00:16:48 - mmengine - INFO - Epoch(train) [8][ 700/1196] lr: 8.0000e-03 eta: 13:54:07 time: 1.4091 data_time: 0.0031 memory: 4847 grad_norm: 0.1393 loss: 0.2688 loss_sem_seg: 0.2688 2023/05/15 00:17:56 - mmengine - INFO - Epoch(train) [8][ 750/1196] lr: 8.0000e-03 eta: 13:52:31 time: 1.3536 data_time: 0.0032 memory: 5060 grad_norm: 0.1463 loss: 0.2574 loss_sem_seg: 0.2574 2023/05/15 00:19:04 - mmengine - INFO - Epoch(train) [8][ 800/1196] lr: 8.0000e-03 eta: 13:50:57 time: 1.3640 data_time: 0.0030 memory: 4695 grad_norm: 0.1361 loss: 0.2503 loss_sem_seg: 0.2503 2023/05/15 00:20:12 - mmengine - INFO - Epoch(train) [8][ 850/1196] lr: 8.0000e-03 eta: 13:49:22 time: 1.3551 data_time: 0.0031 memory: 5161 grad_norm: 0.1765 loss: 0.2688 loss_sem_seg: 0.2688 2023/05/15 00:21:22 - mmengine - INFO - Epoch(train) [8][ 900/1196] lr: 8.0000e-03 eta: 13:47:56 time: 1.4016 data_time: 0.0031 memory: 4622 grad_norm: 0.1278 loss: 0.2635 loss_sem_seg: 0.2635 2023/05/15 00:22:31 - mmengine - INFO - Epoch(train) [8][ 950/1196] lr: 8.0000e-03 eta: 13:46:26 time: 1.3808 data_time: 0.0031 memory: 4622 grad_norm: 0.1300 loss: 0.2479 loss_sem_seg: 0.2479 2023/05/15 00:23:40 - mmengine - INFO - Epoch(train) [8][1000/1196] lr: 8.0000e-03 eta: 13:44:56 time: 1.3779 data_time: 0.0031 memory: 4683 grad_norm: 0.1497 loss: 0.2622 loss_sem_seg: 0.2622 2023/05/15 00:24:48 - mmengine - INFO - Epoch(train) [8][1050/1196] lr: 8.0000e-03 eta: 13:43:27 time: 1.3777 data_time: 0.0031 memory: 5346 grad_norm: 0.1340 loss: 0.2708 loss_sem_seg: 0.2708 2023/05/15 00:25:59 - mmengine - INFO - Epoch(train) [8][1100/1196] lr: 8.0000e-03 eta: 13:42:03 time: 1.4098 data_time: 0.0031 memory: 4837 grad_norm: 0.1399 loss: 0.2450 loss_sem_seg: 0.2450 2023/05/15 00:27:10 - mmengine - INFO - Epoch(train) [8][1150/1196] lr: 8.0000e-03 eta: 13:40:41 time: 1.4214 data_time: 0.0031 memory: 4794 grad_norm: 0.1312 loss: 0.2414 loss_sem_seg: 0.2414 2023/05/15 00:28:33 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 00:28:33 - mmengine - INFO - Saving checkpoint at 8 epochs 2023/05/15 00:28:44 - mmengine - INFO - Epoch(val) [8][ 50/509] eta: 0:00:42 time: 0.0934 data_time: 0.0021 memory: 4942 2023/05/15 00:28:48 - mmengine - INFO - Epoch(val) [8][100/509] eta: 0:00:36 time: 0.0852 data_time: 0.0019 memory: 991 2023/05/15 00:28:52 - mmengine - INFO - Epoch(val) [8][150/509] eta: 0:00:31 time: 0.0828 data_time: 0.0019 memory: 994 2023/05/15 00:28:56 - mmengine - INFO - Epoch(val) [8][200/509] eta: 0:00:26 time: 0.0843 data_time: 0.0019 memory: 979 2023/05/15 00:29:01 - mmengine - INFO - Epoch(val) [8][250/509] eta: 0:00:22 time: 0.0885 data_time: 0.0020 memory: 1004 2023/05/15 00:29:05 - mmengine - INFO - Epoch(val) [8][300/509] eta: 0:00:17 time: 0.0806 data_time: 0.0019 memory: 946 2023/05/15 00:29:09 - mmengine - INFO - Epoch(val) [8][350/509] eta: 0:00:13 time: 0.0801 data_time: 0.0019 memory: 970 2023/05/15 00:29:13 - mmengine - INFO - Epoch(val) [8][400/509] eta: 0:00:09 time: 0.0851 data_time: 0.0019 memory: 978 2023/05/15 00:29:17 - mmengine - INFO - Epoch(val) [8][450/509] eta: 0:00:05 time: 0.0853 data_time: 0.0018 memory: 991 2023/05/15 00:29:21 - mmengine - INFO - Epoch(val) [8][500/509] eta: 0:00:00 time: 0.0784 data_time: 0.0017 memory: 973 2023/05/15 00:30:01 - 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 | 0.9526 | 0.4837 | 0.6761 | 0.7357 | 0.5234 | 0.6839 | 0.7039 | 0.0403 | 0.9330 | 0.4178 | 0.8223 | 0.0410 | 0.9086 | 0.5971 | 0.8687 | 0.6902 | 0.7238 | 0.6467 | 0.4593 | 0.6267 | 0.9149 | 0.7230 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 00:30:01 - mmengine - INFO - Epoch(val) [8][509/509] car: 0.9526 bicycle: 0.4837 motorcycle: 0.6761 truck: 0.7357 bus: 0.5234 person: 0.6839 bicyclist: 0.7039 motorcyclist: 0.0403 road: 0.9330 parking: 0.4178 sidewalk: 0.8223 other-ground: 0.0410 building: 0.9086 fence: 0.5971 vegetation: 0.8687 trunck: 0.6902 terrian: 0.7238 pole: 0.6467 traffic-sign: 0.4593 miou: 0.6267 acc: 0.9149 acc_cls: 0.7230 data_time: 0.0017 time: 0.0801 2023/05/15 00:31:11 - mmengine - INFO - Epoch(train) [9][ 50/1196] lr: 8.0000e-03 eta: 13:39:00 time: 1.3953 data_time: 0.0038 memory: 4882 grad_norm: 0.1497 loss: 0.2397 loss_sem_seg: 0.2397 2023/05/15 00:32:18 - mmengine - INFO - Epoch(train) [9][ 100/1196] lr: 8.0000e-03 eta: 13:37:25 time: 1.3491 data_time: 0.0030 memory: 4637 grad_norm: 0.1400 loss: 0.2629 loss_sem_seg: 0.2629 2023/05/15 00:33:27 - mmengine - INFO - Epoch(train) [9][ 150/1196] lr: 8.0000e-03 eta: 13:35:56 time: 1.3781 data_time: 0.0031 memory: 4896 grad_norm: 0.1389 loss: 0.2476 loss_sem_seg: 0.2476 2023/05/15 00:34:37 - mmengine - INFO - Epoch(train) [9][ 200/1196] lr: 8.0000e-03 eta: 13:34:29 time: 1.3847 data_time: 0.0031 memory: 4823 grad_norm: 0.1296 loss: 0.2581 loss_sem_seg: 0.2581 2023/05/15 00:35:46 - mmengine - INFO - Epoch(train) [9][ 250/1196] lr: 8.0000e-03 eta: 13:33:01 time: 1.3863 data_time: 0.0031 memory: 4639 grad_norm: 0.1285 loss: 0.2472 loss_sem_seg: 0.2472 2023/05/15 00:36:55 - mmengine - INFO - Epoch(train) [9][ 300/1196] lr: 8.0000e-03 eta: 13:31:33 time: 1.3748 data_time: 0.0030 memory: 4696 grad_norm: 0.1198 loss: 0.2533 loss_sem_seg: 0.2533 2023/05/15 00:38:04 - mmengine - INFO - Epoch(train) [9][ 350/1196] lr: 8.0000e-03 eta: 13:30:06 time: 1.3899 data_time: 0.0030 memory: 4642 grad_norm: 0.1469 loss: 0.2595 loss_sem_seg: 0.2595 2023/05/15 00:39:34 - mmengine - INFO - Epoch(train) [9][ 400/1196] lr: 8.0000e-03 eta: 13:29:46 time: 1.7888 data_time: 0.0032 memory: 4962 grad_norm: 0.1403 loss: 0.2733 loss_sem_seg: 0.2733 2023/05/15 00:40:18 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 00:40:43 - mmengine - INFO - Epoch(train) [9][ 450/1196] lr: 8.0000e-03 eta: 13:28:20 time: 1.3894 data_time: 0.0031 memory: 4825 grad_norm: 0.1267 loss: 0.2764 loss_sem_seg: 0.2764 2023/05/15 00:41:52 - mmengine - INFO - Epoch(train) [9][ 500/1196] lr: 8.0000e-03 eta: 13:26:52 time: 1.3812 data_time: 0.0032 memory: 5137 grad_norm: 0.1585 loss: 0.2620 loss_sem_seg: 0.2620 2023/05/15 00:43:01 - mmengine - INFO - Epoch(train) [9][ 550/1196] lr: 8.0000e-03 eta: 13:25:24 time: 1.3766 data_time: 0.0033 memory: 4606 grad_norm: 0.1386 loss: 0.2638 loss_sem_seg: 0.2638 2023/05/15 00:44:10 - mmengine - INFO - Epoch(train) [9][ 600/1196] lr: 8.0000e-03 eta: 13:23:56 time: 1.3740 data_time: 0.0033 memory: 4559 grad_norm: 0.1378 loss: 0.2394 loss_sem_seg: 0.2394 2023/05/15 00:45:19 - mmengine - INFO - Epoch(train) [9][ 650/1196] lr: 8.0000e-03 eta: 13:22:30 time: 1.3895 data_time: 0.0033 memory: 5211 grad_norm: 0.1433 loss: 0.2488 loss_sem_seg: 0.2488 2023/05/15 00:46:28 - mmengine - INFO - Epoch(train) [9][ 700/1196] lr: 8.0000e-03 eta: 13:21:04 time: 1.3849 data_time: 0.0033 memory: 4870 grad_norm: 0.1381 loss: 0.2674 loss_sem_seg: 0.2674 2023/05/15 00:47:36 - mmengine - INFO - Epoch(train) [9][ 750/1196] lr: 8.0000e-03 eta: 13:19:34 time: 1.3603 data_time: 0.0033 memory: 5105 grad_norm: 0.1388 loss: 0.2519 loss_sem_seg: 0.2519 2023/05/15 00:48:45 - mmengine - INFO - Epoch(train) [9][ 800/1196] lr: 8.0000e-03 eta: 13:18:06 time: 1.3760 data_time: 0.0033 memory: 4860 grad_norm: 0.1440 loss: 0.2573 loss_sem_seg: 0.2573 2023/05/15 00:49:52 - mmengine - INFO - Epoch(train) [9][ 850/1196] lr: 8.0000e-03 eta: 13:16:33 time: 1.3374 data_time: 0.0033 memory: 4637 grad_norm: 0.1473 loss: 0.2596 loss_sem_seg: 0.2596 2023/05/15 00:51:01 - mmengine - INFO - Epoch(train) [9][ 900/1196] lr: 8.0000e-03 eta: 13:15:06 time: 1.3744 data_time: 0.0033 memory: 4687 grad_norm: 0.1376 loss: 0.2585 loss_sem_seg: 0.2585 2023/05/15 00:52:09 - mmengine - INFO - Epoch(train) [9][ 950/1196] lr: 8.0000e-03 eta: 13:13:38 time: 1.3699 data_time: 0.0033 memory: 5100 grad_norm: 0.1315 loss: 0.2491 loss_sem_seg: 0.2491 2023/05/15 00:53:19 - mmengine - INFO - Epoch(train) [9][1000/1196] lr: 8.0000e-03 eta: 13:12:13 time: 1.3889 data_time: 0.0033 memory: 4845 grad_norm: 0.1267 loss: 0.2473 loss_sem_seg: 0.2473 2023/05/15 00:54:27 - mmengine - INFO - Epoch(train) [9][1050/1196] lr: 8.0000e-03 eta: 13:10:46 time: 1.3710 data_time: 0.0031 memory: 4717 grad_norm: 0.1466 loss: 0.2451 loss_sem_seg: 0.2451 2023/05/15 00:55:37 - mmengine - INFO - Epoch(train) [9][1100/1196] lr: 8.0000e-03 eta: 13:09:24 time: 1.4004 data_time: 0.0031 memory: 4688 grad_norm: 0.1155 loss: 0.2610 loss_sem_seg: 0.2610 2023/05/15 00:56:46 - mmengine - INFO - Epoch(train) [9][1150/1196] lr: 8.0000e-03 eta: 13:07:57 time: 1.3724 data_time: 0.0031 memory: 5486 grad_norm: 0.1217 loss: 0.2385 loss_sem_seg: 0.2385 2023/05/15 00:57:49 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 00:57:49 - mmengine - INFO - Saving checkpoint at 9 epochs 2023/05/15 00:58:01 - mmengine - INFO - Epoch(val) [9][ 50/509] eta: 0:00:42 time: 0.0930 data_time: 0.0021 memory: 4527 2023/05/15 00:58:05 - mmengine - INFO - Epoch(val) [9][100/509] eta: 0:00:36 time: 0.0847 data_time: 0.0020 memory: 991 2023/05/15 00:58:09 - mmengine - INFO - Epoch(val) [9][150/509] eta: 0:00:31 time: 0.0827 data_time: 0.0019 memory: 994 2023/05/15 00:58:13 - mmengine - INFO - Epoch(val) [9][200/509] eta: 0:00:26 time: 0.0839 data_time: 0.0019 memory: 979 2023/05/15 00:58:18 - mmengine - INFO - Epoch(val) [9][250/509] eta: 0:00:22 time: 0.0882 data_time: 0.0019 memory: 1004 2023/05/15 00:58:21 - mmengine - INFO - Epoch(val) [9][300/509] eta: 0:00:17 time: 0.0764 data_time: 0.0019 memory: 946 2023/05/15 00:58:25 - mmengine - INFO - Epoch(val) [9][350/509] eta: 0:00:13 time: 0.0793 data_time: 0.0019 memory: 970 2023/05/15 00:58:30 - mmengine - INFO - Epoch(val) [9][400/509] eta: 0:00:09 time: 0.0849 data_time: 0.0019 memory: 978 2023/05/15 00:58:34 - mmengine - INFO - Epoch(val) [9][450/509] eta: 0:00:04 time: 0.0849 data_time: 0.0018 memory: 991 2023/05/15 00:58:38 - mmengine - INFO - Epoch(val) [9][500/509] eta: 0:00:00 time: 0.0785 data_time: 0.0017 memory: 973 2023/05/15 00:59:18 - 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 | 0.9725 | 0.4938 | 0.7314 | 0.7807 | 0.7220 | 0.6778 | 0.8007 | 0.0298 | 0.9300 | 0.4871 | 0.8101 | 0.0872 | 0.9051 | 0.6203 | 0.8966 | 0.6274 | 0.7842 | 0.6505 | 0.4524 | 0.6558 | 0.9251 | 0.7348 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 00:59:18 - mmengine - INFO - Epoch(val) [9][509/509] car: 0.9725 bicycle: 0.4938 motorcycle: 0.7314 truck: 0.7807 bus: 0.7220 person: 0.6778 bicyclist: 0.8007 motorcyclist: 0.0298 road: 0.9300 parking: 0.4871 sidewalk: 0.8101 other-ground: 0.0872 building: 0.9051 fence: 0.6203 vegetation: 0.8966 trunck: 0.6274 terrian: 0.7842 pole: 0.6505 traffic-sign: 0.4524 miou: 0.6558 acc: 0.9251 acc_cls: 0.7348 data_time: 0.0017 time: 0.0802 2023/05/15 01:00:28 - mmengine - INFO - Epoch(train) [10][ 50/1196] lr: 8.0000e-03 eta: 13:05:15 time: 1.4007 data_time: 0.0039 memory: 4899 grad_norm: 0.1363 loss: 0.2522 loss_sem_seg: 0.2522 2023/05/15 01:01:38 - mmengine - INFO - Epoch(train) [10][ 100/1196] lr: 8.0000e-03 eta: 13:03:54 time: 1.4071 data_time: 0.0031 memory: 4972 grad_norm: 0.1314 loss: 0.2481 loss_sem_seg: 0.2481 2023/05/15 01:02:47 - mmengine - INFO - Epoch(train) [10][ 150/1196] lr: 8.0000e-03 eta: 13:02:30 time: 1.3878 data_time: 0.0031 memory: 5074 grad_norm: 0.1232 loss: 0.2428 loss_sem_seg: 0.2428 2023/05/15 01:03:57 - mmengine - INFO - Epoch(train) [10][ 200/1196] lr: 8.0000e-03 eta: 13:01:09 time: 1.4022 data_time: 0.0031 memory: 4678 grad_norm: 0.1299 loss: 0.2388 loss_sem_seg: 0.2388 2023/05/15 01:04:47 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 01:05:07 - mmengine - INFO - Epoch(train) [10][ 250/1196] lr: 8.0000e-03 eta: 12:59:44 time: 1.3824 data_time: 0.0031 memory: 4648 grad_norm: 0.1410 loss: 0.2476 loss_sem_seg: 0.2476 2023/05/15 01:06:16 - mmengine - INFO - Epoch(train) [10][ 300/1196] lr: 8.0000e-03 eta: 12:58:22 time: 1.3923 data_time: 0.0031 memory: 4828 grad_norm: 0.1608 loss: 0.2377 loss_sem_seg: 0.2377 2023/05/15 01:07:27 - mmengine - INFO - Epoch(train) [10][ 350/1196] lr: 8.0000e-03 eta: 12:57:02 time: 1.4109 data_time: 0.0031 memory: 4876 grad_norm: 0.1227 loss: 0.2365 loss_sem_seg: 0.2365 2023/05/15 01:08:35 - mmengine - INFO - Epoch(train) [10][ 400/1196] lr: 8.0000e-03 eta: 12:55:36 time: 1.3720 data_time: 0.0031 memory: 4672 grad_norm: 0.1296 loss: 0.2710 loss_sem_seg: 0.2710 2023/05/15 01:09:58 - mmengine - INFO - Epoch(train) [10][ 450/1196] lr: 8.0000e-03 eta: 12:54:51 time: 1.6546 data_time: 0.0031 memory: 4756 grad_norm: 0.1342 loss: 0.2581 loss_sem_seg: 0.2581 2023/05/15 01:11:14 - mmengine - INFO - Epoch(train) [10][ 500/1196] lr: 8.0000e-03 eta: 12:53:45 time: 1.5084 data_time: 0.0031 memory: 5008 grad_norm: 0.1287 loss: 0.2603 loss_sem_seg: 0.2603 2023/05/15 01:12:22 - mmengine - INFO - Epoch(train) [10][ 550/1196] lr: 8.0000e-03 eta: 12:52:19 time: 1.3715 data_time: 0.0030 memory: 4586 grad_norm: 0.1389 loss: 0.2445 loss_sem_seg: 0.2445 2023/05/15 01:13:30 - mmengine - INFO - Epoch(train) [10][ 600/1196] lr: 8.0000e-03 eta: 12:50:52 time: 1.3547 data_time: 0.0031 memory: 4610 grad_norm: 0.1361 loss: 0.2458 loss_sem_seg: 0.2458 2023/05/15 01:14:39 - mmengine - INFO - Epoch(train) [10][ 650/1196] lr: 8.0000e-03 eta: 12:49:29 time: 1.3912 data_time: 0.0031 memory: 5049 grad_norm: 0.1343 loss: 0.2651 loss_sem_seg: 0.2651 2023/05/15 01:15:49 - mmengine - INFO - Epoch(train) [10][ 700/1196] lr: 8.0000e-03 eta: 12:48:06 time: 1.3884 data_time: 0.0031 memory: 4714 grad_norm: 0.1307 loss: 0.2662 loss_sem_seg: 0.2662 2023/05/15 01:16:57 - mmengine - INFO - Epoch(train) [10][ 750/1196] lr: 8.0000e-03 eta: 12:46:41 time: 1.3715 data_time: 0.0030 memory: 4849 grad_norm: 0.1398 loss: 0.2500 loss_sem_seg: 0.2500 2023/05/15 01:18:06 - mmengine - INFO - Epoch(train) [10][ 800/1196] lr: 8.0000e-03 eta: 12:45:17 time: 1.3768 data_time: 0.0031 memory: 4907 grad_norm: 0.1221 loss: 0.2587 loss_sem_seg: 0.2587 2023/05/15 01:19:14 - mmengine - INFO - Epoch(train) [10][ 850/1196] lr: 8.0000e-03 eta: 12:43:52 time: 1.3638 data_time: 0.0031 memory: 4629 grad_norm: 0.1367 loss: 0.2491 loss_sem_seg: 0.2491 2023/05/15 01:20:26 - mmengine - INFO - Epoch(train) [10][ 900/1196] lr: 8.0000e-03 eta: 12:42:37 time: 1.4407 data_time: 0.0031 memory: 4716 grad_norm: 0.1295 loss: 0.2526 loss_sem_seg: 0.2526 2023/05/15 01:21:53 - mmengine - INFO - Epoch(train) [10][ 950/1196] lr: 8.0000e-03 eta: 12:42:01 time: 1.7368 data_time: 0.0031 memory: 4619 grad_norm: 0.1248 loss: 0.2460 loss_sem_seg: 0.2460 2023/05/15 01:23:03 - mmengine - INFO - Epoch(train) [10][1000/1196] lr: 8.0000e-03 eta: 12:40:38 time: 1.3863 data_time: 0.0031 memory: 4624 grad_norm: 0.1427 loss: 0.2531 loss_sem_seg: 0.2531 2023/05/15 01:24:11 - mmengine - INFO - Epoch(train) [10][1050/1196] lr: 8.0000e-03 eta: 12:39:13 time: 1.3616 data_time: 0.0030 memory: 4733 grad_norm: 0.1328 loss: 0.2482 loss_sem_seg: 0.2482 2023/05/15 01:25:20 - mmengine - INFO - Epoch(train) [10][1100/1196] lr: 8.0000e-03 eta: 12:37:50 time: 1.3841 data_time: 0.0030 memory: 4755 grad_norm: 0.1279 loss: 0.2494 loss_sem_seg: 0.2494 2023/05/15 01:26:30 - mmengine - INFO - Epoch(train) [10][1150/1196] lr: 8.0000e-03 eta: 12:36:30 time: 1.4007 data_time: 0.0031 memory: 4623 grad_norm: 0.1300 loss: 0.2488 loss_sem_seg: 0.2488 2023/05/15 01:27:34 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 01:27:34 - mmengine - INFO - Saving checkpoint at 10 epochs 2023/05/15 01:27:45 - mmengine - INFO - Epoch(val) [10][ 50/509] eta: 0:00:42 time: 0.0930 data_time: 0.0021 memory: 4950 2023/05/15 01:27:50 - mmengine - INFO - Epoch(val) [10][100/509] eta: 0:00:36 time: 0.0855 data_time: 0.0020 memory: 991 2023/05/15 01:27:54 - mmengine - INFO - Epoch(val) [10][150/509] eta: 0:00:31 time: 0.0835 data_time: 0.0019 memory: 994 2023/05/15 01:27:58 - mmengine - INFO - Epoch(val) [10][200/509] eta: 0:00:26 time: 0.0844 data_time: 0.0020 memory: 979 2023/05/15 01:28:02 - mmengine - INFO - Epoch(val) [10][250/509] eta: 0:00:22 time: 0.0885 data_time: 0.0019 memory: 1004 2023/05/15 01:28:06 - mmengine - INFO - Epoch(val) [10][300/509] eta: 0:00:17 time: 0.0772 data_time: 0.0019 memory: 946 2023/05/15 01:28:10 - mmengine - INFO - Epoch(val) [10][350/509] eta: 0:00:13 time: 0.0839 data_time: 0.0019 memory: 970 2023/05/15 01:28:15 - mmengine - INFO - Epoch(val) [10][400/509] eta: 0:00:09 time: 0.0843 data_time: 0.0019 memory: 978 2023/05/15 01:28:19 - mmengine - INFO - Epoch(val) [10][450/509] eta: 0:00:05 time: 0.0845 data_time: 0.0018 memory: 991 2023/05/15 01:28:23 - mmengine - INFO - Epoch(val) [10][500/509] eta: 0:00:00 time: 0.0787 data_time: 0.0017 memory: 973 2023/05/15 01:29:03 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9535 | 0.4262 | 0.7377 | 0.6902 | 0.4791 | 0.7109 | 0.8395 | 0.1167 | 0.9358 | 0.4518 | 0.8195 | 0.0046 | 0.8996 | 0.5897 | 0.8932 | 0.6863 | 0.7804 | 0.6108 | 0.4967 | 0.6380 | 0.9235 | 0.7164 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 01:29:03 - mmengine - INFO - Epoch(val) [10][509/509] car: 0.9535 bicycle: 0.4262 motorcycle: 0.7377 truck: 0.6902 bus: 0.4791 person: 0.7109 bicyclist: 0.8395 motorcyclist: 0.1167 road: 0.9358 parking: 0.4518 sidewalk: 0.8195 other-ground: 0.0046 building: 0.8996 fence: 0.5897 vegetation: 0.8932 trunck: 0.6863 terrian: 0.7804 pole: 0.6108 traffic-sign: 0.4967 miou: 0.6380 acc: 0.9235 acc_cls: 0.7164 data_time: 0.0017 time: 0.0806 2023/05/15 01:29:59 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 01:30:12 - mmengine - INFO - Epoch(train) [11][ 50/1196] lr: 8.0000e-03 eta: 12:33:53 time: 1.3853 data_time: 0.0038 memory: 4562 grad_norm: 0.1320 loss: 0.2404 loss_sem_seg: 0.2404 2023/05/15 01:31:22 - mmengine - INFO - Epoch(train) [11][ 100/1196] lr: 8.0000e-03 eta: 12:32:32 time: 1.3970 data_time: 0.0032 memory: 4683 grad_norm: 0.1173 loss: 0.2415 loss_sem_seg: 0.2415 2023/05/15 01:32:31 - mmengine - INFO - Epoch(train) [11][ 150/1196] lr: 8.0000e-03 eta: 12:31:10 time: 1.3829 data_time: 0.0032 memory: 5244 grad_norm: 0.1261 loss: 0.2497 loss_sem_seg: 0.2497 2023/05/15 01:33:40 - mmengine - INFO - Epoch(train) [11][ 200/1196] lr: 8.0000e-03 eta: 12:29:46 time: 1.3689 data_time: 0.0032 memory: 4759 grad_norm: 0.1233 loss: 0.2487 loss_sem_seg: 0.2487 2023/05/15 01:34:48 - mmengine - INFO - Epoch(train) [11][ 250/1196] lr: 8.0000e-03 eta: 12:28:23 time: 1.3769 data_time: 0.0033 memory: 4444 grad_norm: 0.1139 loss: 0.2417 loss_sem_seg: 0.2417 2023/05/15 01:35:58 - mmengine - INFO - Epoch(train) [11][ 300/1196] lr: 8.0000e-03 eta: 12:27:03 time: 1.3949 data_time: 0.0032 memory: 4455 grad_norm: 0.1216 loss: 0.2323 loss_sem_seg: 0.2323 2023/05/15 01:37:08 - mmengine - INFO - Epoch(train) [11][ 350/1196] lr: 8.0000e-03 eta: 12:25:43 time: 1.3982 data_time: 0.0031 memory: 5090 grad_norm: 0.1367 loss: 0.2423 loss_sem_seg: 0.2423 2023/05/15 01:38:16 - mmengine - INFO - Epoch(train) [11][ 400/1196] lr: 8.0000e-03 eta: 12:24:17 time: 1.3522 data_time: 0.0031 memory: 4878 grad_norm: 0.1376 loss: 0.2213 loss_sem_seg: 0.2213 2023/05/15 01:39:23 - mmengine - INFO - Epoch(train) [11][ 450/1196] lr: 8.0000e-03 eta: 12:22:52 time: 1.3512 data_time: 0.0031 memory: 4625 grad_norm: 0.1351 loss: 0.2346 loss_sem_seg: 0.2346 2023/05/15 01:40:32 - mmengine - INFO - Epoch(train) [11][ 500/1196] lr: 8.0000e-03 eta: 12:21:30 time: 1.3760 data_time: 0.0031 memory: 4919 grad_norm: 0.1352 loss: 0.2693 loss_sem_seg: 0.2693 2023/05/15 01:41:41 - mmengine - INFO - Epoch(train) [11][ 550/1196] lr: 8.0000e-03 eta: 12:20:09 time: 1.3896 data_time: 0.0031 memory: 4628 grad_norm: 0.1315 loss: 0.2340 loss_sem_seg: 0.2340 2023/05/15 01:42:50 - mmengine - INFO - Epoch(train) [11][ 600/1196] lr: 8.0000e-03 eta: 12:18:47 time: 1.3738 data_time: 0.0031 memory: 4531 grad_norm: 0.1189 loss: 0.2275 loss_sem_seg: 0.2275 2023/05/15 01:44:00 - mmengine - INFO - Epoch(train) [11][ 650/1196] lr: 8.0000e-03 eta: 12:17:26 time: 1.3872 data_time: 0.0031 memory: 5068 grad_norm: 0.1150 loss: 0.2479 loss_sem_seg: 0.2479 2023/05/15 01:45:09 - mmengine - INFO - Epoch(train) [11][ 700/1196] lr: 8.0000e-03 eta: 12:16:05 time: 1.3842 data_time: 0.0031 memory: 4366 grad_norm: 0.1138 loss: 0.2546 loss_sem_seg: 0.2546 2023/05/15 01:46:19 - mmengine - INFO - Epoch(train) [11][ 750/1196] lr: 8.0000e-03 eta: 12:14:47 time: 1.4118 data_time: 0.0031 memory: 4918 grad_norm: 0.1249 loss: 0.2583 loss_sem_seg: 0.2583 2023/05/15 01:47:28 - mmengine - INFO - Epoch(train) [11][ 800/1196] lr: 8.0000e-03 eta: 12:13:26 time: 1.3810 data_time: 0.0031 memory: 4491 grad_norm: 0.1179 loss: 0.2306 loss_sem_seg: 0.2306 2023/05/15 01:48:38 - mmengine - INFO - Epoch(train) [11][ 850/1196] lr: 8.0000e-03 eta: 12:12:06 time: 1.3897 data_time: 0.0031 memory: 4600 grad_norm: 0.1289 loss: 0.2305 loss_sem_seg: 0.2305 2023/05/15 01:49:46 - mmengine - INFO - Epoch(train) [11][ 900/1196] lr: 8.0000e-03 eta: 12:10:43 time: 1.3625 data_time: 0.0031 memory: 5378 grad_norm: 0.1243 loss: 0.2295 loss_sem_seg: 0.2295 2023/05/15 01:50:57 - mmengine - INFO - Epoch(train) [11][ 950/1196] lr: 8.0000e-03 eta: 12:09:27 time: 1.4239 data_time: 0.0031 memory: 4959 grad_norm: 0.1155 loss: 0.2471 loss_sem_seg: 0.2471 2023/05/15 01:52:29 - mmengine - INFO - Epoch(train) [11][1000/1196] lr: 8.0000e-03 eta: 12:08:59 time: 1.8374 data_time: 0.0031 memory: 4682 grad_norm: 0.1241 loss: 0.2540 loss_sem_seg: 0.2540 2023/05/15 01:53:24 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 01:53:38 - mmengine - INFO - Epoch(train) [11][1050/1196] lr: 8.0000e-03 eta: 12:07:38 time: 1.3788 data_time: 0.0031 memory: 4774 grad_norm: 0.1259 loss: 0.2297 loss_sem_seg: 0.2297 2023/05/15 01:54:47 - mmengine - INFO - Epoch(train) [11][1100/1196] lr: 8.0000e-03 eta: 12:06:17 time: 1.3772 data_time: 0.0032 memory: 4998 grad_norm: 0.1187 loss: 0.2298 loss_sem_seg: 0.2298 2023/05/15 01:55:56 - mmengine - INFO - Epoch(train) [11][1150/1196] lr: 8.0000e-03 eta: 12:04:57 time: 1.3888 data_time: 0.0032 memory: 5127 grad_norm: 0.1196 loss: 0.2468 loss_sem_seg: 0.2468 2023/05/15 01:56:59 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 01:56:59 - mmengine - INFO - Saving checkpoint at 11 epochs 2023/05/15 01:57:10 - mmengine - INFO - Epoch(val) [11][ 50/509] eta: 0:00:42 time: 0.0925 data_time: 0.0021 memory: 4904 2023/05/15 01:57:14 - mmengine - INFO - Epoch(val) [11][100/509] eta: 0:00:36 time: 0.0849 data_time: 0.0020 memory: 991 2023/05/15 01:57:18 - mmengine - INFO - Epoch(val) [11][150/509] eta: 0:00:31 time: 0.0832 data_time: 0.0020 memory: 994 2023/05/15 01:57:23 - mmengine - INFO - Epoch(val) [11][200/509] eta: 0:00:26 time: 0.0842 data_time: 0.0020 memory: 979 2023/05/15 01:57:27 - mmengine - INFO - Epoch(val) [11][250/509] eta: 0:00:22 time: 0.0889 data_time: 0.0019 memory: 1004 2023/05/15 01:57:31 - mmengine - INFO - Epoch(val) [11][300/509] eta: 0:00:17 time: 0.0769 data_time: 0.0019 memory: 946 2023/05/15 01:57:35 - mmengine - INFO - Epoch(val) [11][350/509] eta: 0:00:13 time: 0.0798 data_time: 0.0019 memory: 970 2023/05/15 01:57:39 - mmengine - INFO - Epoch(val) [11][400/509] eta: 0:00:09 time: 0.0852 data_time: 0.0019 memory: 978 2023/05/15 01:57:43 - mmengine - INFO - Epoch(val) [11][450/509] eta: 0:00:04 time: 0.0845 data_time: 0.0019 memory: 991 2023/05/15 01:57:47 - mmengine - INFO - Epoch(val) [11][500/509] eta: 0:00:00 time: 0.0780 data_time: 0.0017 memory: 973 2023/05/15 01:58:27 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9420 | 0.4579 | 0.5985 | 0.6259 | 0.3501 | 0.7062 | 0.7993 | 0.0162 | 0.9420 | 0.4105 | 0.8149 | 0.0743 | 0.9027 | 0.5965 | 0.8928 | 0.6469 | 0.7727 | 0.6525 | 0.5032 | 0.6161 | 0.9224 | 0.6893 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 01:58:27 - mmengine - INFO - Epoch(val) [11][509/509] car: 0.9420 bicycle: 0.4579 motorcycle: 0.5985 truck: 0.6259 bus: 0.3501 person: 0.7062 bicyclist: 0.7993 motorcyclist: 0.0162 road: 0.9420 parking: 0.4105 sidewalk: 0.8149 other-ground: 0.0743 building: 0.9027 fence: 0.5965 vegetation: 0.8928 trunck: 0.6469 terrian: 0.7727 pole: 0.6525 traffic-sign: 0.5032 miou: 0.6161 acc: 0.9224 acc_cls: 0.6893 data_time: 0.0017 time: 0.0798 2023/05/15 01:59:35 - mmengine - INFO - Epoch(train) [12][ 50/1196] lr: 8.0000e-03 eta: 12:02:18 time: 1.3778 data_time: 0.0039 memory: 4833 grad_norm: 0.1150 loss: 0.2388 loss_sem_seg: 0.2388 2023/05/15 02:00:44 - mmengine - INFO - Epoch(train) [12][ 100/1196] lr: 8.0000e-03 eta: 12:00:57 time: 1.3766 data_time: 0.0031 memory: 4872 grad_norm: 0.1375 loss: 0.2333 loss_sem_seg: 0.2333 2023/05/15 02:01:53 - mmengine - INFO - Epoch(train) [12][ 150/1196] lr: 8.0000e-03 eta: 11:59:35 time: 1.3652 data_time: 0.0031 memory: 5149 grad_norm: 0.1122 loss: 0.2374 loss_sem_seg: 0.2374 2023/05/15 02:03:14 - mmengine - INFO - Epoch(train) [12][ 200/1196] lr: 8.0000e-03 eta: 11:58:43 time: 1.6337 data_time: 0.0032 memory: 4894 grad_norm: 0.1198 loss: 0.2361 loss_sem_seg: 0.2361 2023/05/15 02:04:31 - mmengine - INFO - Epoch(train) [12][ 250/1196] lr: 8.0000e-03 eta: 11:57:40 time: 1.5431 data_time: 0.0032 memory: 4917 grad_norm: 0.1395 loss: 0.2131 loss_sem_seg: 0.2131 2023/05/15 02:05:41 - mmengine - INFO - Epoch(train) [12][ 300/1196] lr: 8.0000e-03 eta: 11:56:21 time: 1.3885 data_time: 0.0031 memory: 4669 grad_norm: 0.1068 loss: 0.2544 loss_sem_seg: 0.2544 2023/05/15 02:06:50 - mmengine - INFO - Epoch(train) [12][ 350/1196] lr: 8.0000e-03 eta: 11:55:00 time: 1.3766 data_time: 0.0031 memory: 5015 grad_norm: 0.1094 loss: 0.2444 loss_sem_seg: 0.2444 2023/05/15 02:07:59 - mmengine - INFO - Epoch(train) [12][ 400/1196] lr: 8.0000e-03 eta: 11:53:39 time: 1.3809 data_time: 0.0031 memory: 4629 grad_norm: 0.1164 loss: 0.2240 loss_sem_seg: 0.2240 2023/05/15 02:09:07 - mmengine - INFO - Epoch(train) [12][ 450/1196] lr: 8.0000e-03 eta: 11:52:18 time: 1.3740 data_time: 0.0031 memory: 4996 grad_norm: 0.1134 loss: 0.2304 loss_sem_seg: 0.2304 2023/05/15 02:10:16 - mmengine - INFO - Epoch(train) [12][ 500/1196] lr: 8.0000e-03 eta: 11:50:57 time: 1.3651 data_time: 0.0031 memory: 4576 grad_norm: 0.1260 loss: 0.2439 loss_sem_seg: 0.2439 2023/05/15 02:11:25 - mmengine - INFO - Epoch(train) [12][ 550/1196] lr: 8.0000e-03 eta: 11:49:37 time: 1.3886 data_time: 0.0031 memory: 4875 grad_norm: 0.1283 loss: 0.2386 loss_sem_seg: 0.2386 2023/05/15 02:12:33 - mmengine - INFO - Epoch(train) [12][ 600/1196] lr: 8.0000e-03 eta: 11:48:16 time: 1.3651 data_time: 0.0031 memory: 4565 grad_norm: 0.1110 loss: 0.2380 loss_sem_seg: 0.2380 2023/05/15 02:13:41 - mmengine - INFO - Epoch(train) [12][ 650/1196] lr: 8.0000e-03 eta: 11:46:53 time: 1.3541 data_time: 0.0031 memory: 4628 grad_norm: 0.1251 loss: 0.2462 loss_sem_seg: 0.2462 2023/05/15 02:14:50 - mmengine - INFO - Epoch(train) [12][ 700/1196] lr: 8.0000e-03 eta: 11:45:32 time: 1.3700 data_time: 0.0031 memory: 4527 grad_norm: 0.1268 loss: 0.2343 loss_sem_seg: 0.2343 2023/05/15 02:15:59 - mmengine - INFO - Epoch(train) [12][ 750/1196] lr: 8.0000e-03 eta: 11:44:14 time: 1.3947 data_time: 0.0031 memory: 4783 grad_norm: 0.1239 loss: 0.2276 loss_sem_seg: 0.2276 2023/05/15 02:17:08 - mmengine - INFO - Epoch(train) [12][ 800/1196] lr: 8.0000e-03 eta: 11:42:52 time: 1.3647 data_time: 0.0031 memory: 4705 grad_norm: 0.1117 loss: 0.2107 loss_sem_seg: 0.2107 2023/05/15 02:18:08 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 02:18:16 - mmengine - INFO - Epoch(train) [12][ 850/1196] lr: 8.0000e-03 eta: 11:41:31 time: 1.3635 data_time: 0.0031 memory: 4809 grad_norm: 0.1233 loss: 0.2513 loss_sem_seg: 0.2513 2023/05/15 02:19:26 - mmengine - INFO - Epoch(train) [12][ 900/1196] lr: 8.0000e-03 eta: 11:40:14 time: 1.4051 data_time: 0.0031 memory: 4834 grad_norm: 0.1073 loss: 0.2422 loss_sem_seg: 0.2422 2023/05/15 02:20:35 - mmengine - INFO - Epoch(train) [12][ 950/1196] lr: 8.0000e-03 eta: 11:38:54 time: 1.3765 data_time: 0.0031 memory: 4925 grad_norm: 0.1090 loss: 0.2305 loss_sem_seg: 0.2305 2023/05/15 02:21:43 - mmengine - INFO - Epoch(train) [12][1000/1196] lr: 8.0000e-03 eta: 11:37:32 time: 1.3550 data_time: 0.0034 memory: 4636 grad_norm: 0.1152 loss: 0.2338 loss_sem_seg: 0.2338 2023/05/15 02:22:51 - mmengine - INFO - Epoch(train) [12][1050/1196] lr: 8.0000e-03 eta: 11:36:11 time: 1.3614 data_time: 0.0031 memory: 4932 grad_norm: 0.1124 loss: 0.2287 loss_sem_seg: 0.2287 2023/05/15 02:23:59 - mmengine - INFO - Epoch(train) [12][1100/1196] lr: 8.0000e-03 eta: 11:34:51 time: 1.3749 data_time: 0.0032 memory: 4666 grad_norm: 0.1127 loss: 0.2190 loss_sem_seg: 0.2190 2023/05/15 02:25:09 - mmengine - INFO - Epoch(train) [12][1150/1196] lr: 8.0000e-03 eta: 11:33:32 time: 1.3832 data_time: 0.0032 memory: 4641 grad_norm: 0.1204 loss: 0.2359 loss_sem_seg: 0.2359 2023/05/15 02:26:12 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 02:26:12 - mmengine - INFO - Saving checkpoint at 12 epochs 2023/05/15 02:26:23 - mmengine - INFO - Epoch(val) [12][ 50/509] eta: 0:00:42 time: 0.0925 data_time: 0.0020 memory: 4962 2023/05/15 02:26:27 - mmengine - INFO - Epoch(val) [12][100/509] eta: 0:00:36 time: 0.0847 data_time: 0.0019 memory: 991 2023/05/15 02:26:32 - mmengine - INFO - Epoch(val) [12][150/509] eta: 0:00:31 time: 0.0823 data_time: 0.0019 memory: 994 2023/05/15 02:26:36 - mmengine - INFO - Epoch(val) [12][200/509] eta: 0:00:26 time: 0.0835 data_time: 0.0019 memory: 979 2023/05/15 02:26:40 - mmengine - INFO - Epoch(val) [12][250/509] eta: 0:00:22 time: 0.0877 data_time: 0.0019 memory: 1004 2023/05/15 02:26:44 - mmengine - INFO - Epoch(val) [12][300/509] eta: 0:00:17 time: 0.0762 data_time: 0.0019 memory: 946 2023/05/15 02:26:48 - mmengine - INFO - Epoch(val) [12][350/509] eta: 0:00:13 time: 0.0792 data_time: 0.0018 memory: 970 2023/05/15 02:26:52 - mmengine - INFO - Epoch(val) [12][400/509] eta: 0:00:09 time: 0.0842 data_time: 0.0019 memory: 978 2023/05/15 02:26:56 - mmengine - INFO - Epoch(val) [12][450/509] eta: 0:00:04 time: 0.0841 data_time: 0.0018 memory: 991 2023/05/15 02:27:00 - mmengine - INFO - Epoch(val) [12][500/509] eta: 0:00:00 time: 0.0781 data_time: 0.0017 memory: 973 2023/05/15 02:27:40 - 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 | 0.9670 | 0.4619 | 0.6187 | 0.8071 | 0.7050 | 0.6903 | 0.7463 | 0.0000 | 0.9314 | 0.4678 | 0.8034 | 0.0197 | 0.9057 | 0.6357 | 0.8966 | 0.6863 | 0.7782 | 0.6482 | 0.4988 | 0.6457 | 0.9238 | 0.7200 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 02:27:40 - mmengine - INFO - Epoch(val) [12][509/509] car: 0.9670 bicycle: 0.4619 motorcycle: 0.6187 truck: 0.8071 bus: 0.7050 person: 0.6903 bicyclist: 0.7463 motorcyclist: 0.0000 road: 0.9314 parking: 0.4678 sidewalk: 0.8034 other-ground: 0.0197 building: 0.9057 fence: 0.6357 vegetation: 0.8966 trunck: 0.6863 terrian: 0.7782 pole: 0.6482 traffic-sign: 0.4988 miou: 0.6457 acc: 0.9238 acc_cls: 0.7200 data_time: 0.0017 time: 0.0799 2023/05/15 02:28:48 - mmengine - INFO - Epoch(train) [13][ 50/1196] lr: 8.0000e-03 eta: 11:30:58 time: 1.3612 data_time: 0.0039 memory: 5111 grad_norm: 0.1184 loss: 0.2301 loss_sem_seg: 0.2301 2023/05/15 02:29:56 - mmengine - INFO - Epoch(train) [13][ 100/1196] lr: 8.0000e-03 eta: 11:29:38 time: 1.3614 data_time: 0.0030 memory: 4802 grad_norm: 0.1186 loss: 0.2430 loss_sem_seg: 0.2430 2023/05/15 02:31:04 - mmengine - INFO - Epoch(train) [13][ 150/1196] lr: 8.0000e-03 eta: 11:28:17 time: 1.3616 data_time: 0.0031 memory: 4809 grad_norm: 0.1169 loss: 0.2544 loss_sem_seg: 0.2544 2023/05/15 02:32:12 - mmengine - INFO - Epoch(train) [13][ 200/1196] lr: 8.0000e-03 eta: 11:26:56 time: 1.3601 data_time: 0.0031 memory: 5329 grad_norm: 0.1201 loss: 0.2235 loss_sem_seg: 0.2235 2023/05/15 02:33:23 - mmengine - INFO - Epoch(train) [13][ 250/1196] lr: 8.0000e-03 eta: 11:25:42 time: 1.4258 data_time: 0.0031 memory: 4681 grad_norm: 0.1137 loss: 0.2285 loss_sem_seg: 0.2285 2023/05/15 02:34:50 - mmengine - INFO - Epoch(train) [13][ 300/1196] lr: 8.0000e-03 eta: 11:24:57 time: 1.7254 data_time: 0.0031 memory: 4856 grad_norm: 0.1199 loss: 0.2274 loss_sem_seg: 0.2274 2023/05/15 02:35:59 - mmengine - INFO - Epoch(train) [13][ 350/1196] lr: 8.0000e-03 eta: 11:23:39 time: 1.3925 data_time: 0.0031 memory: 4747 grad_norm: 0.1303 loss: 0.2459 loss_sem_seg: 0.2459 2023/05/15 02:37:07 - mmengine - INFO - Epoch(train) [13][ 400/1196] lr: 8.0000e-03 eta: 11:22:19 time: 1.3625 data_time: 0.0031 memory: 4893 grad_norm: 0.1109 loss: 0.2197 loss_sem_seg: 0.2197 2023/05/15 02:38:15 - mmengine - INFO - Epoch(train) [13][ 450/1196] lr: 8.0000e-03 eta: 11:20:58 time: 1.3564 data_time: 0.0032 memory: 4596 grad_norm: 0.1162 loss: 0.2361 loss_sem_seg: 0.2361 2023/05/15 02:39:23 - mmengine - INFO - Epoch(train) [13][ 500/1196] lr: 8.0000e-03 eta: 11:19:38 time: 1.3659 data_time: 0.0031 memory: 4797 grad_norm: 0.1115 loss: 0.2259 loss_sem_seg: 0.2259 2023/05/15 02:40:33 - mmengine - INFO - Epoch(train) [13][ 550/1196] lr: 8.0000e-03 eta: 11:18:21 time: 1.3985 data_time: 0.0032 memory: 4813 grad_norm: 0.1392 loss: 0.2504 loss_sem_seg: 0.2504 2023/05/15 02:41:42 - mmengine - INFO - Epoch(train) [13][ 600/1196] lr: 8.0000e-03 eta: 11:17:01 time: 1.3667 data_time: 0.0031 memory: 5152 grad_norm: 0.1147 loss: 0.2341 loss_sem_seg: 0.2341 2023/05/15 02:42:47 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 02:42:50 - mmengine - INFO - Epoch(train) [13][ 650/1196] lr: 8.0000e-03 eta: 11:15:41 time: 1.3580 data_time: 0.0031 memory: 4720 grad_norm: 0.1179 loss: 0.2411 loss_sem_seg: 0.2411 2023/05/15 02:43:58 - mmengine - INFO - Epoch(train) [13][ 700/1196] lr: 8.0000e-03 eta: 11:14:21 time: 1.3599 data_time: 0.0031 memory: 4804 grad_norm: 0.1147 loss: 0.2317 loss_sem_seg: 0.2317 2023/05/15 02:45:24 - mmengine - INFO - Epoch(train) [13][ 750/1196] lr: 8.0000e-03 eta: 11:13:34 time: 1.7241 data_time: 0.0033 memory: 4639 grad_norm: 0.0983 loss: 0.2331 loss_sem_seg: 0.2331 2023/05/15 02:46:38 - mmengine - INFO - Epoch(train) [13][ 800/1196] lr: 8.0000e-03 eta: 11:12:26 time: 1.4824 data_time: 0.0033 memory: 4668 grad_norm: 0.1153 loss: 0.2381 loss_sem_seg: 0.2381 2023/05/15 02:47:46 - mmengine - INFO - Epoch(train) [13][ 850/1196] lr: 8.0000e-03 eta: 11:11:06 time: 1.3663 data_time: 0.0031 memory: 4708 grad_norm: 0.1100 loss: 0.2271 loss_sem_seg: 0.2271 2023/05/15 02:48:55 - mmengine - INFO - Epoch(train) [13][ 900/1196] lr: 8.0000e-03 eta: 11:09:47 time: 1.3740 data_time: 0.0031 memory: 4916 grad_norm: 0.1275 loss: 0.2043 loss_sem_seg: 0.2043 2023/05/15 02:50:03 - mmengine - INFO - Epoch(train) [13][ 950/1196] lr: 8.0000e-03 eta: 11:08:28 time: 1.3688 data_time: 0.0032 memory: 4749 grad_norm: 0.1184 loss: 0.2443 loss_sem_seg: 0.2443 2023/05/15 02:51:12 - mmengine - INFO - Epoch(train) [13][1000/1196] lr: 8.0000e-03 eta: 11:07:08 time: 1.3642 data_time: 0.0031 memory: 4724 grad_norm: 0.1038 loss: 0.2385 loss_sem_seg: 0.2385 2023/05/15 02:52:20 - mmengine - INFO - Epoch(train) [13][1050/1196] lr: 8.0000e-03 eta: 11:05:49 time: 1.3613 data_time: 0.0031 memory: 4987 grad_norm: 0.1086 loss: 0.2400 loss_sem_seg: 0.2400 2023/05/15 02:53:28 - mmengine - INFO - Epoch(train) [13][1100/1196] lr: 8.0000e-03 eta: 11:04:29 time: 1.3645 data_time: 0.0031 memory: 4638 grad_norm: 0.1146 loss: 0.2263 loss_sem_seg: 0.2263 2023/05/15 02:54:36 - mmengine - INFO - Epoch(train) [13][1150/1196] lr: 8.0000e-03 eta: 11:03:10 time: 1.3691 data_time: 0.0031 memory: 4691 grad_norm: 0.1087 loss: 0.2192 loss_sem_seg: 0.2192 2023/05/15 02:55:39 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 02:55:39 - mmengine - INFO - Saving checkpoint at 13 epochs 2023/05/15 02:55:50 - mmengine - INFO - Epoch(val) [13][ 50/509] eta: 0:00:42 time: 0.0922 data_time: 0.0020 memory: 4665 2023/05/15 02:55:55 - mmengine - INFO - Epoch(val) [13][100/509] eta: 0:00:36 time: 0.0849 data_time: 0.0020 memory: 991 2023/05/15 02:55:59 - mmengine - INFO - Epoch(val) [13][150/509] eta: 0:00:31 time: 0.0828 data_time: 0.0019 memory: 994 2023/05/15 02:56:03 - mmengine - INFO - Epoch(val) [13][200/509] eta: 0:00:26 time: 0.0843 data_time: 0.0019 memory: 979 2023/05/15 02:56:07 - mmengine - INFO - Epoch(val) [13][250/509] eta: 0:00:22 time: 0.0886 data_time: 0.0020 memory: 1004 2023/05/15 02:56:11 - mmengine - INFO - Epoch(val) [13][300/509] eta: 0:00:17 time: 0.0772 data_time: 0.0019 memory: 946 2023/05/15 02:56:15 - mmengine - INFO - Epoch(val) [13][350/509] eta: 0:00:13 time: 0.0796 data_time: 0.0019 memory: 970 2023/05/15 02:56:20 - mmengine - INFO - Epoch(val) [13][400/509] eta: 0:00:09 time: 0.0849 data_time: 0.0019 memory: 978 2023/05/15 02:56:24 - mmengine - INFO - Epoch(val) [13][450/509] eta: 0:00:04 time: 0.0855 data_time: 0.0020 memory: 991 2023/05/15 02:56:28 - mmengine - INFO - Epoch(val) [13][500/509] eta: 0:00:00 time: 0.0784 data_time: 0.0017 memory: 973 2023/05/15 02:57:11 - 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 | 0.9569 | 0.4901 | 0.6914 | 0.6686 | 0.4705 | 0.6850 | 0.8108 | 0.1077 | 0.9372 | 0.4633 | 0.8064 | 0.0036 | 0.8934 | 0.5879 | 0.8903 | 0.6827 | 0.7784 | 0.6535 | 0.4992 | 0.6356 | 0.9211 | 0.7150 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 02:57:11 - mmengine - INFO - Epoch(val) [13][509/509] car: 0.9569 bicycle: 0.4901 motorcycle: 0.6914 truck: 0.6686 bus: 0.4705 person: 0.6850 bicyclist: 0.8108 motorcyclist: 0.1077 road: 0.9372 parking: 0.4633 sidewalk: 0.8064 other-ground: 0.0036 building: 0.8934 fence: 0.5879 vegetation: 0.8903 trunck: 0.6827 terrian: 0.7784 pole: 0.6535 traffic-sign: 0.4992 miou: 0.6356 acc: 0.9211 acc_cls: 0.7150 data_time: 0.0017 time: 0.0800 2023/05/15 02:58:20 - mmengine - INFO - Epoch(train) [14][ 50/1196] lr: 8.0000e-03 eta: 11:00:41 time: 1.3906 data_time: 0.0039 memory: 4771 grad_norm: 0.1119 loss: 0.2296 loss_sem_seg: 0.2296 2023/05/15 02:59:29 - mmengine - INFO - Epoch(train) [14][ 100/1196] lr: 8.0000e-03 eta: 10:59:23 time: 1.3746 data_time: 0.0031 memory: 4738 grad_norm: 0.1255 loss: 0.2240 loss_sem_seg: 0.2240 2023/05/15 03:00:38 - mmengine - INFO - Epoch(train) [14][ 150/1196] lr: 8.0000e-03 eta: 10:58:05 time: 1.3780 data_time: 0.0031 memory: 4832 grad_norm: 0.1138 loss: 0.2492 loss_sem_seg: 0.2492 2023/05/15 03:01:48 - mmengine - INFO - Epoch(train) [14][ 200/1196] lr: 8.0000e-03 eta: 10:56:49 time: 1.3994 data_time: 0.0031 memory: 4903 grad_norm: 0.1120 loss: 0.2205 loss_sem_seg: 0.2205 2023/05/15 03:02:56 - mmengine - INFO - Epoch(train) [14][ 250/1196] lr: 8.0000e-03 eta: 10:55:30 time: 1.3714 data_time: 0.0031 memory: 4824 grad_norm: 0.1196 loss: 0.2255 loss_sem_seg: 0.2255 2023/05/15 03:04:05 - mmengine - INFO - Epoch(train) [14][ 300/1196] lr: 8.0000e-03 eta: 10:54:13 time: 1.3841 data_time: 0.0031 memory: 4692 grad_norm: 0.1130 loss: 0.2305 loss_sem_seg: 0.2305 2023/05/15 03:05:15 - mmengine - INFO - Epoch(train) [14][ 350/1196] lr: 8.0000e-03 eta: 10:52:56 time: 1.3860 data_time: 0.0031 memory: 4784 grad_norm: 0.1141 loss: 0.2254 loss_sem_seg: 0.2254 2023/05/15 03:06:25 - mmengine - INFO - Epoch(train) [14][ 400/1196] lr: 8.0000e-03 eta: 10:51:41 time: 1.4080 data_time: 0.0031 memory: 4584 grad_norm: 0.1155 loss: 0.2213 loss_sem_seg: 0.2213 2023/05/15 03:07:35 - mmengine - INFO - Epoch(train) [14][ 450/1196] lr: 8.0000e-03 eta: 10:50:25 time: 1.3933 data_time: 0.0032 memory: 4733 grad_norm: 0.1103 loss: 0.2294 loss_sem_seg: 0.2294 2023/05/15 03:07:38 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 03:08:43 - mmengine - INFO - Epoch(train) [14][ 500/1196] lr: 8.0000e-03 eta: 10:49:06 time: 1.3564 data_time: 0.0032 memory: 4403 grad_norm: 0.1185 loss: 0.2363 loss_sem_seg: 0.2363 2023/05/15 03:09:50 - mmengine - INFO - Epoch(train) [14][ 550/1196] lr: 8.0000e-03 eta: 10:47:46 time: 1.3552 data_time: 0.0032 memory: 4694 grad_norm: 0.1199 loss: 0.2297 loss_sem_seg: 0.2297 2023/05/15 03:10:59 - mmengine - INFO - Epoch(train) [14][ 600/1196] lr: 8.0000e-03 eta: 10:46:28 time: 1.3626 data_time: 0.0032 memory: 5038 grad_norm: 0.1129 loss: 0.2265 loss_sem_seg: 0.2265 2023/05/15 03:12:07 - mmengine - INFO - Epoch(train) [14][ 650/1196] lr: 8.0000e-03 eta: 10:45:10 time: 1.3740 data_time: 0.0033 memory: 4653 grad_norm: 0.0979 loss: 0.2182 loss_sem_seg: 0.2182 2023/05/15 03:13:16 - mmengine - INFO - Epoch(train) [14][ 700/1196] lr: 8.0000e-03 eta: 10:43:52 time: 1.3673 data_time: 0.0033 memory: 4869 grad_norm: 0.1112 loss: 0.2334 loss_sem_seg: 0.2334 2023/05/15 03:14:24 - mmengine - INFO - Epoch(train) [14][ 750/1196] lr: 8.0000e-03 eta: 10:42:33 time: 1.3660 data_time: 0.0033 memory: 4826 grad_norm: 0.1272 loss: 0.2456 loss_sem_seg: 0.2456 2023/05/15 03:15:39 - mmengine - INFO - Epoch(train) [14][ 800/1196] lr: 8.0000e-03 eta: 10:41:27 time: 1.5034 data_time: 0.0033 memory: 4460 grad_norm: 0.1138 loss: 0.2224 loss_sem_seg: 0.2224 2023/05/15 03:17:03 - mmengine - INFO - Epoch(train) [14][ 850/1196] lr: 8.0000e-03 eta: 10:40:34 time: 1.6810 data_time: 0.0033 memory: 4724 grad_norm: 0.1082 loss: 0.2247 loss_sem_seg: 0.2247 2023/05/15 03:18:11 - mmengine - INFO - Epoch(train) [14][ 900/1196] lr: 8.0000e-03 eta: 10:39:14 time: 1.3478 data_time: 0.0031 memory: 4951 grad_norm: 0.1080 loss: 0.2305 loss_sem_seg: 0.2305 2023/05/15 03:19:18 - mmengine - INFO - Epoch(train) [14][ 950/1196] lr: 8.0000e-03 eta: 10:37:55 time: 1.3499 data_time: 0.0031 memory: 5099 grad_norm: 0.1132 loss: 0.2377 loss_sem_seg: 0.2377 2023/05/15 03:20:27 - mmengine - INFO - Epoch(train) [14][1000/1196] lr: 8.0000e-03 eta: 10:36:37 time: 1.3735 data_time: 0.0031 memory: 4796 grad_norm: 0.1186 loss: 0.2266 loss_sem_seg: 0.2266 2023/05/15 03:21:36 - mmengine - INFO - Epoch(train) [14][1050/1196] lr: 8.0000e-03 eta: 10:35:20 time: 1.3773 data_time: 0.0032 memory: 4815 grad_norm: 0.1270 loss: 0.2259 loss_sem_seg: 0.2259 2023/05/15 03:22:43 - mmengine - INFO - Epoch(train) [14][1100/1196] lr: 8.0000e-03 eta: 10:34:01 time: 1.3535 data_time: 0.0031 memory: 4743 grad_norm: 0.1062 loss: 0.2255 loss_sem_seg: 0.2255 2023/05/15 03:23:51 - mmengine - INFO - Epoch(train) [14][1150/1196] lr: 8.0000e-03 eta: 10:32:43 time: 1.3593 data_time: 0.0031 memory: 4671 grad_norm: 0.1270 loss: 0.2355 loss_sem_seg: 0.2355 2023/05/15 03:24:55 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 03:24:55 - mmengine - INFO - Saving checkpoint at 14 epochs 2023/05/15 03:25:06 - mmengine - INFO - Epoch(val) [14][ 50/509] eta: 0:00:42 time: 0.0916 data_time: 0.0020 memory: 4543 2023/05/15 03:25:10 - mmengine - INFO - Epoch(val) [14][100/509] eta: 0:00:35 time: 0.0841 data_time: 0.0020 memory: 991 2023/05/15 03:25:14 - mmengine - INFO - Epoch(val) [14][150/509] eta: 0:00:30 time: 0.0819 data_time: 0.0019 memory: 994 2023/05/15 03:25:18 - mmengine - INFO - Epoch(val) [14][200/509] eta: 0:00:26 time: 0.0836 data_time: 0.0019 memory: 979 2023/05/15 03:25:23 - mmengine - INFO - Epoch(val) [14][250/509] eta: 0:00:22 time: 0.0881 data_time: 0.0019 memory: 1004 2023/05/15 03:25:27 - mmengine - INFO - Epoch(val) [14][300/509] eta: 0:00:17 time: 0.0799 data_time: 0.0019 memory: 946 2023/05/15 03:25:31 - mmengine - INFO - Epoch(val) [14][350/509] eta: 0:00:13 time: 0.0794 data_time: 0.0019 memory: 970 2023/05/15 03:25:35 - mmengine - INFO - Epoch(val) [14][400/509] eta: 0:00:09 time: 0.0844 data_time: 0.0019 memory: 978 2023/05/15 03:25:41 - mmengine - INFO - Epoch(val) [14][450/509] eta: 0:00:05 time: 0.1088 data_time: 0.0019 memory: 991 2023/05/15 03:25:45 - mmengine - INFO - Epoch(val) [14][500/509] eta: 0:00:00 time: 0.0993 data_time: 0.0017 memory: 973 2023/05/15 03:26:25 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9444 | 0.4977 | 0.6489 | 0.5486 | 0.2871 | 0.7575 | 0.8305 | 0.0660 | 0.9325 | 0.4081 | 0.8022 | 0.0005 | 0.9063 | 0.6013 | 0.8916 | 0.6558 | 0.7725 | 0.6542 | 0.5122 | 0.6167 | 0.9201 | 0.7015 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 03:26:25 - mmengine - INFO - Epoch(val) [14][509/509] car: 0.9444 bicycle: 0.4977 motorcycle: 0.6489 truck: 0.5486 bus: 0.2871 person: 0.7575 bicyclist: 0.8305 motorcyclist: 0.0660 road: 0.9325 parking: 0.4081 sidewalk: 0.8022 other-ground: 0.0005 building: 0.9063 fence: 0.6013 vegetation: 0.8916 trunck: 0.6558 terrian: 0.7725 pole: 0.6542 traffic-sign: 0.5122 miou: 0.6167 acc: 0.9201 acc_cls: 0.7015 data_time: 0.0017 time: 0.0798 2023/05/15 03:27:55 - mmengine - INFO - Epoch(train) [15][ 50/1196] lr: 8.0000e-03 eta: 10:30:49 time: 1.8009 data_time: 0.0041 memory: 4861 grad_norm: 0.1114 loss: 0.2333 loss_sem_seg: 0.2333 2023/05/15 03:29:05 - mmengine - INFO - Epoch(train) [15][ 100/1196] lr: 8.0000e-03 eta: 10:29:32 time: 1.3838 data_time: 0.0033 memory: 4658 grad_norm: 0.1190 loss: 0.2209 loss_sem_seg: 0.2209 2023/05/15 03:30:13 - mmengine - INFO - Epoch(train) [15][ 150/1196] lr: 8.0000e-03 eta: 10:28:15 time: 1.3780 data_time: 0.0033 memory: 4414 grad_norm: 0.1020 loss: 0.2223 loss_sem_seg: 0.2223 2023/05/15 03:31:22 - mmengine - INFO - Epoch(train) [15][ 200/1196] lr: 8.0000e-03 eta: 10:26:58 time: 1.3762 data_time: 0.0033 memory: 4724 grad_norm: 0.0974 loss: 0.2093 loss_sem_seg: 0.2093 2023/05/15 03:32:32 - mmengine - INFO - Epoch(train) [15][ 250/1196] lr: 8.0000e-03 eta: 10:25:42 time: 1.3860 data_time: 0.0034 memory: 4664 grad_norm: 0.1080 loss: 0.2235 loss_sem_seg: 0.2235 2023/05/15 03:32:40 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 03:33:40 - mmengine - INFO - Epoch(train) [15][ 300/1196] lr: 8.0000e-03 eta: 10:24:24 time: 1.3603 data_time: 0.0032 memory: 4443 grad_norm: 0.1305 loss: 0.2354 loss_sem_seg: 0.2354 2023/05/15 03:34:50 - mmengine - INFO - Epoch(train) [15][ 350/1196] lr: 8.0000e-03 eta: 10:23:09 time: 1.4005 data_time: 0.0032 memory: 4724 grad_norm: 0.1176 loss: 0.2254 loss_sem_seg: 0.2254 2023/05/15 03:36:00 - mmengine - INFO - Epoch(train) [15][ 400/1196] lr: 8.0000e-03 eta: 10:21:54 time: 1.3994 data_time: 0.0031 memory: 5000 grad_norm: 0.1110 loss: 0.2230 loss_sem_seg: 0.2230 2023/05/15 03:37:08 - mmengine - INFO - Epoch(train) [15][ 450/1196] lr: 8.0000e-03 eta: 10:20:37 time: 1.3737 data_time: 0.0031 memory: 4819 grad_norm: 0.1085 loss: 0.2260 loss_sem_seg: 0.2260 2023/05/15 03:38:17 - mmengine - INFO - Epoch(train) [15][ 500/1196] lr: 8.0000e-03 eta: 10:19:19 time: 1.3678 data_time: 0.0031 memory: 4650 grad_norm: 0.1137 loss: 0.2356 loss_sem_seg: 0.2356 2023/05/15 03:39:26 - mmengine - INFO - Epoch(train) [15][ 550/1196] lr: 8.0000e-03 eta: 10:18:04 time: 1.3953 data_time: 0.0032 memory: 4742 grad_norm: 0.1082 loss: 0.2130 loss_sem_seg: 0.2130 2023/05/15 03:40:34 - mmengine - INFO - Epoch(train) [15][ 600/1196] lr: 8.0000e-03 eta: 10:16:46 time: 1.3555 data_time: 0.0033 memory: 4836 grad_norm: 0.1184 loss: 0.2259 loss_sem_seg: 0.2259 2023/05/15 03:41:43 - mmengine - INFO - Epoch(train) [15][ 650/1196] lr: 8.0000e-03 eta: 10:15:29 time: 1.3776 data_time: 0.0033 memory: 4540 grad_norm: 0.1128 loss: 0.2132 loss_sem_seg: 0.2132 2023/05/15 03:42:52 - mmengine - INFO - Epoch(train) [15][ 700/1196] lr: 8.0000e-03 eta: 10:14:12 time: 1.3689 data_time: 0.0032 memory: 4671 grad_norm: 0.1219 loss: 0.2338 loss_sem_seg: 0.2338 2023/05/15 03:44:00 - mmengine - INFO - Epoch(train) [15][ 750/1196] lr: 8.0000e-03 eta: 10:12:56 time: 1.3738 data_time: 0.0032 memory: 4467 grad_norm: 0.1270 loss: 0.2346 loss_sem_seg: 0.2346 2023/05/15 03:45:09 - mmengine - INFO - Epoch(train) [15][ 800/1196] lr: 8.0000e-03 eta: 10:11:39 time: 1.3753 data_time: 0.0032 memory: 5051 grad_norm: 0.1072 loss: 0.2121 loss_sem_seg: 0.2121 2023/05/15 03:46:18 - mmengine - INFO - Epoch(train) [15][ 850/1196] lr: 8.0000e-03 eta: 10:10:23 time: 1.3862 data_time: 0.0031 memory: 4914 grad_norm: 0.1009 loss: 0.2177 loss_sem_seg: 0.2177 2023/05/15 03:47:26 - mmengine - INFO - Epoch(train) [15][ 900/1196] lr: 8.0000e-03 eta: 10:09:06 time: 1.3576 data_time: 0.0031 memory: 4746 grad_norm: 0.1320 loss: 0.2320 loss_sem_seg: 0.2320 2023/05/15 03:48:35 - mmengine - INFO - Epoch(train) [15][ 950/1196] lr: 8.0000e-03 eta: 10:07:49 time: 1.3666 data_time: 0.0031 memory: 4626 grad_norm: 0.1145 loss: 0.2374 loss_sem_seg: 0.2374 2023/05/15 03:49:44 - mmengine - INFO - Epoch(train) [15][1000/1196] lr: 8.0000e-03 eta: 10:06:33 time: 1.3831 data_time: 0.0031 memory: 4636 grad_norm: 0.0978 loss: 0.2195 loss_sem_seg: 0.2195 2023/05/15 03:50:52 - mmengine - INFO - Epoch(train) [15][1050/1196] lr: 8.0000e-03 eta: 10:05:16 time: 1.3743 data_time: 0.0032 memory: 4759 grad_norm: 0.1153 loss: 0.2286 loss_sem_seg: 0.2286 2023/05/15 03:52:02 - mmengine - INFO - Epoch(train) [15][1100/1196] lr: 8.0000e-03 eta: 10:04:01 time: 1.3827 data_time: 0.0031 memory: 4595 grad_norm: 0.1009 loss: 0.2096 loss_sem_seg: 0.2096 2023/05/15 03:53:11 - mmengine - INFO - Epoch(train) [15][1150/1196] lr: 8.0000e-03 eta: 10:02:45 time: 1.3836 data_time: 0.0031 memory: 5059 grad_norm: 0.1070 loss: 0.2179 loss_sem_seg: 0.2179 2023/05/15 03:54:14 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 03:54:14 - mmengine - INFO - Saving checkpoint at 15 epochs 2023/05/15 03:54:25 - mmengine - INFO - Epoch(val) [15][ 50/509] eta: 0:00:42 time: 0.0920 data_time: 0.0020 memory: 4893 2023/05/15 03:54:30 - mmengine - INFO - Epoch(val) [15][100/509] eta: 0:00:36 time: 0.0843 data_time: 0.0019 memory: 991 2023/05/15 03:54:34 - mmengine - INFO - Epoch(val) [15][150/509] eta: 0:00:30 time: 0.0822 data_time: 0.0019 memory: 994 2023/05/15 03:54:38 - mmengine - INFO - Epoch(val) [15][200/509] eta: 0:00:26 time: 0.0831 data_time: 0.0019 memory: 979 2023/05/15 03:54:42 - mmengine - INFO - Epoch(val) [15][250/509] eta: 0:00:22 time: 0.0878 data_time: 0.0019 memory: 1004 2023/05/15 03:54:46 - mmengine - INFO - Epoch(val) [15][300/509] eta: 0:00:17 time: 0.0762 data_time: 0.0019 memory: 946 2023/05/15 03:54:50 - mmengine - INFO - Epoch(val) [15][350/509] eta: 0:00:13 time: 0.0790 data_time: 0.0018 memory: 970 2023/05/15 03:54:54 - mmengine - INFO - Epoch(val) [15][400/509] eta: 0:00:09 time: 0.0845 data_time: 0.0019 memory: 978 2023/05/15 03:54:59 - mmengine - INFO - Epoch(val) [15][450/509] eta: 0:00:04 time: 0.0854 data_time: 0.0019 memory: 991 2023/05/15 03:55:02 - mmengine - INFO - Epoch(val) [15][500/509] eta: 0:00:00 time: 0.0789 data_time: 0.0017 memory: 973 2023/05/15 03:55:43 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9661 | 0.5266 | 0.7235 | 0.2507 | 0.5929 | 0.6825 | 0.7255 | 0.1352 | 0.9307 | 0.3542 | 0.8107 | 0.0726 | 0.9158 | 0.6504 | 0.8948 | 0.6835 | 0.7855 | 0.6623 | 0.4786 | 0.6233 | 0.9247 | 0.6986 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 03:55:43 - mmengine - INFO - Epoch(val) [15][509/509] car: 0.9661 bicycle: 0.5266 motorcycle: 0.7235 truck: 0.2507 bus: 0.5929 person: 0.6825 bicyclist: 0.7255 motorcyclist: 0.1352 road: 0.9307 parking: 0.3542 sidewalk: 0.8107 other-ground: 0.0726 building: 0.9158 fence: 0.6504 vegetation: 0.8948 trunck: 0.6835 terrian: 0.7855 pole: 0.6623 traffic-sign: 0.4786 miou: 0.6233 acc: 0.9247 acc_cls: 0.6986 data_time: 0.0017 time: 0.0805 2023/05/15 03:56:52 - mmengine - INFO - Epoch(train) [16][ 50/1196] lr: 8.0000e-03 eta: 10:00:19 time: 1.3764 data_time: 0.0038 memory: 4759 grad_norm: 0.1124 loss: 0.2315 loss_sem_seg: 0.2315 2023/05/15 03:57:05 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 03:58:19 - mmengine - INFO - Epoch(train) [16][ 100/1196] lr: 8.0000e-03 eta: 9:59:28 time: 1.7390 data_time: 0.0032 memory: 4882 grad_norm: 0.1083 loss: 0.2113 loss_sem_seg: 0.2113 2023/05/15 03:59:30 - mmengine - INFO - Epoch(train) [16][ 150/1196] lr: 8.0000e-03 eta: 9:58:16 time: 1.4376 data_time: 0.0032 memory: 4844 grad_norm: 0.1155 loss: 0.2270 loss_sem_seg: 0.2270 2023/05/15 04:00:38 - mmengine - INFO - Epoch(train) [16][ 200/1196] lr: 8.0000e-03 eta: 9:56:59 time: 1.3590 data_time: 0.0031 memory: 5276 grad_norm: 0.1153 loss: 0.2273 loss_sem_seg: 0.2273 2023/05/15 04:01:47 - mmengine - INFO - Epoch(train) [16][ 250/1196] lr: 8.0000e-03 eta: 9:55:43 time: 1.3728 data_time: 0.0032 memory: 4789 grad_norm: 0.1044 loss: 0.2250 loss_sem_seg: 0.2250 2023/05/15 04:02:55 - mmengine - INFO - Epoch(train) [16][ 300/1196] lr: 8.0000e-03 eta: 9:54:26 time: 1.3671 data_time: 0.0031 memory: 5232 grad_norm: 0.1102 loss: 0.2266 loss_sem_seg: 0.2266 2023/05/15 04:04:04 - mmengine - INFO - Epoch(train) [16][ 350/1196] lr: 8.0000e-03 eta: 9:53:10 time: 1.3800 data_time: 0.0031 memory: 4775 grad_norm: 0.1076 loss: 0.2250 loss_sem_seg: 0.2250 2023/05/15 04:05:13 - mmengine - INFO - Epoch(train) [16][ 400/1196] lr: 8.0000e-03 eta: 9:51:54 time: 1.3686 data_time: 0.0031 memory: 4816 grad_norm: 0.1020 loss: 0.2271 loss_sem_seg: 0.2271 2023/05/15 04:06:23 - mmengine - INFO - Epoch(train) [16][ 450/1196] lr: 8.0000e-03 eta: 9:50:40 time: 1.4009 data_time: 0.0031 memory: 4693 grad_norm: 0.1051 loss: 0.2235 loss_sem_seg: 0.2235 2023/05/15 04:07:31 - mmengine - INFO - Epoch(train) [16][ 500/1196] lr: 8.0000e-03 eta: 9:49:23 time: 1.3713 data_time: 0.0031 memory: 4889 grad_norm: 0.1132 loss: 0.2161 loss_sem_seg: 0.2161 2023/05/15 04:08:42 - mmengine - INFO - Epoch(train) [16][ 550/1196] lr: 8.0000e-03 eta: 9:48:10 time: 1.4171 data_time: 0.0032 memory: 4879 grad_norm: 0.1070 loss: 0.2117 loss_sem_seg: 0.2117 2023/05/15 04:10:10 - mmengine - INFO - Epoch(train) [16][ 600/1196] lr: 8.0000e-03 eta: 9:47:20 time: 1.7556 data_time: 0.0033 memory: 4764 grad_norm: 0.1096 loss: 0.2183 loss_sem_seg: 0.2183 2023/05/15 04:11:19 - mmengine - INFO - Epoch(train) [16][ 650/1196] lr: 8.0000e-03 eta: 9:46:03 time: 1.3730 data_time: 0.0031 memory: 4852 grad_norm: 0.1137 loss: 0.2373 loss_sem_seg: 0.2373 2023/05/15 04:12:28 - mmengine - INFO - Epoch(train) [16][ 700/1196] lr: 8.0000e-03 eta: 9:44:48 time: 1.3882 data_time: 0.0031 memory: 4466 grad_norm: 0.1177 loss: 0.2323 loss_sem_seg: 0.2323 2023/05/15 04:13:37 - mmengine - INFO - Epoch(train) [16][ 750/1196] lr: 8.0000e-03 eta: 9:43:33 time: 1.3771 data_time: 0.0031 memory: 5098 grad_norm: 0.1031 loss: 0.2213 loss_sem_seg: 0.2213 2023/05/15 04:14:47 - mmengine - INFO - Epoch(train) [16][ 800/1196] lr: 8.0000e-03 eta: 9:42:18 time: 1.3912 data_time: 0.0031 memory: 5215 grad_norm: 0.1057 loss: 0.2186 loss_sem_seg: 0.2186 2023/05/15 04:15:57 - mmengine - INFO - Epoch(train) [16][ 850/1196] lr: 8.0000e-03 eta: 9:41:05 time: 1.4155 data_time: 0.0031 memory: 4690 grad_norm: 0.1015 loss: 0.2077 loss_sem_seg: 0.2077 2023/05/15 04:17:06 - mmengine - INFO - Epoch(train) [16][ 900/1196] lr: 8.0000e-03 eta: 9:39:49 time: 1.3746 data_time: 0.0031 memory: 4903 grad_norm: 0.1108 loss: 0.2131 loss_sem_seg: 0.2131 2023/05/15 04:18:15 - mmengine - INFO - Epoch(train) [16][ 950/1196] lr: 8.0000e-03 eta: 9:38:33 time: 1.3801 data_time: 0.0031 memory: 4570 grad_norm: 0.1009 loss: 0.2159 loss_sem_seg: 0.2159 2023/05/15 04:19:24 - mmengine - INFO - Epoch(train) [16][1000/1196] lr: 8.0000e-03 eta: 9:37:17 time: 1.3715 data_time: 0.0031 memory: 4696 grad_norm: 0.0945 loss: 0.2255 loss_sem_seg: 0.2255 2023/05/15 04:20:32 - mmengine - INFO - Epoch(train) [16][1050/1196] lr: 8.0000e-03 eta: 9:36:01 time: 1.3693 data_time: 0.0031 memory: 4837 grad_norm: 0.1087 loss: 0.2184 loss_sem_seg: 0.2184 2023/05/15 04:20:47 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 04:21:42 - mmengine - INFO - Epoch(train) [16][1100/1196] lr: 8.0000e-03 eta: 9:34:46 time: 1.3871 data_time: 0.0031 memory: 4697 grad_norm: 0.1107 loss: 0.2202 loss_sem_seg: 0.2202 2023/05/15 04:22:51 - mmengine - INFO - Epoch(train) [16][1150/1196] lr: 8.0000e-03 eta: 9:33:31 time: 1.3867 data_time: 0.0031 memory: 5093 grad_norm: 0.1107 loss: 0.2224 loss_sem_seg: 0.2224 2023/05/15 04:23:54 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 04:23:54 - mmengine - INFO - Saving checkpoint at 16 epochs 2023/05/15 04:24:05 - mmengine - INFO - Epoch(val) [16][ 50/509] eta: 0:00:42 time: 0.0932 data_time: 0.0021 memory: 4619 2023/05/15 04:24:10 - mmengine - INFO - Epoch(val) [16][100/509] eta: 0:00:36 time: 0.0848 data_time: 0.0020 memory: 991 2023/05/15 04:24:14 - mmengine - INFO - Epoch(val) [16][150/509] eta: 0:00:31 time: 0.0834 data_time: 0.0019 memory: 994 2023/05/15 04:24:18 - mmengine - INFO - Epoch(val) [16][200/509] eta: 0:00:26 time: 0.0842 data_time: 0.0019 memory: 979 2023/05/15 04:24:22 - mmengine - INFO - Epoch(val) [16][250/509] eta: 0:00:22 time: 0.0885 data_time: 0.0019 memory: 1004 2023/05/15 04:24:26 - mmengine - INFO - Epoch(val) [16][300/509] eta: 0:00:17 time: 0.0767 data_time: 0.0019 memory: 946 2023/05/15 04:24:30 - mmengine - INFO - Epoch(val) [16][350/509] eta: 0:00:13 time: 0.0792 data_time: 0.0019 memory: 970 2023/05/15 04:24:35 - mmengine - INFO - Epoch(val) [16][400/509] eta: 0:00:09 time: 0.0844 data_time: 0.0019 memory: 978 2023/05/15 04:24:39 - mmengine - INFO - Epoch(val) [16][450/509] eta: 0:00:04 time: 0.0850 data_time: 0.0019 memory: 991 2023/05/15 04:24:43 - mmengine - INFO - Epoch(val) [16][500/509] eta: 0:00:00 time: 0.0788 data_time: 0.0017 memory: 973 2023/05/15 04:25:23 - 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 | 0.9631 | 0.5237 | 0.7126 | 0.6419 | 0.6492 | 0.7232 | 0.8337 | 0.0915 | 0.9350 | 0.4932 | 0.8122 | 0.0785 | 0.9005 | 0.5996 | 0.8809 | 0.6656 | 0.7419 | 0.6307 | 0.4876 | 0.6508 | 0.9191 | 0.7335 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 04:25:23 - mmengine - INFO - Epoch(val) [16][509/509] car: 0.9631 bicycle: 0.5237 motorcycle: 0.7126 truck: 0.6419 bus: 0.6492 person: 0.7232 bicyclist: 0.8337 motorcyclist: 0.0915 road: 0.9350 parking: 0.4932 sidewalk: 0.8122 other-ground: 0.0785 building: 0.9005 fence: 0.5996 vegetation: 0.8809 trunck: 0.6656 terrian: 0.7419 pole: 0.6307 traffic-sign: 0.4876 miou: 0.6508 acc: 0.9191 acc_cls: 0.7335 data_time: 0.0017 time: 0.0806 2023/05/15 04:26:32 - mmengine - INFO - Epoch(train) [17][ 50/1196] lr: 8.0000e-03 eta: 9:31:07 time: 1.3904 data_time: 0.0040 memory: 4516 grad_norm: 0.1020 loss: 0.2374 loss_sem_seg: 0.2374 2023/05/15 04:27:41 - mmengine - INFO - Epoch(train) [17][ 100/1196] lr: 8.0000e-03 eta: 9:29:51 time: 1.3668 data_time: 0.0031 memory: 5266 grad_norm: 0.1103 loss: 0.2082 loss_sem_seg: 0.2082 2023/05/15 04:28:49 - mmengine - INFO - Epoch(train) [17][ 150/1196] lr: 8.0000e-03 eta: 9:28:35 time: 1.3574 data_time: 0.0031 memory: 4645 grad_norm: 0.1107 loss: 0.2203 loss_sem_seg: 0.2203 2023/05/15 04:29:57 - mmengine - INFO - Epoch(train) [17][ 200/1196] lr: 8.0000e-03 eta: 9:27:19 time: 1.3689 data_time: 0.0031 memory: 4485 grad_norm: 0.1065 loss: 0.2278 loss_sem_seg: 0.2278 2023/05/15 04:31:07 - mmengine - INFO - Epoch(train) [17][ 250/1196] lr: 8.0000e-03 eta: 9:26:05 time: 1.3950 data_time: 0.0031 memory: 4766 grad_norm: 0.1062 loss: 0.2248 loss_sem_seg: 0.2248 2023/05/15 04:32:15 - mmengine - INFO - Epoch(train) [17][ 300/1196] lr: 8.0000e-03 eta: 9:24:49 time: 1.3684 data_time: 0.0031 memory: 4753 grad_norm: 0.1130 loss: 0.2291 loss_sem_seg: 0.2291 2023/05/15 04:33:25 - mmengine - INFO - Epoch(train) [17][ 350/1196] lr: 8.0000e-03 eta: 9:23:35 time: 1.4038 data_time: 0.0031 memory: 4968 grad_norm: 0.1094 loss: 0.2319 loss_sem_seg: 0.2319 2023/05/15 04:34:35 - mmengine - INFO - Epoch(train) [17][ 400/1196] lr: 8.0000e-03 eta: 9:22:21 time: 1.3912 data_time: 0.0031 memory: 4747 grad_norm: 0.1124 loss: 0.2240 loss_sem_seg: 0.2240 2023/05/15 04:35:45 - mmengine - INFO - Epoch(train) [17][ 450/1196] lr: 8.0000e-03 eta: 9:21:07 time: 1.3941 data_time: 0.0032 memory: 5391 grad_norm: 0.1083 loss: 0.2143 loss_sem_seg: 0.2143 2023/05/15 04:36:54 - mmengine - INFO - Epoch(train) [17][ 500/1196] lr: 8.0000e-03 eta: 9:19:52 time: 1.3782 data_time: 0.0033 memory: 4613 grad_norm: 0.1033 loss: 0.2185 loss_sem_seg: 0.2185 2023/05/15 04:38:02 - mmengine - INFO - Epoch(train) [17][ 550/1196] lr: 8.0000e-03 eta: 9:18:36 time: 1.3758 data_time: 0.0033 memory: 4573 grad_norm: 0.0982 loss: 0.2222 loss_sem_seg: 0.2222 2023/05/15 04:39:11 - mmengine - INFO - Epoch(train) [17][ 600/1196] lr: 8.0000e-03 eta: 9:17:21 time: 1.3756 data_time: 0.0034 memory: 4658 grad_norm: 0.1036 loss: 0.2268 loss_sem_seg: 0.2268 2023/05/15 04:40:42 - mmengine - INFO - Epoch(train) [17][ 650/1196] lr: 8.0000e-03 eta: 9:16:32 time: 1.8197 data_time: 0.0033 memory: 4656 grad_norm: 0.1108 loss: 0.2097 loss_sem_seg: 0.2097 2023/05/15 04:41:52 - mmengine - INFO - Epoch(train) [17][ 700/1196] lr: 8.0000e-03 eta: 9:15:18 time: 1.3961 data_time: 0.0032 memory: 4829 grad_norm: 0.1049 loss: 0.2189 loss_sem_seg: 0.2189 2023/05/15 04:43:00 - mmengine - INFO - Epoch(train) [17][ 750/1196] lr: 8.0000e-03 eta: 9:14:03 time: 1.3676 data_time: 0.0032 memory: 4890 grad_norm: 0.1190 loss: 0.2112 loss_sem_seg: 0.2112 2023/05/15 04:44:10 - mmengine - INFO - Epoch(train) [17][ 800/1196] lr: 8.0000e-03 eta: 9:12:48 time: 1.3854 data_time: 0.0031 memory: 4928 grad_norm: 0.1140 loss: 0.2310 loss_sem_seg: 0.2310 2023/05/15 04:45:19 - mmengine - INFO - Epoch(train) [17][ 850/1196] lr: 8.0000e-03 eta: 9:11:33 time: 1.3797 data_time: 0.0031 memory: 4754 grad_norm: 0.1130 loss: 0.2135 loss_sem_seg: 0.2135 2023/05/15 04:45:38 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 04:46:29 - mmengine - INFO - Epoch(train) [17][ 900/1196] lr: 8.0000e-03 eta: 9:10:20 time: 1.4069 data_time: 0.0032 memory: 4779 grad_norm: 0.1119 loss: 0.2172 loss_sem_seg: 0.2172 2023/05/15 04:47:37 - mmengine - INFO - Epoch(train) [17][ 950/1196] lr: 8.0000e-03 eta: 9:09:04 time: 1.3653 data_time: 0.0032 memory: 4579 grad_norm: 0.1250 loss: 0.2172 loss_sem_seg: 0.2172 2023/05/15 04:48:47 - mmengine - INFO - Epoch(train) [17][1000/1196] lr: 8.0000e-03 eta: 9:07:50 time: 1.3929 data_time: 0.0032 memory: 4689 grad_norm: 0.1065 loss: 0.2095 loss_sem_seg: 0.2095 2023/05/15 04:49:56 - mmengine - INFO - Epoch(train) [17][1050/1196] lr: 8.0000e-03 eta: 9:06:35 time: 1.3747 data_time: 0.0032 memory: 4839 grad_norm: 0.1145 loss: 0.2276 loss_sem_seg: 0.2276 2023/05/15 04:51:13 - mmengine - INFO - Epoch(train) [17][1100/1196] lr: 8.0000e-03 eta: 9:05:30 time: 1.5455 data_time: 0.0032 memory: 5177 grad_norm: 0.1165 loss: 0.2228 loss_sem_seg: 0.2228 2023/05/15 04:52:35 - mmengine - INFO - Epoch(train) [17][1150/1196] lr: 8.0000e-03 eta: 9:04:30 time: 1.6482 data_time: 0.0032 memory: 4880 grad_norm: 0.1112 loss: 0.2179 loss_sem_seg: 0.2179 2023/05/15 04:53:37 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 04:53:37 - mmengine - INFO - Saving checkpoint at 17 epochs 2023/05/15 04:53:49 - mmengine - INFO - Epoch(val) [17][ 50/509] eta: 0:00:42 time: 0.0919 data_time: 0.0020 memory: 4401 2023/05/15 04:53:53 - mmengine - INFO - Epoch(val) [17][100/509] eta: 0:00:35 time: 0.0841 data_time: 0.0020 memory: 991 2023/05/15 04:53:57 - mmengine - INFO - Epoch(val) [17][150/509] eta: 0:00:30 time: 0.0826 data_time: 0.0019 memory: 994 2023/05/15 04:54:01 - mmengine - INFO - Epoch(val) [17][200/509] eta: 0:00:26 time: 0.0837 data_time: 0.0019 memory: 979 2023/05/15 04:54:05 - mmengine - INFO - Epoch(val) [17][250/509] eta: 0:00:22 time: 0.0878 data_time: 0.0019 memory: 1004 2023/05/15 04:54:09 - mmengine - INFO - Epoch(val) [17][300/509] eta: 0:00:17 time: 0.0770 data_time: 0.0020 memory: 946 2023/05/15 04:54:13 - mmengine - INFO - Epoch(val) [17][350/509] eta: 0:00:13 time: 0.0794 data_time: 0.0019 memory: 970 2023/05/15 04:54:18 - mmengine - INFO - Epoch(val) [17][400/509] eta: 0:00:09 time: 0.0850 data_time: 0.0019 memory: 978 2023/05/15 04:54:22 - mmengine - INFO - Epoch(val) [17][450/509] eta: 0:00:04 time: 0.0851 data_time: 0.0018 memory: 991 2023/05/15 04:54:26 - mmengine - INFO - Epoch(val) [17][500/509] eta: 0:00:00 time: 0.0785 data_time: 0.0018 memory: 973 2023/05/15 04:55:06 - 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 | 0.9632 | 0.5288 | 0.7273 | 0.7837 | 0.5813 | 0.7309 | 0.8566 | 0.1091 | 0.9358 | 0.4719 | 0.8162 | 0.1246 | 0.8779 | 0.4874 | 0.8782 | 0.6296 | 0.7429 | 0.6599 | 0.4433 | 0.6499 | 0.9153 | 0.7241 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 04:55:06 - mmengine - INFO - Epoch(val) [17][509/509] car: 0.9632 bicycle: 0.5288 motorcycle: 0.7273 truck: 0.7837 bus: 0.5813 person: 0.7309 bicyclist: 0.8566 motorcyclist: 0.1091 road: 0.9358 parking: 0.4719 sidewalk: 0.8162 other-ground: 0.1246 building: 0.8779 fence: 0.4874 vegetation: 0.8782 trunck: 0.6296 terrian: 0.7429 pole: 0.6599 traffic-sign: 0.4433 miou: 0.6499 acc: 0.9153 acc_cls: 0.7241 data_time: 0.0018 time: 0.0802 2023/05/15 04:56:15 - mmengine - INFO - Epoch(train) [18][ 50/1196] lr: 8.0000e-03 eta: 9:02:05 time: 1.3823 data_time: 0.0043 memory: 5060 grad_norm: 0.1042 loss: 0.2110 loss_sem_seg: 0.2110 2023/05/15 04:57:23 - mmengine - INFO - Epoch(train) [18][ 100/1196] lr: 8.0000e-03 eta: 9:00:49 time: 1.3582 data_time: 0.0032 memory: 4407 grad_norm: 0.1206 loss: 0.2232 loss_sem_seg: 0.2232 2023/05/15 04:58:31 - mmengine - INFO - Epoch(train) [18][ 150/1196] lr: 8.0000e-03 eta: 8:59:34 time: 1.3696 data_time: 0.0031 memory: 5134 grad_norm: 0.0959 loss: 0.2180 loss_sem_seg: 0.2180 2023/05/15 04:59:39 - mmengine - INFO - Epoch(train) [18][ 200/1196] lr: 8.0000e-03 eta: 8:58:18 time: 1.3572 data_time: 0.0031 memory: 4929 grad_norm: 0.1027 loss: 0.2262 loss_sem_seg: 0.2262 2023/05/15 05:00:49 - mmengine - INFO - Epoch(train) [18][ 250/1196] lr: 8.0000e-03 eta: 8:57:04 time: 1.3945 data_time: 0.0031 memory: 4977 grad_norm: 0.1200 loss: 0.2267 loss_sem_seg: 0.2267 2023/05/15 05:01:57 - mmengine - INFO - Epoch(train) [18][ 300/1196] lr: 8.0000e-03 eta: 8:55:48 time: 1.3563 data_time: 0.0031 memory: 4736 grad_norm: 0.1012 loss: 0.2168 loss_sem_seg: 0.2168 2023/05/15 05:03:05 - mmengine - INFO - Epoch(train) [18][ 350/1196] lr: 8.0000e-03 eta: 8:54:33 time: 1.3716 data_time: 0.0033 memory: 4815 grad_norm: 0.1148 loss: 0.2307 loss_sem_seg: 0.2307 2023/05/15 05:04:14 - mmengine - INFO - Epoch(train) [18][ 400/1196] lr: 8.0000e-03 eta: 8:53:18 time: 1.3755 data_time: 0.0031 memory: 5099 grad_norm: 0.1113 loss: 0.2148 loss_sem_seg: 0.2148 2023/05/15 05:05:23 - mmengine - INFO - Epoch(train) [18][ 450/1196] lr: 8.0000e-03 eta: 8:52:04 time: 1.3811 data_time: 0.0031 memory: 4788 grad_norm: 0.1093 loss: 0.2169 loss_sem_seg: 0.2169 2023/05/15 05:06:33 - mmengine - INFO - Epoch(train) [18][ 500/1196] lr: 8.0000e-03 eta: 8:50:50 time: 1.3957 data_time: 0.0031 memory: 4455 grad_norm: 0.1013 loss: 0.2306 loss_sem_seg: 0.2306 2023/05/15 05:07:41 - mmengine - INFO - Epoch(train) [18][ 550/1196] lr: 8.0000e-03 eta: 8:49:34 time: 1.3624 data_time: 0.0032 memory: 4773 grad_norm: 0.1118 loss: 0.2118 loss_sem_seg: 0.2118 2023/05/15 05:08:50 - mmengine - INFO - Epoch(train) [18][ 600/1196] lr: 8.0000e-03 eta: 8:48:20 time: 1.3807 data_time: 0.0031 memory: 4975 grad_norm: 0.1078 loss: 0.2292 loss_sem_seg: 0.2292 2023/05/15 05:09:59 - mmengine - INFO - Epoch(train) [18][ 650/1196] lr: 8.0000e-03 eta: 8:47:06 time: 1.3811 data_time: 0.0031 memory: 4882 grad_norm: 0.0955 loss: 0.2103 loss_sem_seg: 0.2103 2023/05/15 05:10:24 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 05:11:08 - mmengine - INFO - Epoch(train) [18][ 700/1196] lr: 8.0000e-03 eta: 8:45:51 time: 1.3731 data_time: 0.0032 memory: 4858 grad_norm: 0.0998 loss: 0.2079 loss_sem_seg: 0.2079 2023/05/15 05:12:16 - mmengine - INFO - Epoch(train) [18][ 750/1196] lr: 8.0000e-03 eta: 8:44:35 time: 1.3576 data_time: 0.0031 memory: 5448 grad_norm: 0.1064 loss: 0.2136 loss_sem_seg: 0.2136 2023/05/15 05:13:24 - mmengine - INFO - Epoch(train) [18][ 800/1196] lr: 8.0000e-03 eta: 8:43:20 time: 1.3653 data_time: 0.0031 memory: 4951 grad_norm: 0.0975 loss: 0.2200 loss_sem_seg: 0.2200 2023/05/15 05:14:34 - mmengine - INFO - Epoch(train) [18][ 850/1196] lr: 8.0000e-03 eta: 8:42:07 time: 1.3921 data_time: 0.0032 memory: 4647 grad_norm: 0.1004 loss: 0.2081 loss_sem_seg: 0.2081 2023/05/15 05:15:42 - mmengine - INFO - Epoch(train) [18][ 900/1196] lr: 8.0000e-03 eta: 8:40:52 time: 1.3640 data_time: 0.0032 memory: 4790 grad_norm: 0.0995 loss: 0.2085 loss_sem_seg: 0.2085 2023/05/15 05:16:51 - mmengine - INFO - Epoch(train) [18][ 950/1196] lr: 8.0000e-03 eta: 8:39:38 time: 1.3900 data_time: 0.0032 memory: 4820 grad_norm: 0.1076 loss: 0.2150 loss_sem_seg: 0.2150 2023/05/15 05:18:00 - mmengine - INFO - Epoch(train) [18][1000/1196] lr: 8.0000e-03 eta: 8:38:23 time: 1.3732 data_time: 0.0032 memory: 4498 grad_norm: 0.1148 loss: 0.2151 loss_sem_seg: 0.2151 2023/05/15 05:19:08 - mmengine - INFO - Epoch(train) [18][1050/1196] lr: 8.0000e-03 eta: 8:37:08 time: 1.3655 data_time: 0.0032 memory: 4918 grad_norm: 0.1101 loss: 0.2202 loss_sem_seg: 0.2202 2023/05/15 05:20:17 - mmengine - INFO - Epoch(train) [18][1100/1196] lr: 8.0000e-03 eta: 8:35:54 time: 1.3763 data_time: 0.0032 memory: 4660 grad_norm: 0.1074 loss: 0.2232 loss_sem_seg: 0.2232 2023/05/15 05:21:25 - mmengine - INFO - Epoch(train) [18][1150/1196] lr: 8.0000e-03 eta: 8:34:39 time: 1.3563 data_time: 0.0031 memory: 5364 grad_norm: 0.1011 loss: 0.2357 loss_sem_seg: 0.2357 2023/05/15 05:22:50 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 05:22:50 - mmengine - INFO - Saving checkpoint at 18 epochs 2023/05/15 05:23:02 - mmengine - INFO - Epoch(val) [18][ 50/509] eta: 0:00:42 time: 0.0930 data_time: 0.0021 memory: 4728 2023/05/15 05:23:06 - mmengine - INFO - Epoch(val) [18][100/509] eta: 0:00:36 time: 0.0858 data_time: 0.0020 memory: 991 2023/05/15 05:23:10 - mmengine - INFO - Epoch(val) [18][150/509] eta: 0:00:31 time: 0.0833 data_time: 0.0020 memory: 994 2023/05/15 05:23:14 - mmengine - INFO - Epoch(val) [18][200/509] eta: 0:00:26 time: 0.0842 data_time: 0.0019 memory: 979 2023/05/15 05:23:19 - mmengine - INFO - Epoch(val) [18][250/509] eta: 0:00:22 time: 0.0890 data_time: 0.0020 memory: 1004 2023/05/15 05:23:23 - mmengine - INFO - Epoch(val) [18][300/509] eta: 0:00:17 time: 0.0812 data_time: 0.0020 memory: 946 2023/05/15 05:23:27 - mmengine - INFO - Epoch(val) [18][350/509] eta: 0:00:13 time: 0.0799 data_time: 0.0019 memory: 970 2023/05/15 05:23:31 - mmengine - INFO - Epoch(val) [18][400/509] eta: 0:00:09 time: 0.0853 data_time: 0.0019 memory: 978 2023/05/15 05:23:35 - mmengine - INFO - Epoch(val) [18][450/509] eta: 0:00:05 time: 0.0854 data_time: 0.0019 memory: 991 2023/05/15 05:23:39 - mmengine - INFO - Epoch(val) [18][500/509] eta: 0:00:00 time: 0.0789 data_time: 0.0018 memory: 973 2023/05/15 05:24:20 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9686 | 0.4469 | 0.7390 | 0.4851 | 0.6183 | 0.7037 | 0.8348 | 0.0350 | 0.9317 | 0.4381 | 0.8038 | 0.0246 | 0.9120 | 0.6652 | 0.8993 | 0.6932 | 0.7852 | 0.6573 | 0.4800 | 0.6380 | 0.9259 | 0.7272 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 05:24:20 - mmengine - INFO - Epoch(val) [18][509/509] car: 0.9686 bicycle: 0.4469 motorcycle: 0.7390 truck: 0.4851 bus: 0.6183 person: 0.7037 bicyclist: 0.8348 motorcyclist: 0.0350 road: 0.9317 parking: 0.4381 sidewalk: 0.8038 other-ground: 0.0246 building: 0.9120 fence: 0.6652 vegetation: 0.8993 trunck: 0.6932 terrian: 0.7852 pole: 0.6573 traffic-sign: 0.4800 miou: 0.6380 acc: 0.9259 acc_cls: 0.7272 data_time: 0.0018 time: 0.0807 2023/05/15 05:25:29 - mmengine - INFO - Epoch(train) [19][ 50/1196] lr: 8.0000e-03 eta: 8:32:38 time: 1.3823 data_time: 0.0039 memory: 4814 grad_norm: 0.0987 loss: 0.2183 loss_sem_seg: 0.2183 2023/05/15 05:26:38 - mmengine - INFO - Epoch(train) [19][ 100/1196] lr: 8.0000e-03 eta: 8:31:25 time: 1.3916 data_time: 0.0031 memory: 4842 grad_norm: 0.1214 loss: 0.2265 loss_sem_seg: 0.2265 2023/05/15 05:27:46 - mmengine - INFO - Epoch(train) [19][ 150/1196] lr: 8.0000e-03 eta: 8:30:09 time: 1.3577 data_time: 0.0031 memory: 4909 grad_norm: 0.1027 loss: 0.2346 loss_sem_seg: 0.2346 2023/05/15 05:28:55 - mmengine - INFO - Epoch(train) [19][ 200/1196] lr: 8.0000e-03 eta: 8:28:55 time: 1.3723 data_time: 0.0032 memory: 4980 grad_norm: 0.0920 loss: 0.2110 loss_sem_seg: 0.2110 2023/05/15 05:30:04 - mmengine - INFO - Epoch(train) [19][ 250/1196] lr: 8.0000e-03 eta: 8:27:41 time: 1.3884 data_time: 0.0031 memory: 4610 grad_norm: 0.0960 loss: 0.2063 loss_sem_seg: 0.2063 2023/05/15 05:31:15 - mmengine - INFO - Epoch(train) [19][ 300/1196] lr: 8.0000e-03 eta: 8:26:29 time: 1.4151 data_time: 0.0031 memory: 4674 grad_norm: 0.0967 loss: 0.2191 loss_sem_seg: 0.2191 2023/05/15 05:32:23 - mmengine - INFO - Epoch(train) [19][ 350/1196] lr: 8.0000e-03 eta: 8:25:14 time: 1.3669 data_time: 0.0031 memory: 4618 grad_norm: 0.0951 loss: 0.2137 loss_sem_seg: 0.2137 2023/05/15 05:33:48 - mmengine - INFO - Epoch(train) [19][ 400/1196] lr: 8.0000e-03 eta: 8:24:15 time: 1.6991 data_time: 0.0031 memory: 4724 grad_norm: 0.1114 loss: 0.2275 loss_sem_seg: 0.2275 2023/05/15 05:35:03 - mmengine - INFO - Epoch(train) [19][ 450/1196] lr: 8.0000e-03 eta: 8:23:07 time: 1.5035 data_time: 0.0032 memory: 5100 grad_norm: 0.1083 loss: 0.2188 loss_sem_seg: 0.2188 2023/05/15 05:35:34 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 05:36:13 - mmengine - INFO - Epoch(train) [19][ 500/1196] lr: 8.0000e-03 eta: 8:21:54 time: 1.4008 data_time: 0.0032 memory: 4942 grad_norm: 0.1039 loss: 0.2128 loss_sem_seg: 0.2128 2023/05/15 05:37:23 - mmengine - INFO - Epoch(train) [19][ 550/1196] lr: 8.0000e-03 eta: 8:20:41 time: 1.3957 data_time: 0.0031 memory: 4570 grad_norm: 0.1281 loss: 0.2379 loss_sem_seg: 0.2379 2023/05/15 05:38:32 - mmengine - INFO - Epoch(train) [19][ 600/1196] lr: 8.0000e-03 eta: 8:19:27 time: 1.3770 data_time: 0.0031 memory: 5147 grad_norm: 0.1063 loss: 0.2240 loss_sem_seg: 0.2240 2023/05/15 05:39:40 - mmengine - INFO - Epoch(train) [19][ 650/1196] lr: 8.0000e-03 eta: 8:18:12 time: 1.3647 data_time: 0.0031 memory: 4626 grad_norm: 0.0988 loss: 0.2171 loss_sem_seg: 0.2171 2023/05/15 05:40:50 - mmengine - INFO - Epoch(train) [19][ 700/1196] lr: 8.0000e-03 eta: 8:16:59 time: 1.3947 data_time: 0.0031 memory: 4965 grad_norm: 0.1216 loss: 0.2222 loss_sem_seg: 0.2222 2023/05/15 05:41:58 - mmengine - INFO - Epoch(train) [19][ 750/1196] lr: 8.0000e-03 eta: 8:15:43 time: 1.3560 data_time: 0.0031 memory: 4892 grad_norm: 0.1116 loss: 0.2165 loss_sem_seg: 0.2165 2023/05/15 05:43:07 - mmengine - INFO - Epoch(train) [19][ 800/1196] lr: 8.0000e-03 eta: 8:14:29 time: 1.3777 data_time: 0.0031 memory: 4703 grad_norm: 0.1074 loss: 0.2260 loss_sem_seg: 0.2260 2023/05/15 05:44:15 - mmengine - INFO - Epoch(train) [19][ 850/1196] lr: 8.0000e-03 eta: 8:13:15 time: 1.3654 data_time: 0.0031 memory: 4622 grad_norm: 0.0976 loss: 0.2032 loss_sem_seg: 0.2032 2023/05/15 05:45:24 - mmengine - INFO - Epoch(train) [19][ 900/1196] lr: 8.0000e-03 eta: 8:12:01 time: 1.3810 data_time: 0.0031 memory: 4750 grad_norm: 0.0984 loss: 0.2084 loss_sem_seg: 0.2084 2023/05/15 05:46:34 - mmengine - INFO - Epoch(train) [19][ 950/1196] lr: 8.0000e-03 eta: 8:10:48 time: 1.3940 data_time: 0.0031 memory: 5314 grad_norm: 0.0909 loss: 0.2047 loss_sem_seg: 0.2047 2023/05/15 05:47:43 - mmengine - INFO - Epoch(train) [19][1000/1196] lr: 8.0000e-03 eta: 8:09:34 time: 1.3772 data_time: 0.0032 memory: 4607 grad_norm: 0.1183 loss: 0.2053 loss_sem_seg: 0.2053 2023/05/15 05:48:52 - mmengine - INFO - Epoch(train) [19][1050/1196] lr: 8.0000e-03 eta: 8:08:20 time: 1.3917 data_time: 0.0031 memory: 5074 grad_norm: 0.1065 loss: 0.2259 loss_sem_seg: 0.2259 2023/05/15 05:50:02 - mmengine - INFO - Epoch(train) [19][1100/1196] lr: 8.0000e-03 eta: 8:07:07 time: 1.3992 data_time: 0.0032 memory: 4865 grad_norm: 0.0958 loss: 0.2051 loss_sem_seg: 0.2051 2023/05/15 05:51:12 - mmengine - INFO - Epoch(train) [19][1150/1196] lr: 8.0000e-03 eta: 8:05:54 time: 1.3932 data_time: 0.0031 memory: 4601 grad_norm: 0.0984 loss: 0.2293 loss_sem_seg: 0.2293 2023/05/15 05:52:15 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 05:52:15 - mmengine - INFO - Saving checkpoint at 19 epochs 2023/05/15 05:52:27 - mmengine - INFO - Epoch(val) [19][ 50/509] eta: 0:00:42 time: 0.0922 data_time: 0.0020 memory: 4956 2023/05/15 05:52:31 - mmengine - INFO - Epoch(val) [19][100/509] eta: 0:00:36 time: 0.0845 data_time: 0.0019 memory: 991 2023/05/15 05:52:35 - mmengine - INFO - Epoch(val) [19][150/509] eta: 0:00:31 time: 0.0825 data_time: 0.0019 memory: 994 2023/05/15 05:52:39 - mmengine - INFO - Epoch(val) [19][200/509] eta: 0:00:26 time: 0.0838 data_time: 0.0019 memory: 979 2023/05/15 05:52:43 - mmengine - INFO - Epoch(val) [19][250/509] eta: 0:00:22 time: 0.0878 data_time: 0.0019 memory: 1004 2023/05/15 05:52:47 - mmengine - INFO - Epoch(val) [19][300/509] eta: 0:00:17 time: 0.0764 data_time: 0.0019 memory: 946 2023/05/15 05:52:51 - mmengine - INFO - Epoch(val) [19][350/509] eta: 0:00:13 time: 0.0795 data_time: 0.0019 memory: 970 2023/05/15 05:52:56 - mmengine - INFO - Epoch(val) [19][400/509] eta: 0:00:09 time: 0.0842 data_time: 0.0019 memory: 978 2023/05/15 05:53:00 - mmengine - INFO - Epoch(val) [19][450/509] eta: 0:00:04 time: 0.0848 data_time: 0.0018 memory: 991 2023/05/15 05:53:04 - mmengine - INFO - Epoch(val) [19][500/509] eta: 0:00:00 time: 0.0784 data_time: 0.0017 memory: 973 2023/05/15 05:53:44 - 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 | 0.9652 | 0.5534 | 0.7266 | 0.8071 | 0.7119 | 0.6842 | 0.8133 | 0.0283 | 0.9292 | 0.5416 | 0.8069 | 0.0288 | 0.9030 | 0.5997 | 0.9002 | 0.7092 | 0.7874 | 0.6407 | 0.4834 | 0.6642 | 0.9257 | 0.7486 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 05:53:44 - mmengine - INFO - Epoch(val) [19][509/509] car: 0.9652 bicycle: 0.5534 motorcycle: 0.7266 truck: 0.8071 bus: 0.7119 person: 0.6842 bicyclist: 0.8133 motorcyclist: 0.0283 road: 0.9292 parking: 0.5416 sidewalk: 0.8069 other-ground: 0.0288 building: 0.9030 fence: 0.5997 vegetation: 0.9002 trunck: 0.7092 terrian: 0.7874 pole: 0.6407 traffic-sign: 0.4834 miou: 0.6642 acc: 0.9257 acc_cls: 0.7486 data_time: 0.0017 time: 0.0801 2023/05/15 05:54:52 - mmengine - INFO - Epoch(train) [20][ 50/1196] lr: 8.0000e-03 eta: 8:03:31 time: 1.3582 data_time: 0.0040 memory: 4669 grad_norm: 0.0927 loss: 0.2147 loss_sem_seg: 0.2147 2023/05/15 05:56:03 - mmengine - INFO - Epoch(train) [20][ 100/1196] lr: 8.0000e-03 eta: 8:02:19 time: 1.4174 data_time: 0.0032 memory: 4836 grad_norm: 0.0962 loss: 0.2218 loss_sem_seg: 0.2218 2023/05/15 05:57:11 - mmengine - INFO - Epoch(train) [20][ 150/1196] lr: 8.0000e-03 eta: 8:01:05 time: 1.3631 data_time: 0.0032 memory: 5279 grad_norm: 0.1044 loss: 0.2016 loss_sem_seg: 0.2016 2023/05/15 05:58:19 - mmengine - INFO - Epoch(train) [20][ 200/1196] lr: 8.0000e-03 eta: 7:59:51 time: 1.3698 data_time: 0.0032 memory: 5279 grad_norm: 0.1060 loss: 0.2231 loss_sem_seg: 0.2231 2023/05/15 05:59:28 - mmengine - INFO - Epoch(train) [20][ 250/1196] lr: 8.0000e-03 eta: 7:58:36 time: 1.3653 data_time: 0.0032 memory: 4823 grad_norm: 0.1324 loss: 0.2234 loss_sem_seg: 0.2234 2023/05/15 06:00:04 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 06:00:36 - mmengine - INFO - Epoch(train) [20][ 300/1196] lr: 8.0000e-03 eta: 7:57:22 time: 1.3743 data_time: 0.0031 memory: 4956 grad_norm: 0.1050 loss: 0.2151 loss_sem_seg: 0.2151 2023/05/15 06:01:45 - mmengine - INFO - Epoch(train) [20][ 350/1196] lr: 8.0000e-03 eta: 7:56:09 time: 1.3812 data_time: 0.0033 memory: 4685 grad_norm: 0.0973 loss: 0.2083 loss_sem_seg: 0.2083 2023/05/15 06:02:54 - mmengine - INFO - Epoch(train) [20][ 400/1196] lr: 8.0000e-03 eta: 7:54:54 time: 1.3614 data_time: 0.0033 memory: 4582 grad_norm: 0.0980 loss: 0.2005 loss_sem_seg: 0.2005 2023/05/15 06:04:11 - mmengine - INFO - Epoch(train) [20][ 450/1196] lr: 8.0000e-03 eta: 7:53:48 time: 1.5438 data_time: 0.0032 memory: 4660 grad_norm: 0.1071 loss: 0.2109 loss_sem_seg: 0.2109 2023/05/15 06:05:33 - mmengine - INFO - Epoch(train) [20][ 500/1196] lr: 8.0000e-03 eta: 7:52:46 time: 1.6509 data_time: 0.0032 memory: 4998 grad_norm: 0.1058 loss: 0.2264 loss_sem_seg: 0.2264 2023/05/15 06:06:43 - mmengine - INFO - Epoch(train) [20][ 550/1196] lr: 8.0000e-03 eta: 7:51:33 time: 1.3986 data_time: 0.0031 memory: 4688 grad_norm: 0.0956 loss: 0.2275 loss_sem_seg: 0.2275 2023/05/15 06:07:52 - mmengine - INFO - Epoch(train) [20][ 600/1196] lr: 8.0000e-03 eta: 7:50:19 time: 1.3774 data_time: 0.0031 memory: 5159 grad_norm: 0.0993 loss: 0.2232 loss_sem_seg: 0.2232 2023/05/15 06:09:01 - mmengine - INFO - Epoch(train) [20][ 650/1196] lr: 8.0000e-03 eta: 7:49:06 time: 1.3813 data_time: 0.0031 memory: 4714 grad_norm: 0.1147 loss: 0.2162 loss_sem_seg: 0.2162 2023/05/15 06:10:10 - mmengine - INFO - Epoch(train) [20][ 700/1196] lr: 8.0000e-03 eta: 7:47:52 time: 1.3789 data_time: 0.0031 memory: 4711 grad_norm: 0.0982 loss: 0.2153 loss_sem_seg: 0.2153 2023/05/15 06:11:19 - mmengine - INFO - Epoch(train) [20][ 750/1196] lr: 8.0000e-03 eta: 7:46:38 time: 1.3739 data_time: 0.0031 memory: 4621 grad_norm: 0.1056 loss: 0.2126 loss_sem_seg: 0.2126 2023/05/15 06:12:27 - mmengine - INFO - Epoch(train) [20][ 800/1196] lr: 8.0000e-03 eta: 7:45:24 time: 1.3661 data_time: 0.0031 memory: 4436 grad_norm: 0.0971 loss: 0.2116 loss_sem_seg: 0.2116 2023/05/15 06:13:36 - mmengine - INFO - Epoch(train) [20][ 850/1196] lr: 8.0000e-03 eta: 7:44:10 time: 1.3698 data_time: 0.0032 memory: 4714 grad_norm: 0.0994 loss: 0.2087 loss_sem_seg: 0.2087 2023/05/15 06:14:45 - mmengine - INFO - Epoch(train) [20][ 900/1196] lr: 8.0000e-03 eta: 7:42:57 time: 1.3847 data_time: 0.0032 memory: 4532 grad_norm: 0.1076 loss: 0.2336 loss_sem_seg: 0.2336 2023/05/15 06:16:13 - mmengine - INFO - Epoch(train) [20][ 950/1196] lr: 8.0000e-03 eta: 7:41:59 time: 1.7577 data_time: 0.0032 memory: 4535 grad_norm: 0.1034 loss: 0.2219 loss_sem_seg: 0.2219 2023/05/15 06:17:24 - mmengine - INFO - Epoch(train) [20][1000/1196] lr: 8.0000e-03 eta: 7:40:47 time: 1.4213 data_time: 0.0032 memory: 4665 grad_norm: 0.1064 loss: 0.2167 loss_sem_seg: 0.2167 2023/05/15 06:18:34 - mmengine - INFO - Epoch(train) [20][1050/1196] lr: 8.0000e-03 eta: 7:39:34 time: 1.4038 data_time: 0.0031 memory: 5333 grad_norm: 0.1061 loss: 0.2237 loss_sem_seg: 0.2237 2023/05/15 06:19:42 - mmengine - INFO - Epoch(train) [20][1100/1196] lr: 8.0000e-03 eta: 7:38:20 time: 1.3697 data_time: 0.0032 memory: 5238 grad_norm: 0.1083 loss: 0.2148 loss_sem_seg: 0.2148 2023/05/15 06:20:51 - mmengine - INFO - Epoch(train) [20][1150/1196] lr: 8.0000e-03 eta: 7:37:06 time: 1.3707 data_time: 0.0031 memory: 5338 grad_norm: 0.0971 loss: 0.2119 loss_sem_seg: 0.2119 2023/05/15 06:21:54 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 06:21:54 - mmengine - INFO - Saving checkpoint at 20 epochs 2023/05/15 06:22:05 - mmengine - INFO - Epoch(val) [20][ 50/509] eta: 0:00:42 time: 0.0922 data_time: 0.0020 memory: 4417 2023/05/15 06:22:09 - mmengine - INFO - Epoch(val) [20][100/509] eta: 0:00:36 time: 0.0846 data_time: 0.0019 memory: 991 2023/05/15 06:22:14 - mmengine - INFO - Epoch(val) [20][150/509] eta: 0:00:31 time: 0.0825 data_time: 0.0019 memory: 994 2023/05/15 06:22:18 - mmengine - INFO - Epoch(val) [20][200/509] eta: 0:00:26 time: 0.0844 data_time: 0.0020 memory: 979 2023/05/15 06:22:22 - mmengine - INFO - Epoch(val) [20][250/509] eta: 0:00:22 time: 0.0885 data_time: 0.0020 memory: 1004 2023/05/15 06:22:26 - mmengine - INFO - Epoch(val) [20][300/509] eta: 0:00:17 time: 0.0765 data_time: 0.0020 memory: 946 2023/05/15 06:22:30 - mmengine - INFO - Epoch(val) [20][350/509] eta: 0:00:13 time: 0.0796 data_time: 0.0019 memory: 970 2023/05/15 06:22:34 - mmengine - INFO - Epoch(val) [20][400/509] eta: 0:00:09 time: 0.0846 data_time: 0.0019 memory: 978 2023/05/15 06:22:39 - mmengine - INFO - Epoch(val) [20][450/509] eta: 0:00:04 time: 0.0850 data_time: 0.0018 memory: 991 2023/05/15 06:22:43 - mmengine - INFO - Epoch(val) [20][500/509] eta: 0:00:00 time: 0.0785 data_time: 0.0017 memory: 973 2023/05/15 06:23:22 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9500 | 0.5212 | 0.7030 | 0.7712 | 0.4522 | 0.7619 | 0.8727 | 0.1505 | 0.9367 | 0.3909 | 0.8206 | 0.0120 | 0.9030 | 0.6476 | 0.8969 | 0.6014 | 0.7954 | 0.6152 | 0.5064 | 0.6478 | 0.9261 | 0.7148 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 06:23:22 - mmengine - INFO - Epoch(val) [20][509/509] car: 0.9500 bicycle: 0.5212 motorcycle: 0.7030 truck: 0.7712 bus: 0.4522 person: 0.7619 bicyclist: 0.8727 motorcyclist: 0.1505 road: 0.9367 parking: 0.3909 sidewalk: 0.8206 other-ground: 0.0120 building: 0.9030 fence: 0.6476 vegetation: 0.8969 trunck: 0.6014 terrian: 0.7954 pole: 0.6152 traffic-sign: 0.5064 miou: 0.6478 acc: 0.9261 acc_cls: 0.7148 data_time: 0.0017 time: 0.0804 2023/05/15 06:24:31 - mmengine - INFO - Epoch(train) [21][ 50/1196] lr: 8.0000e-03 eta: 7:34:45 time: 1.3773 data_time: 0.0040 memory: 5425 grad_norm: 0.1122 loss: 0.2134 loss_sem_seg: 0.2134 2023/05/15 06:25:12 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 06:25:39 - mmengine - INFO - Epoch(train) [21][ 100/1196] lr: 8.0000e-03 eta: 7:33:30 time: 1.3542 data_time: 0.0032 memory: 5065 grad_norm: 0.1023 loss: 0.2009 loss_sem_seg: 0.2009 2023/05/15 06:26:50 - mmengine - INFO - Epoch(train) [21][ 150/1196] lr: 8.0000e-03 eta: 7:32:18 time: 1.4102 data_time: 0.0032 memory: 5139 grad_norm: 0.0946 loss: 0.2104 loss_sem_seg: 0.2104 2023/05/15 06:27:58 - mmengine - INFO - Epoch(train) [21][ 200/1196] lr: 8.0000e-03 eta: 7:31:04 time: 1.3612 data_time: 0.0032 memory: 4580 grad_norm: 0.1010 loss: 0.2094 loss_sem_seg: 0.2094 2023/05/15 06:29:06 - mmengine - INFO - Epoch(train) [21][ 250/1196] lr: 8.0000e-03 eta: 7:29:50 time: 1.3673 data_time: 0.0035 memory: 4630 grad_norm: 0.1194 loss: 0.2158 loss_sem_seg: 0.2158 2023/05/15 06:30:15 - mmengine - INFO - Epoch(train) [21][ 300/1196] lr: 8.0000e-03 eta: 7:28:37 time: 1.3799 data_time: 0.0032 memory: 5043 grad_norm: 0.1024 loss: 0.2179 loss_sem_seg: 0.2179 2023/05/15 06:31:24 - mmengine - INFO - Epoch(train) [21][ 350/1196] lr: 8.0000e-03 eta: 7:27:24 time: 1.3883 data_time: 0.0033 memory: 4671 grad_norm: 0.1033 loss: 0.2133 loss_sem_seg: 0.2133 2023/05/15 06:32:33 - mmengine - INFO - Epoch(train) [21][ 400/1196] lr: 8.0000e-03 eta: 7:26:10 time: 1.3630 data_time: 0.0034 memory: 4789 grad_norm: 0.0968 loss: 0.2143 loss_sem_seg: 0.2143 2023/05/15 06:33:42 - mmengine - INFO - Epoch(train) [21][ 450/1196] lr: 8.0000e-03 eta: 7:24:56 time: 1.3790 data_time: 0.0034 memory: 5023 grad_norm: 0.1004 loss: 0.2073 loss_sem_seg: 0.2073 2023/05/15 06:34:50 - mmengine - INFO - Epoch(train) [21][ 500/1196] lr: 8.0000e-03 eta: 7:23:43 time: 1.3785 data_time: 0.0034 memory: 4782 grad_norm: 0.1060 loss: 0.2077 loss_sem_seg: 0.2077 2023/05/15 06:36:00 - mmengine - INFO - Epoch(train) [21][ 550/1196] lr: 8.0000e-03 eta: 7:22:30 time: 1.3996 data_time: 0.0033 memory: 4749 grad_norm: 0.1016 loss: 0.2050 loss_sem_seg: 0.2050 2023/05/15 06:37:09 - mmengine - INFO - Epoch(train) [21][ 600/1196] lr: 8.0000e-03 eta: 7:21:17 time: 1.3640 data_time: 0.0033 memory: 4498 grad_norm: 0.1077 loss: 0.2173 loss_sem_seg: 0.2173 2023/05/15 06:38:17 - mmengine - INFO - Epoch(train) [21][ 650/1196] lr: 8.0000e-03 eta: 7:20:03 time: 1.3754 data_time: 0.0034 memory: 4951 grad_norm: 0.1006 loss: 0.2108 loss_sem_seg: 0.2108 2023/05/15 06:39:26 - mmengine - INFO - Epoch(train) [21][ 700/1196] lr: 8.0000e-03 eta: 7:18:49 time: 1.3683 data_time: 0.0033 memory: 4625 grad_norm: 0.0947 loss: 0.2102 loss_sem_seg: 0.2102 2023/05/15 06:40:35 - mmengine - INFO - Epoch(train) [21][ 750/1196] lr: 8.0000e-03 eta: 7:17:36 time: 1.3788 data_time: 0.0032 memory: 4647 grad_norm: 0.1031 loss: 0.2028 loss_sem_seg: 0.2028 2023/05/15 06:41:43 - mmengine - INFO - Epoch(train) [21][ 800/1196] lr: 8.0000e-03 eta: 7:16:22 time: 1.3649 data_time: 0.0032 memory: 5084 grad_norm: 0.1181 loss: 0.2138 loss_sem_seg: 0.2138 2023/05/15 06:42:52 - mmengine - INFO - Epoch(train) [21][ 850/1196] lr: 8.0000e-03 eta: 7:15:09 time: 1.3743 data_time: 0.0032 memory: 4806 grad_norm: 0.1028 loss: 0.2169 loss_sem_seg: 0.2169 2023/05/15 06:44:01 - mmengine - INFO - Epoch(train) [21][ 900/1196] lr: 8.0000e-03 eta: 7:13:56 time: 1.3902 data_time: 0.0032 memory: 4650 grad_norm: 0.1077 loss: 0.2206 loss_sem_seg: 0.2206 2023/05/15 06:45:09 - mmengine - INFO - Epoch(train) [21][ 950/1196] lr: 8.0000e-03 eta: 7:12:42 time: 1.3562 data_time: 0.0032 memory: 4825 grad_norm: 0.1012 loss: 0.2080 loss_sem_seg: 0.2080 2023/05/15 06:46:32 - mmengine - INFO - Epoch(train) [21][1000/1196] lr: 8.0000e-03 eta: 7:11:40 time: 1.6665 data_time: 0.0032 memory: 4718 grad_norm: 0.0965 loss: 0.2184 loss_sem_seg: 0.2184 2023/05/15 06:47:50 - mmengine - INFO - Epoch(train) [21][1050/1196] lr: 8.0000e-03 eta: 7:10:33 time: 1.5618 data_time: 0.0032 memory: 4934 grad_norm: 0.0985 loss: 0.2118 loss_sem_seg: 0.2118 2023/05/15 06:48:31 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 06:48:59 - mmengine - INFO - Epoch(train) [21][1100/1196] lr: 8.0000e-03 eta: 7:09:19 time: 1.3620 data_time: 0.0033 memory: 4836 grad_norm: 0.0894 loss: 0.2078 loss_sem_seg: 0.2078 2023/05/15 06:50:08 - mmengine - INFO - Epoch(train) [21][1150/1196] lr: 8.0000e-03 eta: 7:08:06 time: 1.3783 data_time: 0.0032 memory: 4653 grad_norm: 0.1000 loss: 0.2172 loss_sem_seg: 0.2172 2023/05/15 06:51:11 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 06:51:11 - mmengine - INFO - Saving checkpoint at 21 epochs 2023/05/15 06:51:22 - mmengine - INFO - Epoch(val) [21][ 50/509] eta: 0:00:42 time: 0.0934 data_time: 0.0021 memory: 4456 2023/05/15 06:51:26 - mmengine - INFO - Epoch(val) [21][100/509] eta: 0:00:36 time: 0.0855 data_time: 0.0020 memory: 991 2023/05/15 06:51:30 - mmengine - INFO - Epoch(val) [21][150/509] eta: 0:00:31 time: 0.0834 data_time: 0.0020 memory: 994 2023/05/15 06:51:35 - mmengine - INFO - Epoch(val) [21][200/509] eta: 0:00:26 time: 0.0847 data_time: 0.0020 memory: 979 2023/05/15 06:51:39 - mmengine - INFO - Epoch(val) [21][250/509] eta: 0:00:22 time: 0.0886 data_time: 0.0019 memory: 1004 2023/05/15 06:51:43 - mmengine - INFO - Epoch(val) [21][300/509] eta: 0:00:17 time: 0.0765 data_time: 0.0020 memory: 946 2023/05/15 06:51:47 - mmengine - INFO - Epoch(val) [21][350/509] eta: 0:00:13 time: 0.0798 data_time: 0.0019 memory: 970 2023/05/15 06:51:51 - mmengine - INFO - Epoch(val) [21][400/509] eta: 0:00:09 time: 0.0845 data_time: 0.0019 memory: 978 2023/05/15 06:51:55 - mmengine - INFO - Epoch(val) [21][450/509] eta: 0:00:04 time: 0.0843 data_time: 0.0018 memory: 991 2023/05/15 06:51:59 - mmengine - INFO - Epoch(val) [21][500/509] eta: 0:00:00 time: 0.0783 data_time: 0.0017 memory: 973 2023/05/15 06:52:39 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9532 | 0.5385 | 0.7389 | 0.6760 | 0.5590 | 0.7355 | 0.8728 | 0.0779 | 0.9391 | 0.5047 | 0.8203 | 0.0323 | 0.9156 | 0.6602 | 0.8817 | 0.7096 | 0.7414 | 0.6559 | 0.5056 | 0.6588 | 0.9219 | 0.7433 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 06:52:39 - mmengine - INFO - Epoch(val) [21][509/509] car: 0.9532 bicycle: 0.5385 motorcycle: 0.7389 truck: 0.6760 bus: 0.5590 person: 0.7355 bicyclist: 0.8728 motorcyclist: 0.0779 road: 0.9391 parking: 0.5047 sidewalk: 0.8203 other-ground: 0.0323 building: 0.9156 fence: 0.6602 vegetation: 0.8817 trunck: 0.7096 terrian: 0.7414 pole: 0.6559 traffic-sign: 0.5056 miou: 0.6588 acc: 0.9219 acc_cls: 0.7433 data_time: 0.0017 time: 0.0800 2023/05/15 06:53:48 - mmengine - INFO - Epoch(train) [22][ 50/1196] lr: 8.0000e-03 eta: 7:05:46 time: 1.3879 data_time: 0.0040 memory: 5115 grad_norm: 0.0992 loss: 0.2092 loss_sem_seg: 0.2092 2023/05/15 06:54:57 - mmengine - INFO - Epoch(train) [22][ 100/1196] lr: 8.0000e-03 eta: 7:04:32 time: 1.3693 data_time: 0.0032 memory: 5000 grad_norm: 0.0993 loss: 0.2146 loss_sem_seg: 0.2146 2023/05/15 06:56:07 - mmengine - INFO - Epoch(train) [22][ 150/1196] lr: 8.0000e-03 eta: 7:03:20 time: 1.4092 data_time: 0.0034 memory: 4769 grad_norm: 0.0974 loss: 0.2058 loss_sem_seg: 0.2058 2023/05/15 06:57:17 - mmengine - INFO - Epoch(train) [22][ 200/1196] lr: 8.0000e-03 eta: 7:02:08 time: 1.3933 data_time: 0.0033 memory: 4646 grad_norm: 0.0975 loss: 0.2170 loss_sem_seg: 0.2170 2023/05/15 06:58:47 - mmengine - INFO - Epoch(train) [22][ 250/1196] lr: 8.0000e-03 eta: 7:01:09 time: 1.7919 data_time: 0.0035 memory: 4834 grad_norm: 0.0897 loss: 0.2014 loss_sem_seg: 0.2014 2023/05/15 06:59:56 - mmengine - INFO - Epoch(train) [22][ 300/1196] lr: 8.0000e-03 eta: 6:59:56 time: 1.3809 data_time: 0.0033 memory: 4555 grad_norm: 0.1030 loss: 0.1980 loss_sem_seg: 0.1980 2023/05/15 07:01:05 - mmengine - INFO - Epoch(train) [22][ 350/1196] lr: 8.0000e-03 eta: 6:58:43 time: 1.3776 data_time: 0.0031 memory: 5545 grad_norm: 0.0925 loss: 0.2259 loss_sem_seg: 0.2259 2023/05/15 07:02:13 - mmengine - INFO - Epoch(train) [22][ 400/1196] lr: 8.0000e-03 eta: 6:57:29 time: 1.3693 data_time: 0.0031 memory: 4864 grad_norm: 0.1067 loss: 0.2080 loss_sem_seg: 0.2080 2023/05/15 07:03:22 - mmengine - INFO - Epoch(train) [22][ 450/1196] lr: 8.0000e-03 eta: 6:56:16 time: 1.3758 data_time: 0.0032 memory: 4482 grad_norm: 0.0940 loss: 0.2087 loss_sem_seg: 0.2087 2023/05/15 07:04:30 - mmengine - INFO - Epoch(train) [22][ 500/1196] lr: 8.0000e-03 eta: 6:55:02 time: 1.3634 data_time: 0.0031 memory: 4519 grad_norm: 0.0981 loss: 0.2105 loss_sem_seg: 0.2105 2023/05/15 07:05:39 - mmengine - INFO - Epoch(train) [22][ 550/1196] lr: 8.0000e-03 eta: 6:53:49 time: 1.3727 data_time: 0.0031 memory: 4647 grad_norm: 0.1017 loss: 0.2203 loss_sem_seg: 0.2203 2023/05/15 07:06:48 - mmengine - INFO - Epoch(train) [22][ 600/1196] lr: 8.0000e-03 eta: 6:52:36 time: 1.3855 data_time: 0.0032 memory: 5523 grad_norm: 0.0996 loss: 0.2051 loss_sem_seg: 0.2051 2023/05/15 07:07:57 - mmengine - INFO - Epoch(train) [22][ 650/1196] lr: 8.0000e-03 eta: 6:51:23 time: 1.3795 data_time: 0.0032 memory: 4869 grad_norm: 0.0923 loss: 0.1986 loss_sem_seg: 0.1986 2023/05/15 07:09:05 - mmengine - INFO - Epoch(train) [22][ 700/1196] lr: 8.0000e-03 eta: 6:50:10 time: 1.3665 data_time: 0.0032 memory: 4693 grad_norm: 0.0965 loss: 0.2120 loss_sem_seg: 0.2120 2023/05/15 07:10:14 - mmengine - INFO - Epoch(train) [22][ 750/1196] lr: 8.0000e-03 eta: 6:48:57 time: 1.3758 data_time: 0.0032 memory: 4961 grad_norm: 0.1032 loss: 0.2096 loss_sem_seg: 0.2096 2023/05/15 07:11:23 - mmengine - INFO - Epoch(train) [22][ 800/1196] lr: 8.0000e-03 eta: 6:47:44 time: 1.3743 data_time: 0.0032 memory: 4624 grad_norm: 0.1078 loss: 0.2111 loss_sem_seg: 0.2111 2023/05/15 07:12:31 - mmengine - INFO - Epoch(train) [22][ 850/1196] lr: 8.0000e-03 eta: 6:46:30 time: 1.3669 data_time: 0.0032 memory: 4877 grad_norm: 0.1064 loss: 0.2309 loss_sem_seg: 0.2309 2023/05/15 07:13:19 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 07:13:41 - mmengine - INFO - Epoch(train) [22][ 900/1196] lr: 8.0000e-03 eta: 6:45:18 time: 1.4035 data_time: 0.0032 memory: 4631 grad_norm: 0.0978 loss: 0.1980 loss_sem_seg: 0.1980 2023/05/15 07:14:49 - mmengine - INFO - Epoch(train) [22][ 950/1196] lr: 8.0000e-03 eta: 6:44:05 time: 1.3603 data_time: 0.0034 memory: 4881 grad_norm: 0.0885 loss: 0.2214 loss_sem_seg: 0.2214 2023/05/15 07:15:58 - mmengine - INFO - Epoch(train) [22][1000/1196] lr: 8.0000e-03 eta: 6:42:52 time: 1.3841 data_time: 0.0034 memory: 4760 grad_norm: 0.1026 loss: 0.2173 loss_sem_seg: 0.2173 2023/05/15 07:17:07 - mmengine - INFO - Epoch(train) [22][1050/1196] lr: 8.0000e-03 eta: 6:41:38 time: 1.3631 data_time: 0.0032 memory: 4718 grad_norm: 0.0942 loss: 0.1992 loss_sem_seg: 0.1992 2023/05/15 07:18:15 - mmengine - INFO - Epoch(train) [22][1100/1196] lr: 8.0000e-03 eta: 6:40:26 time: 1.3764 data_time: 0.0032 memory: 4816 grad_norm: 0.0939 loss: 0.2176 loss_sem_seg: 0.2176 2023/05/15 07:19:25 - mmengine - INFO - Epoch(train) [22][1150/1196] lr: 8.0000e-03 eta: 6:39:13 time: 1.3887 data_time: 0.0032 memory: 4838 grad_norm: 0.0936 loss: 0.2108 loss_sem_seg: 0.2108 2023/05/15 07:20:28 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 07:20:28 - mmengine - INFO - Saving checkpoint at 22 epochs 2023/05/15 07:20:39 - mmengine - INFO - Epoch(val) [22][ 50/509] eta: 0:00:43 time: 0.0946 data_time: 0.0021 memory: 5062 2023/05/15 07:20:45 - mmengine - INFO - Epoch(val) [22][100/509] eta: 0:00:43 time: 0.1192 data_time: 0.0020 memory: 991 2023/05/15 07:20:49 - mmengine - INFO - Epoch(val) [22][150/509] eta: 0:00:35 time: 0.0835 data_time: 0.0019 memory: 994 2023/05/15 07:20:53 - mmengine - INFO - Epoch(val) [22][200/509] eta: 0:00:29 time: 0.0839 data_time: 0.0019 memory: 979 2023/05/15 07:20:58 - mmengine - INFO - Epoch(val) [22][250/509] eta: 0:00:24 time: 0.0885 data_time: 0.0019 memory: 1004 2023/05/15 07:21:02 - mmengine - INFO - Epoch(val) [22][300/509] eta: 0:00:19 time: 0.0803 data_time: 0.0019 memory: 946 2023/05/15 07:21:06 - mmengine - INFO - Epoch(val) [22][350/509] eta: 0:00:14 time: 0.0794 data_time: 0.0019 memory: 970 2023/05/15 07:21:10 - mmengine - INFO - Epoch(val) [22][400/509] eta: 0:00:09 time: 0.0842 data_time: 0.0019 memory: 978 2023/05/15 07:21:14 - mmengine - INFO - Epoch(val) [22][450/509] eta: 0:00:05 time: 0.0845 data_time: 0.0019 memory: 991 2023/05/15 07:21:18 - mmengine - INFO - Epoch(val) [22][500/509] eta: 0:00:00 time: 0.0782 data_time: 0.0017 memory: 973 2023/05/15 07:21:58 - 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 | 0.9625 | 0.5289 | 0.7331 | 0.6721 | 0.6466 | 0.6594 | 0.8874 | 0.0448 | 0.9366 | 0.4510 | 0.8177 | 0.0085 | 0.9138 | 0.6301 | 0.8827 | 0.6549 | 0.7540 | 0.6444 | 0.5224 | 0.6500 | 0.9219 | 0.7351 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 07:21:58 - mmengine - INFO - Epoch(val) [22][509/509] car: 0.9625 bicycle: 0.5289 motorcycle: 0.7331 truck: 0.6721 bus: 0.6466 person: 0.6594 bicyclist: 0.8874 motorcyclist: 0.0448 road: 0.9366 parking: 0.4510 sidewalk: 0.8177 other-ground: 0.0085 building: 0.9138 fence: 0.6301 vegetation: 0.8827 trunck: 0.6549 terrian: 0.7540 pole: 0.6444 traffic-sign: 0.5224 miou: 0.6500 acc: 0.9219 acc_cls: 0.7351 data_time: 0.0018 time: 0.0799 2023/05/15 07:23:07 - mmengine - INFO - Epoch(train) [23][ 50/1196] lr: 8.0000e-03 eta: 6:36:53 time: 1.3771 data_time: 0.0041 memory: 4841 grad_norm: 0.0998 loss: 0.2036 loss_sem_seg: 0.2036 2023/05/15 07:24:15 - mmengine - INFO - Epoch(train) [23][ 100/1196] lr: 8.0000e-03 eta: 6:35:40 time: 1.3654 data_time: 0.0032 memory: 4743 grad_norm: 0.0959 loss: 0.2081 loss_sem_seg: 0.2081 2023/05/15 07:25:24 - mmengine - INFO - Epoch(train) [23][ 150/1196] lr: 8.0000e-03 eta: 6:34:27 time: 1.3893 data_time: 0.0032 memory: 4601 grad_norm: 0.1111 loss: 0.2033 loss_sem_seg: 0.2033 2023/05/15 07:26:34 - mmengine - INFO - Epoch(train) [23][ 200/1196] lr: 8.0000e-03 eta: 6:33:15 time: 1.3879 data_time: 0.0032 memory: 4674 grad_norm: 0.1214 loss: 0.2255 loss_sem_seg: 0.2255 2023/05/15 07:27:42 - mmengine - INFO - Epoch(train) [23][ 250/1196] lr: 8.0000e-03 eta: 6:32:01 time: 1.3686 data_time: 0.0033 memory: 5047 grad_norm: 0.1066 loss: 0.2213 loss_sem_seg: 0.2213 2023/05/15 07:29:12 - mmengine - INFO - Epoch(train) [23][ 300/1196] lr: 8.0000e-03 eta: 6:31:02 time: 1.8011 data_time: 0.0033 memory: 4645 grad_norm: 0.0990 loss: 0.2027 loss_sem_seg: 0.2027 2023/05/15 07:30:21 - mmengine - INFO - Epoch(train) [23][ 350/1196] lr: 8.0000e-03 eta: 6:29:49 time: 1.3701 data_time: 0.0032 memory: 4805 grad_norm: 0.0958 loss: 0.2203 loss_sem_seg: 0.2203 2023/05/15 07:31:30 - mmengine - INFO - Epoch(train) [23][ 400/1196] lr: 8.0000e-03 eta: 6:28:36 time: 1.3876 data_time: 0.0032 memory: 4985 grad_norm: 0.0922 loss: 0.1962 loss_sem_seg: 0.1962 2023/05/15 07:32:38 - mmengine - INFO - Epoch(train) [23][ 450/1196] lr: 8.0000e-03 eta: 6:27:23 time: 1.3650 data_time: 0.0033 memory: 4818 grad_norm: 0.0934 loss: 0.2118 loss_sem_seg: 0.2118 2023/05/15 07:33:47 - mmengine - INFO - Epoch(train) [23][ 500/1196] lr: 8.0000e-03 eta: 6:26:10 time: 1.3671 data_time: 0.0032 memory: 4702 grad_norm: 0.1022 loss: 0.2104 loss_sem_seg: 0.2104 2023/05/15 07:34:56 - mmengine - INFO - Epoch(train) [23][ 550/1196] lr: 8.0000e-03 eta: 6:24:57 time: 1.3798 data_time: 0.0033 memory: 4913 grad_norm: 0.1001 loss: 0.2141 loss_sem_seg: 0.2141 2023/05/15 07:36:05 - mmengine - INFO - Epoch(train) [23][ 600/1196] lr: 8.0000e-03 eta: 6:23:45 time: 1.3897 data_time: 0.0033 memory: 4997 grad_norm: 0.0993 loss: 0.2005 loss_sem_seg: 0.2005 2023/05/15 07:37:13 - mmengine - INFO - Epoch(train) [23][ 650/1196] lr: 8.0000e-03 eta: 6:22:31 time: 1.3598 data_time: 0.0033 memory: 4593 grad_norm: 0.0967 loss: 0.2091 loss_sem_seg: 0.2091 2023/05/15 07:38:06 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 07:38:22 - mmengine - INFO - Epoch(train) [23][ 700/1196] lr: 8.0000e-03 eta: 6:21:19 time: 1.3767 data_time: 0.0033 memory: 4778 grad_norm: 0.1117 loss: 0.2039 loss_sem_seg: 0.2039 2023/05/15 07:39:35 - mmengine - INFO - Epoch(train) [23][ 750/1196] lr: 8.0000e-03 eta: 6:20:08 time: 1.4493 data_time: 0.0032 memory: 4674 grad_norm: 0.0938 loss: 0.2124 loss_sem_seg: 0.2124 2023/05/15 07:41:02 - mmengine - INFO - Epoch(train) [23][ 800/1196] lr: 8.0000e-03 eta: 6:19:06 time: 1.7515 data_time: 0.0032 memory: 4546 grad_norm: 0.1076 loss: 0.2081 loss_sem_seg: 0.2081 2023/05/15 07:42:11 - mmengine - INFO - Epoch(train) [23][ 850/1196] lr: 8.0000e-03 eta: 6:17:53 time: 1.3696 data_time: 0.0033 memory: 4711 grad_norm: 0.0912 loss: 0.2121 loss_sem_seg: 0.2121 2023/05/15 07:43:19 - mmengine - INFO - Epoch(train) [23][ 900/1196] lr: 8.0000e-03 eta: 6:16:40 time: 1.3655 data_time: 0.0033 memory: 4911 grad_norm: 0.1299 loss: 0.2021 loss_sem_seg: 0.2021 2023/05/15 07:44:28 - mmengine - INFO - Epoch(train) [23][ 950/1196] lr: 8.0000e-03 eta: 6:15:28 time: 1.3842 data_time: 0.0033 memory: 4635 grad_norm: 0.1005 loss: 0.2096 loss_sem_seg: 0.2096 2023/05/15 07:45:38 - mmengine - INFO - Epoch(train) [23][1000/1196] lr: 8.0000e-03 eta: 6:14:15 time: 1.3955 data_time: 0.0033 memory: 4651 grad_norm: 0.1031 loss: 0.2137 loss_sem_seg: 0.2137 2023/05/15 07:46:48 - mmengine - INFO - Epoch(train) [23][1050/1196] lr: 8.0000e-03 eta: 6:13:03 time: 1.3956 data_time: 0.0033 memory: 4896 grad_norm: 0.0879 loss: 0.1937 loss_sem_seg: 0.1937 2023/05/15 07:47:56 - mmengine - INFO - Epoch(train) [23][1100/1196] lr: 8.0000e-03 eta: 6:11:50 time: 1.3567 data_time: 0.0033 memory: 4616 grad_norm: 0.0920 loss: 0.2161 loss_sem_seg: 0.2161 2023/05/15 07:49:03 - mmengine - INFO - Epoch(train) [23][1150/1196] lr: 8.0000e-03 eta: 6:10:37 time: 1.3550 data_time: 0.0033 memory: 5045 grad_norm: 0.0968 loss: 0.2167 loss_sem_seg: 0.2167 2023/05/15 07:50:06 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 07:50:06 - mmengine - INFO - Saving checkpoint at 23 epochs 2023/05/15 07:50:18 - mmengine - INFO - Epoch(val) [23][ 50/509] eta: 0:00:42 time: 0.0928 data_time: 0.0021 memory: 4949 2023/05/15 07:50:22 - mmengine - INFO - Epoch(val) [23][100/509] eta: 0:00:36 time: 0.0848 data_time: 0.0020 memory: 991 2023/05/15 07:50:26 - mmengine - INFO - Epoch(val) [23][150/509] eta: 0:00:31 time: 0.0827 data_time: 0.0019 memory: 994 2023/05/15 07:50:30 - mmengine - INFO - Epoch(val) [23][200/509] eta: 0:00:26 time: 0.0840 data_time: 0.0020 memory: 979 2023/05/15 07:50:35 - mmengine - INFO - Epoch(val) [23][250/509] eta: 0:00:22 time: 0.0885 data_time: 0.0020 memory: 1004 2023/05/15 07:50:38 - mmengine - INFO - Epoch(val) [23][300/509] eta: 0:00:17 time: 0.0767 data_time: 0.0019 memory: 946 2023/05/15 07:50:44 - mmengine - INFO - Epoch(val) [23][350/509] eta: 0:00:14 time: 0.1096 data_time: 0.0019 memory: 970 2023/05/15 07:50:48 - mmengine - INFO - Epoch(val) [23][400/509] eta: 0:00:09 time: 0.0874 data_time: 0.0019 memory: 978 2023/05/15 07:50:53 - mmengine - INFO - Epoch(val) [23][450/509] eta: 0:00:05 time: 0.0852 data_time: 0.0019 memory: 991 2023/05/15 07:50:57 - mmengine - INFO - Epoch(val) [23][500/509] eta: 0:00:00 time: 0.0788 data_time: 0.0018 memory: 973 2023/05/15 07:51:36 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9533 | 0.5358 | 0.7614 | 0.8654 | 0.4795 | 0.7305 | 0.8611 | 0.1281 | 0.9426 | 0.4878 | 0.8173 | 0.0257 | 0.9091 | 0.6496 | 0.8963 | 0.6887 | 0.7760 | 0.6522 | 0.4929 | 0.6660 | 0.9265 | 0.7400 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 07:51:36 - mmengine - INFO - Epoch(val) [23][509/509] car: 0.9533 bicycle: 0.5358 motorcycle: 0.7614 truck: 0.8654 bus: 0.4795 person: 0.7305 bicyclist: 0.8611 motorcyclist: 0.1281 road: 0.9426 parking: 0.4878 sidewalk: 0.8173 other-ground: 0.0257 building: 0.9091 fence: 0.6496 vegetation: 0.8963 trunck: 0.6887 terrian: 0.7760 pole: 0.6522 traffic-sign: 0.4929 miou: 0.6660 acc: 0.9265 acc_cls: 0.7400 data_time: 0.0018 time: 0.0802 2023/05/15 07:52:45 - mmengine - INFO - Epoch(train) [24][ 50/1196] lr: 8.0000e-03 eta: 6:08:17 time: 1.3762 data_time: 0.0042 memory: 4589 grad_norm: 0.1179 loss: 0.2067 loss_sem_seg: 0.2067 2023/05/15 07:53:53 - mmengine - INFO - Epoch(train) [24][ 100/1196] lr: 8.0000e-03 eta: 6:07:04 time: 1.3629 data_time: 0.0035 memory: 4471 grad_norm: 0.0955 loss: 0.2026 loss_sem_seg: 0.2026 2023/05/15 07:55:02 - mmengine - INFO - Epoch(train) [24][ 150/1196] lr: 8.0000e-03 eta: 6:05:51 time: 1.3727 data_time: 0.0036 memory: 5155 grad_norm: 0.1176 loss: 0.1950 loss_sem_seg: 0.1950 2023/05/15 07:56:10 - mmengine - INFO - Epoch(train) [24][ 200/1196] lr: 8.0000e-03 eta: 6:04:38 time: 1.3755 data_time: 0.0033 memory: 4805 grad_norm: 0.1087 loss: 0.2163 loss_sem_seg: 0.2163 2023/05/15 07:57:18 - mmengine - INFO - Epoch(train) [24][ 250/1196] lr: 8.0000e-03 eta: 6:03:25 time: 1.3605 data_time: 0.0033 memory: 4952 grad_norm: 0.1085 loss: 0.2089 loss_sem_seg: 0.2089 2023/05/15 07:58:26 - mmengine - INFO - Epoch(train) [24][ 300/1196] lr: 8.0000e-03 eta: 6:02:12 time: 1.3537 data_time: 0.0033 memory: 4555 grad_norm: 0.1038 loss: 0.2138 loss_sem_seg: 0.2138 2023/05/15 07:59:35 - mmengine - INFO - Epoch(train) [24][ 350/1196] lr: 8.0000e-03 eta: 6:00:59 time: 1.3806 data_time: 0.0033 memory: 4475 grad_norm: 0.0947 loss: 0.2080 loss_sem_seg: 0.2080 2023/05/15 08:00:45 - mmengine - INFO - Epoch(train) [24][ 400/1196] lr: 8.0000e-03 eta: 5:59:47 time: 1.3870 data_time: 0.0033 memory: 4521 grad_norm: 0.0964 loss: 0.2114 loss_sem_seg: 0.2114 2023/05/15 08:01:53 - mmengine - INFO - Epoch(train) [24][ 450/1196] lr: 8.0000e-03 eta: 5:58:34 time: 1.3687 data_time: 0.0032 memory: 4621 grad_norm: 0.1014 loss: 0.2061 loss_sem_seg: 0.2061 2023/05/15 08:02:51 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 08:03:02 - mmengine - INFO - Epoch(train) [24][ 500/1196] lr: 8.0000e-03 eta: 5:57:22 time: 1.3818 data_time: 0.0033 memory: 5090 grad_norm: 0.1004 loss: 0.2067 loss_sem_seg: 0.2067 2023/05/15 08:04:11 - mmengine - INFO - Epoch(train) [24][ 550/1196] lr: 8.0000e-03 eta: 5:56:09 time: 1.3769 data_time: 0.0032 memory: 5387 grad_norm: 0.1014 loss: 0.1992 loss_sem_seg: 0.1992 2023/05/15 08:05:19 - mmengine - INFO - Epoch(train) [24][ 600/1196] lr: 8.0000e-03 eta: 5:54:57 time: 1.3696 data_time: 0.0032 memory: 4726 grad_norm: 0.0939 loss: 0.1936 loss_sem_seg: 0.1936 2023/05/15 08:06:29 - mmengine - INFO - Epoch(train) [24][ 650/1196] lr: 8.0000e-03 eta: 5:53:44 time: 1.3823 data_time: 0.0032 memory: 4676 grad_norm: 0.1038 loss: 0.2072 loss_sem_seg: 0.2072 2023/05/15 08:07:36 - mmengine - INFO - Epoch(train) [24][ 700/1196] lr: 8.0000e-03 eta: 5:52:31 time: 1.3485 data_time: 0.0032 memory: 4807 grad_norm: 0.1027 loss: 0.2102 loss_sem_seg: 0.2102 2023/05/15 08:08:45 - mmengine - INFO - Epoch(train) [24][ 750/1196] lr: 8.0000e-03 eta: 5:51:19 time: 1.3899 data_time: 0.0032 memory: 4969 grad_norm: 0.1013 loss: 0.2051 loss_sem_seg: 0.2051 2023/05/15 08:09:56 - mmengine - INFO - Epoch(train) [24][ 800/1196] lr: 8.0000e-03 eta: 5:50:07 time: 1.4042 data_time: 0.0033 memory: 4855 grad_norm: 0.0938 loss: 0.1987 loss_sem_seg: 0.1987 2023/05/15 08:11:25 - mmengine - INFO - Epoch(train) [24][ 850/1196] lr: 8.0000e-03 eta: 5:49:05 time: 1.7784 data_time: 0.0033 memory: 4907 grad_norm: 0.0965 loss: 0.2075 loss_sem_seg: 0.2075 2023/05/15 08:12:33 - mmengine - INFO - Epoch(train) [24][ 900/1196] lr: 8.0000e-03 eta: 5:47:52 time: 1.3622 data_time: 0.0033 memory: 4844 grad_norm: 0.0963 loss: 0.2117 loss_sem_seg: 0.2117 2023/05/15 08:13:41 - mmengine - INFO - Epoch(train) [24][ 950/1196] lr: 8.0000e-03 eta: 5:46:40 time: 1.3718 data_time: 0.0032 memory: 4782 grad_norm: 0.0995 loss: 0.2044 loss_sem_seg: 0.2044 2023/05/15 08:14:50 - mmengine - INFO - Epoch(train) [24][1000/1196] lr: 8.0000e-03 eta: 5:45:27 time: 1.3711 data_time: 0.0032 memory: 4903 grad_norm: 0.1067 loss: 0.1953 loss_sem_seg: 0.1953 2023/05/15 08:16:00 - mmengine - INFO - Epoch(train) [24][1050/1196] lr: 8.0000e-03 eta: 5:44:15 time: 1.3941 data_time: 0.0035 memory: 4846 grad_norm: 0.0990 loss: 0.1917 loss_sem_seg: 0.1917 2023/05/15 08:17:08 - mmengine - INFO - Epoch(train) [24][1100/1196] lr: 8.0000e-03 eta: 5:43:02 time: 1.3612 data_time: 0.0034 memory: 5282 grad_norm: 0.1060 loss: 0.2042 loss_sem_seg: 0.2042 2023/05/15 08:18:16 - mmengine - INFO - Epoch(train) [24][1150/1196] lr: 8.0000e-03 eta: 5:41:49 time: 1.3654 data_time: 0.0032 memory: 4777 grad_norm: 0.0951 loss: 0.1888 loss_sem_seg: 0.1888 2023/05/15 08:19:19 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 08:19:19 - mmengine - INFO - Saving checkpoint at 24 epochs 2023/05/15 08:19:30 - mmengine - INFO - Epoch(val) [24][ 50/509] eta: 0:00:42 time: 0.0929 data_time: 0.0021 memory: 4481 2023/05/15 08:19:34 - mmengine - INFO - Epoch(val) [24][100/509] eta: 0:00:36 time: 0.0848 data_time: 0.0020 memory: 991 2023/05/15 08:19:38 - mmengine - INFO - Epoch(val) [24][150/509] eta: 0:00:31 time: 0.0831 data_time: 0.0020 memory: 994 2023/05/15 08:19:43 - mmengine - INFO - Epoch(val) [24][200/509] eta: 0:00:26 time: 0.0846 data_time: 0.0020 memory: 979 2023/05/15 08:19:47 - mmengine - INFO - Epoch(val) [24][250/509] eta: 0:00:22 time: 0.0888 data_time: 0.0020 memory: 1004 2023/05/15 08:19:51 - mmengine - INFO - Epoch(val) [24][300/509] eta: 0:00:17 time: 0.0768 data_time: 0.0019 memory: 946 2023/05/15 08:19:55 - mmengine - INFO - Epoch(val) [24][350/509] eta: 0:00:13 time: 0.0802 data_time: 0.0019 memory: 970 2023/05/15 08:19:59 - mmengine - INFO - Epoch(val) [24][400/509] eta: 0:00:09 time: 0.0852 data_time: 0.0020 memory: 978 2023/05/15 08:20:04 - mmengine - INFO - Epoch(val) [24][450/509] eta: 0:00:04 time: 0.0852 data_time: 0.0019 memory: 991 2023/05/15 08:20:07 - mmengine - INFO - Epoch(val) [24][500/509] eta: 0:00:00 time: 0.0785 data_time: 0.0018 memory: 973 2023/05/15 08:20:47 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9583 | 0.5331 | 0.7330 | 0.7520 | 0.5318 | 0.7302 | 0.8469 | 0.0111 | 0.9359 | 0.5358 | 0.8112 | 0.1172 | 0.8991 | 0.6003 | 0.8741 | 0.6915 | 0.7225 | 0.6455 | 0.5052 | 0.6545 | 0.9163 | 0.7328 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 08:20:47 - mmengine - INFO - Epoch(val) [24][509/509] car: 0.9583 bicycle: 0.5331 motorcycle: 0.7330 truck: 0.7520 bus: 0.5318 person: 0.7302 bicyclist: 0.8469 motorcyclist: 0.0111 road: 0.9359 parking: 0.5358 sidewalk: 0.8112 other-ground: 0.1172 building: 0.8991 fence: 0.6003 vegetation: 0.8741 trunck: 0.6915 terrian: 0.7225 pole: 0.6455 traffic-sign: 0.5052 miou: 0.6545 acc: 0.9163 acc_cls: 0.7328 data_time: 0.0018 time: 0.0802 2023/05/15 08:22:07 - mmengine - INFO - Epoch(train) [25][ 50/1196] lr: 8.0000e-04 eta: 5:39:36 time: 1.5969 data_time: 0.0039 memory: 4618 grad_norm: 0.0749 loss: 0.2049 loss_sem_seg: 0.2049 2023/05/15 08:23:24 - mmengine - INFO - Epoch(train) [25][ 100/1196] lr: 8.0000e-04 eta: 5:38:27 time: 1.5415 data_time: 0.0032 memory: 4746 grad_norm: 0.0609 loss: 0.1863 loss_sem_seg: 0.1863 2023/05/15 08:24:33 - mmengine - INFO - Epoch(train) [25][ 150/1196] lr: 8.0000e-04 eta: 5:37:15 time: 1.3785 data_time: 0.0032 memory: 5076 grad_norm: 0.0628 loss: 0.1833 loss_sem_seg: 0.1833 2023/05/15 08:25:43 - mmengine - INFO - Epoch(train) [25][ 200/1196] lr: 8.0000e-04 eta: 5:36:03 time: 1.4045 data_time: 0.0033 memory: 4509 grad_norm: 0.0652 loss: 0.1844 loss_sem_seg: 0.1844 2023/05/15 08:26:52 - mmengine - INFO - Epoch(train) [25][ 250/1196] lr: 8.0000e-04 eta: 5:34:50 time: 1.3637 data_time: 0.0033 memory: 4611 grad_norm: 0.0622 loss: 0.1808 loss_sem_seg: 0.1808 2023/05/15 08:27:54 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 08:28:00 - mmengine - INFO - Epoch(train) [25][ 300/1196] lr: 8.0000e-04 eta: 5:33:38 time: 1.3697 data_time: 0.0032 memory: 4679 grad_norm: 0.0594 loss: 0.1798 loss_sem_seg: 0.1798 2023/05/15 08:29:09 - mmengine - INFO - Epoch(train) [25][ 350/1196] lr: 8.0000e-04 eta: 5:32:26 time: 1.3819 data_time: 0.0032 memory: 4880 grad_norm: 0.0608 loss: 0.1718 loss_sem_seg: 0.1718 2023/05/15 08:30:18 - mmengine - INFO - Epoch(train) [25][ 400/1196] lr: 8.0000e-04 eta: 5:31:13 time: 1.3747 data_time: 0.0032 memory: 4535 grad_norm: 0.0588 loss: 0.1720 loss_sem_seg: 0.1720 2023/05/15 08:31:27 - mmengine - INFO - Epoch(train) [25][ 450/1196] lr: 8.0000e-04 eta: 5:30:01 time: 1.3905 data_time: 0.0032 memory: 4711 grad_norm: 0.0635 loss: 0.1703 loss_sem_seg: 0.1703 2023/05/15 08:32:37 - mmengine - INFO - Epoch(train) [25][ 500/1196] lr: 8.0000e-04 eta: 5:28:49 time: 1.3848 data_time: 0.0033 memory: 4576 grad_norm: 0.0632 loss: 0.1654 loss_sem_seg: 0.1654 2023/05/15 08:33:45 - mmengine - INFO - Epoch(train) [25][ 550/1196] lr: 8.0000e-04 eta: 5:27:37 time: 1.3708 data_time: 0.0033 memory: 4964 grad_norm: 0.0581 loss: 0.1671 loss_sem_seg: 0.1671 2023/05/15 08:34:54 - mmengine - INFO - Epoch(train) [25][ 600/1196] lr: 8.0000e-04 eta: 5:26:24 time: 1.3822 data_time: 0.0033 memory: 4837 grad_norm: 0.0625 loss: 0.1644 loss_sem_seg: 0.1644 2023/05/15 08:36:04 - mmengine - INFO - Epoch(train) [25][ 650/1196] lr: 8.0000e-04 eta: 5:25:12 time: 1.3942 data_time: 0.0032 memory: 4864 grad_norm: 0.0625 loss: 0.1526 loss_sem_seg: 0.1526 2023/05/15 08:37:11 - mmengine - INFO - Epoch(train) [25][ 700/1196] lr: 8.0000e-04 eta: 5:23:59 time: 1.3460 data_time: 0.0032 memory: 4618 grad_norm: 0.0639 loss: 0.1784 loss_sem_seg: 0.1784 2023/05/15 08:38:20 - mmengine - INFO - Epoch(train) [25][ 750/1196] lr: 8.0000e-04 eta: 5:22:47 time: 1.3817 data_time: 0.0032 memory: 4707 grad_norm: 0.0586 loss: 0.1693 loss_sem_seg: 0.1693 2023/05/15 08:39:31 - mmengine - INFO - Epoch(train) [25][ 800/1196] lr: 8.0000e-04 eta: 5:21:36 time: 1.4031 data_time: 0.0032 memory: 4766 grad_norm: 0.0605 loss: 0.1741 loss_sem_seg: 0.1741 2023/05/15 08:40:39 - mmengine - INFO - Epoch(train) [25][ 850/1196] lr: 8.0000e-04 eta: 5:20:23 time: 1.3746 data_time: 0.0033 memory: 4675 grad_norm: 0.0636 loss: 0.1733 loss_sem_seg: 0.1733 2023/05/15 08:41:50 - mmengine - INFO - Epoch(train) [25][ 900/1196] lr: 8.0000e-04 eta: 5:19:12 time: 1.4063 data_time: 0.0033 memory: 4940 grad_norm: 0.0614 loss: 0.1680 loss_sem_seg: 0.1680 2023/05/15 08:42:59 - mmengine - INFO - Epoch(train) [25][ 950/1196] lr: 8.0000e-04 eta: 5:18:00 time: 1.3862 data_time: 0.0033 memory: 4685 grad_norm: 0.0605 loss: 0.1788 loss_sem_seg: 0.1788 2023/05/15 08:44:07 - mmengine - INFO - Epoch(train) [25][1000/1196] lr: 8.0000e-04 eta: 5:16:47 time: 1.3624 data_time: 0.0032 memory: 4788 grad_norm: 0.0625 loss: 0.1645 loss_sem_seg: 0.1645 2023/05/15 08:45:16 - mmengine - INFO - Epoch(train) [25][1050/1196] lr: 8.0000e-04 eta: 5:15:35 time: 1.3704 data_time: 0.0034 memory: 4712 grad_norm: 0.0581 loss: 0.1678 loss_sem_seg: 0.1678 2023/05/15 08:46:24 - mmengine - INFO - Epoch(train) [25][1100/1196] lr: 8.0000e-04 eta: 5:14:22 time: 1.3696 data_time: 0.0033 memory: 4644 grad_norm: 0.0631 loss: 0.1624 loss_sem_seg: 0.1624 2023/05/15 08:47:32 - mmengine - INFO - Epoch(train) [25][1150/1196] lr: 8.0000e-04 eta: 5:13:10 time: 1.3634 data_time: 0.0033 memory: 4918 grad_norm: 0.0636 loss: 0.1719 loss_sem_seg: 0.1719 2023/05/15 08:48:35 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 08:48:35 - mmengine - INFO - Saving checkpoint at 25 epochs 2023/05/15 08:48:46 - mmengine - INFO - Epoch(val) [25][ 50/509] eta: 0:00:42 time: 0.0921 data_time: 0.0021 memory: 5018 2023/05/15 08:48:50 - mmengine - INFO - Epoch(val) [25][100/509] eta: 0:00:36 time: 0.0845 data_time: 0.0019 memory: 991 2023/05/15 08:48:54 - mmengine - INFO - Epoch(val) [25][150/509] eta: 0:00:31 time: 0.0826 data_time: 0.0020 memory: 994 2023/05/15 08:48:59 - mmengine - INFO - Epoch(val) [25][200/509] eta: 0:00:26 time: 0.0840 data_time: 0.0019 memory: 979 2023/05/15 08:49:03 - mmengine - INFO - Epoch(val) [25][250/509] eta: 0:00:22 time: 0.0884 data_time: 0.0019 memory: 1004 2023/05/15 08:49:07 - mmengine - INFO - Epoch(val) [25][300/509] eta: 0:00:17 time: 0.0767 data_time: 0.0019 memory: 946 2023/05/15 08:49:11 - mmengine - INFO - Epoch(val) [25][350/509] eta: 0:00:13 time: 0.0800 data_time: 0.0019 memory: 970 2023/05/15 08:49:15 - mmengine - INFO - Epoch(val) [25][400/509] eta: 0:00:09 time: 0.0846 data_time: 0.0019 memory: 978 2023/05/15 08:49:19 - mmengine - INFO - Epoch(val) [25][450/509] eta: 0:00:04 time: 0.0849 data_time: 0.0018 memory: 991 2023/05/15 08:49:23 - mmengine - INFO - Epoch(val) [25][500/509] eta: 0:00:00 time: 0.0784 data_time: 0.0017 memory: 973 2023/05/15 08:50:03 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9718 | 0.5700 | 0.7823 | 0.8726 | 0.7425 | 0.7802 | 0.8886 | 0.0828 | 0.9444 | 0.5213 | 0.8280 | 0.0462 | 0.9149 | 0.6562 | 0.8856 | 0.6838 | 0.7521 | 0.6571 | 0.5176 | 0.6894 | 0.9261 | 0.7610 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 08:50:03 - mmengine - INFO - Epoch(val) [25][509/509] car: 0.9718 bicycle: 0.5700 motorcycle: 0.7823 truck: 0.8726 bus: 0.7425 person: 0.7802 bicyclist: 0.8886 motorcyclist: 0.0828 road: 0.9444 parking: 0.5213 sidewalk: 0.8280 other-ground: 0.0462 building: 0.9149 fence: 0.6562 vegetation: 0.8856 trunck: 0.6838 terrian: 0.7521 pole: 0.6571 traffic-sign: 0.5176 miou: 0.6894 acc: 0.9261 acc_cls: 0.7610 data_time: 0.0017 time: 0.0802 2023/05/15 08:51:13 - mmengine - INFO - Epoch(train) [26][ 50/1196] lr: 8.0000e-04 eta: 5:10:51 time: 1.3999 data_time: 0.0040 memory: 4586 grad_norm: 0.0582 loss: 0.1748 loss_sem_seg: 0.1748 2023/05/15 08:52:34 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 08:52:34 - mmengine - INFO - Epoch(train) [26][ 100/1196] lr: 8.0000e-04 eta: 5:09:44 time: 1.6139 data_time: 0.0035 memory: 4720 grad_norm: 0.0654 loss: 0.1710 loss_sem_seg: 0.1710 2023/05/15 08:53:52 - mmengine - INFO - Epoch(train) [26][ 150/1196] lr: 8.0000e-04 eta: 5:08:36 time: 1.5668 data_time: 0.0033 memory: 4715 grad_norm: 0.0621 loss: 0.1711 loss_sem_seg: 0.1711 2023/05/15 08:55:01 - mmengine - INFO - Epoch(train) [26][ 200/1196] lr: 8.0000e-04 eta: 5:07:24 time: 1.3833 data_time: 0.0032 memory: 5093 grad_norm: 0.0591 loss: 0.1550 loss_sem_seg: 0.1550 2023/05/15 08:56:10 - mmengine - INFO - Epoch(train) [26][ 250/1196] lr: 8.0000e-04 eta: 5:06:12 time: 1.3848 data_time: 0.0032 memory: 4529 grad_norm: 0.0620 loss: 0.1829 loss_sem_seg: 0.1829 2023/05/15 08:57:20 - mmengine - INFO - Epoch(train) [26][ 300/1196] lr: 8.0000e-04 eta: 5:05:00 time: 1.3932 data_time: 0.0032 memory: 4747 grad_norm: 0.0606 loss: 0.1704 loss_sem_seg: 0.1704 2023/05/15 08:58:29 - mmengine - INFO - Epoch(train) [26][ 350/1196] lr: 8.0000e-04 eta: 5:03:48 time: 1.3792 data_time: 0.0032 memory: 4973 grad_norm: 0.0592 loss: 0.1754 loss_sem_seg: 0.1754 2023/05/15 08:59:37 - mmengine - INFO - Epoch(train) [26][ 400/1196] lr: 8.0000e-04 eta: 5:02:36 time: 1.3680 data_time: 0.0032 memory: 5133 grad_norm: 0.0586 loss: 0.1647 loss_sem_seg: 0.1647 2023/05/15 09:00:46 - mmengine - INFO - Epoch(train) [26][ 450/1196] lr: 8.0000e-04 eta: 5:01:24 time: 1.3661 data_time: 0.0033 memory: 4517 grad_norm: 0.0616 loss: 0.1760 loss_sem_seg: 0.1760 2023/05/15 09:01:55 - mmengine - INFO - Epoch(train) [26][ 500/1196] lr: 8.0000e-04 eta: 5:00:12 time: 1.3870 data_time: 0.0033 memory: 4570 grad_norm: 0.0582 loss: 0.1652 loss_sem_seg: 0.1652 2023/05/15 09:03:03 - mmengine - INFO - Epoch(train) [26][ 550/1196] lr: 8.0000e-04 eta: 4:58:59 time: 1.3678 data_time: 0.0033 memory: 4728 grad_norm: 0.0596 loss: 0.1603 loss_sem_seg: 0.1603 2023/05/15 09:04:29 - mmengine - INFO - Epoch(train) [26][ 600/1196] lr: 8.0000e-04 eta: 4:57:54 time: 1.7038 data_time: 0.0033 memory: 4689 grad_norm: 0.0583 loss: 0.1611 loss_sem_seg: 0.1611 2023/05/15 09:05:43 - mmengine - INFO - Epoch(train) [26][ 650/1196] lr: 8.0000e-04 eta: 4:56:44 time: 1.4938 data_time: 0.0033 memory: 4650 grad_norm: 0.0604 loss: 0.1625 loss_sem_seg: 0.1625 2023/05/15 09:06:53 - mmengine - INFO - Epoch(train) [26][ 700/1196] lr: 8.0000e-04 eta: 4:55:32 time: 1.3882 data_time: 0.0033 memory: 4736 grad_norm: 0.0577 loss: 0.1550 loss_sem_seg: 0.1550 2023/05/15 09:08:00 - mmengine - INFO - Epoch(train) [26][ 750/1196] lr: 8.0000e-04 eta: 4:54:20 time: 1.3509 data_time: 0.0033 memory: 4731 grad_norm: 0.0608 loss: 0.1679 loss_sem_seg: 0.1679 2023/05/15 09:09:10 - mmengine - INFO - Epoch(train) [26][ 800/1196] lr: 8.0000e-04 eta: 4:53:08 time: 1.3902 data_time: 0.0033 memory: 4679 grad_norm: 0.0588 loss: 0.1665 loss_sem_seg: 0.1665 2023/05/15 09:10:20 - mmengine - INFO - Epoch(train) [26][ 850/1196] lr: 8.0000e-04 eta: 4:51:56 time: 1.3987 data_time: 0.0033 memory: 4970 grad_norm: 0.0590 loss: 0.1662 loss_sem_seg: 0.1662 2023/05/15 09:11:29 - mmengine - INFO - Epoch(train) [26][ 900/1196] lr: 8.0000e-04 eta: 4:50:44 time: 1.3771 data_time: 0.0035 memory: 4871 grad_norm: 0.0629 loss: 0.1648 loss_sem_seg: 0.1648 2023/05/15 09:12:38 - mmengine - INFO - Epoch(train) [26][ 950/1196] lr: 8.0000e-04 eta: 4:49:32 time: 1.3967 data_time: 0.0035 memory: 4780 grad_norm: 0.0593 loss: 0.1724 loss_sem_seg: 0.1724 2023/05/15 09:13:47 - mmengine - INFO - Epoch(train) [26][1000/1196] lr: 8.0000e-04 eta: 4:48:20 time: 1.3626 data_time: 0.0035 memory: 4800 grad_norm: 0.0596 loss: 0.1547 loss_sem_seg: 0.1547 2023/05/15 09:14:56 - mmengine - INFO - Epoch(train) [26][1050/1196] lr: 8.0000e-04 eta: 4:47:08 time: 1.3798 data_time: 0.0035 memory: 4755 grad_norm: 0.0614 loss: 0.1655 loss_sem_seg: 0.1655 2023/05/15 09:16:05 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 09:16:05 - mmengine - INFO - Epoch(train) [26][1100/1196] lr: 8.0000e-04 eta: 4:45:56 time: 1.3932 data_time: 0.0035 memory: 4610 grad_norm: 0.0654 loss: 0.1735 loss_sem_seg: 0.1735 2023/05/15 09:17:13 - mmengine - INFO - Epoch(train) [26][1150/1196] lr: 8.0000e-04 eta: 4:44:44 time: 1.3598 data_time: 0.0033 memory: 4844 grad_norm: 0.0609 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/15 09:18:16 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 09:18:16 - mmengine - INFO - Saving checkpoint at 26 epochs 2023/05/15 09:18:27 - mmengine - INFO - Epoch(val) [26][ 50/509] eta: 0:00:42 time: 0.0922 data_time: 0.0020 memory: 4761 2023/05/15 09:18:32 - mmengine - INFO - Epoch(val) [26][100/509] eta: 0:00:36 time: 0.0851 data_time: 0.0020 memory: 991 2023/05/15 09:18:36 - mmengine - INFO - Epoch(val) [26][150/509] eta: 0:00:31 time: 0.0828 data_time: 0.0019 memory: 994 2023/05/15 09:18:40 - mmengine - INFO - Epoch(val) [26][200/509] eta: 0:00:26 time: 0.0842 data_time: 0.0019 memory: 979 2023/05/15 09:18:44 - mmengine - INFO - Epoch(val) [26][250/509] eta: 0:00:22 time: 0.0890 data_time: 0.0019 memory: 1004 2023/05/15 09:18:48 - mmengine - INFO - Epoch(val) [26][300/509] eta: 0:00:17 time: 0.0770 data_time: 0.0019 memory: 946 2023/05/15 09:18:52 - mmengine - INFO - Epoch(val) [26][350/509] eta: 0:00:13 time: 0.0801 data_time: 0.0019 memory: 970 2023/05/15 09:18:57 - mmengine - INFO - Epoch(val) [26][400/509] eta: 0:00:09 time: 0.0854 data_time: 0.0020 memory: 978 2023/05/15 09:19:01 - mmengine - INFO - Epoch(val) [26][450/509] eta: 0:00:04 time: 0.0853 data_time: 0.0019 memory: 991 2023/05/15 09:19:05 - mmengine - INFO - Epoch(val) [26][500/509] eta: 0:00:00 time: 0.0787 data_time: 0.0017 memory: 973 2023/05/15 09:19:44 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9648 | 0.5606 | 0.7706 | 0.8885 | 0.6441 | 0.7882 | 0.9034 | 0.1012 | 0.9459 | 0.4814 | 0.8252 | 0.0285 | 0.9201 | 0.6744 | 0.8819 | 0.6951 | 0.7432 | 0.6563 | 0.5090 | 0.6833 | 0.9246 | 0.7515 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 09:19:44 - mmengine - INFO - Epoch(val) [26][509/509] car: 0.9648 bicycle: 0.5606 motorcycle: 0.7706 truck: 0.8885 bus: 0.6441 person: 0.7882 bicyclist: 0.9034 motorcyclist: 0.1012 road: 0.9459 parking: 0.4814 sidewalk: 0.8252 other-ground: 0.0285 building: 0.9201 fence: 0.6744 vegetation: 0.8819 trunck: 0.6951 terrian: 0.7432 pole: 0.6563 traffic-sign: 0.5090 miou: 0.6833 acc: 0.9246 acc_cls: 0.7515 data_time: 0.0018 time: 0.0806 2023/05/15 09:20:55 - mmengine - INFO - Epoch(train) [27][ 50/1196] lr: 8.0000e-04 eta: 4:42:26 time: 1.4057 data_time: 0.0042 memory: 4347 grad_norm: 0.0628 loss: 0.1695 loss_sem_seg: 0.1695 2023/05/15 09:22:04 - mmengine - INFO - Epoch(train) [27][ 100/1196] lr: 8.0000e-04 eta: 4:41:14 time: 1.3946 data_time: 0.0035 memory: 4809 grad_norm: 0.0561 loss: 0.1521 loss_sem_seg: 0.1521 2023/05/15 09:23:14 - mmengine - INFO - Epoch(train) [27][ 150/1196] lr: 8.0000e-04 eta: 4:40:02 time: 1.3845 data_time: 0.0036 memory: 5224 grad_norm: 0.0625 loss: 0.1690 loss_sem_seg: 0.1690 2023/05/15 09:24:23 - mmengine - INFO - Epoch(train) [27][ 200/1196] lr: 8.0000e-04 eta: 4:38:50 time: 1.3832 data_time: 0.0035 memory: 4786 grad_norm: 0.0574 loss: 0.1671 loss_sem_seg: 0.1671 2023/05/15 09:25:32 - mmengine - INFO - Epoch(train) [27][ 250/1196] lr: 8.0000e-04 eta: 4:37:39 time: 1.3808 data_time: 0.0036 memory: 4627 grad_norm: 0.0599 loss: 0.1729 loss_sem_seg: 0.1729 2023/05/15 09:26:42 - mmengine - INFO - Epoch(train) [27][ 300/1196] lr: 8.0000e-04 eta: 4:36:27 time: 1.4050 data_time: 0.0035 memory: 4824 grad_norm: 0.0608 loss: 0.1641 loss_sem_seg: 0.1641 2023/05/15 09:27:52 - mmengine - INFO - Epoch(train) [27][ 350/1196] lr: 8.0000e-04 eta: 4:35:15 time: 1.3876 data_time: 0.0033 memory: 4693 grad_norm: 0.0601 loss: 0.1760 loss_sem_seg: 0.1760 2023/05/15 09:29:01 - mmengine - INFO - Epoch(train) [27][ 400/1196] lr: 8.0000e-04 eta: 4:34:03 time: 1.3819 data_time: 0.0033 memory: 4974 grad_norm: 0.0642 loss: 0.1600 loss_sem_seg: 0.1600 2023/05/15 09:30:09 - mmengine - INFO - Epoch(train) [27][ 450/1196] lr: 8.0000e-04 eta: 4:32:51 time: 1.3734 data_time: 0.0033 memory: 4547 grad_norm: 0.0594 loss: 0.1566 loss_sem_seg: 0.1566 2023/05/15 09:31:19 - mmengine - INFO - Epoch(train) [27][ 500/1196] lr: 8.0000e-04 eta: 4:31:40 time: 1.3875 data_time: 0.0033 memory: 4669 grad_norm: 0.0602 loss: 0.1565 loss_sem_seg: 0.1565 2023/05/15 09:32:28 - mmengine - INFO - Epoch(train) [27][ 550/1196] lr: 8.0000e-04 eta: 4:30:28 time: 1.3789 data_time: 0.0033 memory: 4948 grad_norm: 0.0587 loss: 0.1691 loss_sem_seg: 0.1691 2023/05/15 09:33:37 - mmengine - INFO - Epoch(train) [27][ 600/1196] lr: 8.0000e-04 eta: 4:29:16 time: 1.3930 data_time: 0.0033 memory: 4631 grad_norm: 0.0575 loss: 0.1674 loss_sem_seg: 0.1674 2023/05/15 09:35:03 - mmengine - INFO - Epoch(train) [27][ 650/1196] lr: 8.0000e-04 eta: 4:28:10 time: 1.7125 data_time: 0.0033 memory: 4821 grad_norm: 0.0623 loss: 0.1718 loss_sem_seg: 0.1718 2023/05/15 09:36:18 - mmengine - INFO - Epoch(train) [27][ 700/1196] lr: 8.0000e-04 eta: 4:27:01 time: 1.5103 data_time: 0.0032 memory: 4890 grad_norm: 0.0616 loss: 0.1669 loss_sem_seg: 0.1669 2023/05/15 09:37:27 - mmengine - INFO - Epoch(train) [27][ 750/1196] lr: 8.0000e-04 eta: 4:25:49 time: 1.3728 data_time: 0.0033 memory: 4976 grad_norm: 0.0621 loss: 0.1574 loss_sem_seg: 0.1574 2023/05/15 09:38:35 - mmengine - INFO - Epoch(train) [27][ 800/1196] lr: 8.0000e-04 eta: 4:24:36 time: 1.3607 data_time: 0.0033 memory: 4772 grad_norm: 0.0616 loss: 0.1594 loss_sem_seg: 0.1594 2023/05/15 09:39:43 - mmengine - INFO - Epoch(train) [27][ 850/1196] lr: 8.0000e-04 eta: 4:23:24 time: 1.3533 data_time: 0.0033 memory: 4752 grad_norm: 0.0582 loss: 0.1739 loss_sem_seg: 0.1739 2023/05/15 09:40:51 - mmengine - INFO - Epoch(train) [27][ 900/1196] lr: 8.0000e-04 eta: 4:22:12 time: 1.3735 data_time: 0.0034 memory: 4734 grad_norm: 0.0606 loss: 0.1533 loss_sem_seg: 0.1533 2023/05/15 09:40:57 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 09:42:00 - mmengine - INFO - Epoch(train) [27][ 950/1196] lr: 8.0000e-04 eta: 4:21:00 time: 1.3660 data_time: 0.0033 memory: 4941 grad_norm: 0.0604 loss: 0.1690 loss_sem_seg: 0.1690 2023/05/15 09:43:07 - mmengine - INFO - Epoch(train) [27][1000/1196] lr: 8.0000e-04 eta: 4:19:47 time: 1.3431 data_time: 0.0033 memory: 4817 grad_norm: 0.0610 loss: 0.1685 loss_sem_seg: 0.1685 2023/05/15 09:44:15 - mmengine - INFO - Epoch(train) [27][1050/1196] lr: 8.0000e-04 eta: 4:18:35 time: 1.3614 data_time: 0.0032 memory: 5240 grad_norm: 0.0554 loss: 0.1635 loss_sem_seg: 0.1635 2023/05/15 09:45:23 - mmengine - INFO - Epoch(train) [27][1100/1196] lr: 8.0000e-04 eta: 4:17:23 time: 1.3597 data_time: 0.0032 memory: 4669 grad_norm: 0.0610 loss: 0.1652 loss_sem_seg: 0.1652 2023/05/15 09:46:54 - mmengine - INFO - Epoch(train) [27][1150/1196] lr: 8.0000e-04 eta: 4:16:19 time: 1.8268 data_time: 0.0033 memory: 4806 grad_norm: 0.0651 loss: 0.1690 loss_sem_seg: 0.1690 2023/05/15 09:47:58 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 09:47:58 - mmengine - INFO - Saving checkpoint at 27 epochs 2023/05/15 09:48:09 - mmengine - INFO - Epoch(val) [27][ 50/509] eta: 0:00:42 time: 0.0923 data_time: 0.0021 memory: 4918 2023/05/15 09:48:14 - mmengine - INFO - Epoch(val) [27][100/509] eta: 0:00:36 time: 0.0846 data_time: 0.0020 memory: 991 2023/05/15 09:48:18 - mmengine - INFO - Epoch(val) [27][150/509] eta: 0:00:31 time: 0.0827 data_time: 0.0019 memory: 994 2023/05/15 09:48:22 - mmengine - INFO - Epoch(val) [27][200/509] eta: 0:00:26 time: 0.0843 data_time: 0.0019 memory: 979 2023/05/15 09:48:26 - mmengine - INFO - Epoch(val) [27][250/509] eta: 0:00:22 time: 0.0884 data_time: 0.0019 memory: 1004 2023/05/15 09:48:30 - mmengine - INFO - Epoch(val) [27][300/509] eta: 0:00:17 time: 0.0769 data_time: 0.0019 memory: 946 2023/05/15 09:48:34 - mmengine - INFO - Epoch(val) [27][350/509] eta: 0:00:13 time: 0.0796 data_time: 0.0019 memory: 970 2023/05/15 09:48:38 - mmengine - INFO - Epoch(val) [27][400/509] eta: 0:00:09 time: 0.0849 data_time: 0.0019 memory: 978 2023/05/15 09:48:43 - mmengine - INFO - Epoch(val) [27][450/509] eta: 0:00:04 time: 0.0854 data_time: 0.0019 memory: 991 2023/05/15 09:48:47 - mmengine - INFO - Epoch(val) [27][500/509] eta: 0:00:00 time: 0.0786 data_time: 0.0018 memory: 973 2023/05/15 09:49:27 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9564 | 0.5589 | 0.7768 | 0.8950 | 0.5411 | 0.7808 | 0.8858 | 0.1328 | 0.9459 | 0.4719 | 0.8255 | 0.0374 | 0.9179 | 0.6629 | 0.8814 | 0.6846 | 0.7423 | 0.6609 | 0.5184 | 0.6777 | 0.9235 | 0.7440 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 09:49:27 - mmengine - INFO - Epoch(val) [27][509/509] car: 0.9564 bicycle: 0.5589 motorcycle: 0.7768 truck: 0.8950 bus: 0.5411 person: 0.7808 bicyclist: 0.8858 motorcyclist: 0.1328 road: 0.9459 parking: 0.4719 sidewalk: 0.8255 other-ground: 0.0374 building: 0.9179 fence: 0.6629 vegetation: 0.8814 trunck: 0.6846 terrian: 0.7423 pole: 0.6609 traffic-sign: 0.5184 miou: 0.6777 acc: 0.9235 acc_cls: 0.7440 data_time: 0.0018 time: 0.0805 2023/05/15 09:50:37 - mmengine - INFO - Epoch(train) [28][ 50/1196] lr: 8.0000e-04 eta: 4:14:01 time: 1.3970 data_time: 0.0045 memory: 4799 grad_norm: 0.0578 loss: 0.1557 loss_sem_seg: 0.1557 2023/05/15 09:51:47 - mmengine - INFO - Epoch(train) [28][ 100/1196] lr: 8.0000e-04 eta: 4:12:50 time: 1.4012 data_time: 0.0032 memory: 4793 grad_norm: 0.0623 loss: 0.1618 loss_sem_seg: 0.1618 2023/05/15 09:52:55 - mmengine - INFO - Epoch(train) [28][ 150/1196] lr: 8.0000e-04 eta: 4:11:38 time: 1.3647 data_time: 0.0032 memory: 4713 grad_norm: 0.0592 loss: 0.1497 loss_sem_seg: 0.1497 2023/05/15 09:54:04 - mmengine - INFO - Epoch(train) [28][ 200/1196] lr: 8.0000e-04 eta: 4:10:26 time: 1.3790 data_time: 0.0032 memory: 4710 grad_norm: 0.0596 loss: 0.1690 loss_sem_seg: 0.1690 2023/05/15 09:55:12 - mmengine - INFO - Epoch(train) [28][ 250/1196] lr: 8.0000e-04 eta: 4:09:14 time: 1.3667 data_time: 0.0032 memory: 4747 grad_norm: 0.0616 loss: 0.1510 loss_sem_seg: 0.1510 2023/05/15 09:56:22 - mmengine - INFO - Epoch(train) [28][ 300/1196] lr: 8.0000e-04 eta: 4:08:02 time: 1.3891 data_time: 0.0032 memory: 4602 grad_norm: 0.0620 loss: 0.1580 loss_sem_seg: 0.1580 2023/05/15 09:57:31 - mmengine - INFO - Epoch(train) [28][ 350/1196] lr: 8.0000e-04 eta: 4:06:50 time: 1.3822 data_time: 0.0032 memory: 4359 grad_norm: 0.0603 loss: 0.1634 loss_sem_seg: 0.1634 2023/05/15 09:58:39 - mmengine - INFO - Epoch(train) [28][ 400/1196] lr: 8.0000e-04 eta: 4:05:38 time: 1.3586 data_time: 0.0032 memory: 5006 grad_norm: 0.0595 loss: 0.1587 loss_sem_seg: 0.1587 2023/05/15 09:59:47 - mmengine - INFO - Epoch(train) [28][ 450/1196] lr: 8.0000e-04 eta: 4:04:26 time: 1.3679 data_time: 0.0032 memory: 4924 grad_norm: 0.0635 loss: 0.1641 loss_sem_seg: 0.1641 2023/05/15 10:00:57 - mmengine - INFO - Epoch(train) [28][ 500/1196] lr: 8.0000e-04 eta: 4:03:15 time: 1.3988 data_time: 0.0032 memory: 4617 grad_norm: 0.0637 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/15 10:02:07 - mmengine - INFO - Epoch(train) [28][ 550/1196] lr: 8.0000e-04 eta: 4:02:03 time: 1.3905 data_time: 0.0032 memory: 4964 grad_norm: 0.0579 loss: 0.1446 loss_sem_seg: 0.1446 2023/05/15 10:03:16 - mmengine - INFO - Epoch(train) [28][ 600/1196] lr: 8.0000e-04 eta: 4:00:52 time: 1.3855 data_time: 0.0032 memory: 4651 grad_norm: 0.0667 loss: 0.1539 loss_sem_seg: 0.1539 2023/05/15 10:04:26 - mmengine - INFO - Epoch(train) [28][ 650/1196] lr: 8.0000e-04 eta: 3:59:40 time: 1.3990 data_time: 0.0032 memory: 4475 grad_norm: 0.0634 loss: 0.1541 loss_sem_seg: 0.1541 2023/05/15 10:05:35 - mmengine - INFO - Epoch(train) [28][ 700/1196] lr: 8.0000e-04 eta: 3:58:28 time: 1.3763 data_time: 0.0032 memory: 4816 grad_norm: 0.0621 loss: 0.1578 loss_sem_seg: 0.1578 2023/05/15 10:05:46 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 10:06:44 - mmengine - INFO - Epoch(train) [28][ 750/1196] lr: 8.0000e-04 eta: 3:57:17 time: 1.3913 data_time: 0.0032 memory: 4301 grad_norm: 0.0615 loss: 0.1669 loss_sem_seg: 0.1669 2023/05/15 10:07:53 - mmengine - INFO - Epoch(train) [28][ 800/1196] lr: 8.0000e-04 eta: 3:56:05 time: 1.3867 data_time: 0.0031 memory: 4946 grad_norm: 0.0631 loss: 0.1578 loss_sem_seg: 0.1578 2023/05/15 10:09:03 - mmengine - INFO - Epoch(train) [28][ 850/1196] lr: 8.0000e-04 eta: 3:54:54 time: 1.3893 data_time: 0.0032 memory: 4824 grad_norm: 0.0587 loss: 0.1620 loss_sem_seg: 0.1620 2023/05/15 10:10:11 - mmengine - INFO - Epoch(train) [28][ 900/1196] lr: 8.0000e-04 eta: 3:53:42 time: 1.3662 data_time: 0.0032 memory: 4682 grad_norm: 0.0572 loss: 0.1637 loss_sem_seg: 0.1637 2023/05/15 10:11:20 - mmengine - INFO - Epoch(train) [28][ 950/1196] lr: 8.0000e-04 eta: 3:52:30 time: 1.3691 data_time: 0.0032 memory: 4537 grad_norm: 0.0602 loss: 0.1527 loss_sem_seg: 0.1527 2023/05/15 10:12:28 - mmengine - INFO - Epoch(train) [28][1000/1196] lr: 8.0000e-04 eta: 3:51:18 time: 1.3633 data_time: 0.0032 memory: 4711 grad_norm: 0.0571 loss: 0.1611 loss_sem_seg: 0.1611 2023/05/15 10:13:36 - mmengine - INFO - Epoch(train) [28][1050/1196] lr: 8.0000e-04 eta: 3:50:06 time: 1.3629 data_time: 0.0032 memory: 4996 grad_norm: 0.0603 loss: 0.1614 loss_sem_seg: 0.1614 2023/05/15 10:14:44 - mmengine - INFO - Epoch(train) [28][1100/1196] lr: 8.0000e-04 eta: 3:48:54 time: 1.3495 data_time: 0.0032 memory: 4719 grad_norm: 0.0665 loss: 0.1586 loss_sem_seg: 0.1586 2023/05/15 10:15:53 - mmengine - INFO - Epoch(train) [28][1150/1196] lr: 8.0000e-04 eta: 3:47:43 time: 1.3927 data_time: 0.0033 memory: 4545 grad_norm: 0.0641 loss: 0.1637 loss_sem_seg: 0.1637 2023/05/15 10:17:17 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 10:17:17 - mmengine - INFO - Saving checkpoint at 28 epochs 2023/05/15 10:17:28 - mmengine - INFO - Epoch(val) [28][ 50/509] eta: 0:00:42 time: 0.0924 data_time: 0.0021 memory: 4746 2023/05/15 10:17:32 - mmengine - INFO - Epoch(val) [28][100/509] eta: 0:00:36 time: 0.0846 data_time: 0.0020 memory: 991 2023/05/15 10:17:36 - mmengine - INFO - Epoch(val) [28][150/509] eta: 0:00:31 time: 0.0829 data_time: 0.0019 memory: 994 2023/05/15 10:17:41 - mmengine - INFO - Epoch(val) [28][200/509] eta: 0:00:26 time: 0.0841 data_time: 0.0019 memory: 979 2023/05/15 10:17:45 - mmengine - INFO - Epoch(val) [28][250/509] eta: 0:00:22 time: 0.0890 data_time: 0.0020 memory: 1004 2023/05/15 10:17:49 - mmengine - INFO - Epoch(val) [28][300/509] eta: 0:00:17 time: 0.0771 data_time: 0.0019 memory: 946 2023/05/15 10:17:53 - mmengine - INFO - Epoch(val) [28][350/509] eta: 0:00:13 time: 0.0801 data_time: 0.0019 memory: 970 2023/05/15 10:17:57 - mmengine - INFO - Epoch(val) [28][400/509] eta: 0:00:09 time: 0.0852 data_time: 0.0019 memory: 978 2023/05/15 10:18:02 - mmengine - INFO - Epoch(val) [28][450/509] eta: 0:00:04 time: 0.0849 data_time: 0.0018 memory: 991 2023/05/15 10:18:05 - mmengine - INFO - Epoch(val) [28][500/509] eta: 0:00:00 time: 0.0788 data_time: 0.0018 memory: 973 2023/05/15 10:18:46 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9647 | 0.5617 | 0.7882 | 0.8706 | 0.6420 | 0.7909 | 0.9011 | 0.0908 | 0.9473 | 0.5010 | 0.8274 | 0.0337 | 0.9181 | 0.6689 | 0.8830 | 0.6989 | 0.7444 | 0.6584 | 0.5113 | 0.6843 | 0.9251 | 0.7526 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 10:18:46 - mmengine - INFO - Epoch(val) [28][509/509] car: 0.9647 bicycle: 0.5617 motorcycle: 0.7882 truck: 0.8706 bus: 0.6420 person: 0.7909 bicyclist: 0.9011 motorcyclist: 0.0908 road: 0.9473 parking: 0.5010 sidewalk: 0.8274 other-ground: 0.0337 building: 0.9181 fence: 0.6689 vegetation: 0.8830 trunck: 0.6989 terrian: 0.7444 pole: 0.6584 traffic-sign: 0.5113 miou: 0.6843 acc: 0.9251 acc_cls: 0.7526 data_time: 0.0018 time: 0.0805 2023/05/15 10:19:55 - mmengine - INFO - Epoch(train) [29][ 50/1196] lr: 8.0000e-04 eta: 3:45:31 time: 1.3976 data_time: 0.0039 memory: 4604 grad_norm: 0.0649 loss: 0.1517 loss_sem_seg: 0.1517 2023/05/15 10:21:05 - mmengine - INFO - Epoch(train) [29][ 100/1196] lr: 8.0000e-04 eta: 3:44:19 time: 1.3883 data_time: 0.0033 memory: 5162 grad_norm: 0.0652 loss: 0.1506 loss_sem_seg: 0.1506 2023/05/15 10:22:14 - mmengine - INFO - Epoch(train) [29][ 150/1196] lr: 8.0000e-04 eta: 3:43:08 time: 1.3746 data_time: 0.0033 memory: 4788 grad_norm: 0.0628 loss: 0.1550 loss_sem_seg: 0.1550 2023/05/15 10:23:23 - mmengine - INFO - Epoch(train) [29][ 200/1196] lr: 8.0000e-04 eta: 3:41:56 time: 1.3847 data_time: 0.0034 memory: 4731 grad_norm: 0.0603 loss: 0.1598 loss_sem_seg: 0.1598 2023/05/15 10:24:31 - mmengine - INFO - Epoch(train) [29][ 250/1196] lr: 8.0000e-04 eta: 3:40:44 time: 1.3529 data_time: 0.0035 memory: 4872 grad_norm: 0.0593 loss: 0.1497 loss_sem_seg: 0.1497 2023/05/15 10:25:39 - mmengine - INFO - Epoch(train) [29][ 300/1196] lr: 8.0000e-04 eta: 3:39:32 time: 1.3693 data_time: 0.0032 memory: 4552 grad_norm: 0.0646 loss: 0.1621 loss_sem_seg: 0.1621 2023/05/15 10:26:48 - mmengine - INFO - Epoch(train) [29][ 350/1196] lr: 8.0000e-04 eta: 3:38:21 time: 1.3857 data_time: 0.0032 memory: 4733 grad_norm: 0.0610 loss: 0.1592 loss_sem_seg: 0.1592 2023/05/15 10:27:58 - mmengine - INFO - Epoch(train) [29][ 400/1196] lr: 8.0000e-04 eta: 3:37:09 time: 1.3941 data_time: 0.0032 memory: 4705 grad_norm: 0.0593 loss: 0.1482 loss_sem_seg: 0.1482 2023/05/15 10:29:26 - mmengine - INFO - Epoch(train) [29][ 450/1196] lr: 8.0000e-04 eta: 3:36:03 time: 1.7598 data_time: 0.0033 memory: 4388 grad_norm: 0.0620 loss: 0.1644 loss_sem_seg: 0.1644 2023/05/15 10:30:36 - mmengine - INFO - Epoch(train) [29][ 500/1196] lr: 8.0000e-04 eta: 3:34:51 time: 1.3909 data_time: 0.0032 memory: 4755 grad_norm: 0.0597 loss: 0.1578 loss_sem_seg: 0.1578 2023/05/15 10:30:52 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 10:31:44 - mmengine - INFO - Epoch(train) [29][ 550/1196] lr: 8.0000e-04 eta: 3:33:40 time: 1.3756 data_time: 0.0032 memory: 4697 grad_norm: 0.0634 loss: 0.1587 loss_sem_seg: 0.1587 2023/05/15 10:32:54 - mmengine - INFO - Epoch(train) [29][ 600/1196] lr: 8.0000e-04 eta: 3:32:28 time: 1.3886 data_time: 0.0032 memory: 4910 grad_norm: 0.0591 loss: 0.1568 loss_sem_seg: 0.1568 2023/05/15 10:34:02 - mmengine - INFO - Epoch(train) [29][ 650/1196] lr: 8.0000e-04 eta: 3:31:16 time: 1.3693 data_time: 0.0032 memory: 4717 grad_norm: 0.0570 loss: 0.1516 loss_sem_seg: 0.1516 2023/05/15 10:35:11 - mmengine - INFO - Epoch(train) [29][ 700/1196] lr: 8.0000e-04 eta: 3:30:05 time: 1.3784 data_time: 0.0032 memory: 4550 grad_norm: 0.0572 loss: 0.1573 loss_sem_seg: 0.1573 2023/05/15 10:36:22 - mmengine - INFO - Epoch(train) [29][ 750/1196] lr: 8.0000e-04 eta: 3:28:53 time: 1.4111 data_time: 0.0032 memory: 4935 grad_norm: 0.0629 loss: 0.1515 loss_sem_seg: 0.1515 2023/05/15 10:37:31 - mmengine - INFO - Epoch(train) [29][ 800/1196] lr: 8.0000e-04 eta: 3:27:42 time: 1.3784 data_time: 0.0032 memory: 4542 grad_norm: 0.0635 loss: 0.1625 loss_sem_seg: 0.1625 2023/05/15 10:38:38 - mmengine - INFO - Epoch(train) [29][ 850/1196] lr: 8.0000e-04 eta: 3:26:30 time: 1.3561 data_time: 0.0034 memory: 4649 grad_norm: 0.0603 loss: 0.1563 loss_sem_seg: 0.1563 2023/05/15 10:39:47 - mmengine - INFO - Epoch(train) [29][ 900/1196] lr: 8.0000e-04 eta: 3:25:18 time: 1.3695 data_time: 0.0035 memory: 4835 grad_norm: 0.0618 loss: 0.1564 loss_sem_seg: 0.1564 2023/05/15 10:40:57 - mmengine - INFO - Epoch(train) [29][ 950/1196] lr: 8.0000e-04 eta: 3:24:07 time: 1.3999 data_time: 0.0035 memory: 4687 grad_norm: 0.0631 loss: 0.1668 loss_sem_seg: 0.1668 2023/05/15 10:42:05 - mmengine - INFO - Epoch(train) [29][1000/1196] lr: 8.0000e-04 eta: 3:22:55 time: 1.3541 data_time: 0.0034 memory: 4946 grad_norm: 0.0623 loss: 0.1498 loss_sem_seg: 0.1498 2023/05/15 10:43:13 - mmengine - INFO - Epoch(train) [29][1050/1196] lr: 8.0000e-04 eta: 3:21:43 time: 1.3747 data_time: 0.0034 memory: 4663 grad_norm: 0.0633 loss: 0.1642 loss_sem_seg: 0.1642 2023/05/15 10:44:22 - mmengine - INFO - Epoch(train) [29][1100/1196] lr: 8.0000e-04 eta: 3:20:32 time: 1.3646 data_time: 0.0033 memory: 4732 grad_norm: 0.0628 loss: 0.1577 loss_sem_seg: 0.1577 2023/05/15 10:45:30 - mmengine - INFO - Epoch(train) [29][1150/1196] lr: 8.0000e-04 eta: 3:19:20 time: 1.3651 data_time: 0.0033 memory: 4616 grad_norm: 0.0652 loss: 0.1642 loss_sem_seg: 0.1642 2023/05/15 10:46:34 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 10:46:34 - mmengine - INFO - Saving checkpoint at 29 epochs 2023/05/15 10:46:45 - mmengine - INFO - Epoch(val) [29][ 50/509] eta: 0:00:42 time: 0.0918 data_time: 0.0021 memory: 4783 2023/05/15 10:46:49 - mmengine - INFO - Epoch(val) [29][100/509] eta: 0:00:36 time: 0.0850 data_time: 0.0020 memory: 991 2023/05/15 10:46:53 - mmengine - INFO - Epoch(val) [29][150/509] eta: 0:00:31 time: 0.0827 data_time: 0.0019 memory: 994 2023/05/15 10:46:58 - mmengine - INFO - Epoch(val) [29][200/509] eta: 0:00:26 time: 0.0839 data_time: 0.0019 memory: 979 2023/05/15 10:47:02 - mmengine - INFO - Epoch(val) [29][250/509] eta: 0:00:22 time: 0.0883 data_time: 0.0019 memory: 1004 2023/05/15 10:47:06 - mmengine - INFO - Epoch(val) [29][300/509] eta: 0:00:17 time: 0.0767 data_time: 0.0019 memory: 946 2023/05/15 10:47:10 - mmengine - INFO - Epoch(val) [29][350/509] eta: 0:00:13 time: 0.0795 data_time: 0.0019 memory: 970 2023/05/15 10:47:14 - mmengine - INFO - Epoch(val) [29][400/509] eta: 0:00:09 time: 0.0846 data_time: 0.0019 memory: 978 2023/05/15 10:47:18 - mmengine - INFO - Epoch(val) [29][450/509] eta: 0:00:04 time: 0.0847 data_time: 0.0018 memory: 991 2023/05/15 10:47:22 - mmengine - INFO - Epoch(val) [29][500/509] eta: 0:00:00 time: 0.0784 data_time: 0.0018 memory: 973 2023/05/15 10:48:02 - 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 | 0.9673 | 0.5640 | 0.7888 | 0.8886 | 0.6809 | 0.7927 | 0.8980 | 0.1168 | 0.9461 | 0.5332 | 0.8287 | 0.0605 | 0.9212 | 0.6821 | 0.8804 | 0.6780 | 0.7381 | 0.6565 | 0.5204 | 0.6917 | 0.9249 | 0.7600 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 10:48:02 - mmengine - INFO - Epoch(val) [29][509/509] car: 0.9673 bicycle: 0.5640 motorcycle: 0.7888 truck: 0.8886 bus: 0.6809 person: 0.7927 bicyclist: 0.8980 motorcyclist: 0.1168 road: 0.9461 parking: 0.5332 sidewalk: 0.8287 other-ground: 0.0605 building: 0.9212 fence: 0.6821 vegetation: 0.8804 trunck: 0.6780 terrian: 0.7381 pole: 0.6565 traffic-sign: 0.5204 miou: 0.6917 acc: 0.9249 acc_cls: 0.7600 data_time: 0.0018 time: 0.0802 2023/05/15 10:49:12 - mmengine - INFO - Epoch(train) [30][ 50/1196] lr: 8.0000e-04 eta: 3:17:03 time: 1.3915 data_time: 0.0040 memory: 4671 grad_norm: 0.0572 loss: 0.1620 loss_sem_seg: 0.1620 2023/05/15 10:50:19 - mmengine - INFO - Epoch(train) [30][ 100/1196] lr: 8.0000e-04 eta: 3:15:51 time: 1.3533 data_time: 0.0032 memory: 5003 grad_norm: 0.0671 loss: 0.1586 loss_sem_seg: 0.1586 2023/05/15 10:51:29 - mmengine - INFO - Epoch(train) [30][ 150/1196] lr: 8.0000e-04 eta: 3:14:40 time: 1.4006 data_time: 0.0032 memory: 4737 grad_norm: 0.0618 loss: 0.1590 loss_sem_seg: 0.1590 2023/05/15 10:52:38 - mmengine - INFO - Epoch(train) [30][ 200/1196] lr: 8.0000e-04 eta: 3:13:28 time: 1.3817 data_time: 0.0033 memory: 4795 grad_norm: 0.0633 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/15 10:53:48 - mmengine - INFO - Epoch(train) [30][ 250/1196] lr: 8.0000e-04 eta: 3:12:17 time: 1.3841 data_time: 0.0033 memory: 4896 grad_norm: 0.0569 loss: 0.1491 loss_sem_seg: 0.1491 2023/05/15 10:54:56 - mmengine - INFO - Epoch(train) [30][ 300/1196] lr: 8.0000e-04 eta: 3:11:05 time: 1.3706 data_time: 0.0034 memory: 4918 grad_norm: 0.0670 loss: 0.1618 loss_sem_seg: 0.1618 2023/05/15 10:55:18 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 10:56:05 - mmengine - INFO - Epoch(train) [30][ 350/1196] lr: 8.0000e-04 eta: 3:09:54 time: 1.3802 data_time: 0.0033 memory: 4793 grad_norm: 0.0630 loss: 0.1543 loss_sem_seg: 0.1543 2023/05/15 10:57:14 - mmengine - INFO - Epoch(train) [30][ 400/1196] lr: 8.0000e-04 eta: 3:08:42 time: 1.3830 data_time: 0.0033 memory: 4680 grad_norm: 0.0602 loss: 0.1590 loss_sem_seg: 0.1590 2023/05/15 10:58:26 - mmengine - INFO - Epoch(train) [30][ 450/1196] lr: 8.0000e-04 eta: 3:07:31 time: 1.4405 data_time: 0.0032 memory: 4352 grad_norm: 0.0638 loss: 0.1604 loss_sem_seg: 0.1604 2023/05/15 10:59:52 - mmengine - INFO - Epoch(train) [30][ 500/1196] lr: 8.0000e-04 eta: 3:06:24 time: 1.7151 data_time: 0.0033 memory: 4847 grad_norm: 0.0635 loss: 0.1527 loss_sem_seg: 0.1527 2023/05/15 11:01:01 - mmengine - INFO - Epoch(train) [30][ 550/1196] lr: 8.0000e-04 eta: 3:05:12 time: 1.3763 data_time: 0.0032 memory: 4440 grad_norm: 0.0666 loss: 0.1656 loss_sem_seg: 0.1656 2023/05/15 11:02:09 - mmengine - INFO - Epoch(train) [30][ 600/1196] lr: 8.0000e-04 eta: 3:04:01 time: 1.3679 data_time: 0.0033 memory: 4857 grad_norm: 0.0607 loss: 0.1457 loss_sem_seg: 0.1457 2023/05/15 11:03:18 - mmengine - INFO - Epoch(train) [30][ 650/1196] lr: 8.0000e-04 eta: 3:02:49 time: 1.3683 data_time: 0.0032 memory: 4909 grad_norm: 0.0600 loss: 0.1605 loss_sem_seg: 0.1605 2023/05/15 11:04:26 - mmengine - INFO - Epoch(train) [30][ 700/1196] lr: 8.0000e-04 eta: 3:01:37 time: 1.3664 data_time: 0.0033 memory: 4551 grad_norm: 0.0605 loss: 0.1585 loss_sem_seg: 0.1585 2023/05/15 11:05:35 - mmengine - INFO - Epoch(train) [30][ 750/1196] lr: 8.0000e-04 eta: 3:00:26 time: 1.3817 data_time: 0.0032 memory: 5148 grad_norm: 0.0650 loss: 0.1596 loss_sem_seg: 0.1596 2023/05/15 11:06:45 - mmengine - INFO - Epoch(train) [30][ 800/1196] lr: 8.0000e-04 eta: 2:59:15 time: 1.3941 data_time: 0.0032 memory: 4531 grad_norm: 0.0639 loss: 0.1637 loss_sem_seg: 0.1637 2023/05/15 11:07:54 - mmengine - INFO - Epoch(train) [30][ 850/1196] lr: 8.0000e-04 eta: 2:58:03 time: 1.3832 data_time: 0.0033 memory: 5055 grad_norm: 0.0647 loss: 0.1522 loss_sem_seg: 0.1522 2023/05/15 11:09:04 - mmengine - INFO - Epoch(train) [30][ 900/1196] lr: 8.0000e-04 eta: 2:56:52 time: 1.3942 data_time: 0.0033 memory: 5302 grad_norm: 0.0580 loss: 0.1470 loss_sem_seg: 0.1470 2023/05/15 11:10:16 - mmengine - INFO - Epoch(train) [30][ 950/1196] lr: 8.0000e-04 eta: 2:55:41 time: 1.4499 data_time: 0.0033 memory: 4950 grad_norm: 0.0593 loss: 0.1493 loss_sem_seg: 0.1493 2023/05/15 11:11:45 - mmengine - INFO - Epoch(train) [30][1000/1196] lr: 8.0000e-04 eta: 2:54:34 time: 1.7662 data_time: 0.0034 memory: 4747 grad_norm: 0.0649 loss: 0.1586 loss_sem_seg: 0.1586 2023/05/15 11:12:53 - mmengine - INFO - Epoch(train) [30][1050/1196] lr: 8.0000e-04 eta: 2:53:22 time: 1.3734 data_time: 0.0034 memory: 4733 grad_norm: 0.0678 loss: 0.1581 loss_sem_seg: 0.1581 2023/05/15 11:14:02 - mmengine - INFO - Epoch(train) [30][1100/1196] lr: 8.0000e-04 eta: 2:52:11 time: 1.3700 data_time: 0.0035 memory: 5357 grad_norm: 0.0625 loss: 0.1526 loss_sem_seg: 0.1526 2023/05/15 11:15:10 - mmengine - INFO - Epoch(train) [30][1150/1196] lr: 8.0000e-04 eta: 2:50:59 time: 1.3562 data_time: 0.0034 memory: 4496 grad_norm: 0.0656 loss: 0.1606 loss_sem_seg: 0.1606 2023/05/15 11:16:13 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 11:16:13 - mmengine - INFO - Saving checkpoint at 30 epochs 2023/05/15 11:16:25 - mmengine - INFO - Epoch(val) [30][ 50/509] eta: 0:00:42 time: 0.0921 data_time: 0.0020 memory: 4524 2023/05/15 11:16:29 - mmengine - INFO - Epoch(val) [30][100/509] eta: 0:00:36 time: 0.0842 data_time: 0.0019 memory: 991 2023/05/15 11:16:33 - mmengine - INFO - Epoch(val) [30][150/509] eta: 0:00:30 time: 0.0820 data_time: 0.0019 memory: 994 2023/05/15 11:16:37 - mmengine - INFO - Epoch(val) [30][200/509] eta: 0:00:26 time: 0.0835 data_time: 0.0019 memory: 979 2023/05/15 11:16:42 - mmengine - INFO - Epoch(val) [30][250/509] eta: 0:00:22 time: 0.0879 data_time: 0.0019 memory: 1004 2023/05/15 11:16:46 - mmengine - INFO - Epoch(val) [30][300/509] eta: 0:00:17 time: 0.0764 data_time: 0.0019 memory: 946 2023/05/15 11:16:50 - mmengine - INFO - Epoch(val) [30][350/509] eta: 0:00:13 time: 0.0796 data_time: 0.0019 memory: 970 2023/05/15 11:16:54 - mmengine - INFO - Epoch(val) [30][400/509] eta: 0:00:09 time: 0.0852 data_time: 0.0019 memory: 978 2023/05/15 11:16:58 - mmengine - INFO - Epoch(val) [30][450/509] eta: 0:00:04 time: 0.0852 data_time: 0.0018 memory: 991 2023/05/15 11:17:02 - mmengine - INFO - Epoch(val) [30][500/509] eta: 0:00:00 time: 0.0789 data_time: 0.0018 memory: 973 2023/05/15 11:17:42 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9684 | 0.5715 | 0.7893 | 0.8742 | 0.7027 | 0.7908 | 0.8845 | 0.1279 | 0.9456 | 0.4960 | 0.8250 | 0.0533 | 0.9172 | 0.6653 | 0.8866 | 0.6844 | 0.7529 | 0.6557 | 0.5219 | 0.6902 | 0.9261 | 0.7574 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 11:17:42 - mmengine - INFO - Epoch(val) [30][509/509] car: 0.9684 bicycle: 0.5715 motorcycle: 0.7893 truck: 0.8742 bus: 0.7027 person: 0.7908 bicyclist: 0.8845 motorcyclist: 0.1279 road: 0.9456 parking: 0.4960 sidewalk: 0.8250 other-ground: 0.0533 building: 0.9172 fence: 0.6653 vegetation: 0.8866 trunck: 0.6844 terrian: 0.7529 pole: 0.6557 traffic-sign: 0.5219 miou: 0.6902 acc: 0.9261 acc_cls: 0.7574 data_time: 0.0018 time: 0.0806 2023/05/15 11:18:51 - mmengine - INFO - Epoch(train) [31][ 50/1196] lr: 8.0000e-04 eta: 2:48:42 time: 1.3747 data_time: 0.0043 memory: 4845 grad_norm: 0.0636 loss: 0.1562 loss_sem_seg: 0.1562 2023/05/15 11:20:01 - mmengine - INFO - Epoch(train) [31][ 100/1196] lr: 8.0000e-04 eta: 2:47:31 time: 1.3907 data_time: 0.0035 memory: 4919 grad_norm: 0.0633 loss: 0.1620 loss_sem_seg: 0.1620 2023/05/15 11:20:28 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 11:21:11 - mmengine - INFO - Epoch(train) [31][ 150/1196] lr: 8.0000e-04 eta: 2:46:19 time: 1.4020 data_time: 0.0032 memory: 4993 grad_norm: 0.0660 loss: 0.1505 loss_sem_seg: 0.1505 2023/05/15 11:22:19 - mmengine - INFO - Epoch(train) [31][ 200/1196] lr: 8.0000e-04 eta: 2:45:08 time: 1.3744 data_time: 0.0032 memory: 5085 grad_norm: 0.0663 loss: 0.1567 loss_sem_seg: 0.1567 2023/05/15 11:23:28 - mmengine - INFO - Epoch(train) [31][ 250/1196] lr: 8.0000e-04 eta: 2:43:56 time: 1.3697 data_time: 0.0032 memory: 4581 grad_norm: 0.0617 loss: 0.1636 loss_sem_seg: 0.1636 2023/05/15 11:24:37 - mmengine - INFO - Epoch(train) [31][ 300/1196] lr: 8.0000e-04 eta: 2:42:45 time: 1.3734 data_time: 0.0033 memory: 4670 grad_norm: 0.0615 loss: 0.1574 loss_sem_seg: 0.1574 2023/05/15 11:25:46 - mmengine - INFO - Epoch(train) [31][ 350/1196] lr: 8.0000e-04 eta: 2:41:34 time: 1.3914 data_time: 0.0033 memory: 4661 grad_norm: 0.0587 loss: 0.1558 loss_sem_seg: 0.1558 2023/05/15 11:26:55 - mmengine - INFO - Epoch(train) [31][ 400/1196] lr: 8.0000e-04 eta: 2:40:22 time: 1.3710 data_time: 0.0036 memory: 4576 grad_norm: 0.0597 loss: 0.1549 loss_sem_seg: 0.1549 2023/05/15 11:28:03 - mmengine - INFO - Epoch(train) [31][ 450/1196] lr: 8.0000e-04 eta: 2:39:11 time: 1.3598 data_time: 0.0034 memory: 4677 grad_norm: 0.0618 loss: 0.1521 loss_sem_seg: 0.1521 2023/05/15 11:29:11 - mmengine - INFO - Epoch(train) [31][ 500/1196] lr: 8.0000e-04 eta: 2:37:59 time: 1.3683 data_time: 0.0033 memory: 4883 grad_norm: 0.0636 loss: 0.1604 loss_sem_seg: 0.1604 2023/05/15 11:30:19 - mmengine - INFO - Epoch(train) [31][ 550/1196] lr: 8.0000e-04 eta: 2:36:48 time: 1.3538 data_time: 0.0032 memory: 4938 grad_norm: 0.0611 loss: 0.1571 loss_sem_seg: 0.1571 2023/05/15 11:31:28 - mmengine - INFO - Epoch(train) [31][ 600/1196] lr: 8.0000e-04 eta: 2:35:36 time: 1.3851 data_time: 0.0033 memory: 4499 grad_norm: 0.0657 loss: 0.1501 loss_sem_seg: 0.1501 2023/05/15 11:32:37 - mmengine - INFO - Epoch(train) [31][ 650/1196] lr: 8.0000e-04 eta: 2:34:25 time: 1.3774 data_time: 0.0032 memory: 4981 grad_norm: 0.0651 loss: 0.1430 loss_sem_seg: 0.1430 2023/05/15 11:33:45 - mmengine - INFO - Epoch(train) [31][ 700/1196] lr: 8.0000e-04 eta: 2:33:13 time: 1.3683 data_time: 0.0032 memory: 4514 grad_norm: 0.0613 loss: 0.1518 loss_sem_seg: 0.1518 2023/05/15 11:34:55 - mmengine - INFO - Epoch(train) [31][ 750/1196] lr: 8.0000e-04 eta: 2:32:02 time: 1.3949 data_time: 0.0032 memory: 4555 grad_norm: 0.0603 loss: 0.1499 loss_sem_seg: 0.1499 2023/05/15 11:36:05 - mmengine - INFO - Epoch(train) [31][ 800/1196] lr: 8.0000e-04 eta: 2:30:51 time: 1.3885 data_time: 0.0036 memory: 4821 grad_norm: 0.0638 loss: 0.1579 loss_sem_seg: 0.1579 2023/05/15 11:37:13 - mmengine - INFO - Epoch(train) [31][ 850/1196] lr: 8.0000e-04 eta: 2:29:39 time: 1.3654 data_time: 0.0037 memory: 4602 grad_norm: 0.0605 loss: 0.1581 loss_sem_seg: 0.1581 2023/05/15 11:38:23 - mmengine - INFO - Epoch(train) [31][ 900/1196] lr: 8.0000e-04 eta: 2:28:28 time: 1.4009 data_time: 0.0033 memory: 4505 grad_norm: 0.0653 loss: 0.1569 loss_sem_seg: 0.1569 2023/05/15 11:39:31 - mmengine - INFO - Epoch(train) [31][ 950/1196] lr: 8.0000e-04 eta: 2:27:17 time: 1.3715 data_time: 0.0033 memory: 4877 grad_norm: 0.0597 loss: 0.1474 loss_sem_seg: 0.1474 2023/05/15 11:40:48 - mmengine - INFO - Epoch(train) [31][1000/1196] lr: 8.0000e-04 eta: 2:26:07 time: 1.5218 data_time: 0.0032 memory: 4801 grad_norm: 0.0586 loss: 0.1518 loss_sem_seg: 0.1518 2023/05/15 11:42:11 - mmengine - INFO - Epoch(train) [31][1050/1196] lr: 8.0000e-04 eta: 2:24:58 time: 1.6591 data_time: 0.0035 memory: 4806 grad_norm: 0.0604 loss: 0.1522 loss_sem_seg: 0.1522 2023/05/15 11:43:19 - mmengine - INFO - Epoch(train) [31][1100/1196] lr: 8.0000e-04 eta: 2:23:46 time: 1.3707 data_time: 0.0034 memory: 4895 grad_norm: 0.0633 loss: 0.1643 loss_sem_seg: 0.1643 2023/05/15 11:43:46 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 11:44:27 - mmengine - INFO - Epoch(train) [31][1150/1196] lr: 8.0000e-04 eta: 2:22:35 time: 1.3667 data_time: 0.0033 memory: 4634 grad_norm: 0.0604 loss: 0.1521 loss_sem_seg: 0.1521 2023/05/15 11:45:32 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 11:45:32 - mmengine - INFO - Saving checkpoint at 31 epochs 2023/05/15 11:45:45 - mmengine - INFO - Epoch(val) [31][ 50/509] eta: 0:01:03 time: 0.1382 data_time: 0.0021 memory: 4795 2023/05/15 11:45:50 - mmengine - INFO - Epoch(val) [31][100/509] eta: 0:00:45 time: 0.0845 data_time: 0.0019 memory: 991 2023/05/15 11:45:54 - mmengine - INFO - Epoch(val) [31][150/509] eta: 0:00:36 time: 0.0828 data_time: 0.0019 memory: 994 2023/05/15 11:45:58 - mmengine - INFO - Epoch(val) [31][200/509] eta: 0:00:30 time: 0.0840 data_time: 0.0020 memory: 979 2023/05/15 11:46:02 - mmengine - INFO - Epoch(val) [31][250/509] eta: 0:00:24 time: 0.0882 data_time: 0.0019 memory: 1004 2023/05/15 11:46:06 - mmengine - INFO - Epoch(val) [31][300/509] eta: 0:00:19 time: 0.0764 data_time: 0.0019 memory: 946 2023/05/15 11:46:10 - mmengine - INFO - Epoch(val) [31][350/509] eta: 0:00:14 time: 0.0795 data_time: 0.0019 memory: 970 2023/05/15 11:46:14 - mmengine - INFO - Epoch(val) [31][400/509] eta: 0:00:09 time: 0.0846 data_time: 0.0019 memory: 978 2023/05/15 11:46:19 - mmengine - INFO - Epoch(val) [31][450/509] eta: 0:00:05 time: 0.0849 data_time: 0.0019 memory: 991 2023/05/15 11:46:23 - mmengine - INFO - Epoch(val) [31][500/509] eta: 0:00:00 time: 0.0781 data_time: 0.0018 memory: 973 2023/05/15 11:47:02 - 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 | 0.9674 | 0.5635 | 0.8041 | 0.8551 | 0.6809 | 0.7774 | 0.8877 | 0.1053 | 0.9436 | 0.4963 | 0.8278 | 0.0435 | 0.9180 | 0.6680 | 0.8793 | 0.6920 | 0.7335 | 0.6555 | 0.5138 | 0.6849 | 0.9235 | 0.7545 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 11:47:02 - mmengine - INFO - Epoch(val) [31][509/509] car: 0.9674 bicycle: 0.5635 motorcycle: 0.8041 truck: 0.8551 bus: 0.6809 person: 0.7774 bicyclist: 0.8877 motorcyclist: 0.1053 road: 0.9436 parking: 0.4963 sidewalk: 0.8278 other-ground: 0.0435 building: 0.9180 fence: 0.6680 vegetation: 0.8793 trunck: 0.6920 terrian: 0.7335 pole: 0.6555 traffic-sign: 0.5138 miou: 0.6849 acc: 0.9235 acc_cls: 0.7545 data_time: 0.0018 time: 0.0799 2023/05/15 11:48:11 - mmengine - INFO - Epoch(train) [32][ 50/1196] lr: 8.0000e-04 eta: 2:20:18 time: 1.3802 data_time: 0.0041 memory: 4748 grad_norm: 0.0646 loss: 0.1500 loss_sem_seg: 0.1500 2023/05/15 11:49:20 - mmengine - INFO - Epoch(train) [32][ 100/1196] lr: 8.0000e-04 eta: 2:19:07 time: 1.3843 data_time: 0.0032 memory: 4538 grad_norm: 0.0621 loss: 0.1579 loss_sem_seg: 0.1579 2023/05/15 11:50:29 - mmengine - INFO - Epoch(train) [32][ 150/1196] lr: 8.0000e-04 eta: 2:17:56 time: 1.3803 data_time: 0.0032 memory: 4959 grad_norm: 0.0591 loss: 0.1486 loss_sem_seg: 0.1486 2023/05/15 11:51:38 - mmengine - INFO - Epoch(train) [32][ 200/1196] lr: 8.0000e-04 eta: 2:16:44 time: 1.3783 data_time: 0.0033 memory: 4490 grad_norm: 0.0652 loss: 0.1557 loss_sem_seg: 0.1557 2023/05/15 11:53:00 - mmengine - INFO - Epoch(train) [32][ 250/1196] lr: 8.0000e-04 eta: 2:15:35 time: 1.6390 data_time: 0.0033 memory: 4717 grad_norm: 0.0605 loss: 0.1632 loss_sem_seg: 0.1632 2023/05/15 11:54:17 - mmengine - INFO - Epoch(train) [32][ 300/1196] lr: 8.0000e-04 eta: 2:14:25 time: 1.5459 data_time: 0.0033 memory: 4862 grad_norm: 0.0594 loss: 0.1560 loss_sem_seg: 0.1560 2023/05/15 11:55:26 - mmengine - INFO - Epoch(train) [32][ 350/1196] lr: 8.0000e-04 eta: 2:13:14 time: 1.3647 data_time: 0.0032 memory: 4681 grad_norm: 0.0595 loss: 0.1563 loss_sem_seg: 0.1563 2023/05/15 11:56:35 - mmengine - INFO - Epoch(train) [32][ 400/1196] lr: 8.0000e-04 eta: 2:12:02 time: 1.3941 data_time: 0.0032 memory: 4593 grad_norm: 0.0611 loss: 0.1494 loss_sem_seg: 0.1494 2023/05/15 11:57:44 - mmengine - INFO - Epoch(train) [32][ 450/1196] lr: 8.0000e-04 eta: 2:10:51 time: 1.3783 data_time: 0.0032 memory: 4716 grad_norm: 0.0666 loss: 0.1494 loss_sem_seg: 0.1494 2023/05/15 11:58:53 - mmengine - INFO - Epoch(train) [32][ 500/1196] lr: 8.0000e-04 eta: 2:09:40 time: 1.3698 data_time: 0.0032 memory: 4570 grad_norm: 0.0601 loss: 0.1488 loss_sem_seg: 0.1488 2023/05/15 12:00:00 - mmengine - INFO - Epoch(train) [32][ 550/1196] lr: 8.0000e-04 eta: 2:08:28 time: 1.3527 data_time: 0.0032 memory: 4781 grad_norm: 0.0638 loss: 0.1560 loss_sem_seg: 0.1560 2023/05/15 12:01:10 - mmengine - INFO - Epoch(train) [32][ 600/1196] lr: 8.0000e-04 eta: 2:07:17 time: 1.3848 data_time: 0.0032 memory: 4647 grad_norm: 0.0651 loss: 0.1460 loss_sem_seg: 0.1460 2023/05/15 12:02:19 - mmengine - INFO - Epoch(train) [32][ 650/1196] lr: 8.0000e-04 eta: 2:06:06 time: 1.3944 data_time: 0.0032 memory: 4457 grad_norm: 0.0682 loss: 0.1525 loss_sem_seg: 0.1525 2023/05/15 12:03:28 - mmengine - INFO - Epoch(train) [32][ 700/1196] lr: 8.0000e-04 eta: 2:04:55 time: 1.3675 data_time: 0.0032 memory: 4837 grad_norm: 0.0637 loss: 0.1448 loss_sem_seg: 0.1448 2023/05/15 12:04:37 - mmengine - INFO - Epoch(train) [32][ 750/1196] lr: 8.0000e-04 eta: 2:03:43 time: 1.3740 data_time: 0.0033 memory: 4476 grad_norm: 0.0611 loss: 0.1631 loss_sem_seg: 0.1631 2023/05/15 12:05:47 - mmengine - INFO - Epoch(train) [32][ 800/1196] lr: 8.0000e-04 eta: 2:02:32 time: 1.4134 data_time: 0.0032 memory: 5422 grad_norm: 0.0611 loss: 0.1501 loss_sem_seg: 0.1501 2023/05/15 12:06:56 - mmengine - INFO - Epoch(train) [32][ 850/1196] lr: 8.0000e-04 eta: 2:01:21 time: 1.3682 data_time: 0.0032 memory: 4594 grad_norm: 0.0617 loss: 0.1510 loss_sem_seg: 0.1510 2023/05/15 12:08:05 - mmengine - INFO - Epoch(train) [32][ 900/1196] lr: 8.0000e-04 eta: 2:00:10 time: 1.3935 data_time: 0.0032 memory: 4900 grad_norm: 0.0592 loss: 0.1487 loss_sem_seg: 0.1487 2023/05/15 12:08:38 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 12:09:15 - mmengine - INFO - Epoch(train) [32][ 950/1196] lr: 8.0000e-04 eta: 1:58:59 time: 1.3905 data_time: 0.0033 memory: 4291 grad_norm: 0.0615 loss: 0.1455 loss_sem_seg: 0.1455 2023/05/15 12:10:24 - mmengine - INFO - Epoch(train) [32][1000/1196] lr: 8.0000e-04 eta: 1:57:48 time: 1.3922 data_time: 0.0033 memory: 5045 grad_norm: 0.0645 loss: 0.1527 loss_sem_seg: 0.1527 2023/05/15 12:11:34 - mmengine - INFO - Epoch(train) [32][1050/1196] lr: 8.0000e-04 eta: 1:56:36 time: 1.3936 data_time: 0.0033 memory: 4745 grad_norm: 0.0581 loss: 0.1523 loss_sem_seg: 0.1523 2023/05/15 12:12:43 - mmengine - INFO - Epoch(train) [32][1100/1196] lr: 8.0000e-04 eta: 1:55:25 time: 1.3756 data_time: 0.0032 memory: 4744 grad_norm: 0.0635 loss: 0.1513 loss_sem_seg: 0.1513 2023/05/15 12:13:51 - mmengine - INFO - Epoch(train) [32][1150/1196] lr: 8.0000e-04 eta: 1:54:14 time: 1.3665 data_time: 0.0032 memory: 4674 grad_norm: 0.0645 loss: 0.1613 loss_sem_seg: 0.1613 2023/05/15 12:14:54 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 12:14:54 - mmengine - INFO - Saving checkpoint at 32 epochs 2023/05/15 12:15:06 - mmengine - INFO - Epoch(val) [32][ 50/509] eta: 0:00:42 time: 0.0926 data_time: 0.0021 memory: 4541 2023/05/15 12:15:10 - mmengine - INFO - Epoch(val) [32][100/509] eta: 0:00:36 time: 0.0846 data_time: 0.0020 memory: 991 2023/05/15 12:15:14 - mmengine - INFO - Epoch(val) [32][150/509] eta: 0:00:31 time: 0.0830 data_time: 0.0019 memory: 994 2023/05/15 12:15:19 - mmengine - INFO - Epoch(val) [32][200/509] eta: 0:00:26 time: 0.0840 data_time: 0.0019 memory: 979 2023/05/15 12:15:23 - mmengine - INFO - Epoch(val) [32][250/509] eta: 0:00:22 time: 0.0886 data_time: 0.0019 memory: 1004 2023/05/15 12:15:27 - mmengine - INFO - Epoch(val) [32][300/509] eta: 0:00:17 time: 0.0767 data_time: 0.0019 memory: 946 2023/05/15 12:15:31 - mmengine - INFO - Epoch(val) [32][350/509] eta: 0:00:13 time: 0.0797 data_time: 0.0019 memory: 970 2023/05/15 12:15:35 - mmengine - INFO - Epoch(val) [32][400/509] eta: 0:00:09 time: 0.0843 data_time: 0.0019 memory: 978 2023/05/15 12:15:41 - mmengine - INFO - Epoch(val) [32][450/509] eta: 0:00:05 time: 0.1087 data_time: 0.0018 memory: 991 2023/05/15 12:15:46 - mmengine - INFO - Epoch(val) [32][500/509] eta: 0:00:00 time: 0.0993 data_time: 0.0017 memory: 973 2023/05/15 12:16:25 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9628 | 0.5488 | 0.8002 | 0.8465 | 0.6252 | 0.7844 | 0.8995 | 0.1180 | 0.9457 | 0.4733 | 0.8248 | 0.0269 | 0.9204 | 0.6808 | 0.8789 | 0.6798 | 0.7328 | 0.6586 | 0.5108 | 0.6799 | 0.9230 | 0.7445 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 12:16:25 - mmengine - INFO - Epoch(val) [32][509/509] car: 0.9628 bicycle: 0.5488 motorcycle: 0.8002 truck: 0.8465 bus: 0.6252 person: 0.7844 bicyclist: 0.8995 motorcyclist: 0.1180 road: 0.9457 parking: 0.4733 sidewalk: 0.8248 other-ground: 0.0269 building: 0.9204 fence: 0.6808 vegetation: 0.8789 trunck: 0.6798 terrian: 0.7328 pole: 0.6586 traffic-sign: 0.5108 miou: 0.6799 acc: 0.9230 acc_cls: 0.7445 data_time: 0.0017 time: 0.0803 2023/05/15 12:17:34 - mmengine - INFO - Epoch(train) [33][ 50/1196] lr: 8.0000e-05 eta: 1:51:57 time: 1.3769 data_time: 0.0044 memory: 4910 grad_norm: 0.0624 loss: 0.1480 loss_sem_seg: 0.1480 2023/05/15 12:18:42 - mmengine - INFO - Epoch(train) [33][ 100/1196] lr: 8.0000e-05 eta: 1:50:46 time: 1.3518 data_time: 0.0034 memory: 4901 grad_norm: 0.0597 loss: 0.1539 loss_sem_seg: 0.1539 2023/05/15 12:19:51 - mmengine - INFO - Epoch(train) [33][ 150/1196] lr: 8.0000e-05 eta: 1:49:35 time: 1.3824 data_time: 0.0033 memory: 4237 grad_norm: 0.0560 loss: 0.1461 loss_sem_seg: 0.1461 2023/05/15 12:21:00 - mmengine - INFO - Epoch(train) [33][ 200/1196] lr: 8.0000e-05 eta: 1:48:23 time: 1.3850 data_time: 0.0033 memory: 5093 grad_norm: 0.0598 loss: 0.1398 loss_sem_seg: 0.1398 2023/05/15 12:22:09 - mmengine - INFO - Epoch(train) [33][ 250/1196] lr: 8.0000e-05 eta: 1:47:12 time: 1.3697 data_time: 0.0032 memory: 4843 grad_norm: 0.0569 loss: 0.1392 loss_sem_seg: 0.1392 2023/05/15 12:23:39 - mmengine - INFO - Epoch(train) [33][ 300/1196] lr: 8.0000e-05 eta: 1:46:04 time: 1.8167 data_time: 0.0033 memory: 4633 grad_norm: 0.0610 loss: 0.1377 loss_sem_seg: 0.1377 2023/05/15 12:24:47 - mmengine - INFO - Epoch(train) [33][ 350/1196] lr: 8.0000e-05 eta: 1:44:52 time: 1.3501 data_time: 0.0033 memory: 4584 grad_norm: 0.0608 loss: 0.1505 loss_sem_seg: 0.1505 2023/05/15 12:25:57 - mmengine - INFO - Epoch(train) [33][ 400/1196] lr: 8.0000e-05 eta: 1:43:41 time: 1.4032 data_time: 0.0033 memory: 5353 grad_norm: 0.0589 loss: 0.1459 loss_sem_seg: 0.1459 2023/05/15 12:27:06 - mmengine - INFO - Epoch(train) [33][ 450/1196] lr: 8.0000e-05 eta: 1:42:30 time: 1.3692 data_time: 0.0032 memory: 4947 grad_norm: 0.0623 loss: 0.1571 loss_sem_seg: 0.1571 2023/05/15 12:28:14 - mmengine - INFO - Epoch(train) [33][ 500/1196] lr: 8.0000e-05 eta: 1:41:19 time: 1.3681 data_time: 0.0032 memory: 4865 grad_norm: 0.0560 loss: 0.1471 loss_sem_seg: 0.1471 2023/05/15 12:29:22 - mmengine - INFO - Epoch(train) [33][ 550/1196] lr: 8.0000e-05 eta: 1:40:07 time: 1.3685 data_time: 0.0033 memory: 5263 grad_norm: 0.0561 loss: 0.1357 loss_sem_seg: 0.1357 2023/05/15 12:30:30 - mmengine - INFO - Epoch(train) [33][ 600/1196] lr: 8.0000e-05 eta: 1:38:56 time: 1.3568 data_time: 0.0033 memory: 4852 grad_norm: 0.0582 loss: 0.1460 loss_sem_seg: 0.1460 2023/05/15 12:31:38 - mmengine - INFO - Epoch(train) [33][ 650/1196] lr: 8.0000e-05 eta: 1:37:45 time: 1.3566 data_time: 0.0034 memory: 4343 grad_norm: 0.0574 loss: 0.1431 loss_sem_seg: 0.1431 2023/05/15 12:32:47 - mmengine - INFO - Epoch(train) [33][ 700/1196] lr: 8.0000e-05 eta: 1:36:34 time: 1.3871 data_time: 0.0032 memory: 4918 grad_norm: 0.0597 loss: 0.1527 loss_sem_seg: 0.1527 2023/05/15 12:33:25 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 12:33:56 - mmengine - INFO - Epoch(train) [33][ 750/1196] lr: 8.0000e-05 eta: 1:35:23 time: 1.3620 data_time: 0.0033 memory: 4624 grad_norm: 0.0624 loss: 0.1546 loss_sem_seg: 0.1546 2023/05/15 12:35:24 - mmengine - INFO - Epoch(train) [33][ 800/1196] lr: 8.0000e-05 eta: 1:34:13 time: 1.7632 data_time: 0.0033 memory: 5267 grad_norm: 0.0565 loss: 0.1420 loss_sem_seg: 0.1420 2023/05/15 12:36:36 - mmengine - INFO - Epoch(train) [33][ 850/1196] lr: 8.0000e-05 eta: 1:33:03 time: 1.4536 data_time: 0.0033 memory: 4741 grad_norm: 0.0577 loss: 0.1427 loss_sem_seg: 0.1427 2023/05/15 12:37:45 - mmengine - INFO - Epoch(train) [33][ 900/1196] lr: 8.0000e-05 eta: 1:31:51 time: 1.3658 data_time: 0.0032 memory: 5623 grad_norm: 0.0595 loss: 0.1503 loss_sem_seg: 0.1503 2023/05/15 12:38:53 - mmengine - INFO - Epoch(train) [33][ 950/1196] lr: 8.0000e-05 eta: 1:30:40 time: 1.3624 data_time: 0.0032 memory: 4426 grad_norm: 0.0564 loss: 0.1404 loss_sem_seg: 0.1404 2023/05/15 12:40:01 - mmengine - INFO - Epoch(train) [33][1000/1196] lr: 8.0000e-05 eta: 1:29:29 time: 1.3555 data_time: 0.0033 memory: 4680 grad_norm: 0.0582 loss: 0.1405 loss_sem_seg: 0.1405 2023/05/15 12:41:10 - mmengine - INFO - Epoch(train) [33][1050/1196] lr: 8.0000e-05 eta: 1:28:18 time: 1.3801 data_time: 0.0032 memory: 4665 grad_norm: 0.0550 loss: 0.1472 loss_sem_seg: 0.1472 2023/05/15 12:42:18 - mmengine - INFO - Epoch(train) [33][1100/1196] lr: 8.0000e-05 eta: 1:27:07 time: 1.3646 data_time: 0.0032 memory: 4518 grad_norm: 0.0572 loss: 0.1402 loss_sem_seg: 0.1402 2023/05/15 12:43:27 - mmengine - INFO - Epoch(train) [33][1150/1196] lr: 8.0000e-05 eta: 1:25:55 time: 1.3737 data_time: 0.0032 memory: 4826 grad_norm: 0.0589 loss: 0.1539 loss_sem_seg: 0.1539 2023/05/15 12:44:31 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 12:44:31 - mmengine - INFO - Saving checkpoint at 33 epochs 2023/05/15 12:44:42 - mmengine - INFO - Epoch(val) [33][ 50/509] eta: 0:00:42 time: 0.0933 data_time: 0.0021 memory: 4919 2023/05/15 12:44:47 - mmengine - INFO - Epoch(val) [33][100/509] eta: 0:00:36 time: 0.0853 data_time: 0.0020 memory: 991 2023/05/15 12:44:51 - mmengine - INFO - Epoch(val) [33][150/509] eta: 0:00:31 time: 0.0830 data_time: 0.0019 memory: 994 2023/05/15 12:44:55 - mmengine - INFO - Epoch(val) [33][200/509] eta: 0:00:26 time: 0.0844 data_time: 0.0020 memory: 979 2023/05/15 12:44:59 - mmengine - INFO - Epoch(val) [33][250/509] eta: 0:00:22 time: 0.0885 data_time: 0.0019 memory: 1004 2023/05/15 12:45:03 - mmengine - INFO - Epoch(val) [33][300/509] eta: 0:00:17 time: 0.0770 data_time: 0.0019 memory: 946 2023/05/15 12:45:07 - mmengine - INFO - Epoch(val) [33][350/509] eta: 0:00:13 time: 0.0795 data_time: 0.0019 memory: 970 2023/05/15 12:45:12 - mmengine - INFO - Epoch(val) [33][400/509] eta: 0:00:09 time: 0.0850 data_time: 0.0019 memory: 978 2023/05/15 12:45:16 - mmengine - INFO - Epoch(val) [33][450/509] eta: 0:00:04 time: 0.0849 data_time: 0.0018 memory: 991 2023/05/15 12:45:20 - mmengine - INFO - Epoch(val) [33][500/509] eta: 0:00:00 time: 0.0783 data_time: 0.0017 memory: 973 2023/05/15 12:46:02 - 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 | 0.9691 | 0.5612 | 0.7961 | 0.8947 | 0.7125 | 0.7895 | 0.8988 | 0.1120 | 0.9466 | 0.5163 | 0.8299 | 0.0379 | 0.9196 | 0.6767 | 0.8806 | 0.6867 | 0.7372 | 0.6594 | 0.5153 | 0.6916 | 0.9249 | 0.7570 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 12:46:02 - mmengine - INFO - Epoch(val) [33][509/509] car: 0.9691 bicycle: 0.5612 motorcycle: 0.7961 truck: 0.8947 bus: 0.7125 person: 0.7895 bicyclist: 0.8988 motorcyclist: 0.1120 road: 0.9466 parking: 0.5163 sidewalk: 0.8299 other-ground: 0.0379 building: 0.9196 fence: 0.6767 vegetation: 0.8806 trunck: 0.6867 terrian: 0.7372 pole: 0.6594 traffic-sign: 0.5153 miou: 0.6916 acc: 0.9249 acc_cls: 0.7570 data_time: 0.0017 time: 0.0802 2023/05/15 12:47:11 - mmengine - INFO - Epoch(train) [34][ 50/1196] lr: 8.0000e-05 eta: 1:23:39 time: 1.3808 data_time: 0.0040 memory: 4401 grad_norm: 0.0593 loss: 0.1580 loss_sem_seg: 0.1580 2023/05/15 12:48:19 - mmengine - INFO - Epoch(train) [34][ 100/1196] lr: 8.0000e-05 eta: 1:22:28 time: 1.3725 data_time: 0.0032 memory: 4649 grad_norm: 0.0587 loss: 0.1554 loss_sem_seg: 0.1554 2023/05/15 12:49:29 - mmengine - INFO - Epoch(train) [34][ 150/1196] lr: 8.0000e-05 eta: 1:21:17 time: 1.3860 data_time: 0.0032 memory: 4686 grad_norm: 0.0573 loss: 0.1502 loss_sem_seg: 0.1502 2023/05/15 12:50:37 - mmengine - INFO - Epoch(train) [34][ 200/1196] lr: 8.0000e-05 eta: 1:20:06 time: 1.3765 data_time: 0.0032 memory: 4743 grad_norm: 0.0562 loss: 0.1429 loss_sem_seg: 0.1429 2023/05/15 12:51:44 - mmengine - INFO - Epoch(train) [34][ 250/1196] lr: 8.0000e-05 eta: 1:18:54 time: 1.3404 data_time: 0.0032 memory: 4686 grad_norm: 0.0592 loss: 0.1485 loss_sem_seg: 0.1485 2023/05/15 12:52:52 - mmengine - INFO - Epoch(train) [34][ 300/1196] lr: 8.0000e-05 eta: 1:17:43 time: 1.3448 data_time: 0.0032 memory: 4603 grad_norm: 0.0596 loss: 0.1539 loss_sem_seg: 0.1539 2023/05/15 12:54:00 - mmengine - INFO - Epoch(train) [34][ 350/1196] lr: 8.0000e-05 eta: 1:16:32 time: 1.3588 data_time: 0.0032 memory: 5079 grad_norm: 0.0597 loss: 0.1526 loss_sem_seg: 0.1526 2023/05/15 12:55:09 - mmengine - INFO - Epoch(train) [34][ 400/1196] lr: 8.0000e-05 eta: 1:15:21 time: 1.3803 data_time: 0.0032 memory: 4572 grad_norm: 0.0587 loss: 0.1497 loss_sem_seg: 0.1497 2023/05/15 12:56:17 - mmengine - INFO - Epoch(train) [34][ 450/1196] lr: 8.0000e-05 eta: 1:14:10 time: 1.3743 data_time: 0.0032 memory: 4826 grad_norm: 0.0605 loss: 0.1513 loss_sem_seg: 0.1513 2023/05/15 12:57:26 - mmengine - INFO - Epoch(train) [34][ 500/1196] lr: 8.0000e-05 eta: 1:12:59 time: 1.3676 data_time: 0.0033 memory: 5146 grad_norm: 0.0579 loss: 0.1417 loss_sem_seg: 0.1417 2023/05/15 12:58:10 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 12:58:34 - mmengine - INFO - Epoch(train) [34][ 550/1196] lr: 8.0000e-05 eta: 1:11:48 time: 1.3687 data_time: 0.0032 memory: 4670 grad_norm: 0.0570 loss: 0.1443 loss_sem_seg: 0.1443 2023/05/15 12:59:43 - mmengine - INFO - Epoch(train) [34][ 600/1196] lr: 8.0000e-05 eta: 1:10:37 time: 1.3676 data_time: 0.0033 memory: 5328 grad_norm: 0.0594 loss: 0.1378 loss_sem_seg: 0.1378 2023/05/15 13:00:53 - mmengine - INFO - Epoch(train) [34][ 650/1196] lr: 8.0000e-05 eta: 1:09:26 time: 1.3986 data_time: 0.0032 memory: 5112 grad_norm: 0.0611 loss: 0.1577 loss_sem_seg: 0.1577 2023/05/15 13:02:02 - mmengine - INFO - Epoch(train) [34][ 700/1196] lr: 8.0000e-05 eta: 1:08:15 time: 1.3887 data_time: 0.0033 memory: 5215 grad_norm: 0.0585 loss: 0.1503 loss_sem_seg: 0.1503 2023/05/15 13:03:10 - mmengine - INFO - Epoch(train) [34][ 750/1196] lr: 8.0000e-05 eta: 1:07:03 time: 1.3598 data_time: 0.0035 memory: 4634 grad_norm: 0.0566 loss: 0.1535 loss_sem_seg: 0.1535 2023/05/15 13:04:18 - mmengine - INFO - Epoch(train) [34][ 800/1196] lr: 8.0000e-05 eta: 1:05:52 time: 1.3677 data_time: 0.0035 memory: 4570 grad_norm: 0.0583 loss: 0.1489 loss_sem_seg: 0.1489 2023/05/15 13:05:27 - mmengine - INFO - Epoch(train) [34][ 850/1196] lr: 8.0000e-05 eta: 1:04:41 time: 1.3822 data_time: 0.0034 memory: 4460 grad_norm: 0.0557 loss: 0.1420 loss_sem_seg: 0.1420 2023/05/15 13:06:53 - mmengine - INFO - Epoch(train) [34][ 900/1196] lr: 8.0000e-05 eta: 1:03:31 time: 1.7113 data_time: 0.0036 memory: 4776 grad_norm: 0.0581 loss: 0.1425 loss_sem_seg: 0.1425 2023/05/15 13:08:07 - mmengine - INFO - Epoch(train) [34][ 950/1196] lr: 8.0000e-05 eta: 1:02:21 time: 1.4728 data_time: 0.0035 memory: 4573 grad_norm: 0.0589 loss: 0.1489 loss_sem_seg: 0.1489 2023/05/15 13:09:15 - mmengine - INFO - Epoch(train) [34][1000/1196] lr: 8.0000e-05 eta: 1:01:10 time: 1.3594 data_time: 0.0034 memory: 5360 grad_norm: 0.0584 loss: 0.1491 loss_sem_seg: 0.1491 2023/05/15 13:10:23 - mmengine - INFO - Epoch(train) [34][1050/1196] lr: 8.0000e-05 eta: 0:59:59 time: 1.3717 data_time: 0.0033 memory: 5455 grad_norm: 0.0622 loss: 0.1396 loss_sem_seg: 0.1396 2023/05/15 13:11:33 - mmengine - INFO - Epoch(train) [34][1100/1196] lr: 8.0000e-05 eta: 0:58:48 time: 1.3853 data_time: 0.0033 memory: 4831 grad_norm: 0.0554 loss: 0.1326 loss_sem_seg: 0.1326 2023/05/15 13:12:42 - mmengine - INFO - Epoch(train) [34][1150/1196] lr: 8.0000e-05 eta: 0:57:37 time: 1.3823 data_time: 0.0033 memory: 4844 grad_norm: 0.0577 loss: 0.1417 loss_sem_seg: 0.1417 2023/05/15 13:13:45 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 13:13:45 - mmengine - INFO - Saving checkpoint at 34 epochs 2023/05/15 13:13:56 - mmengine - INFO - Epoch(val) [34][ 50/509] eta: 0:00:42 time: 0.0919 data_time: 0.0020 memory: 4444 2023/05/15 13:14:00 - mmengine - INFO - Epoch(val) [34][100/509] eta: 0:00:36 time: 0.0846 data_time: 0.0019 memory: 991 2023/05/15 13:14:05 - mmengine - INFO - Epoch(val) [34][150/509] eta: 0:00:30 time: 0.0826 data_time: 0.0019 memory: 994 2023/05/15 13:14:09 - mmengine - INFO - Epoch(val) [34][200/509] eta: 0:00:26 time: 0.0839 data_time: 0.0019 memory: 979 2023/05/15 13:14:13 - mmengine - INFO - Epoch(val) [34][250/509] eta: 0:00:22 time: 0.0882 data_time: 0.0019 memory: 1004 2023/05/15 13:14:17 - mmengine - INFO - Epoch(val) [34][300/509] eta: 0:00:17 time: 0.0762 data_time: 0.0019 memory: 946 2023/05/15 13:14:21 - mmengine - INFO - Epoch(val) [34][350/509] eta: 0:00:13 time: 0.0796 data_time: 0.0019 memory: 970 2023/05/15 13:14:25 - mmengine - INFO - Epoch(val) [34][400/509] eta: 0:00:09 time: 0.0845 data_time: 0.0019 memory: 978 2023/05/15 13:14:29 - mmengine - INFO - Epoch(val) [34][450/509] eta: 0:00:04 time: 0.0851 data_time: 0.0018 memory: 991 2023/05/15 13:14:33 - mmengine - INFO - Epoch(val) [34][500/509] eta: 0:00:00 time: 0.0779 data_time: 0.0017 memory: 973 2023/05/15 13:15:13 - 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 | 0.9680 | 0.5627 | 0.7989 | 0.8911 | 0.6894 | 0.7907 | 0.8985 | 0.1311 | 0.9471 | 0.4981 | 0.8291 | 0.0483 | 0.9196 | 0.6758 | 0.8784 | 0.6830 | 0.7319 | 0.6583 | 0.5185 | 0.6904 | 0.9238 | 0.7559 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 13:15:13 - mmengine - INFO - Epoch(val) [34][509/509] car: 0.9680 bicycle: 0.5627 motorcycle: 0.7989 truck: 0.8911 bus: 0.6894 person: 0.7907 bicyclist: 0.8985 motorcyclist: 0.1311 road: 0.9471 parking: 0.4981 sidewalk: 0.8291 other-ground: 0.0483 building: 0.9196 fence: 0.6758 vegetation: 0.8784 trunck: 0.6830 terrian: 0.7319 pole: 0.6583 traffic-sign: 0.5185 miou: 0.6904 acc: 0.9238 acc_cls: 0.7559 data_time: 0.0017 time: 0.0799 2023/05/15 13:16:25 - mmengine - INFO - Epoch(train) [35][ 50/1196] lr: 8.0000e-05 eta: 0:55:20 time: 1.4287 data_time: 0.0041 memory: 4655 grad_norm: 0.0590 loss: 0.1541 loss_sem_seg: 0.1541 2023/05/15 13:17:54 - mmengine - INFO - Epoch(train) [35][ 100/1196] lr: 8.0000e-05 eta: 0:54:10 time: 1.7900 data_time: 0.0033 memory: 4754 grad_norm: 0.0606 loss: 0.1555 loss_sem_seg: 0.1555 2023/05/15 13:19:03 - mmengine - INFO - Epoch(train) [35][ 150/1196] lr: 8.0000e-05 eta: 0:52:59 time: 1.3845 data_time: 0.0032 memory: 4905 grad_norm: 0.0605 loss: 0.1442 loss_sem_seg: 0.1442 2023/05/15 13:20:12 - mmengine - INFO - Epoch(train) [35][ 200/1196] lr: 8.0000e-05 eta: 0:51:48 time: 1.3811 data_time: 0.0032 memory: 4237 grad_norm: 0.0600 loss: 0.1430 loss_sem_seg: 0.1430 2023/05/15 13:21:21 - mmengine - INFO - Epoch(train) [35][ 250/1196] lr: 8.0000e-05 eta: 0:50:37 time: 1.3775 data_time: 0.0032 memory: 4395 grad_norm: 0.0595 loss: 0.1483 loss_sem_seg: 0.1483 2023/05/15 13:22:31 - mmengine - INFO - Epoch(train) [35][ 300/1196] lr: 8.0000e-05 eta: 0:49:26 time: 1.3868 data_time: 0.0033 memory: 4701 grad_norm: 0.0611 loss: 0.1509 loss_sem_seg: 0.1509 2023/05/15 13:23:21 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 13:23:39 - mmengine - INFO - Epoch(train) [35][ 350/1196] lr: 8.0000e-05 eta: 0:48:15 time: 1.3734 data_time: 0.0035 memory: 5370 grad_norm: 0.0604 loss: 0.1504 loss_sem_seg: 0.1504 2023/05/15 13:24:47 - mmengine - INFO - Epoch(train) [35][ 400/1196] lr: 8.0000e-05 eta: 0:47:04 time: 1.3607 data_time: 0.0035 memory: 4575 grad_norm: 0.0607 loss: 0.1566 loss_sem_seg: 0.1566 2023/05/15 13:25:57 - mmengine - INFO - Epoch(train) [35][ 450/1196] lr: 8.0000e-05 eta: 0:45:53 time: 1.3842 data_time: 0.0033 memory: 4697 grad_norm: 0.0588 loss: 0.1593 loss_sem_seg: 0.1593 2023/05/15 13:27:05 - mmengine - INFO - Epoch(train) [35][ 500/1196] lr: 8.0000e-05 eta: 0:44:42 time: 1.3651 data_time: 0.0033 memory: 4677 grad_norm: 0.0568 loss: 0.1511 loss_sem_seg: 0.1511 2023/05/15 13:28:12 - mmengine - INFO - Epoch(train) [35][ 550/1196] lr: 8.0000e-05 eta: 0:43:31 time: 1.3516 data_time: 0.0033 memory: 4896 grad_norm: 0.0576 loss: 0.1554 loss_sem_seg: 0.1554 2023/05/15 13:29:22 - mmengine - INFO - Epoch(train) [35][ 600/1196] lr: 8.0000e-05 eta: 0:42:20 time: 1.3843 data_time: 0.0035 memory: 4832 grad_norm: 0.0579 loss: 0.1540 loss_sem_seg: 0.1540 2023/05/15 13:30:31 - mmengine - INFO - Epoch(train) [35][ 650/1196] lr: 8.0000e-05 eta: 0:41:09 time: 1.3840 data_time: 0.0035 memory: 4768 grad_norm: 0.0597 loss: 0.1520 loss_sem_seg: 0.1520 2023/05/15 13:31:39 - mmengine - INFO - Epoch(train) [35][ 700/1196] lr: 8.0000e-05 eta: 0:39:58 time: 1.3557 data_time: 0.0034 memory: 4756 grad_norm: 0.0558 loss: 0.1422 loss_sem_seg: 0.1422 2023/05/15 13:32:47 - mmengine - INFO - Epoch(train) [35][ 750/1196] lr: 8.0000e-05 eta: 0:38:47 time: 1.3691 data_time: 0.0035 memory: 5281 grad_norm: 0.0588 loss: 0.1444 loss_sem_seg: 0.1444 2023/05/15 13:33:56 - mmengine - INFO - Epoch(train) [35][ 800/1196] lr: 8.0000e-05 eta: 0:37:36 time: 1.3758 data_time: 0.0034 memory: 4748 grad_norm: 0.0531 loss: 0.1447 loss_sem_seg: 0.1447 2023/05/15 13:35:05 - mmengine - INFO - Epoch(train) [35][ 850/1196] lr: 8.0000e-05 eta: 0:36:25 time: 1.3791 data_time: 0.0034 memory: 5274 grad_norm: 0.0559 loss: 0.1540 loss_sem_seg: 0.1540 2023/05/15 13:36:14 - mmengine - INFO - Epoch(train) [35][ 900/1196] lr: 8.0000e-05 eta: 0:35:15 time: 1.3819 data_time: 0.0034 memory: 4688 grad_norm: 0.0582 loss: 0.1429 loss_sem_seg: 0.1429 2023/05/15 13:37:22 - mmengine - INFO - Epoch(train) [35][ 950/1196] lr: 8.0000e-05 eta: 0:34:04 time: 1.3591 data_time: 0.0034 memory: 4616 grad_norm: 0.0553 loss: 0.1387 loss_sem_seg: 0.1387 2023/05/15 13:38:31 - mmengine - INFO - Epoch(train) [35][1000/1196] lr: 8.0000e-05 eta: 0:32:53 time: 1.3730 data_time: 0.0034 memory: 4738 grad_norm: 0.0569 loss: 0.1436 loss_sem_seg: 0.1436 2023/05/15 13:39:39 - mmengine - INFO - Epoch(train) [35][1050/1196] lr: 8.0000e-05 eta: 0:31:42 time: 1.3740 data_time: 0.0034 memory: 4880 grad_norm: 0.0607 loss: 0.1517 loss_sem_seg: 0.1517 2023/05/15 13:40:49 - mmengine - INFO - Epoch(train) [35][1100/1196] lr: 8.0000e-05 eta: 0:30:31 time: 1.3851 data_time: 0.0033 memory: 4771 grad_norm: 0.0563 loss: 0.1434 loss_sem_seg: 0.1434 2023/05/15 13:41:57 - mmengine - INFO - Epoch(train) [35][1150/1196] lr: 8.0000e-05 eta: 0:29:20 time: 1.3696 data_time: 0.0033 memory: 4448 grad_norm: 0.0565 loss: 0.1442 loss_sem_seg: 0.1442 2023/05/15 13:42:58 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 13:42:58 - mmengine - INFO - Saving checkpoint at 35 epochs 2023/05/15 13:43:10 - mmengine - INFO - Epoch(val) [35][ 50/509] eta: 0:00:42 time: 0.0922 data_time: 0.0021 memory: 4839 2023/05/15 13:43:14 - mmengine - INFO - Epoch(val) [35][100/509] eta: 0:00:36 time: 0.0847 data_time: 0.0020 memory: 991 2023/05/15 13:43:18 - mmengine - INFO - Epoch(val) [35][150/509] eta: 0:00:31 time: 0.0825 data_time: 0.0019 memory: 994 2023/05/15 13:43:22 - mmengine - INFO - Epoch(val) [35][200/509] eta: 0:00:26 time: 0.0839 data_time: 0.0019 memory: 979 2023/05/15 13:43:27 - mmengine - INFO - Epoch(val) [35][250/509] eta: 0:00:22 time: 0.0883 data_time: 0.0019 memory: 1004 2023/05/15 13:43:31 - mmengine - INFO - Epoch(val) [35][300/509] eta: 0:00:17 time: 0.0769 data_time: 0.0020 memory: 946 2023/05/15 13:43:35 - mmengine - INFO - Epoch(val) [35][350/509] eta: 0:00:13 time: 0.0798 data_time: 0.0019 memory: 970 2023/05/15 13:43:39 - mmengine - INFO - Epoch(val) [35][400/509] eta: 0:00:09 time: 0.0848 data_time: 0.0019 memory: 978 2023/05/15 13:43:43 - mmengine - INFO - Epoch(val) [35][450/509] eta: 0:00:04 time: 0.0848 data_time: 0.0018 memory: 991 2023/05/15 13:43:47 - mmengine - INFO - Epoch(val) [35][500/509] eta: 0:00:00 time: 0.0782 data_time: 0.0017 memory: 973 2023/05/15 13:44:27 - mmengine - INFO - +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | classes | car | bicycle | motorcycle | truck | bus | person | bicyclist | motorcyclist | road | parking | sidewalk | other-ground | building | fence | vegetation | trunck | terrian | pole | traffic-sign | miou | acc | acc_cls | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ | results | 0.9698 | 0.5610 | 0.8029 | 0.9007 | 0.7184 | 0.7899 | 0.8972 | 0.1206 | 0.9461 | 0.5113 | 0.8279 | 0.0440 | 0.9180 | 0.6688 | 0.8768 | 0.6873 | 0.7272 | 0.6585 | 0.5175 | 0.6918 | 0.9230 | 0.7579 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 13:44:27 - mmengine - INFO - Epoch(val) [35][509/509] car: 0.9698 bicycle: 0.5610 motorcycle: 0.8029 truck: 0.9007 bus: 0.7184 person: 0.7899 bicyclist: 0.8972 motorcyclist: 0.1206 road: 0.9461 parking: 0.5113 sidewalk: 0.8279 other-ground: 0.0440 building: 0.9180 fence: 0.6688 vegetation: 0.8768 trunck: 0.6873 terrian: 0.7272 pole: 0.6585 traffic-sign: 0.5175 miou: 0.6918 acc: 0.9230 acc_cls: 0.7579 data_time: 0.0017 time: 0.0801 2023/05/15 13:45:36 - mmengine - INFO - Epoch(train) [36][ 50/1196] lr: 8.0000e-05 eta: 0:27:04 time: 1.3823 data_time: 0.0041 memory: 4832 grad_norm: 0.0545 loss: 0.1449 loss_sem_seg: 0.1449 2023/05/15 13:46:47 - mmengine - INFO - Epoch(train) [36][ 100/1196] lr: 8.0000e-05 eta: 0:25:53 time: 1.4116 data_time: 0.0035 memory: 4826 grad_norm: 0.0561 loss: 0.1396 loss_sem_seg: 0.1396 2023/05/15 13:47:42 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 13:47:55 - mmengine - INFO - Epoch(train) [36][ 150/1196] lr: 8.0000e-05 eta: 0:24:42 time: 1.3564 data_time: 0.0034 memory: 5073 grad_norm: 0.0537 loss: 0.1454 loss_sem_seg: 0.1454 2023/05/15 13:49:25 - mmengine - INFO - Epoch(train) [36][ 200/1196] lr: 8.0000e-05 eta: 0:23:31 time: 1.8121 data_time: 0.0033 memory: 4424 grad_norm: 0.0616 loss: 0.1517 loss_sem_seg: 0.1517 2023/05/15 13:50:34 - mmengine - INFO - Epoch(train) [36][ 250/1196] lr: 8.0000e-05 eta: 0:22:20 time: 1.3721 data_time: 0.0032 memory: 4672 grad_norm: 0.0605 loss: 0.1473 loss_sem_seg: 0.1473 2023/05/15 13:51:42 - mmengine - INFO - Epoch(train) [36][ 300/1196] lr: 8.0000e-05 eta: 0:21:10 time: 1.3692 data_time: 0.0033 memory: 4595 grad_norm: 0.0565 loss: 0.1438 loss_sem_seg: 0.1438 2023/05/15 13:52:51 - mmengine - INFO - Epoch(train) [36][ 350/1196] lr: 8.0000e-05 eta: 0:19:59 time: 1.3749 data_time: 0.0032 memory: 4933 grad_norm: 0.0625 loss: 0.1478 loss_sem_seg: 0.1478 2023/05/15 13:54:00 - mmengine - INFO - Epoch(train) [36][ 400/1196] lr: 8.0000e-05 eta: 0:18:48 time: 1.3712 data_time: 0.0033 memory: 4944 grad_norm: 0.0613 loss: 0.1468 loss_sem_seg: 0.1468 2023/05/15 13:55:08 - mmengine - INFO - Epoch(train) [36][ 450/1196] lr: 8.0000e-05 eta: 0:17:37 time: 1.3743 data_time: 0.0033 memory: 4918 grad_norm: 0.0586 loss: 0.1448 loss_sem_seg: 0.1448 2023/05/15 13:56:18 - mmengine - INFO - Epoch(train) [36][ 500/1196] lr: 8.0000e-05 eta: 0:16:26 time: 1.3874 data_time: 0.0035 memory: 4976 grad_norm: 0.0565 loss: 0.1394 loss_sem_seg: 0.1394 2023/05/15 13:57:26 - mmengine - INFO - Epoch(train) [36][ 550/1196] lr: 8.0000e-05 eta: 0:15:15 time: 1.3583 data_time: 0.0035 memory: 5257 grad_norm: 0.0567 loss: 0.1501 loss_sem_seg: 0.1501 2023/05/15 13:58:37 - mmengine - INFO - Epoch(train) [36][ 600/1196] lr: 8.0000e-05 eta: 0:14:04 time: 1.4276 data_time: 0.0034 memory: 4951 grad_norm: 0.0561 loss: 0.1522 loss_sem_seg: 0.1522 2023/05/15 14:00:05 - mmengine - INFO - Epoch(train) [36][ 650/1196] lr: 8.0000e-05 eta: 0:12:54 time: 1.7595 data_time: 0.0036 memory: 4732 grad_norm: 0.0554 loss: 0.1521 loss_sem_seg: 0.1521 2023/05/15 14:01:14 - mmengine - INFO - Epoch(train) [36][ 700/1196] lr: 8.0000e-05 eta: 0:11:43 time: 1.3856 data_time: 0.0034 memory: 4516 grad_norm: 0.0595 loss: 0.1572 loss_sem_seg: 0.1572 2023/05/15 14:02:23 - mmengine - INFO - Epoch(train) [36][ 750/1196] lr: 8.0000e-05 eta: 0:10:32 time: 1.3643 data_time: 0.0035 memory: 4757 grad_norm: 0.0583 loss: 0.1448 loss_sem_seg: 0.1448 2023/05/15 14:03:32 - mmengine - INFO - Epoch(train) [36][ 800/1196] lr: 8.0000e-05 eta: 0:09:21 time: 1.3946 data_time: 0.0034 memory: 4541 grad_norm: 0.0598 loss: 0.1469 loss_sem_seg: 0.1469 2023/05/15 14:04:41 - mmengine - INFO - Epoch(train) [36][ 850/1196] lr: 8.0000e-05 eta: 0:08:10 time: 1.3709 data_time: 0.0034 memory: 5030 grad_norm: 0.0583 loss: 0.1401 loss_sem_seg: 0.1401 2023/05/15 14:05:51 - mmengine - INFO - Epoch(train) [36][ 900/1196] lr: 8.0000e-05 eta: 0:06:59 time: 1.3923 data_time: 0.0034 memory: 4805 grad_norm: 0.0597 loss: 0.1505 loss_sem_seg: 0.1505 2023/05/15 14:06:59 - mmengine - INFO - Epoch(train) [36][ 950/1196] lr: 8.0000e-05 eta: 0:05:48 time: 1.3766 data_time: 0.0035 memory: 4628 grad_norm: 0.0602 loss: 0.1553 loss_sem_seg: 0.1553 2023/05/15 14:08:07 - mmengine - INFO - Epoch(train) [36][1000/1196] lr: 8.0000e-05 eta: 0:04:37 time: 1.3595 data_time: 0.0034 memory: 4678 grad_norm: 0.0629 loss: 0.1545 loss_sem_seg: 0.1545 2023/05/15 14:09:16 - mmengine - INFO - Epoch(train) [36][1050/1196] lr: 8.0000e-05 eta: 0:03:26 time: 1.3692 data_time: 0.0034 memory: 4537 grad_norm: 0.0578 loss: 0.1481 loss_sem_seg: 0.1481 2023/05/15 14:10:24 - mmengine - INFO - Epoch(train) [36][1100/1196] lr: 8.0000e-05 eta: 0:02:16 time: 1.3720 data_time: 0.0034 memory: 4948 grad_norm: 0.0603 loss: 0.1463 loss_sem_seg: 0.1463 2023/05/15 14:11:21 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 14:11:34 - mmengine - INFO - Epoch(train) [36][1150/1196] lr: 8.0000e-05 eta: 0:01:05 time: 1.3997 data_time: 0.0035 memory: 4703 grad_norm: 0.0560 loss: 0.1498 loss_sem_seg: 0.1498 2023/05/15 14:12:38 - mmengine - INFO - Exp name: minkunet34_w32_minkowski_8xb2-lpmix-3x_semantickitti_20230514_202236 2023/05/15 14:12:38 - mmengine - INFO - Saving checkpoint at 36 epochs 2023/05/15 14:12:50 - mmengine - INFO - Epoch(val) [36][ 50/509] eta: 0:00:42 time: 0.0936 data_time: 0.0022 memory: 4646 2023/05/15 14:12:54 - mmengine - INFO - Epoch(val) [36][100/509] eta: 0:00:36 time: 0.0855 data_time: 0.0020 memory: 991 2023/05/15 14:12:58 - mmengine - INFO - Epoch(val) [36][150/509] eta: 0:00:31 time: 0.0837 data_time: 0.0020 memory: 994 2023/05/15 14:13:02 - mmengine - INFO - Epoch(val) [36][200/509] eta: 0:00:26 time: 0.0849 data_time: 0.0020 memory: 979 2023/05/15 14:13:07 - mmengine - INFO - Epoch(val) [36][250/509] eta: 0:00:22 time: 0.0889 data_time: 0.0020 memory: 1004 2023/05/15 14:13:11 - mmengine - INFO - Epoch(val) [36][300/509] eta: 0:00:17 time: 0.0771 data_time: 0.0019 memory: 946 2023/05/15 14:13:15 - mmengine - INFO - Epoch(val) [36][350/509] eta: 0:00:13 time: 0.0803 data_time: 0.0019 memory: 970 2023/05/15 14:13:19 - mmengine - INFO - Epoch(val) [36][400/509] eta: 0:00:09 time: 0.0855 data_time: 0.0019 memory: 978 2023/05/15 14:13:23 - mmengine - INFO - Epoch(val) [36][450/509] eta: 0:00:05 time: 0.0851 data_time: 0.0019 memory: 991 2023/05/15 14:13:27 - mmengine - INFO - Epoch(val) [36][500/509] eta: 0:00:00 time: 0.0790 data_time: 0.0017 memory: 973 2023/05/15 14:14:07 - 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 | 0.9678 | 0.5634 | 0.7971 | 0.9005 | 0.6952 | 0.7916 | 0.8962 | 0.1394 | 0.9468 | 0.5050 | 0.8288 | 0.0371 | 0.9174 | 0.6683 | 0.8802 | 0.6799 | 0.7365 | 0.6574 | 0.5185 | 0.6909 | 0.9242 | 0.7559 | +---------+--------+---------+------------+--------+--------+--------+-----------+--------------+--------+---------+----------+--------------+----------+--------+------------+--------+---------+--------+--------------+--------+--------+---------+ 2023/05/15 14:14:07 - mmengine - INFO - Epoch(val) [36][509/509] car: 0.9678 bicycle: 0.5634 motorcycle: 0.7971 truck: 0.9005 bus: 0.6952 person: 0.7916 bicyclist: 0.8962 motorcyclist: 0.1394 road: 0.9468 parking: 0.5050 sidewalk: 0.8288 other-ground: 0.0371 building: 0.9174 fence: 0.6683 vegetation: 0.8802 trunck: 0.6799 terrian: 0.7365 pole: 0.6574 traffic-sign: 0.5185 miou: 0.6909 acc: 0.9242 acc_cls: 0.7559 data_time: 0.0017 time: 0.0804