2023/05/24 00:15:49 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.8.13 (default, Oct 21 2022, 23:50:54) [GCC 11.2.0] CUDA available: True numpy_random_seed: 835667528 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/petrelfs/share/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (GCC) 5.4.0 PyTorch: 1.11.0+cu113 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.12.0+cu113 OpenCV: 4.6.0 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: slurm Distributed training: True GPU number: 8 ------------------------------------------------------------ 2023/05/24 00:15:50 - mmengine - INFO - Config: 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 = '../mmdetection3d_1/logs/bevfusion_only_lidar_valid_flag/epoch_20.pth' resume = False custom_imports = dict( imports=['projects.BEVFusion.bevfusion'], allow_failed_imports=False) voxel_size = [0.075, 0.075, 0.2] point_cloud_range = [-54.0, -54.0, -5.0, 54.0, 54.0, 3.0] class_names = [ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ] metainfo = dict(classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]) dataset_type = 'NuScenesDataset' data_root = 'data/nuscenes/' data_prefix = dict( pts='samples/LIDAR_TOP', CAM_FRONT='samples/CAM_FRONT', CAM_FRONT_LEFT='samples/CAM_FRONT_LEFT', CAM_FRONT_RIGHT='samples/CAM_FRONT_RIGHT', CAM_BACK='samples/CAM_BACK', CAM_BACK_RIGHT='samples/CAM_BACK_RIGHT', CAM_BACK_LEFT='samples/CAM_BACK_LEFT', sweeps='sweeps/LIDAR_TOP') input_modality = dict(use_lidar=True, use_camera=True) backend_args = None model = dict( type='BEVFusion', data_preprocessor=dict( type='Det3DDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], bgr_to_rgb=False, pad_size_divisor=32, voxelize_cfg=dict( max_num_points=10, point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0], voxel_size=[0.075, 0.075, 0.2], max_voxels=[120000, 160000], voxelize_reduce=True)), img_backbone=dict( type='mmdet.SwinTransformer', embed_dims=96, depths=[2, 2, 6, 2], num_heads=[3, 6, 12, 24], window_size=7, mlp_ratio=4, qkv_bias=True, qk_scale=None, drop_rate=0.0, attn_drop_rate=0.0, drop_path_rate=0.2, patch_norm=True, out_indices=[1, 2, 3], with_cp=False, convert_weights=True, init_cfg=dict( type='Pretrained', checkpoint= '../mmdetection3d/checkpoints/swint-nuimages-pretrained.pth')), img_neck=dict( type='GeneralizedLSSFPN', in_channels=[192, 384, 768], out_channels=256, start_level=0, num_outs=3, norm_cfg=dict(type='BN2d', requires_grad=True), act_cfg=dict(type='ReLU', inplace=True), upsample_cfg=dict(mode='bilinear', align_corners=False)), vtransform=dict( type='DepthLSSTransform', in_channels=256, out_channels=80, image_size=[256, 704], feature_size=[32, 88], xbound=[-54.0, 54.0, 0.3], ybound=[-54.0, 54.0, 0.3], zbound=[-10.0, 10.0, 20.0], dbound=[1.0, 60.0, 0.5], downsample=2), pts_voxel_encoder=dict(type='HardSimpleVFE', num_features=5), pts_middle_encoder=dict( type='BEVFusionSparseEncoder', in_channels=5, sparse_shape=[1440, 1440, 41], order=('conv', 'norm', 'act'), norm_cfg=dict(type='BN1d', eps=0.001, momentum=0.01), encoder_channels=((16, 16, 32), (32, 32, 64), (64, 64, 128), (128, 128)), encoder_paddings=((0, 0, 1), (0, 0, 1), (0, 0, (1, 1, 0)), (0, 0)), block_type='basicblock'), fusion_layer=dict( type='ConvFuser', in_channels=[80, 256], out_channels=256), pts_backbone=dict( type='SECOND', in_channels=256, out_channels=[128, 256], layer_nums=[5, 5], layer_strides=[1, 2], norm_cfg=dict(type='BN', eps=0.001, momentum=0.01), conv_cfg=dict(type='Conv2d', bias=False)), pts_neck=dict( type='SECONDFPN', in_channels=[128, 256], out_channels=[256, 256], upsample_strides=[1, 2], norm_cfg=dict(type='BN', eps=0.001, momentum=0.01), upsample_cfg=dict(type='deconv', bias=False), use_conv_for_no_stride=True), bbox_head=dict( type='TransFusionHead', num_proposals=200, auxiliary=True, in_channels=512, hidden_channel=128, num_classes=10, nms_kernel_size=3, bn_momentum=0.1, num_decoder_layers=1, decoder_layer=dict( type='TransformerDecoderLayer', self_attn_cfg=dict(embed_dims=128, num_heads=8, dropout=0.1), cross_attn_cfg=dict(embed_dims=128, num_heads=8, dropout=0.1), ffn_cfg=dict( embed_dims=128, feedforward_channels=256, num_fcs=2, ffn_drop=0.1, act_cfg=dict(type='ReLU', inplace=True)), norm_cfg=dict(type='LN'), pos_encoding_cfg=dict(input_channel=2, num_pos_feats=128)), train_cfg=dict( dataset='nuScenes', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0], grid_size=[1440, 1440, 41], voxel_size=[0.075, 0.075, 0.2], out_size_factor=8, gaussian_overlap=0.1, min_radius=2, pos_weight=-1, code_weights=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2], assigner=dict( type='HungarianAssigner3D', iou_calculator=dict(type='BboxOverlaps3D', coordinate='lidar'), cls_cost=dict( type='mmdet.FocalLossCost', gamma=2.0, alpha=0.25, weight=0.15), reg_cost=dict(type='BBoxBEVL1Cost', weight=0.25), iou_cost=dict(type='IoU3DCost', weight=0.25))), test_cfg=dict( dataset='nuScenes', grid_size=[1440, 1440, 41], out_size_factor=8, voxel_size=[0.075, 0.075], pc_range=[-54.0, -54.0], nms_type=None), common_heads=dict( center=[2, 2], height=[1, 2], dim=[3, 2], rot=[2, 2], vel=[2, 2]), bbox_coder=dict( type='TransFusionBBoxCoder', pc_range=[-54.0, -54.0], post_center_range=[-61.2, -61.2, -10.0, 61.2, 61.2, 10.0], score_threshold=0.0, out_size_factor=8, voxel_size=[0.075, 0.075], code_size=10), loss_cls=dict( type='mmdet.FocalLoss', use_sigmoid=True, gamma=2.0, alpha=0.25, reduction='mean', loss_weight=1.0), loss_heatmap=dict( type='mmdet.GaussianFocalLoss', reduction='mean', loss_weight=1.0), loss_bbox=dict( type='mmdet.L1Loss', reduction='mean', loss_weight=0.25))) db_sampler = dict( data_root='data/nuscenes/', info_path='data/nuscenes/nuscenes_dbinfos_train.pkl', rate=1.0, prepare=dict( filter_by_difficulty=[-1], filter_by_min_points=dict( car=5, truck=5, bus=5, trailer=5, construction_vehicle=5, traffic_cone=5, barrier=5, motorcycle=5, bicycle=5, pedestrian=5)), classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ], sample_groups=dict( car=2, truck=3, construction_vehicle=7, bus=4, trailer=6, barrier=2, motorcycle=6, bicycle=6, pedestrian=2, traffic_cone=2), points_loader=dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=[0, 1, 2, 3, 4])) train_pipeline = [ dict( type='BEVLoadMultiViewImageFromFiles', to_float32=True, color_type='color', backend_args=None), dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True, with_attr_label=False), dict( type='ImageAug3D', final_dim=[256, 704], resize_lim=[0.38, 0.55], bot_pct_lim=[0.0, 0.0], rot_lim=[-5.4, 5.4], rand_flip=True, is_train=True), dict( type='BEVFusionGlobalRotScaleTrans', scale_ratio_range=[0.9, 1.1], rot_range=[-0.78539816, 0.78539816], translation_std=0.5), dict(type='BEVFusionRandomFlip3D'), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='ObjectRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='ObjectNameFilter', classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), dict( type='GridMask', use_h=True, use_w=True, max_epoch=6, rotate=1, offset=False, ratio=0.5, mode=1, prob=0.0, fixed_prob=True), dict(type='PointShuffle'), dict( type='Pack3DDetInputs', keys=[ 'points', 'img', 'gt_bboxes_3d', 'gt_labels_3d', 'gt_bboxes', 'gt_labels' ], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path', 'transformation_3d_flow', 'pcd_rotation', 'pcd_scale_factor', 'pcd_trans', 'img_aug_matrix', 'lidar_aug_matrix' ]) ] test_pipeline = [ dict( type='BEVLoadMultiViewImageFromFiles', to_float32=True, color_type='color', backend_args=None), dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='ImageAug3D', final_dim=[256, 704], resize_lim=[0.48, 0.48], bot_pct_lim=[0.0, 0.0], rot_lim=[0.0, 0.0], rand_flip=False, is_train=False), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='Pack3DDetInputs', keys=['img', 'points', 'gt_bboxes_3d', 'gt_labels_3d'], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path' ]) ] train_dataloader = dict( batch_size=4, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='CBGSDataset', dataset=dict( type='NuScenesDataset', data_root='data/nuscenes/', ann_file='nuscenes_infos_train.pkl', pipeline=[ dict( type='BEVLoadMultiViewImageFromFiles', to_float32=True, color_type='color', backend_args=None), dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True, with_attr_label=False), dict( type='ImageAug3D', final_dim=[256, 704], resize_lim=[0.38, 0.55], bot_pct_lim=[0.0, 0.0], rot_lim=[-5.4, 5.4], rand_flip=True, is_train=True), dict( type='BEVFusionGlobalRotScaleTrans', scale_ratio_range=[0.9, 1.1], rot_range=[-0.78539816, 0.78539816], translation_std=0.5), dict(type='BEVFusionRandomFlip3D'), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='ObjectRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='ObjectNameFilter', classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), dict( type='GridMask', use_h=True, use_w=True, max_epoch=6, rotate=1, offset=False, ratio=0.5, mode=1, prob=0.0, fixed_prob=True), dict(type='PointShuffle'), dict( type='Pack3DDetInputs', keys=[ 'points', 'img', 'gt_bboxes_3d', 'gt_labels_3d', 'gt_bboxes', 'gt_labels' ], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path', 'transformation_3d_flow', 'pcd_rotation', 'pcd_scale_factor', 'pcd_trans', 'img_aug_matrix', 'lidar_aug_matrix' ]) ], metainfo=dict(classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), modality=dict(use_lidar=True, use_camera=True), test_mode=False, data_prefix=dict( pts='samples/LIDAR_TOP', CAM_FRONT='samples/CAM_FRONT', CAM_FRONT_LEFT='samples/CAM_FRONT_LEFT', CAM_FRONT_RIGHT='samples/CAM_FRONT_RIGHT', CAM_BACK='samples/CAM_BACK', CAM_BACK_RIGHT='samples/CAM_BACK_RIGHT', CAM_BACK_LEFT='samples/CAM_BACK_LEFT', sweeps='sweeps/LIDAR_TOP'), use_valid_flag=True, box_type_3d='LiDAR'))) val_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='NuScenesDataset', data_root='data/nuscenes/', ann_file='nuscenes_infos_val.pkl', pipeline=[ dict( type='BEVLoadMultiViewImageFromFiles', to_float32=True, color_type='color', backend_args=None), dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='ImageAug3D', final_dim=[256, 704], resize_lim=[0.48, 0.48], bot_pct_lim=[0.0, 0.0], rot_lim=[0.0, 0.0], rand_flip=False, is_train=False), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='Pack3DDetInputs', keys=['img', 'points', 'gt_bboxes_3d', 'gt_labels_3d'], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path' ]) ], metainfo=dict(classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), modality=dict(use_lidar=True, use_camera=True), data_prefix=dict( pts='samples/LIDAR_TOP', CAM_FRONT='samples/CAM_FRONT', CAM_FRONT_LEFT='samples/CAM_FRONT_LEFT', CAM_FRONT_RIGHT='samples/CAM_FRONT_RIGHT', CAM_BACK='samples/CAM_BACK', CAM_BACK_RIGHT='samples/CAM_BACK_RIGHT', CAM_BACK_LEFT='samples/CAM_BACK_LEFT', sweeps='sweeps/LIDAR_TOP'), test_mode=True, box_type_3d='LiDAR', backend_args=None)) test_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='NuScenesDataset', data_root='data/nuscenes/', ann_file='nuscenes_infos_val.pkl', pipeline=[ dict( type='BEVLoadMultiViewImageFromFiles', to_float32=True, color_type='color', backend_args=None), dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='ImageAug3D', final_dim=[256, 704], resize_lim=[0.48, 0.48], bot_pct_lim=[0.0, 0.0], rot_lim=[0.0, 0.0], rand_flip=False, is_train=False), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='Pack3DDetInputs', keys=['img', 'points', 'gt_bboxes_3d', 'gt_labels_3d'], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path' ]) ], metainfo=dict(classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), modality=dict(use_lidar=True, use_camera=True), data_prefix=dict( pts='samples/LIDAR_TOP', CAM_FRONT='samples/CAM_FRONT', CAM_FRONT_LEFT='samples/CAM_FRONT_LEFT', CAM_FRONT_RIGHT='samples/CAM_FRONT_RIGHT', CAM_BACK='samples/CAM_BACK', CAM_BACK_RIGHT='samples/CAM_BACK_RIGHT', CAM_BACK_LEFT='samples/CAM_BACK_LEFT', sweeps='sweeps/LIDAR_TOP'), test_mode=True, box_type_3d='LiDAR', backend_args=None)) val_evaluator = dict( type='NuScenesMetric', data_root='data/nuscenes/', ann_file='data/nuscenes/nuscenes_infos_val.pkl', metric='bbox', backend_args=None) test_evaluator = dict( type='NuScenesMetric', data_root='data/nuscenes/', ann_file='data/nuscenes/nuscenes_infos_val.pkl', metric='bbox', backend_args=None) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='Det3DLocalVisualizer', vis_backends=[dict(type='LocalVisBackend')], name='visualizer') param_scheduler = [ dict( type='LinearLR', start_factor=0.33333333, by_epoch=False, begin=0, end=500), dict( type='CosineAnnealingLR', begin=0, T_max=6, end=6, by_epoch=True, eta_min_ratio=0.001, convert_to_iter_based=True), dict( type='CosineAnnealingMomentum', eta_min=0.8947368421052632, begin=0, end=2.4, by_epoch=True, convert_to_iter_based=True), dict( type='CosineAnnealingMomentum', eta_min=1, begin=2.4, end=6, by_epoch=True, convert_to_iter_based=True) ] train_cfg = dict(by_epoch=True, max_epochs=6, val_interval=1) val_cfg = dict() test_cfg = dict() optim_wrapper = dict( type='OptimWrapper', optimizer=dict(type='AdamW', lr=0.0002, weight_decay=0.01), clip_grad=dict(max_norm=35, norm_type=2)) auto_scale_lr = dict(enable=False, base_batch_size=32) launcher = 'slurm' work_dir = 'logs/bevfusion_lidar_cam_bugsweeps_iterbased_coslr' 2023/05/24 00:15:54 - mmengine - INFO - Loads checkpoint by local backend from path: ../mmdetection3d/checkpoints/swint-nuimages-pretrained.pth 2023/05/24 00:15:54 - 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 -------------------- 2023/05/24 00:17:31 - mmengine - INFO - ------------------------------ 2023/05/24 00:17:31 - mmengine - INFO - The length of the dataset: 28130 2023/05/24 00:17:31 - mmengine - INFO - The number of instances per category in the dataset: +----------------------+--------+ | category | number | +----------------------+--------+ | car | 413318 | | truck | 72815 | | construction_vehicle | 11993 | | bus | 13163 | | trailer | 20701 | | barrier | 125095 | | motorcycle | 10109 | | bicycle | 9478 | | pedestrian | 185847 | | traffic_cone | 82362 | +----------------------+--------+ 2023/05/24 00:17:59 - mmengine - INFO - ------------------------------ 2023/05/24 00:17:59 - mmengine - INFO - The length of the dataset: 6019 2023/05/24 00:17:59 - mmengine - INFO - The number of instances per category in the dataset: +----------------------+--------+ | category | number | +----------------------+--------+ | car | 80004 | | truck | 15704 | | construction_vehicle | 2678 | | bus | 3158 | | trailer | 4159 | | barrier | 26992 | | motorcycle | 2508 | | bicycle | 2381 | | pedestrian | 34347 | | traffic_cone | 15597 | +----------------------+--------+ 2023/05/24 00:18:01 - mmengine - INFO - Loads checkpoint by local backend from path: ../mmdetection3d/checkpoints/swint-nuimages-pretrained.pth 2023/05/24 00:18:03 - mmengine - INFO - Load checkpoint from ../mmdetection3d_1/logs/bevfusion_only_lidar_valid_flag/epoch_20.pth 2023/05/24 00:18:03 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/05/24 00:18:03 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/05/24 00:18:03 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/zhangjingwei/mmdetection3d_2/logs/bevfusion_lidar_cam_bugsweeps_iterbased_coslr. 2023/05/24 00:19:43 - mmengine - INFO - Epoch(train) [1][ 50/3862] lr: 7.9759e-05 eta: 12:53:59 time: 2.0085 data_time: 0.0662 memory: 22002 grad_norm: 15.2823 loss: 5.5649 loss_heatmap: 1.9695 layer_-1_loss_cls: 0.2774 layer_-1_loss_bbox: 3.3181 matched_ious: 0.4611 2023/05/24 00:20:49 - mmengine - INFO - Epoch(train) [1][ 100/3862] lr: 9.3115e-05 eta: 10:41:17 time: 1.3270 data_time: 0.0209 memory: 21797 grad_norm: 3.9770 loss: 1.8153 loss_heatmap: 0.7769 layer_-1_loss_cls: 0.1213 layer_-1_loss_bbox: 0.9172 matched_ious: 0.5014 2023/05/24 00:21:56 - mmengine - INFO - Epoch(train) [1][ 150/3862] lr: 1.0647e-04 eta: 9:56:31 time: 1.3285 data_time: 0.0220 memory: 21750 grad_norm: 3.3250 loss: 1.5140 loss_heatmap: 0.6744 layer_-1_loss_cls: 0.1050 layer_-1_loss_bbox: 0.7345 matched_ious: 0.5557 2023/05/24 00:23:03 - mmengine - INFO - Epoch(train) [1][ 200/3862] lr: 1.1982e-04 eta: 9:34:30 time: 1.3381 data_time: 0.0227 memory: 22121 grad_norm: 2.6297 loss: 1.4245 loss_heatmap: 0.6356 layer_-1_loss_cls: 0.0983 layer_-1_loss_bbox: 0.6906 matched_ious: 0.5233 2023/05/24 00:24:11 - mmengine - INFO - Epoch(train) [1][ 250/3862] lr: 1.3316e-04 eta: 9:23:34 time: 1.3739 data_time: 0.0232 memory: 21860 grad_norm: 2.2764 loss: 1.3248 loss_heatmap: 0.6009 layer_-1_loss_cls: 0.0941 layer_-1_loss_bbox: 0.6298 matched_ious: 0.5653 2023/05/24 00:25:18 - mmengine - INFO - Epoch(train) [1][ 300/3862] lr: 1.4650e-04 eta: 9:13:37 time: 1.3378 data_time: 0.0236 memory: 22122 grad_norm: 2.3316 loss: 1.3196 loss_heatmap: 0.5930 layer_-1_loss_cls: 0.0927 layer_-1_loss_bbox: 0.6339 matched_ious: 0.5424 2023/05/24 00:26:25 - mmengine - INFO - Epoch(train) [1][ 350/3862] lr: 1.5983e-04 eta: 9:05:41 time: 1.3286 data_time: 0.0231 memory: 22019 grad_norm: 2.2623 loss: 1.2910 loss_heatmap: 0.5869 layer_-1_loss_cls: 0.0916 layer_-1_loss_bbox: 0.6125 matched_ious: 0.5495 2023/05/24 00:27:32 - mmengine - INFO - Epoch(train) [1][ 400/3862] lr: 1.7315e-04 eta: 9:00:04 time: 1.3415 data_time: 0.0232 memory: 21851 grad_norm: 2.0971 loss: 1.3136 loss_heatmap: 0.5913 layer_-1_loss_cls: 0.0923 layer_-1_loss_bbox: 0.6300 matched_ious: 0.5397 2023/05/24 00:28:39 - mmengine - INFO - Epoch(train) [1][ 450/3862] lr: 1.8647e-04 eta: 8:55:14 time: 1.3365 data_time: 0.0233 memory: 21840 grad_norm: 2.1683 loss: 1.2983 loss_heatmap: 0.5786 layer_-1_loss_cls: 0.0897 layer_-1_loss_bbox: 0.6300 matched_ious: 0.5498 2023/05/24 00:29:46 - mmengine - INFO - Epoch(train) [1][ 500/3862] lr: 1.9977e-04 eta: 8:51:37 time: 1.3486 data_time: 0.0237 memory: 21685 grad_norm: 2.0620 loss: 1.2965 loss_heatmap: 0.5778 layer_-1_loss_cls: 0.0896 layer_-1_loss_bbox: 0.6291 matched_ious: 0.5466 2023/05/24 00:30:53 - mmengine - INFO - Epoch(train) [1][ 550/3862] lr: 1.9972e-04 eta: 8:48:07 time: 1.3394 data_time: 0.0237 memory: 22087 grad_norm: 1.7368 loss: 1.2642 loss_heatmap: 0.5758 layer_-1_loss_cls: 0.0898 layer_-1_loss_bbox: 0.5986 matched_ious: 0.5330 2023/05/24 00:32:00 - mmengine - INFO - Epoch(train) [1][ 600/3862] lr: 1.9967e-04 eta: 8:44:47 time: 1.3315 data_time: 0.0226 memory: 21719 grad_norm: 1.8174 loss: 1.2748 loss_heatmap: 0.5772 layer_-1_loss_cls: 0.0895 layer_-1_loss_bbox: 0.6081 matched_ious: 0.5463 2023/05/24 00:33:06 - mmengine - INFO - Epoch(train) [1][ 650/3862] lr: 1.9961e-04 eta: 8:41:44 time: 1.3296 data_time: 0.0225 memory: 21802 grad_norm: 1.7473 loss: 1.2650 loss_heatmap: 0.5800 layer_-1_loss_cls: 0.0901 layer_-1_loss_bbox: 0.5950 matched_ious: 0.5603 2023/05/24 00:34:14 - mmengine - INFO - Epoch(train) [1][ 700/3862] lr: 1.9955e-04 eta: 8:39:42 time: 1.3569 data_time: 0.0233 memory: 21781 grad_norm: 1.7041 loss: 1.2430 loss_heatmap: 0.5655 layer_-1_loss_cls: 0.0881 layer_-1_loss_bbox: 0.5893 matched_ious: 0.5524 2023/05/24 00:35:21 - mmengine - INFO - Epoch(train) [1][ 750/3862] lr: 1.9949e-04 eta: 8:37:08 time: 1.3314 data_time: 0.0234 memory: 21843 grad_norm: 1.8629 loss: 1.2741 loss_heatmap: 0.5729 layer_-1_loss_cls: 0.0881 layer_-1_loss_bbox: 0.6131 matched_ious: 0.5717 2023/05/24 00:36:28 - mmengine - INFO - Epoch(train) [1][ 800/3862] lr: 1.9941e-04 eta: 8:34:56 time: 1.3391 data_time: 0.0228 memory: 21798 grad_norm: 1.5545 loss: 1.2420 loss_heatmap: 0.5647 layer_-1_loss_cls: 0.0884 layer_-1_loss_bbox: 0.5888 matched_ious: 0.5691 2023/05/24 00:37:35 - mmengine - INFO - Epoch(train) [1][ 850/3862] lr: 1.9934e-04 eta: 8:32:59 time: 1.3441 data_time: 0.0234 memory: 21776 grad_norm: 1.5684 loss: 1.2305 loss_heatmap: 0.5612 layer_-1_loss_cls: 0.0877 layer_-1_loss_bbox: 0.5816 matched_ious: 0.5762 2023/05/24 00:38:42 - mmengine - INFO - Epoch(train) [1][ 900/3862] lr: 1.9926e-04 eta: 8:30:58 time: 1.3365 data_time: 0.0234 memory: 21722 grad_norm: 1.7459 loss: 1.2642 loss_heatmap: 0.5731 layer_-1_loss_cls: 0.0898 layer_-1_loss_bbox: 0.6013 matched_ious: 0.5398 2023/05/24 00:39:49 - mmengine - INFO - Epoch(train) [1][ 950/3862] lr: 1.9917e-04 eta: 8:29:08 time: 1.3420 data_time: 0.0234 memory: 21934 grad_norm: 1.5901 loss: 1.2426 loss_heatmap: 0.5661 layer_-1_loss_cls: 0.0879 layer_-1_loss_bbox: 0.5886 matched_ious: 0.5678 2023/05/24 00:40:56 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 00:40:56 - mmengine - INFO - Epoch(train) [1][1000/3862] lr: 1.9909e-04 eta: 8:27:28 time: 1.3465 data_time: 0.0233 memory: 21921 grad_norm: 1.6840 loss: 1.2562 loss_heatmap: 0.5672 layer_-1_loss_cls: 0.0890 layer_-1_loss_bbox: 0.5999 matched_ious: 0.5471 2023/05/24 00:42:03 - mmengine - INFO - Epoch(train) [1][1050/3862] lr: 1.9899e-04 eta: 8:25:46 time: 1.3417 data_time: 0.0235 memory: 22103 grad_norm: 1.4681 loss: 1.2309 loss_heatmap: 0.5610 layer_-1_loss_cls: 0.0887 layer_-1_loss_bbox: 0.5813 matched_ious: 0.5539 2023/05/24 00:43:10 - mmengine - INFO - Epoch(train) [1][1100/3862] lr: 1.9889e-04 eta: 8:24:02 time: 1.3357 data_time: 0.0229 memory: 21849 grad_norm: 1.4429 loss: 1.2514 loss_heatmap: 0.5671 layer_-1_loss_cls: 0.0887 layer_-1_loss_bbox: 0.5956 matched_ious: 0.5626 2023/05/24 00:44:18 - mmengine - INFO - Epoch(train) [1][1150/3862] lr: 1.9879e-04 eta: 8:22:52 time: 1.3693 data_time: 0.0233 memory: 21941 grad_norm: 1.4892 loss: 1.2535 loss_heatmap: 0.5641 layer_-1_loss_cls: 0.0880 layer_-1_loss_bbox: 0.6014 matched_ious: 0.5615 2023/05/24 00:45:25 - mmengine - INFO - Epoch(train) [1][1200/3862] lr: 1.9868e-04 eta: 8:21:13 time: 1.3362 data_time: 0.0236 memory: 21746 grad_norm: 1.4502 loss: 1.2223 loss_heatmap: 0.5559 layer_-1_loss_cls: 0.0868 layer_-1_loss_bbox: 0.5795 matched_ious: 0.5707 2023/05/24 00:46:32 - mmengine - INFO - Epoch(train) [1][1250/3862] lr: 1.9857e-04 eta: 8:19:31 time: 1.3303 data_time: 0.0233 memory: 21905 grad_norm: 1.3256 loss: 1.2135 loss_heatmap: 0.5682 layer_-1_loss_cls: 0.0890 layer_-1_loss_bbox: 0.5563 matched_ious: 0.5610 2023/05/24 00:47:39 - mmengine - INFO - Epoch(train) [1][1300/3862] lr: 1.9845e-04 eta: 8:18:00 time: 1.3408 data_time: 0.0237 memory: 21905 grad_norm: 1.3677 loss: 1.2305 loss_heatmap: 0.5608 layer_-1_loss_cls: 0.0889 layer_-1_loss_bbox: 0.5808 matched_ious: 0.5477 2023/05/24 00:48:45 - mmengine - INFO - Epoch(train) [1][1350/3862] lr: 1.9833e-04 eta: 8:16:27 time: 1.3356 data_time: 0.0230 memory: 21731 grad_norm: 1.5572 loss: 1.2209 loss_heatmap: 0.5585 layer_-1_loss_cls: 0.0884 layer_-1_loss_bbox: 0.5741 matched_ious: 0.5537 2023/05/24 00:49:53 - mmengine - INFO - Epoch(train) [1][1400/3862] lr: 1.9821e-04 eta: 8:15:05 time: 1.3475 data_time: 0.0228 memory: 21698 grad_norm: 1.3828 loss: 1.2142 loss_heatmap: 0.5547 layer_-1_loss_cls: 0.0871 layer_-1_loss_bbox: 0.5724 matched_ious: 0.5423 2023/05/24 00:51:00 - mmengine - INFO - Epoch(train) [1][1450/3862] lr: 1.9808e-04 eta: 8:13:35 time: 1.3351 data_time: 0.0227 memory: 21982 grad_norm: 1.3206 loss: 1.2369 loss_heatmap: 0.5617 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.5878 matched_ious: 0.5819 2023/05/24 00:52:06 - mmengine - INFO - Epoch(train) [1][1500/3862] lr: 1.9794e-04 eta: 8:12:08 time: 1.3378 data_time: 0.0230 memory: 21772 grad_norm: 1.3613 loss: 1.2039 loss_heatmap: 0.5460 layer_-1_loss_cls: 0.0854 layer_-1_loss_bbox: 0.5724 matched_ious: 0.5866 2023/05/24 00:53:14 - mmengine - INFO - Epoch(train) [1][1550/3862] lr: 1.9781e-04 eta: 8:10:45 time: 1.3408 data_time: 0.0237 memory: 22000 grad_norm: 1.4346 loss: 1.1959 loss_heatmap: 0.5454 layer_-1_loss_cls: 0.0856 layer_-1_loss_bbox: 0.5649 matched_ious: 0.5525 2023/05/24 00:54:20 - mmengine - INFO - Epoch(train) [1][1600/3862] lr: 1.9766e-04 eta: 8:09:21 time: 1.3382 data_time: 0.0239 memory: 21854 grad_norm: 1.3103 loss: 1.2258 loss_heatmap: 0.5559 layer_-1_loss_cls: 0.0877 layer_-1_loss_bbox: 0.5822 matched_ious: 0.5638 2023/05/24 00:55:27 - mmengine - INFO - Epoch(train) [1][1650/3862] lr: 1.9751e-04 eta: 8:07:55 time: 1.3333 data_time: 0.0235 memory: 21594 grad_norm: 1.3911 loss: 1.2202 loss_heatmap: 0.5581 layer_-1_loss_cls: 0.0879 layer_-1_loss_bbox: 0.5742 matched_ious: 0.5838 2023/05/24 00:56:34 - mmengine - INFO - Epoch(train) [1][1700/3862] lr: 1.9736e-04 eta: 8:06:34 time: 1.3391 data_time: 0.0240 memory: 21736 grad_norm: 1.3786 loss: 1.2397 loss_heatmap: 0.5554 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.5978 matched_ious: 0.5801 2023/05/24 00:57:41 - mmengine - INFO - Epoch(train) [1][1750/3862] lr: 1.9720e-04 eta: 8:05:13 time: 1.3396 data_time: 0.0242 memory: 21830 grad_norm: 1.4595 loss: 1.2318 loss_heatmap: 0.5568 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.5874 matched_ious: 0.5784 2023/05/24 00:58:48 - mmengine - INFO - Epoch(train) [1][1800/3862] lr: 1.9704e-04 eta: 8:03:52 time: 1.3361 data_time: 0.0231 memory: 21855 grad_norm: 1.3020 loss: 1.1991 loss_heatmap: 0.5462 layer_-1_loss_cls: 0.0870 layer_-1_loss_bbox: 0.5659 matched_ious: 0.5719 2023/05/24 00:59:55 - mmengine - INFO - Epoch(train) [1][1850/3862] lr: 1.9688e-04 eta: 8:02:38 time: 1.3478 data_time: 0.0239 memory: 21931 grad_norm: 1.3552 loss: 1.2302 loss_heatmap: 0.5595 layer_-1_loss_cls: 0.0866 layer_-1_loss_bbox: 0.5842 matched_ious: 0.5618 2023/05/24 01:01:02 - mmengine - INFO - Epoch(train) [1][1900/3862] lr: 1.9671e-04 eta: 8:01:13 time: 1.3278 data_time: 0.0229 memory: 21775 grad_norm: 1.2044 loss: 1.1895 loss_heatmap: 0.5418 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.5620 matched_ious: 0.5808 2023/05/24 01:02:08 - mmengine - INFO - Epoch(train) [1][1950/3862] lr: 1.9653e-04 eta: 7:59:52 time: 1.3339 data_time: 0.0231 memory: 22302 grad_norm: 1.2788 loss: 1.2180 loss_heatmap: 0.5562 layer_-1_loss_cls: 0.0880 layer_-1_loss_bbox: 0.5738 matched_ious: 0.5776 2023/05/24 01:03:15 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 01:03:15 - mmengine - INFO - Epoch(train) [1][2000/3862] lr: 1.9635e-04 eta: 7:58:35 time: 1.3387 data_time: 0.0235 memory: 21569 grad_norm: 1.2985 loss: 1.2014 loss_heatmap: 0.5429 layer_-1_loss_cls: 0.0867 layer_-1_loss_bbox: 0.5718 matched_ious: 0.5863 2023/05/24 01:04:24 - mmengine - INFO - Epoch(train) [1][2050/3862] lr: 1.9617e-04 eta: 7:57:32 time: 1.3665 data_time: 0.0231 memory: 22018 grad_norm: 1.2124 loss: 1.2241 loss_heatmap: 0.5496 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.5888 matched_ious: 0.5872 2023/05/24 01:05:30 - mmengine - INFO - Epoch(train) [1][2100/3862] lr: 1.9598e-04 eta: 7:56:14 time: 1.3357 data_time: 0.0236 memory: 21586 grad_norm: 1.3178 loss: 1.2102 loss_heatmap: 0.5478 layer_-1_loss_cls: 0.0856 layer_-1_loss_bbox: 0.5767 matched_ious: 0.5667 2023/05/24 01:06:37 - mmengine - INFO - Epoch(train) [1][2150/3862] lr: 1.9579e-04 eta: 7:54:54 time: 1.3303 data_time: 0.0227 memory: 21797 grad_norm: 1.3157 loss: 1.2079 loss_heatmap: 0.5581 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.5624 matched_ious: 0.5697 2023/05/24 01:07:44 - mmengine - INFO - Epoch(train) [1][2200/3862] lr: 1.9559e-04 eta: 7:53:41 time: 1.3446 data_time: 0.0231 memory: 21971 grad_norm: 1.2605 loss: 1.2121 loss_heatmap: 0.5506 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.5750 matched_ious: 0.5771 2023/05/24 01:08:51 - mmengine - INFO - Epoch(train) [1][2250/3862] lr: 1.9539e-04 eta: 7:52:27 time: 1.3424 data_time: 0.0232 memory: 21897 grad_norm: 1.1808 loss: 1.1894 loss_heatmap: 0.5436 layer_-1_loss_cls: 0.0864 layer_-1_loss_bbox: 0.5594 matched_ious: 0.5658 2023/05/24 01:09:58 - mmengine - INFO - Epoch(train) [1][2300/3862] lr: 1.9519e-04 eta: 7:51:09 time: 1.3329 data_time: 0.0237 memory: 21879 grad_norm: 1.2450 loss: 1.2055 loss_heatmap: 0.5473 layer_-1_loss_cls: 0.0868 layer_-1_loss_bbox: 0.5713 matched_ious: 0.5576 2023/05/24 01:11:05 - mmengine - INFO - Epoch(train) [1][2350/3862] lr: 1.9498e-04 eta: 7:49:54 time: 1.3373 data_time: 0.0233 memory: 21819 grad_norm: 1.2549 loss: 1.1929 loss_heatmap: 0.5478 layer_-1_loss_cls: 0.0872 layer_-1_loss_bbox: 0.5578 matched_ious: 0.5676 2023/05/24 01:12:12 - mmengine - INFO - Epoch(train) [1][2400/3862] lr: 1.9476e-04 eta: 7:48:38 time: 1.3352 data_time: 0.0230 memory: 21983 grad_norm: 1.3588 loss: 1.2129 loss_heatmap: 0.5479 layer_-1_loss_cls: 0.0871 layer_-1_loss_bbox: 0.5779 matched_ious: 0.5698 2023/05/24 01:13:18 - mmengine - INFO - Epoch(train) [1][2450/3862] lr: 1.9454e-04 eta: 7:47:23 time: 1.3359 data_time: 0.0237 memory: 21962 grad_norm: 1.2872 loss: 1.2265 loss_heatmap: 0.5596 layer_-1_loss_cls: 0.0882 layer_-1_loss_bbox: 0.5786 matched_ious: 0.5632 2023/05/24 01:14:26 - mmengine - INFO - Epoch(train) [1][2500/3862] lr: 1.9432e-04 eta: 7:46:13 time: 1.3484 data_time: 0.0235 memory: 21888 grad_norm: 1.2201 loss: 1.2021 loss_heatmap: 0.5495 layer_-1_loss_cls: 0.0867 layer_-1_loss_bbox: 0.5660 matched_ious: 0.5517 2023/05/24 01:15:33 - mmengine - INFO - Epoch(train) [1][2550/3862] lr: 1.9409e-04 eta: 7:45:03 time: 1.3476 data_time: 0.0237 memory: 22060 grad_norm: 1.2597 loss: 1.1936 loss_heatmap: 0.5435 layer_-1_loss_cls: 0.0854 layer_-1_loss_bbox: 0.5647 matched_ious: 0.5702 2023/05/24 01:16:40 - mmengine - INFO - Epoch(train) [1][2600/3862] lr: 1.9386e-04 eta: 7:43:49 time: 1.3360 data_time: 0.0241 memory: 22040 grad_norm: 1.2500 loss: 1.2001 loss_heatmap: 0.5458 layer_-1_loss_cls: 0.0854 layer_-1_loss_bbox: 0.5688 matched_ious: 0.5877 2023/05/24 01:17:47 - mmengine - INFO - Epoch(train) [1][2650/3862] lr: 1.9363e-04 eta: 7:42:36 time: 1.3400 data_time: 0.0232 memory: 22204 grad_norm: 1.1811 loss: 1.1893 loss_heatmap: 0.5425 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.5616 matched_ious: 0.5827 2023/05/24 01:18:54 - mmengine - INFO - Epoch(train) [1][2700/3862] lr: 1.9339e-04 eta: 7:41:24 time: 1.3408 data_time: 0.0237 memory: 21920 grad_norm: 1.2723 loss: 1.1970 loss_heatmap: 0.5411 layer_-1_loss_cls: 0.0850 layer_-1_loss_bbox: 0.5710 matched_ious: 0.5431 2023/05/24 01:20:01 - mmengine - INFO - Epoch(train) [1][2750/3862] lr: 1.9314e-04 eta: 7:40:12 time: 1.3403 data_time: 0.0234 memory: 21790 grad_norm: 1.2595 loss: 1.2160 loss_heatmap: 0.5503 layer_-1_loss_cls: 0.0871 layer_-1_loss_bbox: 0.5785 matched_ious: 0.5564 2023/05/24 01:21:08 - mmengine - INFO - Epoch(train) [1][2800/3862] lr: 1.9289e-04 eta: 7:38:58 time: 1.3352 data_time: 0.0231 memory: 22090 grad_norm: 1.1871 loss: 1.1896 loss_heatmap: 0.5395 layer_-1_loss_cls: 0.0859 layer_-1_loss_bbox: 0.5643 matched_ious: 0.5562 2023/05/24 01:22:15 - mmengine - INFO - Epoch(train) [1][2850/3862] lr: 1.9264e-04 eta: 7:37:47 time: 1.3403 data_time: 0.0239 memory: 21673 grad_norm: 1.2382 loss: 1.1949 loss_heatmap: 0.5450 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.5646 matched_ious: 0.5866 2023/05/24 01:23:21 - mmengine - INFO - Epoch(train) [1][2900/3862] lr: 1.9238e-04 eta: 7:36:32 time: 1.3323 data_time: 0.0233 memory: 21768 grad_norm: 1.1485 loss: 1.1743 loss_heatmap: 0.5297 layer_-1_loss_cls: 0.0826 layer_-1_loss_bbox: 0.5620 matched_ious: 0.5707 2023/05/24 01:24:29 - mmengine - INFO - Epoch(train) [1][2950/3862] lr: 1.9212e-04 eta: 7:35:23 time: 1.3471 data_time: 0.0241 memory: 21877 grad_norm: 1.2691 loss: 1.1916 loss_heatmap: 0.5420 layer_-1_loss_cls: 0.0854 layer_-1_loss_bbox: 0.5642 matched_ious: 0.5672 2023/05/24 01:25:36 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 01:25:36 - mmengine - INFO - Epoch(train) [1][3000/3862] lr: 1.9186e-04 eta: 7:34:12 time: 1.3404 data_time: 0.0227 memory: 22110 grad_norm: 1.2358 loss: 1.1889 loss_heatmap: 0.5410 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.5622 matched_ious: 0.5884 2023/05/24 01:26:42 - mmengine - INFO - Epoch(train) [1][3050/3862] lr: 1.9159e-04 eta: 7:32:59 time: 1.3335 data_time: 0.0231 memory: 21889 grad_norm: 1.2037 loss: 1.1829 loss_heatmap: 0.5356 layer_-1_loss_cls: 0.0849 layer_-1_loss_bbox: 0.5624 matched_ious: 0.5557 2023/05/24 01:27:49 - mmengine - INFO - Epoch(train) [1][3100/3862] lr: 1.9131e-04 eta: 7:31:46 time: 1.3360 data_time: 0.0231 memory: 21992 grad_norm: 1.2044 loss: 1.1798 loss_heatmap: 0.5374 layer_-1_loss_cls: 0.0863 layer_-1_loss_bbox: 0.5562 matched_ious: 0.5991 2023/05/24 01:28:57 - mmengine - INFO - Epoch(train) [1][3150/3862] lr: 1.9103e-04 eta: 7:30:38 time: 1.3487 data_time: 0.0245 memory: 22236 grad_norm: 1.1597 loss: 1.2016 loss_heatmap: 0.5402 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.5762 matched_ious: 0.5718 2023/05/24 01:30:04 - mmengine - INFO - Epoch(train) [1][3200/3862] lr: 1.9075e-04 eta: 7:29:28 time: 1.3421 data_time: 0.0232 memory: 21615 grad_norm: 1.2295 loss: 1.1746 loss_heatmap: 0.5352 layer_-1_loss_cls: 0.0841 layer_-1_loss_bbox: 0.5552 matched_ious: 0.5664 2023/05/24 01:31:10 - mmengine - INFO - Epoch(train) [1][3250/3862] lr: 1.9046e-04 eta: 7:28:16 time: 1.3338 data_time: 0.0237 memory: 21942 grad_norm: 1.2164 loss: 1.1732 loss_heatmap: 0.5363 layer_-1_loss_cls: 0.0847 layer_-1_loss_bbox: 0.5522 matched_ious: 0.5769 2023/05/24 01:32:17 - mmengine - INFO - Epoch(train) [1][3300/3862] lr: 1.9017e-04 eta: 7:27:04 time: 1.3356 data_time: 0.0230 memory: 22011 grad_norm: 1.2044 loss: 1.1890 loss_heatmap: 0.5361 layer_-1_loss_cls: 0.0839 layer_-1_loss_bbox: 0.5690 matched_ious: 0.5746 2023/05/24 01:33:24 - mmengine - INFO - Epoch(train) [1][3350/3862] lr: 1.8988e-04 eta: 7:25:54 time: 1.3422 data_time: 0.0236 memory: 21891 grad_norm: 1.1529 loss: 1.1886 loss_heatmap: 0.5398 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.5631 matched_ious: 0.5555 2023/05/24 01:34:32 - mmengine - INFO - Epoch(train) [1][3400/3862] lr: 1.8958e-04 eta: 7:24:50 time: 1.3628 data_time: 0.0234 memory: 21721 grad_norm: 1.1913 loss: 1.1657 loss_heatmap: 0.5304 layer_-1_loss_cls: 0.0846 layer_-1_loss_bbox: 0.5506 matched_ious: 0.5807 2023/05/24 01:35:40 - mmengine - INFO - Epoch(train) [1][3450/3862] lr: 1.8928e-04 eta: 7:23:42 time: 1.3459 data_time: 0.0233 memory: 21689 grad_norm: 1.1091 loss: 1.1526 loss_heatmap: 0.5281 layer_-1_loss_cls: 0.0845 layer_-1_loss_bbox: 0.5399 matched_ious: 0.5600 2023/05/24 01:36:47 - mmengine - INFO - Epoch(train) [1][3500/3862] lr: 1.8897e-04 eta: 7:22:32 time: 1.3428 data_time: 0.0234 memory: 22007 grad_norm: 1.1866 loss: 1.1753 loss_heatmap: 0.5350 layer_-1_loss_cls: 0.0850 layer_-1_loss_bbox: 0.5554 matched_ious: 0.5568 2023/05/24 01:37:54 - mmengine - INFO - Epoch(train) [1][3550/3862] lr: 1.8866e-04 eta: 7:21:21 time: 1.3374 data_time: 0.0235 memory: 21679 grad_norm: 1.2503 loss: 1.1755 loss_heatmap: 0.5307 layer_-1_loss_cls: 0.0850 layer_-1_loss_bbox: 0.5599 matched_ious: 0.5843 2023/05/24 01:39:01 - mmengine - INFO - Epoch(train) [1][3600/3862] lr: 1.8834e-04 eta: 7:20:10 time: 1.3365 data_time: 0.0237 memory: 22061 grad_norm: 1.1404 loss: 1.1668 loss_heatmap: 0.5282 layer_-1_loss_cls: 0.0843 layer_-1_loss_bbox: 0.5543 matched_ious: 0.5469 2023/05/24 01:40:08 - mmengine - INFO - Epoch(train) [1][3650/3862] lr: 1.8802e-04 eta: 7:19:00 time: 1.3385 data_time: 0.0228 memory: 21577 grad_norm: 1.2440 loss: 1.1982 loss_heatmap: 0.5433 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.5697 matched_ious: 0.5670 2023/05/24 01:41:14 - mmengine - INFO - Epoch(train) [1][3700/3862] lr: 1.8770e-04 eta: 7:17:49 time: 1.3379 data_time: 0.0231 memory: 21777 grad_norm: 1.0974 loss: 1.1446 loss_heatmap: 0.5191 layer_-1_loss_cls: 0.0823 layer_-1_loss_bbox: 0.5432 matched_ious: 0.5659 2023/05/24 01:42:21 - mmengine - INFO - Epoch(train) [1][3750/3862] lr: 1.8737e-04 eta: 7:16:38 time: 1.3335 data_time: 0.0236 memory: 21708 grad_norm: 1.1410 loss: 1.1324 loss_heatmap: 0.5121 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5385 matched_ious: 0.5485 2023/05/24 01:43:28 - mmengine - INFO - Epoch(train) [1][3800/3862] lr: 1.8704e-04 eta: 7:15:27 time: 1.3344 data_time: 0.0238 memory: 22026 grad_norm: 1.2708 loss: 1.1849 loss_heatmap: 0.5383 layer_-1_loss_cls: 0.0853 layer_-1_loss_bbox: 0.5613 matched_ious: 0.5591 2023/05/24 01:44:36 - mmengine - INFO - Epoch(train) [1][3850/3862] lr: 1.8670e-04 eta: 7:14:22 time: 1.3591 data_time: 0.0237 memory: 21947 grad_norm: 1.0727 loss: 1.1299 loss_heatmap: 0.5170 layer_-1_loss_cls: 0.0827 layer_-1_loss_bbox: 0.5302 matched_ious: 0.5730 2023/05/24 01:44:52 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 01:44:52 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/05/24 01:45:09 - mmengine - INFO - Epoch(val) [1][ 50/753] eta: 0:02:59 time: 0.2554 data_time: 0.0256 memory: 21306 2023/05/24 01:45:20 - mmengine - INFO - Epoch(val) [1][100/753] eta: 0:02:36 time: 0.2234 data_time: 0.0053 memory: 2850 2023/05/24 01:45:31 - mmengine - INFO - Epoch(val) [1][150/753] eta: 0:02:19 time: 0.2169 data_time: 0.0061 memory: 2848 2023/05/24 01:45:42 - mmengine - INFO - Epoch(val) [1][200/753] eta: 0:02:07 time: 0.2253 data_time: 0.0055 memory: 2852 2023/05/24 01:45:53 - mmengine - INFO - Epoch(val) [1][250/753] eta: 0:01:54 time: 0.2217 data_time: 0.0056 memory: 2848 2023/05/24 01:46:05 - mmengine - INFO - Epoch(val) [1][300/753] eta: 0:01:43 time: 0.2227 data_time: 0.0057 memory: 2848 2023/05/24 01:46:15 - mmengine - INFO - Epoch(val) [1][350/753] eta: 0:01:31 time: 0.2157 data_time: 0.0055 memory: 2851 2023/05/24 01:46:26 - mmengine - INFO - Epoch(val) [1][400/753] eta: 0:01:19 time: 0.2135 data_time: 0.0057 memory: 2851 2023/05/24 01:46:37 - mmengine - INFO - Epoch(val) [1][450/753] eta: 0:01:07 time: 0.2241 data_time: 0.0065 memory: 2849 2023/05/24 01:46:48 - mmengine - INFO - Epoch(val) [1][500/753] eta: 0:00:56 time: 0.2225 data_time: 0.0057 memory: 2850 2023/05/24 01:46:59 - mmengine - INFO - Epoch(val) [1][550/753] eta: 0:00:45 time: 0.2163 data_time: 0.0068 memory: 2849 2023/05/24 01:47:11 - mmengine - INFO - Epoch(val) [1][600/753] eta: 0:00:34 time: 0.2308 data_time: 0.0055 memory: 2852 2023/05/24 01:47:22 - mmengine - INFO - Epoch(val) [1][650/753] eta: 0:00:23 time: 0.2294 data_time: 0.0063 memory: 2849 2023/05/24 01:47:34 - mmengine - INFO - Epoch(val) [1][700/753] eta: 0:00:11 time: 0.2280 data_time: 0.0052 memory: 2852 2023/05/24 01:47:45 - mmengine - INFO - Epoch(val) [1][750/753] eta: 0:00:00 time: 0.2234 data_time: 0.0051 memory: 2852 2023/05/24 01:58:34 - mmengine - INFO - Epoch(val) [1][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.7893 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.8856 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.9121 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.9231 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1775 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1542 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.0990 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.2820 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1873 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2826 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2568 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.3238 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.2894 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1859 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.4184 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.5926 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.6651 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.6996 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3229 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1839 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.0851 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.2462 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2211 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0468 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.2190 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.3667 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.4776 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6461 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4187 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.8548 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1236 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3431 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4605 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.7338 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.8615 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.8832 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3455 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1828 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.0720 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.4817 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2463 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.1493 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.4006 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.5638 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.6523 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5169 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2067 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.6797 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.2287 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1465 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.5868 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.6877 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7277 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7413 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.2003 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2895 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0667 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.6190 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.7180 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.7317 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.7425 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1845 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2355 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.2909 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.4976 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2431 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.5316 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.5542 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.5584 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.5660 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1555 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2605 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.4013 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2344 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0118 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8492 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8631 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8736 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8851 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1415 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2996 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.3644 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2207 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.0880 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.7208 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.7326 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.7508 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.7848 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1353 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3369 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.6902 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.6481 data_time: 0.0051 time: 0.2205 2023/05/24 01:59:42 - mmengine - INFO - Epoch(train) [2][ 50/3862] lr: 1.8628e-04 eta: 7:13:05 time: 1.3743 data_time: 0.0677 memory: 21893 grad_norm: 1.1260 loss: 1.1418 loss_heatmap: 0.5157 layer_-1_loss_cls: 0.0817 layer_-1_loss_bbox: 0.5443 matched_ious: 0.5794 2023/05/24 02:00:49 - mmengine - INFO - Epoch(train) [2][ 100/3862] lr: 1.8594e-04 eta: 7:11:55 time: 1.3395 data_time: 0.0337 memory: 22070 grad_norm: 1.1517 loss: 1.1582 loss_heatmap: 0.5288 layer_-1_loss_cls: 0.0848 layer_-1_loss_bbox: 0.5446 matched_ious: 0.5725 2023/05/24 02:01:40 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 02:01:56 - mmengine - INFO - Epoch(train) [2][ 150/3862] lr: 1.8559e-04 eta: 7:10:45 time: 1.3411 data_time: 0.0351 memory: 21519 grad_norm: 1.1048 loss: 1.1540 loss_heatmap: 0.5253 layer_-1_loss_cls: 0.0845 layer_-1_loss_bbox: 0.5441 matched_ious: 0.5584 2023/05/24 02:03:03 - mmengine - INFO - Epoch(train) [2][ 200/3862] lr: 1.8524e-04 eta: 7:09:34 time: 1.3330 data_time: 0.0354 memory: 21872 grad_norm: 1.1907 loss: 1.1525 loss_heatmap: 0.5267 layer_-1_loss_cls: 0.0843 layer_-1_loss_bbox: 0.5414 matched_ious: 0.5744 2023/05/24 02:04:11 - mmengine - INFO - Epoch(train) [2][ 250/3862] lr: 1.8488e-04 eta: 7:08:29 time: 1.3599 data_time: 0.0372 memory: 21972 grad_norm: 1.2187 loss: 1.1436 loss_heatmap: 0.5213 layer_-1_loss_cls: 0.0836 layer_-1_loss_bbox: 0.5386 matched_ious: 0.5743 2023/05/24 02:05:18 - mmengine - INFO - Epoch(train) [2][ 300/3862] lr: 1.8452e-04 eta: 7:07:19 time: 1.3379 data_time: 0.0353 memory: 21693 grad_norm: 1.1328 loss: 1.1354 loss_heatmap: 0.5234 layer_-1_loss_cls: 0.0839 layer_-1_loss_bbox: 0.5281 matched_ious: 0.5825 2023/05/24 02:06:25 - mmengine - INFO - Epoch(train) [2][ 350/3862] lr: 1.8416e-04 eta: 7:06:11 time: 1.3430 data_time: 0.0351 memory: 21740 grad_norm: 1.1536 loss: 1.1546 loss_heatmap: 0.5196 layer_-1_loss_cls: 0.0830 layer_-1_loss_bbox: 0.5520 matched_ious: 0.5830 2023/05/24 02:07:32 - mmengine - INFO - Epoch(train) [2][ 400/3862] lr: 1.8379e-04 eta: 7:05:02 time: 1.3419 data_time: 0.0352 memory: 21963 grad_norm: 1.1506 loss: 1.1478 loss_heatmap: 0.5135 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5524 matched_ious: 0.5763 2023/05/24 02:08:39 - mmengine - INFO - Epoch(train) [2][ 450/3862] lr: 1.8342e-04 eta: 7:03:53 time: 1.3432 data_time: 0.0355 memory: 21625 grad_norm: 1.1867 loss: 1.1426 loss_heatmap: 0.5213 layer_-1_loss_cls: 0.0830 layer_-1_loss_bbox: 0.5383 matched_ious: 0.5377 2023/05/24 02:09:47 - mmengine - INFO - Epoch(train) [2][ 500/3862] lr: 1.8304e-04 eta: 7:02:46 time: 1.3489 data_time: 0.0365 memory: 22023 grad_norm: 1.1201 loss: 1.1242 loss_heatmap: 0.5178 layer_-1_loss_cls: 0.0827 layer_-1_loss_bbox: 0.5237 matched_ious: 0.5695 2023/05/24 02:10:54 - mmengine - INFO - Epoch(train) [2][ 550/3862] lr: 1.8266e-04 eta: 7:01:37 time: 1.3429 data_time: 0.0368 memory: 21870 grad_norm: 1.0843 loss: 1.1508 loss_heatmap: 0.5237 layer_-1_loss_cls: 0.0826 layer_-1_loss_bbox: 0.5445 matched_ious: 0.5780 2023/05/24 02:12:01 - mmengine - INFO - Epoch(train) [2][ 600/3862] lr: 1.8228e-04 eta: 7:00:28 time: 1.3419 data_time: 0.0363 memory: 21967 grad_norm: 1.0671 loss: 1.1275 loss_heatmap: 0.5119 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5349 matched_ious: 0.5650 2023/05/24 02:13:09 - mmengine - INFO - Epoch(train) [2][ 650/3862] lr: 1.8189e-04 eta: 6:59:21 time: 1.3512 data_time: 0.0380 memory: 22016 grad_norm: 1.0677 loss: 1.1270 loss_heatmap: 0.5068 layer_-1_loss_cls: 0.0801 layer_-1_loss_bbox: 0.5401 matched_ious: 0.5595 2023/05/24 02:14:17 - mmengine - INFO - Epoch(train) [2][ 700/3862] lr: 1.8150e-04 eta: 6:58:17 time: 1.3613 data_time: 0.0390 memory: 21888 grad_norm: 1.1266 loss: 1.1485 loss_heatmap: 0.5175 layer_-1_loss_cls: 0.0813 layer_-1_loss_bbox: 0.5497 matched_ious: 0.5766 2023/05/24 02:15:24 - mmengine - INFO - Epoch(train) [2][ 750/3862] lr: 1.8111e-04 eta: 6:57:09 time: 1.3484 data_time: 0.0382 memory: 21767 grad_norm: 1.2229 loss: 1.1299 loss_heatmap: 0.5135 layer_-1_loss_cls: 0.0810 layer_-1_loss_bbox: 0.5354 matched_ious: 0.5641 2023/05/24 02:16:31 - mmengine - INFO - Epoch(train) [2][ 800/3862] lr: 1.8071e-04 eta: 6:56:01 time: 1.3432 data_time: 0.0368 memory: 21808 grad_norm: 1.0574 loss: 1.1523 loss_heatmap: 0.5208 layer_-1_loss_cls: 0.0836 layer_-1_loss_bbox: 0.5478 matched_ious: 0.5597 2023/05/24 02:17:38 - mmengine - INFO - Epoch(train) [2][ 850/3862] lr: 1.8031e-04 eta: 6:54:50 time: 1.3336 data_time: 0.0380 memory: 21839 grad_norm: 1.1833 loss: 1.1499 loss_heatmap: 0.5288 layer_-1_loss_cls: 0.0847 layer_-1_loss_bbox: 0.5364 matched_ious: 0.5867 2023/05/24 02:18:45 - mmengine - INFO - Epoch(train) [2][ 900/3862] lr: 1.7990e-04 eta: 6:53:42 time: 1.3422 data_time: 0.0364 memory: 21986 grad_norm: 1.0814 loss: 1.1355 loss_heatmap: 0.5108 layer_-1_loss_cls: 0.0824 layer_-1_loss_bbox: 0.5423 matched_ious: 0.5511 2023/05/24 02:19:53 - mmengine - INFO - Epoch(train) [2][ 950/3862] lr: 1.7949e-04 eta: 6:52:36 time: 1.3554 data_time: 0.0380 memory: 21980 grad_norm: 1.1362 loss: 1.1539 loss_heatmap: 0.5221 layer_-1_loss_cls: 0.0823 layer_-1_loss_bbox: 0.5495 matched_ious: 0.5708 2023/05/24 02:21:00 - mmengine - INFO - Epoch(train) [2][1000/3862] lr: 1.7908e-04 eta: 6:51:26 time: 1.3371 data_time: 0.0368 memory: 22094 grad_norm: 1.0709 loss: 1.1391 loss_heatmap: 0.5220 layer_-1_loss_cls: 0.0832 layer_-1_loss_bbox: 0.5338 matched_ious: 0.5548 2023/05/24 02:22:06 - mmengine - INFO - Epoch(train) [2][1050/3862] lr: 1.7866e-04 eta: 6:50:16 time: 1.3352 data_time: 0.0397 memory: 21783 grad_norm: 1.1650 loss: 1.1526 loss_heatmap: 0.5186 layer_-1_loss_cls: 0.0830 layer_-1_loss_bbox: 0.5510 matched_ious: 0.5728 2023/05/24 02:23:14 - mmengine - INFO - Epoch(train) [2][1100/3862] lr: 1.7824e-04 eta: 6:49:08 time: 1.3449 data_time: 0.0365 memory: 22024 grad_norm: 1.1539 loss: 1.1205 loss_heatmap: 0.5078 layer_-1_loss_cls: 0.0810 layer_-1_loss_bbox: 0.5317 matched_ious: 0.5522 2023/05/24 02:24:06 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 02:24:22 - mmengine - INFO - Epoch(train) [2][1150/3862] lr: 1.7782e-04 eta: 6:48:04 time: 1.3630 data_time: 0.0385 memory: 21902 grad_norm: 1.1024 loss: 1.1247 loss_heatmap: 0.5195 layer_-1_loss_cls: 0.0826 layer_-1_loss_bbox: 0.5225 matched_ious: 0.5543 2023/05/24 02:25:29 - mmengine - INFO - Epoch(train) [2][1200/3862] lr: 1.7739e-04 eta: 6:46:54 time: 1.3373 data_time: 0.0382 memory: 21798 grad_norm: 1.1821 loss: 1.1213 loss_heatmap: 0.5181 layer_-1_loss_cls: 0.0832 layer_-1_loss_bbox: 0.5200 matched_ious: 0.5995 2023/05/24 02:26:36 - mmengine - INFO - Epoch(train) [2][1250/3862] lr: 1.7696e-04 eta: 6:45:47 time: 1.3485 data_time: 0.0376 memory: 21969 grad_norm: 1.0690 loss: 1.1378 loss_heatmap: 0.5181 layer_-1_loss_cls: 0.0826 layer_-1_loss_bbox: 0.5372 matched_ious: 0.5972 2023/05/24 02:27:43 - mmengine - INFO - Epoch(train) [2][1300/3862] lr: 1.7653e-04 eta: 6:44:37 time: 1.3349 data_time: 0.0382 memory: 21648 grad_norm: 1.0792 loss: 1.1379 loss_heatmap: 0.5202 layer_-1_loss_cls: 0.0833 layer_-1_loss_bbox: 0.5344 matched_ious: 0.5755 2023/05/24 02:28:50 - mmengine - INFO - Epoch(train) [2][1350/3862] lr: 1.7609e-04 eta: 6:43:27 time: 1.3337 data_time: 0.0386 memory: 21799 grad_norm: 1.1306 loss: 1.1215 loss_heatmap: 0.5126 layer_-1_loss_cls: 0.0822 layer_-1_loss_bbox: 0.5267 matched_ious: 0.5605 2023/05/24 02:29:57 - mmengine - INFO - Epoch(train) [2][1400/3862] lr: 1.7565e-04 eta: 6:42:21 time: 1.3549 data_time: 0.0379 memory: 22098 grad_norm: 1.0585 loss: 1.1109 loss_heatmap: 0.5063 layer_-1_loss_cls: 0.0813 layer_-1_loss_bbox: 0.5233 matched_ious: 0.5654 2023/05/24 02:31:04 - mmengine - INFO - Epoch(train) [2][1450/3862] lr: 1.7520e-04 eta: 6:41:13 time: 1.3422 data_time: 0.0384 memory: 22114 grad_norm: 1.1745 loss: 1.1163 loss_heatmap: 0.5060 layer_-1_loss_cls: 0.0816 layer_-1_loss_bbox: 0.5287 matched_ious: 0.5881 2023/05/24 02:32:12 - mmengine - INFO - Epoch(train) [2][1500/3862] lr: 1.7475e-04 eta: 6:40:05 time: 1.3435 data_time: 0.0369 memory: 21791 grad_norm: 1.0962 loss: 1.0988 loss_heatmap: 0.5003 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5177 matched_ious: 0.5691 2023/05/24 02:33:19 - mmengine - INFO - Epoch(train) [2][1550/3862] lr: 1.7430e-04 eta: 6:38:56 time: 1.3403 data_time: 0.0376 memory: 22054 grad_norm: 1.0893 loss: 1.1383 loss_heatmap: 0.5127 layer_-1_loss_cls: 0.0820 layer_-1_loss_bbox: 0.5436 matched_ious: 0.5653 2023/05/24 02:34:27 - mmengine - INFO - Epoch(train) [2][1600/3862] lr: 1.7385e-04 eta: 6:37:53 time: 1.3735 data_time: 0.0368 memory: 22030 grad_norm: 1.0959 loss: 1.1203 loss_heatmap: 0.5055 layer_-1_loss_cls: 0.0812 layer_-1_loss_bbox: 0.5335 matched_ious: 0.5632 2023/05/24 02:35:34 - mmengine - INFO - Epoch(train) [2][1650/3862] lr: 1.7339e-04 eta: 6:36:44 time: 1.3397 data_time: 0.0403 memory: 21973 grad_norm: 1.0728 loss: 1.0983 loss_heatmap: 0.4982 layer_-1_loss_cls: 0.0795 layer_-1_loss_bbox: 0.5206 matched_ious: 0.5794 2023/05/24 02:36:41 - mmengine - INFO - Epoch(train) [2][1700/3862] lr: 1.7293e-04 eta: 6:35:36 time: 1.3422 data_time: 0.0378 memory: 21767 grad_norm: 1.0727 loss: 1.1410 loss_heatmap: 0.5215 layer_-1_loss_cls: 0.0829 layer_-1_loss_bbox: 0.5366 matched_ious: 0.5498 2023/05/24 02:37:48 - mmengine - INFO - Epoch(train) [2][1750/3862] lr: 1.7246e-04 eta: 6:34:27 time: 1.3399 data_time: 0.0400 memory: 21627 grad_norm: 1.1326 loss: 1.1300 loss_heatmap: 0.5053 layer_-1_loss_cls: 0.0812 layer_-1_loss_bbox: 0.5435 matched_ious: 0.5879 2023/05/24 02:38:55 - mmengine - INFO - Epoch(train) [2][1800/3862] lr: 1.7199e-04 eta: 6:33:18 time: 1.3369 data_time: 0.0382 memory: 21648 grad_norm: 1.0460 loss: 1.1142 loss_heatmap: 0.5076 layer_-1_loss_cls: 0.0815 layer_-1_loss_bbox: 0.5251 matched_ious: 0.5647 2023/05/24 02:40:02 - mmengine - INFO - Epoch(train) [2][1850/3862] lr: 1.7152e-04 eta: 6:32:09 time: 1.3368 data_time: 0.0395 memory: 21975 grad_norm: 1.1179 loss: 1.0984 loss_heatmap: 0.4991 layer_-1_loss_cls: 0.0800 layer_-1_loss_bbox: 0.5193 matched_ious: 0.5711 2023/05/24 02:41:09 - mmengine - INFO - Epoch(train) [2][1900/3862] lr: 1.7105e-04 eta: 6:31:00 time: 1.3400 data_time: 0.0375 memory: 21898 grad_norm: 1.0544 loss: 1.1112 loss_heatmap: 0.5030 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5276 matched_ious: 0.5646 2023/05/24 02:42:16 - mmengine - INFO - Epoch(train) [2][1950/3862] lr: 1.7057e-04 eta: 6:29:51 time: 1.3328 data_time: 0.0394 memory: 21710 grad_norm: 1.0391 loss: 1.0947 loss_heatmap: 0.4959 layer_-1_loss_cls: 0.0798 layer_-1_loss_bbox: 0.5190 matched_ious: 0.5799 2023/05/24 02:43:23 - mmengine - INFO - Epoch(train) [2][2000/3862] lr: 1.7009e-04 eta: 6:28:42 time: 1.3369 data_time: 0.0383 memory: 21699 grad_norm: 1.0360 loss: 1.1109 loss_heatmap: 0.5044 layer_-1_loss_cls: 0.0809 layer_-1_loss_bbox: 0.5256 matched_ious: 0.5990 2023/05/24 02:44:30 - mmengine - INFO - Epoch(train) [2][2050/3862] lr: 1.6960e-04 eta: 6:27:35 time: 1.3500 data_time: 0.0395 memory: 21711 grad_norm: 1.0611 loss: 1.1055 loss_heatmap: 0.5045 layer_-1_loss_cls: 0.0806 layer_-1_loss_bbox: 0.5204 matched_ious: 0.5664 2023/05/24 02:45:37 - mmengine - INFO - Epoch(train) [2][2100/3862] lr: 1.6911e-04 eta: 6:26:25 time: 1.3318 data_time: 0.0390 memory: 21744 grad_norm: 1.0198 loss: 1.0754 loss_heatmap: 0.4892 layer_-1_loss_cls: 0.0790 layer_-1_loss_bbox: 0.5072 matched_ious: 0.5754 2023/05/24 02:46:28 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 02:46:44 - mmengine - INFO - Epoch(train) [2][2150/3862] lr: 1.6862e-04 eta: 6:25:17 time: 1.3383 data_time: 0.0379 memory: 21805 grad_norm: 1.2429 loss: 1.0958 loss_heatmap: 0.4999 layer_-1_loss_cls: 0.0804 layer_-1_loss_bbox: 0.5155 matched_ious: 0.5833 2023/05/24 02:47:50 - mmengine - INFO - Epoch(train) [2][2200/3862] lr: 1.6813e-04 eta: 6:24:07 time: 1.3332 data_time: 0.0374 memory: 21936 grad_norm: 1.2242 loss: 1.1238 loss_heatmap: 0.5126 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.5291 matched_ious: 0.5938 2023/05/24 02:48:58 - mmengine - INFO - Epoch(train) [2][2250/3862] lr: 1.6763e-04 eta: 6:23:01 time: 1.3532 data_time: 0.0399 memory: 21978 grad_norm: 1.1042 loss: 1.0766 loss_heatmap: 0.4891 layer_-1_loss_cls: 0.0790 layer_-1_loss_bbox: 0.5085 matched_ious: 0.5920 2023/05/24 02:50:05 - mmengine - INFO - Epoch(train) [2][2300/3862] lr: 1.6713e-04 eta: 6:21:52 time: 1.3360 data_time: 0.0396 memory: 21623 grad_norm: 1.0449 loss: 1.1230 loss_heatmap: 0.5111 layer_-1_loss_cls: 0.0815 layer_-1_loss_bbox: 0.5304 matched_ious: 0.5725 2023/05/24 02:51:12 - mmengine - INFO - Epoch(train) [2][2350/3862] lr: 1.6663e-04 eta: 6:20:44 time: 1.3412 data_time: 0.0406 memory: 21603 grad_norm: 1.1269 loss: 1.0971 loss_heatmap: 0.5010 layer_-1_loss_cls: 0.0810 layer_-1_loss_bbox: 0.5152 matched_ious: 0.5946 2023/05/24 02:52:19 - mmengine - INFO - Epoch(train) [2][2400/3862] lr: 1.6612e-04 eta: 6:19:36 time: 1.3465 data_time: 0.0403 memory: 21800 grad_norm: 1.0538 loss: 1.0750 loss_heatmap: 0.4908 layer_-1_loss_cls: 0.0780 layer_-1_loss_bbox: 0.5062 matched_ious: 0.5684 2023/05/24 02:53:26 - mmengine - INFO - Epoch(train) [2][2450/3862] lr: 1.6561e-04 eta: 6:18:29 time: 1.3425 data_time: 0.0412 memory: 21922 grad_norm: 1.0072 loss: 1.1061 loss_heatmap: 0.5025 layer_-1_loss_cls: 0.0800 layer_-1_loss_bbox: 0.5236 matched_ious: 0.5743 2023/05/24 02:54:34 - mmengine - INFO - Epoch(train) [2][2500/3862] lr: 1.6510e-04 eta: 6:17:22 time: 1.3564 data_time: 0.0404 memory: 21680 grad_norm: 1.0808 loss: 1.0893 loss_heatmap: 0.5033 layer_-1_loss_cls: 0.0815 layer_-1_loss_bbox: 0.5045 matched_ious: 0.5666 2023/05/24 02:55:41 - mmengine - INFO - Epoch(train) [2][2550/3862] lr: 1.6458e-04 eta: 6:16:15 time: 1.3454 data_time: 0.0409 memory: 21834 grad_norm: 1.0494 loss: 1.0932 loss_heatmap: 0.5008 layer_-1_loss_cls: 0.0805 layer_-1_loss_bbox: 0.5120 matched_ious: 0.5549 2023/05/24 02:56:49 - mmengine - INFO - Epoch(train) [2][2600/3862] lr: 1.6406e-04 eta: 6:15:08 time: 1.3474 data_time: 0.0408 memory: 21732 grad_norm: 1.0580 loss: 1.0935 loss_heatmap: 0.4992 layer_-1_loss_cls: 0.0804 layer_-1_loss_bbox: 0.5140 matched_ious: 0.5996 2023/05/24 02:57:56 - mmengine - INFO - Epoch(train) [2][2650/3862] lr: 1.6354e-04 eta: 6:14:00 time: 1.3439 data_time: 0.0403 memory: 21896 grad_norm: 1.0039 loss: 1.0938 loss_heatmap: 0.5012 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5115 matched_ious: 0.5849 2023/05/24 02:59:03 - mmengine - INFO - Epoch(train) [2][2700/3862] lr: 1.6302e-04 eta: 6:12:52 time: 1.3464 data_time: 0.0403 memory: 21960 grad_norm: 1.0780 loss: 1.1028 loss_heatmap: 0.4997 layer_-1_loss_cls: 0.0800 layer_-1_loss_bbox: 0.5231 matched_ious: 0.5896 2023/05/24 03:00:10 - mmengine - INFO - Epoch(train) [2][2750/3862] lr: 1.6249e-04 eta: 6:11:44 time: 1.3346 data_time: 0.0411 memory: 21780 grad_norm: 1.0919 loss: 1.1012 loss_heatmap: 0.5023 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5170 matched_ious: 0.5771 2023/05/24 03:01:17 - mmengine - INFO - Epoch(train) [2][2800/3862] lr: 1.6196e-04 eta: 6:10:35 time: 1.3405 data_time: 0.0397 memory: 21997 grad_norm: 1.1343 loss: 1.1129 loss_heatmap: 0.5076 layer_-1_loss_cls: 0.0814 layer_-1_loss_bbox: 0.5239 matched_ious: 0.5717 2023/05/24 03:02:24 - mmengine - INFO - Epoch(train) [2][2850/3862] lr: 1.6142e-04 eta: 6:09:28 time: 1.3487 data_time: 0.0414 memory: 21944 grad_norm: 1.1336 loss: 1.0995 loss_heatmap: 0.5009 layer_-1_loss_cls: 0.0814 layer_-1_loss_bbox: 0.5171 matched_ious: 0.5356 2023/05/24 03:03:31 - mmengine - INFO - Epoch(train) [2][2900/3862] lr: 1.6089e-04 eta: 6:08:20 time: 1.3409 data_time: 0.0396 memory: 21816 grad_norm: 1.1771 loss: 1.0775 loss_heatmap: 0.4880 layer_-1_loss_cls: 0.0789 layer_-1_loss_bbox: 0.5105 matched_ious: 0.5689 2023/05/24 03:04:39 - mmengine - INFO - Epoch(train) [2][2950/3862] lr: 1.6035e-04 eta: 6:07:14 time: 1.3595 data_time: 0.0414 memory: 22007 grad_norm: 1.0795 loss: 1.0891 loss_heatmap: 0.4940 layer_-1_loss_cls: 0.0795 layer_-1_loss_bbox: 0.5156 matched_ious: 0.5739 2023/05/24 03:05:47 - mmengine - INFO - Epoch(train) [2][3000/3862] lr: 1.5981e-04 eta: 6:06:07 time: 1.3443 data_time: 0.0398 memory: 21829 grad_norm: 1.0563 loss: 1.0852 loss_heatmap: 0.4926 layer_-1_loss_cls: 0.0810 layer_-1_loss_bbox: 0.5116 matched_ious: 0.5935 2023/05/24 03:06:54 - mmengine - INFO - Epoch(train) [2][3050/3862] lr: 1.5926e-04 eta: 6:04:59 time: 1.3469 data_time: 0.0407 memory: 21993 grad_norm: 1.1060 loss: 1.0607 loss_heatmap: 0.4870 layer_-1_loss_cls: 0.0795 layer_-1_loss_bbox: 0.4943 matched_ious: 0.5690 2023/05/24 03:08:01 - mmengine - INFO - Epoch(train) [2][3100/3862] lr: 1.5872e-04 eta: 6:03:51 time: 1.3359 data_time: 0.0403 memory: 21752 grad_norm: 1.0671 loss: 1.0827 loss_heatmap: 0.4902 layer_-1_loss_cls: 0.0799 layer_-1_loss_bbox: 0.5126 matched_ious: 0.5979 2023/05/24 03:08:52 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 03:09:07 - mmengine - INFO - Epoch(train) [2][3150/3862] lr: 1.5817e-04 eta: 6:02:42 time: 1.3319 data_time: 0.0411 memory: 21787 grad_norm: 1.1144 loss: 1.0849 loss_heatmap: 0.4995 layer_-1_loss_cls: 0.0806 layer_-1_loss_bbox: 0.5048 matched_ious: 0.5903 2023/05/24 03:10:15 - mmengine - INFO - Epoch(train) [2][3200/3862] lr: 1.5761e-04 eta: 6:01:34 time: 1.3439 data_time: 0.0398 memory: 21791 grad_norm: 0.9831 loss: 1.0898 loss_heatmap: 0.4956 layer_-1_loss_cls: 0.0793 layer_-1_loss_bbox: 0.5148 matched_ious: 0.5774 2023/05/24 03:11:21 - mmengine - INFO - Epoch(train) [2][3250/3862] lr: 1.5706e-04 eta: 6:00:26 time: 1.3376 data_time: 0.0413 memory: 21749 grad_norm: 1.2219 loss: 1.0944 loss_heatmap: 0.4998 layer_-1_loss_cls: 0.0804 layer_-1_loss_bbox: 0.5142 matched_ious: 0.5610 2023/05/24 03:12:29 - mmengine - INFO - Epoch(train) [2][3300/3862] lr: 1.5650e-04 eta: 5:59:18 time: 1.3432 data_time: 0.0397 memory: 21902 grad_norm: 1.1407 loss: 1.0846 loss_heatmap: 0.4999 layer_-1_loss_cls: 0.0806 layer_-1_loss_bbox: 0.5041 matched_ious: 0.5761 2023/05/24 03:13:36 - mmengine - INFO - Epoch(train) [2][3350/3862] lr: 1.5594e-04 eta: 5:58:11 time: 1.3496 data_time: 0.0408 memory: 21695 grad_norm: 1.0089 loss: 1.0954 loss_heatmap: 0.4981 layer_-1_loss_cls: 0.0797 layer_-1_loss_bbox: 0.5177 matched_ious: 0.5719 2023/05/24 03:14:44 - mmengine - INFO - Epoch(train) [2][3400/3862] lr: 1.5538e-04 eta: 5:57:06 time: 1.3632 data_time: 0.0414 memory: 21991 grad_norm: 1.1575 loss: 1.0727 loss_heatmap: 0.4863 layer_-1_loss_cls: 0.0780 layer_-1_loss_bbox: 0.5084 matched_ious: 0.5568 2023/05/24 03:15:51 - mmengine - INFO - Epoch(train) [2][3450/3862] lr: 1.5481e-04 eta: 5:55:58 time: 1.3420 data_time: 0.0424 memory: 21625 grad_norm: 1.2605 loss: 1.0867 loss_heatmap: 0.4905 layer_-1_loss_cls: 0.0797 layer_-1_loss_bbox: 0.5165 matched_ious: 0.5701 2023/05/24 03:16:59 - mmengine - INFO - Epoch(train) [2][3500/3862] lr: 1.5425e-04 eta: 5:54:50 time: 1.3467 data_time: 0.0394 memory: 21941 grad_norm: 1.1989 loss: 1.0817 loss_heatmap: 0.4933 layer_-1_loss_cls: 0.0804 layer_-1_loss_bbox: 0.5080 matched_ious: 0.5972 2023/05/24 03:18:06 - mmengine - INFO - Epoch(train) [2][3550/3862] lr: 1.5368e-04 eta: 5:53:42 time: 1.3365 data_time: 0.0400 memory: 21950 grad_norm: 1.0009 loss: 1.0785 loss_heatmap: 0.4898 layer_-1_loss_cls: 0.0792 layer_-1_loss_bbox: 0.5095 matched_ious: 0.6065 2023/05/24 03:19:13 - mmengine - INFO - Epoch(train) [2][3600/3862] lr: 1.5310e-04 eta: 5:52:34 time: 1.3452 data_time: 0.0382 memory: 21722 grad_norm: 1.0066 loss: 1.0596 loss_heatmap: 0.4817 layer_-1_loss_cls: 0.0777 layer_-1_loss_bbox: 0.5002 matched_ious: 0.5598 2023/05/24 03:20:20 - mmengine - INFO - Epoch(train) [2][3650/3862] lr: 1.5253e-04 eta: 5:51:26 time: 1.3405 data_time: 0.0409 memory: 22052 grad_norm: 1.0454 loss: 1.0431 loss_heatmap: 0.4782 layer_-1_loss_cls: 0.0775 layer_-1_loss_bbox: 0.4874 matched_ious: 0.5882 2023/05/24 03:21:27 - mmengine - INFO - Epoch(train) [2][3700/3862] lr: 1.5195e-04 eta: 5:50:18 time: 1.3363 data_time: 0.0396 memory: 22270 grad_norm: 0.9509 loss: 1.0797 loss_heatmap: 0.5000 layer_-1_loss_cls: 0.0799 layer_-1_loss_bbox: 0.4998 matched_ious: 0.5793 2023/05/24 03:22:34 - mmengine - INFO - Epoch(train) [2][3750/3862] lr: 1.5137e-04 eta: 5:49:10 time: 1.3375 data_time: 0.0415 memory: 21883 grad_norm: 1.0852 loss: 1.0666 loss_heatmap: 0.4852 layer_-1_loss_cls: 0.0789 layer_-1_loss_bbox: 0.5025 matched_ious: 0.5829 2023/05/24 03:23:40 - mmengine - INFO - Epoch(train) [2][3800/3862] lr: 1.5079e-04 eta: 5:48:02 time: 1.3399 data_time: 0.0405 memory: 21964 grad_norm: 1.1708 loss: 1.0827 loss_heatmap: 0.4990 layer_-1_loss_cls: 0.0804 layer_-1_loss_bbox: 0.5034 matched_ious: 0.5911 2023/05/24 03:24:49 - mmengine - INFO - Epoch(train) [2][3850/3862] lr: 1.5020e-04 eta: 5:46:56 time: 1.3639 data_time: 0.0419 memory: 22010 grad_norm: 1.0293 loss: 1.0697 loss_heatmap: 0.4863 layer_-1_loss_cls: 0.0785 layer_-1_loss_bbox: 0.5049 matched_ious: 0.5741 2023/05/24 03:25:05 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 03:25:05 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/05/24 03:25:20 - mmengine - INFO - Epoch(val) [2][ 50/753] eta: 0:02:47 time: 0.2389 data_time: 0.0139 memory: 21450 2023/05/24 03:25:32 - mmengine - INFO - Epoch(val) [2][100/753] eta: 0:02:30 time: 0.2218 data_time: 0.0061 memory: 2850 2023/05/24 03:25:43 - mmengine - INFO - Epoch(val) [2][150/753] eta: 0:02:17 time: 0.2255 data_time: 0.0075 memory: 2848 2023/05/24 03:25:55 - mmengine - INFO - Epoch(val) [2][200/753] eta: 0:02:07 time: 0.2334 data_time: 0.0072 memory: 2852 2023/05/24 03:26:06 - mmengine - INFO - Epoch(val) [2][250/753] eta: 0:01:55 time: 0.2260 data_time: 0.0070 memory: 2848 2023/05/24 03:26:17 - mmengine - INFO - Epoch(val) [2][300/753] eta: 0:01:42 time: 0.2169 data_time: 0.0062 memory: 2848 2023/05/24 03:26:28 - mmengine - INFO - Epoch(val) [2][350/753] eta: 0:01:31 time: 0.2287 data_time: 0.0072 memory: 2851 2023/05/24 03:26:39 - mmengine - INFO - Epoch(val) [2][400/753] eta: 0:01:19 time: 0.2084 data_time: 0.0060 memory: 2851 2023/05/24 03:26:50 - mmengine - INFO - Epoch(val) [2][450/753] eta: 0:01:08 time: 0.2224 data_time: 0.0067 memory: 2849 2023/05/24 03:27:01 - mmengine - INFO - Epoch(val) [2][500/753] eta: 0:00:56 time: 0.2266 data_time: 0.0071 memory: 2850 2023/05/24 03:27:12 - mmengine - INFO - Epoch(val) [2][550/753] eta: 0:00:45 time: 0.2135 data_time: 0.0070 memory: 2849 2023/05/24 03:27:23 - mmengine - INFO - Epoch(val) [2][600/753] eta: 0:00:34 time: 0.2271 data_time: 0.0063 memory: 2852 2023/05/24 03:27:35 - mmengine - INFO - Epoch(val) [2][650/753] eta: 0:00:23 time: 0.2309 data_time: 0.0073 memory: 2849 2023/05/24 03:27:46 - mmengine - INFO - Epoch(val) [2][700/753] eta: 0:00:11 time: 0.2287 data_time: 0.0060 memory: 2852 2023/05/24 03:27:58 - mmengine - INFO - Epoch(val) [2][750/753] eta: 0:00:00 time: 0.2353 data_time: 0.0068 memory: 2852 2023/05/24 03:39:06 - mmengine - INFO - Epoch(val) [2][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.8009 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.8917 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.9204 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.9313 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1751 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1513 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.0907 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.2824 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1889 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2867 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2548 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.3168 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.2832 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1886 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.4056 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.5950 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.6820 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.7136 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3404 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1864 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.0930 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.2481 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2233 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0507 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.2241 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.3866 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.5023 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6507 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4213 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.8531 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1259 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3149 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4593 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.7454 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.8680 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.8892 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3412 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1828 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.0566 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.4726 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2419 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.1266 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.4350 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.5986 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.6725 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5398 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2052 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.6559 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.1791 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1661 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.5992 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.6992 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7436 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7574 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.2001 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2888 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0625 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.6320 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.7456 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.7580 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.7691 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1854 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2358 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.3189 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.5186 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2669 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.5680 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.5870 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.5929 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.6018 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1590 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2584 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.3301 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2239 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0110 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8600 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8732 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8828 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8950 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1397 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2907 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.3902 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2152 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.0960 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.7586 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.7700 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.7891 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.8169 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1352 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3273 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.6995 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.6650 data_time: 0.0069 time: 0.2330 2023/05/24 03:40:15 - mmengine - INFO - Epoch(train) [3][ 50/3862] lr: 1.4947e-04 eta: 5:45:35 time: 1.3698 data_time: 0.0572 memory: 21844 grad_norm: 1.1169 loss: 1.0655 loss_heatmap: 0.4847 layer_-1_loss_cls: 0.0781 layer_-1_loss_bbox: 0.5026 matched_ious: 0.5553 2023/05/24 03:41:22 - mmengine - INFO - Epoch(train) [3][ 100/3862] lr: 1.4888e-04 eta: 5:44:27 time: 1.3391 data_time: 0.0265 memory: 22221 grad_norm: 1.0859 loss: 1.0577 loss_heatmap: 0.4892 layer_-1_loss_cls: 0.0782 layer_-1_loss_bbox: 0.4903 matched_ious: 0.5721 2023/05/24 03:42:29 - mmengine - INFO - Epoch(train) [3][ 150/3862] lr: 1.4829e-04 eta: 5:43:19 time: 1.3375 data_time: 0.0288 memory: 21983 grad_norm: 1.1123 loss: 1.0881 loss_heatmap: 0.4974 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5096 matched_ious: 0.5783 2023/05/24 03:43:36 - mmengine - INFO - Epoch(train) [3][ 200/3862] lr: 1.4770e-04 eta: 5:42:11 time: 1.3405 data_time: 0.0267 memory: 21799 grad_norm: 1.1270 loss: 1.0855 loss_heatmap: 0.4915 layer_-1_loss_cls: 0.0790 layer_-1_loss_bbox: 0.5150 matched_ious: 0.6075 2023/05/24 03:44:44 - mmengine - INFO - Epoch(train) [3][ 250/3862] lr: 1.4710e-04 eta: 5:41:04 time: 1.3573 data_time: 0.0284 memory: 21787 grad_norm: 1.0126 loss: 1.0660 loss_heatmap: 0.4835 layer_-1_loss_cls: 0.0777 layer_-1_loss_bbox: 0.5049 matched_ious: 0.5966 2023/05/24 03:45:19 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 03:45:51 - mmengine - INFO - Epoch(train) [3][ 300/3862] lr: 1.4650e-04 eta: 5:39:57 time: 1.3428 data_time: 0.0282 memory: 22006 grad_norm: 1.0795 loss: 1.0709 loss_heatmap: 0.4916 layer_-1_loss_cls: 0.0790 layer_-1_loss_bbox: 0.5002 matched_ious: 0.5884 2023/05/24 03:46:58 - mmengine - INFO - Epoch(train) [3][ 350/3862] lr: 1.4590e-04 eta: 5:38:49 time: 1.3374 data_time: 0.0280 memory: 21851 grad_norm: 0.9926 loss: 1.0329 loss_heatmap: 0.4767 layer_-1_loss_cls: 0.0768 layer_-1_loss_bbox: 0.4794 matched_ious: 0.5836 2023/05/24 03:48:05 - mmengine - INFO - Epoch(train) [3][ 400/3862] lr: 1.4530e-04 eta: 5:37:42 time: 1.3511 data_time: 0.0276 memory: 21604 grad_norm: 1.1166 loss: 1.0705 loss_heatmap: 0.4876 layer_-1_loss_cls: 0.0782 layer_-1_loss_bbox: 0.5047 matched_ious: 0.5840 2023/05/24 03:49:13 - mmengine - INFO - Epoch(train) [3][ 450/3862] lr: 1.4469e-04 eta: 5:36:35 time: 1.3551 data_time: 0.0278 memory: 22009 grad_norm: 1.0393 loss: 1.0708 loss_heatmap: 0.4880 layer_-1_loss_cls: 0.0784 layer_-1_loss_bbox: 0.5044 matched_ious: 0.5802 2023/05/24 03:50:20 - mmengine - INFO - Epoch(train) [3][ 500/3862] lr: 1.4409e-04 eta: 5:35:27 time: 1.3362 data_time: 0.0264 memory: 22166 grad_norm: 1.0856 loss: 1.0531 loss_heatmap: 0.4757 layer_-1_loss_cls: 0.0773 layer_-1_loss_bbox: 0.5001 matched_ious: 0.5808 2023/05/24 03:51:26 - mmengine - INFO - Epoch(train) [3][ 550/3862] lr: 1.4348e-04 eta: 5:34:18 time: 1.3343 data_time: 0.0267 memory: 21917 grad_norm: 1.0097 loss: 1.0614 loss_heatmap: 0.4828 layer_-1_loss_cls: 0.0784 layer_-1_loss_bbox: 0.5002 matched_ious: 0.5662 2023/05/24 03:52:33 - mmengine - INFO - Epoch(train) [3][ 600/3862] lr: 1.4287e-04 eta: 5:33:10 time: 1.3383 data_time: 0.0273 memory: 22021 grad_norm: 1.0351 loss: 1.0725 loss_heatmap: 0.4868 layer_-1_loss_cls: 0.0792 layer_-1_loss_bbox: 0.5065 matched_ious: 0.5785 2023/05/24 03:53:40 - mmengine - INFO - Epoch(train) [3][ 650/3862] lr: 1.4225e-04 eta: 5:32:02 time: 1.3355 data_time: 0.0267 memory: 21539 grad_norm: 1.0341 loss: 1.0534 loss_heatmap: 0.4810 layer_-1_loss_cls: 0.0777 layer_-1_loss_bbox: 0.4947 matched_ious: 0.5823 2023/05/24 03:54:47 - mmengine - INFO - Epoch(train) [3][ 700/3862] lr: 1.4164e-04 eta: 5:30:55 time: 1.3462 data_time: 0.0276 memory: 22152 grad_norm: 1.0417 loss: 1.0689 loss_heatmap: 0.4878 layer_-1_loss_cls: 0.0780 layer_-1_loss_bbox: 0.5031 matched_ious: 0.5709 2023/05/24 03:55:55 - mmengine - INFO - Epoch(train) [3][ 750/3862] lr: 1.4102e-04 eta: 5:29:48 time: 1.3505 data_time: 0.0278 memory: 21896 grad_norm: 1.0940 loss: 1.0529 loss_heatmap: 0.4790 layer_-1_loss_cls: 0.0773 layer_-1_loss_bbox: 0.4966 matched_ious: 0.5539 2023/05/24 03:57:02 - mmengine - INFO - Epoch(train) [3][ 800/3862] lr: 1.4040e-04 eta: 5:28:40 time: 1.3389 data_time: 0.0266 memory: 21949 grad_norm: 1.1254 loss: 1.0582 loss_heatmap: 0.4907 layer_-1_loss_cls: 0.0780 layer_-1_loss_bbox: 0.4895 matched_ious: 0.5959 2023/05/24 03:58:09 - mmengine - INFO - Epoch(train) [3][ 850/3862] lr: 1.3978e-04 eta: 5:27:32 time: 1.3423 data_time: 0.0264 memory: 21760 grad_norm: 0.9776 loss: 1.0479 loss_heatmap: 0.4783 layer_-1_loss_cls: 0.0775 layer_-1_loss_bbox: 0.4921 matched_ious: 0.5576 2023/05/24 03:59:17 - mmengine - INFO - Epoch(train) [3][ 900/3862] lr: 1.3916e-04 eta: 5:26:26 time: 1.3547 data_time: 0.0264 memory: 21825 grad_norm: 1.0259 loss: 1.0648 loss_heatmap: 0.4827 layer_-1_loss_cls: 0.0769 layer_-1_loss_bbox: 0.5052 matched_ious: 0.5823 2023/05/24 04:00:24 - mmengine - INFO - Epoch(train) [3][ 950/3862] lr: 1.3854e-04 eta: 5:25:18 time: 1.3413 data_time: 0.0260 memory: 22009 grad_norm: 1.0797 loss: 1.0518 loss_heatmap: 0.4830 layer_-1_loss_cls: 0.0778 layer_-1_loss_bbox: 0.4911 matched_ious: 0.5856 2023/05/24 04:01:31 - mmengine - INFO - Epoch(train) [3][1000/3862] lr: 1.3791e-04 eta: 5:24:10 time: 1.3375 data_time: 0.0263 memory: 21974 grad_norm: 1.1143 loss: 1.0771 loss_heatmap: 0.4894 layer_-1_loss_cls: 0.0785 layer_-1_loss_bbox: 0.5092 matched_ious: 0.5746 2023/05/24 04:02:38 - mmengine - INFO - Epoch(train) [3][1050/3862] lr: 1.3728e-04 eta: 5:23:03 time: 1.3462 data_time: 0.0276 memory: 22219 grad_norm: 1.0320 loss: 1.0412 loss_heatmap: 0.4766 layer_-1_loss_cls: 0.0774 layer_-1_loss_bbox: 0.4873 matched_ious: 0.5518 2023/05/24 04:03:45 - mmengine - INFO - Epoch(train) [3][1100/3862] lr: 1.3665e-04 eta: 5:21:55 time: 1.3401 data_time: 0.0261 memory: 21793 grad_norm: 1.0493 loss: 1.0710 loss_heatmap: 0.4892 layer_-1_loss_cls: 0.0785 layer_-1_loss_bbox: 0.5033 matched_ious: 0.5796 2023/05/24 04:04:53 - mmengine - INFO - Epoch(train) [3][1150/3862] lr: 1.3602e-04 eta: 5:20:49 time: 1.3656 data_time: 0.0292 memory: 21980 grad_norm: 1.0479 loss: 1.0318 loss_heatmap: 0.4737 layer_-1_loss_cls: 0.0772 layer_-1_loss_bbox: 0.4809 matched_ious: 0.5775 2023/05/24 04:06:00 - mmengine - INFO - Epoch(train) [3][1200/3862] lr: 1.3539e-04 eta: 5:19:41 time: 1.3321 data_time: 0.0268 memory: 21725 grad_norm: 1.0283 loss: 1.0583 loss_heatmap: 0.4818 layer_-1_loss_cls: 0.0789 layer_-1_loss_bbox: 0.4976 matched_ious: 0.5913 2023/05/24 04:07:07 - mmengine - INFO - Epoch(train) [3][1250/3862] lr: 1.3476e-04 eta: 5:18:33 time: 1.3474 data_time: 0.0276 memory: 21916 grad_norm: 1.0993 loss: 1.0251 loss_heatmap: 0.4726 layer_-1_loss_cls: 0.0774 layer_-1_loss_bbox: 0.4751 matched_ious: 0.5597 2023/05/24 04:07:42 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 04:08:14 - mmengine - INFO - Epoch(train) [3][1300/3862] lr: 1.3412e-04 eta: 5:17:25 time: 1.3343 data_time: 0.0275 memory: 21920 grad_norm: 1.0605 loss: 1.0561 loss_heatmap: 0.4808 layer_-1_loss_cls: 0.0776 layer_-1_loss_bbox: 0.4977 matched_ious: 0.5775 2023/05/24 04:09:21 - mmengine - INFO - Epoch(train) [3][1350/3862] lr: 1.3348e-04 eta: 5:16:17 time: 1.3388 data_time: 0.0271 memory: 21755 grad_norm: 1.0535 loss: 1.0306 loss_heatmap: 0.4738 layer_-1_loss_cls: 0.0766 layer_-1_loss_bbox: 0.4803 matched_ious: 0.5760 2023/05/24 04:10:28 - mmengine - INFO - Epoch(train) [3][1400/3862] lr: 1.3284e-04 eta: 5:15:10 time: 1.3427 data_time: 0.0259 memory: 21987 grad_norm: 1.0199 loss: 1.0558 loss_heatmap: 0.4766 layer_-1_loss_cls: 0.0767 layer_-1_loss_bbox: 0.5024 matched_ious: 0.5866 2023/05/24 04:11:35 - mmengine - INFO - Epoch(train) [3][1450/3862] lr: 1.3220e-04 eta: 5:14:02 time: 1.3470 data_time: 0.0268 memory: 21809 grad_norm: 1.0165 loss: 1.0476 loss_heatmap: 0.4764 layer_-1_loss_cls: 0.0771 layer_-1_loss_bbox: 0.4942 matched_ious: 0.5908 2023/05/24 04:12:43 - mmengine - INFO - Epoch(train) [3][1500/3862] lr: 1.3156e-04 eta: 5:12:55 time: 1.3427 data_time: 0.0280 memory: 21808 grad_norm: 1.0616 loss: 1.0561 loss_heatmap: 0.4879 layer_-1_loss_cls: 0.0778 layer_-1_loss_bbox: 0.4904 matched_ious: 0.5917 2023/05/24 04:13:49 - mmengine - INFO - Epoch(train) [3][1550/3862] lr: 1.3092e-04 eta: 5:11:47 time: 1.3359 data_time: 0.0267 memory: 22031 grad_norm: 1.0409 loss: 1.0359 loss_heatmap: 0.4770 layer_-1_loss_cls: 0.0771 layer_-1_loss_bbox: 0.4818 matched_ious: 0.5717 2023/05/24 04:14:57 - mmengine - INFO - Epoch(train) [3][1600/3862] lr: 1.3027e-04 eta: 5:10:40 time: 1.3573 data_time: 0.0267 memory: 21977 grad_norm: 1.0161 loss: 1.0334 loss_heatmap: 0.4703 layer_-1_loss_cls: 0.0760 layer_-1_loss_bbox: 0.4871 matched_ious: 0.5687 2023/05/24 04:16:04 - mmengine - INFO - Epoch(train) [3][1650/3862] lr: 1.2963e-04 eta: 5:09:32 time: 1.3381 data_time: 0.0262 memory: 22258 grad_norm: 1.0049 loss: 1.0513 loss_heatmap: 0.4825 layer_-1_loss_cls: 0.0767 layer_-1_loss_bbox: 0.4921 matched_ious: 0.5952 2023/05/24 04:17:11 - mmengine - INFO - Epoch(train) [3][1700/3862] lr: 1.2898e-04 eta: 5:08:25 time: 1.3452 data_time: 0.0270 memory: 22006 grad_norm: 1.1779 loss: 1.0368 loss_heatmap: 0.4730 layer_-1_loss_cls: 0.0760 layer_-1_loss_bbox: 0.4878 matched_ious: 0.5946 2023/05/24 04:18:19 - mmengine - INFO - Epoch(train) [3][1750/3862] lr: 1.2833e-04 eta: 5:07:18 time: 1.3471 data_time: 0.0276 memory: 21939 grad_norm: 1.0467 loss: 1.0527 loss_heatmap: 0.4736 layer_-1_loss_cls: 0.0761 layer_-1_loss_bbox: 0.5029 matched_ious: 0.5902 2023/05/24 04:19:26 - mmengine - INFO - Epoch(train) [3][1800/3862] lr: 1.2768e-04 eta: 5:06:10 time: 1.3425 data_time: 0.0265 memory: 22105 grad_norm: 1.0445 loss: 1.0404 loss_heatmap: 0.4765 layer_-1_loss_cls: 0.0769 layer_-1_loss_bbox: 0.4870 matched_ious: 0.5763 2023/05/24 04:20:33 - mmengine - INFO - Epoch(train) [3][1850/3862] lr: 1.2703e-04 eta: 5:05:03 time: 1.3409 data_time: 0.0262 memory: 21784 grad_norm: 1.1258 loss: 1.0477 loss_heatmap: 0.4794 layer_-1_loss_cls: 0.0776 layer_-1_loss_bbox: 0.4907 matched_ious: 0.5923 2023/05/24 04:21:40 - mmengine - INFO - Epoch(train) [3][1900/3862] lr: 1.2637e-04 eta: 5:03:55 time: 1.3419 data_time: 0.0266 memory: 22184 grad_norm: 1.0825 loss: 1.0149 loss_heatmap: 0.4620 layer_-1_loss_cls: 0.0745 layer_-1_loss_bbox: 0.4784 matched_ious: 0.5730 2023/05/24 04:22:47 - mmengine - INFO - Epoch(train) [3][1950/3862] lr: 1.2572e-04 eta: 5:02:48 time: 1.3434 data_time: 0.0277 memory: 22024 grad_norm: 1.0558 loss: 1.0437 loss_heatmap: 0.4691 layer_-1_loss_cls: 0.0759 layer_-1_loss_bbox: 0.4987 matched_ious: 0.6094 2023/05/24 04:23:55 - mmengine - INFO - Epoch(train) [3][2000/3862] lr: 1.2507e-04 eta: 5:01:41 time: 1.3596 data_time: 0.0272 memory: 21741 grad_norm: 0.9945 loss: 1.0296 loss_heatmap: 0.4691 layer_-1_loss_cls: 0.0762 layer_-1_loss_bbox: 0.4843 matched_ious: 0.5584 2023/05/24 04:25:03 - mmengine - INFO - Epoch(train) [3][2050/3862] lr: 1.2441e-04 eta: 5:00:34 time: 1.3469 data_time: 0.0267 memory: 21930 grad_norm: 0.9899 loss: 1.0449 loss_heatmap: 0.4784 layer_-1_loss_cls: 0.0758 layer_-1_loss_bbox: 0.4908 matched_ious: 0.5862 2023/05/24 04:26:10 - mmengine - INFO - Epoch(train) [3][2100/3862] lr: 1.2375e-04 eta: 4:59:26 time: 1.3402 data_time: 0.0271 memory: 21707 grad_norm: 1.2026 loss: 1.0465 loss_heatmap: 0.4725 layer_-1_loss_cls: 0.0756 layer_-1_loss_bbox: 0.4984 matched_ious: 0.5957 2023/05/24 04:27:16 - mmengine - INFO - Epoch(train) [3][2150/3862] lr: 1.2309e-04 eta: 4:58:18 time: 1.3387 data_time: 0.0274 memory: 21831 grad_norm: 1.1433 loss: 1.0406 loss_heatmap: 0.4793 layer_-1_loss_cls: 0.0776 layer_-1_loss_bbox: 0.4837 matched_ious: 0.5578 2023/05/24 04:28:23 - mmengine - INFO - Epoch(train) [3][2200/3862] lr: 1.2243e-04 eta: 4:57:10 time: 1.3363 data_time: 0.0259 memory: 21734 grad_norm: 1.0304 loss: 1.0271 loss_heatmap: 0.4695 layer_-1_loss_cls: 0.0767 layer_-1_loss_bbox: 0.4808 matched_ious: 0.5830 2023/05/24 04:29:32 - mmengine - INFO - Epoch(train) [3][2250/3862] lr: 1.2177e-04 eta: 4:56:04 time: 1.3644 data_time: 0.0271 memory: 21817 grad_norm: 0.9893 loss: 1.0252 loss_heatmap: 0.4680 layer_-1_loss_cls: 0.0753 layer_-1_loss_bbox: 0.4818 matched_ious: 0.5823 2023/05/24 04:30:06 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 04:30:38 - mmengine - INFO - Epoch(train) [3][2300/3862] lr: 1.2111e-04 eta: 4:54:57 time: 1.3378 data_time: 0.0269 memory: 22008 grad_norm: 1.0775 loss: 1.0191 loss_heatmap: 0.4699 layer_-1_loss_cls: 0.0764 layer_-1_loss_bbox: 0.4728 matched_ious: 0.5953 2023/05/24 04:31:46 - mmengine - INFO - Epoch(train) [3][2350/3862] lr: 1.2045e-04 eta: 4:53:49 time: 1.3429 data_time: 0.0264 memory: 22055 grad_norm: 1.0061 loss: 1.0556 loss_heatmap: 0.4785 layer_-1_loss_cls: 0.0771 layer_-1_loss_bbox: 0.5000 matched_ious: 0.5556 2023/05/24 04:32:52 - mmengine - INFO - Epoch(train) [3][2400/3862] lr: 1.1979e-04 eta: 4:52:41 time: 1.3343 data_time: 0.0273 memory: 21779 grad_norm: 1.0460 loss: 1.0277 loss_heatmap: 0.4694 layer_-1_loss_cls: 0.0756 layer_-1_loss_bbox: 0.4827 matched_ious: 0.5593 2023/05/24 04:34:00 - mmengine - INFO - Epoch(train) [3][2450/3862] lr: 1.1912e-04 eta: 4:51:35 time: 1.3623 data_time: 0.0262 memory: 21860 grad_norm: 0.9884 loss: 1.0245 loss_heatmap: 0.4602 layer_-1_loss_cls: 0.0743 layer_-1_loss_bbox: 0.4900 matched_ious: 0.5806 2023/05/24 04:35:08 - mmengine - INFO - Epoch(train) [3][2500/3862] lr: 1.1846e-04 eta: 4:50:27 time: 1.3447 data_time: 0.0262 memory: 21681 grad_norm: 1.1007 loss: 1.0356 loss_heatmap: 0.4717 layer_-1_loss_cls: 0.0772 layer_-1_loss_bbox: 0.4866 matched_ious: 0.5906 2023/05/24 04:36:15 - mmengine - INFO - Epoch(train) [3][2550/3862] lr: 1.1779e-04 eta: 4:49:20 time: 1.3442 data_time: 0.0265 memory: 22014 grad_norm: 0.9961 loss: 1.0377 loss_heatmap: 0.4712 layer_-1_loss_cls: 0.0762 layer_-1_loss_bbox: 0.4904 matched_ious: 0.6009 2023/05/24 04:37:22 - mmengine - INFO - Epoch(train) [3][2600/3862] lr: 1.1712e-04 eta: 4:48:13 time: 1.3466 data_time: 0.0266 memory: 21834 grad_norm: 1.0206 loss: 1.0304 loss_heatmap: 0.4657 layer_-1_loss_cls: 0.0754 layer_-1_loss_bbox: 0.4893 matched_ious: 0.5835 2023/05/24 04:38:29 - mmengine - INFO - Epoch(train) [3][2650/3862] lr: 1.1646e-04 eta: 4:47:05 time: 1.3396 data_time: 0.0264 memory: 21637 grad_norm: 1.0595 loss: 1.0230 loss_heatmap: 0.4669 layer_-1_loss_cls: 0.0762 layer_-1_loss_bbox: 0.4798 matched_ious: 0.5924 2023/05/24 04:39:37 - mmengine - INFO - Epoch(train) [3][2700/3862] lr: 1.1579e-04 eta: 4:45:58 time: 1.3545 data_time: 0.0254 memory: 21729 grad_norm: 1.0806 loss: 1.0307 loss_heatmap: 0.4666 layer_-1_loss_cls: 0.0750 layer_-1_loss_bbox: 0.4891 matched_ious: 0.5766 2023/05/24 04:40:44 - mmengine - INFO - Epoch(train) [3][2750/3862] lr: 1.1512e-04 eta: 4:44:51 time: 1.3415 data_time: 0.0269 memory: 21668 grad_norm: 0.9868 loss: 1.0222 loss_heatmap: 0.4614 layer_-1_loss_cls: 0.0739 layer_-1_loss_bbox: 0.4869 matched_ious: 0.5866 2023/05/24 04:41:51 - mmengine - INFO - Epoch(train) [3][2800/3862] lr: 1.1445e-04 eta: 4:43:43 time: 1.3421 data_time: 0.0265 memory: 21982 grad_norm: 0.9848 loss: 1.0344 loss_heatmap: 0.4711 layer_-1_loss_cls: 0.0761 layer_-1_loss_bbox: 0.4871 matched_ious: 0.5896 2023/05/24 04:42:58 - mmengine - INFO - Epoch(train) [3][2850/3862] lr: 1.1378e-04 eta: 4:42:35 time: 1.3353 data_time: 0.0269 memory: 21772 grad_norm: 1.1682 loss: 1.0076 loss_heatmap: 0.4573 layer_-1_loss_cls: 0.0744 layer_-1_loss_bbox: 0.4759 matched_ious: 0.5910 2023/05/24 04:44:06 - mmengine - INFO - Epoch(train) [3][2900/3862] lr: 1.1311e-04 eta: 4:41:29 time: 1.3677 data_time: 0.0265 memory: 21722 grad_norm: 1.1009 loss: 1.0113 loss_heatmap: 0.4606 layer_-1_loss_cls: 0.0748 layer_-1_loss_bbox: 0.4759 matched_ious: 0.5830 2023/05/24 04:45:14 - mmengine - INFO - Epoch(train) [3][2950/3862] lr: 1.1243e-04 eta: 4:40:22 time: 1.3483 data_time: 0.0265 memory: 21763 grad_norm: 1.0225 loss: 1.0083 loss_heatmap: 0.4630 layer_-1_loss_cls: 0.0752 layer_-1_loss_bbox: 0.4701 matched_ious: 0.6007 2023/05/24 04:46:21 - mmengine - INFO - Epoch(train) [3][3000/3862] lr: 1.1176e-04 eta: 4:39:14 time: 1.3388 data_time: 0.0266 memory: 21585 grad_norm: 1.0184 loss: 1.0335 loss_heatmap: 0.4635 layer_-1_loss_cls: 0.0752 layer_-1_loss_bbox: 0.4947 matched_ious: 0.5648 2023/05/24 04:47:28 - mmengine - INFO - Epoch(train) [3][3050/3862] lr: 1.1109e-04 eta: 4:38:07 time: 1.3402 data_time: 0.0269 memory: 22024 grad_norm: 1.0254 loss: 1.0325 loss_heatmap: 0.4639 layer_-1_loss_cls: 0.0745 layer_-1_loss_bbox: 0.4940 matched_ious: 0.5652 2023/05/24 04:48:35 - mmengine - INFO - Epoch(train) [3][3100/3862] lr: 1.1042e-04 eta: 4:37:00 time: 1.3544 data_time: 0.0270 memory: 22060 grad_norm: 1.0291 loss: 1.0187 loss_heatmap: 0.4648 layer_-1_loss_cls: 0.0745 layer_-1_loss_bbox: 0.4794 matched_ious: 0.6031 2023/05/24 04:49:42 - mmengine - INFO - Epoch(train) [3][3150/3862] lr: 1.0974e-04 eta: 4:35:52 time: 1.3431 data_time: 0.0265 memory: 21902 grad_norm: 0.9788 loss: 0.9943 loss_heatmap: 0.4555 layer_-1_loss_cls: 0.0743 layer_-1_loss_bbox: 0.4645 matched_ious: 0.5909 2023/05/24 04:50:50 - mmengine - INFO - Epoch(train) [3][3200/3862] lr: 1.0907e-04 eta: 4:34:45 time: 1.3510 data_time: 0.0271 memory: 21752 grad_norm: 1.0156 loss: 1.0284 loss_heatmap: 0.4667 layer_-1_loss_cls: 0.0752 layer_-1_loss_bbox: 0.4866 matched_ious: 0.5742 2023/05/24 04:51:57 - mmengine - INFO - Epoch(train) [3][3250/3862] lr: 1.0839e-04 eta: 4:33:38 time: 1.3361 data_time: 0.0268 memory: 21818 grad_norm: 1.0161 loss: 1.0318 loss_heatmap: 0.4672 layer_-1_loss_cls: 0.0752 layer_-1_loss_bbox: 0.4893 matched_ious: 0.5718 2023/05/24 04:52:32 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 04:53:04 - mmengine - INFO - Epoch(train) [3][3300/3862] lr: 1.0772e-04 eta: 4:32:30 time: 1.3436 data_time: 0.0257 memory: 21755 grad_norm: 0.9466 loss: 0.9974 loss_heatmap: 0.4541 layer_-1_loss_cls: 0.0743 layer_-1_loss_bbox: 0.4690 matched_ious: 0.5624 2023/05/24 04:54:13 - mmengine - INFO - Epoch(train) [3][3350/3862] lr: 1.0704e-04 eta: 4:31:24 time: 1.3742 data_time: 0.0263 memory: 21938 grad_norm: 1.0286 loss: 1.0221 loss_heatmap: 0.4688 layer_-1_loss_cls: 0.0763 layer_-1_loss_bbox: 0.4770 matched_ious: 0.5911 2023/05/24 04:55:20 - mmengine - INFO - Epoch(train) [3][3400/3862] lr: 1.0637e-04 eta: 4:30:17 time: 1.3463 data_time: 0.0279 memory: 21723 grad_norm: 1.1390 loss: 1.0101 loss_heatmap: 0.4594 layer_-1_loss_cls: 0.0747 layer_-1_loss_bbox: 0.4760 matched_ious: 0.5789 2023/05/24 04:56:27 - mmengine - INFO - Epoch(train) [3][3450/3862] lr: 1.0569e-04 eta: 4:29:09 time: 1.3349 data_time: 0.0269 memory: 21838 grad_norm: 1.2961 loss: 1.0124 loss_heatmap: 0.4647 layer_-1_loss_cls: 0.0743 layer_-1_loss_bbox: 0.4734 matched_ious: 0.5744 2023/05/24 04:57:34 - mmengine - INFO - Epoch(train) [3][3500/3862] lr: 1.0501e-04 eta: 4:28:01 time: 1.3379 data_time: 0.0260 memory: 21948 grad_norm: 1.0285 loss: 1.0293 loss_heatmap: 0.4672 layer_-1_loss_cls: 0.0750 layer_-1_loss_bbox: 0.4871 matched_ious: 0.6022 2023/05/24 04:58:40 - mmengine - INFO - Epoch(train) [3][3550/3862] lr: 1.0434e-04 eta: 4:26:54 time: 1.3349 data_time: 0.0265 memory: 22250 grad_norm: 1.0255 loss: 1.0053 loss_heatmap: 0.4621 layer_-1_loss_cls: 0.0755 layer_-1_loss_bbox: 0.4678 matched_ious: 0.5730 2023/05/24 04:59:47 - mmengine - INFO - Epoch(train) [3][3600/3862] lr: 1.0366e-04 eta: 4:25:46 time: 1.3391 data_time: 0.0259 memory: 21962 grad_norm: 1.0113 loss: 1.0225 loss_heatmap: 0.4656 layer_-1_loss_cls: 0.0751 layer_-1_loss_bbox: 0.4818 matched_ious: 0.5709 2023/05/24 05:00:54 - mmengine - INFO - Epoch(train) [3][3650/3862] lr: 1.0298e-04 eta: 4:24:38 time: 1.3351 data_time: 0.0263 memory: 21660 grad_norm: 1.0676 loss: 0.9987 loss_heatmap: 0.4592 layer_-1_loss_cls: 0.0751 layer_-1_loss_bbox: 0.4644 matched_ious: 0.5800 2023/05/24 05:02:01 - mmengine - INFO - Epoch(train) [3][3700/3862] lr: 1.0231e-04 eta: 4:23:31 time: 1.3456 data_time: 0.0269 memory: 21594 grad_norm: 1.0396 loss: 1.0253 loss_heatmap: 0.4649 layer_-1_loss_cls: 0.0750 layer_-1_loss_bbox: 0.4854 matched_ious: 0.5735 2023/05/24 05:03:08 - mmengine - INFO - Epoch(train) [3][3750/3862] lr: 1.0163e-04 eta: 4:22:23 time: 1.3344 data_time: 0.0266 memory: 21967 grad_norm: 1.0282 loss: 1.0131 loss_heatmap: 0.4596 layer_-1_loss_cls: 0.0745 layer_-1_loss_bbox: 0.4790 matched_ious: 0.5811 2023/05/24 05:04:15 - mmengine - INFO - Epoch(train) [3][3800/3862] lr: 1.0095e-04 eta: 4:21:15 time: 1.3429 data_time: 0.0252 memory: 21707 grad_norm: 1.0350 loss: 0.9983 loss_heatmap: 0.4544 layer_-1_loss_cls: 0.0744 layer_-1_loss_bbox: 0.4695 matched_ious: 0.5761 2023/05/24 05:05:22 - mmengine - INFO - Epoch(train) [3][3850/3862] lr: 1.0028e-04 eta: 4:20:08 time: 1.3378 data_time: 0.0266 memory: 21848 grad_norm: 0.9704 loss: 0.9827 loss_heatmap: 0.4504 layer_-1_loss_cls: 0.0726 layer_-1_loss_bbox: 0.4598 matched_ious: 0.5638 2023/05/24 05:05:38 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 05:05:38 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/05/24 05:05:54 - mmengine - INFO - Epoch(val) [3][ 50/753] eta: 0:02:49 time: 0.2414 data_time: 0.0139 memory: 21522 2023/05/24 05:06:05 - mmengine - INFO - Epoch(val) [3][100/753] eta: 0:02:31 time: 0.2223 data_time: 0.0065 memory: 2850 2023/05/24 05:06:16 - mmengine - INFO - Epoch(val) [3][150/753] eta: 0:02:18 time: 0.2242 data_time: 0.0070 memory: 2848 2023/05/24 05:06:28 - mmengine - INFO - Epoch(val) [3][200/753] eta: 0:02:07 time: 0.2315 data_time: 0.0070 memory: 2852 2023/05/24 05:06:39 - mmengine - INFO - Epoch(val) [3][250/753] eta: 0:01:54 time: 0.2225 data_time: 0.0078 memory: 2848 2023/05/24 05:06:50 - mmengine - INFO - Epoch(val) [3][300/753] eta: 0:01:43 time: 0.2225 data_time: 0.0068 memory: 2848 2023/05/24 05:07:02 - mmengine - INFO - Epoch(val) [3][350/753] eta: 0:01:31 time: 0.2255 data_time: 0.0061 memory: 2851 2023/05/24 05:07:12 - mmengine - INFO - Epoch(val) [3][400/753] eta: 0:01:19 time: 0.2147 data_time: 0.0067 memory: 2851 2023/05/24 05:07:23 - mmengine - INFO - Epoch(val) [3][450/753] eta: 0:01:08 time: 0.2203 data_time: 0.0071 memory: 2849 2023/05/24 05:07:34 - mmengine - INFO - Epoch(val) [3][500/753] eta: 0:00:56 time: 0.2227 data_time: 0.0066 memory: 2850 2023/05/24 05:07:45 - mmengine - INFO - Epoch(val) [3][550/753] eta: 0:00:45 time: 0.2169 data_time: 0.0063 memory: 2849 2023/05/24 05:07:57 - mmengine - INFO - Epoch(val) [3][600/753] eta: 0:00:34 time: 0.2263 data_time: 0.0070 memory: 2852 2023/05/24 05:08:08 - mmengine - INFO - Epoch(val) [3][650/753] eta: 0:00:23 time: 0.2364 data_time: 0.0082 memory: 2849 2023/05/24 05:08:20 - mmengine - INFO - Epoch(val) [3][700/753] eta: 0:00:11 time: 0.2253 data_time: 0.0051 memory: 2852 2023/05/24 05:08:31 - mmengine - INFO - Epoch(val) [3][750/753] eta: 0:00:00 time: 0.2269 data_time: 0.0078 memory: 2852 2023/05/24 05:19:50 - mmengine - INFO - Epoch(val) [3][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.8070 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.8988 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.9246 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.9348 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1748 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1514 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.0785 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.2718 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1872 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2868 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2553 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.3087 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.2728 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1886 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.4019 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.6059 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.6948 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.7359 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3461 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1847 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.0845 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.2541 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2305 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0406 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.2068 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.3864 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.5137 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6894 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4311 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.8279 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1301 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.2927 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4874 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.7656 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.8751 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.8964 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3317 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1869 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.0613 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.4588 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2669 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.1399 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.4248 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.5929 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.6733 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5296 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2120 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.6514 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.1929 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1568 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.6019 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.6971 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7347 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7479 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.1875 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2819 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0613 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.6458 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.7549 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.7682 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.7807 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1835 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2391 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.2802 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.4365 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2620 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.5708 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.5925 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.6006 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.6089 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1569 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2547 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.3355 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2255 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0125 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8651 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8768 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8875 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8969 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1384 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2877 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.3974 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2127 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.1007 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.7666 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.7782 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.7972 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.8237 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1300 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3235 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.7038 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.6701 data_time: 0.0079 time: 0.2245 2023/05/24 05:20:58 - mmengine - INFO - Epoch(train) [4][ 50/3862] lr: 9.9436e-05 eta: 4:18:45 time: 1.3667 data_time: 0.0713 memory: 21794 grad_norm: 1.0246 loss: 1.0069 loss_heatmap: 0.4610 layer_-1_loss_cls: 0.0745 layer_-1_loss_bbox: 0.4715 matched_ious: 0.5765 2023/05/24 05:22:05 - mmengine - INFO - Epoch(train) [4][ 100/3862] lr: 9.8759e-05 eta: 4:17:38 time: 1.3450 data_time: 0.0422 memory: 21844 grad_norm: 1.0376 loss: 1.0080 loss_heatmap: 0.4562 layer_-1_loss_cls: 0.0744 layer_-1_loss_bbox: 0.4774 matched_ious: 0.5668 2023/05/24 05:23:13 - mmengine - INFO - Epoch(train) [4][ 150/3862] lr: 9.8082e-05 eta: 4:16:30 time: 1.3424 data_time: 0.0435 memory: 21957 grad_norm: 0.9594 loss: 1.0085 loss_heatmap: 0.4609 layer_-1_loss_cls: 0.0744 layer_-1_loss_bbox: 0.4733 matched_ious: 0.5619 2023/05/24 05:24:21 - mmengine - INFO - Epoch(train) [4][ 200/3862] lr: 9.7405e-05 eta: 4:15:24 time: 1.3676 data_time: 0.0441 memory: 22159 grad_norm: 1.1034 loss: 1.0118 loss_heatmap: 0.4574 layer_-1_loss_cls: 0.0739 layer_-1_loss_bbox: 0.4806 matched_ious: 0.5537 2023/05/24 05:25:28 - mmengine - INFO - Epoch(train) [4][ 250/3862] lr: 9.6728e-05 eta: 4:14:17 time: 1.3468 data_time: 0.0442 memory: 22054 grad_norm: 1.0629 loss: 1.0059 loss_heatmap: 0.4582 layer_-1_loss_cls: 0.0733 layer_-1_loss_bbox: 0.4745 matched_ious: 0.5827 2023/05/24 05:26:35 - mmengine - INFO - Epoch(train) [4][ 300/3862] lr: 9.6051e-05 eta: 4:13:09 time: 1.3432 data_time: 0.0404 memory: 21940 grad_norm: 1.2509 loss: 0.9958 loss_heatmap: 0.4489 layer_-1_loss_cls: 0.0729 layer_-1_loss_bbox: 0.4740 matched_ious: 0.5806 2023/05/24 05:27:43 - mmengine - INFO - Epoch(train) [4][ 350/3862] lr: 9.5375e-05 eta: 4:12:02 time: 1.3472 data_time: 0.0445 memory: 22002 grad_norm: 1.0595 loss: 0.9808 loss_heatmap: 0.4523 layer_-1_loss_cls: 0.0729 layer_-1_loss_bbox: 0.4555 matched_ious: 0.5953 2023/05/24 05:28:50 - mmengine - INFO - Epoch(train) [4][ 400/3862] lr: 9.4699e-05 eta: 4:10:55 time: 1.3425 data_time: 0.0438 memory: 22090 grad_norm: 1.0924 loss: 1.0007 loss_heatmap: 0.4596 layer_-1_loss_cls: 0.0741 layer_-1_loss_bbox: 0.4669 matched_ious: 0.5936 2023/05/24 05:29:09 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 05:29:58 - mmengine - INFO - Epoch(train) [4][ 450/3862] lr: 9.4022e-05 eta: 4:09:48 time: 1.3550 data_time: 0.0474 memory: 21781 grad_norm: 0.9982 loss: 1.0103 loss_heatmap: 0.4569 layer_-1_loss_cls: 0.0738 layer_-1_loss_bbox: 0.4795 matched_ious: 0.6044 2023/05/24 05:31:04 - mmengine - INFO - Epoch(train) [4][ 500/3862] lr: 9.3347e-05 eta: 4:08:40 time: 1.3347 data_time: 0.0404 memory: 21841 grad_norm: 1.0904 loss: 1.0115 loss_heatmap: 0.4580 layer_-1_loss_cls: 0.0740 layer_-1_loss_bbox: 0.4795 matched_ious: 0.5703 2023/05/24 05:32:11 - mmengine - INFO - Epoch(train) [4][ 550/3862] lr: 9.2671e-05 eta: 4:07:32 time: 1.3367 data_time: 0.0444 memory: 22085 grad_norm: 1.0137 loss: 1.0042 loss_heatmap: 0.4548 layer_-1_loss_cls: 0.0735 layer_-1_loss_bbox: 0.4759 matched_ious: 0.5781 2023/05/24 05:33:18 - mmengine - INFO - Epoch(train) [4][ 600/3862] lr: 9.1996e-05 eta: 4:06:25 time: 1.3385 data_time: 0.0422 memory: 22268 grad_norm: 1.0107 loss: 0.9854 loss_heatmap: 0.4475 layer_-1_loss_cls: 0.0732 layer_-1_loss_bbox: 0.4648 matched_ious: 0.5931 2023/05/24 05:34:26 - mmengine - INFO - Epoch(train) [4][ 650/3862] lr: 9.1321e-05 eta: 4:05:18 time: 1.3555 data_time: 0.0436 memory: 22189 grad_norm: 1.0357 loss: 0.9914 loss_heatmap: 0.4529 layer_-1_loss_cls: 0.0732 layer_-1_loss_bbox: 0.4653 matched_ious: 0.5682 2023/05/24 05:35:33 - mmengine - INFO - Epoch(train) [4][ 700/3862] lr: 9.0647e-05 eta: 4:04:10 time: 1.3443 data_time: 0.0411 memory: 21684 grad_norm: 0.9896 loss: 0.9915 loss_heatmap: 0.4505 layer_-1_loss_cls: 0.0731 layer_-1_loss_bbox: 0.4679 matched_ious: 0.6211 2023/05/24 05:36:41 - mmengine - INFO - Epoch(train) [4][ 750/3862] lr: 8.9973e-05 eta: 4:03:03 time: 1.3486 data_time: 0.0440 memory: 21686 grad_norm: 1.0211 loss: 1.0005 loss_heatmap: 0.4554 layer_-1_loss_cls: 0.0733 layer_-1_loss_bbox: 0.4719 matched_ious: 0.5942 2023/05/24 05:37:48 - mmengine - INFO - Epoch(train) [4][ 800/3862] lr: 8.9299e-05 eta: 4:01:56 time: 1.3397 data_time: 0.0401 memory: 21900 grad_norm: 1.0621 loss: 0.9842 loss_heatmap: 0.4484 layer_-1_loss_cls: 0.0722 layer_-1_loss_bbox: 0.4636 matched_ious: 0.5649 2023/05/24 05:38:55 - mmengine - INFO - Epoch(train) [4][ 850/3862] lr: 8.8626e-05 eta: 4:00:49 time: 1.3541 data_time: 0.0437 memory: 21802 grad_norm: 1.0929 loss: 0.9896 loss_heatmap: 0.4472 layer_-1_loss_cls: 0.0728 layer_-1_loss_bbox: 0.4696 matched_ious: 0.5877 2023/05/24 05:40:02 - mmengine - INFO - Epoch(train) [4][ 900/3862] lr: 8.7954e-05 eta: 3:59:41 time: 1.3377 data_time: 0.0422 memory: 21973 grad_norm: 1.0591 loss: 1.0045 loss_heatmap: 0.4580 layer_-1_loss_cls: 0.0734 layer_-1_loss_bbox: 0.4732 matched_ious: 0.5933 2023/05/24 05:41:09 - mmengine - INFO - Epoch(train) [4][ 950/3862] lr: 8.7282e-05 eta: 3:58:34 time: 1.3410 data_time: 0.0444 memory: 21920 grad_norm: 1.2050 loss: 0.9924 loss_heatmap: 0.4532 layer_-1_loss_cls: 0.0734 layer_-1_loss_bbox: 0.4658 matched_ious: 0.6033 2023/05/24 05:42:17 - mmengine - INFO - Epoch(train) [4][1000/3862] lr: 8.6611e-05 eta: 3:57:26 time: 1.3448 data_time: 0.0422 memory: 21745 grad_norm: 1.0258 loss: 0.9926 loss_heatmap: 0.4539 layer_-1_loss_cls: 0.0729 layer_-1_loss_bbox: 0.4657 matched_ious: 0.5951 2023/05/24 05:43:24 - mmengine - INFO - Epoch(train) [4][1050/3862] lr: 8.5940e-05 eta: 3:56:19 time: 1.3441 data_time: 0.0457 memory: 21769 grad_norm: 1.0226 loss: 0.9937 loss_heatmap: 0.4493 layer_-1_loss_cls: 0.0724 layer_-1_loss_bbox: 0.4720 matched_ious: 0.5745 2023/05/24 05:44:31 - mmengine - INFO - Epoch(train) [4][1100/3862] lr: 8.5270e-05 eta: 3:55:12 time: 1.3524 data_time: 0.0426 memory: 22044 grad_norm: 1.0155 loss: 0.9967 loss_heatmap: 0.4524 layer_-1_loss_cls: 0.0721 layer_-1_loss_bbox: 0.4722 matched_ious: 0.5784 2023/05/24 05:45:38 - mmengine - INFO - Epoch(train) [4][1150/3862] lr: 8.4601e-05 eta: 3:54:04 time: 1.3388 data_time: 0.0443 memory: 22103 grad_norm: 1.0208 loss: 0.9986 loss_heatmap: 0.4500 layer_-1_loss_cls: 0.0730 layer_-1_loss_bbox: 0.4756 matched_ious: 0.6119 2023/05/24 05:46:45 - mmengine - INFO - Epoch(train) [4][1200/3862] lr: 8.3932e-05 eta: 3:52:57 time: 1.3420 data_time: 0.0430 memory: 21526 grad_norm: 1.0214 loss: 0.9968 loss_heatmap: 0.4530 layer_-1_loss_cls: 0.0732 layer_-1_loss_bbox: 0.4706 matched_ious: 0.5846 2023/05/24 05:47:52 - mmengine - INFO - Epoch(train) [4][1250/3862] lr: 8.3264e-05 eta: 3:51:49 time: 1.3333 data_time: 0.0424 memory: 21996 grad_norm: 1.0750 loss: 1.0035 loss_heatmap: 0.4533 layer_-1_loss_cls: 0.0737 layer_-1_loss_bbox: 0.4766 matched_ious: 0.5819 2023/05/24 05:48:59 - mmengine - INFO - Epoch(train) [4][1300/3862] lr: 8.2597e-05 eta: 3:50:42 time: 1.3449 data_time: 0.0423 memory: 21852 grad_norm: 1.0049 loss: 1.0037 loss_heatmap: 0.4613 layer_-1_loss_cls: 0.0737 layer_-1_loss_bbox: 0.4686 matched_ious: 0.5597 2023/05/24 05:50:06 - mmengine - INFO - Epoch(train) [4][1350/3862] lr: 8.1931e-05 eta: 3:49:34 time: 1.3404 data_time: 0.0441 memory: 21947 grad_norm: 0.9738 loss: 0.9725 loss_heatmap: 0.4449 layer_-1_loss_cls: 0.0719 layer_-1_loss_bbox: 0.4558 matched_ious: 0.6015 2023/05/24 05:51:13 - mmengine - INFO - Epoch(train) [4][1400/3862] lr: 8.1265e-05 eta: 3:48:27 time: 1.3365 data_time: 0.0420 memory: 21771 grad_norm: 1.1431 loss: 0.9915 loss_heatmap: 0.4526 layer_-1_loss_cls: 0.0739 layer_-1_loss_bbox: 0.4650 matched_ious: 0.5639 2023/05/24 05:51:32 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 05:52:20 - mmengine - INFO - Epoch(train) [4][1450/3862] lr: 8.0601e-05 eta: 3:47:19 time: 1.3374 data_time: 0.0439 memory: 21734 grad_norm: 1.0406 loss: 0.9906 loss_heatmap: 0.4494 layer_-1_loss_cls: 0.0726 layer_-1_loss_bbox: 0.4685 matched_ious: 0.5921 2023/05/24 05:53:27 - mmengine - INFO - Epoch(train) [4][1500/3862] lr: 7.9937e-05 eta: 3:46:12 time: 1.3398 data_time: 0.0451 memory: 21725 grad_norm: 1.0834 loss: 0.9932 loss_heatmap: 0.4540 layer_-1_loss_cls: 0.0738 layer_-1_loss_bbox: 0.4653 matched_ious: 0.5679 2023/05/24 05:54:35 - mmengine - INFO - Epoch(train) [4][1550/3862] lr: 7.9274e-05 eta: 3:45:05 time: 1.3666 data_time: 0.0452 memory: 22022 grad_norm: 1.0270 loss: 0.9698 loss_heatmap: 0.4463 layer_-1_loss_cls: 0.0727 layer_-1_loss_bbox: 0.4508 matched_ious: 0.5803 2023/05/24 05:55:42 - mmengine - INFO - Epoch(train) [4][1600/3862] lr: 7.8612e-05 eta: 3:43:58 time: 1.3427 data_time: 0.0416 memory: 22013 grad_norm: 1.0737 loss: 0.9665 loss_heatmap: 0.4480 layer_-1_loss_cls: 0.0728 layer_-1_loss_bbox: 0.4457 matched_ious: 0.5587 2023/05/24 05:56:50 - mmengine - INFO - Epoch(train) [4][1650/3862] lr: 7.7951e-05 eta: 3:42:50 time: 1.3434 data_time: 0.0461 memory: 21881 grad_norm: 1.0432 loss: 0.9803 loss_heatmap: 0.4502 layer_-1_loss_cls: 0.0719 layer_-1_loss_bbox: 0.4583 matched_ious: 0.5911 2023/05/24 05:57:57 - mmengine - INFO - Epoch(train) [4][1700/3862] lr: 7.7291e-05 eta: 3:41:43 time: 1.3390 data_time: 0.0408 memory: 21852 grad_norm: 1.0408 loss: 1.0035 loss_heatmap: 0.4604 layer_-1_loss_cls: 0.0738 layer_-1_loss_bbox: 0.4693 matched_ious: 0.5735 2023/05/24 05:59:05 - mmengine - INFO - Epoch(train) [4][1750/3862] lr: 7.6633e-05 eta: 3:40:36 time: 1.3613 data_time: 0.0440 memory: 21894 grad_norm: 1.0766 loss: 1.0013 loss_heatmap: 0.4559 layer_-1_loss_cls: 0.0734 layer_-1_loss_bbox: 0.4720 matched_ious: 0.5676 2023/05/24 06:00:11 - mmengine - INFO - Epoch(train) [4][1800/3862] lr: 7.5975e-05 eta: 3:39:28 time: 1.3353 data_time: 0.0428 memory: 21975 grad_norm: 0.9828 loss: 0.9577 loss_heatmap: 0.4355 layer_-1_loss_cls: 0.0705 layer_-1_loss_bbox: 0.4518 matched_ious: 0.5473 2023/05/24 06:01:18 - mmengine - INFO - Epoch(train) [4][1850/3862] lr: 7.5318e-05 eta: 3:38:21 time: 1.3368 data_time: 0.0438 memory: 21660 grad_norm: 1.1038 loss: 0.9871 loss_heatmap: 0.4507 layer_-1_loss_cls: 0.0737 layer_-1_loss_bbox: 0.4627 matched_ious: 0.5926 2023/05/24 06:02:26 - mmengine - INFO - Epoch(train) [4][1900/3862] lr: 7.4663e-05 eta: 3:37:13 time: 1.3465 data_time: 0.0437 memory: 22027 grad_norm: 1.0572 loss: 0.9797 loss_heatmap: 0.4420 layer_-1_loss_cls: 0.0713 layer_-1_loss_bbox: 0.4664 matched_ious: 0.5810 2023/05/24 06:03:33 - mmengine - INFO - Epoch(train) [4][1950/3862] lr: 7.4009e-05 eta: 3:36:06 time: 1.3477 data_time: 0.0442 memory: 21850 grad_norm: 1.0683 loss: 0.9659 loss_heatmap: 0.4387 layer_-1_loss_cls: 0.0709 layer_-1_loss_bbox: 0.4563 matched_ious: 0.5793 2023/05/24 06:04:41 - mmengine - INFO - Epoch(train) [4][2000/3862] lr: 7.3355e-05 eta: 3:34:59 time: 1.3564 data_time: 0.0420 memory: 21629 grad_norm: 0.9918 loss: 0.9622 loss_heatmap: 0.4443 layer_-1_loss_cls: 0.0719 layer_-1_loss_bbox: 0.4460 matched_ious: 0.5957 2023/05/24 06:05:48 - mmengine - INFO - Epoch(train) [4][2050/3862] lr: 7.2704e-05 eta: 3:33:52 time: 1.3448 data_time: 0.0449 memory: 21766 grad_norm: 0.9836 loss: 0.9697 loss_heatmap: 0.4454 layer_-1_loss_cls: 0.0717 layer_-1_loss_bbox: 0.4526 matched_ious: 0.5682 2023/05/24 06:06:55 - mmengine - INFO - Epoch(train) [4][2100/3862] lr: 7.2053e-05 eta: 3:32:44 time: 1.3352 data_time: 0.0424 memory: 21888 grad_norm: 1.1439 loss: 0.9805 loss_heatmap: 0.4440 layer_-1_loss_cls: 0.0721 layer_-1_loss_bbox: 0.4644 matched_ious: 0.5574 2023/05/24 06:08:02 - mmengine - INFO - Epoch(train) [4][2150/3862] lr: 7.1404e-05 eta: 3:31:37 time: 1.3440 data_time: 0.0447 memory: 21627 grad_norm: 1.1188 loss: 0.9736 loss_heatmap: 0.4425 layer_-1_loss_cls: 0.0714 layer_-1_loss_bbox: 0.4597 matched_ious: 0.5929 2023/05/24 06:09:09 - mmengine - INFO - Epoch(train) [4][2200/3862] lr: 7.0756e-05 eta: 3:30:29 time: 1.3347 data_time: 0.0422 memory: 21683 grad_norm: 0.9949 loss: 0.9440 loss_heatmap: 0.4338 layer_-1_loss_cls: 0.0716 layer_-1_loss_bbox: 0.4386 matched_ious: 0.5923 2023/05/24 06:10:16 - mmengine - INFO - Epoch(train) [4][2250/3862] lr: 7.0109e-05 eta: 3:29:22 time: 1.3437 data_time: 0.0456 memory: 22089 grad_norm: 1.1849 loss: 0.9781 loss_heatmap: 0.4481 layer_-1_loss_cls: 0.0720 layer_-1_loss_bbox: 0.4580 matched_ious: 0.5768 2023/05/24 06:11:23 - mmengine - INFO - Epoch(train) [4][2300/3862] lr: 6.9464e-05 eta: 3:28:14 time: 1.3362 data_time: 0.0435 memory: 21805 grad_norm: 1.0133 loss: 0.9582 loss_heatmap: 0.4338 layer_-1_loss_cls: 0.0702 layer_-1_loss_bbox: 0.4542 matched_ious: 0.5903 2023/05/24 06:12:30 - mmengine - INFO - Epoch(train) [4][2350/3862] lr: 6.8820e-05 eta: 3:27:07 time: 1.3469 data_time: 0.0441 memory: 22289 grad_norm: 0.9539 loss: 0.9621 loss_heatmap: 0.4392 layer_-1_loss_cls: 0.0718 layer_-1_loss_bbox: 0.4511 matched_ious: 0.5763 2023/05/24 06:13:37 - mmengine - INFO - Epoch(train) [4][2400/3862] lr: 6.8177e-05 eta: 3:26:00 time: 1.3351 data_time: 0.0429 memory: 21838 grad_norm: 1.0779 loss: 0.9638 loss_heatmap: 0.4416 layer_-1_loss_cls: 0.0710 layer_-1_loss_bbox: 0.4512 matched_ious: 0.6017 2023/05/24 06:13:56 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 06:14:45 - mmengine - INFO - Epoch(train) [4][2450/3862] lr: 6.7536e-05 eta: 3:24:53 time: 1.3624 data_time: 0.0424 memory: 21940 grad_norm: 0.9808 loss: 0.9611 loss_heatmap: 0.4360 layer_-1_loss_cls: 0.0714 layer_-1_loss_bbox: 0.4537 matched_ious: 0.5825 2023/05/24 06:15:52 - mmengine - INFO - Epoch(train) [4][2500/3862] lr: 6.6897e-05 eta: 3:23:46 time: 1.3420 data_time: 0.0425 memory: 21759 grad_norm: 0.9564 loss: 0.9685 loss_heatmap: 0.4421 layer_-1_loss_cls: 0.0717 layer_-1_loss_bbox: 0.4546 matched_ious: 0.5992 2023/05/24 06:16:59 - mmengine - INFO - Epoch(train) [4][2550/3862] lr: 6.6259e-05 eta: 3:22:38 time: 1.3387 data_time: 0.0455 memory: 21985 grad_norm: 1.0136 loss: 0.9700 loss_heatmap: 0.4396 layer_-1_loss_cls: 0.0712 layer_-1_loss_bbox: 0.4592 matched_ious: 0.5652 2023/05/24 06:18:06 - mmengine - INFO - Epoch(train) [4][2600/3862] lr: 6.5623e-05 eta: 3:21:31 time: 1.3425 data_time: 0.0414 memory: 22036 grad_norm: 1.1172 loss: 0.9535 loss_heatmap: 0.4330 layer_-1_loss_cls: 0.0707 layer_-1_loss_bbox: 0.4498 matched_ious: 0.6071 2023/05/24 06:19:14 - mmengine - INFO - Epoch(train) [4][2650/3862] lr: 6.4988e-05 eta: 3:20:24 time: 1.3547 data_time: 0.0447 memory: 21946 grad_norm: 1.0949 loss: 0.9623 loss_heatmap: 0.4359 layer_-1_loss_cls: 0.0719 layer_-1_loss_bbox: 0.4545 matched_ious: 0.6077 2023/05/24 06:20:21 - mmengine - INFO - Epoch(train) [4][2700/3862] lr: 6.4355e-05 eta: 3:19:16 time: 1.3391 data_time: 0.0420 memory: 21940 grad_norm: 1.0448 loss: 0.9738 loss_heatmap: 0.4460 layer_-1_loss_cls: 0.0724 layer_-1_loss_bbox: 0.4554 matched_ious: 0.5967 2023/05/24 06:21:28 - mmengine - INFO - Epoch(train) [4][2750/3862] lr: 6.3723e-05 eta: 3:18:09 time: 1.3403 data_time: 0.0435 memory: 21853 grad_norm: 1.0421 loss: 0.9531 loss_heatmap: 0.4373 layer_-1_loss_cls: 0.0717 layer_-1_loss_bbox: 0.4441 matched_ious: 0.6102 2023/05/24 06:22:35 - mmengine - INFO - Epoch(train) [4][2800/3862] lr: 6.3093e-05 eta: 3:17:01 time: 1.3416 data_time: 0.0438 memory: 21796 grad_norm: 1.0651 loss: 0.9693 loss_heatmap: 0.4377 layer_-1_loss_cls: 0.0705 layer_-1_loss_bbox: 0.4611 matched_ious: 0.5684 2023/05/24 06:23:43 - mmengine - INFO - Epoch(train) [4][2850/3862] lr: 6.2465e-05 eta: 3:15:54 time: 1.3526 data_time: 0.0427 memory: 21844 grad_norm: 1.1002 loss: 0.9507 loss_heatmap: 0.4350 layer_-1_loss_cls: 0.0703 layer_-1_loss_bbox: 0.4455 matched_ious: 0.5692 2023/05/24 06:24:51 - mmengine - INFO - Epoch(train) [4][2900/3862] lr: 6.1839e-05 eta: 3:14:48 time: 1.3668 data_time: 0.0451 memory: 21618 grad_norm: 0.9817 loss: 0.9588 loss_heatmap: 0.4363 layer_-1_loss_cls: 0.0696 layer_-1_loss_bbox: 0.4530 matched_ious: 0.5740 2023/05/24 06:25:58 - mmengine - INFO - Epoch(train) [4][2950/3862] lr: 6.1214e-05 eta: 3:13:40 time: 1.3433 data_time: 0.0444 memory: 21960 grad_norm: 1.0068 loss: 0.9564 loss_heatmap: 0.4335 layer_-1_loss_cls: 0.0698 layer_-1_loss_bbox: 0.4531 matched_ious: 0.5795 2023/05/24 06:27:05 - mmengine - INFO - Epoch(train) [4][3000/3862] lr: 6.0591e-05 eta: 3:12:33 time: 1.3378 data_time: 0.0422 memory: 21998 grad_norm: 1.0476 loss: 0.9555 loss_heatmap: 0.4364 layer_-1_loss_cls: 0.0711 layer_-1_loss_bbox: 0.4479 matched_ious: 0.6091 2023/05/24 06:28:12 - mmengine - INFO - Epoch(train) [4][3050/3862] lr: 5.9970e-05 eta: 3:11:25 time: 1.3434 data_time: 0.0435 memory: 21802 grad_norm: 1.0717 loss: 0.9522 loss_heatmap: 0.4362 layer_-1_loss_cls: 0.0711 layer_-1_loss_bbox: 0.4450 matched_ious: 0.5767 2023/05/24 06:29:20 - mmengine - INFO - Epoch(train) [4][3100/3862] lr: 5.9351e-05 eta: 3:10:18 time: 1.3485 data_time: 0.0413 memory: 22122 grad_norm: 1.0422 loss: 0.9799 loss_heatmap: 0.4476 layer_-1_loss_cls: 0.0723 layer_-1_loss_bbox: 0.4600 matched_ious: 0.6067 2023/05/24 06:30:27 - mmengine - INFO - Epoch(train) [4][3150/3862] lr: 5.8733e-05 eta: 3:09:11 time: 1.3420 data_time: 0.0446 memory: 21733 grad_norm: 1.1062 loss: 0.9587 loss_heatmap: 0.4369 layer_-1_loss_cls: 0.0703 layer_-1_loss_bbox: 0.4514 matched_ious: 0.5949 2023/05/24 06:31:34 - mmengine - INFO - Epoch(train) [4][3200/3862] lr: 5.8118e-05 eta: 3:08:03 time: 1.3374 data_time: 0.0428 memory: 21776 grad_norm: 1.1994 loss: 0.9727 loss_heatmap: 0.4358 layer_-1_loss_cls: 0.0701 layer_-1_loss_bbox: 0.4668 matched_ious: 0.5866 2023/05/24 06:32:41 - mmengine - INFO - Epoch(train) [4][3250/3862] lr: 5.7504e-05 eta: 3:06:56 time: 1.3508 data_time: 0.0455 memory: 22130 grad_norm: 0.9803 loss: 0.9595 loss_heatmap: 0.4369 layer_-1_loss_cls: 0.0701 layer_-1_loss_bbox: 0.4525 matched_ious: 0.5940 2023/05/24 06:33:48 - mmengine - INFO - Epoch(train) [4][3300/3862] lr: 5.6893e-05 eta: 3:05:49 time: 1.3337 data_time: 0.0430 memory: 21972 grad_norm: 1.0372 loss: 0.9734 loss_heatmap: 0.4469 layer_-1_loss_cls: 0.0713 layer_-1_loss_bbox: 0.4553 matched_ious: 0.5759 2023/05/24 06:34:56 - mmengine - INFO - Epoch(train) [4][3350/3862] lr: 5.6283e-05 eta: 3:04:42 time: 1.3568 data_time: 0.0479 memory: 22005 grad_norm: 0.9595 loss: 0.9606 loss_heatmap: 0.4379 layer_-1_loss_cls: 0.0706 layer_-1_loss_bbox: 0.4520 matched_ious: 0.5752 2023/05/24 06:36:03 - mmengine - INFO - Epoch(train) [4][3400/3862] lr: 5.5676e-05 eta: 3:03:34 time: 1.3465 data_time: 0.0426 memory: 21887 grad_norm: 1.1101 loss: 0.9578 loss_heatmap: 0.4365 layer_-1_loss_cls: 0.0708 layer_-1_loss_bbox: 0.4505 matched_ious: 0.6058 2023/05/24 06:36:22 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 06:37:10 - mmengine - INFO - Epoch(train) [4][3450/3862] lr: 5.5070e-05 eta: 3:02:27 time: 1.3430 data_time: 0.0450 memory: 21738 grad_norm: 1.1242 loss: 0.9491 loss_heatmap: 0.4315 layer_-1_loss_cls: 0.0698 layer_-1_loss_bbox: 0.4478 matched_ious: 0.5734 2023/05/24 06:38:18 - mmengine - INFO - Epoch(train) [4][3500/3862] lr: 5.4467e-05 eta: 3:01:20 time: 1.3481 data_time: 0.0449 memory: 22211 grad_norm: 1.0690 loss: 0.9814 loss_heatmap: 0.4442 layer_-1_loss_cls: 0.0707 layer_-1_loss_bbox: 0.4665 matched_ious: 0.5604 2023/05/24 06:39:25 - mmengine - INFO - Epoch(train) [4][3550/3862] lr: 5.3865e-05 eta: 3:00:13 time: 1.3479 data_time: 0.0447 memory: 21972 grad_norm: 0.9951 loss: 0.9532 loss_heatmap: 0.4338 layer_-1_loss_cls: 0.0701 layer_-1_loss_bbox: 0.4493 matched_ious: 0.6021 2023/05/24 06:40:32 - mmengine - INFO - Epoch(train) [4][3600/3862] lr: 5.3266e-05 eta: 2:59:05 time: 1.3371 data_time: 0.0437 memory: 21809 grad_norm: 1.0362 loss: 0.9512 loss_heatmap: 0.4349 layer_-1_loss_cls: 0.0704 layer_-1_loss_bbox: 0.4459 matched_ious: 0.5920 2023/05/24 06:41:39 - mmengine - INFO - Epoch(train) [4][3650/3862] lr: 5.2669e-05 eta: 2:57:58 time: 1.3420 data_time: 0.0452 memory: 22026 grad_norm: 1.0794 loss: 0.9610 loss_heatmap: 0.4398 layer_-1_loss_cls: 0.0709 layer_-1_loss_bbox: 0.4503 matched_ious: 0.5760 2023/05/24 06:42:46 - mmengine - INFO - Epoch(train) [4][3700/3862] lr: 5.2074e-05 eta: 2:56:50 time: 1.3396 data_time: 0.0441 memory: 22107 grad_norm: 1.1179 loss: 0.9470 loss_heatmap: 0.4346 layer_-1_loss_cls: 0.0700 layer_-1_loss_bbox: 0.4424 matched_ious: 0.6105 2023/05/24 06:43:54 - mmengine - INFO - Epoch(train) [4][3750/3862] lr: 5.1481e-05 eta: 2:55:43 time: 1.3585 data_time: 0.0443 memory: 21896 grad_norm: 1.0166 loss: 0.9620 loss_heatmap: 0.4358 layer_-1_loss_cls: 0.0691 layer_-1_loss_bbox: 0.4571 matched_ious: 0.5839 2023/05/24 06:45:01 - mmengine - INFO - Epoch(train) [4][3800/3862] lr: 5.0891e-05 eta: 2:54:36 time: 1.3350 data_time: 0.0429 memory: 21934 grad_norm: 1.0572 loss: 0.9468 loss_heatmap: 0.4325 layer_-1_loss_cls: 0.0693 layer_-1_loss_bbox: 0.4450 matched_ious: 0.5871 2023/05/24 06:46:07 - mmengine - INFO - Epoch(train) [4][3850/3862] lr: 5.0303e-05 eta: 2:53:28 time: 1.3378 data_time: 0.0446 memory: 22050 grad_norm: 1.0481 loss: 0.9421 loss_heatmap: 0.4302 layer_-1_loss_cls: 0.0699 layer_-1_loss_bbox: 0.4419 matched_ious: 0.6016 2023/05/24 06:46:23 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 06:46:23 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/05/24 06:46:39 - mmengine - INFO - Epoch(val) [4][ 50/753] eta: 0:02:44 time: 0.2341 data_time: 0.0133 memory: 21751 2023/05/24 06:46:50 - mmengine - INFO - Epoch(val) [4][100/753] eta: 0:02:28 time: 0.2220 data_time: 0.0076 memory: 2850 2023/05/24 06:47:01 - mmengine - INFO - Epoch(val) [4][150/753] eta: 0:02:15 time: 0.2172 data_time: 0.0066 memory: 2848 2023/05/24 06:47:13 - mmengine - INFO - Epoch(val) [4][200/753] eta: 0:02:04 time: 0.2282 data_time: 0.0073 memory: 2852 2023/05/24 06:47:24 - mmengine - INFO - Epoch(val) [4][250/753] eta: 0:01:53 time: 0.2307 data_time: 0.0082 memory: 2848 2023/05/24 06:47:35 - mmengine - INFO - Epoch(val) [4][300/753] eta: 0:01:42 time: 0.2239 data_time: 0.0074 memory: 2848 2023/05/24 06:47:46 - mmengine - INFO - Epoch(val) [4][350/753] eta: 0:01:30 time: 0.2241 data_time: 0.0072 memory: 2851 2023/05/24 06:47:57 - mmengine - INFO - Epoch(val) [4][400/753] eta: 0:01:19 time: 0.2149 data_time: 0.0073 memory: 2851 2023/05/24 06:48:09 - mmengine - INFO - Epoch(val) [4][450/753] eta: 0:01:08 time: 0.2264 data_time: 0.0070 memory: 2849 2023/05/24 06:48:20 - mmengine - INFO - Epoch(val) [4][500/753] eta: 0:00:56 time: 0.2268 data_time: 0.0069 memory: 2850 2023/05/24 06:48:31 - mmengine - INFO - Epoch(val) [4][550/753] eta: 0:00:45 time: 0.2247 data_time: 0.0071 memory: 2849 2023/05/24 06:48:43 - mmengine - INFO - Epoch(val) [4][600/753] eta: 0:00:34 time: 0.2274 data_time: 0.0063 memory: 2852 2023/05/24 06:48:56 - mmengine - INFO - Epoch(val) [4][650/753] eta: 0:00:23 time: 0.2765 data_time: 0.0080 memory: 2849 2023/05/24 06:49:08 - mmengine - INFO - Epoch(val) [4][700/753] eta: 0:00:12 time: 0.2306 data_time: 0.0065 memory: 2852 2023/05/24 06:49:19 - mmengine - INFO - Epoch(val) [4][750/753] eta: 0:00:00 time: 0.2242 data_time: 0.0063 memory: 2852 2023/05/24 07:00:37 - mmengine - INFO - Epoch(val) [4][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.8136 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.9018 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.9268 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.9370 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1732 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1500 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.0670 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.2754 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1876 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2818 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2531 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.3046 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.2714 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1860 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.4306 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.6290 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.7206 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.7587 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3330 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1835 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.0929 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.2519 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2240 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0490 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.2181 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.3909 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.5177 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6711 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4186 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.8550 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1303 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3117 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4925 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.7762 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.8903 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.9075 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3294 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1854 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.0548 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.4617 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2412 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.1529 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.4419 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.6197 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.7102 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5197 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2084 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.6303 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.1787 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1682 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.6221 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.7172 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7542 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7668 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.1836 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2786 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0600 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.6537 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.7777 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.7937 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.8043 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1870 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2368 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.2682 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.4604 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2449 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.5866 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.6075 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.6173 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.6298 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1547 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2575 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.3293 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2031 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0116 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8641 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8766 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8864 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8968 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1365 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2881 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.3839 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2100 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.0988 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.7713 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.7828 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.8010 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.8253 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1300 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3235 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.7118 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.6830 data_time: 0.0059 time: 0.2211 2023/05/24 07:01:46 - mmengine - INFO - Epoch(train) [5][ 50/3862] lr: 4.9576e-05 eta: 2:52:05 time: 1.3702 data_time: 0.0581 memory: 22009 grad_norm: 1.0032 loss: 0.9559 loss_heatmap: 0.4312 layer_-1_loss_cls: 0.0691 layer_-1_loss_bbox: 0.4555 matched_ious: 0.5934 2023/05/24 07:02:52 - mmengine - INFO - Epoch(train) [5][ 100/3862] lr: 4.8993e-05 eta: 2:50:58 time: 1.3369 data_time: 0.0287 memory: 21843 grad_norm: 1.1426 loss: 0.9507 loss_heatmap: 0.4332 layer_-1_loss_cls: 0.0698 layer_-1_loss_bbox: 0.4476 matched_ious: 0.5810 2023/05/24 07:03:59 - mmengine - INFO - Epoch(train) [5][ 150/3862] lr: 4.8413e-05 eta: 2:49:50 time: 1.3379 data_time: 0.0296 memory: 22070 grad_norm: 1.0800 loss: 0.9320 loss_heatmap: 0.4209 layer_-1_loss_cls: 0.0677 layer_-1_loss_bbox: 0.4434 matched_ious: 0.6041 2023/05/24 07:05:06 - mmengine - INFO - Epoch(train) [5][ 200/3862] lr: 4.7834e-05 eta: 2:48:43 time: 1.3391 data_time: 0.0301 memory: 21897 grad_norm: 1.0621 loss: 0.9450 loss_heatmap: 0.4296 layer_-1_loss_cls: 0.0693 layer_-1_loss_bbox: 0.4461 matched_ious: 0.5911 2023/05/24 07:06:13 - mmengine - INFO - Epoch(train) [5][ 250/3862] lr: 4.7258e-05 eta: 2:47:36 time: 1.3413 data_time: 0.0294 memory: 21758 grad_norm: 1.0663 loss: 0.9388 loss_heatmap: 0.4275 layer_-1_loss_cls: 0.0696 layer_-1_loss_bbox: 0.4418 matched_ious: 0.5860 2023/05/24 07:07:20 - mmengine - INFO - Epoch(train) [5][ 300/3862] lr: 4.6685e-05 eta: 2:46:28 time: 1.3379 data_time: 0.0300 memory: 21952 grad_norm: 1.1015 loss: 0.9480 loss_heatmap: 0.4291 layer_-1_loss_cls: 0.0687 layer_-1_loss_bbox: 0.4502 matched_ious: 0.6018 2023/05/24 07:08:27 - mmengine - INFO - Epoch(train) [5][ 350/3862] lr: 4.6114e-05 eta: 2:45:21 time: 1.3331 data_time: 0.0296 memory: 21880 grad_norm: 1.1092 loss: 0.9513 loss_heatmap: 0.4382 layer_-1_loss_cls: 0.0708 layer_-1_loss_bbox: 0.4424 matched_ious: 0.6067 2023/05/24 07:09:34 - mmengine - INFO - Epoch(train) [5][ 400/3862] lr: 4.5545e-05 eta: 2:44:13 time: 1.3427 data_time: 0.0301 memory: 21977 grad_norm: 1.0406 loss: 0.9496 loss_heatmap: 0.4347 layer_-1_loss_cls: 0.0700 layer_-1_loss_bbox: 0.4449 matched_ious: 0.5851 2023/05/24 07:10:41 - mmengine - INFO - Epoch(train) [5][ 450/3862] lr: 4.4979e-05 eta: 2:43:06 time: 1.3330 data_time: 0.0307 memory: 21823 grad_norm: 1.0180 loss: 0.9351 loss_heatmap: 0.4275 layer_-1_loss_cls: 0.0699 layer_-1_loss_bbox: 0.4377 matched_ious: 0.5897 2023/05/24 07:11:47 - mmengine - INFO - Epoch(train) [5][ 500/3862] lr: 4.4416e-05 eta: 2:41:58 time: 1.3358 data_time: 0.0289 memory: 21745 grad_norm: 1.0861 loss: 0.9415 loss_heatmap: 0.4268 layer_-1_loss_cls: 0.0689 layer_-1_loss_bbox: 0.4459 matched_ious: 0.5697 2023/05/24 07:12:54 - mmengine - INFO - Epoch(train) [5][ 550/3862] lr: 4.3855e-05 eta: 2:40:51 time: 1.3320 data_time: 0.0295 memory: 21828 grad_norm: 0.9702 loss: 0.9546 loss_heatmap: 0.4342 layer_-1_loss_cls: 0.0691 layer_-1_loss_bbox: 0.4513 matched_ious: 0.5886 2023/05/24 07:12:57 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 07:14:02 - mmengine - INFO - Epoch(train) [5][ 600/3862] lr: 4.3296e-05 eta: 2:39:44 time: 1.3537 data_time: 0.0318 memory: 21936 grad_norm: 1.0074 loss: 0.9373 loss_heatmap: 0.4257 layer_-1_loss_cls: 0.0688 layer_-1_loss_bbox: 0.4427 matched_ious: 0.5861 2023/05/24 07:15:09 - mmengine - INFO - Epoch(train) [5][ 650/3862] lr: 4.2741e-05 eta: 2:38:36 time: 1.3368 data_time: 0.0300 memory: 22148 grad_norm: 0.9867 loss: 0.9581 loss_heatmap: 0.4310 layer_-1_loss_cls: 0.0698 layer_-1_loss_bbox: 0.4573 matched_ious: 0.5890 2023/05/24 07:16:15 - mmengine - INFO - Epoch(train) [5][ 700/3862] lr: 4.2187e-05 eta: 2:37:29 time: 1.3381 data_time: 0.0302 memory: 22028 grad_norm: 1.0182 loss: 0.9652 loss_heatmap: 0.4397 layer_-1_loss_cls: 0.0700 layer_-1_loss_bbox: 0.4554 matched_ious: 0.5844 2023/05/24 07:17:22 - mmengine - INFO - Epoch(train) [5][ 750/3862] lr: 4.1637e-05 eta: 2:36:21 time: 1.3381 data_time: 0.0310 memory: 22148 grad_norm: 1.1014 loss: 0.9497 loss_heatmap: 0.4283 layer_-1_loss_cls: 0.0703 layer_-1_loss_bbox: 0.4512 matched_ious: 0.6036 2023/05/24 07:18:29 - mmengine - INFO - Epoch(train) [5][ 800/3862] lr: 4.1089e-05 eta: 2:35:14 time: 1.3408 data_time: 0.0299 memory: 22003 grad_norm: 1.1122 loss: 0.9434 loss_heatmap: 0.4253 layer_-1_loss_cls: 0.0686 layer_-1_loss_bbox: 0.4496 matched_ious: 0.6087 2023/05/24 07:19:37 - mmengine - INFO - Epoch(train) [5][ 850/3862] lr: 4.0544e-05 eta: 2:34:07 time: 1.3436 data_time: 0.0301 memory: 21655 grad_norm: 1.0428 loss: 0.9454 loss_heatmap: 0.4295 layer_-1_loss_cls: 0.0691 layer_-1_loss_bbox: 0.4468 matched_ious: 0.6031 2023/05/24 07:20:43 - mmengine - INFO - Epoch(train) [5][ 900/3862] lr: 4.0002e-05 eta: 2:32:59 time: 1.3382 data_time: 0.0290 memory: 21774 grad_norm: 1.0538 loss: 0.9450 loss_heatmap: 0.4250 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4521 matched_ious: 0.6121 2023/05/24 07:21:50 - mmengine - INFO - Epoch(train) [5][ 950/3862] lr: 3.9462e-05 eta: 2:31:52 time: 1.3389 data_time: 0.0300 memory: 21926 grad_norm: 1.0272 loss: 0.9348 loss_heatmap: 0.4248 layer_-1_loss_cls: 0.0686 layer_-1_loss_bbox: 0.4415 matched_ious: 0.5772 2023/05/24 07:22:57 - mmengine - INFO - Epoch(train) [5][1000/3862] lr: 3.8925e-05 eta: 2:30:44 time: 1.3368 data_time: 0.0297 memory: 21800 grad_norm: 1.0911 loss: 0.9515 loss_heatmap: 0.4332 layer_-1_loss_cls: 0.0698 layer_-1_loss_bbox: 0.4485 matched_ious: 0.6024 2023/05/24 07:24:04 - mmengine - INFO - Epoch(train) [5][1050/3862] lr: 3.8391e-05 eta: 2:29:37 time: 1.3438 data_time: 0.0300 memory: 22050 grad_norm: 1.0110 loss: 0.9522 loss_heatmap: 0.4299 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4544 matched_ious: 0.5925 2023/05/24 07:25:11 - mmengine - INFO - Epoch(train) [5][1100/3862] lr: 3.7860e-05 eta: 2:28:30 time: 1.3296 data_time: 0.0294 memory: 21842 grad_norm: 1.0360 loss: 0.9397 loss_heatmap: 0.4279 layer_-1_loss_cls: 0.0683 layer_-1_loss_bbox: 0.4434 matched_ious: 0.5929 2023/05/24 07:26:18 - mmengine - INFO - Epoch(train) [5][1150/3862] lr: 3.7332e-05 eta: 2:27:22 time: 1.3372 data_time: 0.0296 memory: 22208 grad_norm: 1.0655 loss: 0.9302 loss_heatmap: 0.4260 layer_-1_loss_cls: 0.0684 layer_-1_loss_bbox: 0.4357 matched_ious: 0.5799 2023/05/24 07:27:25 - mmengine - INFO - Epoch(train) [5][1200/3862] lr: 3.6807e-05 eta: 2:26:15 time: 1.3418 data_time: 0.0293 memory: 21885 grad_norm: 1.0755 loss: 0.9540 loss_heatmap: 0.4288 layer_-1_loss_cls: 0.0689 layer_-1_loss_bbox: 0.4564 matched_ious: 0.6182 2023/05/24 07:28:32 - mmengine - INFO - Epoch(train) [5][1250/3862] lr: 3.6284e-05 eta: 2:25:08 time: 1.3424 data_time: 0.0295 memory: 21725 grad_norm: 1.0881 loss: 0.9332 loss_heatmap: 0.4244 layer_-1_loss_cls: 0.0681 layer_-1_loss_bbox: 0.4408 matched_ious: 0.6054 2023/05/24 07:29:40 - mmengine - INFO - Epoch(train) [5][1300/3862] lr: 3.5765e-05 eta: 2:24:00 time: 1.3526 data_time: 0.0301 memory: 22024 grad_norm: 0.9562 loss: 0.9444 loss_heatmap: 0.4240 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4527 matched_ious: 0.5884 2023/05/24 07:30:47 - mmengine - INFO - Epoch(train) [5][1350/3862] lr: 3.5248e-05 eta: 2:22:53 time: 1.3436 data_time: 0.0296 memory: 21713 grad_norm: 0.9774 loss: 0.9376 loss_heatmap: 0.4217 layer_-1_loss_cls: 0.0680 layer_-1_loss_bbox: 0.4479 matched_ious: 0.6018 2023/05/24 07:31:53 - mmengine - INFO - Epoch(train) [5][1400/3862] lr: 3.4734e-05 eta: 2:21:46 time: 1.3321 data_time: 0.0291 memory: 22102 grad_norm: 1.1463 loss: 0.9333 loss_heatmap: 0.4292 layer_-1_loss_cls: 0.0688 layer_-1_loss_bbox: 0.4353 matched_ious: 0.5799 2023/05/24 07:33:01 - mmengine - INFO - Epoch(train) [5][1450/3862] lr: 3.4224e-05 eta: 2:20:38 time: 1.3459 data_time: 0.0308 memory: 21731 grad_norm: 1.0960 loss: 0.9391 loss_heatmap: 0.4290 layer_-1_loss_cls: 0.0686 layer_-1_loss_bbox: 0.4415 matched_ious: 0.5739 2023/05/24 07:34:09 - mmengine - INFO - Epoch(train) [5][1500/3862] lr: 3.3716e-05 eta: 2:19:31 time: 1.3589 data_time: 0.0304 memory: 21858 grad_norm: 1.1123 loss: 0.9312 loss_heatmap: 0.4274 layer_-1_loss_cls: 0.0693 layer_-1_loss_bbox: 0.4345 matched_ious: 0.5704 2023/05/24 07:35:16 - mmengine - INFO - Epoch(train) [5][1550/3862] lr: 3.3212e-05 eta: 2:18:24 time: 1.3435 data_time: 0.0300 memory: 21785 grad_norm: 0.9956 loss: 0.8961 loss_heatmap: 0.4118 layer_-1_loss_cls: 0.0671 layer_-1_loss_bbox: 0.4173 matched_ious: 0.6004 2023/05/24 07:35:18 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 07:36:23 - mmengine - INFO - Epoch(train) [5][1600/3862] lr: 3.2710e-05 eta: 2:17:17 time: 1.3415 data_time: 0.0292 memory: 21802 grad_norm: 1.1752 loss: 0.9312 loss_heatmap: 0.4297 layer_-1_loss_cls: 0.0692 layer_-1_loss_bbox: 0.4322 matched_ious: 0.6094 2023/05/24 07:37:30 - mmengine - INFO - Epoch(train) [5][1650/3862] lr: 3.2212e-05 eta: 2:16:10 time: 1.3416 data_time: 0.0291 memory: 21909 grad_norm: 1.0352 loss: 0.9399 loss_heatmap: 0.4260 layer_-1_loss_cls: 0.0681 layer_-1_loss_bbox: 0.4458 matched_ious: 0.5872 2023/05/24 07:38:37 - mmengine - INFO - Epoch(train) [5][1700/3862] lr: 3.1717e-05 eta: 2:15:02 time: 1.3400 data_time: 0.0295 memory: 21663 grad_norm: 1.0350 loss: 0.9251 loss_heatmap: 0.4191 layer_-1_loss_cls: 0.0684 layer_-1_loss_bbox: 0.4376 matched_ious: 0.5669 2023/05/24 07:39:45 - mmengine - INFO - Epoch(train) [5][1750/3862] lr: 3.1224e-05 eta: 2:13:55 time: 1.3604 data_time: 0.0306 memory: 21849 grad_norm: 0.9790 loss: 0.9331 loss_heatmap: 0.4251 layer_-1_loss_cls: 0.0688 layer_-1_loss_bbox: 0.4392 matched_ious: 0.5994 2023/05/24 07:40:52 - mmengine - INFO - Epoch(train) [5][1800/3862] lr: 3.0735e-05 eta: 2:12:48 time: 1.3397 data_time: 0.0301 memory: 21852 grad_norm: 1.1000 loss: 0.9266 loss_heatmap: 0.4180 layer_-1_loss_cls: 0.0674 layer_-1_loss_bbox: 0.4412 matched_ious: 0.5886 2023/05/24 07:41:59 - mmengine - INFO - Epoch(train) [5][1850/3862] lr: 3.0250e-05 eta: 2:11:40 time: 1.3318 data_time: 0.0295 memory: 22018 grad_norm: 1.0270 loss: 0.9267 loss_heatmap: 0.4222 layer_-1_loss_cls: 0.0681 layer_-1_loss_bbox: 0.4364 matched_ious: 0.5955 2023/05/24 07:43:06 - mmengine - INFO - Epoch(train) [5][1900/3862] lr: 2.9767e-05 eta: 2:10:33 time: 1.3382 data_time: 0.0285 memory: 21749 grad_norm: 1.0480 loss: 0.9319 loss_heatmap: 0.4270 layer_-1_loss_cls: 0.0687 layer_-1_loss_bbox: 0.4361 matched_ious: 0.5942 2023/05/24 07:44:14 - mmengine - INFO - Epoch(train) [5][1950/3862] lr: 2.9288e-05 eta: 2:09:26 time: 1.3645 data_time: 0.0292 memory: 21900 grad_norm: 0.9945 loss: 0.9411 loss_heatmap: 0.4236 layer_-1_loss_cls: 0.0681 layer_-1_loss_bbox: 0.4494 matched_ious: 0.5938 2023/05/24 07:45:21 - mmengine - INFO - Epoch(train) [5][2000/3862] lr: 2.8812e-05 eta: 2:08:19 time: 1.3442 data_time: 0.0297 memory: 21634 grad_norm: 1.0047 loss: 0.9325 loss_heatmap: 0.4204 layer_-1_loss_cls: 0.0667 layer_-1_loss_bbox: 0.4454 matched_ious: 0.6097 2023/05/24 07:46:28 - mmengine - INFO - Epoch(train) [5][2050/3862] lr: 2.8339e-05 eta: 2:07:11 time: 1.3342 data_time: 0.0297 memory: 21926 grad_norm: 1.0747 loss: 0.9314 loss_heatmap: 0.4245 layer_-1_loss_cls: 0.0689 layer_-1_loss_bbox: 0.4380 matched_ious: 0.5912 2023/05/24 07:47:34 - mmengine - INFO - Epoch(train) [5][2100/3862] lr: 2.7870e-05 eta: 2:06:04 time: 1.3345 data_time: 0.0289 memory: 22082 grad_norm: 1.0409 loss: 0.9386 loss_heatmap: 0.4279 layer_-1_loss_cls: 0.0694 layer_-1_loss_bbox: 0.4414 matched_ious: 0.5880 2023/05/24 07:48:42 - mmengine - INFO - Epoch(train) [5][2150/3862] lr: 2.7403e-05 eta: 2:04:57 time: 1.3515 data_time: 0.0297 memory: 22090 grad_norm: 1.1074 loss: 0.9397 loss_heatmap: 0.4250 layer_-1_loss_cls: 0.0684 layer_-1_loss_bbox: 0.4464 matched_ious: 0.5930 2023/05/24 07:49:49 - mmengine - INFO - Epoch(train) [5][2200/3862] lr: 2.6941e-05 eta: 2:03:49 time: 1.3382 data_time: 0.0311 memory: 21831 grad_norm: 1.0336 loss: 0.9443 loss_heatmap: 0.4262 layer_-1_loss_cls: 0.0693 layer_-1_loss_bbox: 0.4489 matched_ious: 0.5682 2023/05/24 07:50:56 - mmengine - INFO - Epoch(train) [5][2250/3862] lr: 2.6481e-05 eta: 2:02:42 time: 1.3405 data_time: 0.0317 memory: 21890 grad_norm: 1.0205 loss: 0.9200 loss_heatmap: 0.4169 layer_-1_loss_cls: 0.0677 layer_-1_loss_bbox: 0.4354 matched_ious: 0.6178 2023/05/24 07:52:03 - mmengine - INFO - Epoch(train) [5][2300/3862] lr: 2.6025e-05 eta: 2:01:35 time: 1.3371 data_time: 0.0298 memory: 22111 grad_norm: 1.1118 loss: 0.9319 loss_heatmap: 0.4197 layer_-1_loss_cls: 0.0680 layer_-1_loss_bbox: 0.4443 matched_ious: 0.5859 2023/05/24 07:53:10 - mmengine - INFO - Epoch(train) [5][2350/3862] lr: 2.5572e-05 eta: 2:00:27 time: 1.3425 data_time: 0.0302 memory: 22051 grad_norm: 1.0087 loss: 0.9175 loss_heatmap: 0.4157 layer_-1_loss_cls: 0.0671 layer_-1_loss_bbox: 0.4347 matched_ious: 0.6000 2023/05/24 07:54:18 - mmengine - INFO - Epoch(train) [5][2400/3862] lr: 2.5123e-05 eta: 1:59:20 time: 1.3603 data_time: 0.0303 memory: 22127 grad_norm: 1.0189 loss: 0.9265 loss_heatmap: 0.4263 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4324 matched_ious: 0.5927 2023/05/24 07:55:25 - mmengine - INFO - Epoch(train) [5][2450/3862] lr: 2.4677e-05 eta: 1:58:13 time: 1.3380 data_time: 0.0298 memory: 21940 grad_norm: 1.2557 loss: 0.9487 loss_heatmap: 0.4277 layer_-1_loss_cls: 0.0688 layer_-1_loss_bbox: 0.4522 matched_ious: 0.5670 2023/05/24 07:56:32 - mmengine - INFO - Epoch(train) [5][2500/3862] lr: 2.4235e-05 eta: 1:57:06 time: 1.3356 data_time: 0.0302 memory: 22015 grad_norm: 0.9753 loss: 0.9381 loss_heatmap: 0.4208 layer_-1_loss_cls: 0.0684 layer_-1_loss_bbox: 0.4488 matched_ious: 0.5815 2023/05/24 07:57:38 - mmengine - INFO - Epoch(train) [5][2550/3862] lr: 2.3796e-05 eta: 1:55:58 time: 1.3376 data_time: 0.0296 memory: 22212 grad_norm: 1.0703 loss: 0.9167 loss_heatmap: 0.4183 layer_-1_loss_cls: 0.0682 layer_-1_loss_bbox: 0.4302 matched_ious: 0.5872 2023/05/24 07:57:41 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 07:58:46 - mmengine - INFO - Epoch(train) [5][2600/3862] lr: 2.3361e-05 eta: 1:54:51 time: 1.3404 data_time: 0.0301 memory: 21826 grad_norm: 1.0539 loss: 0.9362 loss_heatmap: 0.4211 layer_-1_loss_cls: 0.0679 layer_-1_loss_bbox: 0.4472 matched_ious: 0.5964 2023/05/24 07:59:53 - mmengine - INFO - Epoch(train) [5][2650/3862] lr: 2.2929e-05 eta: 1:53:44 time: 1.3489 data_time: 0.0308 memory: 22088 grad_norm: 1.0965 loss: 0.9357 loss_heatmap: 0.4241 layer_-1_loss_cls: 0.0686 layer_-1_loss_bbox: 0.4430 matched_ious: 0.5813 2023/05/24 08:01:00 - mmengine - INFO - Epoch(train) [5][2700/3862] lr: 2.2501e-05 eta: 1:52:37 time: 1.3451 data_time: 0.0283 memory: 21737 grad_norm: 1.1729 loss: 0.9316 loss_heatmap: 0.4212 layer_-1_loss_cls: 0.0679 layer_-1_loss_bbox: 0.4426 matched_ious: 0.5869 2023/05/24 08:02:07 - mmengine - INFO - Epoch(train) [5][2750/3862] lr: 2.2076e-05 eta: 1:51:29 time: 1.3302 data_time: 0.0307 memory: 21671 grad_norm: 1.0801 loss: 0.9261 loss_heatmap: 0.4239 layer_-1_loss_cls: 0.0699 layer_-1_loss_bbox: 0.4323 matched_ious: 0.5854 2023/05/24 08:03:14 - mmengine - INFO - Epoch(train) [5][2800/3862] lr: 2.1655e-05 eta: 1:50:22 time: 1.3365 data_time: 0.0289 memory: 21764 grad_norm: 1.0318 loss: 0.9263 loss_heatmap: 0.4163 layer_-1_loss_cls: 0.0674 layer_-1_loss_bbox: 0.4426 matched_ious: 0.6061 2023/05/24 08:04:22 - mmengine - INFO - Epoch(train) [5][2850/3862] lr: 2.1237e-05 eta: 1:49:15 time: 1.3681 data_time: 0.0295 memory: 21738 grad_norm: 1.1311 loss: 0.9214 loss_heatmap: 0.4161 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4375 matched_ious: 0.5917 2023/05/24 08:05:29 - mmengine - INFO - Epoch(train) [5][2900/3862] lr: 2.0823e-05 eta: 1:48:08 time: 1.3403 data_time: 0.0292 memory: 21882 grad_norm: 1.0637 loss: 0.9196 loss_heatmap: 0.4182 layer_-1_loss_cls: 0.0673 layer_-1_loss_bbox: 0.4340 matched_ious: 0.5812 2023/05/24 08:06:36 - mmengine - INFO - Epoch(train) [5][2950/3862] lr: 2.0413e-05 eta: 1:47:00 time: 1.3461 data_time: 0.0299 memory: 22020 grad_norm: 1.0213 loss: 0.9200 loss_heatmap: 0.4187 layer_-1_loss_cls: 0.0674 layer_-1_loss_bbox: 0.4339 matched_ious: 0.5776 2023/05/24 08:07:43 - mmengine - INFO - Epoch(train) [5][3000/3862] lr: 2.0007e-05 eta: 1:45:53 time: 1.3422 data_time: 0.0298 memory: 21814 grad_norm: 1.0392 loss: 0.9288 loss_heatmap: 0.4283 layer_-1_loss_cls: 0.0696 layer_-1_loss_bbox: 0.4309 matched_ious: 0.5874 2023/05/24 08:08:50 - mmengine - INFO - Epoch(train) [5][3050/3862] lr: 1.9604e-05 eta: 1:44:46 time: 1.3342 data_time: 0.0293 memory: 22180 grad_norm: 0.9956 loss: 0.9145 loss_heatmap: 0.4163 layer_-1_loss_cls: 0.0680 layer_-1_loss_bbox: 0.4303 matched_ious: 0.5923 2023/05/24 08:09:57 - mmengine - INFO - Epoch(train) [5][3100/3862] lr: 1.9204e-05 eta: 1:43:38 time: 1.3387 data_time: 0.0300 memory: 21868 grad_norm: 1.0249 loss: 0.9269 loss_heatmap: 0.4179 layer_-1_loss_cls: 0.0677 layer_-1_loss_bbox: 0.4412 matched_ious: 0.6171 2023/05/24 08:11:04 - mmengine - INFO - Epoch(train) [5][3150/3862] lr: 1.8809e-05 eta: 1:42:31 time: 1.3462 data_time: 0.0285 memory: 21894 grad_norm: 1.1397 loss: 0.9145 loss_heatmap: 0.4184 layer_-1_loss_cls: 0.0677 layer_-1_loss_bbox: 0.4284 matched_ious: 0.5817 2023/05/24 08:12:11 - mmengine - INFO - Epoch(train) [5][3200/3862] lr: 1.8417e-05 eta: 1:41:24 time: 1.3394 data_time: 0.0282 memory: 21882 grad_norm: 1.1146 loss: 0.9323 loss_heatmap: 0.4186 layer_-1_loss_cls: 0.0680 layer_-1_loss_bbox: 0.4457 matched_ious: 0.5836 2023/05/24 08:13:18 - mmengine - INFO - Epoch(train) [5][3250/3862] lr: 1.8029e-05 eta: 1:40:16 time: 1.3393 data_time: 0.0294 memory: 21836 grad_norm: 1.1561 loss: 0.9357 loss_heatmap: 0.4222 layer_-1_loss_cls: 0.0682 layer_-1_loss_bbox: 0.4454 matched_ious: 0.5991 2023/05/24 08:14:26 - mmengine - INFO - Epoch(train) [5][3300/3862] lr: 1.7645e-05 eta: 1:39:09 time: 1.3515 data_time: 0.0287 memory: 21742 grad_norm: 1.0373 loss: 0.9234 loss_heatmap: 0.4209 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4347 matched_ious: 0.5735 2023/05/24 08:15:33 - mmengine - INFO - Epoch(train) [5][3350/3862] lr: 1.7265e-05 eta: 1:38:02 time: 1.3415 data_time: 0.0297 memory: 21951 grad_norm: 1.0451 loss: 0.9121 loss_heatmap: 0.4124 layer_-1_loss_cls: 0.0664 layer_-1_loss_bbox: 0.4333 matched_ious: 0.6117 2023/05/24 08:16:40 - mmengine - INFO - Epoch(train) [5][3400/3862] lr: 1.6888e-05 eta: 1:36:55 time: 1.3425 data_time: 0.0299 memory: 22085 grad_norm: 1.0600 loss: 0.9154 loss_heatmap: 0.4140 layer_-1_loss_cls: 0.0661 layer_-1_loss_bbox: 0.4352 matched_ious: 0.5740 2023/05/24 08:17:47 - mmengine - INFO - Epoch(train) [5][3450/3862] lr: 1.6515e-05 eta: 1:35:47 time: 1.3431 data_time: 0.0300 memory: 21932 grad_norm: 1.1097 loss: 0.9262 loss_heatmap: 0.4198 layer_-1_loss_cls: 0.0683 layer_-1_loss_bbox: 0.4381 matched_ious: 0.6193 2023/05/24 08:18:54 - mmengine - INFO - Epoch(train) [5][3500/3862] lr: 1.6146e-05 eta: 1:34:40 time: 1.3339 data_time: 0.0296 memory: 21946 grad_norm: 1.0416 loss: 0.9142 loss_heatmap: 0.4154 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4309 matched_ious: 0.6070 2023/05/24 08:20:01 - mmengine - INFO - Epoch(train) [5][3550/3862] lr: 1.5781e-05 eta: 1:33:33 time: 1.3468 data_time: 0.0306 memory: 21985 grad_norm: 1.2089 loss: 0.9461 loss_heatmap: 0.4251 layer_-1_loss_cls: 0.0697 layer_-1_loss_bbox: 0.4514 matched_ious: 0.5773 2023/05/24 08:20:04 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 08:21:08 - mmengine - INFO - Epoch(train) [5][3600/3862] lr: 1.5420e-05 eta: 1:32:26 time: 1.3359 data_time: 0.0301 memory: 21840 grad_norm: 1.0647 loss: 0.9151 loss_heatmap: 0.4206 layer_-1_loss_cls: 0.0684 layer_-1_loss_bbox: 0.4260 matched_ious: 0.5989 2023/05/24 08:22:15 - mmengine - INFO - Epoch(train) [5][3650/3862] lr: 1.5062e-05 eta: 1:31:18 time: 1.3395 data_time: 0.0298 memory: 22141 grad_norm: 1.1732 loss: 0.9125 loss_heatmap: 0.4183 layer_-1_loss_cls: 0.0674 layer_-1_loss_bbox: 0.4267 matched_ious: 0.6032 2023/05/24 08:23:22 - mmengine - INFO - Epoch(train) [5][3700/3862] lr: 1.4709e-05 eta: 1:30:11 time: 1.3386 data_time: 0.0295 memory: 22015 grad_norm: 1.1207 loss: 0.9180 loss_heatmap: 0.4172 layer_-1_loss_cls: 0.0669 layer_-1_loss_bbox: 0.4339 matched_ious: 0.6334 2023/05/24 08:24:30 - mmengine - INFO - Epoch(train) [5][3750/3862] lr: 1.4359e-05 eta: 1:29:04 time: 1.3633 data_time: 0.0299 memory: 22163 grad_norm: 1.0540 loss: 0.9094 loss_heatmap: 0.4133 layer_-1_loss_cls: 0.0663 layer_-1_loss_bbox: 0.4298 matched_ious: 0.5873 2023/05/24 08:25:37 - mmengine - INFO - Epoch(train) [5][3800/3862] lr: 1.4014e-05 eta: 1:27:57 time: 1.3337 data_time: 0.0298 memory: 21650 grad_norm: 1.0297 loss: 0.9164 loss_heatmap: 0.4206 layer_-1_loss_cls: 0.0681 layer_-1_loss_bbox: 0.4276 matched_ious: 0.5876 2023/05/24 08:26:44 - mmengine - INFO - Epoch(train) [5][3850/3862] lr: 1.3672e-05 eta: 1:26:49 time: 1.3400 data_time: 0.0303 memory: 22048 grad_norm: 0.9793 loss: 0.9030 loss_heatmap: 0.4130 layer_-1_loss_cls: 0.0667 layer_-1_loss_bbox: 0.4233 matched_ious: 0.5931 2023/05/24 08:27:00 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 08:27:00 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/05/24 08:27:15 - mmengine - INFO - Epoch(val) [5][ 50/753] eta: 0:02:43 time: 0.2325 data_time: 0.0144 memory: 21545 2023/05/24 08:27:26 - mmengine - INFO - Epoch(val) [5][100/753] eta: 0:02:26 time: 0.2172 data_time: 0.0061 memory: 2850 2023/05/24 08:27:37 - mmengine - INFO - Epoch(val) [5][150/753] eta: 0:02:15 time: 0.2254 data_time: 0.0087 memory: 2848 2023/05/24 08:27:49 - mmengine - INFO - Epoch(val) [5][200/753] eta: 0:02:04 time: 0.2275 data_time: 0.0061 memory: 2852 2023/05/24 08:28:00 - mmengine - INFO - Epoch(val) [5][250/753] eta: 0:01:53 time: 0.2226 data_time: 0.0066 memory: 2848 2023/05/24 08:28:11 - mmengine - INFO - Epoch(val) [5][300/753] eta: 0:01:41 time: 0.2247 data_time: 0.0079 memory: 2848 2023/05/24 08:28:23 - mmengine - INFO - Epoch(val) [5][350/753] eta: 0:01:31 time: 0.2313 data_time: 0.0070 memory: 2851 2023/05/24 08:28:33 - mmengine - INFO - Epoch(val) [5][400/753] eta: 0:01:19 time: 0.2107 data_time: 0.0061 memory: 2851 2023/05/24 08:28:44 - mmengine - INFO - Epoch(val) [5][450/753] eta: 0:01:07 time: 0.2249 data_time: 0.0071 memory: 2849 2023/05/24 08:28:57 - mmengine - INFO - Epoch(val) [5][500/753] eta: 0:00:57 time: 0.2618 data_time: 0.0071 memory: 2850 2023/05/24 08:29:08 - mmengine - INFO - Epoch(val) [5][550/753] eta: 0:00:46 time: 0.2184 data_time: 0.0067 memory: 2849 2023/05/24 08:29:20 - mmengine - INFO - Epoch(val) [5][600/753] eta: 0:00:34 time: 0.2284 data_time: 0.0063 memory: 2852 2023/05/24 08:29:31 - mmengine - INFO - Epoch(val) [5][650/753] eta: 0:00:23 time: 0.2292 data_time: 0.0066 memory: 2849 2023/05/24 08:29:43 - mmengine - INFO - Epoch(val) [5][700/753] eta: 0:00:12 time: 0.2353 data_time: 0.0073 memory: 2852 2023/05/24 08:29:54 - mmengine - INFO - Epoch(val) [5][750/753] eta: 0:00:00 time: 0.2212 data_time: 0.0066 memory: 2852 2023/05/24 08:41:08 - mmengine - INFO - Epoch(val) [5][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.8115 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.9018 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.9275 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.9377 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1717 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1497 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.0624 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.2793 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1830 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2799 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2534 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.2990 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.2732 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1851 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.4412 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.6420 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.7263 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.7628 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3283 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1809 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.0846 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.2468 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2219 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0429 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.2156 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.3895 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.5249 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6753 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4173 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.8434 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1292 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3054 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4841 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.7718 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.8882 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.9104 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3307 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1852 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.0587 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.4644 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2518 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.1498 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.4657 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.6172 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.6986 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5115 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2090 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.6177 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.1943 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1670 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.6266 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.7204 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7565 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7697 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.1811 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2827 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0588 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.6630 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.7847 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.7976 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.8067 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1851 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2374 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.2675 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.4563 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2404 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.5937 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.6192 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.6286 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.6413 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1532 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2561 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.3142 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2041 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0104 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8660 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8777 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8874 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8975 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1351 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2911 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.3840 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2115 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.1008 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.7736 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.7850 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.8030 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.8258 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1268 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3247 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.7139 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.6858 data_time: 0.0066 time: 0.2183 2023/05/24 08:42:17 - mmengine - INFO - Epoch(train) [6][ 50/3862] lr: 1.3254e-05 eta: 1:25:26 time: 1.3788 data_time: 0.0596 memory: 21975 grad_norm: 1.0573 loss: 0.9291 loss_heatmap: 0.4224 layer_-1_loss_cls: 0.0673 layer_-1_loss_bbox: 0.4394 matched_ious: 0.5936 2023/05/24 08:43:24 - mmengine - INFO - Epoch(train) [6][ 100/3862] lr: 1.2921e-05 eta: 1:24:19 time: 1.3387 data_time: 0.0255 memory: 21969 grad_norm: 1.1104 loss: 0.9064 loss_heatmap: 0.4135 layer_-1_loss_cls: 0.0666 layer_-1_loss_bbox: 0.4263 matched_ious: 0.5812 2023/05/24 08:44:31 - mmengine - INFO - Epoch(train) [6][ 150/3862] lr: 1.2593e-05 eta: 1:23:12 time: 1.3517 data_time: 0.0259 memory: 21799 grad_norm: 1.0367 loss: 0.9345 loss_heatmap: 0.4208 layer_-1_loss_cls: 0.0675 layer_-1_loss_bbox: 0.4463 matched_ious: 0.6062 2023/05/24 08:45:39 - mmengine - INFO - Epoch(train) [6][ 200/3862] lr: 1.2268e-05 eta: 1:22:04 time: 1.3450 data_time: 0.0257 memory: 21886 grad_norm: 1.0045 loss: 0.9134 loss_heatmap: 0.4102 layer_-1_loss_cls: 0.0664 layer_-1_loss_bbox: 0.4368 matched_ious: 0.5896 2023/05/24 08:46:46 - mmengine - INFO - Epoch(train) [6][ 250/3862] lr: 1.1947e-05 eta: 1:20:57 time: 1.3458 data_time: 0.0267 memory: 21962 grad_norm: 1.1877 loss: 0.9218 loss_heatmap: 0.4170 layer_-1_loss_cls: 0.0675 layer_-1_loss_bbox: 0.4373 matched_ious: 0.5931 2023/05/24 08:47:53 - mmengine - INFO - Epoch(train) [6][ 300/3862] lr: 1.1631e-05 eta: 1:19:50 time: 1.3422 data_time: 0.0272 memory: 21996 grad_norm: 1.0964 loss: 0.9066 loss_heatmap: 0.4106 layer_-1_loss_cls: 0.0667 layer_-1_loss_bbox: 0.4292 matched_ious: 0.6044 2023/05/24 08:49:01 - mmengine - INFO - Epoch(train) [6][ 350/3862] lr: 1.1318e-05 eta: 1:18:43 time: 1.3522 data_time: 0.0276 memory: 21796 grad_norm: 1.0906 loss: 0.9007 loss_heatmap: 0.4083 layer_-1_loss_cls: 0.0654 layer_-1_loss_bbox: 0.4270 matched_ious: 0.6037 2023/05/24 08:50:07 - mmengine - INFO - Epoch(train) [6][ 400/3862] lr: 1.1010e-05 eta: 1:17:35 time: 1.3334 data_time: 0.0273 memory: 21726 grad_norm: 1.0956 loss: 0.9172 loss_heatmap: 0.4184 layer_-1_loss_cls: 0.0673 layer_-1_loss_bbox: 0.4315 matched_ious: 0.6079 2023/05/24 08:51:15 - mmengine - INFO - Epoch(train) [6][ 450/3862] lr: 1.0706e-05 eta: 1:16:28 time: 1.3505 data_time: 0.0281 memory: 22115 grad_norm: 1.0837 loss: 0.9162 loss_heatmap: 0.4137 layer_-1_loss_cls: 0.0675 layer_-1_loss_bbox: 0.4350 matched_ious: 0.5852 2023/05/24 08:52:22 - mmengine - INFO - Epoch(train) [6][ 500/3862] lr: 1.0405e-05 eta: 1:15:21 time: 1.3436 data_time: 0.0279 memory: 21701 grad_norm: 1.0400 loss: 0.9342 loss_heatmap: 0.4211 layer_-1_loss_cls: 0.0675 layer_-1_loss_bbox: 0.4455 matched_ious: 0.5854 2023/05/24 08:53:30 - mmengine - INFO - Epoch(train) [6][ 550/3862] lr: 1.0109e-05 eta: 1:14:14 time: 1.3549 data_time: 0.0274 memory: 21914 grad_norm: 1.0242 loss: 0.9087 loss_heatmap: 0.4126 layer_-1_loss_cls: 0.0669 layer_-1_loss_bbox: 0.4293 matched_ious: 0.5743 2023/05/24 08:54:38 - mmengine - INFO - Epoch(train) [6][ 600/3862] lr: 9.8172e-06 eta: 1:13:07 time: 1.3691 data_time: 0.0282 memory: 21962 grad_norm: 1.0914 loss: 0.9016 loss_heatmap: 0.4124 layer_-1_loss_cls: 0.0669 layer_-1_loss_bbox: 0.4223 matched_ious: 0.5891 2023/05/24 08:55:46 - mmengine - INFO - Epoch(train) [6][ 650/3862] lr: 9.5294e-06 eta: 1:12:00 time: 1.3475 data_time: 0.0272 memory: 21917 grad_norm: 1.0553 loss: 0.9247 loss_heatmap: 0.4208 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4361 matched_ious: 0.5681 2023/05/24 08:56:39 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 08:56:53 - mmengine - INFO - Epoch(train) [6][ 700/3862] lr: 9.2457e-06 eta: 1:10:52 time: 1.3390 data_time: 0.0271 memory: 21812 grad_norm: 1.1029 loss: 0.9004 loss_heatmap: 0.4066 layer_-1_loss_cls: 0.0664 layer_-1_loss_bbox: 0.4274 matched_ious: 0.5979 2023/05/24 08:58:00 - mmengine - INFO - Epoch(train) [6][ 750/3862] lr: 8.9662e-06 eta: 1:09:45 time: 1.3406 data_time: 0.0269 memory: 22389 grad_norm: 1.0221 loss: 0.9185 loss_heatmap: 0.4169 layer_-1_loss_cls: 0.0670 layer_-1_loss_bbox: 0.4347 matched_ious: 0.5915 2023/05/24 08:59:08 - mmengine - INFO - Epoch(train) [6][ 800/3862] lr: 8.6909e-06 eta: 1:08:38 time: 1.3565 data_time: 0.0271 memory: 21697 grad_norm: 1.0383 loss: 0.9046 loss_heatmap: 0.4110 layer_-1_loss_cls: 0.0665 layer_-1_loss_bbox: 0.4271 matched_ious: 0.6029 2023/05/24 09:00:15 - mmengine - INFO - Epoch(train) [6][ 850/3862] lr: 8.4198e-06 eta: 1:07:31 time: 1.3436 data_time: 0.0280 memory: 21817 grad_norm: 1.0965 loss: 0.9163 loss_heatmap: 0.4193 layer_-1_loss_cls: 0.0674 layer_-1_loss_bbox: 0.4296 matched_ious: 0.6078 2023/05/24 09:01:22 - mmengine - INFO - Epoch(train) [6][ 900/3862] lr: 8.1529e-06 eta: 1:06:23 time: 1.3437 data_time: 0.0276 memory: 21928 grad_norm: 1.0838 loss: 0.9118 loss_heatmap: 0.4143 layer_-1_loss_cls: 0.0670 layer_-1_loss_bbox: 0.4304 matched_ious: 0.5876 2023/05/24 09:02:29 - mmengine - INFO - Epoch(train) [6][ 950/3862] lr: 7.8902e-06 eta: 1:05:16 time: 1.3446 data_time: 0.0272 memory: 21726 grad_norm: 1.0542 loss: 0.9110 loss_heatmap: 0.4091 layer_-1_loss_cls: 0.0662 layer_-1_loss_bbox: 0.4357 matched_ious: 0.6081 2023/05/24 09:03:36 - mmengine - INFO - Epoch(train) [6][1000/3862] lr: 7.6318e-06 eta: 1:04:09 time: 1.3426 data_time: 0.0276 memory: 22102 grad_norm: 1.0434 loss: 0.9224 loss_heatmap: 0.4200 layer_-1_loss_cls: 0.0678 layer_-1_loss_bbox: 0.4346 matched_ious: 0.5857 2023/05/24 09:04:45 - mmengine - INFO - Epoch(train) [6][1050/3862] lr: 7.3776e-06 eta: 1:03:02 time: 1.3766 data_time: 0.0284 memory: 21836 grad_norm: 1.0922 loss: 0.8889 loss_heatmap: 0.4043 layer_-1_loss_cls: 0.0661 layer_-1_loss_bbox: 0.4186 matched_ious: 0.6088 2023/05/24 09:05:52 - mmengine - INFO - Epoch(train) [6][1100/3862] lr: 7.1276e-06 eta: 1:01:54 time: 1.3382 data_time: 0.0283 memory: 21764 grad_norm: 1.1089 loss: 0.9069 loss_heatmap: 0.4110 layer_-1_loss_cls: 0.0660 layer_-1_loss_bbox: 0.4299 matched_ious: 0.5999 2023/05/24 09:06:59 - mmengine - INFO - Epoch(train) [6][1150/3862] lr: 6.8820e-06 eta: 1:00:47 time: 1.3463 data_time: 0.0270 memory: 21867 grad_norm: 1.0674 loss: 0.9198 loss_heatmap: 0.4177 layer_-1_loss_cls: 0.0675 layer_-1_loss_bbox: 0.4346 matched_ious: 0.6316 2023/05/24 09:08:06 - mmengine - INFO - Epoch(train) [6][1200/3862] lr: 6.6406e-06 eta: 0:59:40 time: 1.3420 data_time: 0.0278 memory: 22146 grad_norm: 1.0958 loss: 0.9109 loss_heatmap: 0.4127 layer_-1_loss_cls: 0.0666 layer_-1_loss_bbox: 0.4316 matched_ious: 0.5856 2023/05/24 09:09:14 - mmengine - INFO - Epoch(train) [6][1250/3862] lr: 6.4036e-06 eta: 0:58:33 time: 1.3543 data_time: 0.0281 memory: 21821 grad_norm: 1.1551 loss: 0.9070 loss_heatmap: 0.4088 layer_-1_loss_cls: 0.0673 layer_-1_loss_bbox: 0.4309 matched_ious: 0.5952 2023/05/24 09:10:21 - mmengine - INFO - Epoch(train) [6][1300/3862] lr: 6.1708e-06 eta: 0:57:25 time: 1.3388 data_time: 0.0274 memory: 21978 grad_norm: 1.0268 loss: 0.9140 loss_heatmap: 0.4138 layer_-1_loss_cls: 0.0669 layer_-1_loss_bbox: 0.4333 matched_ious: 0.5914 2023/05/24 09:11:28 - mmengine - INFO - Epoch(train) [6][1350/3862] lr: 5.9423e-06 eta: 0:56:18 time: 1.3392 data_time: 0.0270 memory: 21830 grad_norm: 1.0310 loss: 0.9317 loss_heatmap: 0.4214 layer_-1_loss_cls: 0.0673 layer_-1_loss_bbox: 0.4430 matched_ious: 0.5899 2023/05/24 09:12:35 - mmengine - INFO - Epoch(train) [6][1400/3862] lr: 5.7182e-06 eta: 0:55:11 time: 1.3398 data_time: 0.0279 memory: 22049 grad_norm: 1.0451 loss: 0.9070 loss_heatmap: 0.4135 layer_-1_loss_cls: 0.0668 layer_-1_loss_bbox: 0.4266 matched_ious: 0.5625 2023/05/24 09:13:42 - mmengine - INFO - Epoch(train) [6][1450/3862] lr: 5.4984e-06 eta: 0:54:04 time: 1.3368 data_time: 0.0279 memory: 21846 grad_norm: 1.0498 loss: 0.9031 loss_heatmap: 0.4091 layer_-1_loss_cls: 0.0657 layer_-1_loss_bbox: 0.4283 matched_ious: 0.6169 2023/05/24 09:14:50 - mmengine - INFO - Epoch(train) [6][1500/3862] lr: 5.2830e-06 eta: 0:52:56 time: 1.3641 data_time: 0.0286 memory: 22043 grad_norm: 1.0396 loss: 0.9166 loss_heatmap: 0.4198 layer_-1_loss_cls: 0.0669 layer_-1_loss_bbox: 0.4299 matched_ious: 0.5840 2023/05/24 09:15:57 - mmengine - INFO - Epoch(train) [6][1550/3862] lr: 5.0719e-06 eta: 0:51:49 time: 1.3459 data_time: 0.0281 memory: 21955 grad_norm: 1.1148 loss: 0.9012 loss_heatmap: 0.4056 layer_-1_loss_cls: 0.0658 layer_-1_loss_bbox: 0.4297 matched_ious: 0.5993 2023/05/24 09:17:05 - mmengine - INFO - Epoch(train) [6][1600/3862] lr: 4.8652e-06 eta: 0:50:42 time: 1.3455 data_time: 0.0279 memory: 21698 grad_norm: 1.0688 loss: 0.9064 loss_heatmap: 0.4113 layer_-1_loss_cls: 0.0660 layer_-1_loss_bbox: 0.4292 matched_ious: 0.5926 2023/05/24 09:18:12 - mmengine - INFO - Epoch(train) [6][1650/3862] lr: 4.6628e-06 eta: 0:49:35 time: 1.3465 data_time: 0.0278 memory: 21917 grad_norm: 1.0496 loss: 0.9119 loss_heatmap: 0.4105 layer_-1_loss_cls: 0.0660 layer_-1_loss_bbox: 0.4353 matched_ious: 0.5856 2023/05/24 09:19:06 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 09:19:19 - mmengine - INFO - Epoch(train) [6][1700/3862] lr: 4.4649e-06 eta: 0:48:27 time: 1.3488 data_time: 0.0272 memory: 21820 grad_norm: 1.0236 loss: 0.9065 loss_heatmap: 0.4106 layer_-1_loss_cls: 0.0661 layer_-1_loss_bbox: 0.4298 matched_ious: 0.5904 2023/05/24 09:20:27 - mmengine - INFO - Epoch(train) [6][1750/3862] lr: 4.2713e-06 eta: 0:47:20 time: 1.3520 data_time: 0.0278 memory: 22004 grad_norm: 1.1073 loss: 0.9132 loss_heatmap: 0.4162 layer_-1_loss_cls: 0.0667 layer_-1_loss_bbox: 0.4303 matched_ious: 0.5720 2023/05/24 09:21:34 - mmengine - INFO - Epoch(train) [6][1800/3862] lr: 4.0822e-06 eta: 0:46:13 time: 1.3375 data_time: 0.0276 memory: 21977 grad_norm: 1.0223 loss: 0.9012 loss_heatmap: 0.4077 layer_-1_loss_cls: 0.0653 layer_-1_loss_bbox: 0.4283 matched_ious: 0.5960 2023/05/24 09:22:41 - mmengine - INFO - Epoch(train) [6][1850/3862] lr: 3.8974e-06 eta: 0:45:06 time: 1.3473 data_time: 0.0281 memory: 22000 grad_norm: 1.0864 loss: 0.9137 loss_heatmap: 0.4127 layer_-1_loss_cls: 0.0663 layer_-1_loss_bbox: 0.4346 matched_ious: 0.5927 2023/05/24 09:23:49 - mmengine - INFO - Epoch(train) [6][1900/3862] lr: 3.7171e-06 eta: 0:43:58 time: 1.3473 data_time: 0.0282 memory: 21790 grad_norm: 1.0953 loss: 0.8940 loss_heatmap: 0.4025 layer_-1_loss_cls: 0.0652 layer_-1_loss_bbox: 0.4263 matched_ious: 0.5989 2023/05/24 09:24:57 - mmengine - INFO - Epoch(train) [6][1950/3862] lr: 3.5412e-06 eta: 0:42:51 time: 1.3754 data_time: 0.0276 memory: 21826 grad_norm: 0.9802 loss: 0.9050 loss_heatmap: 0.4086 layer_-1_loss_cls: 0.0652 layer_-1_loss_bbox: 0.4312 matched_ious: 0.5835 2023/05/24 09:26:05 - mmengine - INFO - Epoch(train) [6][2000/3862] lr: 3.3697e-06 eta: 0:41:44 time: 1.3502 data_time: 0.0280 memory: 21717 grad_norm: 1.0467 loss: 0.9107 loss_heatmap: 0.4128 layer_-1_loss_cls: 0.0664 layer_-1_loss_bbox: 0.4315 matched_ious: 0.6051 2023/05/24 09:27:12 - mmengine - INFO - Epoch(train) [6][2050/3862] lr: 3.2027e-06 eta: 0:40:37 time: 1.3500 data_time: 0.0280 memory: 21878 grad_norm: 1.1612 loss: 0.9320 loss_heatmap: 0.4215 layer_-1_loss_cls: 0.0677 layer_-1_loss_bbox: 0.4428 matched_ious: 0.5725 2023/05/24 09:28:20 - mmengine - INFO - Epoch(train) [6][2100/3862] lr: 3.0402e-06 eta: 0:39:30 time: 1.3440 data_time: 0.0288 memory: 21839 grad_norm: 1.1431 loss: 0.9016 loss_heatmap: 0.4114 layer_-1_loss_cls: 0.0662 layer_-1_loss_bbox: 0.4240 matched_ious: 0.5911 2023/05/24 09:29:28 - mmengine - INFO - Epoch(train) [6][2150/3862] lr: 2.8821e-06 eta: 0:38:22 time: 1.3618 data_time: 0.0279 memory: 21740 grad_norm: 1.1669 loss: 0.8980 loss_heatmap: 0.4074 layer_-1_loss_cls: 0.0654 layer_-1_loss_bbox: 0.4253 matched_ious: 0.6003 2023/05/24 09:30:35 - mmengine - INFO - Epoch(train) [6][2200/3862] lr: 2.7284e-06 eta: 0:37:15 time: 1.3411 data_time: 0.0277 memory: 21758 grad_norm: 1.1420 loss: 0.9204 loss_heatmap: 0.4191 layer_-1_loss_cls: 0.0676 layer_-1_loss_bbox: 0.4337 matched_ious: 0.5799 2023/05/24 09:31:42 - mmengine - INFO - Epoch(train) [6][2250/3862] lr: 2.5793e-06 eta: 0:36:08 time: 1.3432 data_time: 0.0281 memory: 21810 grad_norm: 1.0300 loss: 0.8968 loss_heatmap: 0.4075 layer_-1_loss_cls: 0.0657 layer_-1_loss_bbox: 0.4235 matched_ious: 0.5872 2023/05/24 09:32:49 - mmengine - INFO - Epoch(train) [6][2300/3862] lr: 2.4346e-06 eta: 0:35:01 time: 1.3384 data_time: 0.0279 memory: 21956 grad_norm: 1.0843 loss: 0.9149 loss_heatmap: 0.4176 layer_-1_loss_cls: 0.0669 layer_-1_loss_bbox: 0.4303 matched_ious: 0.5691 2023/05/24 09:33:57 - mmengine - INFO - Epoch(train) [6][2350/3862] lr: 2.2944e-06 eta: 0:33:53 time: 1.3582 data_time: 0.0276 memory: 21770 grad_norm: 1.0433 loss: 0.9404 loss_heatmap: 0.4256 layer_-1_loss_cls: 0.0685 layer_-1_loss_bbox: 0.4463 matched_ious: 0.5904 2023/05/24 09:35:05 - mmengine - INFO - Epoch(train) [6][2400/3862] lr: 2.1587e-06 eta: 0:32:46 time: 1.3559 data_time: 0.0272 memory: 22108 grad_norm: 0.9933 loss: 0.8975 loss_heatmap: 0.4075 layer_-1_loss_cls: 0.0662 layer_-1_loss_bbox: 0.4237 matched_ious: 0.5696 2023/05/24 09:36:12 - mmengine - INFO - Epoch(train) [6][2450/3862] lr: 2.0275e-06 eta: 0:31:39 time: 1.3386 data_time: 0.0273 memory: 21853 grad_norm: 1.0588 loss: 0.9103 loss_heatmap: 0.4124 layer_-1_loss_cls: 0.0664 layer_-1_loss_bbox: 0.4315 matched_ious: 0.5905 2023/05/24 09:37:19 - mmengine - INFO - Epoch(train) [6][2500/3862] lr: 1.9008e-06 eta: 0:30:32 time: 1.3541 data_time: 0.0281 memory: 21898 grad_norm: 1.0406 loss: 0.9234 loss_heatmap: 0.4153 layer_-1_loss_cls: 0.0666 layer_-1_loss_bbox: 0.4415 matched_ious: 0.6020 2023/05/24 09:38:26 - mmengine - INFO - Epoch(train) [6][2550/3862] lr: 1.7787e-06 eta: 0:29:24 time: 1.3439 data_time: 0.0279 memory: 22068 grad_norm: 1.0260 loss: 0.9063 loss_heatmap: 0.4112 layer_-1_loss_cls: 0.0658 layer_-1_loss_bbox: 0.4293 matched_ious: 0.5951 2023/05/24 09:39:34 - mmengine - INFO - Epoch(train) [6][2600/3862] lr: 1.6610e-06 eta: 0:28:17 time: 1.3557 data_time: 0.0285 memory: 21811 grad_norm: 0.9952 loss: 0.9180 loss_heatmap: 0.4166 layer_-1_loss_cls: 0.0672 layer_-1_loss_bbox: 0.4341 matched_ious: 0.5762 2023/05/24 09:40:41 - mmengine - INFO - Epoch(train) [6][2650/3862] lr: 1.5479e-06 eta: 0:27:10 time: 1.3391 data_time: 0.0279 memory: 21762 grad_norm: 1.0717 loss: 0.9103 loss_heatmap: 0.4192 layer_-1_loss_cls: 0.0667 layer_-1_loss_bbox: 0.4244 matched_ious: 0.5873 2023/05/24 09:41:35 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 09:41:48 - mmengine - INFO - Epoch(train) [6][2700/3862] lr: 1.4393e-06 eta: 0:26:03 time: 1.3442 data_time: 0.0285 memory: 21901 grad_norm: 1.0217 loss: 0.8967 loss_heatmap: 0.4075 layer_-1_loss_cls: 0.0652 layer_-1_loss_bbox: 0.4240 matched_ious: 0.5993 2023/05/24 09:42:55 - mmengine - INFO - Epoch(train) [6][2750/3862] lr: 1.3352e-06 eta: 0:24:55 time: 1.3375 data_time: 0.0280 memory: 21790 grad_norm: 1.0322 loss: 0.9064 loss_heatmap: 0.4129 layer_-1_loss_cls: 0.0667 layer_-1_loss_bbox: 0.4267 matched_ious: 0.6027 2023/05/24 09:44:03 - mmengine - INFO - Epoch(train) [6][2800/3862] lr: 1.2357e-06 eta: 0:23:48 time: 1.3625 data_time: 0.0270 memory: 21822 grad_norm: 1.1107 loss: 0.9030 loss_heatmap: 0.4082 layer_-1_loss_cls: 0.0655 layer_-1_loss_bbox: 0.4294 matched_ious: 0.5944 2023/05/24 09:45:10 - mmengine - INFO - Epoch(train) [6][2850/3862] lr: 1.1407e-06 eta: 0:22:41 time: 1.3418 data_time: 0.0274 memory: 21828 grad_norm: 0.9791 loss: 0.9005 loss_heatmap: 0.4075 layer_-1_loss_cls: 0.0657 layer_-1_loss_bbox: 0.4273 matched_ious: 0.6025 2023/05/24 09:46:18 - mmengine - INFO - Epoch(train) [6][2900/3862] lr: 1.0502e-06 eta: 0:21:34 time: 1.3460 data_time: 0.0275 memory: 21913 grad_norm: 1.0781 loss: 0.9097 loss_heatmap: 0.4134 layer_-1_loss_cls: 0.0672 layer_-1_loss_bbox: 0.4290 matched_ious: 0.6183 2023/05/24 09:47:25 - mmengine - INFO - Epoch(train) [6][2950/3862] lr: 9.6436e-07 eta: 0:20:26 time: 1.3371 data_time: 0.0275 memory: 21993 grad_norm: 1.0630 loss: 0.9233 loss_heatmap: 0.4173 layer_-1_loss_cls: 0.0672 layer_-1_loss_bbox: 0.4388 matched_ious: 0.6042 2023/05/24 09:48:32 - mmengine - INFO - Epoch(train) [6][3000/3862] lr: 8.8302e-07 eta: 0:19:19 time: 1.3467 data_time: 0.0274 memory: 22073 grad_norm: 1.0078 loss: 0.9168 loss_heatmap: 0.4134 layer_-1_loss_cls: 0.0664 layer_-1_loss_bbox: 0.4370 matched_ious: 0.6131 2023/05/24 09:49:41 - mmengine - INFO - Epoch(train) [6][3050/3862] lr: 8.0625e-07 eta: 0:18:12 time: 1.3857 data_time: 0.0261 memory: 21801 grad_norm: 1.1250 loss: 0.9101 loss_heatmap: 0.4179 layer_-1_loss_cls: 0.0670 layer_-1_loss_bbox: 0.4252 matched_ious: 0.5919 2023/05/24 09:50:48 - mmengine - INFO - Epoch(train) [6][3100/3862] lr: 7.3404e-07 eta: 0:17:05 time: 1.3406 data_time: 0.0281 memory: 21838 grad_norm: 1.2558 loss: 0.8972 loss_heatmap: 0.4059 layer_-1_loss_cls: 0.0662 layer_-1_loss_bbox: 0.4252 matched_ious: 0.5866 2023/05/24 09:51:56 - mmengine - INFO - Epoch(train) [6][3150/3862] lr: 6.6639e-07 eta: 0:15:57 time: 1.3508 data_time: 0.0281 memory: 21934 grad_norm: 1.0976 loss: 0.9033 loss_heatmap: 0.4053 layer_-1_loss_cls: 0.0657 layer_-1_loss_bbox: 0.4323 matched_ious: 0.5860 2023/05/24 09:53:03 - mmengine - INFO - Epoch(train) [6][3200/3862] lr: 6.0331e-07 eta: 0:14:50 time: 1.3432 data_time: 0.0288 memory: 21956 grad_norm: 1.0663 loss: 0.9185 loss_heatmap: 0.4178 layer_-1_loss_cls: 0.0674 layer_-1_loss_bbox: 0.4333 matched_ious: 0.6083 2023/05/24 09:54:12 - mmengine - INFO - Epoch(train) [6][3250/3862] lr: 5.4481e-07 eta: 0:13:43 time: 1.3718 data_time: 0.0278 memory: 21938 grad_norm: 1.2806 loss: 0.9119 loss_heatmap: 0.4107 layer_-1_loss_cls: 0.0662 layer_-1_loss_bbox: 0.4349 matched_ious: 0.5836 2023/05/24 09:55:19 - mmengine - INFO - Epoch(train) [6][3300/3862] lr: 4.9088e-07 eta: 0:12:36 time: 1.3388 data_time: 0.0277 memory: 22245 grad_norm: 1.0114 loss: 0.8968 loss_heatmap: 0.4084 layer_-1_loss_cls: 0.0654 layer_-1_loss_bbox: 0.4230 matched_ious: 0.6000 2023/05/24 09:56:26 - mmengine - INFO - Epoch(train) [6][3350/3862] lr: 4.4153e-07 eta: 0:11:28 time: 1.3488 data_time: 0.0282 memory: 21899 grad_norm: 1.0363 loss: 0.9070 loss_heatmap: 0.4108 layer_-1_loss_cls: 0.0660 layer_-1_loss_bbox: 0.4301 matched_ious: 0.5813 2023/05/24 09:57:33 - mmengine - INFO - Epoch(train) [6][3400/3862] lr: 3.9676e-07 eta: 0:10:21 time: 1.3445 data_time: 0.0276 memory: 21673 grad_norm: 1.0479 loss: 0.9177 loss_heatmap: 0.4124 layer_-1_loss_cls: 0.0661 layer_-1_loss_bbox: 0.4392 matched_ious: 0.5968 2023/05/24 09:58:40 - mmengine - INFO - Epoch(train) [6][3450/3862] lr: 3.5657e-07 eta: 0:09:14 time: 1.3384 data_time: 0.0280 memory: 22092 grad_norm: 1.1745 loss: 0.8944 loss_heatmap: 0.4052 layer_-1_loss_cls: 0.0659 layer_-1_loss_bbox: 0.4233 matched_ious: 0.6072 2023/05/24 09:59:48 - mmengine - INFO - Epoch(train) [6][3500/3862] lr: 3.2096e-07 eta: 0:08:07 time: 1.3489 data_time: 0.0273 memory: 22196 grad_norm: 1.0468 loss: 0.9011 loss_heatmap: 0.4144 layer_-1_loss_cls: 0.0670 layer_-1_loss_bbox: 0.4197 matched_ious: 0.5787 2023/05/24 10:00:55 - mmengine - INFO - Epoch(train) [6][3550/3862] lr: 2.8994e-07 eta: 0:06:59 time: 1.3447 data_time: 0.0273 memory: 22130 grad_norm: 1.1603 loss: 0.9190 loss_heatmap: 0.4153 layer_-1_loss_cls: 0.0676 layer_-1_loss_bbox: 0.4361 matched_ious: 0.5928 2023/05/24 10:02:02 - mmengine - INFO - Epoch(train) [6][3600/3862] lr: 2.6350e-07 eta: 0:05:52 time: 1.3476 data_time: 0.0272 memory: 21753 grad_norm: 1.1778 loss: 0.9072 loss_heatmap: 0.4095 layer_-1_loss_cls: 0.0664 layer_-1_loss_bbox: 0.4314 matched_ious: 0.6079 2023/05/24 10:03:09 - mmengine - INFO - Epoch(train) [6][3650/3862] lr: 2.4165e-07 eta: 0:04:45 time: 1.3432 data_time: 0.0285 memory: 21991 grad_norm: 1.0763 loss: 0.9148 loss_heatmap: 0.4138 layer_-1_loss_cls: 0.0665 layer_-1_loss_bbox: 0.4345 matched_ious: 0.5781 2023/05/24 10:04:05 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 10:04:18 - mmengine - INFO - Epoch(train) [6][3700/3862] lr: 2.2439e-07 eta: 0:03:37 time: 1.3754 data_time: 0.0278 memory: 21726 grad_norm: 1.0536 loss: 0.9044 loss_heatmap: 0.4136 layer_-1_loss_cls: 0.0658 layer_-1_loss_bbox: 0.4250 matched_ious: 0.5850 2023/05/24 10:05:25 - mmengine - INFO - Epoch(train) [6][3750/3862] lr: 2.1172e-07 eta: 0:02:30 time: 1.3456 data_time: 0.0281 memory: 22189 grad_norm: 1.0961 loss: 0.9200 loss_heatmap: 0.4178 layer_-1_loss_cls: 0.0671 layer_-1_loss_bbox: 0.4350 matched_ious: 0.5814 2023/05/24 10:06:32 - mmengine - INFO - Epoch(train) [6][3800/3862] lr: 2.0364e-07 eta: 0:01:23 time: 1.3392 data_time: 0.0277 memory: 21740 grad_norm: 1.0296 loss: 0.8665 loss_heatmap: 0.3948 layer_-1_loss_cls: 0.0643 layer_-1_loss_bbox: 0.4074 matched_ious: 0.5960 2023/05/24 10:07:40 - mmengine - INFO - Epoch(train) [6][3850/3862] lr: 2.0016e-07 eta: 0:00:16 time: 1.3444 data_time: 0.0272 memory: 21849 grad_norm: 1.0106 loss: 0.9045 loss_heatmap: 0.4133 layer_-1_loss_cls: 0.0664 layer_-1_loss_bbox: 0.4248 matched_ious: 0.6191 2023/05/24 10:07:56 - mmengine - INFO - Exp name: bevfusion_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230524_001539 2023/05/24 10:07:56 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/05/24 10:08:11 - mmengine - INFO - Epoch(val) [6][ 50/753] eta: 0:02:47 time: 0.2385 data_time: 0.0150 memory: 21409 2023/05/24 10:08:23 - mmengine - INFO - Epoch(val) [6][100/753] eta: 0:02:31 time: 0.2262 data_time: 0.0070 memory: 2850 2023/05/24 10:08:34 - mmengine - INFO - Epoch(val) [6][150/753] eta: 0:02:17 time: 0.2199 data_time: 0.0075 memory: 2848 2023/05/24 10:08:46 - mmengine - INFO - Epoch(val) [6][200/753] eta: 0:02:07 time: 0.2370 data_time: 0.0073 memory: 2852 2023/05/24 10:08:59 - mmengine - INFO - Epoch(val) [6][250/753] eta: 0:01:59 time: 0.2707 data_time: 0.0104 memory: 2848 2023/05/24 10:09:10 - mmengine - INFO - Epoch(val) [6][300/753] eta: 0:01:46 time: 0.2200 data_time: 0.0067 memory: 2848 2023/05/24 10:09:22 - mmengine - INFO - Epoch(val) [6][350/753] eta: 0:01:34 time: 0.2311 data_time: 0.0073 memory: 2851 2023/05/24 10:09:32 - mmengine - INFO - Epoch(val) [6][400/753] eta: 0:01:21 time: 0.2144 data_time: 0.0072 memory: 2851 2023/05/24 10:09:44 - mmengine - INFO - Epoch(val) [6][450/753] eta: 0:01:10 time: 0.2351 data_time: 0.0078 memory: 2849 2023/05/24 10:09:56 - mmengine - INFO - Epoch(val) [6][500/753] eta: 0:00:58 time: 0.2315 data_time: 0.0084 memory: 2850 2023/05/24 10:10:07 - mmengine - INFO - Epoch(val) [6][550/753] eta: 0:00:46 time: 0.2191 data_time: 0.0064 memory: 2849 2023/05/24 10:10:18 - mmengine - INFO - Epoch(val) [6][600/753] eta: 0:00:35 time: 0.2289 data_time: 0.0070 memory: 2852 2023/05/24 10:10:30 - mmengine - INFO - Epoch(val) [6][650/753] eta: 0:00:23 time: 0.2475 data_time: 0.0097 memory: 2849 2023/05/24 10:10:42 - mmengine - INFO - Epoch(val) [6][700/753] eta: 0:00:12 time: 0.2307 data_time: 0.0061 memory: 2852 2023/05/24 10:10:53 - mmengine - INFO - Epoch(val) [6][750/753] eta: 0:00:00 time: 0.2196 data_time: 0.0063 memory: 2852 2023/05/24 10:22:11 - mmengine - INFO - Epoch(val) [6][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.7892 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.8828 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.9112 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.9226 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1774 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1664 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.0810 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.2778 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1829 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2866 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2762 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.3072 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.2731 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1904 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.3507 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.5359 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.6113 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.6490 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3427 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1950 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.0785 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.2422 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2359 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0447 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.2179 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.3745 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.5045 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6569 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4138 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.8751 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1323 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3062 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4617 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.7329 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.8656 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.8924 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3513 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.2292 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.0624 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.4732 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2521 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.1277 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.3807 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.5439 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.6249 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5356 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2538 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.5822 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.1869 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1794 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.6269 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.7235 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7654 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7782 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.1870 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.3055 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0599 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.6444 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.7621 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.7759 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.7884 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1869 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2579 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.2580 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.4559 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2499 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.5908 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.6124 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.6214 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.6328 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1514 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2809 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.3653 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2024 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0120 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8617 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8738 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8848 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8945 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1408 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.3147 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.4027 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2142 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.1048 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.7686 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.7803 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.8002 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.8260 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1356 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3442 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.6971 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.6609 data_time: 0.0062 time: 0.2174