Traceback (most recent call last): File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/utils/misc.py", line 77, in import_modules_from_strings imported_tmp = import_module(imp) ^^^^^^^^^^^^^^^^^^ File "/home/marimo/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/importlib/__init__.py", line 126, in import_module return _bootstrap._gcd_import(name[level:], package, level) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "", line 1204, in _gcd_import File "", line 1176, in _find_and_load File "", line 1140, in _find_and_load_unlocked ModuleNotFoundError: No module named 'dynamicvis' During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/config/config.py", line 466, in fromfile import_modules_from_strings(**cfg_dict['custom_imports']) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/utils/misc.py", line 84, in import_modules_from_strings raise ImportError(f'Failed to import {imp}') ImportError: Failed to import dynamicvis The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 94, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 87, in main cfg=make_cfg(args,data,out); cfg.dump(str(out/'resolved_config.py')); (out/'experiment_manifest.json').write_text(json.dumps(dict(dataset=args.dataset,seed=42,split_seed=42,epochs=100,patience=15,batch_size=8,workers=8,optimizer='MuSGD',augmentation='shared_yolo_train_pipeline Mosaic p=1.0 + RandomAffine + HSV + flip + Resize + Pad',nms_iou=.5,pretrained=cfg.pretrained_ckpt),indent=2)) ^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 54, in make_cfg cfg=Config.fromfile(base) ^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/config/config.py", line 478, in fromfile raise ImportError(err_msg) from e ImportError: Failed to import custom modules from {'imports': 'dynamicvis', 'allow_failed_imports': False}, the current sys.path is: /usr/local/_marimo/sitedir /tmp/uv-venv/lib/python3.13/site-packages /marimo/mmdet_code /home/marimo/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python311.zip /home/marimo/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11 /home/marimo/.local/share/uv/python/cpython-3.11-linux-x86_64-gnu/lib/python3.11/lib-dynload /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages /marimo You should set `PYTHONPATH` to make `sys.path` include the directory which contains your custom module /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 13:42:27 - mmengine - WARNING - torch.backends.cudnn.benchmark is going to be set as `False` to cause cuDNN to deterministically select an algorithm 09/30 13:42:27 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: True Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 13:42:27 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'projects.set', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=1024, init_cfg=dict( checkpoint= 'work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= 'work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=True, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, pre_transform=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='CocoDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), dict( init_kwargs=dict( group='LevirShip', name='dynamicvis_b_levirship_mamba', project='dynamicvis'), type='WandbVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), dict( init_kwargs=dict( group='LevirShip', name='dynamicvis_b_levirship_mamba', project='dynamicvis'), type='WandbVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 96, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 92, in main runner=Runner.from_cfg(cfg); runner.train(); runner.test() ^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 462, in from_cfg runner = cls( ^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 418, in __init__ self.visualizer.add_config(self.cfg) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/dist/utils.py", line 427, in wrapper return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/visualization/visualizer.py", line 1071, in add_config vis_backend.add_config(config, **kwargs) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/visualization/vis_backend.py", line 57, in wrapper obj._init_env() # type: ignore ^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/visualization/vis_backend.py", line 408, in _init_env wandb.init(**self._init_kwargs) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/wandb/sdk/wandb_init.py", line 1556, in init telemetry_recorder.reraise(e) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/wandb/analytics/opentelemetry/opentelemetry_proxy.py", line 419, in reraise raise exc File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/wandb/sdk/wandb_init.py", line 1468, in init wi.maybe_login(init_settings) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/wandb/sdk/wandb_init.py", line 210, in maybe_login wandb_login._login( File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/wandb/sdk/wandb_login.py", line 205, in _login auth = _find_or_prompt_for_key( ^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/wandb/sdk/wandb_login.py", line 287, in _find_or_prompt_for_key auth = wbauth.authenticate_session( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/wandb/sdk/lib/wbauth/authenticate.py", line 135, in authenticate_session raise UsageError( wandb.errors.errors.UsageError: No API key configured. Use `wandb login` to log in. /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 13:43:38 - mmengine - WARNING - torch.backends.cudnn.benchmark is going to be set as `False` to cause cuDNN to deterministically select an algorithm 09/30 13:43:38 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: True Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 13:43:38 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'projects.set', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=1024, init_cfg=dict( checkpoint= 'work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= 'work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=True, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, pre_transform=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='CocoDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' not trainable parameters: set() not trainable parameters: set() trainable params: 41,464,128 || all params: 41,464,128 || trainable%: 100.0000 09/30 13:43:39 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. 09/30 13:43:39 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook (LOWEST ) EarlyStoppingHook -------------------- 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: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook (LOWEST ) EarlyStoppingHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 98, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 94, in main runner=Runner.from_cfg(cfg); runner.train(); runner.test() ^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1728, in train self._train_loop = self.build_train_loop( ^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1520, in build_train_loop loop = LOOPS.build( ^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/registry/registry.py", line 570, in build return self.build_func(cfg, *args, **kwargs, registry=self) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg obj = obj_cls(**args) # type: ignore ^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 46, in __init__ super().__init__(runner, dataloader) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/base_loop.py", line 26, in __init__ self.dataloader = runner.build_dataloader( ^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1370, in build_dataloader dataset = DATASETS.build(dataset_cfg) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/registry/registry.py", line 570, in build return self.build_func(cfg, *args, **kwargs, registry=self) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg obj = obj_cls(**args) # type: ignore ^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/datasets/base_det_dataset.py", line 51, in __init__ super().__init__(*args, **kwargs) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/dataset/base_dataset.py", line 244, in __init__ self.pipeline = Compose(pipeline) ^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/dataset/base_dataset.py", line 38, in __init__ transform = TRANSFORMS.build(transform) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/registry/registry.py", line 570, in build return self.build_func(cfg, *args, **kwargs, registry=self) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg obj = obj_cls(**args) # type: ignore ^^^^^^^^^^^^^^^ TypeError: Mosaic.__init__() got an unexpected keyword argument 'pre_transform' /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 13:45:04 - mmengine - WARNING - torch.backends.cudnn.benchmark is going to be set as `False` to cause cuDNN to deterministically select an algorithm 09/30 13:45:04 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: True Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 13:45:05 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'projects.set', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=1024, init_cfg=dict( checkpoint= 'work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= 'work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=True, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], type='CocoDataset'), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='MultiImageMixDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' not trainable parameters: set() not trainable parameters: set() trainable params: 41,464,128 || all params: 41,464,128 || trainable%: 100.0000 09/30 13:45:06 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. 09/30 13:45:06 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook (LOWEST ) EarlyStoppingHook -------------------- 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: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook (LOWEST ) EarlyStoppingHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- loading annotations into memory... Done (t=0.12s) creating index... index created! Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 97, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 93, in main runner=Runner.from_cfg(cfg); runner.train(); runner.test() ^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1733, in train self.optim_wrapper = self.build_optim_wrapper(self.optim_wrapper) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1114, in build_optim_wrapper return build_optim_wrapper(self.model, optim_wrapper) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/builder.py", line 214, in build_optim_wrapper optim_wrapper = optim_wrapper_constructor(model) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/default_constructor.py", line 308, in __call__ iter(inspect.signature(optimizer_cls).parameters)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/marimo/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/inspect.py", line 3263, in signature return Signature.from_callable(obj, follow_wrapped=follow_wrapped, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/marimo/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/inspect.py", line 3011, in from_callable return _signature_from_callable(obj, sigcls=cls, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/marimo/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/inspect.py", line 2456, in _signature_from_callable raise TypeError('{!r} is not a callable object'.format(obj)) TypeError: None is not a callable object Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 98, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 91, in main cfg=make_cfg(args,data,out); cfg.dump(str(out/'resolved_config.py')); (out/'experiment_manifest.json').write_text(json.dumps(dict(dataset=args.dataset,seed=42,split_seed=42,epochs=100,patience=15,batch_size=8,workers=8,optimizer='MuSGD',augmentation='shared_yolo_train_pipeline Mosaic p=1.0 + RandomAffine + HSV + flip + Resize + Pad',nms_iou=.5,pretrained=cfg.pretrained_ckpt),indent=2)) ^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 54, in make_cfg import projects.set # registers the MuSGD optimizer used by the baseline protocol ^^^^^^^^^^^^^^^^^^^ File "/marimo/mmdet_code/mmdetection/projects/set/__init__.py", line 1, in from .models import * File "/marimo/mmdet_code/mmdetection/projects/set/models/__init__.py", line 1, in from .fcos_set import FCOS_set File "/marimo/mmdet_code/mmdetection/projects/set/models/fcos_set.py", line 11, in from mmdet.models.detectors.single_stage import SingleStageDetector File "/marimo/DynamicVis/mmdet/models/__init__.py", line 4, in from .dense_heads import * # noqa: F401,F403 ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/models/dense_heads/__init__.py", line 8, in from .cascade_rpn_head import CascadeRPNHead, StageCascadeRPNHead File "/marimo/DynamicVis/mmdet/models/dense_heads/cascade_rpn_head.py", line 23, in from .rpn_head import RPNHead File "/marimo/DynamicVis/mmdet/models/dense_heads/rpn_head.py", line 10, in from dynamicvis.ops import batched_nms File "/marimo/DynamicVis/dynamicvis/__init__.py", line 2, in from .models import * File "/marimo/DynamicVis/dynamicvis/models/__init__.py", line 1, in from .models import * File "/marimo/DynamicVis/dynamicvis/models/models.py", line 15, in from mmdet.models import nlc_to_nchw, nchw_to_nlc ImportError: cannot import name 'nlc_to_nchw' from partially initialized module 'mmdet.models' (most likely due to a circular import) (/marimo/DynamicVis/mmdet/models/__init__.py) Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 99, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 92, in main cfg=make_cfg(args,data,out); cfg.dump(str(out/'resolved_config.py')); (out/'experiment_manifest.json').write_text(json.dumps(dict(dataset=args.dataset,seed=42,split_seed=42,epochs=100,patience=15,batch_size=8,workers=8,optimizer='MuSGD',augmentation='shared_yolo_train_pipeline Mosaic p=1.0 + RandomAffine + HSV + flip + Resize + Pad',nms_iou=.5,pretrained=cfg.pretrained_ckpt),indent=2)) ^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 54, in make_cfg import mmdet.models File "/marimo/DynamicVis/mmdet/models/__init__.py", line 4, in from .dense_heads import * # noqa: F401,F403 ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/models/dense_heads/__init__.py", line 8, in from .cascade_rpn_head import CascadeRPNHead, StageCascadeRPNHead File "/marimo/DynamicVis/mmdet/models/dense_heads/cascade_rpn_head.py", line 23, in from .rpn_head import RPNHead File "/marimo/DynamicVis/mmdet/models/dense_heads/rpn_head.py", line 10, in from dynamicvis.ops import batched_nms File "/marimo/DynamicVis/dynamicvis/__init__.py", line 2, in from .models import * File "/marimo/DynamicVis/dynamicvis/models/__init__.py", line 1, in from .models import * File "/marimo/DynamicVis/dynamicvis/models/models.py", line 15, in from mmdet.models import nlc_to_nchw, nchw_to_nlc ImportError: cannot import name 'nlc_to_nchw' from partially initialized module 'mmdet.models' (most likely due to a circular import) (/marimo/DynamicVis/mmdet/models/__init__.py) /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 13:49:08 - mmengine - WARNING - torch.backends.cudnn.benchmark is going to be set as `False` to cause cuDNN to deterministically select an algorithm 09/30 13:49:08 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: True Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 13:49:08 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'srtod_project.optim.musgd', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=1024, init_cfg=dict( checkpoint= 'work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= 'work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=True, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], type='CocoDataset'), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='MultiImageMixDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' not trainable parameters: set() not trainable parameters: set() trainable params: 41,464,128 || all params: 41,464,128 || trainable%: 100.0000 09/30 13:49:09 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. 09/30 13:49:09 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook (LOWEST ) EarlyStoppingHook -------------------- 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: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook (LOWEST ) EarlyStoppingHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- loading annotations into memory... Done (t=0.12s) creating index... index created! 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.norm.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.0.2.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.norm.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.1.2.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.norm.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.2.2.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.norm.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- backbone.layers.3.2.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.gn.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.gn.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.gn.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.gn.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.gn.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.gn.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.gn.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.gn.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:weight_decay=0.0 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:lr=0.01 09/30 13:49:10 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:weight_decay=0.0 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/amp_optimizer_wrapper.py:97: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. self.loss_scaler = scaler_type() loading annotations into memory... Done (t=0.12s) creating index... index created! loading annotations into memory... Done (t=0.12s) creating index... index created! 09/30 13:49:11 - mmengine - INFO - load backbone. in model from: work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth Loads checkpoint by local backend from path: work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 98, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 94, in main runner=Runner.from_cfg(cfg); runner.train(); runner.test() ^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1748, in train self._init_model_weights() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 923, in _init_model_weights model.init_weights() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_module.py", line 136, in init_weights m.init_weights() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_module.py", line 144, in init_weights initialize(self, pretrained_cfg) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/weight_init.py", line 610, in initialize _initialize(module, cp_cfg) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/weight_init.py", line 518, in _initialize func(module) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/weight_init.py", line 500, in __call__ state_dict = _load_checkpoint_with_prefix( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py", line 566, in _load_checkpoint_with_prefix checkpoint = _load_checkpoint(filename, map_location=map_location) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py", line 548, in _load_checkpoint return CheckpointLoader.load_checkpoint(filename, map_location, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py", line 330, in load_checkpoint return checkpoint_loader(filename, map_location) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py", line 346, in load_from_local raise FileNotFoundError(f'{filename} can not be found.') FileNotFoundError: work_dirs/fMoW/pretrain_dynamicvis_b_bf16_mamba/epoch_200.pth can not be found. /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 13:50:14 - mmengine - WARNING - torch.backends.cudnn.benchmark is going to be set as `False` to cause cuDNN to deterministically select an algorithm 09/30 13:50:14 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: True Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 13:50:15 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'srtod_project.optim.musgd', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=1024, init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=True, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], type='CocoDataset'), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='MultiImageMixDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' not trainable parameters: set() not trainable parameters: set() trainable params: 41,464,128 || all params: 41,464,128 || trainable%: 100.0000 09/30 13:50:15 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. 09/30 13:50:15 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook (LOWEST ) EarlyStoppingHook -------------------- 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: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook (LOWEST ) EarlyStoppingHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- loading annotations into memory... Done (t=0.29s) creating index... index created! 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.norm.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.0.2.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.norm.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.1.2.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.norm.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.2.2.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.norm.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- backbone.layers.3.2.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.gn.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.gn.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.gn.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.gn.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.gn.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.gn.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.gn.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.gn.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:weight_decay=0.0 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:lr=0.01 09/30 13:50:16 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:weight_decay=0.0 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/amp_optimizer_wrapper.py:97: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. self.loss_scaler = scaler_type() loading annotations into memory... Done (t=0.12s) creating index... index created! loading annotations into memory... Done (t=0.12s) creating index... index created! 09/30 13:50:17 - mmengine - INFO - load backbone. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 100, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 96, in main runner=Runner.from_cfg(cfg); runner.train(); runner.test() ^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1748, in train self._init_model_weights() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 923, in _init_model_weights model.init_weights() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_module.py", line 136, in init_weights m.init_weights() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_module.py", line 144, in init_weights initialize(self, pretrained_cfg) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/weight_init.py", line 610, in initialize _initialize(module, cp_cfg) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/weight_init.py", line 518, in _initialize func(module) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/weight_init.py", line 500, in __call__ state_dict = _load_checkpoint_with_prefix( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py", line 566, in _load_checkpoint_with_prefix checkpoint = _load_checkpoint(filename, map_location=map_location) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py", line 548, in _load_checkpoint return CheckpointLoader.load_checkpoint(filename, map_location, logger) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py", line 330, in load_checkpoint return checkpoint_loader(filename, map_location) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py", line 347, in load_from_local checkpoint = torch.load(filename, map_location=map_location) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/serialization.py", line 1609, in load raise pickle.UnpicklingError(_get_wo_message(str(e))) from None _pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint. (1) In PyTorch 2.6, we changed the default value of the `weights_only` argument in `torch.load` from `False` to `True`. Re-running `torch.load` with `weights_only` set to `False` will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source. (2) Alternatively, to load with `weights_only=True` please check the recommended steps in the following error message. WeightsUnpickler error: Unsupported global: GLOBAL mmengine.logging.history_buffer.HistoryBuffer was not an allowed global by default. Please use `torch.serialization.add_safe_globals([mmengine.logging.history_buffer.HistoryBuffer])` or the `torch.serialization.safe_globals([mmengine.logging.history_buffer.HistoryBuffer])` context manager to allowlist this global if you trust this class/function. Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html. /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 13:51:19 - mmengine - WARNING - torch.backends.cudnn.benchmark is going to be set as `False` to cause cuDNN to deterministically select an algorithm 09/30 13:51:19 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: True Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 13:51:19 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'srtod_project.optim.musgd', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=1024, init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=True, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], type='CocoDataset'), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='MultiImageMixDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' not trainable parameters: set() not trainable parameters: set() trainable params: 41,464,128 || all params: 41,464,128 || trainable%: 100.0000 09/30 13:51:20 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. 09/30 13:51:20 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook (LOWEST ) EarlyStoppingHook -------------------- 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: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook (LOWEST ) EarlyStoppingHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- loading annotations into memory... Done (t=0.31s) creating index... index created! 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.norm.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.2.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.norm.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.1.2.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.norm.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.2.2.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.norm.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- backbone.layers.3.2.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.gn.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.gn.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.gn.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.gn.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.gn.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.gn.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.gn.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.gn.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:weight_decay=0.0 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:lr=0.01 09/30 13:51:21 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:weight_decay=0.0 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/amp_optimizer_wrapper.py:97: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. self.loss_scaler = scaler_type() loading annotations into memory... Done (t=0.12s) creating index... index created! loading annotations into memory... Done (t=0.12s) creating index... index created! 09/30 13:51:22 - mmengine - INFO - load backbone. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py:347: UserWarning: Environment variable TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD detected, since the`weights_only` argument was not explicitly passed to `torch.load`, forcing weights_only=False. checkpoint = torch.load(filename, map_location=map_location) Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth 09/30 13:51:22 - mmengine - INFO - Resize the pos_embed shape from torch.Size([1, 16384, 96]) to torch.Size([1, 65536, 96]). 09/30 13:51:23 - mmengine - INFO - load pre_neck. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth 09/30 13:51:23 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 09/30 13:51:23 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 09/30 13:51:23 - mmengine - INFO - Checkpoints will be saved to /marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic. Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 101, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 97, in main runner=Runner.from_cfg(cfg); runner.train(); runner.test() ^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1777, in train model = self.train_loop.run() # type: ignore ^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 98, in run self.run_epoch() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 115, in run_epoch self.run_iter(idx, data_batch) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 131, in run_iter outputs = self.runner.model.train_step( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_model/base_model.py", line 114, in train_step losses = self._run_forward(data, mode='loss') # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_model/base_model.py", line 361, in _run_forward results = self(**data, mode=mode) ^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1778, in _wrapped_call_impl return self._call_impl(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1789, in _call_impl return forward_call(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/models/detectors/base.py", line 92, in forward return self.loss(inputs, data_samples) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/models/detectors/single_stage.py", line 77, in loss x = self.extract_feat(batch_inputs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/models/detectors/single_stage.py", line 146, in extract_feat x = self.backbone(batch_inputs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1778, in _wrapped_call_impl return self._call_impl(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1789, in _call_impl return forward_call(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/dynamicvis/models/models.py", line 602, in forward x = x + self.pos_embed.to(device=x.device) ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ RuntimeError: The size of tensor a (25600) must match the size of tensor b (65536) at non-singleton dimension 1 /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 13:58:07 - mmengine - WARNING - torch.backends.cudnn.benchmark is going to be set as `False` to cause cuDNN to deterministically select an algorithm 09/30 13:58:07 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: True Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 13:58:08 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'srtod_project.optim.musgd', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=1024, init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=True, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], type='CocoDataset'), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='MultiImageMixDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' not trainable parameters: set() not trainable parameters: set() trainable params: 41,464,128 || all params: 41,464,128 || trainable%: 100.0000 09/30 13:58:09 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. 09/30 13:58:09 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook (LOWEST ) EarlyStoppingHook -------------------- 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: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook (LOWEST ) EarlyStoppingHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- loading annotations into memory... Done (t=0.30s) creating index... index created! 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.norm.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.0.2.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.norm.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.1.2.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.norm.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.2.2.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.norm.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- backbone.layers.3.2.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.gn.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.gn.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.gn.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.gn.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.gn.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.gn.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.gn.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.gn.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:weight_decay=0.0 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:lr=0.01 09/30 13:58:09 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:weight_decay=0.0 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/amp_optimizer_wrapper.py:97: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. self.loss_scaler = scaler_type() loading annotations into memory... Done (t=0.12s) creating index... index created! loading annotations into memory... Done (t=0.12s) creating index... index created! 09/30 13:58:11 - mmengine - INFO - load backbone. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py:347: UserWarning: Environment variable TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD detected, since the`weights_only` argument was not explicitly passed to `torch.load`, forcing weights_only=False. checkpoint = torch.load(filename, map_location=map_location) Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth 09/30 13:58:11 - mmengine - INFO - Resize the pos_embed shape from torch.Size([1, 16384, 96]) to torch.Size([1, 65536, 96]). 09/30 13:58:11 - mmengine - INFO - load pre_neck. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth 09/30 13:58:11 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 09/30 13:58:11 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 09/30 13:58:11 - mmengine - INFO - Checkpoints will be saved to /marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic. Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 101, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 97, in main runner=Runner.from_cfg(cfg); runner.train(); runner.test() ^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1777, in train model = self.train_loop.run() # type: ignore ^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 98, in run self.run_epoch() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 115, in run_epoch self.run_iter(idx, data_batch) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 131, in run_iter outputs = self.runner.model.train_step( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_model/base_model.py", line 114, in train_step losses = self._run_forward(data, mode='loss') # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_model/base_model.py", line 361, in _run_forward results = self(**data, mode=mode) ^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1778, in _wrapped_call_impl return self._call_impl(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1789, in _call_impl return forward_call(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/models/detectors/base.py", line 92, in forward return self.loss(inputs, data_samples) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/models/detectors/single_stage.py", line 77, in loss x = self.extract_feat(batch_inputs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/mmdet/models/detectors/single_stage.py", line 146, in extract_feat x = self.backbone(batch_inputs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1778, in _wrapped_call_impl return self._call_impl(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1789, in _call_impl return forward_call(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/DynamicVis/dynamicvis/models/models.py", line 602, in forward x = x + self.pos_embed.to(device=x.device) ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ RuntimeError: The size of tensor a (25600) must match the size of tensor b (65536) at non-singleton dimension 1 /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 14:24:27 - mmengine - WARNING - torch.backends.cudnn.benchmark is going to be set as `False` to cause cuDNN to deterministically select an algorithm 09/30 14:24:27 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: True Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 14:24:27 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'srtod_project.optim.musgd', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=640, init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=True, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], type='CocoDataset'), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='MultiImageMixDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' not trainable parameters: set() not trainable parameters: set() trainable params: 37,630,272 || all params: 37,630,272 || trainable%: 100.0000 09/30 14:24:28 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. 09/30 14:24:28 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook (LOWEST ) EarlyStoppingHook -------------------- 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: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook (LOWEST ) EarlyStoppingHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- loading annotations into memory... Done (t=0.29s) creating index... index created! 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.norm.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.0.2.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.norm.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.1.2.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.norm.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.2.2.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.norm.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- backbone.layers.3.2.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.gn.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.gn.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.gn.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.gn.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.gn.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.gn.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.gn.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.gn.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:weight_decay=0.0 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:lr=0.01 09/30 14:24:29 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:weight_decay=0.0 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/amp_optimizer_wrapper.py:97: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. self.loss_scaler = scaler_type() loading annotations into memory... Done (t=0.12s) creating index... index created! loading annotations into memory... Done (t=0.13s) creating index... index created! 09/30 14:24:30 - mmengine - INFO - load backbone. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py:347: UserWarning: Environment variable TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD detected, since the`weights_only` argument was not explicitly passed to `torch.load`, forcing weights_only=False. checkpoint = torch.load(filename, map_location=map_location) Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth 09/30 14:24:31 - mmengine - INFO - Resize the pos_embed shape from torch.Size([1, 16384, 96]) to torch.Size([1, 25600, 96]). 09/30 14:24:31 - mmengine - INFO - load pre_neck. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth 09/30 14:24:31 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 09/30 14:24:31 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 09/30 14:24:31 - mmengine - INFO - Checkpoints will be saved to /marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic. /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /__w/pytorch/pytorch/aten/src/ATen/native/TensorShape.cpp:4215.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] Traceback (most recent call last): File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 102, in if __name__=='__main__': main() ^^^^^^ File "/marimo/mmdet_code/train_dynamicvis_yolo_mosaic.py", line 98, in main runner=Runner.from_cfg(cfg); runner.train(); runner.test() ^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/runner.py", line 1777, in train model = self.train_loop.run() # type: ignore ^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 98, in run self.run_epoch() File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 115, in run_epoch self.run_iter(idx, data_batch) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/loops.py", line 131, in run_iter outputs = self.runner.model.train_step( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/model/base_model/base_model.py", line 116, in train_step optim_wrapper.update_params(parsed_losses) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/optimizer_wrapper.py", line 196, in update_params self.backward(loss) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/amp_optimizer_wrapper.py", line 126, in backward self.loss_scaler.scale(loss).backward(**kwargs) File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/_tensor.py", line 623, in backward torch.autograd.backward( File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/autograd/__init__.py", line 395, in backward _engine_run_backward( File "/marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/autograd/graph.py", line 979, in _engine_run_backward return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ RuntimeError: adaptive_avg_pool2d_backward_cuda does not have a deterministic implementation, but you set 'torch.use_deterministic_algorithms(True)'. You can turn off determinism just for this operation, or you can use the 'warn_only=True' option, if that's acceptable for your application. You can also file an issue at https://github.com/pytorch/pytorch/issues to help us prioritize adding deterministic support for this operation. /marimo/DynamicVis/dynamicvis/models/models.py:34: UserWarning: horovod is not installed warnings.warn('horovod is not installed') 09/30 14:29:38 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.11.15 (main, Jul 23 2026, 14:43:45) [Clang 22.1.3 ] CUDA available: True MUSA available: False numpy_random_seed: 42 GPU 0: NVIDIA RTX PRO 6000 Blackwell Server Edition CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 13.1, V13.1.115 GCC: cc (Debian 14.2.0-19) 14.2.0 PyTorch: 2.13.0+cu130 PyTorch compiling details: PyTorch built with: - GCC 13.3 - C++ Version: 202002 - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.12.0 (Git Hash 80afa71049cd69a3df32adcccb623b12cd7baa22) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 13.0 - NVCC architecture flags: -gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90;-gencode;arch=compute_100,code=sm_100;-gencode;arch=compute_120,code=sm_120 - CuDNN 92.0 (built against CUDA 13.2) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=cf30153c4c131c8164ee7798e5022d810682e2cb, CUDA_FLAGS= -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90 -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -Xfatbin -compress-all --threads 2 -compress-mode=size -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DDISABLE_CUSPARSE_DEPRECATED -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -DC10_NODEPRECATED, CUDA_VERSION=13.0, CUDNN_VERSION=9.20.0, CXX_COMPILER=/opt/rh/gcc-toolset-13/root/usr/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DHAS_CUPTI -DUSE_FBGEMM -DUSE_MSLK -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-dangling-reference -Wno-error=dangling-reference -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.13.0, USE_CUDA=1, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, TorchVision: 0.28.0+cu130 OpenCV: 4.11.0 MMEngine: 0.10.7 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 42 deterministic: False Distributed launcher: none Distributed training: False GPU number: 1 ------------------------------------------------------------ 09/30 14:29:38 - mmengine - INFO - Config: backend_args = None base_lr = 0.0002 batch_size = 8 bgr_mean = [ 103.53, 116.28, 123.675, ] bgr_std = [ 57.375, 57.12, 58.395, ] code_root = '/mnt/search01/usr/chenkeyan/codes/dynamicvis' crop_size = ( 640, 640, ) custom_hooks = [ dict( min_delta=0.001, monitor='coco/bbox_mAP', patience=15, rule='greater', type='EarlyStoppingHook'), ] custom_imports = dict( allow_failed_imports=False, imports=[ 'srtod_project.optim.musgd', 'mmdet.datasets.transforms', 'dynamicvis', ]) data_preprocessor = dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor') data_root = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset' dataset_type = 'LevirShipDetDataset' default_hooks = dict( checkpoint=dict( by_epoch=True, interval=1, max_keep_ckpts=1, rule='greater', save_best='coco/bbox_mAP', save_last=True, type='CheckpointHook'), logger=dict(interval=5, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict( draw=False, interval=1, score_thr=0.3, test_out_dir='work_dirs/LevirShip/dynamicvis_b_levirship_mamba/vis', type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) find_unused_parameters = True img_size = 640 indices = None line_width = 2 load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=50) model = dict( backbone=dict( arch='b', global_token_cfg=dict(num=-1, pos='head'), img_size=640, init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='backbone.', type='Pretrained'), is_softmax_on_x=True, out_indices=( 0, 1, 2, 3, ), out_type='featmap', patch_sizes=[ 7, 3, 3, 3, ], path_type='forward_reverse_mean', sampling_scale=dict(type='decay', val=0.1), spatial_token_keep_ratios=[ 8, 4, 2, 1, ], strides=[ 4, 2, 2, 2, ], type='mmpretrain.DynamicVisBackbone'), bbox_head=dict( center_sampling=True, centerness_on_reg=True, conv_bias=True, dcn_on_last_conv=False, feat_channels=256, in_channels=256, loss_bbox=dict(loss_weight=1.0, type='GIoULoss'), loss_centerness=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), loss_cls=dict( alpha=0.25, gamma=2.0, loss_weight=1.0, type='FocalLoss', use_sigmoid=True), norm_on_bbox=True, num_classes=1, regress_ranges=( ( 0, 20, ), ( 16, 40, ), ( 32, 80, ), ( 64, 160, ), ( 128, 1024, ), ), stacked_convs=4, strides=[ 4, 8, 16, 32, 64, ], type='FCOSHead'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_size_divisor=32, std=[ 58.395, 57.12, 57.375, ], type='DetDataPreprocessor'), neck=dict( in_channels=[ 96, 192, 384, 768, ], init_cfg=dict( checkpoint= '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth', prefix='pre_neck.', type='Pretrained'), num_outs=5, out_channels=256, type='FPN'), test_cfg=dict( max_per_img=100, min_bbox_size=0, nms=dict(iou_threshold=0.5, type='nms'), nms_pre=1000, score_thr=0.05), type='FCOS') norm_cfg = dict(requires_grad=True, type='SyncBN') num_classes = 1 num_workers = 8 optim_wrapper = dict( clip_grad=dict(max_norm=35, norm_type=2), loss_scale='dynamic', optimizer=dict( lr=0.01, momentum=0.9, muon=0.2, nesterov=True, sgd=1.0, type='MuSGD', weight_decay=0.0005), paramwise_cfg=dict(bias_decay_mult=0.0, bias_lr_mult=1.0), type='AmpOptimWrapper') param_scheduler = [ dict(begin=0, by_epoch=True, end=3, start_factor=0.001, type='LinearLR'), dict( begin=3, by_epoch=True, end=100, end_factor=0.01, start_factor=1.0, type='LinearLR'), ] persistent_workers = True pretrained_ckpt = '/marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth' randomness = dict(deterministic=False, seed=42) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/test.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') test_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='LoadAnnotations', with_bbox=True), dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'pad_shape', 'scale_factor', ), type='PackDetInputs'), ] train_cfg = dict(max_epochs=100, type='EpochBasedTrainLoop', val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( dataset=dict( ann_file='annotations/train.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), ], type='CocoDataset'), pipeline=[ dict( img_scale=( 640, 640, ), pad_val=114.0, prob=1.0, type='Mosaic'), dict( border=( -320, -320, ), border_val=( 114.0, 114.0, 114.0, ), max_rotate_degree=0.0, max_shear_degree=0.0, max_translate_ratio=0.1, scaling_ratio_range=( 0.5, 1.5, ), type='RandomAffine'), dict(type='YOLOXHSVRandomAug'), dict(prob=0.5, type='RandomFlip'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict( pad_val=dict(img=( 114, 114, 114, )), size=( 640, 640, ), type='Pad'), dict(type='PackDetInputs'), ], type='MultiImageMixDataset'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(direction='vertical', prob=0.5, type='RandomFlip'), dict( interpolation='bicubic', keep_ratio=True, ratio_range=( 0.5, 1.8, ), resize_type='Resize', scale=( 1024, 1024, ), type='RandomResize'), dict( allow_negative_crop=True, crop_size=( 1024, 1024, ), crop_type='absolute', recompute_bbox=True, type='RandomCrop'), dict( pad_val=dict(img=( 103.53, 116.28, 123.675, )), size=( 1024, 1024, ), type='Pad'), dict(type='PackDetInputs'), ] tta_model = dict( tta_cfg=dict(max_per_img=100, nms=dict(iou_threshold=0.5, type='nms')), type='DetTTAModel') tta_pipeline = [ dict(backend_args=None, to_float32=True, type='LoadImageFromFile'), dict( transforms=[ [ dict(keep_ratio=True, scale=( 1024, 1024, ), type='Resize'), ], [ dict(prob=0.0, type='RandomFlip'), dict(direction='horizontal', prob=1.0, type='RandomFlip'), dict(direction='vertical', prob=1.0, type='RandomFlip'), dict( direction=[ 'horizontal', 'vertical', ], prob=[ 1.0, 1.0, ], type='RandomFlip'), ], [ dict( pad_val=dict(img=( 103.53, 116.28, 123.675, ), mask=0), size=( 1024, 1024, ), type='Pad'), ], [ dict(type='LoadAnnotations', with_bbox=True), ], [ dict( meta_keys=( 'img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'flip', 'flip_direction', 'border', ), type='PackDetInputs'), ], ], type='TestTimeAug'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=8, dataset=dict( ann_file='annotations/val.json', data_prefix=dict(img=''), data_root= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset', metainfo=dict(classes=('person', )), pipeline=[ dict(type='LoadImageFromFile'), dict(keep_ratio=False, scale=( 640, 640, ), type='Resize'), dict(type='LoadAnnotations', with_bbox=True), dict(type='PackDetInputs'), ], test_mode=True, type='CocoDataset'), drop_last=False, num_workers=8, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file= '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic/dataset/annotations/val.json', iou_thrs=[ 0.5, ], metric=[ 'bbox', ], type='CocoMetric') val_interval = 5 vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( line_width=2, name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) warmup_epochs = 5 work_dir = '/marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic' not trainable parameters: set() not trainable parameters: set() trainable params: 37,630,272 || all params: 37,630,272 || trainable%: 100.0000 09/30 14:29:39 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used. 09/30 14:29:39 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook (LOWEST ) EarlyStoppingHook -------------------- 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: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook (LOWEST ) EarlyStoppingHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- loading annotations into memory... Done (t=0.29s) creating index... index created! 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.projection.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.0.norm.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.0.2.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.projection.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.0.norm.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.1.2.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.projection.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.0.norm.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.4.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.5.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.6.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.7.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.8.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.9.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.10.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.11.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.12.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.13.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.14.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.1.15.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.2.2.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.projection.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.0.norm.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.0.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.1.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.2.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.conv1d.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.1.3.spatial_mamba_mixer.mamba_layer.dt_proj.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- backbone.layers.3.2.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.lateral_convs.0.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.lateral_convs.1.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.lateral_convs.2.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.lateral_convs.3.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.fpn_convs.0.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.fpn_convs.1.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.fpn_convs.2.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- neck.fpn_convs.3.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.0.gn.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.1.gn.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.2.gn.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.cls_convs.3.gn.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.0.gn.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.1.gn.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.2.gn.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.conv.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.reg_convs.3.gn.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.conv_cls.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.conv_reg.bias:weight_decay=0.0 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:lr=0.01 09/30 14:29:40 - mmengine - INFO - paramwise_options -- bbox_head.conv_centerness.bias:weight_decay=0.0 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/optim/optimizer/amp_optimizer_wrapper.py:97: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead. self.loss_scaler = scaler_type() loading annotations into memory... Done (t=0.12s) creating index... index created! loading annotations into memory... Done (t=0.13s) creating index... index created! 09/30 14:29:41 - mmengine - INFO - load backbone. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/runner/checkpoint.py:347: UserWarning: Environment variable TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD detected, since the`weights_only` argument was not explicitly passed to `torch.load`, forcing weights_only=False. checkpoint = torch.load(filename, map_location=map_location) Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth 09/30 14:29:42 - mmengine - INFO - Resize the pos_embed shape from torch.Size([1, 16384, 96]) to torch.Size([1, 25600, 96]). 09/30 14:29:42 - mmengine - INFO - load pre_neck. in model from: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth Loads checkpoint by local backend from path: /marimo/DynamicVis/checkpoints/pretrain_dynamicvis_b_bf16_mamba_epoch_200.pth 09/30 14:29:42 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 09/30 14:29:42 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 09/30 14:29:42 - mmengine - INFO - Checkpoints will be saved to /marimo/mmdet_code/runs/dynamicvis_tinyperson_mosaic. /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /__w/pytorch/pytorch/aten/src/ATen/native/TensorShape.cpp:4215.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] 09/30 14:29:55 - mmengine - INFO - Epoch(train) [1][ 5/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 6:51:19 time: 2.6268 data_time: 0.3009 memory: 12811 grad_norm: nan loss: 0.1443 loss_cls: 0.1443 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:29:57 - mmengine - INFO - Epoch(train) [1][10/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 3:53:20 time: 1.4910 data_time: 0.1572 memory: 11785 grad_norm: nan loss: 0.1295 loss_cls: 0.1295 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:29:59 - mmengine - INFO - Epoch(train) [1][15/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 2:52:32 time: 1.1031 data_time: 0.1059 memory: 11785 grad_norm: nan loss: 0.1108 loss_cls: 0.1108 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:00 - mmengine - INFO - Epoch(train) [1][20/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 2:22:36 time: 0.9122 data_time: 0.0819 memory: 11785 grad_norm: nan loss: 0.0966 loss_cls: 0.0966 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:02 - mmengine - INFO - Epoch(train) [1][25/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 2:04:28 time: 0.7966 data_time: 0.0673 memory: 11785 grad_norm: nan loss: 0.0850 loss_cls: 0.0850 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:04 - mmengine - INFO - Epoch(train) [1][30/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:51:54 time: 0.7166 data_time: 0.0577 memory: 11785 grad_norm: nan loss: 0.0761 loss_cls: 0.0761 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:05 - mmengine - INFO - Epoch(train) [1][35/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:43:16 time: 0.6617 data_time: 0.0508 memory: 11785 grad_norm: nan loss: 0.0691 loss_cls: 0.0691 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:07 - mmengine - INFO - Epoch(train) [1][40/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:36:08 time: 0.6162 data_time: 0.0458 memory: 11785 grad_norm: nan loss: 0.0635 loss_cls: 0.0635 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:08 - mmengine - INFO - Epoch(train) [1][45/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:31:30 time: 0.5869 data_time: 0.0422 memory: 11785 grad_norm: nan loss: 0.0588 loss_cls: 0.0588 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:10 - mmengine - INFO - Epoch(train) [1][50/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:27:50 time: 0.5637 data_time: 0.0389 memory: 11785 grad_norm: nan loss: 0.0548 loss_cls: 0.0548 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:12 - mmengine - INFO - Epoch(train) [1][55/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:24:19 time: 0.3329 data_time: 0.0099 memory: 11785 grad_norm: nan loss: 0.0420 loss_cls: 0.0420 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:13 - mmengine - INFO - Epoch(train) [1][60/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:21:33 time: 0.3305 data_time: 0.0096 memory: 11785 grad_norm: nan loss: 0.0321 loss_cls: 0.0321 loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:15 - mmengine - INFO - Epoch(train) [1][65/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:18:55 time: 0.3285 data_time: 0.0102 memory: 11785 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:17 - mmengine - INFO - Epoch(train) [1][70/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:16:59 time: 0.3283 data_time: 0.0103 memory: 11785 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:18 - mmengine - INFO - Epoch(train) [1][75/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:15:18 time: 0.3285 data_time: 0.0104 memory: 11785 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:20 - mmengine - INFO - Epoch(train) [1][80/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:13:35 time: 0.3281 data_time: 0.0104 memory: 11785 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:21 - mmengine - INFO - Epoch(train) [1][85/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:11:52 time: 0.3238 data_time: 0.0104 memory: 11785 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:23 - mmengine - INFO - Epoch(train) [1][90/94] base_lr: 1.0000e-05 lr: 1.0000e-05 eta: 1:10:31 time: 0.3251 data_time: 0.0106 memory: 11785 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:29 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:30:29 - mmengine - INFO - Saving checkpoint at 1 epochs 09/30 14:30:36 - mmengine - INFO - Epoch(val) [1][ 5/102] eta: 0:01:49 time: 1.1245 data_time: 0.3393 memory: 35292 09/30 14:30:37 - mmengine - INFO - Epoch(val) [1][ 10/102] eta: 0:00:56 time: 0.6171 data_time: 0.1727 memory: 1697 09/30 14:30:37 - mmengine - INFO - Epoch(val) [1][ 15/102] eta: 0:00:38 time: 0.4478 data_time: 0.1168 memory: 1697 09/30 14:30:38 - mmengine - INFO - Epoch(val) [1][ 20/102] eta: 0:00:29 time: 0.3635 data_time: 0.0892 memory: 1697 09/30 14:30:38 - mmengine - INFO - Epoch(val) [1][ 25/102] eta: 0:00:24 time: 0.3135 data_time: 0.0732 memory: 1697 09/30 14:30:39 - mmengine - INFO - Epoch(val) [1][ 30/102] eta: 0:00:20 time: 0.2798 data_time: 0.0624 memory: 1697 09/30 14:30:39 - mmengine - INFO - Epoch(val) [1][ 35/102] eta: 0:00:17 time: 0.2557 data_time: 0.0544 memory: 1697 09/30 14:30:40 - mmengine - INFO - Epoch(val) [1][ 40/102] eta: 0:00:14 time: 0.2377 data_time: 0.0486 memory: 1697 09/30 14:30:41 - mmengine - INFO - Epoch(val) [1][ 45/102] eta: 0:00:12 time: 0.2237 data_time: 0.0440 memory: 1697 09/30 14:30:41 - mmengine - INFO - Epoch(val) [1][ 50/102] eta: 0:00:11 time: 0.2125 data_time: 0.0404 memory: 1697 09/30 14:30:42 - mmengine - INFO - Epoch(val) [1][ 55/102] eta: 0:00:09 time: 0.1112 data_time: 0.0072 memory: 1697 09/30 14:30:42 - mmengine - INFO - Epoch(val) [1][ 60/102] eta: 0:00:08 time: 0.1115 data_time: 0.0074 memory: 1697 09/30 14:30:43 - mmengine - INFO - Epoch(val) [1][ 65/102] eta: 0:00:07 time: 0.1118 data_time: 0.0077 memory: 1697 09/30 14:30:43 - mmengine - INFO - Epoch(val) [1][ 70/102] eta: 0:00:05 time: 0.1118 data_time: 0.0078 memory: 1697 09/30 14:30:44 - mmengine - INFO - Epoch(val) [1][ 75/102] eta: 0:00:04 time: 0.1116 data_time: 0.0077 memory: 1697 09/30 14:30:45 - mmengine - INFO - Epoch(val) [1][ 80/102] eta: 0:00:03 time: 0.1116 data_time: 0.0076 memory: 1697 09/30 14:30:45 - mmengine - INFO - Epoch(val) [1][ 85/102] eta: 0:00:02 time: 0.1117 data_time: 0.0078 memory: 1697 09/30 14:30:46 - mmengine - INFO - Epoch(val) [1][ 90/102] eta: 0:00:02 time: 0.1114 data_time: 0.0077 memory: 1697 09/30 14:30:46 - mmengine - INFO - Epoch(val) [1][ 95/102] eta: 0:00:01 time: 0.1114 data_time: 0.0078 memory: 1697 09/30 14:30:47 - mmengine - INFO - Epoch(val) [1][100/102] eta: 0:00:00 time: 0.1111 data_time: 0.0077 memory: 1697 09/30 14:30:47 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:30:47 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:30:47 - mmengine - INFO - Epoch(val) [1][102/102] data_time: 0.0237 time: 0.1608 09/30 14:30:47 - mmengine - WARNING - Since `metrics` is an empty dict, the behavior to save the best checkpoint will be skipped in this evaluation. /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:30:50 - mmengine - INFO - Epoch(train) [2][ 5/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:18:37 time: 0.4478 data_time: 0.0370 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:52 - mmengine - INFO - Epoch(train) [2][10/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:17:00 time: 0.4439 data_time: 0.0367 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:53 - mmengine - INFO - Epoch(train) [2][15/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:15:52 time: 0.4467 data_time: 0.0363 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:55 - mmengine - INFO - Epoch(train) [2][20/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:14:23 time: 0.4419 data_time: 0.0362 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:56 - mmengine - INFO - Epoch(train) [2][25/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:12:58 time: 0.4365 data_time: 0.0360 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:58 - mmengine - INFO - Epoch(train) [2][30/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:11:50 time: 0.4326 data_time: 0.0361 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:30:59 - mmengine - INFO - Epoch(train) [2][35/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:10:50 time: 0.4315 data_time: 0.0361 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:00 - mmengine - INFO - Epoch(train) [2][40/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:09:40 time: 0.4272 data_time: 0.0361 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:02 - mmengine - INFO - Epoch(train) [2][45/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:08:39 time: 0.4253 data_time: 0.0360 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:03 - mmengine - INFO - Epoch(train) [2][50/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:07:42 time: 0.3253 data_time: 0.0362 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:05 - mmengine - INFO - Epoch(train) [2][55/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:06:53 time: 0.2887 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:06 - mmengine - INFO - Epoch(train) [2][60/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:06:04 time: 0.2868 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:07 - mmengine - INFO - Epoch(train) [2][65/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:05:19 time: 0.2805 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:09 - mmengine - INFO - Epoch(train) [2][70/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:04:32 time: 0.2792 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:10 - mmengine - INFO - Epoch(train) [2][75/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:03:53 time: 0.2806 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:12 - mmengine - INFO - Epoch(train) [2][80/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:03:12 time: 0.2780 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:13 - mmengine - INFO - Epoch(train) [2][85/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:02:34 time: 0.2748 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:14 - mmengine - INFO - Epoch(train) [2][90/94] base_lr: 5.0050e-03 lr: 5.0050e-03 eta: 1:01:53 time: 0.2736 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:15 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:31:15 - mmengine - INFO - Saving checkpoint at 2 epochs 09/30 14:31:18 - mmengine - INFO - Epoch(val) [2][ 5/102] eta: 0:00:26 time: 0.1269 data_time: 0.0235 memory: 11783 09/30 14:31:18 - mmengine - INFO - Epoch(val) [2][ 10/102] eta: 0:00:17 time: 0.1266 data_time: 0.0232 memory: 1697 09/30 14:31:19 - mmengine - INFO - Epoch(val) [2][ 15/102] eta: 0:00:14 time: 0.1262 data_time: 0.0228 memory: 1697 09/30 14:31:19 - mmengine - INFO - Epoch(val) [2][ 20/102] eta: 0:00:12 time: 0.1261 data_time: 0.0228 memory: 1697 09/30 14:31:20 - mmengine - INFO - Epoch(val) [2][ 25/102] eta: 0:00:10 time: 0.1258 data_time: 0.0227 memory: 1697 09/30 14:31:20 - mmengine - INFO - Epoch(val) [2][ 30/102] eta: 0:00:09 time: 0.1258 data_time: 0.0228 memory: 1697 09/30 14:31:21 - mmengine - INFO - Epoch(val) [2][ 35/102] eta: 0:00:08 time: 0.1255 data_time: 0.0225 memory: 1697 09/30 14:31:22 - mmengine - INFO - Epoch(val) [2][ 40/102] eta: 0:00:08 time: 0.1259 data_time: 0.0227 memory: 1697 09/30 14:31:22 - mmengine - INFO - Epoch(val) [2][ 45/102] eta: 0:00:07 time: 0.1260 data_time: 0.0227 memory: 1697 09/30 14:31:23 - mmengine - INFO - Epoch(val) [2][ 50/102] eta: 0:00:06 time: 0.1261 data_time: 0.0227 memory: 1697 09/30 14:31:23 - mmengine - INFO - Epoch(val) [2][ 55/102] eta: 0:00:05 time: 0.1102 data_time: 0.0069 memory: 1697 09/30 14:31:24 - mmengine - INFO - Epoch(val) [2][ 60/102] eta: 0:00:05 time: 0.1103 data_time: 0.0072 memory: 1697 09/30 14:31:24 - mmengine - INFO - Epoch(val) [2][ 65/102] eta: 0:00:04 time: 0.1108 data_time: 0.0076 memory: 1697 09/30 14:31:25 - mmengine - INFO - Epoch(val) [2][ 70/102] eta: 0:00:03 time: 0.1106 data_time: 0.0076 memory: 1697 09/30 14:31:25 - mmengine - INFO - Epoch(val) [2][ 75/102] eta: 0:00:03 time: 0.1110 data_time: 0.0078 memory: 1697 09/30 14:31:26 - mmengine - INFO - Epoch(val) [2][ 80/102] eta: 0:00:02 time: 0.1110 data_time: 0.0076 memory: 1697 09/30 14:31:27 - mmengine - INFO - Epoch(val) [2][ 85/102] eta: 0:00:02 time: 0.1111 data_time: 0.0078 memory: 1697 09/30 14:31:27 - mmengine - INFO - Epoch(val) [2][ 90/102] eta: 0:00:01 time: 0.1108 data_time: 0.0077 memory: 1697 09/30 14:31:28 - mmengine - INFO - Epoch(val) [2][ 95/102] eta: 0:00:00 time: 0.1108 data_time: 0.0078 memory: 1697 09/30 14:31:28 - mmengine - INFO - Epoch(val) [2][100/102] eta: 0:00:00 time: 0.1103 data_time: 0.0075 memory: 1697 09/30 14:31:28 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:31:28 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:31:28 - mmengine - INFO - Epoch(val) [2][102/102] data_time: 0.0149 time: 0.1179 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:31:30 - mmengine - INFO - Epoch(train) [3][ 5/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 1:01:20 time: 0.2841 data_time: 0.0248 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:32 - mmengine - INFO - Epoch(train) [3][10/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 1:00:47 time: 0.2821 data_time: 0.0246 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:33 - mmengine - INFO - Epoch(train) [3][15/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 1:00:14 time: 0.2804 data_time: 0.0247 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:34 - mmengine - INFO - Epoch(train) [3][20/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:59:44 time: 0.2790 data_time: 0.0245 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:36 - mmengine - INFO - Epoch(train) [3][25/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:59:17 time: 0.2797 data_time: 0.0243 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:37 - mmengine - INFO - Epoch(train) [3][30/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:58:55 time: 0.2806 data_time: 0.0243 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:39 - mmengine - INFO - Epoch(train) [3][35/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:58:29 time: 0.2801 data_time: 0.0241 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:40 - mmengine - INFO - Epoch(train) [3][40/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:58:06 time: 0.2809 data_time: 0.0243 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:41 - mmengine - INFO - Epoch(train) [3][45/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:57:42 time: 0.2822 data_time: 0.0244 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:43 - mmengine - INFO - Epoch(train) [3][50/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:57:21 time: 0.2863 data_time: 0.0246 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:44 - mmengine - INFO - Epoch(train) [3][55/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:56:58 time: 0.2714 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:45 - mmengine - INFO - Epoch(train) [3][60/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:56:36 time: 0.2712 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:47 - mmengine - INFO - Epoch(train) [3][65/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:56:15 time: 0.2716 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:48 - mmengine - INFO - Epoch(train) [3][70/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:55:54 time: 0.2711 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:49 - mmengine - INFO - Epoch(train) [3][75/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:55:35 time: 0.2706 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:51 - mmengine - INFO - Epoch(train) [3][80/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:55:16 time: 0.2682 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:52 - mmengine - INFO - Epoch(train) [3][85/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:54:56 time: 0.2665 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:53 - mmengine - INFO - Epoch(train) [3][90/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:54:36 time: 0.2635 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:31:54 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:31:54 - mmengine - INFO - Saving checkpoint at 3 epochs 09/30 14:31:57 - mmengine - INFO - Epoch(val) [3][ 5/102] eta: 0:00:26 time: 0.1262 data_time: 0.0235 memory: 11783 09/30 14:31:58 - mmengine - INFO - Epoch(val) [3][ 10/102] eta: 0:00:17 time: 0.1260 data_time: 0.0232 memory: 1697 09/30 14:31:58 - mmengine - INFO - Epoch(val) [3][ 15/102] eta: 0:00:14 time: 0.1258 data_time: 0.0230 memory: 1697 09/30 14:31:59 - mmengine - INFO - Epoch(val) [3][ 20/102] eta: 0:00:12 time: 0.1259 data_time: 0.0228 memory: 1697 09/30 14:31:59 - mmengine - INFO - Epoch(val) [3][ 25/102] eta: 0:00:10 time: 0.1257 data_time: 0.0227 memory: 1697 09/30 14:32:00 - mmengine - INFO - Epoch(val) [3][ 30/102] eta: 0:00:09 time: 0.1257 data_time: 0.0229 memory: 1697 09/30 14:32:01 - mmengine - INFO - Epoch(val) [3][ 35/102] eta: 0:00:08 time: 0.1254 data_time: 0.0226 memory: 1697 09/30 14:32:01 - mmengine - INFO - Epoch(val) [3][ 40/102] eta: 0:00:08 time: 0.1256 data_time: 0.0227 memory: 1697 09/30 14:32:02 - mmengine - INFO - Epoch(val) [3][ 45/102] eta: 0:00:07 time: 0.1258 data_time: 0.0227 memory: 1697 09/30 14:32:02 - mmengine - INFO - Epoch(val) [3][ 50/102] eta: 0:00:06 time: 0.1261 data_time: 0.0228 memory: 1697 09/30 14:32:03 - mmengine - INFO - Epoch(val) [3][ 55/102] eta: 0:00:05 time: 0.1099 data_time: 0.0067 memory: 1697 09/30 14:32:03 - mmengine - INFO - Epoch(val) [3][ 60/102] eta: 0:00:05 time: 0.1099 data_time: 0.0069 memory: 1697 09/30 14:32:04 - mmengine - INFO - Epoch(val) [3][ 65/102] eta: 0:00:04 time: 0.1101 data_time: 0.0071 memory: 1697 09/30 14:32:04 - mmengine - INFO - Epoch(val) [3][ 70/102] eta: 0:00:03 time: 0.1100 data_time: 0.0072 memory: 1697 09/30 14:32:05 - mmengine - INFO - Epoch(val) [3][ 75/102] eta: 0:00:03 time: 0.1100 data_time: 0.0073 memory: 1697 09/30 14:32:06 - mmengine - INFO - Epoch(val) [3][ 80/102] eta: 0:00:02 time: 0.1100 data_time: 0.0071 memory: 1697 09/30 14:32:06 - mmengine - INFO - Epoch(val) [3][ 85/102] eta: 0:00:02 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 14:32:07 - mmengine - INFO - Epoch(val) [3][ 90/102] eta: 0:00:01 time: 0.1102 data_time: 0.0072 memory: 1697 09/30 14:32:07 - mmengine - INFO - Epoch(val) [3][ 95/102] eta: 0:00:00 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 14:32:08 - mmengine - INFO - Epoch(val) [3][100/102] eta: 0:00:00 time: 0.1101 data_time: 0.0072 memory: 1697 09/30 14:32:08 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:32:08 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:32:08 - mmengine - INFO - Epoch(val) [3][102/102] data_time: 0.0148 time: 0.1178 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:32:11 - mmengine - INFO - Epoch(train) [4][ 5/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:54:57 time: 0.2959 data_time: 0.0467 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:12 - mmengine - INFO - Epoch(train) [4][10/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:54:40 time: 0.2940 data_time: 0.0467 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:14 - mmengine - INFO - Epoch(train) [4][15/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:54:22 time: 0.2937 data_time: 0.0463 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:15 - mmengine - INFO - Epoch(train) [4][20/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:54:07 time: 0.2940 data_time: 0.0460 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:16 - mmengine - INFO - Epoch(train) [4][25/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:53:53 time: 0.2950 data_time: 0.0462 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:18 - mmengine - INFO - Epoch(train) [4][30/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:53:38 time: 0.2952 data_time: 0.0464 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:19 - mmengine - INFO - Epoch(train) [4][35/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:53:24 time: 0.2948 data_time: 0.0466 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:20 - mmengine - INFO - Epoch(train) [4][40/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:53:10 time: 0.2961 data_time: 0.0467 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:22 - mmengine - INFO - Epoch(train) [4][45/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:52:56 time: 0.2977 data_time: 0.0467 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:23 - mmengine - INFO - Epoch(train) [4][50/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:52:43 time: 0.3019 data_time: 0.0469 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:24 - mmengine - INFO - Epoch(train) [4][55/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:52:30 time: 0.2659 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:26 - mmengine - INFO - Epoch(train) [4][60/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:52:18 time: 0.2666 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:27 - mmengine - INFO - Epoch(train) [4][65/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:52:06 time: 0.2676 data_time: 0.0104 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:28 - mmengine - INFO - Epoch(train) [4][70/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:51:54 time: 0.2668 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:30 - mmengine - INFO - Epoch(train) [4][75/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:51:42 time: 0.2662 data_time: 0.0104 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:31 - mmengine - INFO - Epoch(train) [4][80/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:51:30 time: 0.2652 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:32 - mmengine - INFO - Epoch(train) [4][85/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:51:17 time: 0.2641 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:34 - mmengine - INFO - Epoch(train) [4][90/94] base_lr: 1.0000e-02 lr: 1.0000e-02 eta: 0:51:06 time: 0.2637 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:34 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:32:34 - mmengine - INFO - Saving checkpoint at 4 epochs 09/30 14:32:37 - mmengine - INFO - Epoch(val) [4][ 5/102] eta: 0:00:24 time: 0.1248 data_time: 0.0218 memory: 11783 09/30 14:32:38 - mmengine - INFO - Epoch(val) [4][ 10/102] eta: 0:00:16 time: 0.1248 data_time: 0.0215 memory: 1697 09/30 14:32:38 - mmengine - INFO - Epoch(val) [4][ 15/102] eta: 0:00:13 time: 0.1245 data_time: 0.0214 memory: 1697 09/30 14:32:39 - mmengine - INFO - Epoch(val) [4][ 20/102] eta: 0:00:11 time: 0.1242 data_time: 0.0213 memory: 1697 09/30 14:32:39 - mmengine - INFO - Epoch(val) [4][ 25/102] eta: 0:00:10 time: 0.1242 data_time: 0.0212 memory: 1697 09/30 14:32:40 - mmengine - INFO - Epoch(val) [4][ 30/102] eta: 0:00:09 time: 0.1243 data_time: 0.0214 memory: 1697 09/30 14:32:41 - mmengine - INFO - Epoch(val) [4][ 35/102] eta: 0:00:08 time: 0.1241 data_time: 0.0213 memory: 1697 09/30 14:32:41 - mmengine - INFO - Epoch(val) [4][ 40/102] eta: 0:00:07 time: 0.1243 data_time: 0.0214 memory: 1697 09/30 14:32:42 - mmengine - INFO - Epoch(val) [4][ 45/102] eta: 0:00:07 time: 0.1245 data_time: 0.0215 memory: 1697 09/30 14:32:42 - mmengine - INFO - Epoch(val) [4][ 50/102] eta: 0:00:06 time: 0.1248 data_time: 0.0215 memory: 1697 09/30 14:32:43 - mmengine - INFO - Epoch(val) [4][ 55/102] eta: 0:00:05 time: 0.1102 data_time: 0.0070 memory: 1697 09/30 14:32:43 - mmengine - INFO - Epoch(val) [4][ 60/102] eta: 0:00:05 time: 0.1103 data_time: 0.0072 memory: 1697 09/30 14:32:44 - mmengine - INFO - Epoch(val) [4][ 65/102] eta: 0:00:04 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 14:32:44 - mmengine - INFO - Epoch(val) [4][ 70/102] eta: 0:00:03 time: 0.1110 data_time: 0.0075 memory: 1697 09/30 14:32:45 - mmengine - INFO - Epoch(val) [4][ 75/102] eta: 0:00:03 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:32:46 - mmengine - INFO - Epoch(val) [4][ 80/102] eta: 0:00:02 time: 0.1111 data_time: 0.0076 memory: 1697 09/30 14:32:46 - mmengine - INFO - Epoch(val) [4][ 85/102] eta: 0:00:02 time: 0.1112 data_time: 0.0077 memory: 1697 09/30 14:32:47 - mmengine - INFO - Epoch(val) [4][ 90/102] eta: 0:00:01 time: 0.1112 data_time: 0.0077 memory: 1697 09/30 14:32:47 - mmengine - INFO - Epoch(val) [4][ 95/102] eta: 0:00:00 time: 0.1112 data_time: 0.0077 memory: 1697 09/30 14:32:48 - mmengine - INFO - Epoch(val) [4][100/102] eta: 0:00:00 time: 0.1109 data_time: 0.0076 memory: 1697 09/30 14:32:48 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:32:48 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:32:48 - mmengine - INFO - Epoch(val) [4][102/102] data_time: 0.0144 time: 0.1177 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:32:50 - mmengine - INFO - Epoch(train) [5][ 5/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:50:59 time: 0.2739 data_time: 0.0235 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:51 - mmengine - INFO - Epoch(train) [5][10/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:50:48 time: 0.2735 data_time: 0.0233 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:53 - mmengine - INFO - Epoch(train) [5][15/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:50:37 time: 0.2725 data_time: 0.0230 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:54 - mmengine - INFO - Epoch(train) [5][20/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:50:28 time: 0.2722 data_time: 0.0232 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:55 - mmengine - INFO - Epoch(train) [5][25/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:50:19 time: 0.2731 data_time: 0.0233 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:57 - mmengine - INFO - Epoch(train) [5][30/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:50:10 time: 0.2740 data_time: 0.0232 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:58 - mmengine - INFO - Epoch(train) [5][35/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:50:00 time: 0.2739 data_time: 0.0234 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:32:59 - mmengine - INFO - Epoch(train) [5][40/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:49:51 time: 0.2751 data_time: 0.0233 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:01 - mmengine - INFO - Epoch(train) [5][45/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:49:43 time: 0.2766 data_time: 0.0234 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:02 - mmengine - INFO - Epoch(train) [5][50/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:49:34 time: 0.2796 data_time: 0.0233 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:03 - mmengine - INFO - Epoch(train) [5][55/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:49:25 time: 0.2652 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:05 - mmengine - INFO - Epoch(train) [5][60/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:49:17 time: 0.2659 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:06 - mmengine - INFO - Epoch(train) [5][65/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:49:08 time: 0.2660 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:07 - mmengine - INFO - Epoch(train) [5][70/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:49:01 time: 0.2663 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:09 - mmengine - INFO - Epoch(train) [5][75/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:48:54 time: 0.2673 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:10 - mmengine - INFO - Epoch(train) [5][80/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:48:47 time: 0.2671 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:11 - mmengine - INFO - Epoch(train) [5][85/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:48:38 time: 0.2659 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:13 - mmengine - INFO - Epoch(train) [5][90/94] base_lr: 9.8969e-03 lr: 9.8969e-03 eta: 0:48:30 time: 0.2652 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:13 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:33:13 - mmengine - INFO - Saving checkpoint at 5 epochs 09/30 14:33:16 - mmengine - INFO - Epoch(val) [5][ 5/102] eta: 0:00:24 time: 0.1253 data_time: 0.0220 memory: 11783 09/30 14:33:16 - mmengine - INFO - Epoch(val) [5][ 10/102] eta: 0:00:16 time: 0.1251 data_time: 0.0217 memory: 1697 09/30 14:33:17 - mmengine - INFO - Epoch(val) [5][ 15/102] eta: 0:00:13 time: 0.1249 data_time: 0.0214 memory: 1697 09/30 14:33:18 - mmengine - INFO - Epoch(val) [5][ 20/102] eta: 0:00:11 time: 0.1247 data_time: 0.0214 memory: 1697 09/30 14:33:18 - mmengine - INFO - Epoch(val) [5][ 25/102] eta: 0:00:10 time: 0.1245 data_time: 0.0212 memory: 1697 09/30 14:33:19 - mmengine - INFO - Epoch(val) [5][ 30/102] eta: 0:00:09 time: 0.1245 data_time: 0.0213 memory: 1697 09/30 14:33:19 - mmengine - INFO - Epoch(val) [5][ 35/102] eta: 0:00:08 time: 0.1243 data_time: 0.0212 memory: 1697 09/30 14:33:20 - mmengine - INFO - Epoch(val) [5][ 40/102] eta: 0:00:07 time: 0.1248 data_time: 0.0213 memory: 1697 09/30 14:33:20 - mmengine - INFO - Epoch(val) [5][ 45/102] eta: 0:00:07 time: 0.1248 data_time: 0.0214 memory: 1697 09/30 14:33:21 - mmengine - INFO - Epoch(val) [5][ 50/102] eta: 0:00:06 time: 0.1248 data_time: 0.0214 memory: 1697 09/30 14:33:21 - mmengine - INFO - Epoch(val) [5][ 55/102] eta: 0:00:05 time: 0.1104 data_time: 0.0070 memory: 1697 09/30 14:33:22 - mmengine - INFO - Epoch(val) [5][ 60/102] eta: 0:00:05 time: 0.1106 data_time: 0.0073 memory: 1697 09/30 14:33:23 - mmengine - INFO - Epoch(val) [5][ 65/102] eta: 0:00:04 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:33:23 - mmengine - INFO - Epoch(val) [5][ 70/102] eta: 0:00:03 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:33:24 - mmengine - INFO - Epoch(val) [5][ 75/102] eta: 0:00:03 time: 0.1112 data_time: 0.0078 memory: 1697 09/30 14:33:24 - mmengine - INFO - Epoch(val) [5][ 80/102] eta: 0:00:02 time: 0.1111 data_time: 0.0077 memory: 1697 09/30 14:33:25 - mmengine - INFO - Epoch(val) [5][ 85/102] eta: 0:00:02 time: 0.1111 data_time: 0.0078 memory: 1697 09/30 14:33:25 - mmengine - INFO - Epoch(val) [5][ 90/102] eta: 0:00:01 time: 0.1107 data_time: 0.0078 memory: 1697 09/30 14:33:26 - mmengine - INFO - Epoch(val) [5][ 95/102] eta: 0:00:00 time: 0.1106 data_time: 0.0078 memory: 1697 09/30 14:33:26 - mmengine - INFO - Epoch(val) [5][100/102] eta: 0:00:00 time: 0.1108 data_time: 0.0076 memory: 1697 09/30 14:33:27 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:33:27 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:33:27 - mmengine - INFO - Epoch(val) [5][102/102] data_time: 0.0143 time: 0.1175 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:33:29 - mmengine - INFO - Epoch(train) [6][ 5/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:48:34 time: 0.2832 data_time: 0.0302 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:30 - mmengine - INFO - Epoch(train) [6][10/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:48:27 time: 0.2848 data_time: 0.0318 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:32 - mmengine - INFO - Epoch(train) [6][15/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:48:20 time: 0.2850 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:33 - mmengine - INFO - Epoch(train) [6][20/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:48:13 time: 0.2845 data_time: 0.0316 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:34 - mmengine - INFO - Epoch(train) [6][25/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:48:06 time: 0.2837 data_time: 0.0313 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:36 - mmengine - INFO - Epoch(train) [6][30/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:59 time: 0.2825 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:37 - mmengine - INFO - Epoch(train) [6][35/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:52 time: 0.2814 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:38 - mmengine - INFO - Epoch(train) [6][40/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:45 time: 0.2830 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:40 - mmengine - INFO - Epoch(train) [6][45/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:39 time: 0.2839 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:41 - mmengine - INFO - Epoch(train) [6][50/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:32 time: 0.2875 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:42 - mmengine - INFO - Epoch(train) [6][55/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:26 time: 0.2655 data_time: 0.0109 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:44 - mmengine - INFO - Epoch(train) [6][60/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:20 time: 0.2647 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:45 - mmengine - INFO - Epoch(train) [6][65/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:14 time: 0.2646 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:46 - mmengine - INFO - Epoch(train) [6][70/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:08 time: 0.2650 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:48 - mmengine - INFO - Epoch(train) [6][75/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:47:02 time: 0.2653 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:49 - mmengine - INFO - Epoch(train) [6][80/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:46:56 time: 0.2653 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:50 - mmengine - INFO - Epoch(train) [6][85/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:46:49 time: 0.2642 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:52 - mmengine - INFO - Epoch(train) [6][90/94] base_lr: 9.7938e-03 lr: 9.7938e-03 eta: 0:46:42 time: 0.2627 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:33:52 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:33:52 - mmengine - INFO - Saving checkpoint at 6 epochs 09/30 14:33:55 - mmengine - INFO - Epoch(val) [6][ 5/102] eta: 0:00:25 time: 0.1260 data_time: 0.0227 memory: 11783 09/30 14:33:56 - mmengine - INFO - Epoch(val) [6][ 10/102] eta: 0:00:17 time: 0.1260 data_time: 0.0225 memory: 1697 09/30 14:33:56 - mmengine - INFO - Epoch(val) [6][ 15/102] eta: 0:00:14 time: 0.1257 data_time: 0.0221 memory: 1697 09/30 14:33:57 - mmengine - INFO - Epoch(val) [6][ 20/102] eta: 0:00:12 time: 0.1257 data_time: 0.0221 memory: 1697 09/30 14:33:57 - mmengine - INFO - Epoch(val) [6][ 25/102] eta: 0:00:10 time: 0.1256 data_time: 0.0220 memory: 1697 09/30 14:33:58 - mmengine - INFO - Epoch(val) [6][ 30/102] eta: 0:00:09 time: 0.1258 data_time: 0.0221 memory: 1697 09/30 14:33:59 - mmengine - INFO - Epoch(val) [6][ 35/102] eta: 0:00:08 time: 0.1259 data_time: 0.0219 memory: 1697 09/30 14:33:59 - mmengine - INFO - Epoch(val) [6][ 40/102] eta: 0:00:08 time: 0.1262 data_time: 0.0220 memory: 1697 09/30 14:34:00 - mmengine - INFO - Epoch(val) [6][ 45/102] eta: 0:00:07 time: 0.1260 data_time: 0.0221 memory: 1697 09/30 14:34:00 - mmengine - INFO - Epoch(val) [6][ 50/102] eta: 0:00:06 time: 0.1260 data_time: 0.0221 memory: 1697 09/30 14:34:01 - mmengine - INFO - Epoch(val) [6][ 55/102] eta: 0:00:05 time: 0.1106 data_time: 0.0070 memory: 1697 09/30 14:34:01 - mmengine - INFO - Epoch(val) [6][ 60/102] eta: 0:00:05 time: 0.1107 data_time: 0.0073 memory: 1697 09/30 14:34:02 - mmengine - INFO - Epoch(val) [6][ 65/102] eta: 0:00:04 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:34:02 - mmengine - INFO - Epoch(val) [6][ 70/102] eta: 0:00:03 time: 0.1112 data_time: 0.0077 memory: 1697 09/30 14:34:03 - mmengine - INFO - Epoch(val) [6][ 75/102] eta: 0:00:03 time: 0.1114 data_time: 0.0078 memory: 1697 09/30 14:34:04 - mmengine - INFO - Epoch(val) [6][ 80/102] eta: 0:00:02 time: 0.1112 data_time: 0.0077 memory: 1697 09/30 14:34:04 - mmengine - INFO - Epoch(val) [6][ 85/102] eta: 0:00:02 time: 0.1112 data_time: 0.0078 memory: 1697 09/30 14:34:05 - mmengine - INFO - Epoch(val) [6][ 90/102] eta: 0:00:01 time: 0.1111 data_time: 0.0078 memory: 1697 09/30 14:34:05 - mmengine - INFO - Epoch(val) [6][ 95/102] eta: 0:00:00 time: 0.1112 data_time: 0.0079 memory: 1697 09/30 14:34:06 - mmengine - INFO - Epoch(val) [6][100/102] eta: 0:00:00 time: 0.1112 data_time: 0.0078 memory: 1697 09/30 14:34:06 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:34:06 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:34:06 - mmengine - INFO - Epoch(val) [6][102/102] data_time: 0.0147 time: 0.1183 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:34:09 - mmengine - INFO - Epoch(train) [7][ 5/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:50 time: 0.2864 data_time: 0.0368 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:10 - mmengine - INFO - Epoch(train) [7][10/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:45 time: 0.2873 data_time: 0.0373 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:11 - mmengine - INFO - Epoch(train) [7][15/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:39 time: 0.2863 data_time: 0.0366 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:13 - mmengine - INFO - Epoch(train) [7][20/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:34 time: 0.2870 data_time: 0.0366 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:14 - mmengine - INFO - Epoch(train) [7][25/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:28 time: 0.2864 data_time: 0.0364 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:15 - mmengine - INFO - Epoch(train) [7][30/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:23 time: 0.2866 data_time: 0.0364 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:17 - mmengine - INFO - Epoch(train) [7][35/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:18 time: 0.2865 data_time: 0.0365 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:18 - mmengine - INFO - Epoch(train) [7][40/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:12 time: 0.2874 data_time: 0.0363 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:19 - mmengine - INFO - Epoch(train) [7][45/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:07 time: 0.2888 data_time: 0.0365 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:21 - mmengine - INFO - Epoch(train) [7][50/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:46:02 time: 0.2925 data_time: 0.0368 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:22 - mmengine - INFO - Epoch(train) [7][55/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:45:57 time: 0.2660 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:23 - mmengine - INFO - Epoch(train) [7][60/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:45:52 time: 0.2651 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:25 - mmengine - INFO - Epoch(train) [7][65/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:45:47 time: 0.2661 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:26 - mmengine - INFO - Epoch(train) [7][70/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:45:43 time: 0.2651 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:27 - mmengine - INFO - Epoch(train) [7][75/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:45:38 time: 0.2667 data_time: 0.0109 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:29 - mmengine - INFO - Epoch(train) [7][80/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:45:33 time: 0.2662 data_time: 0.0109 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:30 - mmengine - INFO - Epoch(train) [7][85/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:45:28 time: 0.2648 data_time: 0.0106 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:31 - mmengine - INFO - Epoch(train) [7][90/94] base_lr: 9.6906e-03 lr: 9.6906e-03 eta: 0:45:22 time: 0.2633 data_time: 0.0106 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:32 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:34:32 - mmengine - INFO - Saving checkpoint at 7 epochs 09/30 14:34:35 - mmengine - INFO - Epoch(val) [7][ 5/102] eta: 0:00:26 time: 0.1273 data_time: 0.0237 memory: 11783 09/30 14:34:36 - mmengine - INFO - Epoch(val) [7][ 10/102] eta: 0:00:17 time: 0.1270 data_time: 0.0234 memory: 1697 09/30 14:34:36 - mmengine - INFO - Epoch(val) [7][ 15/102] eta: 0:00:14 time: 0.1266 data_time: 0.0231 memory: 1697 09/30 14:34:37 - mmengine - INFO - Epoch(val) [7][ 20/102] eta: 0:00:12 time: 0.1261 data_time: 0.0229 memory: 1697 09/30 14:34:37 - mmengine - INFO - Epoch(val) [7][ 25/102] eta: 0:00:10 time: 0.1260 data_time: 0.0228 memory: 1697 09/30 14:34:38 - mmengine - INFO - Epoch(val) [7][ 30/102] eta: 0:00:09 time: 0.1257 data_time: 0.0227 memory: 1697 09/30 14:34:38 - mmengine - INFO - Epoch(val) [7][ 35/102] eta: 0:00:08 time: 0.1255 data_time: 0.0224 memory: 1697 09/30 14:34:39 - mmengine - INFO - Epoch(val) [7][ 40/102] eta: 0:00:08 time: 0.1255 data_time: 0.0224 memory: 1697 09/30 14:34:40 - mmengine - INFO - Epoch(val) [7][ 45/102] eta: 0:00:07 time: 0.1256 data_time: 0.0225 memory: 1697 09/30 14:34:40 - mmengine - INFO - Epoch(val) [7][ 50/102] eta: 0:00:06 time: 0.1258 data_time: 0.0226 memory: 1697 09/30 14:34:41 - mmengine - INFO - Epoch(val) [7][ 55/102] eta: 0:00:05 time: 0.1097 data_time: 0.0066 memory: 1697 09/30 14:34:41 - mmengine - INFO - Epoch(val) [7][ 60/102] eta: 0:00:05 time: 0.1098 data_time: 0.0069 memory: 1697 09/30 14:34:42 - mmengine - INFO - Epoch(val) [7][ 65/102] eta: 0:00:04 time: 0.1101 data_time: 0.0071 memory: 1697 09/30 14:34:42 - mmengine - INFO - Epoch(val) [7][ 70/102] eta: 0:00:03 time: 0.1102 data_time: 0.0072 memory: 1697 09/30 14:34:43 - mmengine - INFO - Epoch(val) [7][ 75/102] eta: 0:00:03 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 14:34:43 - mmengine - INFO - Epoch(val) [7][ 80/102] eta: 0:00:02 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 14:34:44 - mmengine - INFO - Epoch(val) [7][ 85/102] eta: 0:00:02 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 14:34:45 - mmengine - INFO - Epoch(val) [7][ 90/102] eta: 0:00:01 time: 0.1105 data_time: 0.0073 memory: 1697 09/30 14:34:45 - mmengine - INFO - Epoch(val) [7][ 95/102] eta: 0:00:00 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 14:34:46 - mmengine - INFO - Epoch(val) [7][100/102] eta: 0:00:00 time: 0.1100 data_time: 0.0071 memory: 1697 09/30 14:34:46 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:34:46 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:34:46 - mmengine - INFO - Epoch(val) [7][102/102] data_time: 0.0146 time: 0.1177 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:34:49 - mmengine - INFO - Epoch(train) [8][ 5/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:45:32 time: 0.2923 data_time: 0.0430 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:50 - mmengine - INFO - Epoch(train) [8][10/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:45:28 time: 0.2924 data_time: 0.0428 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:51 - mmengine - INFO - Epoch(train) [8][15/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:45:23 time: 0.2915 data_time: 0.0421 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:53 - mmengine - INFO - Epoch(train) [8][20/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:45:19 time: 0.2914 data_time: 0.0420 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:54 - mmengine - INFO - Epoch(train) [8][25/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:45:14 time: 0.2912 data_time: 0.0416 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:55 - mmengine - INFO - Epoch(train) [8][30/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:45:10 time: 0.2910 data_time: 0.0411 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:57 - mmengine - INFO - Epoch(train) [8][35/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:45:06 time: 0.2912 data_time: 0.0415 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:58 - mmengine - INFO - Epoch(train) [8][40/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:45:01 time: 0.2926 data_time: 0.0415 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:34:59 - mmengine - INFO - Epoch(train) [8][45/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:57 time: 0.2943 data_time: 0.0416 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:01 - mmengine - INFO - Epoch(train) [8][50/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:52 time: 0.2982 data_time: 0.0418 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:02 - mmengine - INFO - Epoch(train) [8][55/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:48 time: 0.2658 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:03 - mmengine - INFO - Epoch(train) [8][60/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:44 time: 0.2647 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:05 - mmengine - INFO - Epoch(train) [8][65/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:40 time: 0.2658 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:06 - mmengine - INFO - Epoch(train) [8][70/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:36 time: 0.2660 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:07 - mmengine - INFO - Epoch(train) [8][75/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:32 time: 0.2659 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:09 - mmengine - INFO - Epoch(train) [8][80/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:27 time: 0.2653 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:10 - mmengine - INFO - Epoch(train) [8][85/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:23 time: 0.2635 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:11 - mmengine - INFO - Epoch(train) [8][90/94] base_lr: 9.5875e-03 lr: 9.5875e-03 eta: 0:44:18 time: 0.2620 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:12 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:35:12 - mmengine - INFO - Saving checkpoint at 8 epochs 09/30 14:35:15 - mmengine - INFO - Epoch(val) [8][ 5/102] eta: 0:00:25 time: 0.1247 data_time: 0.0217 memory: 11783 09/30 14:35:15 - mmengine - INFO - Epoch(val) [8][ 10/102] eta: 0:00:16 time: 0.1245 data_time: 0.0214 memory: 1697 09/30 14:35:16 - mmengine - INFO - Epoch(val) [8][ 15/102] eta: 0:00:13 time: 0.1243 data_time: 0.0211 memory: 1697 09/30 14:35:16 - mmengine - INFO - Epoch(val) [8][ 20/102] eta: 0:00:11 time: 0.1242 data_time: 0.0211 memory: 1697 09/30 14:35:17 - mmengine - INFO - Epoch(val) [8][ 25/102] eta: 0:00:10 time: 0.1240 data_time: 0.0210 memory: 1697 09/30 14:35:17 - mmengine - INFO - Epoch(val) [8][ 30/102] eta: 0:00:09 time: 0.1243 data_time: 0.0212 memory: 1697 09/30 14:35:18 - mmengine - INFO - Epoch(val) [8][ 35/102] eta: 0:00:08 time: 0.1241 data_time: 0.0211 memory: 1697 09/30 14:35:19 - mmengine - INFO - Epoch(val) [8][ 40/102] eta: 0:00:07 time: 0.1244 data_time: 0.0213 memory: 1697 09/30 14:35:19 - mmengine - INFO - Epoch(val) [8][ 45/102] eta: 0:00:07 time: 0.1246 data_time: 0.0214 memory: 1697 09/30 14:35:20 - mmengine - INFO - Epoch(val) [8][ 50/102] eta: 0:00:06 time: 0.1248 data_time: 0.0215 memory: 1697 09/30 14:35:20 - mmengine - INFO - Epoch(val) [8][ 55/102] eta: 0:00:05 time: 0.1101 data_time: 0.0069 memory: 1697 09/30 14:35:21 - mmengine - INFO - Epoch(val) [8][ 60/102] eta: 0:00:05 time: 0.1102 data_time: 0.0072 memory: 1697 09/30 14:35:21 - mmengine - INFO - Epoch(val) [8][ 65/102] eta: 0:00:04 time: 0.1104 data_time: 0.0076 memory: 1697 09/30 14:35:22 - mmengine - INFO - Epoch(val) [8][ 70/102] eta: 0:00:03 time: 0.1104 data_time: 0.0076 memory: 1697 09/30 14:35:22 - mmengine - INFO - Epoch(val) [8][ 75/102] eta: 0:00:03 time: 0.1105 data_time: 0.0076 memory: 1697 09/30 14:35:23 - mmengine - INFO - Epoch(val) [8][ 80/102] eta: 0:00:02 time: 0.1104 data_time: 0.0075 memory: 1697 09/30 14:35:23 - mmengine - INFO - Epoch(val) [8][ 85/102] eta: 0:00:02 time: 0.1106 data_time: 0.0076 memory: 1697 09/30 14:35:24 - mmengine - INFO - Epoch(val) [8][ 90/102] eta: 0:00:01 time: 0.1105 data_time: 0.0076 memory: 1697 09/30 14:35:25 - mmengine - INFO - Epoch(val) [8][ 95/102] eta: 0:00:00 time: 0.1105 data_time: 0.0076 memory: 1697 09/30 14:35:25 - mmengine - INFO - Epoch(val) [8][100/102] eta: 0:00:00 time: 0.1103 data_time: 0.0075 memory: 1697 09/30 14:35:25 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:35:25 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:35:25 - mmengine - INFO - Epoch(val) [8][102/102] data_time: 0.0143 time: 0.1173 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:35:28 - mmengine - INFO - Epoch(train) [9][ 5/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:44:27 time: 0.2915 data_time: 0.0435 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:30 - mmengine - INFO - Epoch(train) [9][10/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:44:23 time: 0.2911 data_time: 0.0429 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:31 - mmengine - INFO - Epoch(train) [9][15/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:44:19 time: 0.2912 data_time: 0.0426 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:32 - mmengine - INFO - Epoch(train) [9][20/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:44:15 time: 0.2914 data_time: 0.0425 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:34 - mmengine - INFO - Epoch(train) [9][25/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:44:11 time: 0.2907 data_time: 0.0423 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:35 - mmengine - INFO - Epoch(train) [9][30/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:44:07 time: 0.2910 data_time: 0.0424 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:36 - mmengine - INFO - Epoch(train) [9][35/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:44:04 time: 0.2912 data_time: 0.0423 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:38 - mmengine - INFO - Epoch(train) [9][40/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:44:00 time: 0.2925 data_time: 0.0423 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:39 - mmengine - INFO - Epoch(train) [9][45/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:56 time: 0.2943 data_time: 0.0422 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:40 - mmengine - INFO - Epoch(train) [9][50/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:53 time: 0.2989 data_time: 0.0426 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:42 - mmengine - INFO - Epoch(train) [9][55/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:49 time: 0.2656 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:43 - mmengine - INFO - Epoch(train) [9][60/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:46 time: 0.2669 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:44 - mmengine - INFO - Epoch(train) [9][65/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:42 time: 0.2664 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:46 - mmengine - INFO - Epoch(train) [9][70/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:38 time: 0.2664 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:47 - mmengine - INFO - Epoch(train) [9][75/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:34 time: 0.2665 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:48 - mmengine - INFO - Epoch(train) [9][80/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:31 time: 0.2659 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:50 - mmengine - INFO - Epoch(train) [9][85/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:26 time: 0.2639 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:51 - mmengine - INFO - Epoch(train) [9][90/94] base_lr: 9.4844e-03 lr: 9.4844e-03 eta: 0:43:22 time: 0.2625 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:35:52 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:35:52 - mmengine - INFO - Saving checkpoint at 9 epochs 09/30 14:35:55 - mmengine - INFO - Epoch(val) [9][ 5/102] eta: 0:00:25 time: 0.1256 data_time: 0.0230 memory: 11783 09/30 14:35:55 - mmengine - INFO - Epoch(val) [9][ 10/102] eta: 0:00:17 time: 0.1254 data_time: 0.0227 memory: 1697 09/30 14:35:56 - mmengine - INFO - Epoch(val) [9][ 15/102] eta: 0:00:13 time: 0.1253 data_time: 0.0224 memory: 1697 09/30 14:35:56 - mmengine - INFO - Epoch(val) [9][ 20/102] eta: 0:00:12 time: 0.1252 data_time: 0.0223 memory: 1697 09/30 14:35:57 - mmengine - INFO - Epoch(val) [9][ 25/102] eta: 0:00:10 time: 0.1249 data_time: 0.0222 memory: 1697 09/30 14:35:57 - mmengine - INFO - Epoch(val) [9][ 30/102] eta: 0:00:09 time: 0.1251 data_time: 0.0223 memory: 1697 09/30 14:35:58 - mmengine - INFO - Epoch(val) [9][ 35/102] eta: 0:00:08 time: 0.1248 data_time: 0.0220 memory: 1697 09/30 14:35:58 - mmengine - INFO - Epoch(val) [9][ 40/102] eta: 0:00:07 time: 0.1247 data_time: 0.0221 memory: 1697 09/30 14:35:59 - mmengine - INFO - Epoch(val) [9][ 45/102] eta: 0:00:07 time: 0.1247 data_time: 0.0221 memory: 1697 09/30 14:35:59 - mmengine - INFO - Epoch(val) [9][ 50/102] eta: 0:00:06 time: 0.1248 data_time: 0.0221 memory: 1697 09/30 14:36:00 - mmengine - INFO - Epoch(val) [9][ 55/102] eta: 0:00:05 time: 0.1092 data_time: 0.0065 memory: 1697 09/30 14:36:01 - mmengine - INFO - Epoch(val) [9][ 60/102] eta: 0:00:05 time: 0.1095 data_time: 0.0068 memory: 1697 09/30 14:36:01 - mmengine - INFO - Epoch(val) [9][ 65/102] eta: 0:00:04 time: 0.1097 data_time: 0.0072 memory: 1697 09/30 14:36:02 - mmengine - INFO - Epoch(val) [9][ 70/102] eta: 0:00:03 time: 0.1099 data_time: 0.0072 memory: 1697 09/30 14:36:02 - mmengine - INFO - Epoch(val) [9][ 75/102] eta: 0:00:03 time: 0.1102 data_time: 0.0074 memory: 1697 09/30 14:36:03 - mmengine - INFO - Epoch(val) [9][ 80/102] eta: 0:00:02 time: 0.1100 data_time: 0.0073 memory: 1697 09/30 14:36:03 - mmengine - INFO - Epoch(val) [9][ 85/102] eta: 0:00:02 time: 0.1103 data_time: 0.0075 memory: 1697 09/30 14:36:04 - mmengine - INFO - Epoch(val) [9][ 90/102] eta: 0:00:01 time: 0.1104 data_time: 0.0075 memory: 1697 09/30 14:36:04 - mmengine - INFO - Epoch(val) [9][ 95/102] eta: 0:00:00 time: 0.1107 data_time: 0.0076 memory: 1697 09/30 14:36:05 - mmengine - INFO - Epoch(val) [9][100/102] eta: 0:00:00 time: 0.1106 data_time: 0.0074 memory: 1697 09/30 14:36:05 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:36:05 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:36:05 - mmengine - INFO - Epoch(val) [9][102/102] data_time: 0.0145 time: 0.1174 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:36:07 - mmengine - INFO - Epoch(train) [10][ 5/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:43:22 time: 0.2751 data_time: 0.0259 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:09 - mmengine - INFO - Epoch(train) [10][10/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:43:19 time: 0.2751 data_time: 0.0258 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:10 - mmengine - INFO - Epoch(train) [10][15/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:43:15 time: 0.2739 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:11 - mmengine - INFO - Epoch(train) [10][20/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:43:12 time: 0.2741 data_time: 0.0259 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:13 - mmengine - INFO - Epoch(train) [10][25/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:43:08 time: 0.2736 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:14 - mmengine - INFO - Epoch(train) [10][30/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:43:05 time: 0.2737 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:15 - mmengine - INFO - Epoch(train) [10][35/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:43:01 time: 0.2741 data_time: 0.0257 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:17 - mmengine - INFO - Epoch(train) [10][40/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:58 time: 0.2749 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:18 - mmengine - INFO - Epoch(train) [10][45/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:54 time: 0.2761 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:19 - mmengine - INFO - Epoch(train) [10][50/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:51 time: 0.2800 data_time: 0.0258 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:21 - mmengine - INFO - Epoch(train) [10][55/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:48 time: 0.2634 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:22 - mmengine - INFO - Epoch(train) [10][60/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:44 time: 0.2631 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:23 - mmengine - INFO - Epoch(train) [10][65/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:41 time: 0.2640 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:25 - mmengine - INFO - Epoch(train) [10][70/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:38 time: 0.2645 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:26 - mmengine - INFO - Epoch(train) [10][75/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:35 time: 0.2645 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:27 - mmengine - INFO - Epoch(train) [10][80/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:32 time: 0.2643 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:28 - mmengine - INFO - Epoch(train) [10][85/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:28 time: 0.2630 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:30 - mmengine - INFO - Epoch(train) [10][90/94] base_lr: 9.3813e-03 lr: 9.3813e-03 eta: 0:42:24 time: 0.2621 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:31 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:36:31 - mmengine - INFO - Saving checkpoint at 10 epochs 09/30 14:36:33 - mmengine - INFO - Epoch(val) [10][ 5/102] eta: 0:00:25 time: 0.1262 data_time: 0.0231 memory: 11783 09/30 14:36:34 - mmengine - INFO - Epoch(val) [10][ 10/102] eta: 0:00:17 time: 0.1261 data_time: 0.0229 memory: 1697 09/30 14:36:34 - mmengine - INFO - Epoch(val) [10][ 15/102] eta: 0:00:13 time: 0.1255 data_time: 0.0226 memory: 1697 09/30 14:36:35 - mmengine - INFO - Epoch(val) [10][ 20/102] eta: 0:00:12 time: 0.1254 data_time: 0.0225 memory: 1697 09/30 14:36:36 - mmengine - INFO - Epoch(val) [10][ 25/102] eta: 0:00:10 time: 0.1252 data_time: 0.0224 memory: 1697 09/30 14:36:36 - mmengine - INFO - Epoch(val) [10][ 30/102] eta: 0:00:09 time: 0.1253 data_time: 0.0225 memory: 1697 09/30 14:36:37 - mmengine - INFO - Epoch(val) [10][ 35/102] eta: 0:00:08 time: 0.1249 data_time: 0.0221 memory: 1697 09/30 14:36:37 - mmengine - INFO - Epoch(val) [10][ 40/102] eta: 0:00:08 time: 0.1252 data_time: 0.0223 memory: 1697 09/30 14:36:38 - mmengine - INFO - Epoch(val) [10][ 45/102] eta: 0:00:07 time: 0.1253 data_time: 0.0224 memory: 1697 09/30 14:36:38 - mmengine - INFO - Epoch(val) [10][ 50/102] eta: 0:00:06 time: 0.1252 data_time: 0.0224 memory: 1697 09/30 14:36:39 - mmengine - INFO - Epoch(val) [10][ 55/102] eta: 0:00:05 time: 0.1093 data_time: 0.0067 memory: 1697 09/30 14:36:39 - mmengine - INFO - Epoch(val) [10][ 60/102] eta: 0:00:05 time: 0.1097 data_time: 0.0070 memory: 1697 09/30 14:36:40 - mmengine - INFO - Epoch(val) [10][ 65/102] eta: 0:00:04 time: 0.1101 data_time: 0.0072 memory: 1697 09/30 14:36:41 - mmengine - INFO - Epoch(val) [10][ 70/102] eta: 0:00:03 time: 0.1101 data_time: 0.0073 memory: 1697 09/30 14:36:41 - mmengine - INFO - Epoch(val) [10][ 75/102] eta: 0:00:03 time: 0.1101 data_time: 0.0074 memory: 1697 09/30 14:36:42 - mmengine - INFO - Epoch(val) [10][ 80/102] eta: 0:00:02 time: 0.1099 data_time: 0.0072 memory: 1697 09/30 14:36:42 - mmengine - INFO - Epoch(val) [10][ 85/102] eta: 0:00:02 time: 0.1101 data_time: 0.0074 memory: 1697 09/30 14:36:43 - mmengine - INFO - Epoch(val) [10][ 90/102] eta: 0:00:01 time: 0.1099 data_time: 0.0073 memory: 1697 09/30 14:36:43 - mmengine - INFO - Epoch(val) [10][ 95/102] eta: 0:00:00 time: 0.1098 data_time: 0.0073 memory: 1697 09/30 14:36:44 - mmengine - INFO - Epoch(val) [10][100/102] eta: 0:00:00 time: 0.1097 data_time: 0.0072 memory: 1697 09/30 14:36:44 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:36:44 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:36:44 - mmengine - INFO - Epoch(val) [10][102/102] data_time: 0.0146 time: 0.1172 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:36:47 - mmengine - INFO - Epoch(train) [11][ 5/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:31 time: 0.2891 data_time: 0.0398 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:48 - mmengine - INFO - Epoch(train) [11][10/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:28 time: 0.2903 data_time: 0.0402 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:50 - mmengine - INFO - Epoch(train) [11][15/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:25 time: 0.2899 data_time: 0.0396 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:51 - mmengine - INFO - Epoch(train) [11][20/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:21 time: 0.2894 data_time: 0.0393 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:52 - mmengine - INFO - Epoch(train) [11][25/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:18 time: 0.2889 data_time: 0.0393 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:54 - mmengine - INFO - Epoch(train) [11][30/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:15 time: 0.2896 data_time: 0.0394 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:55 - mmengine - INFO - Epoch(train) [11][35/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:13 time: 0.2901 data_time: 0.0394 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:56 - mmengine - INFO - Epoch(train) [11][40/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:10 time: 0.2916 data_time: 0.0395 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:58 - mmengine - INFO - Epoch(train) [11][45/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:07 time: 0.2928 data_time: 0.0395 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:36:59 - mmengine - INFO - Epoch(train) [11][50/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:04 time: 0.2971 data_time: 0.0398 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:00 - mmengine - INFO - Epoch(train) [11][55/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:42:01 time: 0.2668 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:02 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:37:02 - mmengine - INFO - Epoch(train) [11][60/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:41:58 time: 0.2654 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:03 - mmengine - INFO - Epoch(train) [11][65/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:41:55 time: 0.2656 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:04 - mmengine - INFO - Epoch(train) [11][70/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:41:51 time: 0.2652 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:06 - mmengine - INFO - Epoch(train) [11][75/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:41:48 time: 0.2654 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:07 - mmengine - INFO - Epoch(train) [11][80/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:41:45 time: 0.2637 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:08 - mmengine - INFO - Epoch(train) [11][85/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:41:42 time: 0.2618 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:09 - mmengine - INFO - Epoch(train) [11][90/94] base_lr: 9.2781e-03 lr: 9.2781e-03 eta: 0:41:38 time: 0.2604 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:10 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:37:10 - mmengine - INFO - Saving checkpoint at 11 epochs 09/30 14:37:13 - mmengine - INFO - Epoch(val) [11][ 5/102] eta: 0:00:25 time: 0.1247 data_time: 0.0220 memory: 11783 09/30 14:37:14 - mmengine - INFO - Epoch(val) [11][ 10/102] eta: 0:00:16 time: 0.1242 data_time: 0.0218 memory: 1697 09/30 14:37:14 - mmengine - INFO - Epoch(val) [11][ 15/102] eta: 0:00:13 time: 0.1240 data_time: 0.0214 memory: 1697 09/30 14:37:15 - mmengine - INFO - Epoch(val) [11][ 20/102] eta: 0:00:11 time: 0.1239 data_time: 0.0214 memory: 1697 09/30 14:37:15 - mmengine - INFO - Epoch(val) [11][ 25/102] eta: 0:00:10 time: 0.1238 data_time: 0.0212 memory: 1697 09/30 14:37:16 - mmengine - INFO - Epoch(val) [11][ 30/102] eta: 0:00:09 time: 0.1237 data_time: 0.0213 memory: 1697 09/30 14:37:17 - mmengine - INFO - Epoch(val) [11][ 35/102] eta: 0:00:08 time: 0.1233 data_time: 0.0210 memory: 1697 09/30 14:37:17 - mmengine - INFO - Epoch(val) [11][ 40/102] eta: 0:00:07 time: 0.1235 data_time: 0.0211 memory: 1697 09/30 14:37:18 - mmengine - INFO - Epoch(val) [11][ 45/102] eta: 0:00:07 time: 0.1234 data_time: 0.0211 memory: 1697 09/30 14:37:18 - mmengine - INFO - Epoch(val) [11][ 50/102] eta: 0:00:06 time: 0.1234 data_time: 0.0211 memory: 1697 09/30 14:37:19 - mmengine - INFO - Epoch(val) [11][ 55/102] eta: 0:00:05 time: 0.1085 data_time: 0.0063 memory: 1697 09/30 14:37:19 - mmengine - INFO - Epoch(val) [11][ 60/102] eta: 0:00:05 time: 0.1088 data_time: 0.0065 memory: 1697 09/30 14:37:20 - mmengine - INFO - Epoch(val) [11][ 65/102] eta: 0:00:04 time: 0.1090 data_time: 0.0069 memory: 1697 09/30 14:37:20 - mmengine - INFO - Epoch(val) [11][ 70/102] eta: 0:00:03 time: 0.1091 data_time: 0.0069 memory: 1697 09/30 14:37:21 - mmengine - INFO - Epoch(val) [11][ 75/102] eta: 0:00:03 time: 0.1091 data_time: 0.0070 memory: 1697 09/30 14:37:21 - mmengine - INFO - Epoch(val) [11][ 80/102] eta: 0:00:02 time: 0.1091 data_time: 0.0069 memory: 1697 09/30 14:37:22 - mmengine - INFO - Epoch(val) [11][ 85/102] eta: 0:00:01 time: 0.1091 data_time: 0.0070 memory: 1697 09/30 14:37:23 - mmengine - INFO - Epoch(val) [11][ 90/102] eta: 0:00:01 time: 0.1090 data_time: 0.0070 memory: 1697 09/30 14:37:23 - mmengine - INFO - Epoch(val) [11][ 95/102] eta: 0:00:00 time: 0.1092 data_time: 0.0071 memory: 1697 09/30 14:37:24 - mmengine - INFO - Epoch(val) [11][100/102] eta: 0:00:00 time: 0.1090 data_time: 0.0070 memory: 1697 09/30 14:37:24 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:37:24 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:37:24 - mmengine - INFO - Epoch(val) [11][102/102] data_time: 0.0139 time: 0.1160 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:37:26 - mmengine - INFO - Epoch(train) [12][ 5/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:41 time: 0.2798 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:28 - mmengine - INFO - Epoch(train) [12][10/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:38 time: 0.2791 data_time: 0.0319 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:29 - mmengine - INFO - Epoch(train) [12][15/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:35 time: 0.2798 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:30 - mmengine - INFO - Epoch(train) [12][20/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:32 time: 0.2797 data_time: 0.0320 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:32 - mmengine - INFO - Epoch(train) [12][25/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:31 time: 0.2839 data_time: 0.0317 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:33 - mmengine - INFO - Epoch(train) [12][30/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:28 time: 0.2831 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:34 - mmengine - INFO - Epoch(train) [12][35/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:25 time: 0.2847 data_time: 0.0316 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:36 - mmengine - INFO - Epoch(train) [12][40/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:23 time: 0.2862 data_time: 0.0319 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:37 - mmengine - INFO - Epoch(train) [12][45/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:20 time: 0.2877 data_time: 0.0317 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:38 - mmengine - INFO - Epoch(train) [12][50/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:17 time: 0.2921 data_time: 0.0319 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:40 - mmengine - INFO - Epoch(train) [12][55/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:14 time: 0.2682 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:41 - mmengine - INFO - Epoch(train) [12][60/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:11 time: 0.2684 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:42 - mmengine - INFO - Epoch(train) [12][65/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:09 time: 0.2678 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:44 - mmengine - INFO - Epoch(train) [12][70/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:06 time: 0.2681 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:45 - mmengine - INFO - Epoch(train) [12][75/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:03 time: 0.2651 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:46 - mmengine - INFO - Epoch(train) [12][80/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:41:00 time: 0.2648 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:48 - mmengine - INFO - Epoch(train) [12][85/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:40:57 time: 0.2628 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:49 - mmengine - INFO - Epoch(train) [12][90/94] base_lr: 9.1750e-03 lr: 9.1750e-03 eta: 0:40:54 time: 0.2607 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:37:50 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:37:50 - mmengine - INFO - Saving checkpoint at 12 epochs 09/30 14:37:52 - mmengine - INFO - Epoch(val) [12][ 5/102] eta: 0:00:24 time: 0.1232 data_time: 0.0213 memory: 11783 09/30 14:37:53 - mmengine - INFO - Epoch(val) [12][ 10/102] eta: 0:00:16 time: 0.1230 data_time: 0.0211 memory: 1697 09/30 14:37:53 - mmengine - INFO - Epoch(val) [12][ 15/102] eta: 0:00:13 time: 0.1227 data_time: 0.0207 memory: 1697 09/30 14:37:54 - mmengine - INFO - Epoch(val) [12][ 20/102] eta: 0:00:11 time: 0.1228 data_time: 0.0208 memory: 1697 09/30 14:37:54 - mmengine - INFO - Epoch(val) [12][ 25/102] eta: 0:00:10 time: 0.1229 data_time: 0.0207 memory: 1697 09/30 14:37:55 - mmengine - INFO - Epoch(val) [12][ 30/102] eta: 0:00:09 time: 0.1230 data_time: 0.0208 memory: 1697 09/30 14:37:55 - mmengine - INFO - Epoch(val) [12][ 35/102] eta: 0:00:08 time: 0.1229 data_time: 0.0207 memory: 1697 09/30 14:37:56 - mmengine - INFO - Epoch(val) [12][ 40/102] eta: 0:00:07 time: 0.1230 data_time: 0.0208 memory: 1697 09/30 14:37:57 - mmengine - INFO - Epoch(val) [12][ 45/102] eta: 0:00:07 time: 0.1230 data_time: 0.0208 memory: 1697 09/30 14:37:57 - mmengine - INFO - Epoch(val) [12][ 50/102] eta: 0:00:06 time: 0.1232 data_time: 0.0209 memory: 1697 09/30 14:37:58 - mmengine - INFO - Epoch(val) [12][ 55/102] eta: 0:00:05 time: 0.1090 data_time: 0.0066 memory: 1697 09/30 14:37:58 - mmengine - INFO - Epoch(val) [12][ 60/102] eta: 0:00:05 time: 0.1092 data_time: 0.0068 memory: 1697 09/30 14:37:59 - mmengine - INFO - Epoch(val) [12][ 65/102] eta: 0:00:04 time: 0.1094 data_time: 0.0071 memory: 1697 09/30 14:37:59 - mmengine - INFO - Epoch(val) [12][ 70/102] eta: 0:00:03 time: 0.1095 data_time: 0.0072 memory: 1697 09/30 14:38:00 - mmengine - INFO - Epoch(val) [12][ 75/102] eta: 0:00:03 time: 0.1096 data_time: 0.0073 memory: 1697 09/30 14:38:00 - mmengine - INFO - Epoch(val) [12][ 80/102] eta: 0:00:02 time: 0.1096 data_time: 0.0072 memory: 1697 09/30 14:38:01 - mmengine - INFO - Epoch(val) [12][ 85/102] eta: 0:00:01 time: 0.1097 data_time: 0.0073 memory: 1697 09/30 14:38:02 - mmengine - INFO - Epoch(val) [12][ 90/102] eta: 0:00:01 time: 0.1098 data_time: 0.0073 memory: 1697 09/30 14:38:02 - mmengine - INFO - Epoch(val) [12][ 95/102] eta: 0:00:00 time: 0.1097 data_time: 0.0074 memory: 1697 09/30 14:38:03 - mmengine - INFO - Epoch(val) [12][100/102] eta: 0:00:00 time: 0.1093 data_time: 0.0072 memory: 1697 09/30 14:38:03 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:38:03 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:38:03 - mmengine - INFO - Epoch(val) [12][102/102] data_time: 0.0138 time: 0.1160 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:38:05 - mmengine - INFO - Epoch(train) [13][ 5/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:55 time: 0.2764 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:06 - mmengine - INFO - Epoch(train) [13][10/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:52 time: 0.2772 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:08 - mmengine - INFO - Epoch(train) [13][15/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:50 time: 0.2780 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:09 - mmengine - INFO - Epoch(train) [13][20/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:48 time: 0.2788 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:11 - mmengine - INFO - Epoch(train) [13][25/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:45 time: 0.2789 data_time: 0.0285 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:12 - mmengine - INFO - Epoch(train) [13][30/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:42 time: 0.2785 data_time: 0.0285 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:13 - mmengine - INFO - Epoch(train) [13][35/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:40 time: 0.2791 data_time: 0.0284 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:15 - mmengine - INFO - Epoch(train) [13][40/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:37 time: 0.2806 data_time: 0.0285 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:16 - mmengine - INFO - Epoch(train) [13][45/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:35 time: 0.2828 data_time: 0.0287 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:17 - mmengine - INFO - Epoch(train) [13][50/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:32 time: 0.2869 data_time: 0.0287 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:19 - mmengine - INFO - Epoch(train) [13][55/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:30 time: 0.2671 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:20 - mmengine - INFO - Epoch(train) [13][60/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:27 time: 0.2665 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:21 - mmengine - INFO - Epoch(train) [13][65/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:25 time: 0.2666 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:23 - mmengine - INFO - Epoch(train) [13][70/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:22 time: 0.2662 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:24 - mmengine - INFO - Epoch(train) [13][75/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:20 time: 0.2663 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:25 - mmengine - INFO - Epoch(train) [13][80/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:17 time: 0.2664 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:26 - mmengine - INFO - Epoch(train) [13][85/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:14 time: 0.2647 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:28 - mmengine - INFO - Epoch(train) [13][90/94] base_lr: 9.0719e-03 lr: 9.0719e-03 eta: 0:40:11 time: 0.2635 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:29 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:38:29 - mmengine - INFO - Saving checkpoint at 13 epochs 09/30 14:38:31 - mmengine - INFO - Epoch(val) [13][ 5/102] eta: 0:00:25 time: 0.1244 data_time: 0.0223 memory: 11783 09/30 14:38:32 - mmengine - INFO - Epoch(val) [13][ 10/102] eta: 0:00:17 time: 0.1243 data_time: 0.0221 memory: 1697 09/30 14:38:32 - mmengine - INFO - Epoch(val) [13][ 15/102] eta: 0:00:13 time: 0.1242 data_time: 0.0217 memory: 1697 09/30 14:38:33 - mmengine - INFO - Epoch(val) [13][ 20/102] eta: 0:00:12 time: 0.1243 data_time: 0.0218 memory: 1697 09/30 14:38:34 - mmengine - INFO - Epoch(val) [13][ 25/102] eta: 0:00:10 time: 0.1241 data_time: 0.0217 memory: 1697 09/30 14:38:34 - mmengine - INFO - Epoch(val) [13][ 30/102] eta: 0:00:09 time: 0.1245 data_time: 0.0219 memory: 1697 09/30 14:38:35 - mmengine - INFO - Epoch(val) [13][ 35/102] eta: 0:00:08 time: 0.1243 data_time: 0.0217 memory: 1697 09/30 14:38:35 - mmengine - INFO - Epoch(val) [13][ 40/102] eta: 0:00:07 time: 0.1244 data_time: 0.0218 memory: 1697 09/30 14:38:36 - mmengine - INFO - Epoch(val) [13][ 45/102] eta: 0:00:07 time: 0.1249 data_time: 0.0220 memory: 1697 09/30 14:38:36 - mmengine - INFO - Epoch(val) [13][ 50/102] eta: 0:00:06 time: 0.1252 data_time: 0.0220 memory: 1697 09/30 14:38:37 - mmengine - INFO - Epoch(val) [13][ 55/102] eta: 0:00:05 time: 0.1100 data_time: 0.0069 memory: 1697 09/30 14:38:37 - mmengine - INFO - Epoch(val) [13][ 60/102] eta: 0:00:05 time: 0.1103 data_time: 0.0072 memory: 1697 09/30 14:38:38 - mmengine - INFO - Epoch(val) [13][ 65/102] eta: 0:00:04 time: 0.1105 data_time: 0.0075 memory: 1697 09/30 14:38:39 - mmengine - INFO - Epoch(val) [13][ 70/102] eta: 0:00:03 time: 0.1104 data_time: 0.0075 memory: 1697 09/30 14:38:39 - mmengine - INFO - Epoch(val) [13][ 75/102] eta: 0:00:03 time: 0.1105 data_time: 0.0076 memory: 1697 09/30 14:38:40 - mmengine - INFO - Epoch(val) [13][ 80/102] eta: 0:00:02 time: 0.1102 data_time: 0.0076 memory: 1697 09/30 14:38:40 - mmengine - INFO - Epoch(val) [13][ 85/102] eta: 0:00:02 time: 0.1105 data_time: 0.0077 memory: 1697 09/30 14:38:41 - mmengine - INFO - Epoch(val) [13][ 90/102] eta: 0:00:01 time: 0.1104 data_time: 0.0076 memory: 1697 09/30 14:38:41 - mmengine - INFO - Epoch(val) [13][ 95/102] eta: 0:00:00 time: 0.1105 data_time: 0.0076 memory: 1697 09/30 14:38:42 - mmengine - INFO - Epoch(val) [13][100/102] eta: 0:00:00 time: 0.1102 data_time: 0.0075 memory: 1697 09/30 14:38:42 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:38:42 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:38:42 - mmengine - INFO - Epoch(val) [13][102/102] data_time: 0.0146 time: 0.1175 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:38:45 - mmengine - INFO - Epoch(train) [14][ 5/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:40:13 time: 0.2820 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:46 - mmengine - INFO - Epoch(train) [14][10/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:40:11 time: 0.2825 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:47 - mmengine - INFO - Epoch(train) [14][15/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:40:08 time: 0.2817 data_time: 0.0331 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:49 - mmengine - INFO - Epoch(train) [14][20/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:40:06 time: 0.2818 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:50 - mmengine - INFO - Epoch(train) [14][25/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:40:04 time: 0.2818 data_time: 0.0329 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:51 - mmengine - INFO - Epoch(train) [14][30/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:40:01 time: 0.2811 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:52 - mmengine - INFO - Epoch(train) [14][35/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:58 time: 0.2807 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:54 - mmengine - INFO - Epoch(train) [14][40/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:56 time: 0.2824 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:55 - mmengine - INFO - Epoch(train) [14][45/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:54 time: 0.2831 data_time: 0.0325 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:56 - mmengine - INFO - Epoch(train) [14][50/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:51 time: 0.2871 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:58 - mmengine - INFO - Epoch(train) [14][55/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:49 time: 0.2642 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:38:59 - mmengine - INFO - Epoch(train) [14][60/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:46 time: 0.2639 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:00 - mmengine - INFO - Epoch(train) [14][65/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:44 time: 0.2652 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:02 - mmengine - INFO - Epoch(train) [14][70/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:42 time: 0.2658 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:03 - mmengine - INFO - Epoch(train) [14][75/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:40 time: 0.2662 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:04 - mmengine - INFO - Epoch(train) [14][80/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:37 time: 0.2663 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:06 - mmengine - INFO - Epoch(train) [14][85/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:34 time: 0.2645 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:07 - mmengine - INFO - Epoch(train) [14][90/94] base_lr: 8.9688e-03 lr: 8.9688e-03 eta: 0:39:32 time: 0.2627 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:08 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:39:08 - mmengine - INFO - Saving checkpoint at 14 epochs 09/30 14:39:12 - mmengine - INFO - Epoch(val) [14][ 5/102] eta: 0:00:25 time: 0.1258 data_time: 0.0230 memory: 11783 09/30 14:39:13 - mmengine - INFO - Epoch(val) [14][ 10/102] eta: 0:00:17 time: 0.1258 data_time: 0.0227 memory: 1697 09/30 14:39:13 - mmengine - INFO - Epoch(val) [14][ 15/102] eta: 0:00:14 time: 0.1255 data_time: 0.0223 memory: 1697 09/30 14:39:14 - mmengine - INFO - Epoch(val) [14][ 20/102] eta: 0:00:12 time: 0.1256 data_time: 0.0223 memory: 1697 09/30 14:39:14 - mmengine - INFO - Epoch(val) [14][ 25/102] eta: 0:00:10 time: 0.1254 data_time: 0.0221 memory: 1697 09/30 14:39:15 - mmengine - INFO - Epoch(val) [14][ 30/102] eta: 0:00:09 time: 0.1255 data_time: 0.0221 memory: 1697 09/30 14:39:16 - mmengine - INFO - Epoch(val) [14][ 35/102] eta: 0:00:08 time: 0.1255 data_time: 0.0219 memory: 1697 09/30 14:39:16 - mmengine - INFO - Epoch(val) [14][ 40/102] eta: 0:00:08 time: 0.1256 data_time: 0.0220 memory: 1697 09/30 14:39:17 - mmengine - INFO - Epoch(val) [14][ 45/102] eta: 0:00:07 time: 0.1256 data_time: 0.0221 memory: 1697 09/30 14:39:17 - mmengine - INFO - Epoch(val) [14][ 50/102] eta: 0:00:06 time: 0.1255 data_time: 0.0221 memory: 1697 09/30 14:39:18 - mmengine - INFO - Epoch(val) [14][ 55/102] eta: 0:00:05 time: 0.1099 data_time: 0.0065 memory: 1697 09/30 14:39:18 - mmengine - INFO - Epoch(val) [14][ 60/102] eta: 0:00:05 time: 0.1098 data_time: 0.0068 memory: 1697 09/30 14:39:19 - mmengine - INFO - Epoch(val) [14][ 65/102] eta: 0:00:04 time: 0.1101 data_time: 0.0072 memory: 1697 09/30 14:39:19 - mmengine - INFO - Epoch(val) [14][ 70/102] eta: 0:00:03 time: 0.1099 data_time: 0.0073 memory: 1697 09/30 14:39:20 - mmengine - INFO - Epoch(val) [14][ 75/102] eta: 0:00:03 time: 0.1100 data_time: 0.0074 memory: 1697 09/30 14:39:20 - mmengine - INFO - Epoch(val) [14][ 80/102] eta: 0:00:02 time: 0.1099 data_time: 0.0073 memory: 1697 09/30 14:39:21 - mmengine - INFO - Epoch(val) [14][ 85/102] eta: 0:00:02 time: 0.1099 data_time: 0.0074 memory: 1697 09/30 14:39:22 - mmengine - INFO - Epoch(val) [14][ 90/102] eta: 0:00:01 time: 0.1099 data_time: 0.0074 memory: 1697 09/30 14:39:22 - mmengine - INFO - Epoch(val) [14][ 95/102] eta: 0:00:00 time: 0.1099 data_time: 0.0075 memory: 1697 09/30 14:39:23 - mmengine - INFO - Epoch(val) [14][100/102] eta: 0:00:00 time: 0.1098 data_time: 0.0074 memory: 1697 09/30 14:39:23 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:39:23 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:39:23 - mmengine - INFO - Epoch(val) [14][102/102] data_time: 0.0145 time: 0.1174 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:39:26 - mmengine - INFO - Epoch(train) [15][ 5/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:37 time: 0.2931 data_time: 0.0436 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:27 - mmengine - INFO - Epoch(train) [15][10/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:34 time: 0.2938 data_time: 0.0437 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:29 - mmengine - INFO - Epoch(train) [15][15/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:32 time: 0.2939 data_time: 0.0433 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:30 - mmengine - INFO - Epoch(train) [15][20/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:30 time: 0.2947 data_time: 0.0430 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:31 - mmengine - INFO - Epoch(train) [15][25/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:28 time: 0.2941 data_time: 0.0428 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:33 - mmengine - INFO - Epoch(train) [15][30/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:26 time: 0.2939 data_time: 0.0429 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:34 - mmengine - INFO - Epoch(train) [15][35/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:23 time: 0.2943 data_time: 0.0429 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:35 - mmengine - INFO - Epoch(train) [15][40/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:21 time: 0.2961 data_time: 0.0428 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:37 - mmengine - INFO - Epoch(train) [15][45/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:19 time: 0.2977 data_time: 0.0429 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:38 - mmengine - INFO - Epoch(train) [15][50/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:17 time: 0.3022 data_time: 0.0431 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:39 - mmengine - INFO - Epoch(train) [15][55/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:14 time: 0.2682 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:41 - mmengine - INFO - Epoch(train) [15][60/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:12 time: 0.2679 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:42 - mmengine - INFO - Epoch(train) [15][65/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:09 time: 0.2666 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:43 - mmengine - INFO - Epoch(train) [15][70/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:07 time: 0.2659 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:45 - mmengine - INFO - Epoch(train) [15][75/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:05 time: 0.2646 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:46 - mmengine - INFO - Epoch(train) [15][80/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:02 time: 0.2644 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:47 - mmengine - INFO - Epoch(train) [15][85/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:39:00 time: 0.2628 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:48 - mmengine - INFO - Epoch(train) [15][90/94] base_lr: 8.8656e-03 lr: 8.8656e-03 eta: 0:38:57 time: 0.2611 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:39:49 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:39:49 - mmengine - INFO - Saving checkpoint at 15 epochs 09/30 14:39:52 - mmengine - INFO - Epoch(val) [15][ 5/102] eta: 0:00:25 time: 0.1251 data_time: 0.0225 memory: 11783 09/30 14:39:52 - mmengine - INFO - Epoch(val) [15][ 10/102] eta: 0:00:17 time: 0.1248 data_time: 0.0223 memory: 1697 09/30 14:39:53 - mmengine - INFO - Epoch(val) [15][ 15/102] eta: 0:00:13 time: 0.1246 data_time: 0.0219 memory: 1697 09/30 14:39:53 - mmengine - INFO - Epoch(val) [15][ 20/102] eta: 0:00:12 time: 0.1245 data_time: 0.0219 memory: 1697 09/30 14:39:54 - mmengine - INFO - Epoch(val) [15][ 25/102] eta: 0:00:10 time: 0.1245 data_time: 0.0218 memory: 1697 09/30 14:39:55 - mmengine - INFO - Epoch(val) [15][ 30/102] eta: 0:00:09 time: 0.1246 data_time: 0.0218 memory: 1697 09/30 14:39:55 - mmengine - INFO - Epoch(val) [15][ 35/102] eta: 0:00:08 time: 0.1246 data_time: 0.0217 memory: 1697 09/30 14:39:56 - mmengine - INFO - Epoch(val) [15][ 40/102] eta: 0:00:07 time: 0.1247 data_time: 0.0217 memory: 1697 09/30 14:39:56 - mmengine - INFO - Epoch(val) [15][ 45/102] eta: 0:00:07 time: 0.1247 data_time: 0.0217 memory: 1697 09/30 14:39:57 - mmengine - INFO - Epoch(val) [15][ 50/102] eta: 0:00:06 time: 0.1249 data_time: 0.0218 memory: 1697 09/30 14:39:57 - mmengine - INFO - Epoch(val) [15][ 55/102] eta: 0:00:05 time: 0.1097 data_time: 0.0067 memory: 1697 09/30 14:39:58 - mmengine - INFO - Epoch(val) [15][ 60/102] eta: 0:00:05 time: 0.1102 data_time: 0.0070 memory: 1697 09/30 14:39:58 - mmengine - INFO - Epoch(val) [15][ 65/102] eta: 0:00:04 time: 0.1107 data_time: 0.0073 memory: 1697 09/30 14:39:59 - mmengine - INFO - Epoch(val) [15][ 70/102] eta: 0:00:03 time: 0.1108 data_time: 0.0073 memory: 1697 09/30 14:40:00 - mmengine - INFO - Epoch(val) [15][ 75/102] eta: 0:00:03 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 14:40:00 - mmengine - INFO - Epoch(val) [15][ 80/102] eta: 0:00:02 time: 0.1108 data_time: 0.0074 memory: 1697 09/30 14:40:01 - mmengine - INFO - Epoch(val) [15][ 85/102] eta: 0:00:02 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 14:40:01 - mmengine - INFO - Epoch(val) [15][ 90/102] eta: 0:00:01 time: 0.1105 data_time: 0.0074 memory: 1697 09/30 14:40:02 - mmengine - INFO - Epoch(val) [15][ 95/102] eta: 0:00:00 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 14:40:02 - mmengine - INFO - Epoch(val) [15][100/102] eta: 0:00:00 time: 0.1100 data_time: 0.0072 memory: 1697 09/30 14:40:03 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:40:03 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:40:03 - mmengine - INFO - Epoch(val) [15][102/102] data_time: 0.0143 time: 0.1172 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:40:05 - mmengine - INFO - Epoch(train) [16][ 5/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:59 time: 0.2826 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:06 - mmengine - INFO - Epoch(train) [16][10/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:57 time: 0.2829 data_time: 0.0347 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:08 - mmengine - INFO - Epoch(train) [16][15/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:55 time: 0.2822 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:09 - mmengine - INFO - Epoch(train) [16][20/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:52 time: 0.2823 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:10 - mmengine - INFO - Epoch(train) [16][25/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:50 time: 0.2822 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:12 - mmengine - INFO - Epoch(train) [16][30/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:48 time: 0.2820 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:13 - mmengine - INFO - Epoch(train) [16][35/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:45 time: 0.2819 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:14 - mmengine - INFO - Epoch(train) [16][40/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:43 time: 0.2835 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:16 - mmengine - INFO - Epoch(train) [16][45/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:41 time: 0.2852 data_time: 0.0343 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:17 - mmengine - INFO - Epoch(train) [16][50/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:39 time: 0.2897 data_time: 0.0346 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:18 - mmengine - INFO - Epoch(train) [16][55/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:37 time: 0.2646 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:20 - mmengine - INFO - Epoch(train) [16][60/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:35 time: 0.2643 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:21 - mmengine - INFO - Epoch(train) [16][65/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:33 time: 0.2652 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:22 - mmengine - INFO - Epoch(train) [16][70/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:30 time: 0.2652 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:24 - mmengine - INFO - Epoch(train) [16][75/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:28 time: 0.2653 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:25 - mmengine - INFO - Epoch(train) [16][80/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:26 time: 0.2655 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:26 - mmengine - INFO - Epoch(train) [16][85/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:23 time: 0.2645 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:27 - mmengine - INFO - Epoch(train) [16][90/94] base_lr: 8.7625e-03 lr: 8.7625e-03 eta: 0:38:21 time: 0.2629 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:28 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:40:28 - mmengine - INFO - Saving checkpoint at 16 epochs 09/30 14:40:31 - mmengine - INFO - Epoch(val) [16][ 5/102] eta: 0:00:25 time: 0.1250 data_time: 0.0222 memory: 11783 09/30 14:40:32 - mmengine - INFO - Epoch(val) [16][ 10/102] eta: 0:00:16 time: 0.1243 data_time: 0.0219 memory: 1697 09/30 14:40:32 - mmengine - INFO - Epoch(val) [16][ 15/102] eta: 0:00:13 time: 0.1241 data_time: 0.0215 memory: 1697 09/30 14:40:33 - mmengine - INFO - Epoch(val) [16][ 20/102] eta: 0:00:12 time: 0.1237 data_time: 0.0215 memory: 1697 09/30 14:40:33 - mmengine - INFO - Epoch(val) [16][ 25/102] eta: 0:00:10 time: 0.1237 data_time: 0.0214 memory: 1697 09/30 14:40:34 - mmengine - INFO - Epoch(val) [16][ 30/102] eta: 0:00:09 time: 0.1242 data_time: 0.0216 memory: 1697 09/30 14:40:34 - mmengine - INFO - Epoch(val) [16][ 35/102] eta: 0:00:08 time: 0.1242 data_time: 0.0214 memory: 1697 09/30 14:40:35 - mmengine - INFO - Epoch(val) [16][ 40/102] eta: 0:00:07 time: 0.1248 data_time: 0.0215 memory: 1697 09/30 14:40:36 - mmengine - INFO - Epoch(val) [16][ 45/102] eta: 0:00:07 time: 0.1249 data_time: 0.0216 memory: 1697 09/30 14:40:36 - mmengine - INFO - Epoch(val) [16][ 50/102] eta: 0:00:06 time: 0.1249 data_time: 0.0216 memory: 1697 09/30 14:40:37 - mmengine - INFO - Epoch(val) [16][ 55/102] eta: 0:00:05 time: 0.1097 data_time: 0.0066 memory: 1697 09/30 14:40:37 - mmengine - INFO - Epoch(val) [16][ 60/102] eta: 0:00:05 time: 0.1101 data_time: 0.0068 memory: 1697 09/30 14:40:38 - mmengine - INFO - Epoch(val) [16][ 65/102] eta: 0:00:04 time: 0.1104 data_time: 0.0071 memory: 1697 09/30 14:40:38 - mmengine - INFO - Epoch(val) [16][ 70/102] eta: 0:00:03 time: 0.1104 data_time: 0.0071 memory: 1697 09/30 14:40:39 - mmengine - INFO - Epoch(val) [16][ 75/102] eta: 0:00:03 time: 0.1103 data_time: 0.0072 memory: 1697 09/30 14:40:39 - mmengine - INFO - Epoch(val) [16][ 80/102] eta: 0:00:02 time: 0.1098 data_time: 0.0069 memory: 1697 09/30 14:40:40 - mmengine - INFO - Epoch(val) [16][ 85/102] eta: 0:00:02 time: 0.1096 data_time: 0.0070 memory: 1697 09/30 14:40:40 - mmengine - INFO - Epoch(val) [16][ 90/102] eta: 0:00:01 time: 0.1092 data_time: 0.0070 memory: 1697 09/30 14:40:41 - mmengine - INFO - Epoch(val) [16][ 95/102] eta: 0:00:00 time: 0.1091 data_time: 0.0071 memory: 1697 09/30 14:40:42 - mmengine - INFO - Epoch(val) [16][100/102] eta: 0:00:00 time: 0.1090 data_time: 0.0069 memory: 1697 09/30 14:40:42 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:40:42 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:40:42 - mmengine - INFO - Epoch(val) [16][102/102] data_time: 0.0140 time: 0.1167 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:40:45 - mmengine - INFO - Epoch(train) [17][ 5/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:23 time: 0.2869 data_time: 0.0390 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:46 - mmengine - INFO - Epoch(train) [17][10/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:21 time: 0.2870 data_time: 0.0389 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:47 - mmengine - INFO - Epoch(train) [17][15/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:19 time: 0.2859 data_time: 0.0386 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:48 - mmengine - INFO - Epoch(train) [17][20/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:17 time: 0.2864 data_time: 0.0383 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:50 - mmengine - INFO - Epoch(train) [17][25/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:15 time: 0.2861 data_time: 0.0383 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:51 - mmengine - INFO - Epoch(train) [17][30/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:13 time: 0.2862 data_time: 0.0383 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:52 - mmengine - INFO - Epoch(train) [17][35/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:10 time: 0.2866 data_time: 0.0382 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:54 - mmengine - INFO - Epoch(train) [17][40/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:08 time: 0.2878 data_time: 0.0382 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:55 - mmengine - INFO - Epoch(train) [17][45/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:06 time: 0.2893 data_time: 0.0383 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:56 - mmengine - INFO - Epoch(train) [17][50/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:04 time: 0.2935 data_time: 0.0384 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:58 - mmengine - INFO - Epoch(train) [17][55/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:02 time: 0.2652 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:40:59 - mmengine - INFO - Epoch(train) [17][60/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:38:00 time: 0.2654 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:00 - mmengine - INFO - Epoch(train) [17][65/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:37:58 time: 0.2662 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:02 - mmengine - INFO - Epoch(train) [17][70/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:37:56 time: 0.2656 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:03 - mmengine - INFO - Epoch(train) [17][75/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:37:54 time: 0.2661 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:04 - mmengine - INFO - Epoch(train) [17][80/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:37:52 time: 0.2661 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:06 - mmengine - INFO - Epoch(train) [17][85/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:37:49 time: 0.2646 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:07 - mmengine - INFO - Epoch(train) [17][90/94] base_lr: 8.6594e-03 lr: 8.6594e-03 eta: 0:37:47 time: 0.2632 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:08 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:41:08 - mmengine - INFO - Saving checkpoint at 17 epochs 09/30 14:41:11 - mmengine - INFO - Epoch(val) [17][ 5/102] eta: 0:00:26 time: 0.1250 data_time: 0.0228 memory: 11783 09/30 14:41:11 - mmengine - INFO - Epoch(val) [17][ 10/102] eta: 0:00:17 time: 0.1249 data_time: 0.0226 memory: 1697 09/30 14:41:12 - mmengine - INFO - Epoch(val) [17][ 15/102] eta: 0:00:14 time: 0.1245 data_time: 0.0223 memory: 1697 09/30 14:41:12 - mmengine - INFO - Epoch(val) [17][ 20/102] eta: 0:00:12 time: 0.1247 data_time: 0.0223 memory: 1697 09/30 14:41:13 - mmengine - INFO - Epoch(val) [17][ 25/102] eta: 0:00:10 time: 0.1247 data_time: 0.0223 memory: 1697 09/30 14:41:13 - mmengine - INFO - Epoch(val) [17][ 30/102] eta: 0:00:09 time: 0.1252 data_time: 0.0225 memory: 1697 09/30 14:41:14 - mmengine - INFO - Epoch(val) [17][ 35/102] eta: 0:00:08 time: 0.1251 data_time: 0.0222 memory: 1697 09/30 14:41:15 - mmengine - INFO - Epoch(val) [17][ 40/102] eta: 0:00:08 time: 0.1254 data_time: 0.0224 memory: 1697 09/30 14:41:15 - mmengine - INFO - Epoch(val) [17][ 45/102] eta: 0:00:07 time: 0.1255 data_time: 0.0224 memory: 1697 09/30 14:41:16 - mmengine - INFO - Epoch(val) [17][ 50/102] eta: 0:00:06 time: 0.1257 data_time: 0.0225 memory: 1697 09/30 14:41:16 - mmengine - INFO - Epoch(val) [17][ 55/102] eta: 0:00:05 time: 0.1098 data_time: 0.0067 memory: 1697 09/30 14:41:17 - mmengine - INFO - Epoch(val) [17][ 60/102] eta: 0:00:05 time: 0.1101 data_time: 0.0069 memory: 1697 09/30 14:41:17 - mmengine - INFO - Epoch(val) [17][ 65/102] eta: 0:00:04 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 14:41:18 - mmengine - INFO - Epoch(val) [17][ 70/102] eta: 0:00:03 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 14:41:18 - mmengine - INFO - Epoch(val) [17][ 75/102] eta: 0:00:03 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 14:41:19 - mmengine - INFO - Epoch(val) [17][ 80/102] eta: 0:00:02 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 14:41:20 - mmengine - INFO - Epoch(val) [17][ 85/102] eta: 0:00:02 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 14:41:20 - mmengine - INFO - Epoch(val) [17][ 90/102] eta: 0:00:01 time: 0.1105 data_time: 0.0073 memory: 1697 09/30 14:41:21 - mmengine - INFO - Epoch(val) [17][ 95/102] eta: 0:00:00 time: 0.1107 data_time: 0.0075 memory: 1697 09/30 14:41:21 - mmengine - INFO - Epoch(val) [17][100/102] eta: 0:00:00 time: 0.1105 data_time: 0.0073 memory: 1697 09/30 14:41:21 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:41:21 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:41:21 - mmengine - INFO - Epoch(val) [17][102/102] data_time: 0.0147 time: 0.1178 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:41:25 - mmengine - INFO - Epoch(train) [18][ 5/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:54 time: 0.3056 data_time: 0.0561 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:26 - mmengine - INFO - Epoch(train) [18][10/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:51 time: 0.3053 data_time: 0.0560 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:28 - mmengine - INFO - Epoch(train) [18][15/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:49 time: 0.3042 data_time: 0.0554 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:29 - mmengine - INFO - Epoch(train) [18][20/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:47 time: 0.3036 data_time: 0.0552 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:30 - mmengine - INFO - Epoch(train) [18][25/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:45 time: 0.3039 data_time: 0.0553 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:32 - mmengine - INFO - Epoch(train) [18][30/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:43 time: 0.3041 data_time: 0.0552 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:33 - mmengine - INFO - Epoch(train) [18][35/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:41 time: 0.3048 data_time: 0.0549 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:34 - mmengine - INFO - Epoch(train) [18][40/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:39 time: 0.3061 data_time: 0.0552 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:36 - mmengine - INFO - Epoch(train) [18][45/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:37 time: 0.3070 data_time: 0.0552 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:37 - mmengine - INFO - Epoch(train) [18][50/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:35 time: 0.3109 data_time: 0.0552 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:38 - mmengine - INFO - Epoch(train) [18][55/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:33 time: 0.2645 data_time: 0.0086 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:40 - mmengine - INFO - Epoch(train) [18][60/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:30 time: 0.2644 data_time: 0.0086 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:41 - mmengine - INFO - Epoch(train) [18][65/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:28 time: 0.2652 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:42 - mmengine - INFO - Epoch(train) [18][70/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:26 time: 0.2652 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:44 - mmengine - INFO - Epoch(train) [18][75/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:24 time: 0.2647 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:45 - mmengine - INFO - Epoch(train) [18][80/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:22 time: 0.2639 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:46 - mmengine - INFO - Epoch(train) [18][85/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:20 time: 0.2611 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:47 - mmengine - INFO - Epoch(train) [18][90/94] base_lr: 8.5563e-03 lr: 8.5563e-03 eta: 0:37:17 time: 0.2591 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:41:48 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:41:48 - mmengine - INFO - Saving checkpoint at 18 epochs 09/30 14:41:51 - mmengine - INFO - Epoch(val) [18][ 5/102] eta: 0:00:26 time: 0.1264 data_time: 0.0234 memory: 11783 09/30 14:41:51 - mmengine - INFO - Epoch(val) [18][ 10/102] eta: 0:00:17 time: 0.1261 data_time: 0.0231 memory: 1697 09/30 14:41:52 - mmengine - INFO - Epoch(val) [18][ 15/102] eta: 0:00:14 time: 0.1256 data_time: 0.0228 memory: 1697 09/30 14:41:52 - mmengine - INFO - Epoch(val) [18][ 20/102] eta: 0:00:12 time: 0.1253 data_time: 0.0227 memory: 1697 09/30 14:41:53 - mmengine - INFO - Epoch(val) [18][ 25/102] eta: 0:00:10 time: 0.1252 data_time: 0.0225 memory: 1697 09/30 14:41:53 - mmengine - INFO - Epoch(val) [18][ 30/102] eta: 0:00:09 time: 0.1252 data_time: 0.0227 memory: 1697 09/30 14:41:54 - mmengine - INFO - Epoch(val) [18][ 35/102] eta: 0:00:08 time: 0.1246 data_time: 0.0223 memory: 1697 09/30 14:41:55 - mmengine - INFO - Epoch(val) [18][ 40/102] eta: 0:00:07 time: 0.1245 data_time: 0.0224 memory: 1697 09/30 14:41:55 - mmengine - INFO - Epoch(val) [18][ 45/102] eta: 0:00:07 time: 0.1245 data_time: 0.0223 memory: 1697 09/30 14:41:56 - mmengine - INFO - Epoch(val) [18][ 50/102] eta: 0:00:06 time: 0.1246 data_time: 0.0223 memory: 1697 09/30 14:41:56 - mmengine - INFO - Epoch(val) [18][ 55/102] eta: 0:00:05 time: 0.1084 data_time: 0.0062 memory: 1697 09/30 14:41:57 - mmengine - INFO - Epoch(val) [18][ 60/102] eta: 0:00:05 time: 0.1083 data_time: 0.0064 memory: 1697 09/30 14:41:57 - mmengine - INFO - Epoch(val) [18][ 65/102] eta: 0:00:04 time: 0.1086 data_time: 0.0067 memory: 1697 09/30 14:41:58 - mmengine - INFO - Epoch(val) [18][ 70/102] eta: 0:00:03 time: 0.1089 data_time: 0.0068 memory: 1697 09/30 14:41:58 - mmengine - INFO - Epoch(val) [18][ 75/102] eta: 0:00:03 time: 0.1090 data_time: 0.0069 memory: 1697 09/30 14:41:59 - mmengine - INFO - Epoch(val) [18][ 80/102] eta: 0:00:02 time: 0.1087 data_time: 0.0066 memory: 1697 09/30 14:41:59 - mmengine - INFO - Epoch(val) [18][ 85/102] eta: 0:00:02 time: 0.1091 data_time: 0.0069 memory: 1697 09/30 14:42:00 - mmengine - INFO - Epoch(val) [18][ 90/102] eta: 0:00:01 time: 0.1088 data_time: 0.0067 memory: 1697 09/30 14:42:01 - mmengine - INFO - Epoch(val) [18][ 95/102] eta: 0:00:00 time: 0.1087 data_time: 0.0067 memory: 1697 09/30 14:42:01 - mmengine - INFO - Epoch(val) [18][100/102] eta: 0:00:00 time: 0.1085 data_time: 0.0066 memory: 1697 09/30 14:42:01 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:42:01 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:42:01 - mmengine - INFO - Epoch(val) [18][102/102] data_time: 0.0142 time: 0.1163 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:42:03 - mmengine - INFO - Epoch(train) [19][ 5/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:16 time: 0.2713 data_time: 0.0240 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:05 - mmengine - INFO - Epoch(train) [19][10/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:14 time: 0.2717 data_time: 0.0245 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:06 - mmengine - INFO - Epoch(train) [19][15/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:12 time: 0.2709 data_time: 0.0238 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:07 - mmengine - INFO - Epoch(train) [19][20/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:10 time: 0.2708 data_time: 0.0236 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:09 - mmengine - INFO - Epoch(train) [19][25/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:08 time: 0.2706 data_time: 0.0236 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:10 - mmengine - INFO - Epoch(train) [19][30/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:06 time: 0.2709 data_time: 0.0238 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:11 - mmengine - INFO - Epoch(train) [19][35/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:04 time: 0.2715 data_time: 0.0235 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:13 - mmengine - INFO - Epoch(train) [19][40/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:02 time: 0.2726 data_time: 0.0236 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:14 - mmengine - INFO - Epoch(train) [19][45/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:37:01 time: 0.2786 data_time: 0.0237 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:15 - mmengine - INFO - Epoch(train) [19][50/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:59 time: 0.2832 data_time: 0.0238 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:17 - mmengine - INFO - Epoch(train) [19][55/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:57 time: 0.2677 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:18 - mmengine - INFO - Epoch(train) [19][60/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:55 time: 0.2676 data_time: 0.0085 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:19 - mmengine - INFO - Epoch(train) [19][65/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:53 time: 0.2680 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:21 - mmengine - INFO - Epoch(train) [19][70/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:51 time: 0.2681 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:22 - mmengine - INFO - Epoch(train) [19][75/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:49 time: 0.2682 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:23 - mmengine - INFO - Epoch(train) [19][80/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:47 time: 0.2680 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:25 - mmengine - INFO - Epoch(train) [19][85/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:44 time: 0.2670 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:26 - mmengine - INFO - Epoch(train) [19][90/94] base_lr: 8.4531e-03 lr: 8.4531e-03 eta: 0:36:42 time: 0.2663 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:27 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:42:27 - mmengine - INFO - Saving checkpoint at 19 epochs 09/30 14:42:29 - mmengine - INFO - Epoch(val) [19][ 5/102] eta: 0:00:22 time: 0.1209 data_time: 0.0187 memory: 11783 09/30 14:42:30 - mmengine - INFO - Epoch(val) [19][ 10/102] eta: 0:00:15 time: 0.1210 data_time: 0.0185 memory: 1697 09/30 14:42:30 - mmengine - INFO - Epoch(val) [19][ 15/102] eta: 0:00:13 time: 0.1211 data_time: 0.0182 memory: 1697 09/30 14:42:31 - mmengine - INFO - Epoch(val) [19][ 20/102] eta: 0:00:11 time: 0.1211 data_time: 0.0182 memory: 1697 09/30 14:42:31 - mmengine - INFO - Epoch(val) [19][ 25/102] eta: 0:00:10 time: 0.1210 data_time: 0.0183 memory: 1697 09/30 14:42:32 - mmengine - INFO - Epoch(val) [19][ 30/102] eta: 0:00:09 time: 0.1215 data_time: 0.0185 memory: 1697 09/30 14:42:33 - mmengine - INFO - Epoch(val) [19][ 35/102] eta: 0:00:08 time: 0.1213 data_time: 0.0184 memory: 1697 09/30 14:42:33 - mmengine - INFO - Epoch(val) [19][ 40/102] eta: 0:00:07 time: 0.1218 data_time: 0.0186 memory: 1697 09/30 14:42:34 - mmengine - INFO - Epoch(val) [19][ 45/102] eta: 0:00:07 time: 0.1221 data_time: 0.0188 memory: 1697 09/30 14:42:34 - mmengine - INFO - Epoch(val) [19][ 50/102] eta: 0:00:06 time: 0.1225 data_time: 0.0189 memory: 1697 09/30 14:42:35 - mmengine - INFO - Epoch(val) [19][ 55/102] eta: 0:00:05 time: 0.1102 data_time: 0.0068 memory: 1697 09/30 14:42:35 - mmengine - INFO - Epoch(val) [19][ 60/102] eta: 0:00:05 time: 0.1103 data_time: 0.0071 memory: 1697 09/30 14:42:36 - mmengine - INFO - Epoch(val) [19][ 65/102] eta: 0:00:04 time: 0.1105 data_time: 0.0074 memory: 1697 09/30 14:42:36 - mmengine - INFO - Epoch(val) [19][ 70/102] eta: 0:00:03 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 14:42:37 - mmengine - INFO - Epoch(val) [19][ 75/102] eta: 0:00:03 time: 0.1107 data_time: 0.0076 memory: 1697 09/30 14:42:38 - mmengine - INFO - Epoch(val) [19][ 80/102] eta: 0:00:02 time: 0.1102 data_time: 0.0074 memory: 1697 09/30 14:42:38 - mmengine - INFO - Epoch(val) [19][ 85/102] eta: 0:00:01 time: 0.1103 data_time: 0.0075 memory: 1697 09/30 14:42:39 - mmengine - INFO - Epoch(val) [19][ 90/102] eta: 0:00:01 time: 0.1102 data_time: 0.0075 memory: 1697 09/30 14:42:39 - mmengine - INFO - Epoch(val) [19][ 95/102] eta: 0:00:00 time: 0.1101 data_time: 0.0075 memory: 1697 09/30 14:42:40 - mmengine - INFO - Epoch(val) [19][100/102] eta: 0:00:00 time: 0.1099 data_time: 0.0073 memory: 1697 09/30 14:42:40 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:42:40 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:42:40 - mmengine - INFO - Epoch(val) [19][102/102] data_time: 0.0129 time: 0.1160 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:42:42 - mmengine - INFO - Epoch(train) [20][ 5/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:42 time: 0.2760 data_time: 0.0281 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:44 - mmengine - INFO - Epoch(train) [20][10/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:40 time: 0.2769 data_time: 0.0286 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:45 - mmengine - INFO - Epoch(train) [20][15/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:38 time: 0.2767 data_time: 0.0279 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:46 - mmengine - INFO - Epoch(train) [20][20/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:36 time: 0.2770 data_time: 0.0280 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:47 - mmengine - INFO - Epoch(train) [20][25/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:34 time: 0.2763 data_time: 0.0277 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:49 - mmengine - INFO - Epoch(train) [20][30/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:32 time: 0.2771 data_time: 0.0276 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:50 - mmengine - INFO - Epoch(train) [20][35/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:30 time: 0.2767 data_time: 0.0276 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:51 - mmengine - INFO - Epoch(train) [20][40/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:28 time: 0.2780 data_time: 0.0276 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:53 - mmengine - INFO - Epoch(train) [20][45/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:26 time: 0.2797 data_time: 0.0278 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:54 - mmengine - INFO - Epoch(train) [20][50/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:24 time: 0.2835 data_time: 0.0278 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:55 - mmengine - INFO - Epoch(train) [20][55/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:22 time: 0.2657 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:57 - mmengine - INFO - Epoch(train) [20][60/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:20 time: 0.2650 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:58 - mmengine - INFO - Epoch(train) [20][65/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:18 time: 0.2654 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:42:59 - mmengine - INFO - Epoch(train) [20][70/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:16 time: 0.2651 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:01 - mmengine - INFO - Epoch(train) [20][75/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:15 time: 0.2666 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:02 - mmengine - INFO - Epoch(train) [20][80/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:13 time: 0.2671 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:03 - mmengine - INFO - Epoch(train) [20][85/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:11 time: 0.2657 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:05 - mmengine - INFO - Epoch(train) [20][90/94] base_lr: 8.3500e-03 lr: 8.3500e-03 eta: 0:36:09 time: 0.2640 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:06 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:43:06 - mmengine - INFO - Saving checkpoint at 20 epochs 09/30 14:43:10 - mmengine - INFO - Epoch(val) [20][ 5/102] eta: 0:00:24 time: 0.1245 data_time: 0.0219 memory: 11783 09/30 14:43:11 - mmengine - INFO - Epoch(val) [20][ 10/102] eta: 0:00:16 time: 0.1244 data_time: 0.0216 memory: 1697 09/30 14:43:11 - mmengine - INFO - Epoch(val) [20][ 15/102] eta: 0:00:13 time: 0.1240 data_time: 0.0213 memory: 1697 09/30 14:43:12 - mmengine - INFO - Epoch(val) [20][ 20/102] eta: 0:00:11 time: 0.1241 data_time: 0.0212 memory: 1697 09/30 14:43:12 - mmengine - INFO - Epoch(val) [20][ 25/102] eta: 0:00:10 time: 0.1240 data_time: 0.0211 memory: 1697 09/30 14:43:13 - mmengine - INFO - Epoch(val) [20][ 30/102] eta: 0:00:09 time: 0.1244 data_time: 0.0213 memory: 1697 09/30 14:43:14 - mmengine - INFO - Epoch(val) [20][ 35/102] eta: 0:00:08 time: 0.1241 data_time: 0.0209 memory: 1697 09/30 14:43:14 - mmengine - INFO - Epoch(val) [20][ 40/102] eta: 0:00:07 time: 0.1243 data_time: 0.0210 memory: 1697 09/30 14:43:15 - mmengine - INFO - Epoch(val) [20][ 45/102] eta: 0:00:07 time: 0.1245 data_time: 0.0212 memory: 1697 09/30 14:43:15 - mmengine - INFO - Epoch(val) [20][ 50/102] eta: 0:00:06 time: 0.1247 data_time: 0.0213 memory: 1697 09/30 14:43:16 - mmengine - INFO - Epoch(val) [20][ 55/102] eta: 0:00:05 time: 0.1099 data_time: 0.0067 memory: 1697 09/30 14:43:16 - mmengine - INFO - Epoch(val) [20][ 60/102] eta: 0:00:05 time: 0.1101 data_time: 0.0069 memory: 1697 09/30 14:43:17 - mmengine - INFO - Epoch(val) [20][ 65/102] eta: 0:00:04 time: 0.1105 data_time: 0.0072 memory: 1697 09/30 14:43:17 - mmengine - INFO - Epoch(val) [20][ 70/102] eta: 0:00:03 time: 0.1103 data_time: 0.0072 memory: 1697 09/30 14:43:18 - mmengine - INFO - Epoch(val) [20][ 75/102] eta: 0:00:03 time: 0.1105 data_time: 0.0073 memory: 1697 09/30 14:43:19 - mmengine - INFO - Epoch(val) [20][ 80/102] eta: 0:00:02 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 14:43:19 - mmengine - INFO - Epoch(val) [20][ 85/102] eta: 0:00:02 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 14:43:20 - mmengine - INFO - Epoch(val) [20][ 90/102] eta: 0:00:01 time: 0.1102 data_time: 0.0072 memory: 1697 09/30 14:43:20 - mmengine - INFO - Epoch(val) [20][ 95/102] eta: 0:00:00 time: 0.1100 data_time: 0.0073 memory: 1697 09/30 14:43:21 - mmengine - INFO - Epoch(val) [20][100/102] eta: 0:00:00 time: 0.1098 data_time: 0.0071 memory: 1697 09/30 14:43:21 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:43:21 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:43:21 - mmengine - INFO - Epoch(val) [20][102/102] data_time: 0.0140 time: 0.1170 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:43:24 - mmengine - INFO - Epoch(train) [21][ 5/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:36:11 time: 0.2932 data_time: 0.0430 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:25 - mmengine - INFO - Epoch(train) [21][10/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:36:09 time: 0.2934 data_time: 0.0430 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:27 - mmengine - INFO - Epoch(train) [21][15/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:36:07 time: 0.2931 data_time: 0.0424 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:28 - mmengine - INFO - Epoch(train) [21][20/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:36:05 time: 0.2927 data_time: 0.0422 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:29 - mmengine - INFO - Epoch(train) [21][25/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:36:03 time: 0.2930 data_time: 0.0421 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:31 - mmengine - INFO - Epoch(train) [21][30/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:36:01 time: 0.2921 data_time: 0.0421 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:32 - mmengine - INFO - Epoch(train) [21][35/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:59 time: 0.2911 data_time: 0.0421 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:33 - mmengine - INFO - Epoch(train) [21][40/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:57 time: 0.2923 data_time: 0.0421 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:34 - mmengine - INFO - Epoch(train) [21][45/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:56 time: 0.2937 data_time: 0.0422 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:36 - mmengine - INFO - Epoch(train) [21][50/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:54 time: 0.2972 data_time: 0.0422 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:37 - mmengine - INFO - Epoch(train) [21][55/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:52 time: 0.2645 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:38 - mmengine - INFO - Epoch(train) [21][60/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:50 time: 0.2643 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:40 - mmengine - INFO - Epoch(train) [21][65/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:48 time: 0.2644 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:41 - mmengine - INFO - Epoch(train) [21][70/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:46 time: 0.2638 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:42 - mmengine - INFO - Epoch(train) [21][75/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:44 time: 0.2635 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:44 - mmengine - INFO - Epoch(train) [21][80/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:42 time: 0.2639 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:45 - mmengine - INFO - Epoch(train) [21][85/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:40 time: 0.2620 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:46 - mmengine - INFO - Epoch(train) [21][90/94] base_lr: 8.2469e-03 lr: 8.2469e-03 eta: 0:35:38 time: 0.2605 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:43:47 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:43:47 - mmengine - INFO - Saving checkpoint at 21 epochs 09/30 14:43:50 - mmengine - INFO - Epoch(val) [21][ 5/102] eta: 0:00:23 time: 0.1234 data_time: 0.0205 memory: 11783 09/30 14:43:50 - mmengine - INFO - Epoch(val) [21][ 10/102] eta: 0:00:16 time: 0.1230 data_time: 0.0204 memory: 1697 09/30 14:43:51 - mmengine - INFO - Epoch(val) [21][ 15/102] eta: 0:00:13 time: 0.1226 data_time: 0.0200 memory: 1697 09/30 14:43:51 - mmengine - INFO - Epoch(val) [21][ 20/102] eta: 0:00:11 time: 0.1227 data_time: 0.0200 memory: 1697 09/30 14:43:52 - mmengine - INFO - Epoch(val) [21][ 25/102] eta: 0:00:10 time: 0.1227 data_time: 0.0199 memory: 1697 09/30 14:43:52 - mmengine - INFO - Epoch(val) [21][ 30/102] eta: 0:00:09 time: 0.1229 data_time: 0.0201 memory: 1697 09/30 14:43:53 - mmengine - INFO - Epoch(val) [21][ 35/102] eta: 0:00:08 time: 0.1230 data_time: 0.0200 memory: 1697 09/30 14:43:54 - mmengine - INFO - Epoch(val) [21][ 40/102] eta: 0:00:07 time: 0.1231 data_time: 0.0202 memory: 1697 09/30 14:43:54 - mmengine - INFO - Epoch(val) [21][ 45/102] eta: 0:00:07 time: 0.1233 data_time: 0.0202 memory: 1697 09/30 14:43:55 - mmengine - INFO - Epoch(val) [21][ 50/102] eta: 0:00:06 time: 0.1233 data_time: 0.0203 memory: 1697 09/30 14:43:55 - mmengine - INFO - Epoch(val) [21][ 55/102] eta: 0:00:05 time: 0.1097 data_time: 0.0068 memory: 1697 09/30 14:43:56 - mmengine - INFO - Epoch(val) [21][ 60/102] eta: 0:00:05 time: 0.1097 data_time: 0.0069 memory: 1697 09/30 14:43:56 - mmengine - INFO - Epoch(val) [21][ 65/102] eta: 0:00:04 time: 0.1101 data_time: 0.0072 memory: 1697 09/30 14:43:57 - mmengine - INFO - Epoch(val) [21][ 70/102] eta: 0:00:03 time: 0.1101 data_time: 0.0072 memory: 1697 09/30 14:43:57 - mmengine - INFO - Epoch(val) [21][ 75/102] eta: 0:00:03 time: 0.1098 data_time: 0.0072 memory: 1697 09/30 14:43:58 - mmengine - INFO - Epoch(val) [21][ 80/102] eta: 0:00:02 time: 0.1097 data_time: 0.0070 memory: 1697 09/30 14:43:59 - mmengine - INFO - Epoch(val) [21][ 85/102] eta: 0:00:01 time: 0.1095 data_time: 0.0071 memory: 1697 09/30 14:43:59 - mmengine - INFO - Epoch(val) [21][ 90/102] eta: 0:00:01 time: 0.1094 data_time: 0.0070 memory: 1697 09/30 14:44:00 - mmengine - INFO - Epoch(val) [21][ 95/102] eta: 0:00:00 time: 0.1092 data_time: 0.0070 memory: 1697 09/30 14:44:00 - mmengine - INFO - Epoch(val) [21][100/102] eta: 0:00:00 time: 0.1089 data_time: 0.0068 memory: 1697 09/30 14:44:00 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:44:00 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:44:00 - mmengine - INFO - Epoch(val) [21][102/102] data_time: 0.0133 time: 0.1159 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:44:03 - mmengine - INFO - Epoch(train) [22][ 5/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:39 time: 0.2862 data_time: 0.0394 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:04 - mmengine - INFO - Epoch(train) [22][10/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:37 time: 0.2861 data_time: 0.0395 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:06 - mmengine - INFO - Epoch(train) [22][15/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:35 time: 0.2849 data_time: 0.0388 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:07 - mmengine - INFO - Epoch(train) [22][20/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:33 time: 0.2853 data_time: 0.0386 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:08 - mmengine - INFO - Epoch(train) [22][25/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:32 time: 0.2861 data_time: 0.0389 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:09 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:44:10 - mmengine - INFO - Epoch(train) [22][30/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:30 time: 0.2861 data_time: 0.0388 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:11 - mmengine - INFO - Epoch(train) [22][35/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:28 time: 0.2855 data_time: 0.0386 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:12 - mmengine - INFO - Epoch(train) [22][40/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:26 time: 0.2874 data_time: 0.0389 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:14 - mmengine - INFO - Epoch(train) [22][45/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:24 time: 0.2891 data_time: 0.0389 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:15 - mmengine - INFO - Epoch(train) [22][50/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:22 time: 0.2931 data_time: 0.0391 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:16 - mmengine - INFO - Epoch(train) [22][55/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:20 time: 0.2635 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:18 - mmengine - INFO - Epoch(train) [22][60/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:19 time: 0.2637 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:19 - mmengine - INFO - Epoch(train) [22][65/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:17 time: 0.2650 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:20 - mmengine - INFO - Epoch(train) [22][70/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:15 time: 0.2646 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:22 - mmengine - INFO - Epoch(train) [22][75/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:13 time: 0.2641 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:23 - mmengine - INFO - Epoch(train) [22][80/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:11 time: 0.2644 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:24 - mmengine - INFO - Epoch(train) [22][85/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:09 time: 0.2634 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:26 - mmengine - INFO - Epoch(train) [22][90/94] base_lr: 8.1438e-03 lr: 8.1438e-03 eta: 0:35:07 time: 0.2625 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:26 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:44:26 - mmengine - INFO - Saving checkpoint at 22 epochs 09/30 14:44:29 - mmengine - INFO - Epoch(val) [22][ 5/102] eta: 0:00:26 time: 0.1249 data_time: 0.0227 memory: 11783 09/30 14:44:30 - mmengine - INFO - Epoch(val) [22][ 10/102] eta: 0:00:17 time: 0.1247 data_time: 0.0225 memory: 1697 09/30 14:44:30 - mmengine - INFO - Epoch(val) [22][ 15/102] eta: 0:00:14 time: 0.1247 data_time: 0.0223 memory: 1697 09/30 14:44:31 - mmengine - INFO - Epoch(val) [22][ 20/102] eta: 0:00:12 time: 0.1248 data_time: 0.0223 memory: 1697 09/30 14:44:31 - mmengine - INFO - Epoch(val) [22][ 25/102] eta: 0:00:10 time: 0.1248 data_time: 0.0222 memory: 1697 09/30 14:44:32 - mmengine - INFO - Epoch(val) [22][ 30/102] eta: 0:00:09 time: 0.1251 data_time: 0.0223 memory: 1697 09/30 14:44:32 - mmengine - INFO - Epoch(val) [22][ 35/102] eta: 0:00:08 time: 0.1253 data_time: 0.0223 memory: 1697 09/30 14:44:33 - mmengine - INFO - Epoch(val) [22][ 40/102] eta: 0:00:08 time: 0.1257 data_time: 0.0225 memory: 1697 09/30 14:44:33 - mmengine - INFO - Epoch(val) [22][ 45/102] eta: 0:00:07 time: 0.1260 data_time: 0.0227 memory: 1697 09/30 14:44:34 - mmengine - INFO - Epoch(val) [22][ 50/102] eta: 0:00:06 time: 0.1263 data_time: 0.0228 memory: 1697 09/30 14:44:35 - mmengine - INFO - Epoch(val) [22][ 55/102] eta: 0:00:05 time: 0.1104 data_time: 0.0069 memory: 1697 09/30 14:44:35 - mmengine - INFO - Epoch(val) [22][ 60/102] eta: 0:00:05 time: 0.1107 data_time: 0.0072 memory: 1697 09/30 14:44:36 - mmengine - INFO - Epoch(val) [22][ 65/102] eta: 0:00:04 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 14:44:36 - mmengine - INFO - Epoch(val) [22][ 70/102] eta: 0:00:03 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 14:44:37 - mmengine - INFO - Epoch(val) [22][ 75/102] eta: 0:00:03 time: 0.1112 data_time: 0.0076 memory: 1697 09/30 14:44:37 - mmengine - INFO - Epoch(val) [22][ 80/102] eta: 0:00:02 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 14:44:38 - mmengine - INFO - Epoch(val) [22][ 85/102] eta: 0:00:02 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 14:44:38 - mmengine - INFO - Epoch(val) [22][ 90/102] eta: 0:00:01 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 14:44:39 - mmengine - INFO - Epoch(val) [22][ 95/102] eta: 0:00:00 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 14:44:40 - mmengine - INFO - Epoch(val) [22][100/102] eta: 0:00:00 time: 0.1106 data_time: 0.0074 memory: 1697 09/30 14:44:40 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:44:40 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:44:40 - mmengine - INFO - Epoch(val) [22][102/102] data_time: 0.0149 time: 0.1182 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:44:43 - mmengine - INFO - Epoch(train) [23][ 5/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:35:09 time: 0.2925 data_time: 0.0445 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:44 - mmengine - INFO - Epoch(train) [23][10/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:35:07 time: 0.2925 data_time: 0.0441 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:45 - mmengine - INFO - Epoch(train) [23][15/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:35:05 time: 0.2920 data_time: 0.0440 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:47 - mmengine - INFO - Epoch(train) [23][20/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:35:03 time: 0.2923 data_time: 0.0438 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:48 - mmengine - INFO - Epoch(train) [23][25/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:35:02 time: 0.2926 data_time: 0.0436 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:49 - mmengine - INFO - Epoch(train) [23][30/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:35:00 time: 0.2924 data_time: 0.0434 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:51 - mmengine - INFO - Epoch(train) [23][35/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:58 time: 0.2924 data_time: 0.0434 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:52 - mmengine - INFO - Epoch(train) [23][40/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:56 time: 0.2931 data_time: 0.0433 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:53 - mmengine - INFO - Epoch(train) [23][45/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:54 time: 0.2949 data_time: 0.0435 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:55 - mmengine - INFO - Epoch(train) [23][50/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:53 time: 0.2988 data_time: 0.0435 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:56 - mmengine - INFO - Epoch(train) [23][55/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:51 time: 0.2654 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:57 - mmengine - INFO - Epoch(train) [23][60/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:49 time: 0.2652 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:44:59 - mmengine - INFO - Epoch(train) [23][65/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:47 time: 0.2652 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:00 - mmengine - INFO - Epoch(train) [23][70/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:45 time: 0.2650 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:01 - mmengine - INFO - Epoch(train) [23][75/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:43 time: 0.2649 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:03 - mmengine - INFO - Epoch(train) [23][80/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:42 time: 0.2647 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:04 - mmengine - INFO - Epoch(train) [23][85/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:40 time: 0.2635 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:05 - mmengine - INFO - Epoch(train) [23][90/94] base_lr: 8.0406e-03 lr: 8.0406e-03 eta: 0:34:38 time: 0.2625 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:06 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:45:06 - mmengine - INFO - Saving checkpoint at 23 epochs 09/30 14:45:09 - mmengine - INFO - Epoch(val) [23][ 5/102] eta: 0:00:25 time: 0.1259 data_time: 0.0227 memory: 11783 09/30 14:45:09 - mmengine - INFO - Epoch(val) [23][ 10/102] eta: 0:00:17 time: 0.1257 data_time: 0.0224 memory: 1697 09/30 14:45:10 - mmengine - INFO - Epoch(val) [23][ 15/102] eta: 0:00:13 time: 0.1254 data_time: 0.0221 memory: 1697 09/30 14:45:10 - mmengine - INFO - Epoch(val) [23][ 20/102] eta: 0:00:12 time: 0.1250 data_time: 0.0220 memory: 1697 09/30 14:45:11 - mmengine - INFO - Epoch(val) [23][ 25/102] eta: 0:00:10 time: 0.1248 data_time: 0.0219 memory: 1697 09/30 14:45:12 - mmengine - INFO - Epoch(val) [23][ 30/102] eta: 0:00:09 time: 0.1249 data_time: 0.0219 memory: 1697 09/30 14:45:12 - mmengine - INFO - Epoch(val) [23][ 35/102] eta: 0:00:08 time: 0.1247 data_time: 0.0217 memory: 1697 09/30 14:45:13 - mmengine - INFO - Epoch(val) [23][ 40/102] eta: 0:00:07 time: 0.1247 data_time: 0.0218 memory: 1697 09/30 14:45:13 - mmengine - INFO - Epoch(val) [23][ 45/102] eta: 0:00:07 time: 0.1246 data_time: 0.0218 memory: 1697 09/30 14:45:14 - mmengine - INFO - Epoch(val) [23][ 50/102] eta: 0:00:06 time: 0.1247 data_time: 0.0218 memory: 1697 09/30 14:45:14 - mmengine - INFO - Epoch(val) [23][ 55/102] eta: 0:00:05 time: 0.1093 data_time: 0.0064 memory: 1697 09/30 14:45:15 - mmengine - INFO - Epoch(val) [23][ 60/102] eta: 0:00:05 time: 0.1094 data_time: 0.0067 memory: 1697 09/30 14:45:15 - mmengine - INFO - Epoch(val) [23][ 65/102] eta: 0:00:04 time: 0.1096 data_time: 0.0069 memory: 1697 09/30 14:45:16 - mmengine - INFO - Epoch(val) [23][ 70/102] eta: 0:00:03 time: 0.1096 data_time: 0.0071 memory: 1697 09/30 14:45:16 - mmengine - INFO - Epoch(val) [23][ 75/102] eta: 0:00:03 time: 0.1097 data_time: 0.0072 memory: 1697 09/30 14:45:17 - mmengine - INFO - Epoch(val) [23][ 80/102] eta: 0:00:02 time: 0.1097 data_time: 0.0071 memory: 1697 09/30 14:45:18 - mmengine - INFO - Epoch(val) [23][ 85/102] eta: 0:00:02 time: 0.1096 data_time: 0.0072 memory: 1697 09/30 14:45:18 - mmengine - INFO - Epoch(val) [23][ 90/102] eta: 0:00:01 time: 0.1093 data_time: 0.0071 memory: 1697 09/30 14:45:19 - mmengine - INFO - Epoch(val) [23][ 95/102] eta: 0:00:00 time: 0.1093 data_time: 0.0071 memory: 1697 09/30 14:45:19 - mmengine - INFO - Epoch(val) [23][100/102] eta: 0:00:00 time: 0.1091 data_time: 0.0070 memory: 1697 09/30 14:45:19 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:45:19 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:45:19 - mmengine - INFO - Epoch(val) [23][102/102] data_time: 0.0142 time: 0.1166 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:45:22 - mmengine - INFO - Epoch(train) [24][ 5/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:38 time: 0.2855 data_time: 0.0368 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:23 - mmengine - INFO - Epoch(train) [24][10/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:36 time: 0.2847 data_time: 0.0361 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:25 - mmengine - INFO - Epoch(train) [24][15/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:34 time: 0.2846 data_time: 0.0360 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:26 - mmengine - INFO - Epoch(train) [24][20/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:33 time: 0.2847 data_time: 0.0359 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:27 - mmengine - INFO - Epoch(train) [24][25/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:31 time: 0.2848 data_time: 0.0357 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:29 - mmengine - INFO - Epoch(train) [24][30/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:29 time: 0.2850 data_time: 0.0356 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:30 - mmengine - INFO - Epoch(train) [24][35/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:27 time: 0.2854 data_time: 0.0356 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:31 - mmengine - INFO - Epoch(train) [24][40/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:25 time: 0.2859 data_time: 0.0355 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:33 - mmengine - INFO - Epoch(train) [24][45/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:24 time: 0.2870 data_time: 0.0355 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:34 - mmengine - INFO - Epoch(train) [24][50/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:22 time: 0.2910 data_time: 0.0358 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:35 - mmengine - INFO - Epoch(train) [24][55/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:20 time: 0.2636 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:37 - mmengine - INFO - Epoch(train) [24][60/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:18 time: 0.2635 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:38 - mmengine - INFO - Epoch(train) [24][65/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:16 time: 0.2644 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:39 - mmengine - INFO - Epoch(train) [24][70/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:15 time: 0.2647 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:41 - mmengine - INFO - Epoch(train) [24][75/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:13 time: 0.2650 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:42 - mmengine - INFO - Epoch(train) [24][80/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:11 time: 0.2650 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:43 - mmengine - INFO - Epoch(train) [24][85/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:09 time: 0.2640 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:45 - mmengine - INFO - Epoch(train) [24][90/94] base_lr: 7.9375e-03 lr: 7.9375e-03 eta: 0:34:07 time: 0.2631 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:45:45 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:45:45 - mmengine - INFO - Saving checkpoint at 24 epochs 09/30 14:45:50 - mmengine - INFO - Epoch(val) [24][ 5/102] eta: 0:00:24 time: 0.1228 data_time: 0.0208 memory: 11783 09/30 14:45:51 - mmengine - INFO - Epoch(val) [24][ 10/102] eta: 0:00:16 time: 0.1228 data_time: 0.0205 memory: 1697 09/30 14:45:51 - mmengine - INFO - Epoch(val) [24][ 15/102] eta: 0:00:13 time: 0.1227 data_time: 0.0202 memory: 1697 09/30 14:45:52 - mmengine - INFO - Epoch(val) [24][ 20/102] eta: 0:00:11 time: 0.1229 data_time: 0.0203 memory: 1697 09/30 14:45:52 - mmengine - INFO - Epoch(val) [24][ 25/102] eta: 0:00:10 time: 0.1227 data_time: 0.0202 memory: 1697 09/30 14:45:53 - mmengine - INFO - Epoch(val) [24][ 30/102] eta: 0:00:09 time: 0.1230 data_time: 0.0204 memory: 1697 09/30 14:45:53 - mmengine - INFO - Epoch(val) [24][ 35/102] eta: 0:00:08 time: 0.1227 data_time: 0.0202 memory: 1697 09/30 14:45:54 - mmengine - INFO - Epoch(val) [24][ 40/102] eta: 0:00:07 time: 0.1232 data_time: 0.0204 memory: 1697 09/30 14:45:55 - mmengine - INFO - Epoch(val) [24][ 45/102] eta: 0:00:07 time: 0.1234 data_time: 0.0205 memory: 1697 09/30 14:45:55 - mmengine - INFO - Epoch(val) [24][ 50/102] eta: 0:00:06 time: 0.1235 data_time: 0.0205 memory: 1697 09/30 14:45:56 - mmengine - INFO - Epoch(val) [24][ 55/102] eta: 0:00:05 time: 0.1096 data_time: 0.0067 memory: 1697 09/30 14:45:56 - mmengine - INFO - Epoch(val) [24][ 60/102] eta: 0:00:05 time: 0.1096 data_time: 0.0069 memory: 1697 09/30 14:45:57 - mmengine - INFO - Epoch(val) [24][ 65/102] eta: 0:00:04 time: 0.1100 data_time: 0.0073 memory: 1697 09/30 14:45:57 - mmengine - INFO - Epoch(val) [24][ 70/102] eta: 0:00:03 time: 0.1099 data_time: 0.0072 memory: 1697 09/30 14:45:58 - mmengine - INFO - Epoch(val) [24][ 75/102] eta: 0:00:03 time: 0.1100 data_time: 0.0073 memory: 1697 09/30 14:45:58 - mmengine - INFO - Epoch(val) [24][ 80/102] eta: 0:00:02 time: 0.1097 data_time: 0.0071 memory: 1697 09/30 14:45:59 - mmengine - INFO - Epoch(val) [24][ 85/102] eta: 0:00:02 time: 0.1099 data_time: 0.0073 memory: 1697 09/30 14:45:59 - mmengine - INFO - Epoch(val) [24][ 90/102] eta: 0:00:01 time: 0.1096 data_time: 0.0072 memory: 1697 09/30 14:46:00 - mmengine - INFO - Epoch(val) [24][ 95/102] eta: 0:00:00 time: 0.1097 data_time: 0.0072 memory: 1697 09/30 14:46:01 - mmengine - INFO - Epoch(val) [24][100/102] eta: 0:00:00 time: 0.1094 data_time: 0.0070 memory: 1697 09/30 14:46:01 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:46:01 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:46:01 - mmengine - INFO - Epoch(val) [24][102/102] data_time: 0.0136 time: 0.1162 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:46:03 - mmengine - INFO - Epoch(train) [25][ 5/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:34:07 time: 0.2824 data_time: 0.0320 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:05 - mmengine - INFO - Epoch(train) [25][10/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:34:05 time: 0.2826 data_time: 0.0320 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:06 - mmengine - INFO - Epoch(train) [25][15/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:34:03 time: 0.2828 data_time: 0.0317 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:07 - mmengine - INFO - Epoch(train) [25][20/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:34:02 time: 0.2814 data_time: 0.0316 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:09 - mmengine - INFO - Epoch(train) [25][25/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:34:00 time: 0.2807 data_time: 0.0316 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:10 - mmengine - INFO - Epoch(train) [25][30/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:58 time: 0.2809 data_time: 0.0317 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:11 - mmengine - INFO - Epoch(train) [25][35/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:56 time: 0.2810 data_time: 0.0318 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:12 - mmengine - INFO - Epoch(train) [25][40/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:55 time: 0.2817 data_time: 0.0318 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:14 - mmengine - INFO - Epoch(train) [25][45/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:53 time: 0.2834 data_time: 0.0318 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:15 - mmengine - INFO - Epoch(train) [25][50/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:51 time: 0.2874 data_time: 0.0320 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:17 - mmengine - INFO - Epoch(train) [25][55/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:49 time: 0.2651 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:18 - mmengine - INFO - Epoch(train) [25][60/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:48 time: 0.2650 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:19 - mmengine - INFO - Epoch(train) [25][65/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:46 time: 0.2653 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:20 - mmengine - INFO - Epoch(train) [25][70/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:44 time: 0.2655 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:22 - mmengine - INFO - Epoch(train) [25][75/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:42 time: 0.2659 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:23 - mmengine - INFO - Epoch(train) [25][80/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:41 time: 0.2659 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:24 - mmengine - INFO - Epoch(train) [25][85/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:39 time: 0.2644 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:26 - mmengine - INFO - Epoch(train) [25][90/94] base_lr: 7.8344e-03 lr: 7.8344e-03 eta: 0:33:37 time: 0.2635 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:27 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:46:27 - mmengine - INFO - Saving checkpoint at 25 epochs 09/30 14:46:29 - mmengine - INFO - Epoch(val) [25][ 5/102] eta: 0:00:26 time: 0.1255 data_time: 0.0229 memory: 11783 09/30 14:46:30 - mmengine - INFO - Epoch(val) [25][ 10/102] eta: 0:00:17 time: 0.1252 data_time: 0.0227 memory: 1697 09/30 14:46:30 - mmengine - INFO - Epoch(val) [25][ 15/102] eta: 0:00:14 time: 0.1250 data_time: 0.0224 memory: 1697 09/30 14:46:31 - mmengine - INFO - Epoch(val) [25][ 20/102] eta: 0:00:12 time: 0.1250 data_time: 0.0224 memory: 1697 09/30 14:46:31 - mmengine - INFO - Epoch(val) [25][ 25/102] eta: 0:00:10 time: 0.1250 data_time: 0.0223 memory: 1697 09/30 14:46:32 - mmengine - INFO - Epoch(val) [25][ 30/102] eta: 0:00:09 time: 0.1253 data_time: 0.0225 memory: 1697 09/30 14:46:32 - mmengine - INFO - Epoch(val) [25][ 35/102] eta: 0:00:08 time: 0.1252 data_time: 0.0223 memory: 1697 09/30 14:46:33 - mmengine - INFO - Epoch(val) [25][ 40/102] eta: 0:00:08 time: 0.1256 data_time: 0.0225 memory: 1697 09/30 14:46:34 - mmengine - INFO - Epoch(val) [25][ 45/102] eta: 0:00:07 time: 0.1257 data_time: 0.0226 memory: 1697 09/30 14:46:34 - mmengine - INFO - Epoch(val) [25][ 50/102] eta: 0:00:06 time: 0.1260 data_time: 0.0227 memory: 1697 09/30 14:46:35 - mmengine - INFO - Epoch(val) [25][ 55/102] eta: 0:00:05 time: 0.1100 data_time: 0.0069 memory: 1697 09/30 14:46:35 - mmengine - INFO - Epoch(val) [25][ 60/102] eta: 0:00:05 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 14:46:36 - mmengine - INFO - Epoch(val) [25][ 65/102] eta: 0:00:04 time: 0.1108 data_time: 0.0074 memory: 1697 09/30 14:46:36 - mmengine - INFO - Epoch(val) [25][ 70/102] eta: 0:00:03 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 14:46:37 - mmengine - INFO - Epoch(val) [25][ 75/102] eta: 0:00:03 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:46:37 - mmengine - INFO - Epoch(val) [25][ 80/102] eta: 0:00:02 time: 0.1107 data_time: 0.0075 memory: 1697 09/30 14:46:38 - mmengine - INFO - Epoch(val) [25][ 85/102] eta: 0:00:02 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:46:39 - mmengine - INFO - Epoch(val) [25][ 90/102] eta: 0:00:01 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:46:39 - mmengine - INFO - Epoch(val) [25][ 95/102] eta: 0:00:00 time: 0.1113 data_time: 0.0078 memory: 1697 09/30 14:46:40 - mmengine - INFO - Epoch(val) [25][100/102] eta: 0:00:00 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:46:40 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:46:40 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:46:40 - mmengine - INFO - Epoch(val) [25][102/102] data_time: 0.0150 time: 0.1183 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:46:43 - mmengine - INFO - Epoch(train) [26][ 5/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:38 time: 0.2930 data_time: 0.0437 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:44 - mmengine - INFO - Epoch(train) [26][10/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:36 time: 0.2919 data_time: 0.0435 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:45 - mmengine - INFO - Epoch(train) [26][15/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:34 time: 0.2914 data_time: 0.0427 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:47 - mmengine - INFO - Epoch(train) [26][20/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:33 time: 0.2914 data_time: 0.0431 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:48 - mmengine - INFO - Epoch(train) [26][25/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:31 time: 0.2908 data_time: 0.0425 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:49 - mmengine - INFO - Epoch(train) [26][30/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:29 time: 0.2903 data_time: 0.0424 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:51 - mmengine - INFO - Epoch(train) [26][35/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:27 time: 0.2907 data_time: 0.0427 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:52 - mmengine - INFO - Epoch(train) [26][40/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:26 time: 0.2912 data_time: 0.0425 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:53 - mmengine - INFO - Epoch(train) [26][45/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:24 time: 0.2926 data_time: 0.0426 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:55 - mmengine - INFO - Epoch(train) [26][50/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:22 time: 0.2966 data_time: 0.0427 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:56 - mmengine - INFO - Epoch(train) [26][55/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:20 time: 0.2630 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:57 - mmengine - INFO - Epoch(train) [26][60/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:19 time: 0.2635 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:46:59 - mmengine - INFO - Epoch(train) [26][65/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:17 time: 0.2638 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:00 - mmengine - INFO - Epoch(train) [26][70/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:15 time: 0.2639 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:01 - mmengine - INFO - Epoch(train) [26][75/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:13 time: 0.2643 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:03 - mmengine - INFO - Epoch(train) [26][80/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:12 time: 0.2642 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:04 - mmengine - INFO - Epoch(train) [26][85/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:10 time: 0.2678 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:05 - mmengine - INFO - Epoch(train) [26][90/94] base_lr: 7.7313e-03 lr: 7.7313e-03 eta: 0:33:08 time: 0.2665 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:06 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:47:06 - mmengine - INFO - Saving checkpoint at 26 epochs 09/30 14:47:09 - mmengine - INFO - Epoch(val) [26][ 5/102] eta: 0:00:26 time: 0.1273 data_time: 0.0239 memory: 11783 09/30 14:47:09 - mmengine - INFO - Epoch(val) [26][ 10/102] eta: 0:00:17 time: 0.1270 data_time: 0.0236 memory: 1697 09/30 14:47:10 - mmengine - INFO - Epoch(val) [26][ 15/102] eta: 0:00:14 time: 0.1265 data_time: 0.0233 memory: 1697 09/30 14:47:11 - mmengine - INFO - Epoch(val) [26][ 20/102] eta: 0:00:12 time: 0.1265 data_time: 0.0232 memory: 1697 09/30 14:47:11 - mmengine - INFO - Epoch(val) [26][ 25/102] eta: 0:00:10 time: 0.1264 data_time: 0.0231 memory: 1697 09/30 14:47:12 - mmengine - INFO - Epoch(val) [26][ 30/102] eta: 0:00:09 time: 0.1265 data_time: 0.0233 memory: 1697 09/30 14:47:12 - mmengine - INFO - Epoch(val) [26][ 35/102] eta: 0:00:08 time: 0.1262 data_time: 0.0229 memory: 1697 09/30 14:47:13 - mmengine - INFO - Epoch(val) [26][ 40/102] eta: 0:00:08 time: 0.1263 data_time: 0.0229 memory: 1697 09/30 14:47:13 - mmengine - INFO - Epoch(val) [26][ 45/102] eta: 0:00:07 time: 0.1264 data_time: 0.0230 memory: 1697 09/30 14:47:14 - mmengine - INFO - Epoch(val) [26][ 50/102] eta: 0:00:06 time: 0.1266 data_time: 0.0230 memory: 1697 09/30 14:47:14 - mmengine - INFO - Epoch(val) [26][ 55/102] eta: 0:00:05 time: 0.1102 data_time: 0.0068 memory: 1697 09/30 14:47:15 - mmengine - INFO - Epoch(val) [26][ 60/102] eta: 0:00:05 time: 0.1105 data_time: 0.0070 memory: 1697 09/30 14:47:16 - mmengine - INFO - Epoch(val) [26][ 65/102] eta: 0:00:04 time: 0.1108 data_time: 0.0073 memory: 1697 09/30 14:47:16 - mmengine - INFO - Epoch(val) [26][ 70/102] eta: 0:00:03 time: 0.1108 data_time: 0.0074 memory: 1697 09/30 14:47:17 - mmengine - INFO - Epoch(val) [26][ 75/102] eta: 0:00:03 time: 0.1107 data_time: 0.0075 memory: 1697 09/30 14:47:17 - mmengine - INFO - Epoch(val) [26][ 80/102] eta: 0:00:02 time: 0.1107 data_time: 0.0072 memory: 1697 09/30 14:47:18 - mmengine - INFO - Epoch(val) [26][ 85/102] eta: 0:00:02 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 14:47:18 - mmengine - INFO - Epoch(val) [26][ 90/102] eta: 0:00:01 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 14:47:19 - mmengine - INFO - Epoch(val) [26][ 95/102] eta: 0:00:00 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:47:19 - mmengine - INFO - Epoch(val) [26][100/102] eta: 0:00:00 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 14:47:20 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:47:20 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:47:20 - mmengine - INFO - Epoch(val) [26][102/102] data_time: 0.0150 time: 0.1185 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:47:22 - mmengine - INFO - Epoch(train) [27][ 5/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:33:09 time: 0.2901 data_time: 0.0369 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:24 - mmengine - INFO - Epoch(train) [27][10/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:33:07 time: 0.2903 data_time: 0.0371 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:25 - mmengine - INFO - Epoch(train) [27][15/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:33:05 time: 0.2901 data_time: 0.0364 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:26 - mmengine - INFO - Epoch(train) [27][20/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:33:04 time: 0.2908 data_time: 0.0368 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:28 - mmengine - INFO - Epoch(train) [27][25/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:33:02 time: 0.2905 data_time: 0.0361 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:29 - mmengine - INFO - Epoch(train) [27][30/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:33:00 time: 0.2904 data_time: 0.0360 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:30 - mmengine - INFO - Epoch(train) [27][35/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:58 time: 0.2910 data_time: 0.0359 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:32 - mmengine - INFO - Epoch(train) [27][40/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:57 time: 0.2876 data_time: 0.0359 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:33 - mmengine - INFO - Epoch(train) [27][45/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:55 time: 0.2887 data_time: 0.0359 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:34 - mmengine - INFO - Epoch(train) [27][50/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:53 time: 0.2924 data_time: 0.0361 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:36 - mmengine - INFO - Epoch(train) [27][55/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:51 time: 0.2649 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:37 - mmengine - INFO - Epoch(train) [27][60/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:50 time: 0.2647 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:38 - mmengine - INFO - Epoch(train) [27][65/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:48 time: 0.2652 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:40 - mmengine - INFO - Epoch(train) [27][70/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:46 time: 0.2646 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:41 - mmengine - INFO - Epoch(train) [27][75/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:45 time: 0.2647 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:42 - mmengine - INFO - Epoch(train) [27][80/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:43 time: 0.2648 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:43 - mmengine - INFO - Epoch(train) [27][85/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:41 time: 0.2634 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:45 - mmengine - INFO - Epoch(train) [27][90/94] base_lr: 7.6281e-03 lr: 7.6281e-03 eta: 0:32:39 time: 0.2618 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:47:46 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:47:46 - mmengine - INFO - Saving checkpoint at 27 epochs 09/30 14:47:48 - mmengine - INFO - Epoch(val) [27][ 5/102] eta: 0:00:26 time: 0.1272 data_time: 0.0239 memory: 11783 09/30 14:47:49 - mmengine - INFO - Epoch(val) [27][ 10/102] eta: 0:00:17 time: 0.1273 data_time: 0.0237 memory: 1697 09/30 14:47:50 - mmengine - INFO - Epoch(val) [27][ 15/102] eta: 0:00:14 time: 0.1270 data_time: 0.0234 memory: 1697 09/30 14:47:50 - mmengine - INFO - Epoch(val) [27][ 20/102] eta: 0:00:12 time: 0.1269 data_time: 0.0234 memory: 1697 09/30 14:47:51 - mmengine - INFO - Epoch(val) [27][ 25/102] eta: 0:00:10 time: 0.1268 data_time: 0.0232 memory: 1697 09/30 14:47:51 - mmengine - INFO - Epoch(val) [27][ 30/102] eta: 0:00:09 time: 0.1267 data_time: 0.0233 memory: 1697 09/30 14:47:52 - mmengine - INFO - Epoch(val) [27][ 35/102] eta: 0:00:08 time: 0.1264 data_time: 0.0231 memory: 1697 09/30 14:47:52 - mmengine - INFO - Epoch(val) [27][ 40/102] eta: 0:00:08 time: 0.1261 data_time: 0.0232 memory: 1697 09/30 14:47:53 - mmengine - INFO - Epoch(val) [27][ 45/102] eta: 0:00:07 time: 0.1260 data_time: 0.0231 memory: 1697 09/30 14:47:53 - mmengine - INFO - Epoch(val) [27][ 50/102] eta: 0:00:06 time: 0.1259 data_time: 0.0231 memory: 1697 09/30 14:47:54 - mmengine - INFO - Epoch(val) [27][ 55/102] eta: 0:00:05 time: 0.1094 data_time: 0.0066 memory: 1697 09/30 14:47:54 - mmengine - INFO - Epoch(val) [27][ 60/102] eta: 0:00:05 time: 0.1091 data_time: 0.0068 memory: 1697 09/30 14:47:55 - mmengine - INFO - Epoch(val) [27][ 65/102] eta: 0:00:04 time: 0.1095 data_time: 0.0071 memory: 1697 09/30 14:47:56 - mmengine - INFO - Epoch(val) [27][ 70/102] eta: 0:00:03 time: 0.1096 data_time: 0.0071 memory: 1697 09/30 14:47:56 - mmengine - INFO - Epoch(val) [27][ 75/102] eta: 0:00:03 time: 0.1098 data_time: 0.0072 memory: 1697 09/30 14:47:57 - mmengine - INFO - Epoch(val) [27][ 80/102] eta: 0:00:02 time: 0.1098 data_time: 0.0071 memory: 1697 09/30 14:47:57 - mmengine - INFO - Epoch(val) [27][ 85/102] eta: 0:00:02 time: 0.1101 data_time: 0.0072 memory: 1697 09/30 14:47:58 - mmengine - INFO - Epoch(val) [27][ 90/102] eta: 0:00:01 time: 0.1103 data_time: 0.0072 memory: 1697 09/30 14:47:58 - mmengine - INFO - Epoch(val) [27][ 95/102] eta: 0:00:00 time: 0.1102 data_time: 0.0072 memory: 1697 09/30 14:47:59 - mmengine - INFO - Epoch(val) [27][100/102] eta: 0:00:00 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 14:47:59 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:47:59 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:47:59 - mmengine - INFO - Epoch(val) [27][102/102] data_time: 0.0149 time: 0.1178 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:48:02 - mmengine - INFO - Epoch(train) [28][ 5/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:40 time: 0.2923 data_time: 0.0432 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:03 - mmengine - INFO - Epoch(train) [28][10/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:38 time: 0.2923 data_time: 0.0433 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:05 - mmengine - INFO - Epoch(train) [28][15/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:37 time: 0.2913 data_time: 0.0427 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:06 - mmengine - INFO - Epoch(train) [28][20/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:35 time: 0.2912 data_time: 0.0425 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:07 - mmengine - INFO - Epoch(train) [28][25/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:33 time: 0.2917 data_time: 0.0427 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:09 - mmengine - INFO - Epoch(train) [28][30/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:31 time: 0.2913 data_time: 0.0425 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:10 - mmengine - INFO - Epoch(train) [28][35/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:30 time: 0.2914 data_time: 0.0421 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:11 - mmengine - INFO - Epoch(train) [28][40/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:28 time: 0.2925 data_time: 0.0424 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:13 - mmengine - INFO - Epoch(train) [28][45/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:26 time: 0.2933 data_time: 0.0423 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:14 - mmengine - INFO - Epoch(train) [28][50/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:25 time: 0.2972 data_time: 0.0425 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:15 - mmengine - INFO - Epoch(train) [28][55/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:23 time: 0.2631 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:17 - mmengine - INFO - Epoch(train) [28][60/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:21 time: 0.2628 data_time: 0.0087 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:18 - mmengine - INFO - Epoch(train) [28][65/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:19 time: 0.2639 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:19 - mmengine - INFO - Epoch(train) [28][70/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:18 time: 0.2639 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:21 - mmengine - INFO - Epoch(train) [28][75/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:16 time: 0.2633 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:22 - mmengine - INFO - Epoch(train) [28][80/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:14 time: 0.2634 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:23 - mmengine - INFO - Epoch(train) [28][85/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:12 time: 0.2618 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:24 - mmengine - INFO - Epoch(train) [28][90/94] base_lr: 7.5250e-03 lr: 7.5250e-03 eta: 0:32:11 time: 0.2610 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:25 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:48:25 - mmengine - INFO - Saving checkpoint at 28 epochs 09/30 14:48:28 - mmengine - INFO - Epoch(val) [28][ 5/102] eta: 0:00:25 time: 0.1251 data_time: 0.0219 memory: 11783 09/30 14:48:29 - mmengine - INFO - Epoch(val) [28][ 10/102] eta: 0:00:16 time: 0.1246 data_time: 0.0217 memory: 1697 09/30 14:48:29 - mmengine - INFO - Epoch(val) [28][ 15/102] eta: 0:00:13 time: 0.1244 data_time: 0.0215 memory: 1697 09/30 14:48:30 - mmengine - INFO - Epoch(val) [28][ 20/102] eta: 0:00:11 time: 0.1244 data_time: 0.0214 memory: 1697 09/30 14:48:30 - mmengine - INFO - Epoch(val) [28][ 25/102] eta: 0:00:10 time: 0.1242 data_time: 0.0212 memory: 1697 09/30 14:48:31 - mmengine - INFO - Epoch(val) [28][ 30/102] eta: 0:00:09 time: 0.1245 data_time: 0.0215 memory: 1697 09/30 14:48:31 - mmengine - INFO - Epoch(val) [28][ 35/102] eta: 0:00:08 time: 0.1242 data_time: 0.0213 memory: 1697 09/30 14:48:32 - mmengine - INFO - Epoch(val) [28][ 40/102] eta: 0:00:07 time: 0.1246 data_time: 0.0215 memory: 1697 09/30 14:48:32 - mmengine - INFO - Epoch(val) [28][ 45/102] eta: 0:00:07 time: 0.1248 data_time: 0.0216 memory: 1697 09/30 14:48:33 - mmengine - INFO - Epoch(val) [28][ 50/102] eta: 0:00:06 time: 0.1249 data_time: 0.0216 memory: 1697 09/30 14:48:34 - mmengine - INFO - Epoch(val) [28][ 55/102] eta: 0:00:05 time: 0.1100 data_time: 0.0068 memory: 1697 09/30 14:48:34 - mmengine - INFO - Epoch(val) [28][ 60/102] eta: 0:00:05 time: 0.1104 data_time: 0.0070 memory: 1697 09/30 14:48:35 - mmengine - INFO - Epoch(val) [28][ 65/102] eta: 0:00:04 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 14:48:35 - mmengine - INFO - Epoch(val) [28][ 70/102] eta: 0:00:03 time: 0.1108 data_time: 0.0077 memory: 1697 09/30 14:48:36 - mmengine - INFO - Epoch(val) [28][ 75/102] eta: 0:00:03 time: 0.1114 data_time: 0.0081 memory: 1697 09/30 14:48:36 - mmengine - INFO - Epoch(val) [28][ 80/102] eta: 0:00:02 time: 0.1114 data_time: 0.0081 memory: 1697 09/30 14:48:37 - mmengine - INFO - Epoch(val) [28][ 85/102] eta: 0:00:02 time: 0.1119 data_time: 0.0084 memory: 1697 09/30 14:48:37 - mmengine - INFO - Epoch(val) [28][ 90/102] eta: 0:00:01 time: 0.1118 data_time: 0.0083 memory: 1697 09/30 14:48:38 - mmengine - INFO - Epoch(val) [28][ 95/102] eta: 0:00:00 time: 0.1119 data_time: 0.0084 memory: 1697 09/30 14:48:39 - mmengine - INFO - Epoch(val) [28][100/102] eta: 0:00:00 time: 0.1117 data_time: 0.0083 memory: 1697 09/30 14:48:39 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:48:39 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:48:39 - mmengine - INFO - Epoch(val) [28][102/102] data_time: 0.0147 time: 0.1180 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:48:41 - mmengine - INFO - Epoch(train) [29][ 5/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:32:10 time: 0.2827 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:43 - mmengine - INFO - Epoch(train) [29][10/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:32:09 time: 0.2834 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:44 - mmengine - INFO - Epoch(train) [29][15/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:32:07 time: 0.2834 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:45 - mmengine - INFO - Epoch(train) [29][20/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:32:05 time: 0.2830 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:47 - mmengine - INFO - Epoch(train) [29][25/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:32:03 time: 0.2828 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:48 - mmengine - INFO - Epoch(train) [29][30/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:32:02 time: 0.2835 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:49 - mmengine - INFO - Epoch(train) [29][35/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:32:00 time: 0.2837 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:51 - mmengine - INFO - Epoch(train) [29][40/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:58 time: 0.2851 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:52 - mmengine - INFO - Epoch(train) [29][45/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:57 time: 0.2864 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:53 - mmengine - INFO - Epoch(train) [29][50/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:55 time: 0.2903 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:55 - mmengine - INFO - Epoch(train) [29][55/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:53 time: 0.2654 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:56 - mmengine - INFO - Epoch(train) [29][60/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:52 time: 0.2651 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:57 - mmengine - INFO - Epoch(train) [29][65/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:50 time: 0.2662 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:48:59 - mmengine - INFO - Epoch(train) [29][70/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:49 time: 0.2672 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:00 - mmengine - INFO - Epoch(train) [29][75/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:47 time: 0.2681 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:01 - mmengine - INFO - Epoch(train) [29][80/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:45 time: 0.2670 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:03 - mmengine - INFO - Epoch(train) [29][85/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:44 time: 0.2659 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:04 - mmengine - INFO - Epoch(train) [29][90/94] base_lr: 7.4219e-03 lr: 7.4219e-03 eta: 0:31:42 time: 0.2649 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:05 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:49:05 - mmengine - INFO - Saving checkpoint at 29 epochs 09/30 14:49:07 - mmengine - INFO - Epoch(val) [29][ 5/102] eta: 0:00:25 time: 0.1274 data_time: 0.0239 memory: 11783 09/30 14:49:08 - mmengine - INFO - Epoch(val) [29][ 10/102] eta: 0:00:17 time: 0.1273 data_time: 0.0236 memory: 1697 09/30 14:49:09 - mmengine - INFO - Epoch(val) [29][ 15/102] eta: 0:00:13 time: 0.1268 data_time: 0.0232 memory: 1697 09/30 14:49:09 - mmengine - INFO - Epoch(val) [29][ 20/102] eta: 0:00:12 time: 0.1265 data_time: 0.0229 memory: 1697 09/30 14:49:10 - mmengine - INFO - Epoch(val) [29][ 25/102] eta: 0:00:10 time: 0.1258 data_time: 0.0225 memory: 1697 09/30 14:49:10 - mmengine - INFO - Epoch(val) [29][ 30/102] eta: 0:00:09 time: 0.1255 data_time: 0.0224 memory: 1697 09/30 14:49:11 - mmengine - INFO - Epoch(val) [29][ 35/102] eta: 0:00:08 time: 0.1249 data_time: 0.0220 memory: 1697 09/30 14:49:11 - mmengine - INFO - Epoch(val) [29][ 40/102] eta: 0:00:07 time: 0.1251 data_time: 0.0222 memory: 1697 09/30 14:49:12 - mmengine - INFO - Epoch(val) [29][ 45/102] eta: 0:00:07 time: 0.1252 data_time: 0.0222 memory: 1697 09/30 14:49:12 - mmengine - INFO - Epoch(val) [29][ 50/102] eta: 0:00:06 time: 0.1254 data_time: 0.0222 memory: 1697 09/30 14:49:13 - mmengine - INFO - Epoch(val) [29][ 55/102] eta: 0:00:05 time: 0.1098 data_time: 0.0067 memory: 1697 09/30 14:49:13 - mmengine - INFO - Epoch(val) [29][ 60/102] eta: 0:00:05 time: 0.1098 data_time: 0.0069 memory: 1697 09/30 14:49:14 - mmengine - INFO - Epoch(val) [29][ 65/102] eta: 0:00:04 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 14:49:15 - mmengine - INFO - Epoch(val) [29][ 70/102] eta: 0:00:03 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 14:49:15 - mmengine - INFO - Epoch(val) [29][ 75/102] eta: 0:00:03 time: 0.1107 data_time: 0.0075 memory: 1697 09/30 14:49:16 - mmengine - INFO - Epoch(val) [29][ 80/102] eta: 0:00:02 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 14:49:16 - mmengine - INFO - Epoch(val) [29][ 85/102] eta: 0:00:02 time: 0.1107 data_time: 0.0075 memory: 1697 09/30 14:49:17 - mmengine - INFO - Epoch(val) [29][ 90/102] eta: 0:00:01 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 14:49:17 - mmengine - INFO - Epoch(val) [29][ 95/102] eta: 0:00:00 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 14:49:18 - mmengine - INFO - Epoch(val) [29][100/102] eta: 0:00:00 time: 0.1102 data_time: 0.0074 memory: 1697 09/30 14:49:18 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:49:18 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:49:18 - mmengine - INFO - Epoch(val) [29][102/102] data_time: 0.0146 time: 0.1176 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:49:21 - mmengine - INFO - Epoch(train) [30][ 5/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:41 time: 0.2856 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:22 - mmengine - INFO - Epoch(train) [30][10/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:40 time: 0.2857 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:23 - mmengine - INFO - Epoch(train) [30][15/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:38 time: 0.2858 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:25 - mmengine - INFO - Epoch(train) [30][20/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:36 time: 0.2854 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:26 - mmengine - INFO - Epoch(train) [30][25/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:35 time: 0.2846 data_time: 0.0329 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:27 - mmengine - INFO - Epoch(train) [30][30/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:33 time: 0.2841 data_time: 0.0331 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:29 - mmengine - INFO - Epoch(train) [30][35/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:31 time: 0.2837 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:30 - mmengine - INFO - Epoch(train) [30][40/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:30 time: 0.2849 data_time: 0.0332 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:31 - mmengine - INFO - Epoch(train) [30][45/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:28 time: 0.2858 data_time: 0.0332 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:33 - mmengine - INFO - Epoch(train) [30][50/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:26 time: 0.2894 data_time: 0.0333 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:34 - mmengine - INFO - Epoch(train) [30][55/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:25 time: 0.2648 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:35 - mmengine - INFO - Epoch(train) [30][60/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:23 time: 0.2647 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:37 - mmengine - INFO - Epoch(train) [30][65/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:21 time: 0.2641 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:38 - mmengine - INFO - Epoch(train) [30][70/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:20 time: 0.2641 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:39 - mmengine - INFO - Epoch(train) [30][75/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:18 time: 0.2639 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:41 - mmengine - INFO - Epoch(train) [30][80/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:16 time: 0.2640 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:42 - mmengine - INFO - Epoch(train) [30][85/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:14 time: 0.2630 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:43 - mmengine - INFO - Epoch(train) [30][90/94] base_lr: 7.3188e-03 lr: 7.3188e-03 eta: 0:31:13 time: 0.2614 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:49:44 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:49:44 - mmengine - INFO - Saving checkpoint at 30 epochs 09/30 14:49:47 - mmengine - INFO - Epoch(val) [30][ 5/102] eta: 0:00:24 time: 0.1242 data_time: 0.0210 memory: 11783 09/30 14:49:47 - mmengine - INFO - Epoch(val) [30][ 10/102] eta: 0:00:16 time: 0.1239 data_time: 0.0207 memory: 1697 09/30 14:49:48 - mmengine - INFO - Epoch(val) [30][ 15/102] eta: 0:00:13 time: 0.1236 data_time: 0.0204 memory: 1697 09/30 14:49:48 - mmengine - INFO - Epoch(val) [30][ 20/102] eta: 0:00:11 time: 0.1235 data_time: 0.0203 memory: 1697 09/30 14:49:49 - mmengine - INFO - Epoch(val) [30][ 25/102] eta: 0:00:10 time: 0.1233 data_time: 0.0202 memory: 1697 09/30 14:49:49 - mmengine - INFO - Epoch(val) [30][ 30/102] eta: 0:00:09 time: 0.1235 data_time: 0.0204 memory: 1697 09/30 14:49:50 - mmengine - INFO - Epoch(val) [30][ 35/102] eta: 0:00:08 time: 0.1233 data_time: 0.0201 memory: 1697 09/30 14:49:50 - mmengine - INFO - Epoch(val) [30][ 40/102] eta: 0:00:07 time: 0.1236 data_time: 0.0202 memory: 1697 09/30 14:49:51 - mmengine - INFO - Epoch(val) [30][ 45/102] eta: 0:00:07 time: 0.1241 data_time: 0.0203 memory: 1697 09/30 14:49:52 - mmengine - INFO - Epoch(val) [30][ 50/102] eta: 0:00:06 time: 0.1243 data_time: 0.0204 memory: 1697 09/30 14:49:52 - mmengine - INFO - Epoch(val) [30][ 55/102] eta: 0:00:05 time: 0.1104 data_time: 0.0067 memory: 1697 09/30 14:49:53 - mmengine - INFO - Epoch(val) [30][ 60/102] eta: 0:00:05 time: 0.1106 data_time: 0.0069 memory: 1697 09/30 14:49:53 - mmengine - INFO - Epoch(val) [30][ 65/102] eta: 0:00:04 time: 0.1111 data_time: 0.0072 memory: 1697 09/30 14:49:54 - mmengine - INFO - Epoch(val) [30][ 70/102] eta: 0:00:03 time: 0.1110 data_time: 0.0072 memory: 1697 09/30 14:49:54 - mmengine - INFO - Epoch(val) [30][ 75/102] eta: 0:00:03 time: 0.1113 data_time: 0.0074 memory: 1697 09/30 14:49:55 - mmengine - INFO - Epoch(val) [30][ 80/102] eta: 0:00:02 time: 0.1110 data_time: 0.0072 memory: 1697 09/30 14:49:55 - mmengine - INFO - Epoch(val) [30][ 85/102] eta: 0:00:02 time: 0.1110 data_time: 0.0074 memory: 1697 09/30 14:49:56 - mmengine - INFO - Epoch(val) [30][ 90/102] eta: 0:00:01 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 14:49:57 - mmengine - INFO - Epoch(val) [30][ 95/102] eta: 0:00:00 time: 0.1104 data_time: 0.0075 memory: 1697 09/30 14:49:57 - mmengine - INFO - Epoch(val) [30][100/102] eta: 0:00:00 time: 0.1103 data_time: 0.0074 memory: 1697 09/30 14:49:57 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:49:57 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:49:57 - mmengine - INFO - Epoch(val) [30][102/102] data_time: 0.0137 time: 0.1170 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:50:00 - mmengine - INFO - Epoch(train) [31][ 5/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:31:13 time: 0.2879 data_time: 0.0398 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:01 - mmengine - INFO - Epoch(train) [31][10/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:31:11 time: 0.2882 data_time: 0.0400 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:03 - mmengine - INFO - Epoch(train) [31][15/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:31:09 time: 0.2874 data_time: 0.0392 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:04 - mmengine - INFO - Epoch(train) [31][20/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:31:08 time: 0.2873 data_time: 0.0388 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:05 - mmengine - INFO - Epoch(train) [31][25/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:31:06 time: 0.2871 data_time: 0.0387 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:07 - mmengine - INFO - Epoch(train) [31][30/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:31:04 time: 0.2876 data_time: 0.0389 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:08 - mmengine - INFO - Epoch(train) [31][35/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:31:03 time: 0.2878 data_time: 0.0390 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:09 - mmengine - INFO - Epoch(train) [31][40/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:31:01 time: 0.2885 data_time: 0.0390 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:11 - mmengine - INFO - Epoch(train) [31][45/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:59 time: 0.2898 data_time: 0.0388 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:12 - mmengine - INFO - Epoch(train) [31][50/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:58 time: 0.2938 data_time: 0.0392 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:13 - mmengine - INFO - Epoch(train) [31][55/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:56 time: 0.2646 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:15 - mmengine - INFO - Epoch(train) [31][60/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:55 time: 0.2652 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:16 - mmengine - INFO - Epoch(train) [31][65/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:53 time: 0.2664 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:17 - mmengine - INFO - Epoch(train) [31][70/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:51 time: 0.2675 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:19 - mmengine - INFO - Epoch(train) [31][75/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:50 time: 0.2676 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:20 - mmengine - INFO - Epoch(train) [31][80/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:48 time: 0.2679 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:21 - mmengine - INFO - Epoch(train) [31][85/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:46 time: 0.2663 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:23 - mmengine - INFO - Epoch(train) [31][90/94] base_lr: 7.2156e-03 lr: 7.2156e-03 eta: 0:30:45 time: 0.2654 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:24 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:50:24 - mmengine - INFO - Saving checkpoint at 31 epochs 09/30 14:50:26 - mmengine - INFO - Epoch(val) [31][ 5/102] eta: 0:00:25 time: 0.1252 data_time: 0.0224 memory: 11783 09/30 14:50:27 - mmengine - INFO - Epoch(val) [31][ 10/102] eta: 0:00:16 time: 0.1249 data_time: 0.0221 memory: 1697 09/30 14:50:27 - mmengine - INFO - Epoch(val) [31][ 15/102] eta: 0:00:13 time: 0.1245 data_time: 0.0218 memory: 1697 09/30 14:50:28 - mmengine - INFO - Epoch(val) [31][ 20/102] eta: 0:00:12 time: 0.1246 data_time: 0.0218 memory: 1697 09/30 14:50:29 - mmengine - INFO - Epoch(val) [31][ 25/102] eta: 0:00:10 time: 0.1245 data_time: 0.0217 memory: 1697 09/30 14:50:29 - mmengine - INFO - Epoch(val) [31][ 30/102] eta: 0:00:09 time: 0.1246 data_time: 0.0218 memory: 1697 09/30 14:50:30 - mmengine - INFO - Epoch(val) [31][ 35/102] eta: 0:00:08 time: 0.1243 data_time: 0.0216 memory: 1697 09/30 14:50:30 - mmengine - INFO - Epoch(val) [31][ 40/102] eta: 0:00:07 time: 0.1245 data_time: 0.0217 memory: 1697 09/30 14:50:31 - mmengine - INFO - Epoch(val) [31][ 45/102] eta: 0:00:07 time: 0.1245 data_time: 0.0217 memory: 1697 09/30 14:50:31 - mmengine - INFO - Epoch(val) [31][ 50/102] eta: 0:00:06 time: 0.1246 data_time: 0.0217 memory: 1697 09/30 14:50:32 - mmengine - INFO - Epoch(val) [31][ 55/102] eta: 0:00:05 time: 0.1094 data_time: 0.0066 memory: 1697 09/30 14:50:32 - mmengine - INFO - Epoch(val) [31][ 60/102] eta: 0:00:05 time: 0.1096 data_time: 0.0069 memory: 1697 09/30 14:50:33 - mmengine - INFO - Epoch(val) [31][ 65/102] eta: 0:00:04 time: 0.1099 data_time: 0.0072 memory: 1697 09/30 14:50:33 - mmengine - INFO - Epoch(val) [31][ 70/102] eta: 0:00:03 time: 0.1097 data_time: 0.0071 memory: 1697 09/30 14:50:34 - mmengine - INFO - Epoch(val) [31][ 75/102] eta: 0:00:03 time: 0.1097 data_time: 0.0072 memory: 1697 09/30 14:50:35 - mmengine - INFO - Epoch(val) [31][ 80/102] eta: 0:00:02 time: 0.1095 data_time: 0.0071 memory: 1697 09/30 14:50:35 - mmengine - INFO - Epoch(val) [31][ 85/102] eta: 0:00:02 time: 0.1095 data_time: 0.0072 memory: 1697 09/30 14:50:36 - mmengine - INFO - Epoch(val) [31][ 90/102] eta: 0:00:01 time: 0.1093 data_time: 0.0072 memory: 1697 09/30 14:50:36 - mmengine - INFO - Epoch(val) [31][ 95/102] eta: 0:00:00 time: 0.1094 data_time: 0.0072 memory: 1697 09/30 14:50:37 - mmengine - INFO - Epoch(val) [31][100/102] eta: 0:00:00 time: 0.1091 data_time: 0.0071 memory: 1697 09/30 14:50:37 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:50:37 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:50:37 - mmengine - INFO - Epoch(val) [31][102/102] data_time: 0.0142 time: 0.1166 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:50:39 - mmengine - INFO - Epoch(train) [32][ 5/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:44 time: 0.2857 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:41 - mmengine - INFO - Epoch(train) [32][10/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:42 time: 0.2839 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:42 - mmengine - INFO - Epoch(train) [32][15/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:40 time: 0.2827 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:43 - mmengine - INFO - Epoch(train) [32][20/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:39 time: 0.2829 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:45 - mmengine - INFO - Epoch(train) [32][25/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:37 time: 0.2820 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:46 - mmengine - INFO - Epoch(train) [32][30/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:36 time: 0.2812 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:47 - mmengine - INFO - Epoch(train) [32][35/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:34 time: 0.2801 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:49 - mmengine - INFO - Epoch(train) [32][40/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:32 time: 0.2816 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:50 - mmengine - INFO - Epoch(train) [32][45/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:31 time: 0.2830 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:51 - mmengine - INFO - Epoch(train) [32][50/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:29 time: 0.2868 data_time: 0.0331 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:53 - mmengine - INFO - Epoch(train) [32][55/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:27 time: 0.2625 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:54 - mmengine - INFO - Epoch(train) [32][60/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:26 time: 0.2630 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:55 - mmengine - INFO - Epoch(train) [32][65/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:24 time: 0.2635 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:57 - mmengine - INFO - Epoch(train) [32][70/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:22 time: 0.2628 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:58 - mmengine - INFO - Epoch(train) [32][75/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:21 time: 0.2635 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:50:59 - mmengine - INFO - Epoch(train) [32][80/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:19 time: 0.2644 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:00 - mmengine - INFO - Epoch(train) [32][85/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:17 time: 0.2634 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:01 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:51:02 - mmengine - INFO - Epoch(train) [32][90/94] base_lr: 7.1125e-03 lr: 7.1125e-03 eta: 0:30:16 time: 0.2617 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:03 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:51:03 - mmengine - INFO - Saving checkpoint at 32 epochs 09/30 14:51:07 - mmengine - INFO - Epoch(val) [32][ 5/102] eta: 0:00:24 time: 0.1234 data_time: 0.0207 memory: 11783 09/30 14:51:08 - mmengine - INFO - Epoch(val) [32][ 10/102] eta: 0:00:16 time: 0.1233 data_time: 0.0205 memory: 1697 09/30 14:51:08 - mmengine - INFO - Epoch(val) [32][ 15/102] eta: 0:00:13 time: 0.1230 data_time: 0.0202 memory: 1697 09/30 14:51:09 - mmengine - INFO - Epoch(val) [32][ 20/102] eta: 0:00:11 time: 0.1230 data_time: 0.0202 memory: 1697 09/30 14:51:10 - mmengine - INFO - Epoch(val) [32][ 25/102] eta: 0:00:10 time: 0.1230 data_time: 0.0201 memory: 1697 09/30 14:51:10 - mmengine - INFO - Epoch(val) [32][ 30/102] eta: 0:00:09 time: 0.1233 data_time: 0.0202 memory: 1697 09/30 14:51:11 - mmengine - INFO - Epoch(val) [32][ 35/102] eta: 0:00:08 time: 0.1233 data_time: 0.0200 memory: 1697 09/30 14:51:11 - mmengine - INFO - Epoch(val) [32][ 40/102] eta: 0:00:07 time: 0.1234 data_time: 0.0201 memory: 1697 09/30 14:51:12 - mmengine - INFO - Epoch(val) [32][ 45/102] eta: 0:00:07 time: 0.1234 data_time: 0.0201 memory: 1697 09/30 14:51:12 - mmengine - INFO - Epoch(val) [32][ 50/102] eta: 0:00:06 time: 0.1234 data_time: 0.0201 memory: 1697 09/30 14:51:13 - mmengine - INFO - Epoch(val) [32][ 55/102] eta: 0:00:05 time: 0.1093 data_time: 0.0064 memory: 1697 09/30 14:51:13 - mmengine - INFO - Epoch(val) [32][ 60/102] eta: 0:00:05 time: 0.1094 data_time: 0.0066 memory: 1697 09/30 14:51:14 - mmengine - INFO - Epoch(val) [32][ 65/102] eta: 0:00:04 time: 0.1097 data_time: 0.0069 memory: 1697 09/30 14:51:15 - mmengine - INFO - Epoch(val) [32][ 70/102] eta: 0:00:03 time: 0.1098 data_time: 0.0069 memory: 1697 09/30 14:51:15 - mmengine - INFO - Epoch(val) [32][ 75/102] eta: 0:00:03 time: 0.1100 data_time: 0.0070 memory: 1697 09/30 14:51:16 - mmengine - INFO - Epoch(val) [32][ 80/102] eta: 0:00:02 time: 0.1099 data_time: 0.0069 memory: 1697 09/30 14:51:16 - mmengine - INFO - Epoch(val) [32][ 85/102] eta: 0:00:02 time: 0.1098 data_time: 0.0069 memory: 1697 09/30 14:51:17 - mmengine - INFO - Epoch(val) [32][ 90/102] eta: 0:00:01 time: 0.1098 data_time: 0.0070 memory: 1697 09/30 14:51:17 - mmengine - INFO - Epoch(val) [32][ 95/102] eta: 0:00:00 time: 0.1099 data_time: 0.0070 memory: 1697 09/30 14:51:18 - mmengine - INFO - Epoch(val) [32][100/102] eta: 0:00:00 time: 0.1099 data_time: 0.0071 memory: 1697 09/30 14:51:18 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:51:18 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:51:18 - mmengine - INFO - Epoch(val) [32][102/102] data_time: 0.0134 time: 0.1164 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:51:20 - mmengine - INFO - Epoch(train) [33][ 5/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:14 time: 0.2729 data_time: 0.0243 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:21 - mmengine - INFO - Epoch(train) [33][10/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:12 time: 0.2740 data_time: 0.0245 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:23 - mmengine - INFO - Epoch(train) [33][15/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:11 time: 0.2737 data_time: 0.0242 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:24 - mmengine - INFO - Epoch(train) [33][20/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:09 time: 0.2742 data_time: 0.0241 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:25 - mmengine - INFO - Epoch(train) [33][25/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:07 time: 0.2739 data_time: 0.0238 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:27 - mmengine - INFO - Epoch(train) [33][30/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:06 time: 0.2732 data_time: 0.0239 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:28 - mmengine - INFO - Epoch(train) [33][35/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:04 time: 0.2737 data_time: 0.0237 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:29 - mmengine - INFO - Epoch(train) [33][40/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:03 time: 0.2753 data_time: 0.0236 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:31 - mmengine - INFO - Epoch(train) [33][45/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:30:01 time: 0.2760 data_time: 0.0236 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:32 - mmengine - INFO - Epoch(train) [33][50/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:59 time: 0.2802 data_time: 0.0236 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:33 - mmengine - INFO - Epoch(train) [33][55/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:58 time: 0.2658 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:35 - mmengine - INFO - Epoch(train) [33][60/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:56 time: 0.2649 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:36 - mmengine - INFO - Epoch(train) [33][65/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:55 time: 0.2658 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:38 - mmengine - INFO - Epoch(train) [33][70/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:53 time: 0.2706 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:39 - mmengine - INFO - Epoch(train) [33][75/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:52 time: 0.2704 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:40 - mmengine - INFO - Epoch(train) [33][80/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:50 time: 0.2704 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:41 - mmengine - INFO - Epoch(train) [33][85/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:48 time: 0.2680 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:43 - mmengine - INFO - Epoch(train) [33][90/94] base_lr: 7.0094e-03 lr: 7.0094e-03 eta: 0:29:47 time: 0.2662 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:51:44 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:51:44 - mmengine - INFO - Saving checkpoint at 33 epochs 09/30 14:51:47 - mmengine - INFO - Epoch(val) [33][ 5/102] eta: 0:00:21 time: 0.1214 data_time: 0.0182 memory: 11783 09/30 14:51:47 - mmengine - INFO - Epoch(val) [33][ 10/102] eta: 0:00:15 time: 0.1212 data_time: 0.0180 memory: 1697 09/30 14:51:48 - mmengine - INFO - Epoch(val) [33][ 15/102] eta: 0:00:12 time: 0.1207 data_time: 0.0177 memory: 1697 09/30 14:51:48 - mmengine - INFO - Epoch(val) [33][ 20/102] eta: 0:00:11 time: 0.1205 data_time: 0.0177 memory: 1697 09/30 14:51:49 - mmengine - INFO - Epoch(val) [33][ 25/102] eta: 0:00:10 time: 0.1206 data_time: 0.0176 memory: 1697 09/30 14:51:49 - mmengine - INFO - Epoch(val) [33][ 30/102] eta: 0:00:09 time: 0.1208 data_time: 0.0178 memory: 1697 09/30 14:51:50 - mmengine - INFO - Epoch(val) [33][ 35/102] eta: 0:00:08 time: 0.1209 data_time: 0.0176 memory: 1697 09/30 14:51:50 - mmengine - INFO - Epoch(val) [33][ 40/102] eta: 0:00:07 time: 0.1212 data_time: 0.0177 memory: 1697 09/30 14:51:51 - mmengine - INFO - Epoch(val) [33][ 45/102] eta: 0:00:06 time: 0.1214 data_time: 0.0178 memory: 1697 09/30 14:51:51 - mmengine - INFO - Epoch(val) [33][ 50/102] eta: 0:00:06 time: 0.1214 data_time: 0.0176 memory: 1697 09/30 14:51:52 - mmengine - INFO - Epoch(val) [33][ 55/102] eta: 0:00:05 time: 0.1099 data_time: 0.0065 memory: 1697 09/30 14:51:53 - mmengine - INFO - Epoch(val) [33][ 60/102] eta: 0:00:05 time: 0.1100 data_time: 0.0067 memory: 1697 09/30 14:51:53 - mmengine - INFO - Epoch(val) [33][ 65/102] eta: 0:00:04 time: 0.1105 data_time: 0.0070 memory: 1697 09/30 14:51:54 - mmengine - INFO - Epoch(val) [33][ 70/102] eta: 0:00:03 time: 0.1103 data_time: 0.0070 memory: 1697 09/30 14:51:54 - mmengine - INFO - Epoch(val) [33][ 75/102] eta: 0:00:03 time: 0.1105 data_time: 0.0072 memory: 1697 09/30 14:51:55 - mmengine - INFO - Epoch(val) [33][ 80/102] eta: 0:00:02 time: 0.1101 data_time: 0.0070 memory: 1697 09/30 14:51:55 - mmengine - INFO - Epoch(val) [33][ 85/102] eta: 0:00:01 time: 0.1100 data_time: 0.0071 memory: 1697 09/30 14:51:56 - mmengine - INFO - Epoch(val) [33][ 90/102] eta: 0:00:01 time: 0.1098 data_time: 0.0071 memory: 1697 09/30 14:51:56 - mmengine - INFO - Epoch(val) [33][ 95/102] eta: 0:00:00 time: 0.1096 data_time: 0.0071 memory: 1697 09/30 14:51:57 - mmengine - INFO - Epoch(val) [33][100/102] eta: 0:00:00 time: 0.1093 data_time: 0.0069 memory: 1697 09/30 14:51:57 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:51:57 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:51:57 - mmengine - INFO - Epoch(val) [33][102/102] data_time: 0.0121 time: 0.1151 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:52:00 - mmengine - INFO - Epoch(train) [34][ 5/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:45 time: 0.2829 data_time: 0.0292 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:01 - mmengine - INFO - Epoch(train) [34][10/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:44 time: 0.2830 data_time: 0.0297 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:02 - mmengine - INFO - Epoch(train) [34][15/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:42 time: 0.2821 data_time: 0.0293 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:03 - mmengine - INFO - Epoch(train) [34][20/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:41 time: 0.2819 data_time: 0.0291 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:05 - mmengine - INFO - Epoch(train) [34][25/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:39 time: 0.2814 data_time: 0.0292 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:06 - mmengine - INFO - Epoch(train) [34][30/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:37 time: 0.2772 data_time: 0.0291 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:07 - mmengine - INFO - Epoch(train) [34][35/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:36 time: 0.2767 data_time: 0.0292 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:09 - mmengine - INFO - Epoch(train) [34][40/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:34 time: 0.2781 data_time: 0.0293 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:10 - mmengine - INFO - Epoch(train) [34][45/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:32 time: 0.2801 data_time: 0.0293 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:11 - mmengine - INFO - Epoch(train) [34][50/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:31 time: 0.2848 data_time: 0.0297 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:13 - mmengine - INFO - Epoch(train) [34][55/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:29 time: 0.2642 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:14 - mmengine - INFO - Epoch(train) [34][60/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:28 time: 0.2638 data_time: 0.0087 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:15 - mmengine - INFO - Epoch(train) [34][65/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:26 time: 0.2645 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:17 - mmengine - INFO - Epoch(train) [34][70/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:24 time: 0.2643 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:18 - mmengine - INFO - Epoch(train) [34][75/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:23 time: 0.2641 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:19 - mmengine - INFO - Epoch(train) [34][80/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:21 time: 0.2639 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:21 - mmengine - INFO - Epoch(train) [34][85/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:19 time: 0.2628 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:22 - mmengine - INFO - Epoch(train) [34][90/94] base_lr: 6.9063e-03 lr: 6.9063e-03 eta: 0:29:18 time: 0.2615 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:23 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:52:23 - mmengine - INFO - Saving checkpoint at 34 epochs 09/30 14:52:25 - mmengine - INFO - Epoch(val) [34][ 5/102] eta: 0:00:23 time: 0.1226 data_time: 0.0204 memory: 11783 09/30 14:52:26 - mmengine - INFO - Epoch(val) [34][ 10/102] eta: 0:00:16 time: 0.1223 data_time: 0.0201 memory: 1697 09/30 14:52:26 - mmengine - INFO - Epoch(val) [34][ 15/102] eta: 0:00:13 time: 0.1222 data_time: 0.0198 memory: 1697 09/30 14:52:27 - mmengine - INFO - Epoch(val) [34][ 20/102] eta: 0:00:11 time: 0.1220 data_time: 0.0197 memory: 1697 09/30 14:52:28 - mmengine - INFO - Epoch(val) [34][ 25/102] eta: 0:00:10 time: 0.1218 data_time: 0.0196 memory: 1697 09/30 14:52:28 - mmengine - INFO - Epoch(val) [34][ 30/102] eta: 0:00:09 time: 0.1218 data_time: 0.0197 memory: 1697 09/30 14:52:29 - mmengine - INFO - Epoch(val) [34][ 35/102] eta: 0:00:08 time: 0.1217 data_time: 0.0195 memory: 1697 09/30 14:52:29 - mmengine - INFO - Epoch(val) [34][ 40/102] eta: 0:00:07 time: 0.1220 data_time: 0.0196 memory: 1697 09/30 14:52:30 - mmengine - INFO - Epoch(val) [34][ 45/102] eta: 0:00:07 time: 0.1220 data_time: 0.0197 memory: 1697 09/30 14:52:30 - mmengine - INFO - Epoch(val) [34][ 50/102] eta: 0:00:06 time: 0.1222 data_time: 0.0197 memory: 1697 09/30 14:52:31 - mmengine - INFO - Epoch(val) [34][ 55/102] eta: 0:00:05 time: 0.1089 data_time: 0.0062 memory: 1697 09/30 14:52:31 - mmengine - INFO - Epoch(val) [34][ 60/102] eta: 0:00:05 time: 0.1091 data_time: 0.0065 memory: 1697 09/30 14:52:32 - mmengine - INFO - Epoch(val) [34][ 65/102] eta: 0:00:04 time: 0.1093 data_time: 0.0068 memory: 1697 09/30 14:52:32 - mmengine - INFO - Epoch(val) [34][ 70/102] eta: 0:00:03 time: 0.1095 data_time: 0.0069 memory: 1697 09/30 14:52:33 - mmengine - INFO - Epoch(val) [34][ 75/102] eta: 0:00:03 time: 0.1099 data_time: 0.0071 memory: 1697 09/30 14:52:34 - mmengine - INFO - Epoch(val) [34][ 80/102] eta: 0:00:02 time: 0.1101 data_time: 0.0070 memory: 1697 09/30 14:52:34 - mmengine - INFO - Epoch(val) [34][ 85/102] eta: 0:00:01 time: 0.1103 data_time: 0.0072 memory: 1697 09/30 14:52:35 - mmengine - INFO - Epoch(val) [34][ 90/102] eta: 0:00:01 time: 0.1101 data_time: 0.0071 memory: 1697 09/30 14:52:35 - mmengine - INFO - Epoch(val) [34][ 95/102] eta: 0:00:00 time: 0.1102 data_time: 0.0072 memory: 1697 09/30 14:52:36 - mmengine - INFO - Epoch(val) [34][100/102] eta: 0:00:00 time: 0.1101 data_time: 0.0071 memory: 1697 09/30 14:52:36 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:52:36 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:52:36 - mmengine - INFO - Epoch(val) [34][102/102] data_time: 0.0132 time: 0.1160 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:52:38 - mmengine - INFO - Epoch(train) [35][ 5/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:16 time: 0.2779 data_time: 0.0290 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:40 - mmengine - INFO - Epoch(train) [35][10/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:15 time: 0.2774 data_time: 0.0290 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:41 - mmengine - INFO - Epoch(train) [35][15/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:13 time: 0.2778 data_time: 0.0290 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:42 - mmengine - INFO - Epoch(train) [35][20/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:12 time: 0.2771 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:44 - mmengine - INFO - Epoch(train) [35][25/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:10 time: 0.2772 data_time: 0.0287 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:45 - mmengine - INFO - Epoch(train) [35][30/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:08 time: 0.2775 data_time: 0.0287 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:46 - mmengine - INFO - Epoch(train) [35][35/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:07 time: 0.2776 data_time: 0.0286 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:48 - mmengine - INFO - Epoch(train) [35][40/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:05 time: 0.2787 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:49 - mmengine - INFO - Epoch(train) [35][45/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:04 time: 0.2797 data_time: 0.0286 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:50 - mmengine - INFO - Epoch(train) [35][50/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:02 time: 0.2835 data_time: 0.0289 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:52 - mmengine - INFO - Epoch(train) [35][55/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:29:00 time: 0.2630 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:53 - mmengine - INFO - Epoch(train) [35][60/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:28:59 time: 0.2633 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:54 - mmengine - INFO - Epoch(train) [35][65/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:28:57 time: 0.2637 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:55 - mmengine - INFO - Epoch(train) [35][70/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:28:56 time: 0.2636 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:57 - mmengine - INFO - Epoch(train) [35][75/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:28:54 time: 0.2639 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:58 - mmengine - INFO - Epoch(train) [35][80/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:28:52 time: 0.2636 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:52:59 - mmengine - INFO - Epoch(train) [35][85/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:28:51 time: 0.2621 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:01 - mmengine - INFO - Epoch(train) [35][90/94] base_lr: 6.8031e-03 lr: 6.8031e-03 eta: 0:28:49 time: 0.2612 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:01 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:53:01 - mmengine - INFO - Saving checkpoint at 35 epochs 09/30 14:53:04 - mmengine - INFO - Epoch(val) [35][ 5/102] eta: 0:00:25 time: 0.1252 data_time: 0.0221 memory: 11783 09/30 14:53:05 - mmengine - INFO - Epoch(val) [35][ 10/102] eta: 0:00:17 time: 0.1253 data_time: 0.0219 memory: 1697 09/30 14:53:05 - mmengine - INFO - Epoch(val) [35][ 15/102] eta: 0:00:13 time: 0.1254 data_time: 0.0217 memory: 1697 09/30 14:53:06 - mmengine - INFO - Epoch(val) [35][ 20/102] eta: 0:00:12 time: 0.1252 data_time: 0.0216 memory: 1697 09/30 14:53:06 - mmengine - INFO - Epoch(val) [35][ 25/102] eta: 0:00:10 time: 0.1249 data_time: 0.0214 memory: 1697 09/30 14:53:07 - mmengine - INFO - Epoch(val) [35][ 30/102] eta: 0:00:09 time: 0.1250 data_time: 0.0217 memory: 1697 09/30 14:53:08 - mmengine - INFO - Epoch(val) [35][ 35/102] eta: 0:00:08 time: 0.1247 data_time: 0.0213 memory: 1697 09/30 14:53:08 - mmengine - INFO - Epoch(val) [35][ 40/102] eta: 0:00:07 time: 0.1250 data_time: 0.0215 memory: 1697 09/30 14:53:09 - mmengine - INFO - Epoch(val) [35][ 45/102] eta: 0:00:07 time: 0.1254 data_time: 0.0216 memory: 1697 09/30 14:53:09 - mmengine - INFO - Epoch(val) [35][ 50/102] eta: 0:00:06 time: 0.1255 data_time: 0.0217 memory: 1697 09/30 14:53:10 - mmengine - INFO - Epoch(val) [35][ 55/102] eta: 0:00:05 time: 0.1104 data_time: 0.0068 memory: 1697 09/30 14:53:10 - mmengine - INFO - Epoch(val) [35][ 60/102] eta: 0:00:05 time: 0.1106 data_time: 0.0071 memory: 1697 09/30 14:53:11 - mmengine - INFO - Epoch(val) [35][ 65/102] eta: 0:00:04 time: 0.1109 data_time: 0.0074 memory: 1697 09/30 14:53:12 - mmengine - INFO - Epoch(val) [35][ 70/102] eta: 0:00:03 time: 0.1111 data_time: 0.0075 memory: 1697 09/30 14:53:12 - mmengine - INFO - Epoch(val) [35][ 75/102] eta: 0:00:03 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 14:53:13 - mmengine - INFO - Epoch(val) [35][ 80/102] eta: 0:00:02 time: 0.1110 data_time: 0.0074 memory: 1697 09/30 14:53:13 - mmengine - INFO - Epoch(val) [35][ 85/102] eta: 0:00:02 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 14:53:14 - mmengine - INFO - Epoch(val) [35][ 90/102] eta: 0:00:01 time: 0.1112 data_time: 0.0076 memory: 1697 09/30 14:53:14 - mmengine - INFO - Epoch(val) [35][ 95/102] eta: 0:00:00 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 14:53:15 - mmengine - INFO - Epoch(val) [35][100/102] eta: 0:00:00 time: 0.1107 data_time: 0.0075 memory: 1697 09/30 14:53:15 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:53:15 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:53:15 - mmengine - INFO - Epoch(val) [35][102/102] data_time: 0.0144 time: 0.1179 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:53:17 - mmengine - INFO - Epoch(train) [36][ 5/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:48 time: 0.2803 data_time: 0.0324 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:19 - mmengine - INFO - Epoch(train) [36][10/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:46 time: 0.2808 data_time: 0.0325 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:20 - mmengine - INFO - Epoch(train) [36][15/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:45 time: 0.2816 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:22 - mmengine - INFO - Epoch(train) [36][20/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:43 time: 0.2808 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:23 - mmengine - INFO - Epoch(train) [36][25/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:42 time: 0.2808 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:24 - mmengine - INFO - Epoch(train) [36][30/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:40 time: 0.2810 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:26 - mmengine - INFO - Epoch(train) [36][35/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:39 time: 0.2826 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:27 - mmengine - INFO - Epoch(train) [36][40/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:37 time: 0.2846 data_time: 0.0324 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:28 - mmengine - INFO - Epoch(train) [36][45/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:36 time: 0.2868 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:30 - mmengine - INFO - Epoch(train) [36][50/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:34 time: 0.2932 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:31 - mmengine - INFO - Epoch(train) [36][55/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:33 time: 0.2705 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:32 - mmengine - INFO - Epoch(train) [36][60/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:31 time: 0.2702 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:34 - mmengine - INFO - Epoch(train) [36][65/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:29 time: 0.2694 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:35 - mmengine - INFO - Epoch(train) [36][70/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:28 time: 0.2697 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:36 - mmengine - INFO - Epoch(train) [36][75/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:26 time: 0.2695 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:38 - mmengine - INFO - Epoch(train) [36][80/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:25 time: 0.2694 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:39 - mmengine - INFO - Epoch(train) [36][85/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:23 time: 0.2667 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:40 - mmengine - INFO - Epoch(train) [36][90/94] base_lr: 6.7000e-03 lr: 6.7000e-03 eta: 0:28:21 time: 0.2642 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:41 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:53:41 - mmengine - INFO - Saving checkpoint at 36 epochs 09/30 14:53:44 - mmengine - INFO - Epoch(val) [36][ 5/102] eta: 0:00:25 time: 0.1255 data_time: 0.0227 memory: 11783 09/30 14:53:44 - mmengine - INFO - Epoch(val) [36][ 10/102] eta: 0:00:16 time: 0.1249 data_time: 0.0224 memory: 1697 09/30 14:53:45 - mmengine - INFO - Epoch(val) [36][ 15/102] eta: 0:00:13 time: 0.1245 data_time: 0.0221 memory: 1697 09/30 14:53:45 - mmengine - INFO - Epoch(val) [36][ 20/102] eta: 0:00:11 time: 0.1242 data_time: 0.0219 memory: 1697 09/30 14:53:46 - mmengine - INFO - Epoch(val) [36][ 25/102] eta: 0:00:10 time: 0.1240 data_time: 0.0217 memory: 1697 09/30 14:53:46 - mmengine - INFO - Epoch(val) [36][ 30/102] eta: 0:00:09 time: 0.1238 data_time: 0.0217 memory: 1697 09/30 14:53:47 - mmengine - INFO - Epoch(val) [36][ 35/102] eta: 0:00:08 time: 0.1236 data_time: 0.0215 memory: 1697 09/30 14:53:47 - mmengine - INFO - Epoch(val) [36][ 40/102] eta: 0:00:07 time: 0.1237 data_time: 0.0215 memory: 1697 09/30 14:53:48 - mmengine - INFO - Epoch(val) [36][ 45/102] eta: 0:00:07 time: 0.1235 data_time: 0.0215 memory: 1697 09/30 14:53:48 - mmengine - INFO - Epoch(val) [36][ 50/102] eta: 0:00:06 time: 0.1235 data_time: 0.0214 memory: 1697 09/30 14:53:49 - mmengine - INFO - Epoch(val) [36][ 55/102] eta: 0:00:05 time: 0.1084 data_time: 0.0061 memory: 1697 09/30 14:53:49 - mmengine - INFO - Epoch(val) [36][ 60/102] eta: 0:00:05 time: 0.1086 data_time: 0.0063 memory: 1697 09/30 14:53:50 - mmengine - INFO - Epoch(val) [36][ 65/102] eta: 0:00:04 time: 0.1089 data_time: 0.0065 memory: 1697 09/30 14:53:51 - mmengine - INFO - Epoch(val) [36][ 70/102] eta: 0:00:03 time: 0.1091 data_time: 0.0067 memory: 1697 09/30 14:53:51 - mmengine - INFO - Epoch(val) [36][ 75/102] eta: 0:00:03 time: 0.1091 data_time: 0.0068 memory: 1697 09/30 14:53:52 - mmengine - INFO - Epoch(val) [36][ 80/102] eta: 0:00:02 time: 0.1092 data_time: 0.0067 memory: 1697 09/30 14:53:52 - mmengine - INFO - Epoch(val) [36][ 85/102] eta: 0:00:02 time: 0.1092 data_time: 0.0068 memory: 1697 09/30 14:53:53 - mmengine - INFO - Epoch(val) [36][ 90/102] eta: 0:00:01 time: 0.1090 data_time: 0.0067 memory: 1697 09/30 14:53:53 - mmengine - INFO - Epoch(val) [36][ 95/102] eta: 0:00:00 time: 0.1090 data_time: 0.0068 memory: 1697 09/30 14:53:54 - mmengine - INFO - Epoch(val) [36][100/102] eta: 0:00:00 time: 0.1089 data_time: 0.0067 memory: 1697 09/30 14:53:54 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:53:54 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:53:54 - mmengine - INFO - Epoch(val) [36][102/102] data_time: 0.0138 time: 0.1159 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:53:56 - mmengine - INFO - Epoch(train) [37][ 5/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:19 time: 0.2739 data_time: 0.0247 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:57 - mmengine - INFO - Epoch(train) [37][10/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:18 time: 0.2727 data_time: 0.0250 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:53:59 - mmengine - INFO - Epoch(train) [37][15/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:16 time: 0.2714 data_time: 0.0243 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:00 - mmengine - INFO - Epoch(train) [37][20/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:15 time: 0.2713 data_time: 0.0241 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:01 - mmengine - INFO - Epoch(train) [37][25/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:13 time: 0.2715 data_time: 0.0241 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:03 - mmengine - INFO - Epoch(train) [37][30/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:11 time: 0.2718 data_time: 0.0241 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:04 - mmengine - INFO - Epoch(train) [37][35/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:10 time: 0.2712 data_time: 0.0241 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:05 - mmengine - INFO - Epoch(train) [37][40/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:08 time: 0.2738 data_time: 0.0241 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:07 - mmengine - INFO - Epoch(train) [37][45/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:07 time: 0.2755 data_time: 0.0242 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:08 - mmengine - INFO - Epoch(train) [37][50/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:05 time: 0.2808 data_time: 0.0245 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:09 - mmengine - INFO - Epoch(train) [37][55/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:04 time: 0.2644 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:11 - mmengine - INFO - Epoch(train) [37][60/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:02 time: 0.2645 data_time: 0.0086 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:12 - mmengine - INFO - Epoch(train) [37][65/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:28:01 time: 0.2653 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:13 - mmengine - INFO - Epoch(train) [37][70/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:27:59 time: 0.2654 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:15 - mmengine - INFO - Epoch(train) [37][75/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:27:57 time: 0.2648 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:16 - mmengine - INFO - Epoch(train) [37][80/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:27:56 time: 0.2648 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:17 - mmengine - INFO - Epoch(train) [37][85/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:27:54 time: 0.2637 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:18 - mmengine - INFO - Epoch(train) [37][90/94] base_lr: 6.5969e-03 lr: 6.5969e-03 eta: 0:27:52 time: 0.2607 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:19 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:54:19 - mmengine - INFO - Saving checkpoint at 37 epochs 09/30 14:54:22 - mmengine - INFO - Epoch(val) [37][ 5/102] eta: 0:00:22 time: 0.1208 data_time: 0.0188 memory: 11783 09/30 14:54:23 - mmengine - INFO - Epoch(val) [37][ 10/102] eta: 0:00:15 time: 0.1206 data_time: 0.0186 memory: 1697 09/30 14:54:23 - mmengine - INFO - Epoch(val) [37][ 15/102] eta: 0:00:12 time: 0.1205 data_time: 0.0183 memory: 1697 09/30 14:54:24 - mmengine - INFO - Epoch(val) [37][ 20/102] eta: 0:00:11 time: 0.1202 data_time: 0.0182 memory: 1697 09/30 14:54:24 - mmengine - INFO - Epoch(val) [37][ 25/102] eta: 0:00:10 time: 0.1203 data_time: 0.0182 memory: 1697 09/30 14:54:25 - mmengine - INFO - Epoch(val) [37][ 30/102] eta: 0:00:09 time: 0.1207 data_time: 0.0184 memory: 1697 09/30 14:54:26 - mmengine - INFO - Epoch(val) [37][ 35/102] eta: 0:00:08 time: 0.1206 data_time: 0.0181 memory: 1697 09/30 14:54:26 - mmengine - INFO - Epoch(val) [37][ 40/102] eta: 0:00:07 time: 0.1209 data_time: 0.0183 memory: 1697 09/30 14:54:27 - mmengine - INFO - Epoch(val) [37][ 45/102] eta: 0:00:06 time: 0.1213 data_time: 0.0183 memory: 1697 09/30 14:54:27 - mmengine - INFO - Epoch(val) [37][ 50/102] eta: 0:00:06 time: 0.1214 data_time: 0.0184 memory: 1697 09/30 14:54:28 - mmengine - INFO - Epoch(val) [37][ 55/102] eta: 0:00:05 time: 0.1094 data_time: 0.0062 memory: 1697 09/30 14:54:28 - mmengine - INFO - Epoch(val) [37][ 60/102] eta: 0:00:05 time: 0.1096 data_time: 0.0063 memory: 1697 09/30 14:54:29 - mmengine - INFO - Epoch(val) [37][ 65/102] eta: 0:00:04 time: 0.1100 data_time: 0.0067 memory: 1697 09/30 14:54:29 - mmengine - INFO - Epoch(val) [37][ 70/102] eta: 0:00:03 time: 0.1100 data_time: 0.0066 memory: 1697 09/30 14:54:30 - mmengine - INFO - Epoch(val) [37][ 75/102] eta: 0:00:03 time: 0.1098 data_time: 0.0067 memory: 1697 09/30 14:54:31 - mmengine - INFO - Epoch(val) [37][ 80/102] eta: 0:00:02 time: 0.1095 data_time: 0.0065 memory: 1697 09/30 14:54:31 - mmengine - INFO - Epoch(val) [37][ 85/102] eta: 0:00:01 time: 0.1094 data_time: 0.0067 memory: 1697 09/30 14:54:32 - mmengine - INFO - Epoch(val) [37][ 90/102] eta: 0:00:01 time: 0.1093 data_time: 0.0067 memory: 1697 09/30 14:54:32 - mmengine - INFO - Epoch(val) [37][ 95/102] eta: 0:00:00 time: 0.1092 data_time: 0.0067 memory: 1697 09/30 14:54:33 - mmengine - INFO - Epoch(val) [37][100/102] eta: 0:00:00 time: 0.1089 data_time: 0.0065 memory: 1697 09/30 14:54:33 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:54:33 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:54:33 - mmengine - INFO - Epoch(val) [37][102/102] data_time: 0.0123 time: 0.1149 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:54:35 - mmengine - INFO - Epoch(train) [38][ 5/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:51 time: 0.2717 data_time: 0.0248 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:36 - mmengine - INFO - Epoch(train) [38][10/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:49 time: 0.2727 data_time: 0.0248 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:38 - mmengine - INFO - Epoch(train) [38][15/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:47 time: 0.2730 data_time: 0.0253 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:39 - mmengine - INFO - Epoch(train) [38][20/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:46 time: 0.2730 data_time: 0.0247 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:40 - mmengine - INFO - Epoch(train) [38][25/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:44 time: 0.2730 data_time: 0.0247 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:42 - mmengine - INFO - Epoch(train) [38][30/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:43 time: 0.2734 data_time: 0.0247 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:43 - mmengine - INFO - Epoch(train) [38][35/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:41 time: 0.2737 data_time: 0.0249 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:44 - mmengine - INFO - Epoch(train) [38][40/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:40 time: 0.2752 data_time: 0.0249 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:46 - mmengine - INFO - Epoch(train) [38][45/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:38 time: 0.2771 data_time: 0.0250 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:47 - mmengine - INFO - Epoch(train) [38][50/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:37 time: 0.2809 data_time: 0.0251 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:48 - mmengine - INFO - Epoch(train) [38][55/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:35 time: 0.2654 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:50 - mmengine - INFO - Epoch(train) [38][60/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:34 time: 0.2652 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:51 - mmengine - INFO - Epoch(train) [38][65/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:32 time: 0.2650 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:52 - mmengine - INFO - Epoch(train) [38][70/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:30 time: 0.2653 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:54 - mmengine - INFO - Epoch(train) [38][75/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:29 time: 0.2655 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:55 - mmengine - INFO - Epoch(train) [38][80/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:27 time: 0.2650 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:56 - mmengine - INFO - Epoch(train) [38][85/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:26 time: 0.2638 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:57 - mmengine - INFO - Epoch(train) [38][90/94] base_lr: 6.4938e-03 lr: 6.4938e-03 eta: 0:27:24 time: 0.2627 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:54:58 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:54:58 - mmengine - INFO - Saving checkpoint at 38 epochs 09/30 14:55:01 - mmengine - INFO - Epoch(val) [38][ 5/102] eta: 0:00:21 time: 0.1195 data_time: 0.0170 memory: 11783 09/30 14:55:02 - mmengine - INFO - Epoch(val) [38][ 10/102] eta: 0:00:14 time: 0.1193 data_time: 0.0168 memory: 1697 09/30 14:55:02 - mmengine - INFO - Epoch(val) [38][ 15/102] eta: 0:00:12 time: 0.1190 data_time: 0.0165 memory: 1697 09/30 14:55:03 - mmengine - INFO - Epoch(val) [38][ 20/102] eta: 0:00:11 time: 0.1192 data_time: 0.0166 memory: 1697 09/30 14:55:04 - mmengine - INFO - Epoch(val) [38][ 25/102] eta: 0:00:10 time: 0.1193 data_time: 0.0165 memory: 1697 09/30 14:55:04 - mmengine - INFO - Epoch(val) [38][ 30/102] eta: 0:00:09 time: 0.1196 data_time: 0.0167 memory: 1697 09/30 14:55:05 - mmengine - INFO - Epoch(val) [38][ 35/102] eta: 0:00:08 time: 0.1196 data_time: 0.0165 memory: 1697 09/30 14:55:05 - mmengine - INFO - Epoch(val) [38][ 40/102] eta: 0:00:07 time: 0.1199 data_time: 0.0167 memory: 1697 09/30 14:55:06 - mmengine - INFO - Epoch(val) [38][ 45/102] eta: 0:00:06 time: 0.1202 data_time: 0.0168 memory: 1697 09/30 14:55:06 - mmengine - INFO - Epoch(val) [38][ 50/102] eta: 0:00:06 time: 0.1205 data_time: 0.0169 memory: 1697 09/30 14:55:07 - mmengine - INFO - Epoch(val) [38][ 55/102] eta: 0:00:05 time: 0.1097 data_time: 0.0065 memory: 1697 09/30 14:55:07 - mmengine - INFO - Epoch(val) [38][ 60/102] eta: 0:00:04 time: 0.1101 data_time: 0.0067 memory: 1697 09/30 14:55:08 - mmengine - INFO - Epoch(val) [38][ 65/102] eta: 0:00:04 time: 0.1103 data_time: 0.0070 memory: 1697 09/30 14:55:09 - mmengine - INFO - Epoch(val) [38][ 70/102] eta: 0:00:03 time: 0.1101 data_time: 0.0070 memory: 1697 09/30 14:55:09 - mmengine - INFO - Epoch(val) [38][ 75/102] eta: 0:00:03 time: 0.1100 data_time: 0.0071 memory: 1697 09/30 14:55:10 - mmengine - INFO - Epoch(val) [38][ 80/102] eta: 0:00:02 time: 0.1097 data_time: 0.0070 memory: 1697 09/30 14:55:10 - mmengine - INFO - Epoch(val) [38][ 85/102] eta: 0:00:01 time: 0.1097 data_time: 0.0071 memory: 1697 09/30 14:55:11 - mmengine - INFO - Epoch(val) [38][ 90/102] eta: 0:00:01 time: 0.1097 data_time: 0.0071 memory: 1697 09/30 14:55:11 - mmengine - INFO - Epoch(val) [38][ 95/102] eta: 0:00:00 time: 0.1096 data_time: 0.0071 memory: 1697 09/30 14:55:12 - mmengine - INFO - Epoch(val) [38][100/102] eta: 0:00:00 time: 0.1094 data_time: 0.0071 memory: 1697 09/30 14:55:12 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:55:12 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:55:12 - mmengine - INFO - Epoch(val) [38][102/102] data_time: 0.0119 time: 0.1148 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:55:15 - mmengine - INFO - Epoch(train) [39][ 5/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:23 time: 0.2848 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:16 - mmengine - INFO - Epoch(train) [39][10/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:21 time: 0.2847 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:17 - mmengine - INFO - Epoch(train) [39][15/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:20 time: 0.2839 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:19 - mmengine - INFO - Epoch(train) [39][20/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:18 time: 0.2839 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:20 - mmengine - INFO - Epoch(train) [39][25/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:17 time: 0.2831 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:21 - mmengine - INFO - Epoch(train) [39][30/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:15 time: 0.2834 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:23 - mmengine - INFO - Epoch(train) [39][35/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:14 time: 0.2837 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:24 - mmengine - INFO - Epoch(train) [39][40/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:12 time: 0.2846 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:25 - mmengine - INFO - Epoch(train) [39][45/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:11 time: 0.2854 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:27 - mmengine - INFO - Epoch(train) [39][50/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:09 time: 0.2899 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:28 - mmengine - INFO - Epoch(train) [39][55/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:07 time: 0.2640 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:29 - mmengine - INFO - Epoch(train) [39][60/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:06 time: 0.2634 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:31 - mmengine - INFO - Epoch(train) [39][65/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:04 time: 0.2642 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:32 - mmengine - INFO - Epoch(train) [39][70/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:03 time: 0.2640 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:33 - mmengine - INFO - Epoch(train) [39][75/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:01 time: 0.2647 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:34 - mmengine - INFO - Epoch(train) [39][80/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:27:00 time: 0.2635 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:36 - mmengine - INFO - Epoch(train) [39][85/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:26:58 time: 0.2622 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:37 - mmengine - INFO - Epoch(train) [39][90/94] base_lr: 6.3906e-03 lr: 6.3906e-03 eta: 0:26:56 time: 0.2605 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:38 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:55:38 - mmengine - INFO - Saving checkpoint at 39 epochs 09/30 14:55:40 - mmengine - INFO - Epoch(val) [39][ 5/102] eta: 0:00:22 time: 0.1218 data_time: 0.0196 memory: 11783 09/30 14:55:41 - mmengine - INFO - Epoch(val) [39][ 10/102] eta: 0:00:15 time: 0.1218 data_time: 0.0193 memory: 1697 09/30 14:55:42 - mmengine - INFO - Epoch(val) [39][ 15/102] eta: 0:00:13 time: 0.1217 data_time: 0.0191 memory: 1697 09/30 14:55:42 - mmengine - INFO - Epoch(val) [39][ 20/102] eta: 0:00:11 time: 0.1219 data_time: 0.0191 memory: 1697 09/30 14:55:43 - mmengine - INFO - Epoch(val) [39][ 25/102] eta: 0:00:10 time: 0.1220 data_time: 0.0191 memory: 1697 09/30 14:55:43 - mmengine - INFO - Epoch(val) [39][ 30/102] eta: 0:00:09 time: 0.1223 data_time: 0.0192 memory: 1697 09/30 14:55:44 - mmengine - INFO - Epoch(val) [39][ 35/102] eta: 0:00:08 time: 0.1220 data_time: 0.0190 memory: 1697 09/30 14:55:44 - mmengine - INFO - Epoch(val) [39][ 40/102] eta: 0:00:07 time: 0.1223 data_time: 0.0191 memory: 1697 09/30 14:55:45 - mmengine - INFO - Epoch(val) [39][ 45/102] eta: 0:00:07 time: 0.1223 data_time: 0.0191 memory: 1697 09/30 14:55:45 - mmengine - INFO - Epoch(val) [39][ 50/102] eta: 0:00:06 time: 0.1224 data_time: 0.0190 memory: 1697 09/30 14:55:46 - mmengine - INFO - Epoch(val) [39][ 55/102] eta: 0:00:05 time: 0.1100 data_time: 0.0066 memory: 1697 09/30 14:55:47 - mmengine - INFO - Epoch(val) [39][ 60/102] eta: 0:00:05 time: 0.1100 data_time: 0.0067 memory: 1697 09/30 14:55:47 - mmengine - INFO - Epoch(val) [39][ 65/102] eta: 0:00:04 time: 0.1106 data_time: 0.0072 memory: 1697 09/30 14:55:48 - mmengine - INFO - Epoch(val) [39][ 70/102] eta: 0:00:03 time: 0.1107 data_time: 0.0071 memory: 1697 09/30 14:55:48 - mmengine - INFO - Epoch(val) [39][ 75/102] eta: 0:00:03 time: 0.1108 data_time: 0.0073 memory: 1697 09/30 14:55:49 - mmengine - INFO - Epoch(val) [39][ 80/102] eta: 0:00:02 time: 0.1108 data_time: 0.0072 memory: 1697 09/30 14:55:49 - mmengine - INFO - Epoch(val) [39][ 85/102] eta: 0:00:02 time: 0.1111 data_time: 0.0074 memory: 1697 09/30 14:55:50 - mmengine - INFO - Epoch(val) [39][ 90/102] eta: 0:00:01 time: 0.1113 data_time: 0.0075 memory: 1697 09/30 14:55:50 - mmengine - INFO - Epoch(val) [39][ 95/102] eta: 0:00:00 time: 0.1115 data_time: 0.0076 memory: 1697 09/30 14:55:51 - mmengine - INFO - Epoch(val) [39][100/102] eta: 0:00:00 time: 0.1113 data_time: 0.0075 memory: 1697 09/30 14:55:51 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:55:51 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:55:51 - mmengine - INFO - Epoch(val) [39][102/102] data_time: 0.0131 time: 0.1167 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:55:54 - mmengine - INFO - Epoch(train) [40][ 5/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:55 time: 0.2813 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:55 - mmengine - INFO - Epoch(train) [40][10/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:54 time: 0.2814 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:56 - mmengine - INFO - Epoch(train) [40][15/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:52 time: 0.2807 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:58 - mmengine - INFO - Epoch(train) [40][20/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:50 time: 0.2815 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:55:59 - mmengine - INFO - Epoch(train) [40][25/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:49 time: 0.2813 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:00 - mmengine - INFO - Epoch(train) [40][30/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:47 time: 0.2803 data_time: 0.0331 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:02 - mmengine - INFO - Epoch(train) [40][35/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:46 time: 0.2801 data_time: 0.0328 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:03 - mmengine - INFO - Epoch(train) [40][40/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:44 time: 0.2816 data_time: 0.0332 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:04 - mmengine - INFO - Epoch(train) [40][45/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:43 time: 0.2831 data_time: 0.0331 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:06 - mmengine - INFO - Epoch(train) [40][50/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:41 time: 0.2871 data_time: 0.0333 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:07 - mmengine - INFO - Epoch(train) [40][55/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:40 time: 0.2625 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:08 - mmengine - INFO - Epoch(train) [40][60/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:38 time: 0.2623 data_time: 0.0087 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:10 - mmengine - INFO - Epoch(train) [40][65/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:36 time: 0.2632 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:11 - mmengine - INFO - Epoch(train) [40][70/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:35 time: 0.2626 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:12 - mmengine - INFO - Epoch(train) [40][75/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:33 time: 0.2628 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:13 - mmengine - INFO - Epoch(train) [40][80/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:32 time: 0.2633 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:15 - mmengine - INFO - Epoch(train) [40][85/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:30 time: 0.2623 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:16 - mmengine - INFO - Epoch(train) [40][90/94] base_lr: 6.2875e-03 lr: 6.2875e-03 eta: 0:26:29 time: 0.2610 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:17 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:56:17 - mmengine - INFO - Saving checkpoint at 40 epochs 09/30 14:56:19 - mmengine - INFO - Epoch(val) [40][ 5/102] eta: 0:00:25 time: 0.1261 data_time: 0.0219 memory: 11783 09/30 14:56:20 - mmengine - INFO - Epoch(val) [40][ 10/102] eta: 0:00:16 time: 0.1257 data_time: 0.0217 memory: 1697 09/30 14:56:20 - mmengine - INFO - Epoch(val) [40][ 15/102] eta: 0:00:13 time: 0.1253 data_time: 0.0213 memory: 1697 09/30 14:56:21 - mmengine - INFO - Epoch(val) [40][ 20/102] eta: 0:00:11 time: 0.1250 data_time: 0.0213 memory: 1697 09/30 14:56:22 - mmengine - INFO - Epoch(val) [40][ 25/102] eta: 0:00:10 time: 0.1250 data_time: 0.0211 memory: 1697 09/30 14:56:22 - mmengine - INFO - Epoch(val) [40][ 30/102] eta: 0:00:09 time: 0.1250 data_time: 0.0212 memory: 1697 09/30 14:56:23 - mmengine - INFO - Epoch(val) [40][ 35/102] eta: 0:00:08 time: 0.1249 data_time: 0.0209 memory: 1697 09/30 14:56:23 - mmengine - INFO - Epoch(val) [40][ 40/102] eta: 0:00:07 time: 0.1249 data_time: 0.0210 memory: 1697 09/30 14:56:24 - mmengine - INFO - Epoch(val) [40][ 45/102] eta: 0:00:07 time: 0.1249 data_time: 0.0211 memory: 1697 09/30 14:56:24 - mmengine - INFO - Epoch(val) [40][ 50/102] eta: 0:00:06 time: 0.1249 data_time: 0.0211 memory: 1697 09/30 14:56:25 - mmengine - INFO - Epoch(val) [40][ 55/102] eta: 0:00:05 time: 0.1102 data_time: 0.0067 memory: 1697 09/30 14:56:25 - mmengine - INFO - Epoch(val) [40][ 60/102] eta: 0:00:05 time: 0.1101 data_time: 0.0069 memory: 1697 09/30 14:56:26 - mmengine - INFO - Epoch(val) [40][ 65/102] eta: 0:00:04 time: 0.1105 data_time: 0.0073 memory: 1697 09/30 14:56:27 - mmengine - INFO - Epoch(val) [40][ 70/102] eta: 0:00:03 time: 0.1108 data_time: 0.0073 memory: 1697 09/30 14:56:27 - mmengine - INFO - Epoch(val) [40][ 75/102] eta: 0:00:03 time: 0.1108 data_time: 0.0074 memory: 1697 09/30 14:56:28 - mmengine - INFO - Epoch(val) [40][ 80/102] eta: 0:00:02 time: 0.1107 data_time: 0.0073 memory: 1697 09/30 14:56:28 - mmengine - INFO - Epoch(val) [40][ 85/102] eta: 0:00:02 time: 0.1106 data_time: 0.0074 memory: 1697 09/30 14:56:29 - mmengine - INFO - Epoch(val) [40][ 90/102] eta: 0:00:01 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 14:56:29 - mmengine - INFO - Epoch(val) [40][ 95/102] eta: 0:00:00 time: 0.1105 data_time: 0.0074 memory: 1697 09/30 14:56:30 - mmengine - INFO - Epoch(val) [40][100/102] eta: 0:00:00 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 14:56:30 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:56:30 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:56:30 - mmengine - INFO - Epoch(val) [40][102/102] data_time: 0.0140 time: 0.1174 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:56:32 - mmengine - INFO - Epoch(train) [41][ 5/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:27 time: 0.2768 data_time: 0.0280 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:34 - mmengine - INFO - Epoch(train) [41][10/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:25 time: 0.2769 data_time: 0.0278 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:35 - mmengine - INFO - Epoch(train) [41][15/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:24 time: 0.2768 data_time: 0.0280 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:36 - mmengine - INFO - Epoch(train) [41][20/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:22 time: 0.2763 data_time: 0.0277 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:38 - mmengine - INFO - Epoch(train) [41][25/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:21 time: 0.2754 data_time: 0.0275 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:39 - mmengine - INFO - Epoch(train) [41][30/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:19 time: 0.2757 data_time: 0.0273 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:40 - mmengine - INFO - Epoch(train) [41][35/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:18 time: 0.2758 data_time: 0.0273 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:42 - mmengine - INFO - Epoch(train) [41][40/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:16 time: 0.2768 data_time: 0.0274 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:43 - mmengine - INFO - Epoch(train) [41][45/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:15 time: 0.2782 data_time: 0.0274 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:44 - mmengine - INFO - Epoch(train) [41][50/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:13 time: 0.2830 data_time: 0.0275 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:46 - mmengine - INFO - Epoch(train) [41][55/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:12 time: 0.2637 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:47 - mmengine - INFO - Epoch(train) [41][60/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:10 time: 0.2636 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:48 - mmengine - INFO - Epoch(train) [41][65/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:08 time: 0.2636 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:50 - mmengine - INFO - Epoch(train) [41][70/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:07 time: 0.2640 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:51 - mmengine - INFO - Epoch(train) [41][75/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:05 time: 0.2645 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:52 - mmengine - INFO - Epoch(train) [41][80/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:04 time: 0.2640 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:53 - mmengine - INFO - Epoch(train) [41][85/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:02 time: 0.2626 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:55 - mmengine - INFO - Epoch(train) [41][90/94] base_lr: 6.1844e-03 lr: 6.1844e-03 eta: 0:26:01 time: 0.2612 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:56:55 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:56:55 - mmengine - INFO - Saving checkpoint at 41 epochs 09/30 14:56:58 - mmengine - INFO - Epoch(val) [41][ 5/102] eta: 0:00:23 time: 0.1237 data_time: 0.0207 memory: 11783 09/30 14:56:59 - mmengine - INFO - Epoch(val) [41][ 10/102] eta: 0:00:16 time: 0.1233 data_time: 0.0205 memory: 1697 09/30 14:56:59 - mmengine - INFO - Epoch(val) [41][ 15/102] eta: 0:00:13 time: 0.1230 data_time: 0.0201 memory: 1697 09/30 14:57:00 - mmengine - INFO - Epoch(val) [41][ 20/102] eta: 0:00:11 time: 0.1227 data_time: 0.0201 memory: 1697 09/30 14:57:00 - mmengine - INFO - Epoch(val) [41][ 25/102] eta: 0:00:10 time: 0.1225 data_time: 0.0199 memory: 1697 09/30 14:57:01 - mmengine - INFO - Epoch(val) [41][ 30/102] eta: 0:00:09 time: 0.1223 data_time: 0.0198 memory: 1697 09/30 14:57:01 - mmengine - INFO - Epoch(val) [41][ 35/102] eta: 0:00:08 time: 0.1220 data_time: 0.0195 memory: 1697 09/30 14:57:02 - mmengine - INFO - Epoch(val) [41][ 40/102] eta: 0:00:07 time: 0.1221 data_time: 0.0196 memory: 1697 09/30 14:57:03 - mmengine - INFO - Epoch(val) [41][ 45/102] eta: 0:00:07 time: 0.1223 data_time: 0.0196 memory: 1697 09/30 14:57:03 - mmengine - INFO - Epoch(val) [41][ 50/102] eta: 0:00:06 time: 0.1221 data_time: 0.0196 memory: 1697 09/30 14:57:04 - mmengine - INFO - Epoch(val) [41][ 55/102] eta: 0:00:05 time: 0.1087 data_time: 0.0061 memory: 1697 09/30 14:57:04 - mmengine - INFO - Epoch(val) [41][ 60/102] eta: 0:00:05 time: 0.1091 data_time: 0.0063 memory: 1697 09/30 14:57:05 - mmengine - INFO - Epoch(val) [41][ 65/102] eta: 0:00:04 time: 0.1092 data_time: 0.0066 memory: 1697 09/30 14:57:05 - mmengine - INFO - Epoch(val) [41][ 70/102] eta: 0:00:03 time: 0.1092 data_time: 0.0067 memory: 1697 09/30 14:57:06 - mmengine - INFO - Epoch(val) [41][ 75/102] eta: 0:00:03 time: 0.1092 data_time: 0.0068 memory: 1697 09/30 14:57:06 - mmengine - INFO - Epoch(val) [41][ 80/102] eta: 0:00:02 time: 0.1094 data_time: 0.0068 memory: 1697 09/30 14:57:07 - mmengine - INFO - Epoch(val) [41][ 85/102] eta: 0:00:01 time: 0.1098 data_time: 0.0070 memory: 1697 09/30 14:57:07 - mmengine - INFO - Epoch(val) [41][ 90/102] eta: 0:00:01 time: 0.1099 data_time: 0.0070 memory: 1697 09/30 14:57:08 - mmengine - INFO - Epoch(val) [41][ 95/102] eta: 0:00:00 time: 0.1096 data_time: 0.0070 memory: 1697 09/30 14:57:09 - mmengine - INFO - Epoch(val) [41][100/102] eta: 0:00:00 time: 0.1097 data_time: 0.0069 memory: 1697 09/30 14:57:09 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:57:09 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:57:09 - mmengine - INFO - Epoch(val) [41][102/102] data_time: 0.0131 time: 0.1157 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:57:11 - mmengine - INFO - Epoch(train) [42][ 5/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:59 time: 0.2751 data_time: 0.0271 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:12 - mmengine - INFO - Epoch(train) [42][10/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:57 time: 0.2752 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:14 - mmengine - INFO - Epoch(train) [42][15/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:56 time: 0.2758 data_time: 0.0274 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:15 - mmengine - INFO - Epoch(train) [42][20/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:54 time: 0.2759 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:16 - mmengine - INFO - Epoch(train) [42][25/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:53 time: 0.2757 data_time: 0.0268 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:18 - mmengine - INFO - Epoch(train) [42][30/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:51 time: 0.2758 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:19 - mmengine - INFO - Epoch(train) [42][35/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:50 time: 0.2764 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:20 - mmengine - INFO - Epoch(train) [42][40/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:48 time: 0.2779 data_time: 0.0271 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:22 - mmengine - INFO - Epoch(train) [42][45/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:47 time: 0.2802 data_time: 0.0271 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:23 - mmengine - INFO - Epoch(train) [42][50/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:45 time: 0.2849 data_time: 0.0273 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:24 - mmengine - INFO - Epoch(train) [42][55/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:44 time: 0.2663 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:26 - mmengine - INFO - Epoch(train) [42][60/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:42 time: 0.2667 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:27 - mmengine - INFO - Epoch(train) [42][65/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:41 time: 0.2662 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:28 - mmengine - INFO - Epoch(train) [42][70/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:39 time: 0.2659 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:30 - mmengine - INFO - Epoch(train) [42][75/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:38 time: 0.2666 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:31 - mmengine - INFO - Epoch(train) [42][80/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:36 time: 0.2663 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:32 - mmengine - INFO - Epoch(train) [42][85/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:34 time: 0.2646 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:34 - mmengine - INFO - Epoch(train) [42][90/94] base_lr: 6.0813e-03 lr: 6.0813e-03 eta: 0:25:33 time: 0.2629 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:34 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:57:34 - mmengine - INFO - Saving checkpoint at 42 epochs 09/30 14:57:37 - mmengine - INFO - Epoch(val) [42][ 5/102] eta: 0:00:24 time: 0.1242 data_time: 0.0214 memory: 11783 09/30 14:57:38 - mmengine - INFO - Epoch(val) [42][ 10/102] eta: 0:00:16 time: 0.1239 data_time: 0.0212 memory: 1697 09/30 14:57:38 - mmengine - INFO - Epoch(val) [42][ 15/102] eta: 0:00:13 time: 0.1238 data_time: 0.0209 memory: 1697 09/30 14:57:39 - mmengine - INFO - Epoch(val) [42][ 20/102] eta: 0:00:11 time: 0.1239 data_time: 0.0209 memory: 1697 09/30 14:57:39 - mmengine - INFO - Epoch(val) [42][ 25/102] eta: 0:00:10 time: 0.1238 data_time: 0.0208 memory: 1697 09/30 14:57:40 - mmengine - INFO - Epoch(val) [42][ 30/102] eta: 0:00:09 time: 0.1237 data_time: 0.0209 memory: 1697 09/30 14:57:40 - mmengine - INFO - Epoch(val) [42][ 35/102] eta: 0:00:08 time: 0.1233 data_time: 0.0207 memory: 1697 09/30 14:57:41 - mmengine - INFO - Epoch(val) [42][ 40/102] eta: 0:00:07 time: 0.1232 data_time: 0.0208 memory: 1697 09/30 14:57:41 - mmengine - INFO - Epoch(val) [42][ 45/102] eta: 0:00:07 time: 0.1231 data_time: 0.0207 memory: 1697 09/30 14:57:42 - mmengine - INFO - Epoch(val) [42][ 50/102] eta: 0:00:06 time: 0.1232 data_time: 0.0208 memory: 1697 09/30 14:57:43 - mmengine - INFO - Epoch(val) [42][ 55/102] eta: 0:00:05 time: 0.1087 data_time: 0.0063 memory: 1697 09/30 14:57:43 - mmengine - INFO - Epoch(val) [42][ 60/102] eta: 0:00:05 time: 0.1091 data_time: 0.0066 memory: 1697 09/30 14:57:44 - mmengine - INFO - Epoch(val) [42][ 65/102] eta: 0:00:04 time: 0.1093 data_time: 0.0069 memory: 1697 09/30 14:57:44 - mmengine - INFO - Epoch(val) [42][ 70/102] eta: 0:00:03 time: 0.1093 data_time: 0.0069 memory: 1697 09/30 14:57:45 - mmengine - INFO - Epoch(val) [42][ 75/102] eta: 0:00:03 time: 0.1093 data_time: 0.0070 memory: 1697 09/30 14:57:45 - mmengine - INFO - Epoch(val) [42][ 80/102] eta: 0:00:02 time: 0.1092 data_time: 0.0069 memory: 1697 09/30 14:57:46 - mmengine - INFO - Epoch(val) [42][ 85/102] eta: 0:00:01 time: 0.1094 data_time: 0.0070 memory: 1697 09/30 14:57:46 - mmengine - INFO - Epoch(val) [42][ 90/102] eta: 0:00:01 time: 0.1094 data_time: 0.0070 memory: 1697 09/30 14:57:47 - mmengine - INFO - Epoch(val) [42][ 95/102] eta: 0:00:00 time: 0.1097 data_time: 0.0072 memory: 1697 09/30 14:57:47 - mmengine - INFO - Epoch(val) [42][100/102] eta: 0:00:00 time: 0.1094 data_time: 0.0070 memory: 1697 09/30 14:57:48 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:57:48 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:57:48 - mmengine - INFO - Epoch(val) [42][102/102] data_time: 0.0137 time: 0.1161 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:57:50 - mmengine - INFO - Epoch(train) [43][ 5/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:31 time: 0.2720 data_time: 0.0228 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:51 - mmengine - INFO - Epoch(train) [43][10/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:29 time: 0.2716 data_time: 0.0224 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:52 - mmengine - INFO - Epoch(train) [43][15/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:28 time: 0.2713 data_time: 0.0223 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:54 - mmengine - INFO - Epoch(train) [43][20/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:26 time: 0.2705 data_time: 0.0220 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:55 - mmengine - INFO - Epoch(train) [43][25/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:25 time: 0.2706 data_time: 0.0220 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:56 - mmengine - INFO - Epoch(train) [43][30/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:23 time: 0.2703 data_time: 0.0220 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:58 - mmengine - INFO - Epoch(train) [43][35/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:22 time: 0.2707 data_time: 0.0221 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:57:59 - mmengine - INFO - Epoch(train) [43][40/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:20 time: 0.2722 data_time: 0.0220 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:00 - mmengine - INFO - Epoch(train) [43][45/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:19 time: 0.2736 data_time: 0.0220 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:02 - mmengine - INFO - Epoch(train) [43][50/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:17 time: 0.2777 data_time: 0.0221 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:02 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:58:03 - mmengine - INFO - Epoch(train) [43][55/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:16 time: 0.2638 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:04 - mmengine - INFO - Epoch(train) [43][60/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:14 time: 0.2642 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:06 - mmengine - INFO - Epoch(train) [43][65/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:13 time: 0.2644 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:07 - mmengine - INFO - Epoch(train) [43][70/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:11 time: 0.2646 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:08 - mmengine - INFO - Epoch(train) [43][75/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:10 time: 0.2643 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:09 - mmengine - INFO - Epoch(train) [43][80/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:08 time: 0.2637 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:11 - mmengine - INFO - Epoch(train) [43][85/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:06 time: 0.2619 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:12 - mmengine - INFO - Epoch(train) [43][90/94] base_lr: 5.9781e-03 lr: 5.9781e-03 eta: 0:25:05 time: 0.2600 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:13 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:58:13 - mmengine - INFO - Saving checkpoint at 43 epochs 09/30 14:58:15 - mmengine - INFO - Epoch(val) [43][ 5/102] eta: 0:00:25 time: 0.1244 data_time: 0.0217 memory: 11783 09/30 14:58:16 - mmengine - INFO - Epoch(val) [43][ 10/102] eta: 0:00:16 time: 0.1243 data_time: 0.0215 memory: 1697 09/30 14:58:16 - mmengine - INFO - Epoch(val) [43][ 15/102] eta: 0:00:13 time: 0.1241 data_time: 0.0211 memory: 1697 09/30 14:58:17 - mmengine - INFO - Epoch(val) [43][ 20/102] eta: 0:00:12 time: 0.1241 data_time: 0.0212 memory: 1697 09/30 14:58:18 - mmengine - INFO - Epoch(val) [43][ 25/102] eta: 0:00:10 time: 0.1239 data_time: 0.0211 memory: 1697 09/30 14:58:18 - mmengine - INFO - Epoch(val) [43][ 30/102] eta: 0:00:09 time: 0.1239 data_time: 0.0212 memory: 1697 09/30 14:58:19 - mmengine - INFO - Epoch(val) [43][ 35/102] eta: 0:00:08 time: 0.1239 data_time: 0.0209 memory: 1697 09/30 14:58:19 - mmengine - INFO - Epoch(val) [43][ 40/102] eta: 0:00:07 time: 0.1241 data_time: 0.0210 memory: 1697 09/30 14:58:20 - mmengine - INFO - Epoch(val) [43][ 45/102] eta: 0:00:07 time: 0.1242 data_time: 0.0210 memory: 1697 09/30 14:58:20 - mmengine - INFO - Epoch(val) [43][ 50/102] eta: 0:00:06 time: 0.1242 data_time: 0.0211 memory: 1697 09/30 14:58:21 - mmengine - INFO - Epoch(val) [43][ 55/102] eta: 0:00:05 time: 0.1091 data_time: 0.0064 memory: 1697 09/30 14:58:21 - mmengine - INFO - Epoch(val) [43][ 60/102] eta: 0:00:05 time: 0.1092 data_time: 0.0066 memory: 1697 09/30 14:58:22 - mmengine - INFO - Epoch(val) [43][ 65/102] eta: 0:00:04 time: 0.1094 data_time: 0.0070 memory: 1697 09/30 14:58:22 - mmengine - INFO - Epoch(val) [43][ 70/102] eta: 0:00:03 time: 0.1094 data_time: 0.0069 memory: 1697 09/30 14:58:23 - mmengine - INFO - Epoch(val) [43][ 75/102] eta: 0:00:03 time: 0.1094 data_time: 0.0070 memory: 1697 09/30 14:58:24 - mmengine - INFO - Epoch(val) [43][ 80/102] eta: 0:00:02 time: 0.1093 data_time: 0.0069 memory: 1697 09/30 14:58:24 - mmengine - INFO - Epoch(val) [43][ 85/102] eta: 0:00:02 time: 0.1093 data_time: 0.0070 memory: 1697 09/30 14:58:25 - mmengine - INFO - Epoch(val) [43][ 90/102] eta: 0:00:01 time: 0.1093 data_time: 0.0070 memory: 1697 09/30 14:58:25 - mmengine - INFO - Epoch(val) [43][ 95/102] eta: 0:00:00 time: 0.1094 data_time: 0.0071 memory: 1697 09/30 14:58:26 - mmengine - INFO - Epoch(val) [43][100/102] eta: 0:00:00 time: 0.1092 data_time: 0.0070 memory: 1697 09/30 14:58:26 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:58:26 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:58:26 - mmengine - INFO - Epoch(val) [43][102/102] data_time: 0.0138 time: 0.1165 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:58:29 - mmengine - INFO - Epoch(train) [44][ 5/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:25:04 time: 0.2967 data_time: 0.0498 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:31 - mmengine - INFO - Epoch(train) [44][10/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:25:03 time: 0.2971 data_time: 0.0499 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:32 - mmengine - INFO - Epoch(train) [44][15/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:25:01 time: 0.2965 data_time: 0.0493 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:33 - mmengine - INFO - Epoch(train) [44][20/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:25:00 time: 0.2965 data_time: 0.0491 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:35 - mmengine - INFO - Epoch(train) [44][25/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:58 time: 0.2968 data_time: 0.0492 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:36 - mmengine - INFO - Epoch(train) [44][30/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:57 time: 0.2974 data_time: 0.0494 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:37 - mmengine - INFO - Epoch(train) [44][35/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:55 time: 0.2968 data_time: 0.0493 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:39 - mmengine - INFO - Epoch(train) [44][40/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:54 time: 0.2982 data_time: 0.0494 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:40 - mmengine - INFO - Epoch(train) [44][45/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:52 time: 0.3001 data_time: 0.0495 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:41 - mmengine - INFO - Epoch(train) [44][50/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:51 time: 0.3040 data_time: 0.0496 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:43 - mmengine - INFO - Epoch(train) [44][55/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:49 time: 0.2643 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:44 - mmengine - INFO - Epoch(train) [44][60/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:48 time: 0.2639 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:45 - mmengine - INFO - Epoch(train) [44][65/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:46 time: 0.2645 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:46 - mmengine - INFO - Epoch(train) [44][70/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:45 time: 0.2642 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:48 - mmengine - INFO - Epoch(train) [44][75/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:43 time: 0.2655 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:49 - mmengine - INFO - Epoch(train) [44][80/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:42 time: 0.2690 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:51 - mmengine - INFO - Epoch(train) [44][85/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:40 time: 0.2683 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:52 - mmengine - INFO - Epoch(train) [44][90/94] base_lr: 5.8750e-03 lr: 5.8750e-03 eta: 0:24:39 time: 0.2670 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:58:53 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:58:53 - mmengine - INFO - Saving checkpoint at 44 epochs 09/30 14:58:55 - mmengine - INFO - Epoch(val) [44][ 5/102] eta: 0:00:22 time: 0.1217 data_time: 0.0194 memory: 11783 09/30 14:58:56 - mmengine - INFO - Epoch(val) [44][ 10/102] eta: 0:00:15 time: 0.1217 data_time: 0.0192 memory: 1697 09/30 14:58:56 - mmengine - INFO - Epoch(val) [44][ 15/102] eta: 0:00:13 time: 0.1215 data_time: 0.0190 memory: 1697 09/30 14:58:57 - mmengine - INFO - Epoch(val) [44][ 20/102] eta: 0:00:11 time: 0.1215 data_time: 0.0188 memory: 1697 09/30 14:58:57 - mmengine - INFO - Epoch(val) [44][ 25/102] eta: 0:00:10 time: 0.1214 data_time: 0.0187 memory: 1697 09/30 14:58:58 - mmengine - INFO - Epoch(val) [44][ 30/102] eta: 0:00:09 time: 0.1215 data_time: 0.0188 memory: 1697 09/30 14:58:58 - mmengine - INFO - Epoch(val) [44][ 35/102] eta: 0:00:08 time: 0.1212 data_time: 0.0185 memory: 1697 09/30 14:58:59 - mmengine - INFO - Epoch(val) [44][ 40/102] eta: 0:00:07 time: 0.1212 data_time: 0.0186 memory: 1697 09/30 14:59:00 - mmengine - INFO - Epoch(val) [44][ 45/102] eta: 0:00:06 time: 0.1213 data_time: 0.0186 memory: 1697 09/30 14:59:00 - mmengine - INFO - Epoch(val) [44][ 50/102] eta: 0:00:06 time: 0.1213 data_time: 0.0186 memory: 1697 09/30 14:59:01 - mmengine - INFO - Epoch(val) [44][ 55/102] eta: 0:00:05 time: 0.1086 data_time: 0.0061 memory: 1697 09/30 14:59:01 - mmengine - INFO - Epoch(val) [44][ 60/102] eta: 0:00:05 time: 0.1086 data_time: 0.0063 memory: 1697 09/30 14:59:02 - mmengine - INFO - Epoch(val) [44][ 65/102] eta: 0:00:04 time: 0.1088 data_time: 0.0065 memory: 1697 09/30 14:59:02 - mmengine - INFO - Epoch(val) [44][ 70/102] eta: 0:00:03 time: 0.1087 data_time: 0.0066 memory: 1697 09/30 14:59:03 - mmengine - INFO - Epoch(val) [44][ 75/102] eta: 0:00:03 time: 0.1088 data_time: 0.0067 memory: 1697 09/30 14:59:03 - mmengine - INFO - Epoch(val) [44][ 80/102] eta: 0:00:02 time: 0.1085 data_time: 0.0066 memory: 1697 09/30 14:59:04 - mmengine - INFO - Epoch(val) [44][ 85/102] eta: 0:00:01 time: 0.1087 data_time: 0.0067 memory: 1697 09/30 14:59:04 - mmengine - INFO - Epoch(val) [44][ 90/102] eta: 0:00:01 time: 0.1086 data_time: 0.0067 memory: 1697 09/30 14:59:05 - mmengine - INFO - Epoch(val) [44][ 95/102] eta: 0:00:00 time: 0.1085 data_time: 0.0067 memory: 1697 09/30 14:59:06 - mmengine - INFO - Epoch(val) [44][100/102] eta: 0:00:00 time: 0.1082 data_time: 0.0066 memory: 1697 09/30 14:59:06 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:59:06 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:59:06 - mmengine - INFO - Epoch(val) [44][102/102] data_time: 0.0124 time: 0.1145 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:59:08 - mmengine - INFO - Epoch(train) [45][ 5/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:37 time: 0.2862 data_time: 0.0312 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:10 - mmengine - INFO - Epoch(train) [45][10/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:36 time: 0.2854 data_time: 0.0317 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:11 - mmengine - INFO - Epoch(train) [45][15/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:34 time: 0.2856 data_time: 0.0314 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:12 - mmengine - INFO - Epoch(train) [45][20/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:33 time: 0.2861 data_time: 0.0316 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:13 - mmengine - INFO - Epoch(train) [45][25/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:31 time: 0.2853 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:15 - mmengine - INFO - Epoch(train) [45][30/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:30 time: 0.2842 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:16 - mmengine - INFO - Epoch(train) [45][35/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:28 time: 0.2790 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:17 - mmengine - INFO - Epoch(train) [45][40/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:27 time: 0.2811 data_time: 0.0312 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:19 - mmengine - INFO - Epoch(train) [45][45/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:25 time: 0.2828 data_time: 0.0312 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:20 - mmengine - INFO - Epoch(train) [45][50/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:24 time: 0.2866 data_time: 0.0313 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:21 - mmengine - INFO - Epoch(train) [45][55/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:22 time: 0.2637 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:23 - mmengine - INFO - Epoch(train) [45][60/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:21 time: 0.2640 data_time: 0.0087 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:24 - mmengine - INFO - Epoch(train) [45][65/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:19 time: 0.2639 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:25 - mmengine - INFO - Epoch(train) [45][70/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:18 time: 0.2636 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:27 - mmengine - INFO - Epoch(train) [45][75/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:16 time: 0.2644 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:28 - mmengine - INFO - Epoch(train) [45][80/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:15 time: 0.2641 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:29 - mmengine - INFO - Epoch(train) [45][85/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:13 time: 0.2629 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:30 - mmengine - INFO - Epoch(train) [45][90/94] base_lr: 5.7719e-03 lr: 5.7719e-03 eta: 0:24:11 time: 0.2607 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:31 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 14:59:31 - mmengine - INFO - Saving checkpoint at 45 epochs 09/30 14:59:34 - mmengine - INFO - Epoch(val) [45][ 5/102] eta: 0:00:21 time: 0.1198 data_time: 0.0179 memory: 11783 09/30 14:59:34 - mmengine - INFO - Epoch(val) [45][ 10/102] eta: 0:00:15 time: 0.1197 data_time: 0.0177 memory: 1697 09/30 14:59:35 - mmengine - INFO - Epoch(val) [45][ 15/102] eta: 0:00:12 time: 0.1194 data_time: 0.0175 memory: 1697 09/30 14:59:36 - mmengine - INFO - Epoch(val) [45][ 20/102] eta: 0:00:11 time: 0.1197 data_time: 0.0175 memory: 1697 09/30 14:59:36 - mmengine - INFO - Epoch(val) [45][ 25/102] eta: 0:00:10 time: 0.1196 data_time: 0.0174 memory: 1697 09/30 14:59:37 - mmengine - INFO - Epoch(val) [45][ 30/102] eta: 0:00:09 time: 0.1199 data_time: 0.0176 memory: 1697 09/30 14:59:37 - mmengine - INFO - Epoch(val) [45][ 35/102] eta: 0:00:08 time: 0.1195 data_time: 0.0173 memory: 1697 09/30 14:59:38 - mmengine - INFO - Epoch(val) [45][ 40/102] eta: 0:00:07 time: 0.1199 data_time: 0.0175 memory: 1697 09/30 14:59:38 - mmengine - INFO - Epoch(val) [45][ 45/102] eta: 0:00:06 time: 0.1202 data_time: 0.0175 memory: 1697 09/30 14:59:39 - mmengine - INFO - Epoch(val) [45][ 50/102] eta: 0:00:06 time: 0.1207 data_time: 0.0177 memory: 1697 09/30 14:59:39 - mmengine - INFO - Epoch(val) [45][ 55/102] eta: 0:00:05 time: 0.1090 data_time: 0.0063 memory: 1697 09/30 14:59:40 - mmengine - INFO - Epoch(val) [45][ 60/102] eta: 0:00:04 time: 0.1094 data_time: 0.0066 memory: 1697 09/30 14:59:41 - mmengine - INFO - Epoch(val) [45][ 65/102] eta: 0:00:04 time: 0.1098 data_time: 0.0071 memory: 1697 09/30 14:59:41 - mmengine - INFO - Epoch(val) [45][ 70/102] eta: 0:00:03 time: 0.1101 data_time: 0.0073 memory: 1697 09/30 14:59:42 - mmengine - INFO - Epoch(val) [45][ 75/102] eta: 0:00:03 time: 0.1108 data_time: 0.0077 memory: 1697 09/30 14:59:42 - mmengine - INFO - Epoch(val) [45][ 80/102] eta: 0:00:02 time: 0.1106 data_time: 0.0077 memory: 1697 09/30 14:59:43 - mmengine - INFO - Epoch(val) [45][ 85/102] eta: 0:00:01 time: 0.1108 data_time: 0.0079 memory: 1697 09/30 14:59:43 - mmengine - INFO - Epoch(val) [45][ 90/102] eta: 0:00:01 time: 0.1109 data_time: 0.0079 memory: 1697 09/30 14:59:44 - mmengine - INFO - Epoch(val) [45][ 95/102] eta: 0:00:00 time: 0.1109 data_time: 0.0081 memory: 1697 09/30 14:59:44 - mmengine - INFO - Epoch(val) [45][100/102] eta: 0:00:00 time: 0.1109 data_time: 0.0080 memory: 1697 09/30 14:59:45 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 14:59:45 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 14:59:45 - mmengine - INFO - Epoch(val) [45][102/102] data_time: 0.0127 time: 0.1156 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 14:59:47 - mmengine - INFO - Epoch(train) [46][ 5/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:24:09 time: 0.2682 data_time: 0.0208 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:48 - mmengine - INFO - Epoch(train) [46][10/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:24:08 time: 0.2680 data_time: 0.0211 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:49 - mmengine - INFO - Epoch(train) [46][15/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:24:06 time: 0.2673 data_time: 0.0206 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:50 - mmengine - INFO - Epoch(train) [46][20/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:24:05 time: 0.2673 data_time: 0.0205 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:52 - mmengine - INFO - Epoch(train) [46][25/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:24:03 time: 0.2672 data_time: 0.0204 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:53 - mmengine - INFO - Epoch(train) [46][30/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:24:02 time: 0.2669 data_time: 0.0204 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:54 - mmengine - INFO - Epoch(train) [46][35/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:24:00 time: 0.2675 data_time: 0.0203 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:56 - mmengine - INFO - Epoch(train) [46][40/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:59 time: 0.2688 data_time: 0.0204 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:57 - mmengine - INFO - Epoch(train) [46][45/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:57 time: 0.2703 data_time: 0.0206 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 14:59:58 - mmengine - INFO - Epoch(train) [46][50/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:56 time: 0.2747 data_time: 0.0206 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:00 - mmengine - INFO - Epoch(train) [46][55/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:54 time: 0.2635 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:01 - mmengine - INFO - Epoch(train) [46][60/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:53 time: 0.2632 data_time: 0.0086 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:02 - mmengine - INFO - Epoch(train) [46][65/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:51 time: 0.2642 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:04 - mmengine - INFO - Epoch(train) [46][70/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:50 time: 0.2646 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:05 - mmengine - INFO - Epoch(train) [46][75/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:48 time: 0.2661 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:06 - mmengine - INFO - Epoch(train) [46][80/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:47 time: 0.2659 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:08 - mmengine - INFO - Epoch(train) [46][85/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:45 time: 0.2638 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:09 - mmengine - INFO - Epoch(train) [46][90/94] base_lr: 5.6688e-03 lr: 5.6688e-03 eta: 0:23:44 time: 0.2622 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:10 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:00:10 - mmengine - INFO - Saving checkpoint at 46 epochs 09/30 15:00:13 - mmengine - INFO - Epoch(val) [46][ 5/102] eta: 0:00:25 time: 0.1266 data_time: 0.0235 memory: 11783 09/30 15:00:13 - mmengine - INFO - Epoch(val) [46][ 10/102] eta: 0:00:17 time: 0.1262 data_time: 0.0232 memory: 1697 09/30 15:00:14 - mmengine - INFO - Epoch(val) [46][ 15/102] eta: 0:00:13 time: 0.1258 data_time: 0.0226 memory: 1697 09/30 15:00:14 - mmengine - INFO - Epoch(val) [46][ 20/102] eta: 0:00:12 time: 0.1253 data_time: 0.0224 memory: 1697 09/30 15:00:15 - mmengine - INFO - Epoch(val) [46][ 25/102] eta: 0:00:10 time: 0.1250 data_time: 0.0220 memory: 1697 09/30 15:00:15 - mmengine - INFO - Epoch(val) [46][ 30/102] eta: 0:00:09 time: 0.1251 data_time: 0.0221 memory: 1697 09/30 15:00:16 - mmengine - INFO - Epoch(val) [46][ 35/102] eta: 0:00:08 time: 0.1249 data_time: 0.0220 memory: 1697 09/30 15:00:16 - mmengine - INFO - Epoch(val) [46][ 40/102] eta: 0:00:07 time: 0.1249 data_time: 0.0220 memory: 1697 09/30 15:00:17 - mmengine - INFO - Epoch(val) [46][ 45/102] eta: 0:00:07 time: 0.1248 data_time: 0.0220 memory: 1697 09/30 15:00:17 - mmengine - INFO - Epoch(val) [46][ 50/102] eta: 0:00:06 time: 0.1246 data_time: 0.0219 memory: 1697 09/30 15:00:18 - mmengine - INFO - Epoch(val) [46][ 55/102] eta: 0:00:05 time: 0.1088 data_time: 0.0064 memory: 1697 09/30 15:00:18 - mmengine - INFO - Epoch(val) [46][ 60/102] eta: 0:00:05 time: 0.1089 data_time: 0.0066 memory: 1697 09/30 15:00:19 - mmengine - INFO - Epoch(val) [46][ 65/102] eta: 0:00:04 time: 0.1091 data_time: 0.0069 memory: 1697 09/30 15:00:20 - mmengine - INFO - Epoch(val) [46][ 70/102] eta: 0:00:03 time: 0.1092 data_time: 0.0069 memory: 1697 09/30 15:00:20 - mmengine - INFO - Epoch(val) [46][ 75/102] eta: 0:00:03 time: 0.1091 data_time: 0.0070 memory: 1697 09/30 15:00:21 - mmengine - INFO - Epoch(val) [46][ 80/102] eta: 0:00:02 time: 0.1092 data_time: 0.0069 memory: 1697 09/30 15:00:21 - mmengine - INFO - Epoch(val) [46][ 85/102] eta: 0:00:02 time: 0.1092 data_time: 0.0068 memory: 1697 09/30 15:00:22 - mmengine - INFO - Epoch(val) [46][ 90/102] eta: 0:00:01 time: 0.1091 data_time: 0.0068 memory: 1697 09/30 15:00:22 - mmengine - INFO - Epoch(val) [46][ 95/102] eta: 0:00:00 time: 0.1090 data_time: 0.0068 memory: 1697 09/30 15:00:23 - mmengine - INFO - Epoch(val) [46][100/102] eta: 0:00:00 time: 0.1088 data_time: 0.0067 memory: 1697 09/30 15:00:23 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:00:23 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:00:23 - mmengine - INFO - Epoch(val) [46][102/102] data_time: 0.0141 time: 0.1165 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:00:26 - mmengine - INFO - Epoch(train) [47][ 5/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:42 time: 0.2807 data_time: 0.0314 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:27 - mmengine - INFO - Epoch(train) [47][10/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:40 time: 0.2808 data_time: 0.0314 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:28 - mmengine - INFO - Epoch(train) [47][15/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:39 time: 0.2809 data_time: 0.0311 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:30 - mmengine - INFO - Epoch(train) [47][20/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:37 time: 0.2809 data_time: 0.0308 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:31 - mmengine - INFO - Epoch(train) [47][25/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:36 time: 0.2810 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:32 - mmengine - INFO - Epoch(train) [47][30/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:34 time: 0.2795 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:33 - mmengine - INFO - Epoch(train) [47][35/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:33 time: 0.2796 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:35 - mmengine - INFO - Epoch(train) [47][40/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:31 time: 0.2811 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:36 - mmengine - INFO - Epoch(train) [47][45/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:30 time: 0.2827 data_time: 0.0308 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:37 - mmengine - INFO - Epoch(train) [47][50/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:28 time: 0.2871 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:39 - mmengine - INFO - Epoch(train) [47][55/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:27 time: 0.2643 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:40 - mmengine - INFO - Epoch(train) [47][60/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:25 time: 0.2644 data_time: 0.0087 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:41 - mmengine - INFO - Epoch(train) [47][65/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:24 time: 0.2647 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:43 - mmengine - INFO - Epoch(train) [47][70/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:23 time: 0.2647 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:44 - mmengine - INFO - Epoch(train) [47][75/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:21 time: 0.2649 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:45 - mmengine - INFO - Epoch(train) [47][80/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:20 time: 0.2642 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:47 - mmengine - INFO - Epoch(train) [47][85/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:18 time: 0.2621 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:48 - mmengine - INFO - Epoch(train) [47][90/94] base_lr: 5.5656e-03 lr: 5.5656e-03 eta: 0:23:16 time: 0.2603 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:00:49 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:00:49 - mmengine - INFO - Saving checkpoint at 47 epochs 09/30 15:00:51 - mmengine - INFO - Epoch(val) [47][ 5/102] eta: 0:00:22 time: 0.1214 data_time: 0.0191 memory: 11783 09/30 15:00:52 - mmengine - INFO - Epoch(val) [47][ 10/102] eta: 0:00:15 time: 0.1213 data_time: 0.0189 memory: 1697 09/30 15:00:52 - mmengine - INFO - Epoch(val) [47][ 15/102] eta: 0:00:13 time: 0.1212 data_time: 0.0186 memory: 1697 09/30 15:00:53 - mmengine - INFO - Epoch(val) [47][ 20/102] eta: 0:00:11 time: 0.1211 data_time: 0.0186 memory: 1697 09/30 15:00:53 - mmengine - INFO - Epoch(val) [47][ 25/102] eta: 0:00:10 time: 0.1208 data_time: 0.0184 memory: 1697 09/30 15:00:54 - mmengine - INFO - Epoch(val) [47][ 30/102] eta: 0:00:09 time: 0.1207 data_time: 0.0185 memory: 1697 09/30 15:00:54 - mmengine - INFO - Epoch(val) [47][ 35/102] eta: 0:00:08 time: 0.1204 data_time: 0.0183 memory: 1697 09/30 15:00:55 - mmengine - INFO - Epoch(val) [47][ 40/102] eta: 0:00:07 time: 0.1205 data_time: 0.0184 memory: 1697 09/30 15:00:55 - mmengine - INFO - Epoch(val) [47][ 45/102] eta: 0:00:06 time: 0.1206 data_time: 0.0184 memory: 1697 09/30 15:00:56 - mmengine - INFO - Epoch(val) [47][ 50/102] eta: 0:00:06 time: 0.1206 data_time: 0.0184 memory: 1697 09/30 15:00:56 - mmengine - INFO - Epoch(val) [47][ 55/102] eta: 0:00:05 time: 0.1079 data_time: 0.0059 memory: 1697 09/30 15:00:57 - mmengine - INFO - Epoch(val) [47][ 60/102] eta: 0:00:04 time: 0.1080 data_time: 0.0061 memory: 1697 09/30 15:00:58 - mmengine - INFO - Epoch(val) [47][ 65/102] eta: 0:00:04 time: 0.1082 data_time: 0.0063 memory: 1697 09/30 15:00:58 - mmengine - INFO - Epoch(val) [47][ 70/102] eta: 0:00:03 time: 0.1081 data_time: 0.0063 memory: 1697 09/30 15:00:59 - mmengine - INFO - Epoch(val) [47][ 75/102] eta: 0:00:03 time: 0.1082 data_time: 0.0064 memory: 1697 09/30 15:00:59 - mmengine - INFO - Epoch(val) [47][ 80/102] eta: 0:00:02 time: 0.1083 data_time: 0.0063 memory: 1697 09/30 15:01:00 - mmengine - INFO - Epoch(val) [47][ 85/102] eta: 0:00:01 time: 0.1084 data_time: 0.0063 memory: 1697 09/30 15:01:00 - mmengine - INFO - Epoch(val) [47][ 90/102] eta: 0:00:01 time: 0.1085 data_time: 0.0064 memory: 1697 09/30 15:01:01 - mmengine - INFO - Epoch(val) [47][ 95/102] eta: 0:00:00 time: 0.1086 data_time: 0.0064 memory: 1697 09/30 15:01:01 - mmengine - INFO - Epoch(val) [47][100/102] eta: 0:00:00 time: 0.1086 data_time: 0.0063 memory: 1697 09/30 15:01:02 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:01:02 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:01:02 - mmengine - INFO - Epoch(val) [47][102/102] data_time: 0.0122 time: 0.1144 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:01:04 - mmengine - INFO - Epoch(train) [48][ 5/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:15 time: 0.2791 data_time: 0.0320 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:05 - mmengine - INFO - Epoch(train) [48][10/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:13 time: 0.2780 data_time: 0.0314 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:07 - mmengine - INFO - Epoch(train) [48][15/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:12 time: 0.2785 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:08 - mmengine - INFO - Epoch(train) [48][20/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:10 time: 0.2778 data_time: 0.0313 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:09 - mmengine - INFO - Epoch(train) [48][25/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:09 time: 0.2774 data_time: 0.0311 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:11 - mmengine - INFO - Epoch(train) [48][30/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:07 time: 0.2766 data_time: 0.0311 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:12 - mmengine - INFO - Epoch(train) [48][35/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:06 time: 0.2774 data_time: 0.0311 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:13 - mmengine - INFO - Epoch(train) [48][40/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:04 time: 0.2790 data_time: 0.0312 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:15 - mmengine - INFO - Epoch(train) [48][45/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:03 time: 0.2810 data_time: 0.0312 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:16 - mmengine - INFO - Epoch(train) [48][50/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:01 time: 0.2850 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:17 - mmengine - INFO - Epoch(train) [48][55/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:23:00 time: 0.2624 data_time: 0.0085 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:19 - mmengine - INFO - Epoch(train) [48][60/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:22:58 time: 0.2633 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:20 - mmengine - INFO - Epoch(train) [48][65/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:22:57 time: 0.2632 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:21 - mmengine - INFO - Epoch(train) [48][70/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:22:55 time: 0.2636 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:22 - mmengine - INFO - Epoch(train) [48][75/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:22:54 time: 0.2635 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:24 - mmengine - INFO - Epoch(train) [48][80/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:22:52 time: 0.2632 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:25 - mmengine - INFO - Epoch(train) [48][85/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:22:51 time: 0.2616 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:26 - mmengine - INFO - Epoch(train) [48][90/94] base_lr: 5.4625e-03 lr: 5.4625e-03 eta: 0:22:49 time: 0.2600 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:27 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:01:27 - mmengine - INFO - Saving checkpoint at 48 epochs 09/30 15:01:30 - mmengine - INFO - Epoch(val) [48][ 5/102] eta: 0:00:20 time: 0.1195 data_time: 0.0169 memory: 11783 09/30 15:01:30 - mmengine - INFO - Epoch(val) [48][ 10/102] eta: 0:00:14 time: 0.1191 data_time: 0.0167 memory: 1697 09/30 15:01:31 - mmengine - INFO - Epoch(val) [48][ 15/102] eta: 0:00:12 time: 0.1187 data_time: 0.0164 memory: 1697 09/30 15:01:31 - mmengine - INFO - Epoch(val) [48][ 20/102] eta: 0:00:10 time: 0.1186 data_time: 0.0164 memory: 1697 09/30 15:01:32 - mmengine - INFO - Epoch(val) [48][ 25/102] eta: 0:00:09 time: 0.1185 data_time: 0.0163 memory: 1697 09/30 15:01:32 - mmengine - INFO - Epoch(val) [48][ 30/102] eta: 0:00:09 time: 0.1186 data_time: 0.0164 memory: 1697 09/30 15:01:33 - mmengine - INFO - Epoch(val) [48][ 35/102] eta: 0:00:08 time: 0.1181 data_time: 0.0162 memory: 1697 09/30 15:01:33 - mmengine - INFO - Epoch(val) [48][ 40/102] eta: 0:00:07 time: 0.1182 data_time: 0.0163 memory: 1697 09/30 15:01:34 - mmengine - INFO - Epoch(val) [48][ 45/102] eta: 0:00:06 time: 0.1183 data_time: 0.0164 memory: 1697 09/30 15:01:34 - mmengine - INFO - Epoch(val) [48][ 50/102] eta: 0:00:06 time: 0.1183 data_time: 0.0164 memory: 1697 09/30 15:01:35 - mmengine - INFO - Epoch(val) [48][ 55/102] eta: 0:00:05 time: 0.1075 data_time: 0.0058 memory: 1697 09/30 15:01:36 - mmengine - INFO - Epoch(val) [48][ 60/102] eta: 0:00:04 time: 0.1076 data_time: 0.0060 memory: 1697 09/30 15:01:36 - mmengine - INFO - Epoch(val) [48][ 65/102] eta: 0:00:04 time: 0.1080 data_time: 0.0063 memory: 1697 09/30 15:01:37 - mmengine - INFO - Epoch(val) [48][ 70/102] eta: 0:00:03 time: 0.1080 data_time: 0.0063 memory: 1697 09/30 15:01:37 - mmengine - INFO - Epoch(val) [48][ 75/102] eta: 0:00:03 time: 0.1081 data_time: 0.0063 memory: 1697 09/30 15:01:38 - mmengine - INFO - Epoch(val) [48][ 80/102] eta: 0:00:02 time: 0.1080 data_time: 0.0062 memory: 1697 09/30 15:01:38 - mmengine - INFO - Epoch(val) [48][ 85/102] eta: 0:00:01 time: 0.1081 data_time: 0.0063 memory: 1697 09/30 15:01:39 - mmengine - INFO - Epoch(val) [48][ 90/102] eta: 0:00:01 time: 0.1079 data_time: 0.0062 memory: 1697 09/30 15:01:39 - mmengine - INFO - Epoch(val) [48][ 95/102] eta: 0:00:00 time: 0.1077 data_time: 0.0062 memory: 1697 09/30 15:01:40 - mmengine - INFO - Epoch(val) [48][100/102] eta: 0:00:00 time: 0.1074 data_time: 0.0061 memory: 1697 09/30 15:01:40 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:01:40 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:01:40 - mmengine - INFO - Epoch(val) [48][102/102] data_time: 0.0111 time: 0.1127 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:01:42 - mmengine - INFO - Epoch(train) [49][ 5/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:47 time: 0.2732 data_time: 0.0258 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:44 - mmengine - INFO - Epoch(train) [49][10/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:46 time: 0.2730 data_time: 0.0260 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:45 - mmengine - INFO - Epoch(train) [49][15/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:44 time: 0.2723 data_time: 0.0255 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:46 - mmengine - INFO - Epoch(train) [49][20/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:43 time: 0.2722 data_time: 0.0255 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:47 - mmengine - INFO - Epoch(train) [49][25/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:41 time: 0.2718 data_time: 0.0253 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:49 - mmengine - INFO - Epoch(train) [49][30/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:40 time: 0.2721 data_time: 0.0253 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:50 - mmengine - INFO - Epoch(train) [49][35/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:38 time: 0.2723 data_time: 0.0253 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:51 - mmengine - INFO - Epoch(train) [49][40/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:37 time: 0.2736 data_time: 0.0253 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:53 - mmengine - INFO - Epoch(train) [49][45/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:35 time: 0.2757 data_time: 0.0255 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:54 - mmengine - INFO - Epoch(train) [49][50/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:34 time: 0.2797 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:55 - mmengine - INFO - Epoch(train) [49][55/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:32 time: 0.2625 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:57 - mmengine - INFO - Epoch(train) [49][60/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:31 time: 0.2629 data_time: 0.0084 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:58 - mmengine - INFO - Epoch(train) [49][65/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:29 time: 0.2633 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:01:59 - mmengine - INFO - Epoch(train) [49][70/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:28 time: 0.2632 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:01 - mmengine - INFO - Epoch(train) [49][75/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:26 time: 0.2634 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:02 - mmengine - INFO - Epoch(train) [49][80/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:25 time: 0.2638 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:03 - mmengine - INFO - Epoch(train) [49][85/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:23 time: 0.2624 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:04 - mmengine - INFO - Epoch(train) [49][90/94] base_lr: 5.3594e-03 lr: 5.3594e-03 eta: 0:22:22 time: 0.2605 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:05 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:02:05 - mmengine - INFO - Saving checkpoint at 49 epochs 09/30 15:02:08 - mmengine - INFO - Epoch(val) [49][ 5/102] eta: 0:00:23 time: 0.1213 data_time: 0.0198 memory: 11783 09/30 15:02:09 - mmengine - INFO - Epoch(val) [49][ 10/102] eta: 0:00:16 time: 0.1216 data_time: 0.0198 memory: 1697 09/30 15:02:09 - mmengine - INFO - Epoch(val) [49][ 15/102] eta: 0:00:13 time: 0.1219 data_time: 0.0197 memory: 1697 09/30 15:02:10 - mmengine - INFO - Epoch(val) [49][ 20/102] eta: 0:00:11 time: 0.1226 data_time: 0.0202 memory: 1697 09/30 15:02:10 - mmengine - INFO - Epoch(val) [49][ 25/102] eta: 0:00:10 time: 0.1230 data_time: 0.0204 memory: 1697 09/30 15:02:11 - mmengine - INFO - Epoch(val) [49][ 30/102] eta: 0:00:09 time: 0.1232 data_time: 0.0208 memory: 1697 09/30 15:02:11 - mmengine - INFO - Epoch(val) [49][ 35/102] eta: 0:00:08 time: 0.1232 data_time: 0.0206 memory: 1697 09/30 15:02:12 - mmengine - INFO - Epoch(val) [49][ 40/102] eta: 0:00:07 time: 0.1239 data_time: 0.0209 memory: 1697 09/30 15:02:13 - mmengine - INFO - Epoch(val) [49][ 45/102] eta: 0:00:07 time: 0.1244 data_time: 0.0210 memory: 1697 09/30 15:02:13 - mmengine - INFO - Epoch(val) [49][ 50/102] eta: 0:00:06 time: 0.1250 data_time: 0.0212 memory: 1697 09/30 15:02:14 - mmengine - INFO - Epoch(val) [49][ 55/102] eta: 0:00:05 time: 0.1114 data_time: 0.0075 memory: 1697 09/30 15:02:14 - mmengine - INFO - Epoch(val) [49][ 60/102] eta: 0:00:05 time: 0.1114 data_time: 0.0077 memory: 1697 09/30 15:02:15 - mmengine - INFO - Epoch(val) [49][ 65/102] eta: 0:00:04 time: 0.1114 data_time: 0.0079 memory: 1697 09/30 15:02:15 - mmengine - INFO - Epoch(val) [49][ 70/102] eta: 0:00:03 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 15:02:16 - mmengine - INFO - Epoch(val) [49][ 75/102] eta: 0:00:03 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:02:16 - mmengine - INFO - Epoch(val) [49][ 80/102] eta: 0:00:02 time: 0.1106 data_time: 0.0071 memory: 1697 09/30 15:02:17 - mmengine - INFO - Epoch(val) [49][ 85/102] eta: 0:00:02 time: 0.1109 data_time: 0.0073 memory: 1697 09/30 15:02:18 - mmengine - INFO - Epoch(val) [49][ 90/102] eta: 0:00:01 time: 0.1106 data_time: 0.0073 memory: 1697 09/30 15:02:18 - mmengine - INFO - Epoch(val) [49][ 95/102] eta: 0:00:00 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:02:19 - mmengine - INFO - Epoch(val) [49][100/102] eta: 0:00:00 time: 0.1099 data_time: 0.0071 memory: 1697 09/30 15:02:19 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:02:19 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:02:19 - mmengine - INFO - Epoch(val) [49][102/102] data_time: 0.0139 time: 0.1172 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:02:22 - mmengine - INFO - Epoch(train) [50][ 5/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:20 time: 0.2844 data_time: 0.0370 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:23 - mmengine - INFO - Epoch(train) [50][10/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:19 time: 0.2848 data_time: 0.0370 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:24 - mmengine - INFO - Epoch(train) [50][15/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:17 time: 0.2842 data_time: 0.0368 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:26 - mmengine - INFO - Epoch(train) [50][20/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:16 time: 0.2845 data_time: 0.0371 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:27 - mmengine - INFO - Epoch(train) [50][25/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:14 time: 0.2841 data_time: 0.0367 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:28 - mmengine - INFO - Epoch(train) [50][30/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:13 time: 0.2848 data_time: 0.0367 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:30 - mmengine - INFO - Epoch(train) [50][35/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:11 time: 0.2848 data_time: 0.0367 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:31 - mmengine - INFO - Epoch(train) [50][40/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:10 time: 0.2861 data_time: 0.0370 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:32 - mmengine - INFO - Epoch(train) [50][45/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:08 time: 0.2875 data_time: 0.0368 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:34 - mmengine - INFO - Epoch(train) [50][50/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:07 time: 0.2921 data_time: 0.0371 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:35 - mmengine - INFO - Epoch(train) [50][55/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:05 time: 0.2645 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:36 - mmengine - INFO - Epoch(train) [50][60/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:04 time: 0.2648 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:38 - mmengine - INFO - Epoch(train) [50][65/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:02 time: 0.2652 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:39 - mmengine - INFO - Epoch(train) [50][70/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:22:01 time: 0.2649 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:40 - mmengine - INFO - Epoch(train) [50][75/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:21:59 time: 0.2657 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:41 - mmengine - INFO - Epoch(train) [50][80/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:21:58 time: 0.2647 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:43 - mmengine - INFO - Epoch(train) [50][85/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:21:56 time: 0.2630 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:44 - mmengine - INFO - Epoch(train) [50][90/94] base_lr: 5.2563e-03 lr: 5.2563e-03 eta: 0:21:55 time: 0.2612 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:02:45 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:02:45 - mmengine - INFO - Saving checkpoint at 50 epochs 09/30 15:02:47 - mmengine - INFO - Epoch(val) [50][ 5/102] eta: 0:00:23 time: 0.1227 data_time: 0.0199 memory: 11783 09/30 15:02:48 - mmengine - INFO - Epoch(val) [50][ 10/102] eta: 0:00:15 time: 0.1222 data_time: 0.0196 memory: 1697 09/30 15:02:48 - mmengine - INFO - Epoch(val) [50][ 15/102] eta: 0:00:13 time: 0.1218 data_time: 0.0193 memory: 1697 09/30 15:02:49 - mmengine - INFO - Epoch(val) [50][ 20/102] eta: 0:00:11 time: 0.1219 data_time: 0.0192 memory: 1697 09/30 15:02:49 - mmengine - INFO - Epoch(val) [50][ 25/102] eta: 0:00:10 time: 0.1216 data_time: 0.0191 memory: 1697 09/30 15:02:50 - mmengine - INFO - Epoch(val) [50][ 30/102] eta: 0:00:09 time: 0.1218 data_time: 0.0194 memory: 1697 09/30 15:02:51 - mmengine - INFO - Epoch(val) [50][ 35/102] eta: 0:00:08 time: 0.1214 data_time: 0.0190 memory: 1697 09/30 15:02:51 - mmengine - INFO - Epoch(val) [50][ 40/102] eta: 0:00:07 time: 0.1218 data_time: 0.0192 memory: 1697 09/30 15:02:52 - mmengine - INFO - Epoch(val) [50][ 45/102] eta: 0:00:07 time: 0.1221 data_time: 0.0192 memory: 1697 09/30 15:02:52 - mmengine - INFO - Epoch(val) [50][ 50/102] eta: 0:00:06 time: 0.1223 data_time: 0.0193 memory: 1697 09/30 15:02:53 - mmengine - INFO - Epoch(val) [50][ 55/102] eta: 0:00:05 time: 0.1094 data_time: 0.0064 memory: 1697 09/30 15:02:53 - mmengine - INFO - Epoch(val) [50][ 60/102] eta: 0:00:05 time: 0.1096 data_time: 0.0066 memory: 1697 09/30 15:02:54 - mmengine - INFO - Epoch(val) [50][ 65/102] eta: 0:00:04 time: 0.1099 data_time: 0.0069 memory: 1697 09/30 15:02:54 - mmengine - INFO - Epoch(val) [50][ 70/102] eta: 0:00:03 time: 0.1099 data_time: 0.0069 memory: 1697 09/30 15:02:55 - mmengine - INFO - Epoch(val) [50][ 75/102] eta: 0:00:03 time: 0.1100 data_time: 0.0069 memory: 1697 09/30 15:02:55 - mmengine - INFO - Epoch(val) [50][ 80/102] eta: 0:00:02 time: 0.1098 data_time: 0.0067 memory: 1697 09/30 15:02:56 - mmengine - INFO - Epoch(val) [50][ 85/102] eta: 0:00:01 time: 0.1098 data_time: 0.0068 memory: 1697 09/30 15:02:57 - mmengine - INFO - Epoch(val) [50][ 90/102] eta: 0:00:01 time: 0.1097 data_time: 0.0068 memory: 1697 09/30 15:02:57 - mmengine - INFO - Epoch(val) [50][ 95/102] eta: 0:00:00 time: 0.1097 data_time: 0.0068 memory: 1697 09/30 15:02:58 - mmengine - INFO - Epoch(val) [50][100/102] eta: 0:00:00 time: 0.1093 data_time: 0.0067 memory: 1697 09/30 15:02:58 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:02:58 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:02:58 - mmengine - INFO - Epoch(val) [50][102/102] data_time: 0.0128 time: 0.1156 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:03:00 - mmengine - INFO - Epoch(train) [51][ 5/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:53 time: 0.2824 data_time: 0.0345 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:02 - mmengine - INFO - Epoch(train) [51][10/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:52 time: 0.2821 data_time: 0.0347 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:03 - mmengine - INFO - Epoch(train) [51][15/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:50 time: 0.2811 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:04 - mmengine - INFO - Epoch(train) [51][20/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:49 time: 0.2806 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:06 - mmengine - INFO - Epoch(train) [51][25/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:47 time: 0.2808 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:07 - mmengine - INFO - Epoch(train) [51][30/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:46 time: 0.2814 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:08 - mmengine - INFO - Epoch(train) [51][35/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:44 time: 0.2819 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:10 - mmengine - INFO - Epoch(train) [51][40/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:43 time: 0.2839 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:11 - mmengine - INFO - Epoch(train) [51][45/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:42 time: 0.2855 data_time: 0.0343 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:12 - mmengine - INFO - Epoch(train) [51][50/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:40 time: 0.2898 data_time: 0.0346 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:14 - mmengine - INFO - Epoch(train) [51][55/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:39 time: 0.2651 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:15 - mmengine - INFO - Epoch(train) [51][60/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:37 time: 0.2652 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:16 - mmengine - INFO - Epoch(train) [51][65/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:36 time: 0.2659 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:18 - mmengine - INFO - Epoch(train) [51][70/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:34 time: 0.2668 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:19 - mmengine - INFO - Epoch(train) [51][75/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:33 time: 0.2666 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:21 - mmengine - INFO - Epoch(train) [51][80/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:31 time: 0.2705 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:22 - mmengine - INFO - Epoch(train) [51][85/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:30 time: 0.2688 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:23 - mmengine - INFO - Epoch(train) [51][90/94] base_lr: 5.1531e-03 lr: 5.1531e-03 eta: 0:21:28 time: 0.2670 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:24 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:03:24 - mmengine - INFO - Saving checkpoint at 51 epochs 09/30 15:03:26 - mmengine - INFO - Epoch(val) [51][ 5/102] eta: 0:00:24 time: 0.1231 data_time: 0.0203 memory: 11783 09/30 15:03:27 - mmengine - INFO - Epoch(val) [51][ 10/102] eta: 0:00:16 time: 0.1233 data_time: 0.0203 memory: 1697 09/30 15:03:28 - mmengine - INFO - Epoch(val) [51][ 15/102] eta: 0:00:13 time: 0.1231 data_time: 0.0200 memory: 1697 09/30 15:03:28 - mmengine - INFO - Epoch(val) [51][ 20/102] eta: 0:00:11 time: 0.1231 data_time: 0.0201 memory: 1697 09/30 15:03:29 - mmengine - INFO - Epoch(val) [51][ 25/102] eta: 0:00:10 time: 0.1232 data_time: 0.0200 memory: 1697 09/30 15:03:29 - mmengine - INFO - Epoch(val) [51][ 30/102] eta: 0:00:09 time: 0.1235 data_time: 0.0202 memory: 1697 09/30 15:03:30 - mmengine - INFO - Epoch(val) [51][ 35/102] eta: 0:00:08 time: 0.1233 data_time: 0.0201 memory: 1697 09/30 15:03:30 - mmengine - INFO - Epoch(val) [51][ 40/102] eta: 0:00:07 time: 0.1233 data_time: 0.0202 memory: 1697 09/30 15:03:31 - mmengine - INFO - Epoch(val) [51][ 45/102] eta: 0:00:07 time: 0.1236 data_time: 0.0204 memory: 1697 09/30 15:03:31 - mmengine - INFO - Epoch(val) [51][ 50/102] eta: 0:00:06 time: 0.1239 data_time: 0.0205 memory: 1697 09/30 15:03:32 - mmengine - INFO - Epoch(val) [51][ 55/102] eta: 0:00:05 time: 0.1102 data_time: 0.0069 memory: 1697 09/30 15:03:33 - mmengine - INFO - Epoch(val) [51][ 60/102] eta: 0:00:05 time: 0.1103 data_time: 0.0071 memory: 1697 09/30 15:03:33 - mmengine - INFO - Epoch(val) [51][ 65/102] eta: 0:00:04 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:03:34 - mmengine - INFO - Epoch(val) [51][ 70/102] eta: 0:00:03 time: 0.1108 data_time: 0.0074 memory: 1697 09/30 15:03:34 - mmengine - INFO - Epoch(val) [51][ 75/102] eta: 0:00:03 time: 0.1110 data_time: 0.0076 memory: 1697 09/30 15:03:35 - mmengine - INFO - Epoch(val) [51][ 80/102] eta: 0:00:02 time: 0.1109 data_time: 0.0074 memory: 1697 09/30 15:03:35 - mmengine - INFO - Epoch(val) [51][ 85/102] eta: 0:00:02 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:03:36 - mmengine - INFO - Epoch(val) [51][ 90/102] eta: 0:00:01 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:03:36 - mmengine - INFO - Epoch(val) [51][ 95/102] eta: 0:00:00 time: 0.1112 data_time: 0.0077 memory: 1697 09/30 15:03:37 - mmengine - INFO - Epoch(val) [51][100/102] eta: 0:00:00 time: 0.1110 data_time: 0.0075 memory: 1697 09/30 15:03:37 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:03:37 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:03:37 - mmengine - INFO - Epoch(val) [51][102/102] data_time: 0.0138 time: 0.1172 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:03:40 - mmengine - INFO - Epoch(train) [52][ 5/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:27 time: 0.2879 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:41 - mmengine - INFO - Epoch(train) [52][10/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:25 time: 0.2872 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:42 - mmengine - INFO - Epoch(train) [52][15/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:24 time: 0.2871 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:44 - mmengine - INFO - Epoch(train) [52][20/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:22 time: 0.2863 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:45 - mmengine - INFO - Epoch(train) [52][25/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:21 time: 0.2867 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:46 - mmengine - INFO - Epoch(train) [52][30/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:19 time: 0.2883 data_time: 0.0332 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:48 - mmengine - INFO - Epoch(train) [52][35/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:18 time: 0.2893 data_time: 0.0331 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:49 - mmengine - INFO - Epoch(train) [52][40/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:17 time: 0.2862 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:50 - mmengine - INFO - Epoch(train) [52][45/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:15 time: 0.2876 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:52 - mmengine - INFO - Epoch(train) [52][50/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:14 time: 0.2926 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:53 - mmengine - INFO - Epoch(train) [52][55/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:12 time: 0.2674 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:54 - mmengine - INFO - Epoch(train) [52][60/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:11 time: 0.2679 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:56 - mmengine - INFO - Epoch(train) [52][65/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:09 time: 0.2682 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:57 - mmengine - INFO - Epoch(train) [52][70/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:08 time: 0.2686 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:03:58 - mmengine - INFO - Epoch(train) [52][75/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:06 time: 0.2681 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:00 - mmengine - INFO - Epoch(train) [52][80/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:05 time: 0.2659 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:01 - mmengine - INFO - Epoch(train) [52][85/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:03 time: 0.2631 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:02 - mmengine - INFO - Epoch(train) [52][90/94] base_lr: 5.0500e-03 lr: 5.0500e-03 eta: 0:21:02 time: 0.2619 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:03 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:04:03 - mmengine - INFO - Saving checkpoint at 52 epochs 09/30 15:04:06 - mmengine - INFO - Epoch(val) [52][ 5/102] eta: 0:00:26 time: 0.1266 data_time: 0.0231 memory: 11783 09/30 15:04:07 - mmengine - INFO - Epoch(val) [52][ 10/102] eta: 0:00:17 time: 0.1263 data_time: 0.0229 memory: 1697 09/30 15:04:07 - mmengine - INFO - Epoch(val) [52][ 15/102] eta: 0:00:14 time: 0.1258 data_time: 0.0225 memory: 1697 09/30 15:04:08 - mmengine - INFO - Epoch(val) [52][ 20/102] eta: 0:00:12 time: 0.1257 data_time: 0.0224 memory: 1697 09/30 15:04:08 - mmengine - INFO - Epoch(val) [52][ 25/102] eta: 0:00:10 time: 0.1257 data_time: 0.0224 memory: 1697 09/30 15:04:09 - mmengine - INFO - Epoch(val) [52][ 30/102] eta: 0:00:09 time: 0.1260 data_time: 0.0226 memory: 1697 09/30 15:04:10 - mmengine - INFO - Epoch(val) [52][ 35/102] eta: 0:00:08 time: 0.1255 data_time: 0.0222 memory: 1697 09/30 15:04:10 - mmengine - INFO - Epoch(val) [52][ 40/102] eta: 0:00:08 time: 0.1256 data_time: 0.0223 memory: 1697 09/30 15:04:11 - mmengine - INFO - Epoch(val) [52][ 45/102] eta: 0:00:07 time: 0.1258 data_time: 0.0224 memory: 1697 09/30 15:04:11 - mmengine - INFO - Epoch(val) [52][ 50/102] eta: 0:00:06 time: 0.1257 data_time: 0.0224 memory: 1697 09/30 15:04:12 - mmengine - INFO - Epoch(val) [52][ 55/102] eta: 0:00:05 time: 0.1098 data_time: 0.0067 memory: 1697 09/30 15:04:12 - mmengine - INFO - Epoch(val) [52][ 60/102] eta: 0:00:05 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 15:04:13 - mmengine - INFO - Epoch(val) [52][ 65/102] eta: 0:00:04 time: 0.1108 data_time: 0.0076 memory: 1697 09/30 15:04:13 - mmengine - INFO - Epoch(val) [52][ 70/102] eta: 0:00:03 time: 0.1112 data_time: 0.0078 memory: 1697 09/30 15:04:14 - mmengine - INFO - Epoch(val) [52][ 75/102] eta: 0:00:03 time: 0.1115 data_time: 0.0081 memory: 1697 09/30 15:04:15 - mmengine - INFO - Epoch(val) [52][ 80/102] eta: 0:00:02 time: 0.1115 data_time: 0.0080 memory: 1697 09/30 15:04:15 - mmengine - INFO - Epoch(val) [52][ 85/102] eta: 0:00:02 time: 0.1117 data_time: 0.0083 memory: 1697 09/30 15:04:16 - mmengine - INFO - Epoch(val) [52][ 90/102] eta: 0:00:01 time: 0.1118 data_time: 0.0083 memory: 1697 09/30 15:04:16 - mmengine - INFO - Epoch(val) [52][ 95/102] eta: 0:00:00 time: 0.1117 data_time: 0.0083 memory: 1697 09/30 15:04:17 - mmengine - INFO - Epoch(val) [52][100/102] eta: 0:00:00 time: 0.1115 data_time: 0.0082 memory: 1697 09/30 15:04:17 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:04:17 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:04:17 - mmengine - INFO - Epoch(val) [52][102/102] data_time: 0.0151 time: 0.1184 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:04:19 - mmengine - INFO - Epoch(train) [53][ 5/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:21:00 time: 0.2769 data_time: 0.0282 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:21 - mmengine - INFO - Epoch(train) [53][10/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:58 time: 0.2766 data_time: 0.0283 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:22 - mmengine - INFO - Epoch(train) [53][15/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:57 time: 0.2772 data_time: 0.0283 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:23 - mmengine - INFO - Epoch(train) [53][20/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:55 time: 0.2766 data_time: 0.0283 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:25 - mmengine - INFO - Epoch(train) [53][25/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:54 time: 0.2761 data_time: 0.0281 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:26 - mmengine - INFO - Epoch(train) [53][30/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:52 time: 0.2762 data_time: 0.0277 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:27 - mmengine - INFO - Epoch(train) [53][35/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:51 time: 0.2763 data_time: 0.0278 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:29 - mmengine - INFO - Epoch(train) [53][40/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:50 time: 0.2784 data_time: 0.0278 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:30 - mmengine - INFO - Epoch(train) [53][45/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:48 time: 0.2804 data_time: 0.0280 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:31 - mmengine - INFO - Epoch(train) [53][50/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:47 time: 0.2852 data_time: 0.0281 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:33 - mmengine - INFO - Epoch(train) [53][55/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:45 time: 0.2656 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:34 - mmengine - INFO - Epoch(train) [53][60/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:44 time: 0.2654 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:35 - mmengine - INFO - Epoch(train) [53][65/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:42 time: 0.2655 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:37 - mmengine - INFO - Epoch(train) [53][70/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:41 time: 0.2664 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:38 - mmengine - INFO - Epoch(train) [53][75/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:39 time: 0.2667 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:39 - mmengine - INFO - Epoch(train) [53][80/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:38 time: 0.2661 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:40 - mmengine - INFO - Epoch(train) [53][85/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:36 time: 0.2650 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:42 - mmengine - INFO - Epoch(train) [53][90/94] base_lr: 4.9469e-03 lr: 4.9469e-03 eta: 0:20:35 time: 0.2627 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:04:43 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:04:43 - mmengine - INFO - Saving checkpoint at 53 epochs 09/30 15:04:45 - mmengine - INFO - Epoch(val) [53][ 5/102] eta: 0:00:25 time: 0.1273 data_time: 0.0238 memory: 11783 09/30 15:04:46 - mmengine - INFO - Epoch(val) [53][ 10/102] eta: 0:00:17 time: 0.1269 data_time: 0.0235 memory: 1697 09/30 15:04:46 - mmengine - INFO - Epoch(val) [53][ 15/102] eta: 0:00:14 time: 0.1264 data_time: 0.0231 memory: 1697 09/30 15:04:47 - mmengine - INFO - Epoch(val) [53][ 20/102] eta: 0:00:12 time: 0.1259 data_time: 0.0228 memory: 1697 09/30 15:04:48 - mmengine - INFO - Epoch(val) [53][ 25/102] eta: 0:00:10 time: 0.1253 data_time: 0.0224 memory: 1697 09/30 15:04:48 - mmengine - INFO - Epoch(val) [53][ 30/102] eta: 0:00:09 time: 0.1252 data_time: 0.0224 memory: 1697 09/30 15:04:49 - mmengine - INFO - Epoch(val) [53][ 35/102] eta: 0:00:08 time: 0.1249 data_time: 0.0222 memory: 1697 09/30 15:04:49 - mmengine - INFO - Epoch(val) [53][ 40/102] eta: 0:00:08 time: 0.1252 data_time: 0.0223 memory: 1697 09/30 15:04:50 - mmengine - INFO - Epoch(val) [53][ 45/102] eta: 0:00:07 time: 0.1256 data_time: 0.0224 memory: 1697 09/30 15:04:50 - mmengine - INFO - Epoch(val) [53][ 50/102] eta: 0:00:06 time: 0.1258 data_time: 0.0223 memory: 1697 09/30 15:04:51 - mmengine - INFO - Epoch(val) [53][ 55/102] eta: 0:00:05 time: 0.1101 data_time: 0.0066 memory: 1697 09/30 15:04:51 - mmengine - INFO - Epoch(val) [53][ 60/102] eta: 0:00:05 time: 0.1103 data_time: 0.0069 memory: 1697 09/30 15:04:52 - mmengine - INFO - Epoch(val) [53][ 65/102] eta: 0:00:04 time: 0.1106 data_time: 0.0071 memory: 1697 09/30 15:04:53 - mmengine - INFO - Epoch(val) [53][ 70/102] eta: 0:00:03 time: 0.1106 data_time: 0.0072 memory: 1697 09/30 15:04:53 - mmengine - INFO - Epoch(val) [53][ 75/102] eta: 0:00:03 time: 0.1106 data_time: 0.0073 memory: 1697 09/30 15:04:54 - mmengine - INFO - Epoch(val) [53][ 80/102] eta: 0:00:02 time: 0.1107 data_time: 0.0071 memory: 1697 09/30 15:04:54 - mmengine - INFO - Epoch(val) [53][ 85/102] eta: 0:00:02 time: 0.1108 data_time: 0.0073 memory: 1697 09/30 15:04:55 - mmengine - INFO - Epoch(val) [53][ 90/102] eta: 0:00:01 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 15:04:55 - mmengine - INFO - Epoch(val) [53][ 95/102] eta: 0:00:00 time: 0.1101 data_time: 0.0072 memory: 1697 09/30 15:04:56 - mmengine - INFO - Epoch(val) [53][100/102] eta: 0:00:00 time: 0.1096 data_time: 0.0071 memory: 1697 09/30 15:04:56 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:04:56 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:04:56 - mmengine - INFO - Epoch(val) [53][102/102] data_time: 0.0145 time: 0.1175 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:04:59 - mmengine - INFO - Epoch(train) [54][ 5/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:33 time: 0.2817 data_time: 0.0329 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:00 - mmengine - INFO - Epoch(train) [54][10/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:32 time: 0.2805 data_time: 0.0333 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:01 - mmengine - INFO - Epoch(train) [54][15/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:30 time: 0.2801 data_time: 0.0328 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:02 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:05:02 - mmengine - INFO - Epoch(train) [54][20/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:29 time: 0.2795 data_time: 0.0329 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:04 - mmengine - INFO - Epoch(train) [54][25/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:27 time: 0.2787 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:05 - mmengine - INFO - Epoch(train) [54][30/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:26 time: 0.2788 data_time: 0.0328 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:06 - mmengine - INFO - Epoch(train) [54][35/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:24 time: 0.2791 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:08 - mmengine - INFO - Epoch(train) [54][40/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:23 time: 0.2807 data_time: 0.0328 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:09 - mmengine - INFO - Epoch(train) [54][45/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:21 time: 0.2822 data_time: 0.0331 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:10 - mmengine - INFO - Epoch(train) [54][50/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:20 time: 0.2865 data_time: 0.0331 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:12 - mmengine - INFO - Epoch(train) [54][55/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:18 time: 0.2633 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:13 - mmengine - INFO - Epoch(train) [54][60/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:17 time: 0.2639 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:14 - mmengine - INFO - Epoch(train) [54][65/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:16 time: 0.2660 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:16 - mmengine - INFO - Epoch(train) [54][70/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:14 time: 0.2676 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:17 - mmengine - INFO - Epoch(train) [54][75/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:13 time: 0.2684 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:18 - mmengine - INFO - Epoch(train) [54][80/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:11 time: 0.2680 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:20 - mmengine - INFO - Epoch(train) [54][85/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:10 time: 0.2668 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:21 - mmengine - INFO - Epoch(train) [54][90/94] base_lr: 4.8438e-03 lr: 4.8438e-03 eta: 0:20:08 time: 0.2652 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:22 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:05:22 - mmengine - INFO - Saving checkpoint at 54 epochs 09/30 15:05:24 - mmengine - INFO - Epoch(val) [54][ 5/102] eta: 0:00:25 time: 0.1247 data_time: 0.0222 memory: 11783 09/30 15:05:25 - mmengine - INFO - Epoch(val) [54][ 10/102] eta: 0:00:17 time: 0.1247 data_time: 0.0220 memory: 1697 09/30 15:05:26 - mmengine - INFO - Epoch(val) [54][ 15/102] eta: 0:00:13 time: 0.1246 data_time: 0.0217 memory: 1697 09/30 15:05:26 - mmengine - INFO - Epoch(val) [54][ 20/102] eta: 0:00:12 time: 0.1248 data_time: 0.0217 memory: 1697 09/30 15:05:27 - mmengine - INFO - Epoch(val) [54][ 25/102] eta: 0:00:10 time: 0.1247 data_time: 0.0216 memory: 1697 09/30 15:05:27 - mmengine - INFO - Epoch(val) [54][ 30/102] eta: 0:00:09 time: 0.1250 data_time: 0.0217 memory: 1697 09/30 15:05:28 - mmengine - INFO - Epoch(val) [54][ 35/102] eta: 0:00:08 time: 0.1251 data_time: 0.0216 memory: 1697 09/30 15:05:28 - mmengine - INFO - Epoch(val) [54][ 40/102] eta: 0:00:08 time: 0.1253 data_time: 0.0217 memory: 1697 09/30 15:05:29 - mmengine - INFO - Epoch(val) [54][ 45/102] eta: 0:00:07 time: 0.1257 data_time: 0.0218 memory: 1697 09/30 15:05:29 - mmengine - INFO - Epoch(val) [54][ 50/102] eta: 0:00:06 time: 0.1259 data_time: 0.0218 memory: 1697 09/30 15:05:30 - mmengine - INFO - Epoch(val) [54][ 55/102] eta: 0:00:05 time: 0.1109 data_time: 0.0068 memory: 1697 09/30 15:05:31 - mmengine - INFO - Epoch(val) [54][ 60/102] eta: 0:00:05 time: 0.1108 data_time: 0.0070 memory: 1697 09/30 15:05:31 - mmengine - INFO - Epoch(val) [54][ 65/102] eta: 0:00:04 time: 0.1110 data_time: 0.0073 memory: 1697 09/30 15:05:32 - mmengine - INFO - Epoch(val) [54][ 70/102] eta: 0:00:03 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:05:32 - mmengine - INFO - Epoch(val) [54][ 75/102] eta: 0:00:03 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 15:05:33 - mmengine - INFO - Epoch(val) [54][ 80/102] eta: 0:00:02 time: 0.1105 data_time: 0.0074 memory: 1697 09/30 15:05:33 - mmengine - INFO - Epoch(val) [54][ 85/102] eta: 0:00:02 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 15:05:34 - mmengine - INFO - Epoch(val) [54][ 90/102] eta: 0:00:01 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:05:34 - mmengine - INFO - Epoch(val) [54][ 95/102] eta: 0:00:00 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 15:05:35 - mmengine - INFO - Epoch(val) [54][100/102] eta: 0:00:00 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 15:05:35 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:05:35 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:05:35 - mmengine - INFO - Epoch(val) [54][102/102] data_time: 0.0144 time: 0.1179 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:05:37 - mmengine - INFO - Epoch(train) [55][ 5/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:20:06 time: 0.2768 data_time: 0.0259 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:39 - mmengine - INFO - Epoch(train) [55][10/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:20:05 time: 0.2771 data_time: 0.0265 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:40 - mmengine - INFO - Epoch(train) [55][15/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:20:03 time: 0.2759 data_time: 0.0258 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:41 - mmengine - INFO - Epoch(train) [55][20/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:20:02 time: 0.2751 data_time: 0.0260 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:43 - mmengine - INFO - Epoch(train) [55][25/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:20:00 time: 0.2739 data_time: 0.0257 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:44 - mmengine - INFO - Epoch(train) [55][30/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:59 time: 0.2727 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:45 - mmengine - INFO - Epoch(train) [55][35/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:57 time: 0.2735 data_time: 0.0255 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:47 - mmengine - INFO - Epoch(train) [55][40/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:56 time: 0.2756 data_time: 0.0255 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:48 - mmengine - INFO - Epoch(train) [55][45/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:54 time: 0.2767 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:49 - mmengine - INFO - Epoch(train) [55][50/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:53 time: 0.2806 data_time: 0.0257 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:51 - mmengine - INFO - Epoch(train) [55][55/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:51 time: 0.2649 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:52 - mmengine - INFO - Epoch(train) [55][60/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:50 time: 0.2652 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:53 - mmengine - INFO - Epoch(train) [55][65/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:49 time: 0.2667 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:55 - mmengine - INFO - Epoch(train) [55][70/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:47 time: 0.2666 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:56 - mmengine - INFO - Epoch(train) [55][75/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:46 time: 0.2661 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:57 - mmengine - INFO - Epoch(train) [55][80/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:44 time: 0.2661 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:05:58 - mmengine - INFO - Epoch(train) [55][85/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:43 time: 0.2637 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:00 - mmengine - INFO - Epoch(train) [55][90/94] base_lr: 4.7406e-03 lr: 4.7406e-03 eta: 0:19:41 time: 0.2617 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:01 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:06:01 - mmengine - INFO - Saving checkpoint at 55 epochs 09/30 15:06:03 - mmengine - INFO - Epoch(val) [55][ 5/102] eta: 0:00:25 time: 0.1259 data_time: 0.0228 memory: 11783 09/30 15:06:04 - mmengine - INFO - Epoch(val) [55][ 10/102] eta: 0:00:17 time: 0.1260 data_time: 0.0227 memory: 1697 09/30 15:06:04 - mmengine - INFO - Epoch(val) [55][ 15/102] eta: 0:00:14 time: 0.1258 data_time: 0.0223 memory: 1697 09/30 15:06:05 - mmengine - INFO - Epoch(val) [55][ 20/102] eta: 0:00:12 time: 0.1258 data_time: 0.0223 memory: 1697 09/30 15:06:06 - mmengine - INFO - Epoch(val) [55][ 25/102] eta: 0:00:10 time: 0.1256 data_time: 0.0222 memory: 1697 09/30 15:06:06 - mmengine - INFO - Epoch(val) [55][ 30/102] eta: 0:00:09 time: 0.1255 data_time: 0.0224 memory: 1697 09/30 15:06:07 - mmengine - INFO - Epoch(val) [55][ 35/102] eta: 0:00:08 time: 0.1252 data_time: 0.0221 memory: 1697 09/30 15:06:07 - mmengine - INFO - Epoch(val) [55][ 40/102] eta: 0:00:08 time: 0.1252 data_time: 0.0222 memory: 1697 09/30 15:06:08 - mmengine - INFO - Epoch(val) [55][ 45/102] eta: 0:00:07 time: 0.1252 data_time: 0.0222 memory: 1697 09/30 15:06:08 - mmengine - INFO - Epoch(val) [55][ 50/102] eta: 0:00:06 time: 0.1252 data_time: 0.0223 memory: 1697 09/30 15:06:09 - mmengine - INFO - Epoch(val) [55][ 55/102] eta: 0:00:05 time: 0.1096 data_time: 0.0068 memory: 1697 09/30 15:06:09 - mmengine - INFO - Epoch(val) [55][ 60/102] eta: 0:00:05 time: 0.1095 data_time: 0.0070 memory: 1697 09/30 15:06:10 - mmengine - INFO - Epoch(val) [55][ 65/102] eta: 0:00:04 time: 0.1098 data_time: 0.0073 memory: 1697 09/30 15:06:11 - mmengine - INFO - Epoch(val) [55][ 70/102] eta: 0:00:03 time: 0.1099 data_time: 0.0073 memory: 1697 09/30 15:06:11 - mmengine - INFO - Epoch(val) [55][ 75/102] eta: 0:00:03 time: 0.1102 data_time: 0.0075 memory: 1697 09/30 15:06:12 - mmengine - INFO - Epoch(val) [55][ 80/102] eta: 0:00:02 time: 0.1102 data_time: 0.0073 memory: 1697 09/30 15:06:12 - mmengine - INFO - Epoch(val) [55][ 85/102] eta: 0:00:02 time: 0.1104 data_time: 0.0075 memory: 1697 09/30 15:06:13 - mmengine - INFO - Epoch(val) [55][ 90/102] eta: 0:00:01 time: 0.1103 data_time: 0.0075 memory: 1697 09/30 15:06:13 - mmengine - INFO - Epoch(val) [55][ 95/102] eta: 0:00:00 time: 0.1102 data_time: 0.0076 memory: 1697 09/30 15:06:14 - mmengine - INFO - Epoch(val) [55][100/102] eta: 0:00:00 time: 0.1103 data_time: 0.0074 memory: 1697 09/30 15:06:14 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:06:14 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:06:14 - mmengine - INFO - Epoch(val) [55][102/102] data_time: 0.0146 time: 0.1175 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:06:16 - mmengine - INFO - Epoch(train) [56][ 5/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:39 time: 0.2748 data_time: 0.0253 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:18 - mmengine - INFO - Epoch(train) [56][10/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:38 time: 0.2760 data_time: 0.0258 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:19 - mmengine - INFO - Epoch(train) [56][15/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:36 time: 0.2759 data_time: 0.0262 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:20 - mmengine - INFO - Epoch(train) [56][20/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:35 time: 0.2747 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:22 - mmengine - INFO - Epoch(train) [56][25/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:33 time: 0.2740 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:23 - mmengine - INFO - Epoch(train) [56][30/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:32 time: 0.2756 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:24 - mmengine - INFO - Epoch(train) [56][35/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:30 time: 0.2758 data_time: 0.0258 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:26 - mmengine - INFO - Epoch(train) [56][40/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:29 time: 0.2774 data_time: 0.0260 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:27 - mmengine - INFO - Epoch(train) [56][45/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:28 time: 0.2792 data_time: 0.0260 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:28 - mmengine - INFO - Epoch(train) [56][50/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:26 time: 0.2832 data_time: 0.0262 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:30 - mmengine - INFO - Epoch(train) [56][55/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:25 time: 0.2668 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:31 - mmengine - INFO - Epoch(train) [56][60/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:23 time: 0.2661 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:32 - mmengine - INFO - Epoch(train) [56][65/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:22 time: 0.2662 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:34 - mmengine - INFO - Epoch(train) [56][70/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:20 time: 0.2670 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:35 - mmengine - INFO - Epoch(train) [56][75/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:19 time: 0.2673 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:36 - mmengine - INFO - Epoch(train) [56][80/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:17 time: 0.2660 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:37 - mmengine - INFO - Epoch(train) [56][85/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:16 time: 0.2647 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:39 - mmengine - INFO - Epoch(train) [56][90/94] base_lr: 4.6375e-03 lr: 4.6375e-03 eta: 0:19:14 time: 0.2632 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:40 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:06:40 - mmengine - INFO - Saving checkpoint at 56 epochs 09/30 15:06:42 - mmengine - INFO - Epoch(val) [56][ 5/102] eta: 0:00:24 time: 0.1250 data_time: 0.0216 memory: 11783 09/30 15:06:43 - mmengine - INFO - Epoch(val) [56][ 10/102] eta: 0:00:16 time: 0.1249 data_time: 0.0214 memory: 1697 09/30 15:06:43 - mmengine - INFO - Epoch(val) [56][ 15/102] eta: 0:00:13 time: 0.1247 data_time: 0.0210 memory: 1697 09/30 15:06:44 - mmengine - INFO - Epoch(val) [56][ 20/102] eta: 0:00:11 time: 0.1247 data_time: 0.0211 memory: 1697 09/30 15:06:45 - mmengine - INFO - Epoch(val) [56][ 25/102] eta: 0:00:10 time: 0.1246 data_time: 0.0210 memory: 1697 09/30 15:06:45 - mmengine - INFO - Epoch(val) [56][ 30/102] eta: 0:00:09 time: 0.1250 data_time: 0.0210 memory: 1697 09/30 15:06:46 - mmengine - INFO - Epoch(val) [56][ 35/102] eta: 0:00:08 time: 0.1247 data_time: 0.0208 memory: 1697 09/30 15:06:46 - mmengine - INFO - Epoch(val) [56][ 40/102] eta: 0:00:07 time: 0.1248 data_time: 0.0209 memory: 1697 09/30 15:06:47 - mmengine - INFO - Epoch(val) [56][ 45/102] eta: 0:00:07 time: 0.1250 data_time: 0.0210 memory: 1697 09/30 15:06:47 - mmengine - INFO - Epoch(val) [56][ 50/102] eta: 0:00:06 time: 0.1251 data_time: 0.0211 memory: 1697 09/30 15:06:48 - mmengine - INFO - Epoch(val) [56][ 55/102] eta: 0:00:05 time: 0.1105 data_time: 0.0069 memory: 1697 09/30 15:06:48 - mmengine - INFO - Epoch(val) [56][ 60/102] eta: 0:00:05 time: 0.1105 data_time: 0.0071 memory: 1697 09/30 15:06:49 - mmengine - INFO - Epoch(val) [56][ 65/102] eta: 0:00:04 time: 0.1110 data_time: 0.0075 memory: 1697 09/30 15:06:50 - mmengine - INFO - Epoch(val) [56][ 70/102] eta: 0:00:03 time: 0.1109 data_time: 0.0074 memory: 1697 09/30 15:06:50 - mmengine - INFO - Epoch(val) [56][ 75/102] eta: 0:00:03 time: 0.1109 data_time: 0.0076 memory: 1697 09/30 15:06:51 - mmengine - INFO - Epoch(val) [56][ 80/102] eta: 0:00:02 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 15:06:51 - mmengine - INFO - Epoch(val) [56][ 85/102] eta: 0:00:02 time: 0.1111 data_time: 0.0076 memory: 1697 09/30 15:06:52 - mmengine - INFO - Epoch(val) [56][ 90/102] eta: 0:00:01 time: 0.1111 data_time: 0.0076 memory: 1697 09/30 15:06:52 - mmengine - INFO - Epoch(val) [56][ 95/102] eta: 0:00:00 time: 0.1113 data_time: 0.0077 memory: 1697 09/30 15:06:53 - mmengine - INFO - Epoch(val) [56][100/102] eta: 0:00:00 time: 0.1110 data_time: 0.0076 memory: 1697 09/30 15:06:53 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:06:53 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:06:53 - mmengine - INFO - Epoch(val) [56][102/102] data_time: 0.0142 time: 0.1179 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:06:56 - mmengine - INFO - Epoch(train) [57][ 5/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:13 time: 0.2835 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:57 - mmengine - INFO - Epoch(train) [57][10/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:11 time: 0.2826 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:06:58 - mmengine - INFO - Epoch(train) [57][15/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:10 time: 0.2816 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:00 - mmengine - INFO - Epoch(train) [57][20/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:08 time: 0.2813 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:01 - mmengine - INFO - Epoch(train) [57][25/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:07 time: 0.2814 data_time: 0.0328 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:02 - mmengine - INFO - Epoch(train) [57][30/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:05 time: 0.2811 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:04 - mmengine - INFO - Epoch(train) [57][35/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:04 time: 0.2815 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:05 - mmengine - INFO - Epoch(train) [57][40/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:02 time: 0.2823 data_time: 0.0324 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:06 - mmengine - INFO - Epoch(train) [57][45/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:01 time: 0.2839 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:08 - mmengine - INFO - Epoch(train) [57][50/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:19:00 time: 0.2885 data_time: 0.0328 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:09 - mmengine - INFO - Epoch(train) [57][55/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:18:58 time: 0.2643 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:10 - mmengine - INFO - Epoch(train) [57][60/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:18:57 time: 0.2648 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:12 - mmengine - INFO - Epoch(train) [57][65/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:18:55 time: 0.2656 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:13 - mmengine - INFO - Epoch(train) [57][70/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:18:54 time: 0.2653 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:14 - mmengine - INFO - Epoch(train) [57][75/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:18:52 time: 0.2655 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:15 - mmengine - INFO - Epoch(train) [57][80/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:18:51 time: 0.2654 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:17 - mmengine - INFO - Epoch(train) [57][85/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:18:49 time: 0.2638 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:18 - mmengine - INFO - Epoch(train) [57][90/94] base_lr: 4.5344e-03 lr: 4.5344e-03 eta: 0:18:48 time: 0.2625 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:19 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:07:19 - mmengine - INFO - Saving checkpoint at 57 epochs 09/30 15:07:21 - mmengine - INFO - Epoch(val) [57][ 5/102] eta: 0:00:23 time: 0.1247 data_time: 0.0209 memory: 11783 09/30 15:07:22 - mmengine - INFO - Epoch(val) [57][ 10/102] eta: 0:00:16 time: 0.1245 data_time: 0.0207 memory: 1697 09/30 15:07:23 - mmengine - INFO - Epoch(val) [57][ 15/102] eta: 0:00:13 time: 0.1241 data_time: 0.0204 memory: 1697 09/30 15:07:23 - mmengine - INFO - Epoch(val) [57][ 20/102] eta: 0:00:11 time: 0.1241 data_time: 0.0203 memory: 1697 09/30 15:07:24 - mmengine - INFO - Epoch(val) [57][ 25/102] eta: 0:00:10 time: 0.1239 data_time: 0.0202 memory: 1697 09/30 15:07:24 - mmengine - INFO - Epoch(val) [57][ 30/102] eta: 0:00:09 time: 0.1239 data_time: 0.0202 memory: 1697 09/30 15:07:25 - mmengine - INFO - Epoch(val) [57][ 35/102] eta: 0:00:08 time: 0.1234 data_time: 0.0200 memory: 1697 09/30 15:07:25 - mmengine - INFO - Epoch(val) [57][ 40/102] eta: 0:00:07 time: 0.1235 data_time: 0.0201 memory: 1697 09/30 15:07:26 - mmengine - INFO - Epoch(val) [57][ 45/102] eta: 0:00:07 time: 0.1235 data_time: 0.0200 memory: 1697 09/30 15:07:26 - mmengine - INFO - Epoch(val) [57][ 50/102] eta: 0:00:06 time: 0.1235 data_time: 0.0200 memory: 1697 09/30 15:07:27 - mmengine - INFO - Epoch(val) [57][ 55/102] eta: 0:00:05 time: 0.1098 data_time: 0.0067 memory: 1697 09/30 15:07:27 - mmengine - INFO - Epoch(val) [57][ 60/102] eta: 0:00:05 time: 0.1099 data_time: 0.0069 memory: 1697 09/30 15:07:28 - mmengine - INFO - Epoch(val) [57][ 65/102] eta: 0:00:04 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:07:29 - mmengine - INFO - Epoch(val) [57][ 70/102] eta: 0:00:03 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:07:29 - mmengine - INFO - Epoch(val) [57][ 75/102] eta: 0:00:03 time: 0.1105 data_time: 0.0074 memory: 1697 09/30 15:07:30 - mmengine - INFO - Epoch(val) [57][ 80/102] eta: 0:00:02 time: 0.1106 data_time: 0.0073 memory: 1697 09/30 15:07:30 - mmengine - INFO - Epoch(val) [57][ 85/102] eta: 0:00:02 time: 0.1109 data_time: 0.0074 memory: 1697 09/30 15:07:31 - mmengine - INFO - Epoch(val) [57][ 90/102] eta: 0:00:01 time: 0.1109 data_time: 0.0074 memory: 1697 09/30 15:07:31 - mmengine - INFO - Epoch(val) [57][ 95/102] eta: 0:00:00 time: 0.1112 data_time: 0.0075 memory: 1697 09/30 15:07:32 - mmengine - INFO - Epoch(val) [57][100/102] eta: 0:00:00 time: 0.1110 data_time: 0.0074 memory: 1697 09/30 15:07:32 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:07:32 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:07:32 - mmengine - INFO - Epoch(val) [57][102/102] data_time: 0.0135 time: 0.1170 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:07:34 - mmengine - INFO - Epoch(train) [58][ 5/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:46 time: 0.2766 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:36 - mmengine - INFO - Epoch(train) [58][10/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:44 time: 0.2761 data_time: 0.0272 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:37 - mmengine - INFO - Epoch(train) [58][15/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:43 time: 0.2753 data_time: 0.0271 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:38 - mmengine - INFO - Epoch(train) [58][20/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:41 time: 0.2759 data_time: 0.0268 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:40 - mmengine - INFO - Epoch(train) [58][25/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:40 time: 0.2754 data_time: 0.0266 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:41 - mmengine - INFO - Epoch(train) [58][30/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:38 time: 0.2756 data_time: 0.0266 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:42 - mmengine - INFO - Epoch(train) [58][35/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:37 time: 0.2752 data_time: 0.0265 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:44 - mmengine - INFO - Epoch(train) [58][40/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:36 time: 0.2765 data_time: 0.0265 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:45 - mmengine - INFO - Epoch(train) [58][45/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:34 time: 0.2783 data_time: 0.0265 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:46 - mmengine - INFO - Epoch(train) [58][50/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:33 time: 0.2823 data_time: 0.0266 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:48 - mmengine - INFO - Epoch(train) [58][55/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:31 time: 0.2639 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:49 - mmengine - INFO - Epoch(train) [58][60/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:30 time: 0.2635 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:50 - mmengine - INFO - Epoch(train) [58][65/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:28 time: 0.2647 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:52 - mmengine - INFO - Epoch(train) [58][70/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:27 time: 0.2646 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:53 - mmengine - INFO - Epoch(train) [58][75/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:26 time: 0.2657 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:54 - mmengine - INFO - Epoch(train) [58][80/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:24 time: 0.2655 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:55 - mmengine - INFO - Epoch(train) [58][85/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:23 time: 0.2644 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:57 - mmengine - INFO - Epoch(train) [58][90/94] base_lr: 4.4313e-03 lr: 4.4313e-03 eta: 0:18:21 time: 0.2632 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:07:58 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:07:58 - mmengine - INFO - Saving checkpoint at 58 epochs 09/30 15:08:00 - mmengine - INFO - Epoch(val) [58][ 5/102] eta: 0:00:23 time: 0.1239 data_time: 0.0201 memory: 11783 09/30 15:08:01 - mmengine - INFO - Epoch(val) [58][ 10/102] eta: 0:00:15 time: 0.1235 data_time: 0.0199 memory: 1697 09/30 15:08:01 - mmengine - INFO - Epoch(val) [58][ 15/102] eta: 0:00:13 time: 0.1233 data_time: 0.0195 memory: 1697 09/30 15:08:02 - mmengine - INFO - Epoch(val) [58][ 20/102] eta: 0:00:11 time: 0.1232 data_time: 0.0195 memory: 1697 09/30 15:08:02 - mmengine - INFO - Epoch(val) [58][ 25/102] eta: 0:00:10 time: 0.1229 data_time: 0.0194 memory: 1697 09/30 15:08:03 - mmengine - INFO - Epoch(val) [58][ 30/102] eta: 0:00:09 time: 0.1226 data_time: 0.0194 memory: 1697 09/30 15:08:04 - mmengine - INFO - Epoch(val) [58][ 35/102] eta: 0:00:08 time: 0.1223 data_time: 0.0192 memory: 1697 09/30 15:08:04 - mmengine - INFO - Epoch(val) [58][ 40/102] eta: 0:00:07 time: 0.1222 data_time: 0.0192 memory: 1697 09/30 15:08:05 - mmengine - INFO - Epoch(val) [58][ 45/102] eta: 0:00:07 time: 0.1221 data_time: 0.0193 memory: 1697 09/30 15:08:05 - mmengine - INFO - Epoch(val) [58][ 50/102] eta: 0:00:06 time: 0.1220 data_time: 0.0192 memory: 1697 09/30 15:08:06 - mmengine - INFO - Epoch(val) [58][ 55/102] eta: 0:00:05 time: 0.1090 data_time: 0.0065 memory: 1697 09/30 15:08:06 - mmengine - INFO - Epoch(val) [58][ 60/102] eta: 0:00:05 time: 0.1091 data_time: 0.0066 memory: 1697 09/30 15:08:07 - mmengine - INFO - Epoch(val) [58][ 65/102] eta: 0:00:04 time: 0.1095 data_time: 0.0070 memory: 1697 09/30 15:08:07 - mmengine - INFO - Epoch(val) [58][ 70/102] eta: 0:00:03 time: 0.1095 data_time: 0.0069 memory: 1697 09/30 15:08:08 - mmengine - INFO - Epoch(val) [58][ 75/102] eta: 0:00:03 time: 0.1096 data_time: 0.0070 memory: 1697 09/30 15:08:09 - mmengine - INFO - Epoch(val) [58][ 80/102] eta: 0:00:02 time: 0.1096 data_time: 0.0069 memory: 1697 09/30 15:08:09 - mmengine - INFO - Epoch(val) [58][ 85/102] eta: 0:00:01 time: 0.1097 data_time: 0.0070 memory: 1697 09/30 15:08:10 - mmengine - INFO - Epoch(val) [58][ 90/102] eta: 0:00:01 time: 0.1098 data_time: 0.0071 memory: 1697 09/30 15:08:10 - mmengine - INFO - Epoch(val) [58][ 95/102] eta: 0:00:00 time: 0.1098 data_time: 0.0071 memory: 1697 09/30 15:08:11 - mmengine - INFO - Epoch(val) [58][100/102] eta: 0:00:00 time: 0.1095 data_time: 0.0070 memory: 1697 09/30 15:08:11 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:08:11 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:08:11 - mmengine - INFO - Epoch(val) [58][102/102] data_time: 0.0129 time: 0.1155 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:08:13 - mmengine - INFO - Epoch(train) [59][ 5/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:19 time: 0.2840 data_time: 0.0343 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:15 - mmengine - INFO - Epoch(train) [59][10/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:18 time: 0.2835 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:16 - mmengine - INFO - Epoch(train) [59][15/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:16 time: 0.2834 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:17 - mmengine - INFO - Epoch(train) [59][20/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:15 time: 0.2827 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:19 - mmengine - INFO - Epoch(train) [59][25/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:13 time: 0.2824 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:20 - mmengine - INFO - Epoch(train) [59][30/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:12 time: 0.2822 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:21 - mmengine - INFO - Epoch(train) [59][35/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:11 time: 0.2825 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:23 - mmengine - INFO - Epoch(train) [59][40/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:09 time: 0.2841 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:24 - mmengine - INFO - Epoch(train) [59][45/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:08 time: 0.2855 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:25 - mmengine - INFO - Epoch(train) [59][50/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:06 time: 0.2900 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:27 - mmengine - INFO - Epoch(train) [59][55/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:05 time: 0.2653 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:28 - mmengine - INFO - Epoch(train) [59][60/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:03 time: 0.2659 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:29 - mmengine - INFO - Epoch(train) [59][65/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:02 time: 0.2671 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:31 - mmengine - INFO - Epoch(train) [59][70/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:18:01 time: 0.2677 data_time: 0.0104 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:32 - mmengine - INFO - Epoch(train) [59][75/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:17:59 time: 0.2682 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:33 - mmengine - INFO - Epoch(train) [59][80/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:17:58 time: 0.2673 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:35 - mmengine - INFO - Epoch(train) [59][85/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:17:56 time: 0.2660 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:36 - mmengine - INFO - Epoch(train) [59][90/94] base_lr: 4.3281e-03 lr: 4.3281e-03 eta: 0:17:55 time: 0.2649 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:37 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:08:37 - mmengine - INFO - Saving checkpoint at 59 epochs 09/30 15:08:40 - mmengine - INFO - Epoch(val) [59][ 5/102] eta: 0:00:24 time: 0.1241 data_time: 0.0211 memory: 11783 09/30 15:08:40 - mmengine - INFO - Epoch(val) [59][ 10/102] eta: 0:00:16 time: 0.1239 data_time: 0.0210 memory: 1697 09/30 15:08:41 - mmengine - INFO - Epoch(val) [59][ 15/102] eta: 0:00:13 time: 0.1237 data_time: 0.0208 memory: 1697 09/30 15:08:41 - mmengine - INFO - Epoch(val) [59][ 20/102] eta: 0:00:11 time: 0.1237 data_time: 0.0208 memory: 1697 09/30 15:08:42 - mmengine - INFO - Epoch(val) [59][ 25/102] eta: 0:00:10 time: 0.1240 data_time: 0.0208 memory: 1697 09/30 15:08:42 - mmengine - INFO - Epoch(val) [59][ 30/102] eta: 0:00:09 time: 0.1243 data_time: 0.0211 memory: 1697 09/30 15:08:43 - mmengine - INFO - Epoch(val) [59][ 35/102] eta: 0:00:08 time: 0.1240 data_time: 0.0207 memory: 1697 09/30 15:08:44 - mmengine - INFO - Epoch(val) [59][ 40/102] eta: 0:00:07 time: 0.1244 data_time: 0.0208 memory: 1697 09/30 15:08:44 - mmengine - INFO - Epoch(val) [59][ 45/102] eta: 0:00:07 time: 0.1247 data_time: 0.0209 memory: 1697 09/30 15:08:45 - mmengine - INFO - Epoch(val) [59][ 50/102] eta: 0:00:06 time: 0.1251 data_time: 0.0210 memory: 1697 09/30 15:08:45 - mmengine - INFO - Epoch(val) [59][ 55/102] eta: 0:00:05 time: 0.1107 data_time: 0.0069 memory: 1697 09/30 15:08:46 - mmengine - INFO - Epoch(val) [59][ 60/102] eta: 0:00:05 time: 0.1109 data_time: 0.0071 memory: 1697 09/30 15:08:46 - mmengine - INFO - Epoch(val) [59][ 65/102] eta: 0:00:04 time: 0.1113 data_time: 0.0074 memory: 1697 09/30 15:08:47 - mmengine - INFO - Epoch(val) [59][ 70/102] eta: 0:00:03 time: 0.1112 data_time: 0.0075 memory: 1697 09/30 15:08:47 - mmengine - INFO - Epoch(val) [59][ 75/102] eta: 0:00:03 time: 0.1112 data_time: 0.0076 memory: 1697 09/30 15:08:48 - mmengine - INFO - Epoch(val) [59][ 80/102] eta: 0:00:02 time: 0.1111 data_time: 0.0074 memory: 1697 09/30 15:08:49 - mmengine - INFO - Epoch(val) [59][ 85/102] eta: 0:00:02 time: 0.1112 data_time: 0.0077 memory: 1697 09/30 15:08:49 - mmengine - INFO - Epoch(val) [59][ 90/102] eta: 0:00:01 time: 0.1111 data_time: 0.0077 memory: 1697 09/30 15:08:50 - mmengine - INFO - Epoch(val) [59][ 95/102] eta: 0:00:00 time: 0.1109 data_time: 0.0078 memory: 1697 09/30 15:08:50 - mmengine - INFO - Epoch(val) [59][100/102] eta: 0:00:00 time: 0.1108 data_time: 0.0076 memory: 1697 09/30 15:08:50 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:08:50 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:08:50 - mmengine - INFO - Epoch(val) [59][102/102] data_time: 0.0141 time: 0.1176 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:08:53 - mmengine - INFO - Epoch(train) [60][ 5/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:53 time: 0.2836 data_time: 0.0329 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:54 - mmengine - INFO - Epoch(train) [60][10/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:51 time: 0.2846 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:56 - mmengine - INFO - Epoch(train) [60][15/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:50 time: 0.2843 data_time: 0.0332 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:57 - mmengine - INFO - Epoch(train) [60][20/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:48 time: 0.2840 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:08:58 - mmengine - INFO - Epoch(train) [60][25/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:47 time: 0.2828 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:00 - mmengine - INFO - Epoch(train) [60][30/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:46 time: 0.2830 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:01 - mmengine - INFO - Epoch(train) [60][35/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:44 time: 0.2828 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:02 - mmengine - INFO - Epoch(train) [60][40/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:43 time: 0.2840 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:04 - mmengine - INFO - Epoch(train) [60][45/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:41 time: 0.2857 data_time: 0.0328 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:05 - mmengine - INFO - Epoch(train) [60][50/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:40 time: 0.2900 data_time: 0.0329 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:06 - mmengine - INFO - Epoch(train) [60][55/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:38 time: 0.2669 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:08 - mmengine - INFO - Epoch(train) [60][60/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:37 time: 0.2662 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:09 - mmengine - INFO - Epoch(train) [60][65/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:36 time: 0.2663 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:10 - mmengine - INFO - Epoch(train) [60][70/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:34 time: 0.2661 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:12 - mmengine - INFO - Epoch(train) [60][75/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:33 time: 0.2666 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:13 - mmengine - INFO - Epoch(train) [60][80/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:31 time: 0.2665 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:14 - mmengine - INFO - Epoch(train) [60][85/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:30 time: 0.2656 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:15 - mmengine - INFO - Epoch(train) [60][90/94] base_lr: 4.2250e-03 lr: 4.2250e-03 eta: 0:17:28 time: 0.2643 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:16 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:09:16 - mmengine - INFO - Saving checkpoint at 60 epochs 09/30 15:09:19 - mmengine - INFO - Epoch(val) [60][ 5/102] eta: 0:00:24 time: 0.1243 data_time: 0.0210 memory: 11783 09/30 15:09:19 - mmengine - INFO - Epoch(val) [60][ 10/102] eta: 0:00:16 time: 0.1243 data_time: 0.0207 memory: 1697 09/30 15:09:20 - mmengine - INFO - Epoch(val) [60][ 15/102] eta: 0:00:13 time: 0.1237 data_time: 0.0203 memory: 1697 09/30 15:09:21 - mmengine - INFO - Epoch(val) [60][ 20/102] eta: 0:00:11 time: 0.1239 data_time: 0.0202 memory: 1697 09/30 15:09:21 - mmengine - INFO - Epoch(val) [60][ 25/102] eta: 0:00:10 time: 0.1240 data_time: 0.0200 memory: 1697 09/30 15:09:22 - mmengine - INFO - Epoch(val) [60][ 30/102] eta: 0:00:09 time: 0.1240 data_time: 0.0201 memory: 1697 09/30 15:09:22 - mmengine - INFO - Epoch(val) [60][ 35/102] eta: 0:00:08 time: 0.1237 data_time: 0.0198 memory: 1697 09/30 15:09:23 - mmengine - INFO - Epoch(val) [60][ 40/102] eta: 0:00:07 time: 0.1239 data_time: 0.0201 memory: 1697 09/30 15:09:23 - mmengine - INFO - Epoch(val) [60][ 45/102] eta: 0:00:07 time: 0.1240 data_time: 0.0200 memory: 1697 09/30 15:09:24 - mmengine - INFO - Epoch(val) [60][ 50/102] eta: 0:00:06 time: 0.1241 data_time: 0.0200 memory: 1697 09/30 15:09:24 - mmengine - INFO - Epoch(val) [60][ 55/102] eta: 0:00:05 time: 0.1103 data_time: 0.0066 memory: 1697 09/30 15:09:25 - mmengine - INFO - Epoch(val) [60][ 60/102] eta: 0:00:05 time: 0.1103 data_time: 0.0067 memory: 1697 09/30 15:09:25 - mmengine - INFO - Epoch(val) [60][ 65/102] eta: 0:00:04 time: 0.1108 data_time: 0.0071 memory: 1697 09/30 15:09:26 - mmengine - INFO - Epoch(val) [60][ 70/102] eta: 0:00:03 time: 0.1105 data_time: 0.0071 memory: 1697 09/30 15:09:27 - mmengine - INFO - Epoch(val) [60][ 75/102] eta: 0:00:03 time: 0.1104 data_time: 0.0071 memory: 1697 09/30 15:09:27 - mmengine - INFO - Epoch(val) [60][ 80/102] eta: 0:00:02 time: 0.1100 data_time: 0.0070 memory: 1697 09/30 15:09:28 - mmengine - INFO - Epoch(val) [60][ 85/102] eta: 0:00:02 time: 0.1103 data_time: 0.0071 memory: 1697 09/30 15:09:28 - mmengine - INFO - Epoch(val) [60][ 90/102] eta: 0:00:01 time: 0.1102 data_time: 0.0070 memory: 1697 09/30 15:09:29 - mmengine - INFO - Epoch(val) [60][ 95/102] eta: 0:00:00 time: 0.1104 data_time: 0.0071 memory: 1697 09/30 15:09:29 - mmengine - INFO - Epoch(val) [60][100/102] eta: 0:00:00 time: 0.1104 data_time: 0.0070 memory: 1697 09/30 15:09:30 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:09:30 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:09:30 - mmengine - INFO - Epoch(val) [60][102/102] data_time: 0.0133 time: 0.1170 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:09:32 - mmengine - INFO - Epoch(train) [61][ 5/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:26 time: 0.2821 data_time: 0.0320 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:33 - mmengine - INFO - Epoch(train) [61][10/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:25 time: 0.2844 data_time: 0.0324 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:35 - mmengine - INFO - Epoch(train) [61][15/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:24 time: 0.2839 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:36 - mmengine - INFO - Epoch(train) [61][20/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:22 time: 0.2857 data_time: 0.0324 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:38 - mmengine - INFO - Epoch(train) [61][25/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:21 time: 0.2848 data_time: 0.0316 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:39 - mmengine - INFO - Epoch(train) [61][30/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:19 time: 0.2855 data_time: 0.0313 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:40 - mmengine - INFO - Epoch(train) [61][35/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:18 time: 0.2859 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:42 - mmengine - INFO - Epoch(train) [61][40/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:16 time: 0.2872 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:43 - mmengine - INFO - Epoch(train) [61][45/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:15 time: 0.2882 data_time: 0.0314 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:44 - mmengine - INFO - Epoch(train) [61][50/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:14 time: 0.2977 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:46 - mmengine - INFO - Epoch(train) [61][55/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:12 time: 0.2752 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:47 - mmengine - INFO - Epoch(train) [61][60/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:11 time: 0.2734 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:48 - mmengine - INFO - Epoch(train) [61][65/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:09 time: 0.2729 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:50 - mmengine - INFO - Epoch(train) [61][70/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:08 time: 0.2714 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:51 - mmengine - INFO - Epoch(train) [61][75/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:07 time: 0.2722 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:52 - mmengine - INFO - Epoch(train) [61][80/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:05 time: 0.2718 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:54 - mmengine - INFO - Epoch(train) [61][85/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:04 time: 0.2701 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:55 - mmengine - INFO - Epoch(train) [61][90/94] base_lr: 4.1219e-03 lr: 4.1219e-03 eta: 0:17:02 time: 0.2688 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:09:56 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:09:56 - mmengine - INFO - Saving checkpoint at 61 epochs 09/30 15:09:58 - mmengine - INFO - Epoch(val) [61][ 5/102] eta: 0:00:23 time: 0.1234 data_time: 0.0200 memory: 11783 09/30 15:09:59 - mmengine - INFO - Epoch(val) [61][ 10/102] eta: 0:00:16 time: 0.1231 data_time: 0.0198 memory: 1697 09/30 15:09:59 - mmengine - INFO - Epoch(val) [61][ 15/102] eta: 0:00:13 time: 0.1227 data_time: 0.0196 memory: 1697 09/30 15:10:00 - mmengine - INFO - Epoch(val) [61][ 20/102] eta: 0:00:11 time: 0.1224 data_time: 0.0196 memory: 1697 09/30 15:10:01 - mmengine - INFO - Epoch(val) [61][ 25/102] eta: 0:00:10 time: 0.1224 data_time: 0.0195 memory: 1697 09/30 15:10:01 - mmengine - INFO - Epoch(val) [61][ 30/102] eta: 0:00:09 time: 0.1230 data_time: 0.0199 memory: 1697 09/30 15:10:02 - mmengine - INFO - Epoch(val) [61][ 35/102] eta: 0:00:08 time: 0.1225 data_time: 0.0195 memory: 1697 09/30 15:10:02 - mmengine - INFO - Epoch(val) [61][ 40/102] eta: 0:00:07 time: 0.1227 data_time: 0.0196 memory: 1697 09/30 15:10:03 - mmengine - INFO - Epoch(val) [61][ 45/102] eta: 0:00:07 time: 0.1227 data_time: 0.0197 memory: 1697 09/30 15:10:03 - mmengine - INFO - Epoch(val) [61][ 50/102] eta: 0:00:06 time: 0.1225 data_time: 0.0198 memory: 1697 09/30 15:10:04 - mmengine - INFO - Epoch(val) [61][ 55/102] eta: 0:00:05 time: 0.1096 data_time: 0.0068 memory: 1697 09/30 15:10:04 - mmengine - INFO - Epoch(val) [61][ 60/102] eta: 0:00:05 time: 0.1099 data_time: 0.0070 memory: 1697 09/30 15:10:05 - mmengine - INFO - Epoch(val) [61][ 65/102] eta: 0:00:04 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:10:06 - mmengine - INFO - Epoch(val) [61][ 70/102] eta: 0:00:03 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 15:10:06 - mmengine - INFO - Epoch(val) [61][ 75/102] eta: 0:00:03 time: 0.1112 data_time: 0.0077 memory: 1697 09/30 15:10:07 - mmengine - INFO - Epoch(val) [61][ 80/102] eta: 0:00:02 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 15:10:07 - mmengine - INFO - Epoch(val) [61][ 85/102] eta: 0:00:02 time: 0.1110 data_time: 0.0077 memory: 1697 09/30 15:10:08 - mmengine - INFO - Epoch(val) [61][ 90/102] eta: 0:00:01 time: 0.1111 data_time: 0.0077 memory: 1697 09/30 15:10:08 - mmengine - INFO - Epoch(val) [61][ 95/102] eta: 0:00:00 time: 0.1111 data_time: 0.0077 memory: 1697 09/30 15:10:09 - mmengine - INFO - Epoch(val) [61][100/102] eta: 0:00:00 time: 0.1110 data_time: 0.0076 memory: 1697 09/30 15:10:09 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:10:09 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:10:09 - mmengine - INFO - Epoch(val) [61][102/102] data_time: 0.0135 time: 0.1165 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:10:11 - mmengine - INFO - Epoch(train) [62][ 5/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:17:00 time: 0.2795 data_time: 0.0289 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:13 - mmengine - INFO - Epoch(train) [62][10/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:59 time: 0.2797 data_time: 0.0290 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:14 - mmengine - INFO - Epoch(train) [62][15/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:57 time: 0.2791 data_time: 0.0290 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:15 - mmengine - INFO - Epoch(train) [62][20/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:56 time: 0.2796 data_time: 0.0290 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:17 - mmengine - INFO - Epoch(train) [62][25/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:54 time: 0.2798 data_time: 0.0291 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:18 - mmengine - INFO - Epoch(train) [62][30/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:53 time: 0.2794 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:19 - mmengine - INFO - Epoch(train) [62][35/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:51 time: 0.2788 data_time: 0.0286 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:21 - mmengine - INFO - Epoch(train) [62][40/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:50 time: 0.2799 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:22 - mmengine - INFO - Epoch(train) [62][45/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:49 time: 0.2815 data_time: 0.0288 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:23 - mmengine - INFO - Epoch(train) [62][50/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:47 time: 0.2857 data_time: 0.0290 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:25 - mmengine - INFO - Epoch(train) [62][55/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:46 time: 0.2660 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:26 - mmengine - INFO - Epoch(train) [62][60/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:44 time: 0.2662 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:27 - mmengine - INFO - Epoch(train) [62][65/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:43 time: 0.2675 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:29 - mmengine - INFO - Epoch(train) [62][70/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:41 time: 0.2670 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:30 - mmengine - INFO - Epoch(train) [62][75/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:40 time: 0.2670 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:31 - mmengine - INFO - Epoch(train) [62][80/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:39 time: 0.2673 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:33 - mmengine - INFO - Epoch(train) [62][85/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:37 time: 0.2665 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:34 - mmengine - INFO - Epoch(train) [62][90/94] base_lr: 4.0188e-03 lr: 4.0188e-03 eta: 0:16:36 time: 0.2662 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:35 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:10:35 - mmengine - INFO - Saving checkpoint at 62 epochs 09/30 15:10:38 - mmengine - INFO - Epoch(val) [62][ 5/102] eta: 0:00:22 time: 0.1226 data_time: 0.0191 memory: 11783 09/30 15:10:38 - mmengine - INFO - Epoch(val) [62][ 10/102] eta: 0:00:15 time: 0.1223 data_time: 0.0189 memory: 1697 09/30 15:10:39 - mmengine - INFO - Epoch(val) [62][ 15/102] eta: 0:00:12 time: 0.1220 data_time: 0.0185 memory: 1697 09/30 15:10:39 - mmengine - INFO - Epoch(val) [62][ 20/102] eta: 0:00:11 time: 0.1213 data_time: 0.0182 memory: 1697 09/30 15:10:40 - mmengine - INFO - Epoch(val) [62][ 25/102] eta: 0:00:10 time: 0.1213 data_time: 0.0181 memory: 1697 09/30 15:10:40 - mmengine - INFO - Epoch(val) [62][ 30/102] eta: 0:00:09 time: 0.1213 data_time: 0.0182 memory: 1697 09/30 15:10:41 - mmengine - INFO - Epoch(val) [62][ 35/102] eta: 0:00:08 time: 0.1214 data_time: 0.0180 memory: 1697 09/30 15:10:41 - mmengine - INFO - Epoch(val) [62][ 40/102] eta: 0:00:07 time: 0.1217 data_time: 0.0181 memory: 1697 09/30 15:10:42 - mmengine - INFO - Epoch(val) [62][ 45/102] eta: 0:00:07 time: 0.1219 data_time: 0.0181 memory: 1697 09/30 15:10:43 - mmengine - INFO - Epoch(val) [62][ 50/102] eta: 0:00:06 time: 0.1220 data_time: 0.0181 memory: 1697 09/30 15:10:43 - mmengine - INFO - Epoch(val) [62][ 55/102] eta: 0:00:05 time: 0.1103 data_time: 0.0065 memory: 1697 09/30 15:10:44 - mmengine - INFO - Epoch(val) [62][ 60/102] eta: 0:00:05 time: 0.1105 data_time: 0.0067 memory: 1697 09/30 15:10:44 - mmengine - INFO - Epoch(val) [62][ 65/102] eta: 0:00:04 time: 0.1109 data_time: 0.0071 memory: 1697 09/30 15:10:45 - mmengine - INFO - Epoch(val) [62][ 70/102] eta: 0:00:03 time: 0.1112 data_time: 0.0072 memory: 1697 09/30 15:10:45 - mmengine - INFO - Epoch(val) [62][ 75/102] eta: 0:00:03 time: 0.1112 data_time: 0.0071 memory: 1697 09/30 15:10:46 - mmengine - INFO - Epoch(val) [62][ 80/102] eta: 0:00:02 time: 0.1112 data_time: 0.0070 memory: 1697 09/30 15:10:46 - mmengine - INFO - Epoch(val) [62][ 85/102] eta: 0:00:01 time: 0.1110 data_time: 0.0071 memory: 1697 09/30 15:10:47 - mmengine - INFO - Epoch(val) [62][ 90/102] eta: 0:00:01 time: 0.1109 data_time: 0.0071 memory: 1697 09/30 15:10:48 - mmengine - INFO - Epoch(val) [62][ 95/102] eta: 0:00:00 time: 0.1110 data_time: 0.0072 memory: 1697 09/30 15:10:48 - mmengine - INFO - Epoch(val) [62][100/102] eta: 0:00:00 time: 0.1107 data_time: 0.0070 memory: 1697 09/30 15:10:48 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:10:48 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:10:48 - mmengine - INFO - Epoch(val) [62][102/102] data_time: 0.0124 time: 0.1162 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:10:51 - mmengine - INFO - Epoch(train) [63][ 5/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:34 time: 0.2843 data_time: 0.0325 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:52 - mmengine - INFO - Epoch(train) [63][10/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:32 time: 0.2846 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:53 - mmengine - INFO - Epoch(train) [63][15/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:31 time: 0.2851 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:55 - mmengine - INFO - Epoch(train) [63][20/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:29 time: 0.2842 data_time: 0.0330 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:56 - mmengine - INFO - Epoch(train) [63][25/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:28 time: 0.2836 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:57 - mmengine - INFO - Epoch(train) [63][30/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:27 time: 0.2828 data_time: 0.0320 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:10:59 - mmengine - INFO - Epoch(train) [63][35/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:25 time: 0.2827 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:00 - mmengine - INFO - Epoch(train) [63][40/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:24 time: 0.2836 data_time: 0.0325 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:01 - mmengine - INFO - Epoch(train) [63][45/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:22 time: 0.2851 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:03 - mmengine - INFO - Epoch(train) [63][50/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:21 time: 0.2891 data_time: 0.0328 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:04 - mmengine - INFO - Epoch(train) [63][55/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:19 time: 0.2663 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:05 - mmengine - INFO - Epoch(train) [63][60/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:18 time: 0.2660 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:07 - mmengine - INFO - Epoch(train) [63][65/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:17 time: 0.2650 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:08 - mmengine - INFO - Epoch(train) [63][70/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:15 time: 0.2653 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:09 - mmengine - INFO - Epoch(train) [63][75/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:14 time: 0.2662 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:11 - mmengine - INFO - Epoch(train) [63][80/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:12 time: 0.2668 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:12 - mmengine - INFO - Epoch(train) [63][85/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:11 time: 0.2661 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:13 - mmengine - INFO - Epoch(train) [63][90/94] base_lr: 3.9156e-03 lr: 3.9156e-03 eta: 0:16:09 time: 0.2654 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:14 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:11:14 - mmengine - INFO - Saving checkpoint at 63 epochs 09/30 15:11:17 - mmengine - INFO - Epoch(val) [63][ 5/102] eta: 0:00:25 time: 0.1257 data_time: 0.0218 memory: 11783 09/30 15:11:18 - mmengine - INFO - Epoch(val) [63][ 10/102] eta: 0:00:17 time: 0.1257 data_time: 0.0216 memory: 1697 09/30 15:11:18 - mmengine - INFO - Epoch(val) [63][ 15/102] eta: 0:00:13 time: 0.1256 data_time: 0.0213 memory: 1697 09/30 15:11:19 - mmengine - INFO - Epoch(val) [63][ 20/102] eta: 0:00:12 time: 0.1258 data_time: 0.0214 memory: 1697 09/30 15:11:19 - mmengine - INFO - Epoch(val) [63][ 25/102] eta: 0:00:10 time: 0.1259 data_time: 0.0213 memory: 1697 09/30 15:11:20 - mmengine - INFO - Epoch(val) [63][ 30/102] eta: 0:00:09 time: 0.1260 data_time: 0.0215 memory: 1697 09/30 15:11:20 - mmengine - INFO - Epoch(val) [63][ 35/102] eta: 0:00:08 time: 0.1260 data_time: 0.0215 memory: 1697 09/30 15:11:21 - mmengine - INFO - Epoch(val) [63][ 40/102] eta: 0:00:08 time: 0.1261 data_time: 0.0217 memory: 1697 09/30 15:11:21 - mmengine - INFO - Epoch(val) [63][ 45/102] eta: 0:00:07 time: 0.1261 data_time: 0.0217 memory: 1697 09/30 15:11:22 - mmengine - INFO - Epoch(val) [63][ 50/102] eta: 0:00:06 time: 0.1262 data_time: 0.0218 memory: 1697 09/30 15:11:23 - mmengine - INFO - Epoch(val) [63][ 55/102] eta: 0:00:05 time: 0.1114 data_time: 0.0071 memory: 1697 09/30 15:11:23 - mmengine - INFO - Epoch(val) [63][ 60/102] eta: 0:00:05 time: 0.1114 data_time: 0.0073 memory: 1697 09/30 15:11:24 - mmengine - INFO - Epoch(val) [63][ 65/102] eta: 0:00:04 time: 0.1118 data_time: 0.0077 memory: 1697 09/30 15:11:24 - mmengine - INFO - Epoch(val) [63][ 70/102] eta: 0:00:03 time: 0.1118 data_time: 0.0078 memory: 1697 09/30 15:11:25 - mmengine - INFO - Epoch(val) [63][ 75/102] eta: 0:00:03 time: 0.1119 data_time: 0.0079 memory: 1697 09/30 15:11:25 - mmengine - INFO - Epoch(val) [63][ 80/102] eta: 0:00:02 time: 0.1117 data_time: 0.0078 memory: 1697 09/30 15:11:26 - mmengine - INFO - Epoch(val) [63][ 85/102] eta: 0:00:02 time: 0.1120 data_time: 0.0078 memory: 1697 09/30 15:11:27 - mmengine - INFO - Epoch(val) [63][ 90/102] eta: 0:00:01 time: 0.1117 data_time: 0.0077 memory: 1697 09/30 15:11:27 - mmengine - INFO - Epoch(val) [63][ 95/102] eta: 0:00:00 time: 0.1116 data_time: 0.0077 memory: 1697 09/30 15:11:28 - mmengine - INFO - Epoch(val) [63][100/102] eta: 0:00:00 time: 0.1114 data_time: 0.0075 memory: 1697 09/30 15:11:28 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:11:28 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:11:28 - mmengine - INFO - Epoch(val) [63][102/102] data_time: 0.0144 time: 0.1185 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:11:30 - mmengine - INFO - Epoch(train) [64][ 5/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:16:07 time: 0.2831 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:32 - mmengine - INFO - Epoch(train) [64][10/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:16:06 time: 0.2828 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:33 - mmengine - INFO - Epoch(train) [64][15/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:16:04 time: 0.2827 data_time: 0.0318 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:34 - mmengine - INFO - Epoch(train) [64][20/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:16:03 time: 0.2830 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:36 - mmengine - INFO - Epoch(train) [64][25/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:16:02 time: 0.2830 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:37 - mmengine - INFO - Epoch(train) [64][30/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:16:00 time: 0.2829 data_time: 0.0316 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:38 - mmengine - INFO - Epoch(train) [64][35/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:59 time: 0.2827 data_time: 0.0316 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:40 - mmengine - INFO - Epoch(train) [64][40/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:57 time: 0.2839 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:41 - mmengine - INFO - Epoch(train) [64][45/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:56 time: 0.2854 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:42 - mmengine - INFO - Epoch(train) [64][50/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:54 time: 0.2893 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:44 - mmengine - INFO - Epoch(train) [64][55/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:53 time: 0.2677 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:45 - mmengine - INFO - Epoch(train) [64][60/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:52 time: 0.2680 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:46 - mmengine - INFO - Epoch(train) [64][65/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:50 time: 0.2682 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:48 - mmengine - INFO - Epoch(train) [64][70/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:49 time: 0.2682 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:49 - mmengine - INFO - Epoch(train) [64][75/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:47 time: 0.2683 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:50 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:11:50 - mmengine - INFO - Epoch(train) [64][80/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:46 time: 0.2676 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:52 - mmengine - INFO - Epoch(train) [64][85/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:44 time: 0.2663 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:53 - mmengine - INFO - Epoch(train) [64][90/94] base_lr: 3.8125e-03 lr: 3.8125e-03 eta: 0:15:43 time: 0.2642 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:11:54 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:11:54 - mmengine - INFO - Saving checkpoint at 64 epochs 09/30 15:11:56 - mmengine - INFO - Epoch(val) [64][ 5/102] eta: 0:00:25 time: 0.1268 data_time: 0.0230 memory: 11783 09/30 15:11:57 - mmengine - INFO - Epoch(val) [64][ 10/102] eta: 0:00:17 time: 0.1264 data_time: 0.0227 memory: 1697 09/30 15:11:57 - mmengine - INFO - Epoch(val) [64][ 15/102] eta: 0:00:14 time: 0.1257 data_time: 0.0222 memory: 1697 09/30 15:11:58 - mmengine - INFO - Epoch(val) [64][ 20/102] eta: 0:00:12 time: 0.1257 data_time: 0.0222 memory: 1697 09/30 15:11:58 - mmengine - INFO - Epoch(val) [64][ 25/102] eta: 0:00:10 time: 0.1253 data_time: 0.0220 memory: 1697 09/30 15:11:59 - mmengine - INFO - Epoch(val) [64][ 30/102] eta: 0:00:09 time: 0.1254 data_time: 0.0222 memory: 1697 09/30 15:12:00 - mmengine - INFO - Epoch(val) [64][ 35/102] eta: 0:00:08 time: 0.1250 data_time: 0.0220 memory: 1697 09/30 15:12:00 - mmengine - INFO - Epoch(val) [64][ 40/102] eta: 0:00:08 time: 0.1253 data_time: 0.0222 memory: 1697 09/30 15:12:01 - mmengine - INFO - Epoch(val) [64][ 45/102] eta: 0:00:07 time: 0.1260 data_time: 0.0224 memory: 1697 09/30 15:12:01 - mmengine - INFO - Epoch(val) [64][ 50/102] eta: 0:00:06 time: 0.1262 data_time: 0.0225 memory: 1697 09/30 15:12:02 - mmengine - INFO - Epoch(val) [64][ 55/102] eta: 0:00:05 time: 0.1105 data_time: 0.0069 memory: 1697 09/30 15:12:02 - mmengine - INFO - Epoch(val) [64][ 60/102] eta: 0:00:05 time: 0.1110 data_time: 0.0072 memory: 1697 09/30 15:12:03 - mmengine - INFO - Epoch(val) [64][ 65/102] eta: 0:00:04 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:12:04 - mmengine - INFO - Epoch(val) [64][ 70/102] eta: 0:00:03 time: 0.1111 data_time: 0.0076 memory: 1697 09/30 15:12:04 - mmengine - INFO - Epoch(val) [64][ 75/102] eta: 0:00:03 time: 0.1113 data_time: 0.0077 memory: 1697 09/30 15:12:05 - mmengine - INFO - Epoch(val) [64][ 80/102] eta: 0:00:02 time: 0.1111 data_time: 0.0075 memory: 1697 09/30 15:12:05 - mmengine - INFO - Epoch(val) [64][ 85/102] eta: 0:00:02 time: 0.1114 data_time: 0.0078 memory: 1697 09/30 15:12:06 - mmengine - INFO - Epoch(val) [64][ 90/102] eta: 0:00:01 time: 0.1113 data_time: 0.0077 memory: 1697 09/30 15:12:06 - mmengine - INFO - Epoch(val) [64][ 95/102] eta: 0:00:00 time: 0.1108 data_time: 0.0078 memory: 1697 09/30 15:12:07 - mmengine - INFO - Epoch(val) [64][100/102] eta: 0:00:00 time: 0.1107 data_time: 0.0076 memory: 1697 09/30 15:12:07 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:12:07 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:12:07 - mmengine - INFO - Epoch(val) [64][102/102] data_time: 0.0148 time: 0.1182 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:12:10 - mmengine - INFO - Epoch(train) [65][ 5/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:41 time: 0.3004 data_time: 0.0509 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:12 - mmengine - INFO - Epoch(train) [65][10/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:40 time: 0.2990 data_time: 0.0507 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:13 - mmengine - INFO - Epoch(train) [65][15/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:39 time: 0.2986 data_time: 0.0505 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:14 - mmengine - INFO - Epoch(train) [65][20/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:37 time: 0.2982 data_time: 0.0506 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:16 - mmengine - INFO - Epoch(train) [65][25/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:36 time: 0.2977 data_time: 0.0500 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:17 - mmengine - INFO - Epoch(train) [65][30/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:34 time: 0.2974 data_time: 0.0500 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:18 - mmengine - INFO - Epoch(train) [65][35/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:33 time: 0.2983 data_time: 0.0499 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:20 - mmengine - INFO - Epoch(train) [65][40/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:31 time: 0.2998 data_time: 0.0497 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:21 - mmengine - INFO - Epoch(train) [65][45/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:30 time: 0.3014 data_time: 0.0500 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:22 - mmengine - INFO - Epoch(train) [65][50/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:29 time: 0.3056 data_time: 0.0502 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:24 - mmengine - INFO - Epoch(train) [65][55/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:27 time: 0.2651 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:25 - mmengine - INFO - Epoch(train) [65][60/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:26 time: 0.2657 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:26 - mmengine - INFO - Epoch(train) [65][65/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:24 time: 0.2660 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:28 - mmengine - INFO - Epoch(train) [65][70/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:23 time: 0.2662 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:29 - mmengine - INFO - Epoch(train) [65][75/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:21 time: 0.2669 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:30 - mmengine - INFO - Epoch(train) [65][80/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:20 time: 0.2669 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:32 - mmengine - INFO - Epoch(train) [65][85/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:19 time: 0.2649 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:33 - mmengine - INFO - Epoch(train) [65][90/94] base_lr: 3.7094e-03 lr: 3.7094e-03 eta: 0:15:17 time: 0.2632 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:34 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:12:34 - mmengine - INFO - Saving checkpoint at 65 epochs 09/30 15:12:37 - mmengine - INFO - Epoch(val) [65][ 5/102] eta: 0:00:25 time: 0.1254 data_time: 0.0222 memory: 11783 09/30 15:12:37 - mmengine - INFO - Epoch(val) [65][ 10/102] eta: 0:00:16 time: 0.1251 data_time: 0.0220 memory: 1697 09/30 15:12:38 - mmengine - INFO - Epoch(val) [65][ 15/102] eta: 0:00:13 time: 0.1248 data_time: 0.0216 memory: 1697 09/30 15:12:38 - mmengine - INFO - Epoch(val) [65][ 20/102] eta: 0:00:12 time: 0.1248 data_time: 0.0217 memory: 1697 09/30 15:12:39 - mmengine - INFO - Epoch(val) [65][ 25/102] eta: 0:00:10 time: 0.1245 data_time: 0.0215 memory: 1697 09/30 15:12:39 - mmengine - INFO - Epoch(val) [65][ 30/102] eta: 0:00:09 time: 0.1248 data_time: 0.0216 memory: 1697 09/30 15:12:40 - mmengine - INFO - Epoch(val) [65][ 35/102] eta: 0:00:08 time: 0.1246 data_time: 0.0214 memory: 1697 09/30 15:12:40 - mmengine - INFO - Epoch(val) [65][ 40/102] eta: 0:00:07 time: 0.1250 data_time: 0.0215 memory: 1697 09/30 15:12:41 - mmengine - INFO - Epoch(val) [65][ 45/102] eta: 0:00:07 time: 0.1253 data_time: 0.0216 memory: 1697 09/30 15:12:42 - mmengine - INFO - Epoch(val) [65][ 50/102] eta: 0:00:06 time: 0.1254 data_time: 0.0216 memory: 1697 09/30 15:12:42 - mmengine - INFO - Epoch(val) [65][ 55/102] eta: 0:00:05 time: 0.1106 data_time: 0.0070 memory: 1697 09/30 15:12:43 - mmengine - INFO - Epoch(val) [65][ 60/102] eta: 0:00:05 time: 0.1111 data_time: 0.0074 memory: 1697 09/30 15:12:43 - mmengine - INFO - Epoch(val) [65][ 65/102] eta: 0:00:04 time: 0.1114 data_time: 0.0077 memory: 1697 09/30 15:12:44 - mmengine - INFO - Epoch(val) [65][ 70/102] eta: 0:00:03 time: 0.1115 data_time: 0.0077 memory: 1697 09/30 15:12:44 - mmengine - INFO - Epoch(val) [65][ 75/102] eta: 0:00:03 time: 0.1119 data_time: 0.0078 memory: 1697 09/30 15:12:45 - mmengine - INFO - Epoch(val) [65][ 80/102] eta: 0:00:02 time: 0.1115 data_time: 0.0077 memory: 1697 09/30 15:12:45 - mmengine - INFO - Epoch(val) [65][ 85/102] eta: 0:00:02 time: 0.1117 data_time: 0.0079 memory: 1697 09/30 15:12:46 - mmengine - INFO - Epoch(val) [65][ 90/102] eta: 0:00:01 time: 0.1115 data_time: 0.0079 memory: 1697 09/30 15:12:47 - mmengine - INFO - Epoch(val) [65][ 95/102] eta: 0:00:00 time: 0.1115 data_time: 0.0080 memory: 1697 09/30 15:12:47 - mmengine - INFO - Epoch(val) [65][100/102] eta: 0:00:00 time: 0.1113 data_time: 0.0078 memory: 1697 09/30 15:12:47 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:12:47 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:12:47 - mmengine - INFO - Epoch(val) [65][102/102] data_time: 0.0145 time: 0.1181 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:12:49 - mmengine - INFO - Epoch(train) [66][ 5/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:15 time: 0.2764 data_time: 0.0259 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:51 - mmengine - INFO - Epoch(train) [66][10/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:13 time: 0.2775 data_time: 0.0265 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:52 - mmengine - INFO - Epoch(train) [66][15/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:12 time: 0.2774 data_time: 0.0260 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:54 - mmengine - INFO - Epoch(train) [66][20/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:11 time: 0.2779 data_time: 0.0264 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:55 - mmengine - INFO - Epoch(train) [66][25/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:09 time: 0.2774 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:56 - mmengine - INFO - Epoch(train) [66][30/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:08 time: 0.2770 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:58 - mmengine - INFO - Epoch(train) [66][35/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:06 time: 0.2769 data_time: 0.0255 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:12:59 - mmengine - INFO - Epoch(train) [66][40/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:05 time: 0.2783 data_time: 0.0255 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:00 - mmengine - INFO - Epoch(train) [66][45/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:03 time: 0.2793 data_time: 0.0255 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:01 - mmengine - INFO - Epoch(train) [66][50/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:02 time: 0.2830 data_time: 0.0256 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:03 - mmengine - INFO - Epoch(train) [66][55/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:15:01 time: 0.2664 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:04 - mmengine - INFO - Epoch(train) [66][60/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:14:59 time: 0.2653 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:05 - mmengine - INFO - Epoch(train) [66][65/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:14:58 time: 0.2658 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:07 - mmengine - INFO - Epoch(train) [66][70/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:14:56 time: 0.2662 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:08 - mmengine - INFO - Epoch(train) [66][75/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:14:55 time: 0.2672 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:10 - mmengine - INFO - Epoch(train) [66][80/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:14:53 time: 0.2672 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:11 - mmengine - INFO - Epoch(train) [66][85/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:14:52 time: 0.2658 data_time: 0.0104 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:12 - mmengine - INFO - Epoch(train) [66][90/94] base_lr: 3.6063e-03 lr: 3.6063e-03 eta: 0:14:51 time: 0.2641 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:13 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:13:13 - mmengine - INFO - Saving checkpoint at 66 epochs 09/30 15:13:16 - mmengine - INFO - Epoch(val) [66][ 5/102] eta: 0:00:26 time: 0.1272 data_time: 0.0239 memory: 11783 09/30 15:13:16 - mmengine - INFO - Epoch(val) [66][ 10/102] eta: 0:00:17 time: 0.1270 data_time: 0.0236 memory: 1697 09/30 15:13:17 - mmengine - INFO - Epoch(val) [66][ 15/102] eta: 0:00:14 time: 0.1265 data_time: 0.0232 memory: 1697 09/30 15:13:17 - mmengine - INFO - Epoch(val) [66][ 20/102] eta: 0:00:12 time: 0.1261 data_time: 0.0231 memory: 1697 09/30 15:13:18 - mmengine - INFO - Epoch(val) [66][ 25/102] eta: 0:00:10 time: 0.1257 data_time: 0.0229 memory: 1697 09/30 15:13:19 - mmengine - INFO - Epoch(val) [66][ 30/102] eta: 0:00:09 time: 0.1257 data_time: 0.0231 memory: 1697 09/30 15:13:19 - mmengine - INFO - Epoch(val) [66][ 35/102] eta: 0:00:08 time: 0.1253 data_time: 0.0227 memory: 1697 09/30 15:13:20 - mmengine - INFO - Epoch(val) [66][ 40/102] eta: 0:00:08 time: 0.1253 data_time: 0.0228 memory: 1697 09/30 15:13:20 - mmengine - INFO - Epoch(val) [66][ 45/102] eta: 0:00:07 time: 0.1256 data_time: 0.0228 memory: 1697 09/30 15:13:21 - mmengine - INFO - Epoch(val) [66][ 50/102] eta: 0:00:06 time: 0.1254 data_time: 0.0228 memory: 1697 09/30 15:13:21 - mmengine - INFO - Epoch(val) [66][ 55/102] eta: 0:00:05 time: 0.1092 data_time: 0.0066 memory: 1697 09/30 15:13:22 - mmengine - INFO - Epoch(val) [66][ 60/102] eta: 0:00:05 time: 0.1093 data_time: 0.0069 memory: 1697 09/30 15:13:22 - mmengine - INFO - Epoch(val) [66][ 65/102] eta: 0:00:04 time: 0.1096 data_time: 0.0072 memory: 1697 09/30 15:13:23 - mmengine - INFO - Epoch(val) [66][ 70/102] eta: 0:00:03 time: 0.1098 data_time: 0.0072 memory: 1697 09/30 15:13:23 - mmengine - INFO - Epoch(val) [66][ 75/102] eta: 0:00:03 time: 0.1101 data_time: 0.0073 memory: 1697 09/30 15:13:24 - mmengine - INFO - Epoch(val) [66][ 80/102] eta: 0:00:02 time: 0.1101 data_time: 0.0071 memory: 1697 09/30 15:13:25 - mmengine - INFO - Epoch(val) [66][ 85/102] eta: 0:00:02 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:13:25 - mmengine - INFO - Epoch(val) [66][ 90/102] eta: 0:00:01 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:13:26 - mmengine - INFO - Epoch(val) [66][ 95/102] eta: 0:00:00 time: 0.1100 data_time: 0.0073 memory: 1697 09/30 15:13:26 - mmengine - INFO - Epoch(val) [66][100/102] eta: 0:00:00 time: 0.1099 data_time: 0.0072 memory: 1697 09/30 15:13:26 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:13:26 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:13:26 - mmengine - INFO - Epoch(val) [66][102/102] data_time: 0.0148 time: 0.1174 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:13:29 - mmengine - INFO - Epoch(train) [67][ 5/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:48 time: 0.2829 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:30 - mmengine - INFO - Epoch(train) [67][10/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:47 time: 0.2819 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:32 - mmengine - INFO - Epoch(train) [67][15/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:46 time: 0.2819 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:33 - mmengine - INFO - Epoch(train) [67][20/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:44 time: 0.2825 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:34 - mmengine - INFO - Epoch(train) [67][25/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:43 time: 0.2817 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:36 - mmengine - INFO - Epoch(train) [67][30/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:41 time: 0.2807 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:37 - mmengine - INFO - Epoch(train) [67][35/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:40 time: 0.2810 data_time: 0.0306 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:38 - mmengine - INFO - Epoch(train) [67][40/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:38 time: 0.2818 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:39 - mmengine - INFO - Epoch(train) [67][45/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:37 time: 0.2826 data_time: 0.0308 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:41 - mmengine - INFO - Epoch(train) [67][50/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:36 time: 0.2860 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:42 - mmengine - INFO - Epoch(train) [67][55/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:34 time: 0.2643 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:43 - mmengine - INFO - Epoch(train) [67][60/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:33 time: 0.2648 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:45 - mmengine - INFO - Epoch(train) [67][65/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:31 time: 0.2642 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:46 - mmengine - INFO - Epoch(train) [67][70/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:30 time: 0.2641 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:47 - mmengine - INFO - Epoch(train) [67][75/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:28 time: 0.2642 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:49 - mmengine - INFO - Epoch(train) [67][80/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:27 time: 0.2637 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:50 - mmengine - INFO - Epoch(train) [67][85/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:26 time: 0.2620 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:51 - mmengine - INFO - Epoch(train) [67][90/94] base_lr: 3.5031e-03 lr: 3.5031e-03 eta: 0:14:24 time: 0.2610 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:13:52 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:13:52 - mmengine - INFO - Saving checkpoint at 67 epochs 09/30 15:13:55 - mmengine - INFO - Epoch(val) [67][ 5/102] eta: 0:00:26 time: 0.1262 data_time: 0.0230 memory: 11783 09/30 15:13:55 - mmengine - INFO - Epoch(val) [67][ 10/102] eta: 0:00:17 time: 0.1260 data_time: 0.0227 memory: 1697 09/30 15:13:56 - mmengine - INFO - Epoch(val) [67][ 15/102] eta: 0:00:14 time: 0.1257 data_time: 0.0225 memory: 1697 09/30 15:13:56 - mmengine - INFO - Epoch(val) [67][ 20/102] eta: 0:00:12 time: 0.1257 data_time: 0.0224 memory: 1697 09/30 15:13:57 - mmengine - INFO - Epoch(val) [67][ 25/102] eta: 0:00:10 time: 0.1256 data_time: 0.0224 memory: 1697 09/30 15:13:57 - mmengine - INFO - Epoch(val) [67][ 30/102] eta: 0:00:09 time: 0.1259 data_time: 0.0226 memory: 1697 09/30 15:13:58 - mmengine - INFO - Epoch(val) [67][ 35/102] eta: 0:00:08 time: 0.1258 data_time: 0.0224 memory: 1697 09/30 15:13:59 - mmengine - INFO - Epoch(val) [67][ 40/102] eta: 0:00:08 time: 0.1260 data_time: 0.0225 memory: 1697 09/30 15:13:59 - mmengine - INFO - Epoch(val) [67][ 45/102] eta: 0:00:07 time: 0.1262 data_time: 0.0225 memory: 1697 09/30 15:14:00 - mmengine - INFO - Epoch(val) [67][ 50/102] eta: 0:00:06 time: 0.1264 data_time: 0.0225 memory: 1697 09/30 15:14:00 - mmengine - INFO - Epoch(val) [67][ 55/102] eta: 0:00:05 time: 0.1099 data_time: 0.0066 memory: 1697 09/30 15:14:01 - mmengine - INFO - Epoch(val) [67][ 60/102] eta: 0:00:05 time: 0.1102 data_time: 0.0069 memory: 1697 09/30 15:14:01 - mmengine - INFO - Epoch(val) [67][ 65/102] eta: 0:00:04 time: 0.1105 data_time: 0.0071 memory: 1697 09/30 15:14:02 - mmengine - INFO - Epoch(val) [67][ 70/102] eta: 0:00:03 time: 0.1106 data_time: 0.0072 memory: 1697 09/30 15:14:02 - mmengine - INFO - Epoch(val) [67][ 75/102] eta: 0:00:03 time: 0.1108 data_time: 0.0073 memory: 1697 09/30 15:14:03 - mmengine - INFO - Epoch(val) [67][ 80/102] eta: 0:00:02 time: 0.1105 data_time: 0.0071 memory: 1697 09/30 15:14:04 - mmengine - INFO - Epoch(val) [67][ 85/102] eta: 0:00:02 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:14:04 - mmengine - INFO - Epoch(val) [67][ 90/102] eta: 0:00:01 time: 0.1102 data_time: 0.0073 memory: 1697 09/30 15:14:05 - mmengine - INFO - Epoch(val) [67][ 95/102] eta: 0:00:00 time: 0.1101 data_time: 0.0073 memory: 1697 09/30 15:14:05 - mmengine - INFO - Epoch(val) [67][100/102] eta: 0:00:00 time: 0.1096 data_time: 0.0071 memory: 1697 09/30 15:14:05 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:14:05 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:14:05 - mmengine - INFO - Epoch(val) [67][102/102] data_time: 0.0146 time: 0.1177 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:14:08 - mmengine - INFO - Epoch(train) [68][ 5/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:22 time: 0.2801 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:09 - mmengine - INFO - Epoch(train) [68][10/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:21 time: 0.2799 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:10 - mmengine - INFO - Epoch(train) [68][15/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:19 time: 0.2803 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:12 - mmengine - INFO - Epoch(train) [68][20/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:18 time: 0.2805 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:13 - mmengine - INFO - Epoch(train) [68][25/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:16 time: 0.2805 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:14 - mmengine - INFO - Epoch(train) [68][30/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:15 time: 0.2804 data_time: 0.0306 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:16 - mmengine - INFO - Epoch(train) [68][35/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:13 time: 0.2810 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:17 - mmengine - INFO - Epoch(train) [68][40/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:12 time: 0.2825 data_time: 0.0308 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:18 - mmengine - INFO - Epoch(train) [68][45/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:11 time: 0.2838 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:20 - mmengine - INFO - Epoch(train) [68][50/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:09 time: 0.2881 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:21 - mmengine - INFO - Epoch(train) [68][55/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:08 time: 0.2665 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:22 - mmengine - INFO - Epoch(train) [68][60/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:06 time: 0.2663 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:24 - mmengine - INFO - Epoch(train) [68][65/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:05 time: 0.2656 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:25 - mmengine - INFO - Epoch(train) [68][70/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:04 time: 0.2660 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:26 - mmengine - INFO - Epoch(train) [68][75/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:02 time: 0.2661 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:28 - mmengine - INFO - Epoch(train) [68][80/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:14:01 time: 0.2655 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:29 - mmengine - INFO - Epoch(train) [68][85/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:13:59 time: 0.2638 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:30 - mmengine - INFO - Epoch(train) [68][90/94] base_lr: 3.4000e-03 lr: 3.4000e-03 eta: 0:13:58 time: 0.2624 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:31 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:14:31 - mmengine - INFO - Saving checkpoint at 68 epochs 09/30 15:14:35 - mmengine - INFO - Epoch(val) [68][ 5/102] eta: 0:00:24 time: 0.1238 data_time: 0.0211 memory: 11783 09/30 15:14:36 - mmengine - INFO - Epoch(val) [68][ 10/102] eta: 0:00:16 time: 0.1236 data_time: 0.0208 memory: 1697 09/30 15:14:36 - mmengine - INFO - Epoch(val) [68][ 15/102] eta: 0:00:13 time: 0.1234 data_time: 0.0205 memory: 1697 09/30 15:14:37 - mmengine - INFO - Epoch(val) [68][ 20/102] eta: 0:00:11 time: 0.1231 data_time: 0.0205 memory: 1697 09/30 15:14:37 - mmengine - INFO - Epoch(val) [68][ 25/102] eta: 0:00:10 time: 0.1228 data_time: 0.0203 memory: 1697 09/30 15:14:38 - mmengine - INFO - Epoch(val) [68][ 30/102] eta: 0:00:09 time: 0.1232 data_time: 0.0205 memory: 1697 09/30 15:14:38 - mmengine - INFO - Epoch(val) [68][ 35/102] eta: 0:00:08 time: 0.1230 data_time: 0.0203 memory: 1697 09/30 15:14:39 - mmengine - INFO - Epoch(val) [68][ 40/102] eta: 0:00:07 time: 0.1233 data_time: 0.0205 memory: 1697 09/30 15:14:40 - mmengine - INFO - Epoch(val) [68][ 45/102] eta: 0:00:07 time: 0.1237 data_time: 0.0206 memory: 1697 09/30 15:14:40 - mmengine - INFO - Epoch(val) [68][ 50/102] eta: 0:00:06 time: 0.1240 data_time: 0.0207 memory: 1697 09/30 15:14:41 - mmengine - INFO - Epoch(val) [68][ 55/102] eta: 0:00:05 time: 0.1100 data_time: 0.0067 memory: 1697 09/30 15:14:41 - mmengine - INFO - Epoch(val) [68][ 60/102] eta: 0:00:05 time: 0.1101 data_time: 0.0069 memory: 1697 09/30 15:14:42 - mmengine - INFO - Epoch(val) [68][ 65/102] eta: 0:00:04 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:14:42 - mmengine - INFO - Epoch(val) [68][ 70/102] eta: 0:00:03 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:14:43 - mmengine - INFO - Epoch(val) [68][ 75/102] eta: 0:00:03 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 15:14:43 - mmengine - INFO - Epoch(val) [68][ 80/102] eta: 0:00:02 time: 0.1100 data_time: 0.0073 memory: 1697 09/30 15:14:44 - mmengine - INFO - Epoch(val) [68][ 85/102] eta: 0:00:02 time: 0.1100 data_time: 0.0074 memory: 1697 09/30 15:14:44 - mmengine - INFO - Epoch(val) [68][ 90/102] eta: 0:00:01 time: 0.1101 data_time: 0.0074 memory: 1697 09/30 15:14:45 - mmengine - INFO - Epoch(val) [68][ 95/102] eta: 0:00:00 time: 0.1100 data_time: 0.0074 memory: 1697 09/30 15:14:46 - mmengine - INFO - Epoch(val) [68][100/102] eta: 0:00:00 time: 0.1100 data_time: 0.0073 memory: 1697 09/30 15:14:46 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:14:46 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:14:46 - mmengine - INFO - Epoch(val) [68][102/102] data_time: 0.0138 time: 0.1167 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:14:48 - mmengine - INFO - Epoch(train) [69][ 5/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:56 time: 0.2836 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:50 - mmengine - INFO - Epoch(train) [69][10/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:54 time: 0.2832 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:51 - mmengine - INFO - Epoch(train) [69][15/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:53 time: 0.2835 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:52 - mmengine - INFO - Epoch(train) [69][20/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:51 time: 0.2831 data_time: 0.0345 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:54 - mmengine - INFO - Epoch(train) [69][25/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:50 time: 0.2829 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:55 - mmengine - INFO - Epoch(train) [69][30/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:49 time: 0.2829 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:56 - mmengine - INFO - Epoch(train) [69][35/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:47 time: 0.2835 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:58 - mmengine - INFO - Epoch(train) [69][40/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:46 time: 0.2852 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:14:59 - mmengine - INFO - Epoch(train) [69][45/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:44 time: 0.2862 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:00 - mmengine - INFO - Epoch(train) [69][50/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:43 time: 0.2901 data_time: 0.0343 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:02 - mmengine - INFO - Epoch(train) [69][55/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:41 time: 0.2646 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:03 - mmengine - INFO - Epoch(train) [69][60/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:40 time: 0.2647 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:04 - mmengine - INFO - Epoch(train) [69][65/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:39 time: 0.2643 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:06 - mmengine - INFO - Epoch(train) [69][70/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:37 time: 0.2647 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:07 - mmengine - INFO - Epoch(train) [69][75/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:36 time: 0.2646 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:08 - mmengine - INFO - Epoch(train) [69][80/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:34 time: 0.2635 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:09 - mmengine - INFO - Epoch(train) [69][85/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:33 time: 0.2618 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:11 - mmengine - INFO - Epoch(train) [69][90/94] base_lr: 3.2969e-03 lr: 3.2969e-03 eta: 0:13:31 time: 0.2600 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:12 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:15:12 - mmengine - INFO - Saving checkpoint at 69 epochs 09/30 15:15:15 - mmengine - INFO - Epoch(val) [69][ 5/102] eta: 0:00:26 time: 0.1265 data_time: 0.0238 memory: 11783 09/30 15:15:15 - mmengine - INFO - Epoch(val) [69][ 10/102] eta: 0:00:17 time: 0.1264 data_time: 0.0235 memory: 1697 09/30 15:15:16 - mmengine - INFO - Epoch(val) [69][ 15/102] eta: 0:00:14 time: 0.1263 data_time: 0.0233 memory: 1697 09/30 15:15:16 - mmengine - INFO - Epoch(val) [69][ 20/102] eta: 0:00:12 time: 0.1264 data_time: 0.0232 memory: 1697 09/30 15:15:17 - mmengine - INFO - Epoch(val) [69][ 25/102] eta: 0:00:11 time: 0.1265 data_time: 0.0231 memory: 1697 09/30 15:15:17 - mmengine - INFO - Epoch(val) [69][ 30/102] eta: 0:00:09 time: 0.1270 data_time: 0.0232 memory: 1697 09/30 15:15:18 - mmengine - INFO - Epoch(val) [69][ 35/102] eta: 0:00:08 time: 0.1269 data_time: 0.0230 memory: 1697 09/30 15:15:18 - mmengine - INFO - Epoch(val) [69][ 40/102] eta: 0:00:08 time: 0.1273 data_time: 0.0232 memory: 1697 09/30 15:15:19 - mmengine - INFO - Epoch(val) [69][ 45/102] eta: 0:00:07 time: 0.1270 data_time: 0.0232 memory: 1697 09/30 15:15:20 - mmengine - INFO - Epoch(val) [69][ 50/102] eta: 0:00:06 time: 0.1271 data_time: 0.0232 memory: 1697 09/30 15:15:20 - mmengine - INFO - Epoch(val) [69][ 55/102] eta: 0:00:05 time: 0.1103 data_time: 0.0068 memory: 1697 09/30 15:15:21 - mmengine - INFO - Epoch(val) [69][ 60/102] eta: 0:00:05 time: 0.1105 data_time: 0.0070 memory: 1697 09/30 15:15:21 - mmengine - INFO - Epoch(val) [69][ 65/102] eta: 0:00:04 time: 0.1109 data_time: 0.0072 memory: 1697 09/30 15:15:22 - mmengine - INFO - Epoch(val) [69][ 70/102] eta: 0:00:03 time: 0.1110 data_time: 0.0073 memory: 1697 09/30 15:15:22 - mmengine - INFO - Epoch(val) [69][ 75/102] eta: 0:00:03 time: 0.1109 data_time: 0.0074 memory: 1697 09/30 15:15:23 - mmengine - INFO - Epoch(val) [69][ 80/102] eta: 0:00:02 time: 0.1107 data_time: 0.0073 memory: 1697 09/30 15:15:23 - mmengine - INFO - Epoch(val) [69][ 85/102] eta: 0:00:02 time: 0.1106 data_time: 0.0074 memory: 1697 09/30 15:15:24 - mmengine - INFO - Epoch(val) [69][ 90/102] eta: 0:00:01 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:15:24 - mmengine - INFO - Epoch(val) [69][ 95/102] eta: 0:00:00 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 15:15:25 - mmengine - INFO - Epoch(val) [69][100/102] eta: 0:00:00 time: 0.1099 data_time: 0.0072 memory: 1697 09/30 15:15:25 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:15:25 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:15:25 - mmengine - INFO - Epoch(val) [69][102/102] data_time: 0.0150 time: 0.1182 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:15:28 - mmengine - INFO - Epoch(train) [70][ 5/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:29 time: 0.2801 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:29 - mmengine - INFO - Epoch(train) [70][10/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:28 time: 0.2812 data_time: 0.0324 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:30 - mmengine - INFO - Epoch(train) [70][15/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:26 time: 0.2815 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:32 - mmengine - INFO - Epoch(train) [70][20/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:25 time: 0.2815 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:33 - mmengine - INFO - Epoch(train) [70][25/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:24 time: 0.2809 data_time: 0.0319 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:34 - mmengine - INFO - Epoch(train) [70][30/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:22 time: 0.2810 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:36 - mmengine - INFO - Epoch(train) [70][35/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:21 time: 0.2810 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:37 - mmengine - INFO - Epoch(train) [70][40/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:19 time: 0.2829 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:38 - mmengine - INFO - Epoch(train) [70][45/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:18 time: 0.2840 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:40 - mmengine - INFO - Epoch(train) [70][50/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:16 time: 0.2878 data_time: 0.0325 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:41 - mmengine - INFO - Epoch(train) [70][55/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:15 time: 0.2645 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:42 - mmengine - INFO - Epoch(train) [70][60/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:14 time: 0.2642 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:44 - mmengine - INFO - Epoch(train) [70][65/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:12 time: 0.2644 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:45 - mmengine - INFO - Epoch(train) [70][70/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:11 time: 0.2646 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:46 - mmengine - INFO - Epoch(train) [70][75/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:09 time: 0.2653 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:48 - mmengine - INFO - Epoch(train) [70][80/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:08 time: 0.2651 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:49 - mmengine - INFO - Epoch(train) [70][85/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:07 time: 0.2641 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:50 - mmengine - INFO - Epoch(train) [70][90/94] base_lr: 3.1938e-03 lr: 3.1938e-03 eta: 0:13:05 time: 0.2631 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:15:51 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:15:51 - mmengine - INFO - Saving checkpoint at 70 epochs 09/30 15:15:54 - mmengine - INFO - Epoch(val) [70][ 5/102] eta: 0:00:26 time: 0.1260 data_time: 0.0230 memory: 11783 09/30 15:15:54 - mmengine - INFO - Epoch(val) [70][ 10/102] eta: 0:00:17 time: 0.1259 data_time: 0.0227 memory: 1697 09/30 15:15:55 - mmengine - INFO - Epoch(val) [70][ 15/102] eta: 0:00:14 time: 0.1256 data_time: 0.0225 memory: 1697 09/30 15:15:56 - mmengine - INFO - Epoch(val) [70][ 20/102] eta: 0:00:12 time: 0.1256 data_time: 0.0225 memory: 1697 09/30 15:15:56 - mmengine - INFO - Epoch(val) [70][ 25/102] eta: 0:00:10 time: 0.1257 data_time: 0.0224 memory: 1697 09/30 15:15:57 - mmengine - INFO - Epoch(val) [70][ 30/102] eta: 0:00:09 time: 0.1259 data_time: 0.0226 memory: 1697 09/30 15:15:57 - mmengine - INFO - Epoch(val) [70][ 35/102] eta: 0:00:08 time: 0.1259 data_time: 0.0224 memory: 1697 09/30 15:15:58 - mmengine - INFO - Epoch(val) [70][ 40/102] eta: 0:00:08 time: 0.1262 data_time: 0.0226 memory: 1697 09/30 15:15:58 - mmengine - INFO - Epoch(val) [70][ 45/102] eta: 0:00:07 time: 0.1268 data_time: 0.0227 memory: 1697 09/30 15:15:59 - mmengine - INFO - Epoch(val) [70][ 50/102] eta: 0:00:06 time: 0.1272 data_time: 0.0229 memory: 1697 09/30 15:15:59 - mmengine - INFO - Epoch(val) [70][ 55/102] eta: 0:00:05 time: 0.1110 data_time: 0.0070 memory: 1697 09/30 15:16:00 - mmengine - INFO - Epoch(val) [70][ 60/102] eta: 0:00:05 time: 0.1114 data_time: 0.0073 memory: 1697 09/30 15:16:01 - mmengine - INFO - Epoch(val) [70][ 65/102] eta: 0:00:04 time: 0.1116 data_time: 0.0077 memory: 1697 09/30 15:16:01 - mmengine - INFO - Epoch(val) [70][ 70/102] eta: 0:00:03 time: 0.1118 data_time: 0.0077 memory: 1697 09/30 15:16:02 - mmengine - INFO - Epoch(val) [70][ 75/102] eta: 0:00:03 time: 0.1117 data_time: 0.0078 memory: 1697 09/30 15:16:02 - mmengine - INFO - Epoch(val) [70][ 80/102] eta: 0:00:02 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:16:03 - mmengine - INFO - Epoch(val) [70][ 85/102] eta: 0:00:02 time: 0.1116 data_time: 0.0078 memory: 1697 09/30 15:16:03 - mmengine - INFO - Epoch(val) [70][ 90/102] eta: 0:00:01 time: 0.1116 data_time: 0.0078 memory: 1697 09/30 15:16:04 - mmengine - INFO - Epoch(val) [70][ 95/102] eta: 0:00:00 time: 0.1114 data_time: 0.0078 memory: 1697 09/30 15:16:04 - mmengine - INFO - Epoch(val) [70][100/102] eta: 0:00:00 time: 0.1113 data_time: 0.0077 memory: 1697 09/30 15:16:05 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:16:05 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:16:05 - mmengine - INFO - Epoch(val) [70][102/102] data_time: 0.0150 time: 0.1190 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:16:07 - mmengine - INFO - Epoch(train) [71][ 5/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:13:03 time: 0.2837 data_time: 0.0345 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:09 - mmengine - INFO - Epoch(train) [71][10/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:13:02 time: 0.2825 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:10 - mmengine - INFO - Epoch(train) [71][15/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:13:00 time: 0.2828 data_time: 0.0343 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:11 - mmengine - INFO - Epoch(train) [71][20/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:59 time: 0.2827 data_time: 0.0339 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:13 - mmengine - INFO - Epoch(train) [71][25/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:57 time: 0.2829 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:14 - mmengine - INFO - Epoch(train) [71][30/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:56 time: 0.2829 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:15 - mmengine - INFO - Epoch(train) [71][35/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:54 time: 0.2830 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:16 - mmengine - INFO - Epoch(train) [71][40/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:53 time: 0.2837 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:18 - mmengine - INFO - Epoch(train) [71][45/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:52 time: 0.2847 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:19 - mmengine - INFO - Epoch(train) [71][50/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:50 time: 0.2888 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:20 - mmengine - INFO - Epoch(train) [71][55/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:49 time: 0.2651 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:22 - mmengine - INFO - Epoch(train) [71][60/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:47 time: 0.2664 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:23 - mmengine - INFO - Epoch(train) [71][65/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:46 time: 0.2662 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:25 - mmengine - INFO - Epoch(train) [71][70/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:45 time: 0.2673 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:26 - mmengine - INFO - Epoch(train) [71][75/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:43 time: 0.2669 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:27 - mmengine - INFO - Epoch(train) [71][80/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:42 time: 0.2666 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:28 - mmengine - INFO - Epoch(train) [71][85/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:40 time: 0.2655 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:30 - mmengine - INFO - Epoch(train) [71][90/94] base_lr: 3.0906e-03 lr: 3.0906e-03 eta: 0:12:39 time: 0.2645 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:31 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:16:31 - mmengine - INFO - Saving checkpoint at 71 epochs 09/30 15:16:33 - mmengine - INFO - Epoch(val) [71][ 5/102] eta: 0:00:26 time: 0.1273 data_time: 0.0234 memory: 11783 09/30 15:16:34 - mmengine - INFO - Epoch(val) [71][ 10/102] eta: 0:00:17 time: 0.1270 data_time: 0.0231 memory: 1697 09/30 15:16:34 - mmengine - INFO - Epoch(val) [71][ 15/102] eta: 0:00:14 time: 0.1266 data_time: 0.0229 memory: 1697 09/30 15:16:35 - mmengine - INFO - Epoch(val) [71][ 20/102] eta: 0:00:12 time: 0.1264 data_time: 0.0228 memory: 1697 09/30 15:16:35 - mmengine - INFO - Epoch(val) [71][ 25/102] eta: 0:00:10 time: 0.1263 data_time: 0.0227 memory: 1697 09/30 15:16:36 - mmengine - INFO - Epoch(val) [71][ 30/102] eta: 0:00:09 time: 0.1266 data_time: 0.0228 memory: 1697 09/30 15:16:37 - mmengine - INFO - Epoch(val) [71][ 35/102] eta: 0:00:08 time: 0.1263 data_time: 0.0226 memory: 1697 09/30 15:16:37 - mmengine - INFO - Epoch(val) [71][ 40/102] eta: 0:00:08 time: 0.1265 data_time: 0.0226 memory: 1697 09/30 15:16:38 - mmengine - INFO - Epoch(val) [71][ 45/102] eta: 0:00:07 time: 0.1268 data_time: 0.0228 memory: 1697 09/30 15:16:38 - mmengine - INFO - Epoch(val) [71][ 50/102] eta: 0:00:06 time: 0.1267 data_time: 0.0228 memory: 1697 09/30 15:16:39 - mmengine - INFO - Epoch(val) [71][ 55/102] eta: 0:00:05 time: 0.1105 data_time: 0.0070 memory: 1697 09/30 15:16:39 - mmengine - INFO - Epoch(val) [71][ 60/102] eta: 0:00:05 time: 0.1107 data_time: 0.0072 memory: 1697 09/30 15:16:40 - mmengine - INFO - Epoch(val) [71][ 65/102] eta: 0:00:04 time: 0.1111 data_time: 0.0075 memory: 1697 09/30 15:16:40 - mmengine - INFO - Epoch(val) [71][ 70/102] eta: 0:00:03 time: 0.1112 data_time: 0.0075 memory: 1697 09/30 15:16:41 - mmengine - INFO - Epoch(val) [71][ 75/102] eta: 0:00:03 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:16:42 - mmengine - INFO - Epoch(val) [71][ 80/102] eta: 0:00:02 time: 0.1111 data_time: 0.0076 memory: 1697 09/30 15:16:42 - mmengine - INFO - Epoch(val) [71][ 85/102] eta: 0:00:02 time: 0.1114 data_time: 0.0077 memory: 1697 09/30 15:16:43 - mmengine - INFO - Epoch(val) [71][ 90/102] eta: 0:00:01 time: 0.1113 data_time: 0.0077 memory: 1697 09/30 15:16:43 - mmengine - INFO - Epoch(val) [71][ 95/102] eta: 0:00:00 time: 0.1112 data_time: 0.0078 memory: 1697 09/30 15:16:44 - mmengine - INFO - Epoch(val) [71][100/102] eta: 0:00:00 time: 0.1110 data_time: 0.0076 memory: 1697 09/30 15:16:44 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:16:44 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:16:44 - mmengine - INFO - Epoch(val) [71][102/102] data_time: 0.0150 time: 0.1186 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:16:47 - mmengine - INFO - Epoch(train) [72][ 5/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:37 time: 0.2855 data_time: 0.0348 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:48 - mmengine - INFO - Epoch(train) [72][10/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:35 time: 0.2853 data_time: 0.0354 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:49 - mmengine - INFO - Epoch(train) [72][15/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:34 time: 0.2847 data_time: 0.0347 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:51 - mmengine - INFO - Epoch(train) [72][20/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:32 time: 0.2855 data_time: 0.0348 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:52 - mmengine - INFO - Epoch(train) [72][25/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:31 time: 0.2841 data_time: 0.0343 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:53 - mmengine - INFO - Epoch(train) [72][30/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:30 time: 0.2845 data_time: 0.0343 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:55 - mmengine - INFO - Epoch(train) [72][35/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:28 time: 0.2843 data_time: 0.0343 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:56 - mmengine - INFO - Epoch(train) [72][40/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:27 time: 0.2854 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:57 - mmengine - INFO - Epoch(train) [72][45/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:25 time: 0.2879 data_time: 0.0345 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:16:59 - mmengine - INFO - Epoch(train) [72][50/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:24 time: 0.2918 data_time: 0.0346 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:00 - mmengine - INFO - Epoch(train) [72][55/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:23 time: 0.2674 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:01 - mmengine - INFO - Epoch(train) [72][60/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:21 time: 0.2668 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:03 - mmengine - INFO - Epoch(train) [72][65/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:20 time: 0.2671 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:04 - mmengine - INFO - Epoch(train) [72][70/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:18 time: 0.2660 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:05 - mmengine - INFO - Epoch(train) [72][75/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:17 time: 0.2669 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:07 - mmengine - INFO - Epoch(train) [72][80/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:16 time: 0.2668 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:08 - mmengine - INFO - Epoch(train) [72][85/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:14 time: 0.2658 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:09 - mmengine - INFO - Epoch(train) [72][90/94] base_lr: 2.9875e-03 lr: 2.9875e-03 eta: 0:12:13 time: 0.2656 data_time: 0.0104 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:10 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:17:10 - mmengine - INFO - Saving checkpoint at 72 epochs 09/30 15:17:13 - mmengine - INFO - Epoch(val) [72][ 5/102] eta: 0:00:26 time: 0.1271 data_time: 0.0236 memory: 11783 09/30 15:17:14 - mmengine - INFO - Epoch(val) [72][ 10/102] eta: 0:00:17 time: 0.1270 data_time: 0.0233 memory: 1697 09/30 15:17:14 - mmengine - INFO - Epoch(val) [72][ 15/102] eta: 0:00:14 time: 0.1269 data_time: 0.0230 memory: 1697 09/30 15:17:15 - mmengine - INFO - Epoch(val) [72][ 20/102] eta: 0:00:12 time: 0.1272 data_time: 0.0231 memory: 1697 09/30 15:17:15 - mmengine - INFO - Epoch(val) [72][ 25/102] eta: 0:00:11 time: 0.1272 data_time: 0.0229 memory: 1697 09/30 15:17:16 - mmengine - INFO - Epoch(val) [72][ 30/102] eta: 0:00:09 time: 0.1271 data_time: 0.0231 memory: 1697 09/30 15:17:16 - mmengine - INFO - Epoch(val) [72][ 35/102] eta: 0:00:08 time: 0.1268 data_time: 0.0228 memory: 1697 09/30 15:17:17 - mmengine - INFO - Epoch(val) [72][ 40/102] eta: 0:00:08 time: 0.1272 data_time: 0.0229 memory: 1697 09/30 15:17:17 - mmengine - INFO - Epoch(val) [72][ 45/102] eta: 0:00:07 time: 0.1274 data_time: 0.0230 memory: 1697 09/30 15:17:18 - mmengine - INFO - Epoch(val) [72][ 50/102] eta: 0:00:06 time: 0.1276 data_time: 0.0231 memory: 1697 09/30 15:17:19 - mmengine - INFO - Epoch(val) [72][ 55/102] eta: 0:00:05 time: 0.1119 data_time: 0.0073 memory: 1697 09/30 15:17:19 - mmengine - INFO - Epoch(val) [72][ 60/102] eta: 0:00:05 time: 0.1122 data_time: 0.0076 memory: 1697 09/30 15:17:20 - mmengine - INFO - Epoch(val) [72][ 65/102] eta: 0:00:04 time: 0.1124 data_time: 0.0079 memory: 1697 09/30 15:17:20 - mmengine - INFO - Epoch(val) [72][ 70/102] eta: 0:00:03 time: 0.1121 data_time: 0.0079 memory: 1697 09/30 15:17:21 - mmengine - INFO - Epoch(val) [72][ 75/102] eta: 0:00:03 time: 0.1123 data_time: 0.0080 memory: 1697 09/30 15:17:21 - mmengine - INFO - Epoch(val) [72][ 80/102] eta: 0:00:02 time: 0.1122 data_time: 0.0078 memory: 1697 09/30 15:17:22 - mmengine - INFO - Epoch(val) [72][ 85/102] eta: 0:00:02 time: 0.1123 data_time: 0.0080 memory: 1697 09/30 15:17:22 - mmengine - INFO - Epoch(val) [72][ 90/102] eta: 0:00:01 time: 0.1120 data_time: 0.0080 memory: 1697 09/30 15:17:23 - mmengine - INFO - Epoch(val) [72][ 95/102] eta: 0:00:00 time: 0.1123 data_time: 0.0080 memory: 1697 09/30 15:17:24 - mmengine - INFO - Epoch(val) [72][100/102] eta: 0:00:00 time: 0.1120 data_time: 0.0078 memory: 1697 09/30 15:17:24 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:17:24 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:17:24 - mmengine - INFO - Epoch(val) [72][102/102] data_time: 0.0152 time: 0.1195 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:17:27 - mmengine - INFO - Epoch(train) [73][ 5/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:11 time: 0.3049 data_time: 0.0534 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:29 - mmengine - INFO - Epoch(train) [73][10/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:09 time: 0.3040 data_time: 0.0531 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:30 - mmengine - INFO - Epoch(train) [73][15/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:08 time: 0.3036 data_time: 0.0526 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:31 - mmengine - INFO - Epoch(train) [73][20/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:07 time: 0.3035 data_time: 0.0524 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:33 - mmengine - INFO - Epoch(train) [73][25/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:05 time: 0.3038 data_time: 0.0525 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:34 - mmengine - INFO - Epoch(train) [73][30/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:04 time: 0.3035 data_time: 0.0524 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:35 - mmengine - INFO - Epoch(train) [73][35/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:02 time: 0.3036 data_time: 0.0524 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:37 - mmengine - INFO - Epoch(train) [73][40/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:01 time: 0.3040 data_time: 0.0523 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:38 - mmengine - INFO - Epoch(train) [73][45/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:12:00 time: 0.3048 data_time: 0.0521 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:39 - mmengine - INFO - Epoch(train) [73][50/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:58 time: 0.3084 data_time: 0.0521 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:41 - mmengine - INFO - Epoch(train) [73][55/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:57 time: 0.2648 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:42 - mmengine - INFO - Epoch(train) [73][60/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:55 time: 0.2654 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:43 - mmengine - INFO - Epoch(train) [73][65/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:54 time: 0.2660 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:45 - mmengine - INFO - Epoch(train) [73][70/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:52 time: 0.2661 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:46 - mmengine - INFO - Epoch(train) [73][75/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:51 time: 0.2662 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:47 - mmengine - INFO - Epoch(train) [73][80/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:50 time: 0.2660 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:48 - mmengine - INFO - Epoch(train) [73][85/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:48 time: 0.2643 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:50 - mmengine - INFO - Epoch(train) [73][90/94] base_lr: 2.8844e-03 lr: 2.8844e-03 eta: 0:11:47 time: 0.2632 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:17:51 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:17:51 - mmengine - INFO - Saving checkpoint at 73 epochs 09/30 15:17:54 - mmengine - INFO - Epoch(val) [73][ 5/102] eta: 0:00:25 time: 0.1272 data_time: 0.0233 memory: 11783 09/30 15:17:54 - mmengine - INFO - Epoch(val) [73][ 10/102] eta: 0:00:17 time: 0.1267 data_time: 0.0230 memory: 1697 09/30 15:17:55 - mmengine - INFO - Epoch(val) [73][ 15/102] eta: 0:00:14 time: 0.1266 data_time: 0.0227 memory: 1697 09/30 15:17:55 - mmengine - INFO - Epoch(val) [73][ 20/102] eta: 0:00:12 time: 0.1264 data_time: 0.0226 memory: 1697 09/30 15:17:56 - mmengine - INFO - Epoch(val) [73][ 25/102] eta: 0:00:10 time: 0.1261 data_time: 0.0225 memory: 1697 09/30 15:17:56 - mmengine - INFO - Epoch(val) [73][ 30/102] eta: 0:00:09 time: 0.1262 data_time: 0.0225 memory: 1697 09/30 15:17:57 - mmengine - INFO - Epoch(val) [73][ 35/102] eta: 0:00:08 time: 0.1260 data_time: 0.0223 memory: 1697 09/30 15:17:57 - mmengine - INFO - Epoch(val) [73][ 40/102] eta: 0:00:08 time: 0.1262 data_time: 0.0225 memory: 1697 09/30 15:17:58 - mmengine - INFO - Epoch(val) [73][ 45/102] eta: 0:00:07 time: 0.1261 data_time: 0.0226 memory: 1697 09/30 15:17:58 - mmengine - INFO - Epoch(val) [73][ 50/102] eta: 0:00:06 time: 0.1264 data_time: 0.0226 memory: 1697 09/30 15:17:59 - mmengine - INFO - Epoch(val) [73][ 55/102] eta: 0:00:05 time: 0.1107 data_time: 0.0070 memory: 1697 09/30 15:18:00 - mmengine - INFO - Epoch(val) [73][ 60/102] eta: 0:00:05 time: 0.1110 data_time: 0.0072 memory: 1697 09/30 15:18:00 - mmengine - INFO - Epoch(val) [73][ 65/102] eta: 0:00:04 time: 0.1111 data_time: 0.0075 memory: 1697 09/30 15:18:01 - mmengine - INFO - Epoch(val) [73][ 70/102] eta: 0:00:03 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:18:01 - mmengine - INFO - Epoch(val) [73][ 75/102] eta: 0:00:03 time: 0.1114 data_time: 0.0077 memory: 1697 09/30 15:18:02 - mmengine - INFO - Epoch(val) [73][ 80/102] eta: 0:00:02 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:18:02 - mmengine - INFO - Epoch(val) [73][ 85/102] eta: 0:00:02 time: 0.1113 data_time: 0.0077 memory: 1697 09/30 15:18:03 - mmengine - INFO - Epoch(val) [73][ 90/102] eta: 0:00:01 time: 0.1110 data_time: 0.0076 memory: 1697 09/30 15:18:03 - mmengine - INFO - Epoch(val) [73][ 95/102] eta: 0:00:00 time: 0.1111 data_time: 0.0077 memory: 1697 09/30 15:18:04 - mmengine - INFO - Epoch(val) [73][100/102] eta: 0:00:00 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 15:18:04 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:18:04 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:18:04 - mmengine - INFO - Epoch(val) [73][102/102] data_time: 0.0148 time: 0.1184 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:18:06 - mmengine - INFO - Epoch(train) [74][ 5/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:44 time: 0.2750 data_time: 0.0247 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:08 - mmengine - INFO - Epoch(train) [74][10/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:43 time: 0.2748 data_time: 0.0248 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:09 - mmengine - INFO - Epoch(train) [74][15/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:42 time: 0.2749 data_time: 0.0246 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:10 - mmengine - INFO - Epoch(train) [74][20/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:40 time: 0.2753 data_time: 0.0248 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:12 - mmengine - INFO - Epoch(train) [74][25/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:39 time: 0.2750 data_time: 0.0242 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:13 - mmengine - INFO - Epoch(train) [74][30/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:37 time: 0.2748 data_time: 0.0242 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:14 - mmengine - INFO - Epoch(train) [74][35/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:36 time: 0.2756 data_time: 0.0242 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:16 - mmengine - INFO - Epoch(train) [74][40/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:35 time: 0.2768 data_time: 0.0243 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:17 - mmengine - INFO - Epoch(train) [74][45/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:33 time: 0.2778 data_time: 0.0242 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:18 - mmengine - INFO - Epoch(train) [74][50/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:32 time: 0.2817 data_time: 0.0244 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:20 - mmengine - INFO - Epoch(train) [74][55/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:30 time: 0.2660 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:21 - mmengine - INFO - Epoch(train) [74][60/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:29 time: 0.2663 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:22 - mmengine - INFO - Epoch(train) [74][65/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:27 time: 0.2661 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:24 - mmengine - INFO - Epoch(train) [74][70/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:26 time: 0.2651 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:25 - mmengine - INFO - Epoch(train) [74][75/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:25 time: 0.2652 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:26 - mmengine - INFO - Epoch(train) [74][80/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:23 time: 0.2649 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:28 - mmengine - INFO - Epoch(train) [74][85/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:22 time: 0.2633 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:29 - mmengine - INFO - Epoch(train) [74][90/94] base_lr: 2.7813e-03 lr: 2.7813e-03 eta: 0:11:20 time: 0.2621 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:30 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:18:30 - mmengine - INFO - Saving checkpoint at 74 epochs 09/30 15:18:32 - mmengine - INFO - Epoch(val) [74][ 5/102] eta: 0:00:22 time: 0.1226 data_time: 0.0193 memory: 11783 09/30 15:18:33 - mmengine - INFO - Epoch(val) [74][ 10/102] eta: 0:00:15 time: 0.1225 data_time: 0.0191 memory: 1697 09/30 15:18:33 - mmengine - INFO - Epoch(val) [74][ 15/102] eta: 0:00:12 time: 0.1221 data_time: 0.0188 memory: 1697 09/30 15:18:34 - mmengine - INFO - Epoch(val) [74][ 20/102] eta: 0:00:11 time: 0.1220 data_time: 0.0186 memory: 1697 09/30 15:18:34 - mmengine - INFO - Epoch(val) [74][ 25/102] eta: 0:00:10 time: 0.1220 data_time: 0.0187 memory: 1697 09/30 15:18:35 - mmengine - INFO - Epoch(val) [74][ 30/102] eta: 0:00:09 time: 0.1220 data_time: 0.0187 memory: 1697 09/30 15:18:35 - mmengine - INFO - Epoch(val) [74][ 35/102] eta: 0:00:08 time: 0.1217 data_time: 0.0185 memory: 1697 09/30 15:18:36 - mmengine - INFO - Epoch(val) [74][ 40/102] eta: 0:00:07 time: 0.1220 data_time: 0.0186 memory: 1697 09/30 15:18:37 - mmengine - INFO - Epoch(val) [74][ 45/102] eta: 0:00:07 time: 0.1220 data_time: 0.0186 memory: 1697 09/30 15:18:37 - mmengine - INFO - Epoch(val) [74][ 50/102] eta: 0:00:06 time: 0.1220 data_time: 0.0186 memory: 1697 09/30 15:18:38 - mmengine - INFO - Epoch(val) [74][ 55/102] eta: 0:00:05 time: 0.1101 data_time: 0.0066 memory: 1697 09/30 15:18:38 - mmengine - INFO - Epoch(val) [74][ 60/102] eta: 0:00:05 time: 0.1102 data_time: 0.0069 memory: 1697 09/30 15:18:39 - mmengine - INFO - Epoch(val) [74][ 65/102] eta: 0:00:04 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 15:18:39 - mmengine - INFO - Epoch(val) [74][ 70/102] eta: 0:00:03 time: 0.1105 data_time: 0.0074 memory: 1697 09/30 15:18:40 - mmengine - INFO - Epoch(val) [74][ 75/102] eta: 0:00:03 time: 0.1105 data_time: 0.0073 memory: 1697 09/30 15:18:40 - mmengine - INFO - Epoch(val) [74][ 80/102] eta: 0:00:02 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 15:18:41 - mmengine - INFO - Epoch(val) [74][ 85/102] eta: 0:00:01 time: 0.1106 data_time: 0.0073 memory: 1697 09/30 15:18:42 - mmengine - INFO - Epoch(val) [74][ 90/102] eta: 0:00:01 time: 0.1106 data_time: 0.0073 memory: 1697 09/30 15:18:42 - mmengine - INFO - Epoch(val) [74][ 95/102] eta: 0:00:00 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 15:18:43 - mmengine - INFO - Epoch(val) [74][100/102] eta: 0:00:00 time: 0.1102 data_time: 0.0073 memory: 1697 09/30 15:18:43 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:18:43 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:18:43 - mmengine - INFO - Epoch(val) [74][102/102] data_time: 0.0128 time: 0.1159 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:18:45 - mmengine - INFO - Epoch(train) [75][ 5/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:18 time: 0.2786 data_time: 0.0294 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:47 - mmengine - INFO - Epoch(train) [75][10/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:17 time: 0.2790 data_time: 0.0298 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:48 - mmengine - INFO - Epoch(train) [75][15/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:15 time: 0.2783 data_time: 0.0291 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:49 - mmengine - INFO - Epoch(train) [75][20/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:14 time: 0.2783 data_time: 0.0289 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:50 - mmengine - INFO - Epoch(train) [75][25/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:12 time: 0.2791 data_time: 0.0289 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:52 - mmengine - INFO - Epoch(train) [75][30/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:11 time: 0.2795 data_time: 0.0289 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:53 - mmengine - INFO - Epoch(train) [75][35/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:10 time: 0.2794 data_time: 0.0289 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:55 - mmengine - INFO - Epoch(train) [75][40/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:08 time: 0.2813 data_time: 0.0289 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:56 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:18:56 - mmengine - INFO - Epoch(train) [75][45/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:07 time: 0.2823 data_time: 0.0290 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:57 - mmengine - INFO - Epoch(train) [75][50/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:05 time: 0.2866 data_time: 0.0292 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:18:58 - mmengine - INFO - Epoch(train) [75][55/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:04 time: 0.2658 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:00 - mmengine - INFO - Epoch(train) [75][60/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:03 time: 0.2660 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:01 - mmengine - INFO - Epoch(train) [75][65/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:01 time: 0.2672 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:02 - mmengine - INFO - Epoch(train) [75][70/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:11:00 time: 0.2671 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:04 - mmengine - INFO - Epoch(train) [75][75/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:10:58 time: 0.2672 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:05 - mmengine - INFO - Epoch(train) [75][80/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:10:57 time: 0.2675 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:06 - mmengine - INFO - Epoch(train) [75][85/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:10:55 time: 0.2658 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:08 - mmengine - INFO - Epoch(train) [75][90/94] base_lr: 2.6781e-03 lr: 2.6781e-03 eta: 0:10:54 time: 0.2639 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:09 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:19:09 - mmengine - INFO - Saving checkpoint at 75 epochs 09/30 15:19:11 - mmengine - INFO - Epoch(val) [75][ 5/102] eta: 0:00:22 time: 0.1220 data_time: 0.0190 memory: 11783 09/30 15:19:12 - mmengine - INFO - Epoch(val) [75][ 10/102] eta: 0:00:15 time: 0.1218 data_time: 0.0188 memory: 1697 09/30 15:19:12 - mmengine - INFO - Epoch(val) [75][ 15/102] eta: 0:00:12 time: 0.1215 data_time: 0.0185 memory: 1697 09/30 15:19:13 - mmengine - INFO - Epoch(val) [75][ 20/102] eta: 0:00:11 time: 0.1216 data_time: 0.0185 memory: 1697 09/30 15:19:13 - mmengine - INFO - Epoch(val) [75][ 25/102] eta: 0:00:10 time: 0.1214 data_time: 0.0184 memory: 1697 09/30 15:19:14 - mmengine - INFO - Epoch(val) [75][ 30/102] eta: 0:00:09 time: 0.1217 data_time: 0.0186 memory: 1697 09/30 15:19:15 - mmengine - INFO - Epoch(val) [75][ 35/102] eta: 0:00:08 time: 0.1212 data_time: 0.0182 memory: 1697 09/30 15:19:15 - mmengine - INFO - Epoch(val) [75][ 40/102] eta: 0:00:07 time: 0.1214 data_time: 0.0183 memory: 1697 09/30 15:19:16 - mmengine - INFO - Epoch(val) [75][ 45/102] eta: 0:00:07 time: 0.1217 data_time: 0.0183 memory: 1697 09/30 15:19:16 - mmengine - INFO - Epoch(val) [75][ 50/102] eta: 0:00:06 time: 0.1218 data_time: 0.0183 memory: 1697 09/30 15:19:17 - mmengine - INFO - Epoch(val) [75][ 55/102] eta: 0:00:05 time: 0.1100 data_time: 0.0066 memory: 1697 09/30 15:19:17 - mmengine - INFO - Epoch(val) [75][ 60/102] eta: 0:00:05 time: 0.1104 data_time: 0.0069 memory: 1697 09/30 15:19:18 - mmengine - INFO - Epoch(val) [75][ 65/102] eta: 0:00:04 time: 0.1106 data_time: 0.0072 memory: 1697 09/30 15:19:18 - mmengine - INFO - Epoch(val) [75][ 70/102] eta: 0:00:03 time: 0.1105 data_time: 0.0072 memory: 1697 09/30 15:19:19 - mmengine - INFO - Epoch(val) [75][ 75/102] eta: 0:00:03 time: 0.1105 data_time: 0.0073 memory: 1697 09/30 15:19:19 - mmengine - INFO - Epoch(val) [75][ 80/102] eta: 0:00:02 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 15:19:20 - mmengine - INFO - Epoch(val) [75][ 85/102] eta: 0:00:01 time: 0.1106 data_time: 0.0073 memory: 1697 09/30 15:19:21 - mmengine - INFO - Epoch(val) [75][ 90/102] eta: 0:00:01 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 15:19:21 - mmengine - INFO - Epoch(val) [75][ 95/102] eta: 0:00:00 time: 0.1103 data_time: 0.0074 memory: 1697 09/30 15:19:22 - mmengine - INFO - Epoch(val) [75][100/102] eta: 0:00:00 time: 0.1101 data_time: 0.0073 memory: 1697 09/30 15:19:22 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:19:22 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:19:22 - mmengine - INFO - Epoch(val) [75][102/102] data_time: 0.0127 time: 0.1159 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:19:24 - mmengine - INFO - Epoch(train) [76][ 5/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:52 time: 0.2797 data_time: 0.0292 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:26 - mmengine - INFO - Epoch(train) [76][10/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:50 time: 0.2800 data_time: 0.0293 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:27 - mmengine - INFO - Epoch(train) [76][15/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:49 time: 0.2801 data_time: 0.0294 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:28 - mmengine - INFO - Epoch(train) [76][20/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:48 time: 0.2794 data_time: 0.0293 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:30 - mmengine - INFO - Epoch(train) [76][25/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:46 time: 0.2788 data_time: 0.0286 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:31 - mmengine - INFO - Epoch(train) [76][30/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:45 time: 0.2784 data_time: 0.0286 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:32 - mmengine - INFO - Epoch(train) [76][35/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:43 time: 0.2783 data_time: 0.0285 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:34 - mmengine - INFO - Epoch(train) [76][40/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:42 time: 0.2791 data_time: 0.0284 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:35 - mmengine - INFO - Epoch(train) [76][45/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:40 time: 0.2806 data_time: 0.0287 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:36 - mmengine - INFO - Epoch(train) [76][50/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:39 time: 0.2849 data_time: 0.0289 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:37 - mmengine - INFO - Epoch(train) [76][55/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:38 time: 0.2653 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:39 - mmengine - INFO - Epoch(train) [76][60/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:36 time: 0.2655 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:40 - mmengine - INFO - Epoch(train) [76][65/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:35 time: 0.2646 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:41 - mmengine - INFO - Epoch(train) [76][70/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:33 time: 0.2648 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:43 - mmengine - INFO - Epoch(train) [76][75/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:32 time: 0.2656 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:44 - mmengine - INFO - Epoch(train) [76][80/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:31 time: 0.2653 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:45 - mmengine - INFO - Epoch(train) [76][85/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:29 time: 0.2634 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:47 - mmengine - INFO - Epoch(train) [76][90/94] base_lr: 2.5750e-03 lr: 2.5750e-03 eta: 0:10:28 time: 0.2623 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:19:47 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:19:47 - mmengine - INFO - Saving checkpoint at 76 epochs 09/30 15:19:50 - mmengine - INFO - Epoch(val) [76][ 5/102] eta: 0:00:25 time: 0.1257 data_time: 0.0225 memory: 11783 09/30 15:19:51 - mmengine - INFO - Epoch(val) [76][ 10/102] eta: 0:00:17 time: 0.1255 data_time: 0.0223 memory: 1697 09/30 15:19:51 - mmengine - INFO - Epoch(val) [76][ 15/102] eta: 0:00:14 time: 0.1254 data_time: 0.0220 memory: 1697 09/30 15:19:52 - mmengine - INFO - Epoch(val) [76][ 20/102] eta: 0:00:12 time: 0.1255 data_time: 0.0220 memory: 1697 09/30 15:19:53 - mmengine - INFO - Epoch(val) [76][ 25/102] eta: 0:00:10 time: 0.1253 data_time: 0.0219 memory: 1697 09/30 15:19:53 - mmengine - INFO - Epoch(val) [76][ 30/102] eta: 0:00:09 time: 0.1255 data_time: 0.0220 memory: 1697 09/30 15:19:54 - mmengine - INFO - Epoch(val) [76][ 35/102] eta: 0:00:08 time: 0.1253 data_time: 0.0217 memory: 1697 09/30 15:19:54 - mmengine - INFO - Epoch(val) [76][ 40/102] eta: 0:00:08 time: 0.1256 data_time: 0.0219 memory: 1697 09/30 15:19:55 - mmengine - INFO - Epoch(val) [76][ 45/102] eta: 0:00:07 time: 0.1253 data_time: 0.0219 memory: 1697 09/30 15:19:55 - mmengine - INFO - Epoch(val) [76][ 50/102] eta: 0:00:06 time: 0.1253 data_time: 0.0218 memory: 1697 09/30 15:19:56 - mmengine - INFO - Epoch(val) [76][ 55/102] eta: 0:00:05 time: 0.1099 data_time: 0.0067 memory: 1697 09/30 15:19:56 - mmengine - INFO - Epoch(val) [76][ 60/102] eta: 0:00:05 time: 0.1100 data_time: 0.0069 memory: 1697 09/30 15:19:57 - mmengine - INFO - Epoch(val) [76][ 65/102] eta: 0:00:04 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 15:19:58 - mmengine - INFO - Epoch(val) [76][ 70/102] eta: 0:00:03 time: 0.1103 data_time: 0.0073 memory: 1697 09/30 15:19:58 - mmengine - INFO - Epoch(val) [76][ 75/102] eta: 0:00:03 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:19:59 - mmengine - INFO - Epoch(val) [76][ 80/102] eta: 0:00:02 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 15:19:59 - mmengine - INFO - Epoch(val) [76][ 85/102] eta: 0:00:02 time: 0.1106 data_time: 0.0074 memory: 1697 09/30 15:20:00 - mmengine - INFO - Epoch(val) [76][ 90/102] eta: 0:00:01 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:20:00 - mmengine - INFO - Epoch(val) [76][ 95/102] eta: 0:00:00 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 15:20:01 - mmengine - INFO - Epoch(val) [76][100/102] eta: 0:00:00 time: 0.1110 data_time: 0.0074 memory: 1697 09/30 15:20:01 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:20:01 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:20:01 - mmengine - INFO - Epoch(val) [76][102/102] data_time: 0.0144 time: 0.1178 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:20:04 - mmengine - INFO - Epoch(train) [77][ 5/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:26 time: 0.2876 data_time: 0.0391 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:05 - mmengine - INFO - Epoch(train) [77][10/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:24 time: 0.2875 data_time: 0.0397 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:06 - mmengine - INFO - Epoch(train) [77][15/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:23 time: 0.2866 data_time: 0.0391 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:08 - mmengine - INFO - Epoch(train) [77][20/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:21 time: 0.2867 data_time: 0.0391 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:09 - mmengine - INFO - Epoch(train) [77][25/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:20 time: 0.2869 data_time: 0.0390 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:10 - mmengine - INFO - Epoch(train) [77][30/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:19 time: 0.2871 data_time: 0.0387 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:12 - mmengine - INFO - Epoch(train) [77][35/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:17 time: 0.2878 data_time: 0.0388 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:13 - mmengine - INFO - Epoch(train) [77][40/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:16 time: 0.2893 data_time: 0.0388 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:14 - mmengine - INFO - Epoch(train) [77][45/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:14 time: 0.2901 data_time: 0.0389 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:16 - mmengine - INFO - Epoch(train) [77][50/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:13 time: 0.2944 data_time: 0.0390 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:17 - mmengine - INFO - Epoch(train) [77][55/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:11 time: 0.2653 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:18 - mmengine - INFO - Epoch(train) [77][60/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:10 time: 0.2645 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:20 - mmengine - INFO - Epoch(train) [77][65/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:09 time: 0.2656 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:21 - mmengine - INFO - Epoch(train) [77][70/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:07 time: 0.2651 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:22 - mmengine - INFO - Epoch(train) [77][75/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:06 time: 0.2647 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:24 - mmengine - INFO - Epoch(train) [77][80/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:04 time: 0.2643 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:25 - mmengine - INFO - Epoch(train) [77][85/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:03 time: 0.2627 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:26 - mmengine - INFO - Epoch(train) [77][90/94] base_lr: 2.4719e-03 lr: 2.4719e-03 eta: 0:10:02 time: 0.2611 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:27 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:20:27 - mmengine - INFO - Saving checkpoint at 77 epochs 09/30 15:20:30 - mmengine - INFO - Epoch(val) [77][ 5/102] eta: 0:00:25 time: 0.1255 data_time: 0.0222 memory: 11783 09/30 15:20:31 - mmengine - INFO - Epoch(val) [77][ 10/102] eta: 0:00:16 time: 0.1253 data_time: 0.0220 memory: 1697 09/30 15:20:31 - mmengine - INFO - Epoch(val) [77][ 15/102] eta: 0:00:13 time: 0.1249 data_time: 0.0216 memory: 1697 09/30 15:20:32 - mmengine - INFO - Epoch(val) [77][ 20/102] eta: 0:00:12 time: 0.1250 data_time: 0.0215 memory: 1697 09/30 15:20:33 - mmengine - INFO - Epoch(val) [77][ 25/102] eta: 0:00:10 time: 0.1247 data_time: 0.0215 memory: 1697 09/30 15:20:33 - mmengine - INFO - Epoch(val) [77][ 30/102] eta: 0:00:09 time: 0.1250 data_time: 0.0216 memory: 1697 09/30 15:20:34 - mmengine - INFO - Epoch(val) [77][ 35/102] eta: 0:00:08 time: 0.1248 data_time: 0.0214 memory: 1697 09/30 15:20:34 - mmengine - INFO - Epoch(val) [77][ 40/102] eta: 0:00:07 time: 0.1251 data_time: 0.0216 memory: 1697 09/30 15:20:35 - mmengine - INFO - Epoch(val) [77][ 45/102] eta: 0:00:07 time: 0.1253 data_time: 0.0216 memory: 1697 09/30 15:20:35 - mmengine - INFO - Epoch(val) [77][ 50/102] eta: 0:00:06 time: 0.1253 data_time: 0.0216 memory: 1697 09/30 15:20:36 - mmengine - INFO - Epoch(val) [77][ 55/102] eta: 0:00:05 time: 0.1105 data_time: 0.0068 memory: 1697 09/30 15:20:36 - mmengine - INFO - Epoch(val) [77][ 60/102] eta: 0:00:05 time: 0.1109 data_time: 0.0071 memory: 1697 09/30 15:20:37 - mmengine - INFO - Epoch(val) [77][ 65/102] eta: 0:00:04 time: 0.1114 data_time: 0.0075 memory: 1697 09/30 15:20:38 - mmengine - INFO - Epoch(val) [77][ 70/102] eta: 0:00:03 time: 0.1112 data_time: 0.0075 memory: 1697 09/30 15:20:38 - mmengine - INFO - Epoch(val) [77][ 75/102] eta: 0:00:03 time: 0.1114 data_time: 0.0076 memory: 1697 09/30 15:20:39 - mmengine - INFO - Epoch(val) [77][ 80/102] eta: 0:00:02 time: 0.1113 data_time: 0.0074 memory: 1697 09/30 15:20:39 - mmengine - INFO - Epoch(val) [77][ 85/102] eta: 0:00:02 time: 0.1114 data_time: 0.0075 memory: 1697 09/30 15:20:40 - mmengine - INFO - Epoch(val) [77][ 90/102] eta: 0:00:01 time: 0.1112 data_time: 0.0075 memory: 1697 09/30 15:20:40 - mmengine - INFO - Epoch(val) [77][ 95/102] eta: 0:00:00 time: 0.1110 data_time: 0.0075 memory: 1697 09/30 15:20:41 - mmengine - INFO - Epoch(val) [77][100/102] eta: 0:00:00 time: 0.1110 data_time: 0.0074 memory: 1697 09/30 15:20:41 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:20:41 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:20:41 - mmengine - INFO - Epoch(val) [77][102/102] data_time: 0.0143 time: 0.1178 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:20:43 - mmengine - INFO - Epoch(train) [78][ 5/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:59 time: 0.2746 data_time: 0.0268 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:45 - mmengine - INFO - Epoch(train) [78][10/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:58 time: 0.2740 data_time: 0.0268 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:46 - mmengine - INFO - Epoch(train) [78][15/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:56 time: 0.2747 data_time: 0.0268 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:47 - mmengine - INFO - Epoch(train) [78][20/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:55 time: 0.2746 data_time: 0.0264 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:49 - mmengine - INFO - Epoch(train) [78][25/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:54 time: 0.2748 data_time: 0.0263 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:50 - mmengine - INFO - Epoch(train) [78][30/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:52 time: 0.2751 data_time: 0.0264 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:51 - mmengine - INFO - Epoch(train) [78][35/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:51 time: 0.2749 data_time: 0.0264 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:53 - mmengine - INFO - Epoch(train) [78][40/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:49 time: 0.2762 data_time: 0.0264 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:54 - mmengine - INFO - Epoch(train) [78][45/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:48 time: 0.2777 data_time: 0.0265 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:55 - mmengine - INFO - Epoch(train) [78][50/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:47 time: 0.2819 data_time: 0.0267 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:57 - mmengine - INFO - Epoch(train) [78][55/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:45 time: 0.2651 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:58 - mmengine - INFO - Epoch(train) [78][60/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:44 time: 0.2657 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:20:59 - mmengine - INFO - Epoch(train) [78][65/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:42 time: 0.2657 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:00 - mmengine - INFO - Epoch(train) [78][70/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:41 time: 0.2658 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:02 - mmengine - INFO - Epoch(train) [78][75/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:40 time: 0.2652 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:03 - mmengine - INFO - Epoch(train) [78][80/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:38 time: 0.2649 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:04 - mmengine - INFO - Epoch(train) [78][85/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:37 time: 0.2637 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:06 - mmengine - INFO - Epoch(train) [78][90/94] base_lr: 2.3688e-03 lr: 2.3688e-03 eta: 0:09:35 time: 0.2621 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:06 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:21:06 - mmengine - INFO - Saving checkpoint at 78 epochs 09/30 15:21:09 - mmengine - INFO - Epoch(val) [78][ 5/102] eta: 0:00:25 time: 0.1257 data_time: 0.0224 memory: 11783 09/30 15:21:10 - mmengine - INFO - Epoch(val) [78][ 10/102] eta: 0:00:17 time: 0.1255 data_time: 0.0222 memory: 1697 09/30 15:21:10 - mmengine - INFO - Epoch(val) [78][ 15/102] eta: 0:00:13 time: 0.1250 data_time: 0.0218 memory: 1697 09/30 15:21:11 - mmengine - INFO - Epoch(val) [78][ 20/102] eta: 0:00:12 time: 0.1248 data_time: 0.0218 memory: 1697 09/30 15:21:11 - mmengine - INFO - Epoch(val) [78][ 25/102] eta: 0:00:10 time: 0.1250 data_time: 0.0216 memory: 1697 09/30 15:21:12 - mmengine - INFO - Epoch(val) [78][ 30/102] eta: 0:00:09 time: 0.1249 data_time: 0.0218 memory: 1697 09/30 15:21:13 - mmengine - INFO - Epoch(val) [78][ 35/102] eta: 0:00:08 time: 0.1247 data_time: 0.0215 memory: 1697 09/30 15:21:13 - mmengine - INFO - Epoch(val) [78][ 40/102] eta: 0:00:07 time: 0.1249 data_time: 0.0216 memory: 1697 09/30 15:21:14 - mmengine - INFO - Epoch(val) [78][ 45/102] eta: 0:00:07 time: 0.1250 data_time: 0.0217 memory: 1697 09/30 15:21:14 - mmengine - INFO - Epoch(val) [78][ 50/102] eta: 0:00:06 time: 0.1252 data_time: 0.0217 memory: 1697 09/30 15:21:15 - mmengine - INFO - Epoch(val) [78][ 55/102] eta: 0:00:05 time: 0.1101 data_time: 0.0066 memory: 1697 09/30 15:21:15 - mmengine - INFO - Epoch(val) [78][ 60/102] eta: 0:00:05 time: 0.1102 data_time: 0.0069 memory: 1697 09/30 15:21:16 - mmengine - INFO - Epoch(val) [78][ 65/102] eta: 0:00:04 time: 0.1106 data_time: 0.0072 memory: 1697 09/30 15:21:16 - mmengine - INFO - Epoch(val) [78][ 70/102] eta: 0:00:03 time: 0.1107 data_time: 0.0073 memory: 1697 09/30 15:21:17 - mmengine - INFO - Epoch(val) [78][ 75/102] eta: 0:00:03 time: 0.1106 data_time: 0.0074 memory: 1697 09/30 15:21:18 - mmengine - INFO - Epoch(val) [78][ 80/102] eta: 0:00:02 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 15:21:18 - mmengine - INFO - Epoch(val) [78][ 85/102] eta: 0:00:02 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 15:21:19 - mmengine - INFO - Epoch(val) [78][ 90/102] eta: 0:00:01 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 15:21:19 - mmengine - INFO - Epoch(val) [78][ 95/102] eta: 0:00:00 time: 0.1109 data_time: 0.0076 memory: 1697 09/30 15:21:20 - mmengine - INFO - Epoch(val) [78][100/102] eta: 0:00:00 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:21:20 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:21:20 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:21:20 - mmengine - INFO - Epoch(val) [78][102/102] data_time: 0.0144 time: 0.1178 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:21:23 - mmengine - INFO - Epoch(train) [79][ 5/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:33 time: 0.2833 data_time: 0.0332 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:24 - mmengine - INFO - Epoch(train) [79][10/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:32 time: 0.2834 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:25 - mmengine - INFO - Epoch(train) [79][15/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:30 time: 0.2825 data_time: 0.0335 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:27 - mmengine - INFO - Epoch(train) [79][20/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:29 time: 0.2824 data_time: 0.0333 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:28 - mmengine - INFO - Epoch(train) [79][25/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:27 time: 0.2829 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:29 - mmengine - INFO - Epoch(train) [79][30/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:26 time: 0.2823 data_time: 0.0333 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:31 - mmengine - INFO - Epoch(train) [79][35/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:25 time: 0.2823 data_time: 0.0333 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:32 - mmengine - INFO - Epoch(train) [79][40/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:23 time: 0.2841 data_time: 0.0333 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:33 - mmengine - INFO - Epoch(train) [79][45/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:22 time: 0.2856 data_time: 0.0334 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:35 - mmengine - INFO - Epoch(train) [79][50/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:20 time: 0.2901 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:36 - mmengine - INFO - Epoch(train) [79][55/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:19 time: 0.2646 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:37 - mmengine - INFO - Epoch(train) [79][60/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:18 time: 0.2647 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:38 - mmengine - INFO - Epoch(train) [79][65/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:16 time: 0.2650 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:40 - mmengine - INFO - Epoch(train) [79][70/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:15 time: 0.2657 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:41 - mmengine - INFO - Epoch(train) [79][75/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:13 time: 0.2648 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:42 - mmengine - INFO - Epoch(train) [79][80/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:12 time: 0.2655 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:44 - mmengine - INFO - Epoch(train) [79][85/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:10 time: 0.2651 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:45 - mmengine - INFO - Epoch(train) [79][90/94] base_lr: 2.2656e-03 lr: 2.2656e-03 eta: 0:09:09 time: 0.2632 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:21:46 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:21:46 - mmengine - INFO - Saving checkpoint at 79 epochs 09/30 15:21:49 - mmengine - INFO - Epoch(val) [79][ 5/102] eta: 0:00:25 time: 0.1266 data_time: 0.0231 memory: 11783 09/30 15:21:50 - mmengine - INFO - Epoch(val) [79][ 10/102] eta: 0:00:17 time: 0.1265 data_time: 0.0229 memory: 1697 09/30 15:21:51 - mmengine - INFO - Epoch(val) [79][ 15/102] eta: 0:00:14 time: 0.1265 data_time: 0.0227 memory: 1697 09/30 15:21:51 - mmengine - INFO - Epoch(val) [79][ 20/102] eta: 0:00:12 time: 0.1266 data_time: 0.0226 memory: 1697 09/30 15:21:52 - mmengine - INFO - Epoch(val) [79][ 25/102] eta: 0:00:10 time: 0.1268 data_time: 0.0225 memory: 1697 09/30 15:21:52 - mmengine - INFO - Epoch(val) [79][ 30/102] eta: 0:00:09 time: 0.1270 data_time: 0.0226 memory: 1697 09/30 15:21:53 - mmengine - INFO - Epoch(val) [79][ 35/102] eta: 0:00:08 time: 0.1266 data_time: 0.0224 memory: 1697 09/30 15:21:53 - mmengine - INFO - Epoch(val) [79][ 40/102] eta: 0:00:08 time: 0.1267 data_time: 0.0225 memory: 1697 09/30 15:21:54 - mmengine - INFO - Epoch(val) [79][ 45/102] eta: 0:00:07 time: 0.1268 data_time: 0.0225 memory: 1697 09/30 15:21:54 - mmengine - INFO - Epoch(val) [79][ 50/102] eta: 0:00:06 time: 0.1268 data_time: 0.0225 memory: 1697 09/30 15:21:55 - mmengine - INFO - Epoch(val) [79][ 55/102] eta: 0:00:05 time: 0.1111 data_time: 0.0069 memory: 1697 09/30 15:21:56 - mmengine - INFO - Epoch(val) [79][ 60/102] eta: 0:00:05 time: 0.1112 data_time: 0.0072 memory: 1697 09/30 15:21:56 - mmengine - INFO - Epoch(val) [79][ 65/102] eta: 0:00:04 time: 0.1112 data_time: 0.0074 memory: 1697 09/30 15:21:57 - mmengine - INFO - Epoch(val) [79][ 70/102] eta: 0:00:03 time: 0.1112 data_time: 0.0075 memory: 1697 09/30 15:21:57 - mmengine - INFO - Epoch(val) [79][ 75/102] eta: 0:00:03 time: 0.1112 data_time: 0.0076 memory: 1697 09/30 15:21:58 - mmengine - INFO - Epoch(val) [79][ 80/102] eta: 0:00:02 time: 0.1110 data_time: 0.0075 memory: 1697 09/30 15:21:58 - mmengine - INFO - Epoch(val) [79][ 85/102] eta: 0:00:02 time: 0.1111 data_time: 0.0075 memory: 1697 09/30 15:21:59 - mmengine - INFO - Epoch(val) [79][ 90/102] eta: 0:00:01 time: 0.1108 data_time: 0.0075 memory: 1697 09/30 15:21:59 - mmengine - INFO - Epoch(val) [79][ 95/102] eta: 0:00:00 time: 0.1105 data_time: 0.0075 memory: 1697 09/30 15:22:00 - mmengine - INFO - Epoch(val) [79][100/102] eta: 0:00:00 time: 0.1102 data_time: 0.0074 memory: 1697 09/30 15:22:00 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:22:00 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:22:00 - mmengine - INFO - Epoch(val) [79][102/102] data_time: 0.0147 time: 0.1183 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:22:02 - mmengine - INFO - Epoch(train) [80][ 5/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:09:07 time: 0.2773 data_time: 0.0276 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:04 - mmengine - INFO - Epoch(train) [80][10/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:09:05 time: 0.2774 data_time: 0.0277 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:05 - mmengine - INFO - Epoch(train) [80][15/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:09:04 time: 0.2762 data_time: 0.0275 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:06 - mmengine - INFO - Epoch(train) [80][20/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:09:02 time: 0.2772 data_time: 0.0276 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:08 - mmengine - INFO - Epoch(train) [80][25/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:09:01 time: 0.2760 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:09 - mmengine - INFO - Epoch(train) [80][30/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:09:00 time: 0.2759 data_time: 0.0268 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:10 - mmengine - INFO - Epoch(train) [80][35/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:58 time: 0.2756 data_time: 0.0269 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:12 - mmengine - INFO - Epoch(train) [80][40/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:57 time: 0.2779 data_time: 0.0269 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:13 - mmengine - INFO - Epoch(train) [80][45/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:55 time: 0.2800 data_time: 0.0269 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:14 - mmengine - INFO - Epoch(train) [80][50/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:54 time: 0.2835 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:16 - mmengine - INFO - Epoch(train) [80][55/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:53 time: 0.2658 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:17 - mmengine - INFO - Epoch(train) [80][60/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:51 time: 0.2660 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:18 - mmengine - INFO - Epoch(train) [80][65/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:50 time: 0.2672 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:20 - mmengine - INFO - Epoch(train) [80][70/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:48 time: 0.2672 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:21 - mmengine - INFO - Epoch(train) [80][75/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:47 time: 0.2676 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:22 - mmengine - INFO - Epoch(train) [80][80/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:46 time: 0.2674 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:24 - mmengine - INFO - Epoch(train) [80][85/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:44 time: 0.2661 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:25 - mmengine - INFO - Epoch(train) [80][90/94] base_lr: 2.1625e-03 lr: 2.1625e-03 eta: 0:08:43 time: 0.2637 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:26 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:22:26 - mmengine - INFO - Saving checkpoint at 80 epochs 09/30 15:22:28 - mmengine - INFO - Epoch(val) [80][ 5/102] eta: 0:00:25 time: 0.1258 data_time: 0.0231 memory: 11783 09/30 15:22:29 - mmengine - INFO - Epoch(val) [80][ 10/102] eta: 0:00:17 time: 0.1254 data_time: 0.0228 memory: 1697 09/30 15:22:29 - mmengine - INFO - Epoch(val) [80][ 15/102] eta: 0:00:13 time: 0.1253 data_time: 0.0225 memory: 1697 09/30 15:22:30 - mmengine - INFO - Epoch(val) [80][ 20/102] eta: 0:00:12 time: 0.1251 data_time: 0.0224 memory: 1697 09/30 15:22:31 - mmengine - INFO - Epoch(val) [80][ 25/102] eta: 0:00:10 time: 0.1250 data_time: 0.0223 memory: 1697 09/30 15:22:31 - mmengine - INFO - Epoch(val) [80][ 30/102] eta: 0:00:09 time: 0.1251 data_time: 0.0225 memory: 1697 09/30 15:22:32 - mmengine - INFO - Epoch(val) [80][ 35/102] eta: 0:00:08 time: 0.1251 data_time: 0.0222 memory: 1697 09/30 15:22:32 - mmengine - INFO - Epoch(val) [80][ 40/102] eta: 0:00:08 time: 0.1253 data_time: 0.0223 memory: 1697 09/30 15:22:33 - mmengine - INFO - Epoch(val) [80][ 45/102] eta: 0:00:07 time: 0.1256 data_time: 0.0223 memory: 1697 09/30 15:22:33 - mmengine - INFO - Epoch(val) [80][ 50/102] eta: 0:00:06 time: 0.1258 data_time: 0.0223 memory: 1697 09/30 15:22:34 - mmengine - INFO - Epoch(val) [80][ 55/102] eta: 0:00:05 time: 0.1100 data_time: 0.0066 memory: 1697 09/30 15:22:34 - mmengine - INFO - Epoch(val) [80][ 60/102] eta: 0:00:05 time: 0.1103 data_time: 0.0068 memory: 1697 09/30 15:22:35 - mmengine - INFO - Epoch(val) [80][ 65/102] eta: 0:00:04 time: 0.1106 data_time: 0.0071 memory: 1697 09/30 15:22:36 - mmengine - INFO - Epoch(val) [80][ 70/102] eta: 0:00:03 time: 0.1104 data_time: 0.0070 memory: 1697 09/30 15:22:36 - mmengine - INFO - Epoch(val) [80][ 75/102] eta: 0:00:03 time: 0.1106 data_time: 0.0071 memory: 1697 09/30 15:22:37 - mmengine - INFO - Epoch(val) [80][ 80/102] eta: 0:00:02 time: 0.1103 data_time: 0.0069 memory: 1697 09/30 15:22:37 - mmengine - INFO - Epoch(val) [80][ 85/102] eta: 0:00:02 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 15:22:38 - mmengine - INFO - Epoch(val) [80][ 90/102] eta: 0:00:01 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 15:22:38 - mmengine - INFO - Epoch(val) [80][ 95/102] eta: 0:00:00 time: 0.1100 data_time: 0.0071 memory: 1697 09/30 15:22:39 - mmengine - INFO - Epoch(val) [80][100/102] eta: 0:00:00 time: 0.1098 data_time: 0.0070 memory: 1697 09/30 15:22:39 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:22:39 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:22:39 - mmengine - INFO - Epoch(val) [80][102/102] data_time: 0.0144 time: 0.1175 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:22:41 - mmengine - INFO - Epoch(train) [81][ 5/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:40 time: 0.2801 data_time: 0.0299 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:43 - mmengine - INFO - Epoch(train) [81][10/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:39 time: 0.2794 data_time: 0.0302 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:44 - mmengine - INFO - Epoch(train) [81][15/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:38 time: 0.2792 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:45 - mmengine - INFO - Epoch(train) [81][20/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:36 time: 0.2787 data_time: 0.0297 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:47 - mmengine - INFO - Epoch(train) [81][25/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:35 time: 0.2777 data_time: 0.0298 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:48 - mmengine - INFO - Epoch(train) [81][30/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:33 time: 0.2777 data_time: 0.0295 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:49 - mmengine - INFO - Epoch(train) [81][35/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:32 time: 0.2787 data_time: 0.0295 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:51 - mmengine - INFO - Epoch(train) [81][40/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:31 time: 0.2798 data_time: 0.0296 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:52 - mmengine - INFO - Epoch(train) [81][45/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:29 time: 0.2809 data_time: 0.0296 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:53 - mmengine - INFO - Epoch(train) [81][50/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:28 time: 0.2850 data_time: 0.0297 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:55 - mmengine - INFO - Epoch(train) [81][55/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:26 time: 0.2641 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:56 - mmengine - INFO - Epoch(train) [81][60/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:25 time: 0.2648 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:58 - mmengine - INFO - Epoch(train) [81][65/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:24 time: 0.2699 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:22:59 - mmengine - INFO - Epoch(train) [81][70/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:22 time: 0.2707 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:00 - mmengine - INFO - Epoch(train) [81][75/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:21 time: 0.2715 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:02 - mmengine - INFO - Epoch(train) [81][80/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:19 time: 0.2713 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:03 - mmengine - INFO - Epoch(train) [81][85/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:18 time: 0.2697 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:04 - mmengine - INFO - Epoch(train) [81][90/94] base_lr: 2.0594e-03 lr: 2.0594e-03 eta: 0:08:17 time: 0.2687 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:05 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:23:05 - mmengine - INFO - Saving checkpoint at 81 epochs 09/30 15:23:08 - mmengine - INFO - Epoch(val) [81][ 5/102] eta: 0:00:23 time: 0.1230 data_time: 0.0198 memory: 11783 09/30 15:23:08 - mmengine - INFO - Epoch(val) [81][ 10/102] eta: 0:00:16 time: 0.1232 data_time: 0.0197 memory: 1697 09/30 15:23:09 - mmengine - INFO - Epoch(val) [81][ 15/102] eta: 0:00:13 time: 0.1230 data_time: 0.0195 memory: 1697 09/30 15:23:09 - mmengine - INFO - Epoch(val) [81][ 20/102] eta: 0:00:11 time: 0.1232 data_time: 0.0196 memory: 1697 09/30 15:23:10 - mmengine - INFO - Epoch(val) [81][ 25/102] eta: 0:00:10 time: 0.1234 data_time: 0.0195 memory: 1697 09/30 15:23:10 - mmengine - INFO - Epoch(val) [81][ 30/102] eta: 0:00:09 time: 0.1239 data_time: 0.0198 memory: 1697 09/30 15:23:11 - mmengine - INFO - Epoch(val) [81][ 35/102] eta: 0:00:08 time: 0.1237 data_time: 0.0195 memory: 1697 09/30 15:23:11 - mmengine - INFO - Epoch(val) [81][ 40/102] eta: 0:00:07 time: 0.1242 data_time: 0.0197 memory: 1697 09/30 15:23:12 - mmengine - INFO - Epoch(val) [81][ 45/102] eta: 0:00:07 time: 0.1246 data_time: 0.0199 memory: 1697 09/30 15:23:13 - mmengine - INFO - Epoch(val) [81][ 50/102] eta: 0:00:06 time: 0.1249 data_time: 0.0199 memory: 1697 09/30 15:23:13 - mmengine - INFO - Epoch(val) [81][ 55/102] eta: 0:00:05 time: 0.1118 data_time: 0.0072 memory: 1697 09/30 15:23:14 - mmengine - INFO - Epoch(val) [81][ 60/102] eta: 0:00:05 time: 0.1117 data_time: 0.0074 memory: 1697 09/30 15:23:14 - mmengine - INFO - Epoch(val) [81][ 65/102] eta: 0:00:04 time: 0.1119 data_time: 0.0077 memory: 1697 09/30 15:23:15 - mmengine - INFO - Epoch(val) [81][ 70/102] eta: 0:00:03 time: 0.1119 data_time: 0.0077 memory: 1697 09/30 15:23:15 - mmengine - INFO - Epoch(val) [81][ 75/102] eta: 0:00:03 time: 0.1120 data_time: 0.0079 memory: 1697 09/30 15:23:16 - mmengine - INFO - Epoch(val) [81][ 80/102] eta: 0:00:02 time: 0.1117 data_time: 0.0077 memory: 1697 09/30 15:23:16 - mmengine - INFO - Epoch(val) [81][ 85/102] eta: 0:00:02 time: 0.1122 data_time: 0.0080 memory: 1697 09/30 15:23:17 - mmengine - INFO - Epoch(val) [81][ 90/102] eta: 0:00:01 time: 0.1119 data_time: 0.0079 memory: 1697 09/30 15:23:18 - mmengine - INFO - Epoch(val) [81][ 95/102] eta: 0:00:00 time: 0.1118 data_time: 0.0079 memory: 1697 09/30 15:23:18 - mmengine - INFO - Epoch(val) [81][100/102] eta: 0:00:00 time: 0.1116 data_time: 0.0078 memory: 1697 09/30 15:23:18 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:23:18 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:23:18 - mmengine - INFO - Epoch(val) [81][102/102] data_time: 0.0137 time: 0.1180 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:23:21 - mmengine - INFO - Epoch(train) [82][ 5/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:14 time: 0.2940 data_time: 0.0389 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:23 - mmengine - INFO - Epoch(train) [82][10/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:13 time: 0.2954 data_time: 0.0393 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:24 - mmengine - INFO - Epoch(train) [82][15/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:12 time: 0.2940 data_time: 0.0385 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:25 - mmengine - INFO - Epoch(train) [82][20/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:10 time: 0.2890 data_time: 0.0385 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:26 - mmengine - INFO - Epoch(train) [82][25/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:09 time: 0.2886 data_time: 0.0386 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:28 - mmengine - INFO - Epoch(train) [82][30/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:07 time: 0.2878 data_time: 0.0385 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:29 - mmengine - INFO - Epoch(train) [82][35/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:06 time: 0.2881 data_time: 0.0385 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:30 - mmengine - INFO - Epoch(train) [82][40/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:05 time: 0.2893 data_time: 0.0385 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:32 - mmengine - INFO - Epoch(train) [82][45/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:03 time: 0.2909 data_time: 0.0385 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:33 - mmengine - INFO - Epoch(train) [82][50/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:02 time: 0.2945 data_time: 0.0386 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:34 - mmengine - INFO - Epoch(train) [82][55/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:08:00 time: 0.2657 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:36 - mmengine - INFO - Epoch(train) [82][60/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:07:59 time: 0.2655 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:37 - mmengine - INFO - Epoch(train) [82][65/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:07:58 time: 0.2664 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:38 - mmengine - INFO - Epoch(train) [82][70/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:07:56 time: 0.2665 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:40 - mmengine - INFO - Epoch(train) [82][75/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:07:55 time: 0.2667 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:41 - mmengine - INFO - Epoch(train) [82][80/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:07:53 time: 0.2673 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:42 - mmengine - INFO - Epoch(train) [82][85/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:07:52 time: 0.2661 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:44 - mmengine - INFO - Epoch(train) [82][90/94] base_lr: 1.9563e-03 lr: 1.9563e-03 eta: 0:07:51 time: 0.2650 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:23:45 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:23:45 - mmengine - INFO - Saving checkpoint at 82 epochs 09/30 15:23:47 - mmengine - INFO - Epoch(val) [82][ 5/102] eta: 0:00:26 time: 0.1281 data_time: 0.0241 memory: 11783 09/30 15:23:48 - mmengine - INFO - Epoch(val) [82][ 10/102] eta: 0:00:17 time: 0.1278 data_time: 0.0238 memory: 1697 09/30 15:23:49 - mmengine - INFO - Epoch(val) [82][ 15/102] eta: 0:00:14 time: 0.1278 data_time: 0.0234 memory: 1697 09/30 15:23:49 - mmengine - INFO - Epoch(val) [82][ 20/102] eta: 0:00:12 time: 0.1277 data_time: 0.0233 memory: 1697 09/30 15:23:50 - mmengine - INFO - Epoch(val) [82][ 25/102] eta: 0:00:11 time: 0.1277 data_time: 0.0232 memory: 1697 09/30 15:23:50 - mmengine - INFO - Epoch(val) [82][ 30/102] eta: 0:00:10 time: 0.1278 data_time: 0.0233 memory: 1697 09/30 15:23:51 - mmengine - INFO - Epoch(val) [82][ 35/102] eta: 0:00:09 time: 0.1274 data_time: 0.0231 memory: 1697 09/30 15:23:51 - mmengine - INFO - Epoch(val) [82][ 40/102] eta: 0:00:08 time: 0.1279 data_time: 0.0232 memory: 1697 09/30 15:23:52 - mmengine - INFO - Epoch(val) [82][ 45/102] eta: 0:00:07 time: 0.1283 data_time: 0.0234 memory: 1697 09/30 15:23:52 - mmengine - INFO - Epoch(val) [82][ 50/102] eta: 0:00:06 time: 0.1285 data_time: 0.0235 memory: 1697 09/30 15:23:53 - mmengine - INFO - Epoch(val) [82][ 55/102] eta: 0:00:05 time: 0.1122 data_time: 0.0072 memory: 1697 09/30 15:23:54 - mmengine - INFO - Epoch(val) [82][ 60/102] eta: 0:00:05 time: 0.1124 data_time: 0.0075 memory: 1697 09/30 15:23:54 - mmengine - INFO - Epoch(val) [82][ 65/102] eta: 0:00:04 time: 0.1128 data_time: 0.0080 memory: 1697 09/30 15:23:55 - mmengine - INFO - Epoch(val) [82][ 70/102] eta: 0:00:03 time: 0.1129 data_time: 0.0080 memory: 1697 09/30 15:23:55 - mmengine - INFO - Epoch(val) [82][ 75/102] eta: 0:00:03 time: 0.1131 data_time: 0.0082 memory: 1697 09/30 15:23:56 - mmengine - INFO - Epoch(val) [82][ 80/102] eta: 0:00:02 time: 0.1129 data_time: 0.0081 memory: 1697 09/30 15:23:56 - mmengine - INFO - Epoch(val) [82][ 85/102] eta: 0:00:02 time: 0.1132 data_time: 0.0082 memory: 1697 09/30 15:23:57 - mmengine - INFO - Epoch(val) [82][ 90/102] eta: 0:00:01 time: 0.1130 data_time: 0.0082 memory: 1697 09/30 15:23:58 - mmengine - INFO - Epoch(val) [82][ 95/102] eta: 0:00:00 time: 0.1130 data_time: 0.0083 memory: 1697 09/30 15:23:58 - mmengine - INFO - Epoch(val) [82][100/102] eta: 0:00:00 time: 0.1128 data_time: 0.0082 memory: 1697 09/30 15:23:58 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:23:58 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:23:58 - mmengine - INFO - Epoch(val) [82][102/102] data_time: 0.0156 time: 0.1205 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:24:02 - mmengine - INFO - Epoch(train) [83][ 5/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:48 time: 0.3005 data_time: 0.0484 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:03 - mmengine - INFO - Epoch(train) [83][10/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:47 time: 0.3004 data_time: 0.0488 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:04 - mmengine - INFO - Epoch(train) [83][15/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:46 time: 0.2984 data_time: 0.0482 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:06 - mmengine - INFO - Epoch(train) [83][20/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:44 time: 0.2988 data_time: 0.0480 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:07 - mmengine - INFO - Epoch(train) [83][25/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:43 time: 0.2986 data_time: 0.0480 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:08 - mmengine - INFO - Epoch(train) [83][30/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:41 time: 0.2986 data_time: 0.0480 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:10 - mmengine - INFO - Epoch(train) [83][35/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:40 time: 0.2983 data_time: 0.0476 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:11 - mmengine - INFO - Epoch(train) [83][40/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:39 time: 0.2998 data_time: 0.0478 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:12 - mmengine - INFO - Epoch(train) [83][45/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:37 time: 0.3007 data_time: 0.0479 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:14 - mmengine - INFO - Epoch(train) [83][50/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:36 time: 0.3050 data_time: 0.0481 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:15 - mmengine - INFO - Epoch(train) [83][55/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:34 time: 0.2657 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:16 - mmengine - INFO - Epoch(train) [83][60/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:33 time: 0.2660 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:18 - mmengine - INFO - Epoch(train) [83][65/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:32 time: 0.2673 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:19 - mmengine - INFO - Epoch(train) [83][70/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:30 time: 0.2673 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:20 - mmengine - INFO - Epoch(train) [83][75/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:29 time: 0.2681 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:22 - mmengine - INFO - Epoch(train) [83][80/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:27 time: 0.2678 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:23 - mmengine - INFO - Epoch(train) [83][85/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:26 time: 0.2667 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:24 - mmengine - INFO - Epoch(train) [83][90/94] base_lr: 1.8531e-03 lr: 1.8531e-03 eta: 0:07:25 time: 0.2653 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:25 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:24:25 - mmengine - INFO - Saving checkpoint at 83 epochs 09/30 15:24:28 - mmengine - INFO - Epoch(val) [83][ 5/102] eta: 0:00:26 time: 0.1291 data_time: 0.0243 memory: 11783 09/30 15:24:28 - mmengine - INFO - Epoch(val) [83][ 10/102] eta: 0:00:17 time: 0.1288 data_time: 0.0240 memory: 1697 09/30 15:24:29 - mmengine - INFO - Epoch(val) [83][ 15/102] eta: 0:00:14 time: 0.1283 data_time: 0.0236 memory: 1697 09/30 15:24:29 - mmengine - INFO - Epoch(val) [83][ 20/102] eta: 0:00:12 time: 0.1281 data_time: 0.0236 memory: 1697 09/30 15:24:30 - mmengine - INFO - Epoch(val) [83][ 25/102] eta: 0:00:11 time: 0.1279 data_time: 0.0236 memory: 1697 09/30 15:24:31 - mmengine - INFO - Epoch(val) [83][ 30/102] eta: 0:00:09 time: 0.1281 data_time: 0.0237 memory: 1697 09/30 15:24:31 - mmengine - INFO - Epoch(val) [83][ 35/102] eta: 0:00:08 time: 0.1276 data_time: 0.0233 memory: 1697 09/30 15:24:32 - mmengine - INFO - Epoch(val) [83][ 40/102] eta: 0:00:08 time: 0.1277 data_time: 0.0234 memory: 1697 09/30 15:24:32 - mmengine - INFO - Epoch(val) [83][ 45/102] eta: 0:00:07 time: 0.1278 data_time: 0.0234 memory: 1697 09/30 15:24:33 - mmengine - INFO - Epoch(val) [83][ 50/102] eta: 0:00:06 time: 0.1277 data_time: 0.0234 memory: 1697 09/30 15:24:33 - mmengine - INFO - Epoch(val) [83][ 55/102] eta: 0:00:05 time: 0.1113 data_time: 0.0074 memory: 1697 09/30 15:24:34 - mmengine - INFO - Epoch(val) [83][ 60/102] eta: 0:00:05 time: 0.1116 data_time: 0.0077 memory: 1697 09/30 15:24:35 - mmengine - INFO - Epoch(val) [83][ 65/102] eta: 0:00:04 time: 0.1119 data_time: 0.0081 memory: 1697 09/30 15:24:35 - mmengine - INFO - Epoch(val) [83][ 70/102] eta: 0:00:03 time: 0.1118 data_time: 0.0080 memory: 1697 09/30 15:24:36 - mmengine - INFO - Epoch(val) [83][ 75/102] eta: 0:00:03 time: 0.1121 data_time: 0.0081 memory: 1697 09/30 15:24:36 - mmengine - INFO - Epoch(val) [83][ 80/102] eta: 0:00:02 time: 0.1119 data_time: 0.0080 memory: 1697 09/30 15:24:37 - mmengine - INFO - Epoch(val) [83][ 85/102] eta: 0:00:02 time: 0.1123 data_time: 0.0083 memory: 1697 09/30 15:24:37 - mmengine - INFO - Epoch(val) [83][ 90/102] eta: 0:00:01 time: 0.1123 data_time: 0.0083 memory: 1697 09/30 15:24:38 - mmengine - INFO - Epoch(val) [83][ 95/102] eta: 0:00:00 time: 0.1124 data_time: 0.0084 memory: 1697 09/30 15:24:38 - mmengine - INFO - Epoch(val) [83][100/102] eta: 0:00:00 time: 0.1121 data_time: 0.0082 memory: 1697 09/30 15:24:39 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:24:39 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:24:39 - mmengine - INFO - Epoch(val) [83][102/102] data_time: 0.0156 time: 0.1197 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:24:41 - mmengine - INFO - Epoch(train) [84][ 5/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:22 time: 0.2842 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:43 - mmengine - INFO - Epoch(train) [84][10/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:21 time: 0.2845 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:44 - mmengine - INFO - Epoch(train) [84][15/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:19 time: 0.2838 data_time: 0.0268 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:45 - mmengine - INFO - Epoch(train) [84][20/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:18 time: 0.2848 data_time: 0.0272 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:46 - mmengine - INFO - Epoch(train) [84][25/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:17 time: 0.2839 data_time: 0.0266 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:48 - mmengine - INFO - Epoch(train) [84][30/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:15 time: 0.2830 data_time: 0.0267 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:49 - mmengine - INFO - Epoch(train) [84][35/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:14 time: 0.2829 data_time: 0.0265 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:50 - mmengine - INFO - Epoch(train) [84][40/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:12 time: 0.2843 data_time: 0.0265 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:52 - mmengine - INFO - Epoch(train) [84][45/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:11 time: 0.2858 data_time: 0.0264 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:53 - mmengine - INFO - Epoch(train) [84][50/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:10 time: 0.2895 data_time: 0.0267 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:54 - mmengine - INFO - Epoch(train) [84][55/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:08 time: 0.2666 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:56 - mmengine - INFO - Epoch(train) [84][60/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:07 time: 0.2664 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:57 - mmengine - INFO - Epoch(train) [84][65/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:05 time: 0.2666 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:24:58 - mmengine - INFO - Epoch(train) [84][70/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:04 time: 0.2658 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:00 - mmengine - INFO - Epoch(train) [84][75/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:03 time: 0.2666 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:01 - mmengine - INFO - Epoch(train) [84][80/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:01 time: 0.2663 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:02 - mmengine - INFO - Epoch(train) [84][85/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:07:00 time: 0.2653 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:04 - mmengine - INFO - Epoch(train) [84][90/94] base_lr: 1.7500e-03 lr: 1.7500e-03 eta: 0:06:58 time: 0.2639 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:05 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:25:05 - mmengine - INFO - Saving checkpoint at 84 epochs 09/30 15:25:07 - mmengine - INFO - Epoch(val) [84][ 5/102] eta: 0:00:25 time: 0.1272 data_time: 0.0231 memory: 11783 09/30 15:25:08 - mmengine - INFO - Epoch(val) [84][ 10/102] eta: 0:00:17 time: 0.1271 data_time: 0.0228 memory: 1697 09/30 15:25:08 - mmengine - INFO - Epoch(val) [84][ 15/102] eta: 0:00:14 time: 0.1269 data_time: 0.0225 memory: 1697 09/30 15:25:09 - mmengine - INFO - Epoch(val) [84][ 20/102] eta: 0:00:12 time: 0.1268 data_time: 0.0223 memory: 1697 09/30 15:25:09 - mmengine - INFO - Epoch(val) [84][ 25/102] eta: 0:00:10 time: 0.1265 data_time: 0.0222 memory: 1697 09/30 15:25:10 - mmengine - INFO - Epoch(val) [84][ 30/102] eta: 0:00:09 time: 0.1266 data_time: 0.0222 memory: 1697 09/30 15:25:11 - mmengine - INFO - Epoch(val) [84][ 35/102] eta: 0:00:08 time: 0.1264 data_time: 0.0220 memory: 1697 09/30 15:25:11 - mmengine - INFO - Epoch(val) [84][ 40/102] eta: 0:00:08 time: 0.1265 data_time: 0.0221 memory: 1697 09/30 15:25:12 - mmengine - INFO - Epoch(val) [84][ 45/102] eta: 0:00:07 time: 0.1267 data_time: 0.0221 memory: 1697 09/30 15:25:12 - mmengine - INFO - Epoch(val) [84][ 50/102] eta: 0:00:06 time: 0.1267 data_time: 0.0221 memory: 1697 09/30 15:25:13 - mmengine - INFO - Epoch(val) [84][ 55/102] eta: 0:00:05 time: 0.1114 data_time: 0.0071 memory: 1697 09/30 15:25:13 - mmengine - INFO - Epoch(val) [84][ 60/102] eta: 0:00:05 time: 0.1115 data_time: 0.0074 memory: 1697 09/30 15:25:14 - mmengine - INFO - Epoch(val) [84][ 65/102] eta: 0:00:04 time: 0.1118 data_time: 0.0077 memory: 1697 09/30 15:25:14 - mmengine - INFO - Epoch(val) [84][ 70/102] eta: 0:00:03 time: 0.1120 data_time: 0.0078 memory: 1697 09/30 15:25:15 - mmengine - INFO - Epoch(val) [84][ 75/102] eta: 0:00:03 time: 0.1121 data_time: 0.0079 memory: 1697 09/30 15:25:16 - mmengine - INFO - Epoch(val) [84][ 80/102] eta: 0:00:02 time: 0.1119 data_time: 0.0078 memory: 1697 09/30 15:25:16 - mmengine - INFO - Epoch(val) [84][ 85/102] eta: 0:00:02 time: 0.1118 data_time: 0.0079 memory: 1697 09/30 15:25:17 - mmengine - INFO - Epoch(val) [84][ 90/102] eta: 0:00:01 time: 0.1122 data_time: 0.0079 memory: 1697 09/30 15:25:17 - mmengine - INFO - Epoch(val) [84][ 95/102] eta: 0:00:00 time: 0.1122 data_time: 0.0080 memory: 1697 09/30 15:25:18 - mmengine - INFO - Epoch(val) [84][100/102] eta: 0:00:00 time: 0.1123 data_time: 0.0080 memory: 1697 09/30 15:25:18 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:25:18 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:25:18 - mmengine - INFO - Epoch(val) [84][102/102] data_time: 0.0148 time: 0.1193 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:25:21 - mmengine - INFO - Epoch(train) [85][ 5/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:56 time: 0.2864 data_time: 0.0355 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:22 - mmengine - INFO - Epoch(train) [85][10/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:55 time: 0.2869 data_time: 0.0356 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:23 - mmengine - INFO - Epoch(train) [85][15/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:53 time: 0.2875 data_time: 0.0354 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:25 - mmengine - INFO - Epoch(train) [85][20/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:52 time: 0.2868 data_time: 0.0349 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:26 - mmengine - INFO - Epoch(train) [85][25/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:51 time: 0.2871 data_time: 0.0350 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:27 - mmengine - INFO - Epoch(train) [85][30/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:49 time: 0.2872 data_time: 0.0349 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:29 - mmengine - INFO - Epoch(train) [85][35/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:48 time: 0.2870 data_time: 0.0349 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:30 - mmengine - INFO - Epoch(train) [85][40/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:46 time: 0.2887 data_time: 0.0349 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:31 - mmengine - INFO - Epoch(train) [85][45/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:45 time: 0.2904 data_time: 0.0350 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:33 - mmengine - INFO - Epoch(train) [85][50/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:44 time: 0.2939 data_time: 0.0350 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:34 - mmengine - INFO - Epoch(train) [85][55/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:42 time: 0.2678 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:35 - mmengine - INFO - Epoch(train) [85][60/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:41 time: 0.2676 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:37 - mmengine - INFO - Epoch(train) [85][65/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:39 time: 0.2672 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:38 - mmengine - INFO - Epoch(train) [85][70/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:38 time: 0.2677 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:39 - mmengine - INFO - Epoch(train) [85][75/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:37 time: 0.2669 data_time: 0.0104 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:41 - mmengine - INFO - Epoch(train) [85][80/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:35 time: 0.2666 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:42 - mmengine - INFO - Epoch(train) [85][85/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:34 time: 0.2657 data_time: 0.0106 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:43 - mmengine - INFO - Epoch(train) [85][90/94] base_lr: 1.6469e-03 lr: 1.6469e-03 eta: 0:06:32 time: 0.2641 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:25:44 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:25:44 - mmengine - INFO - Saving checkpoint at 85 epochs 09/30 15:25:47 - mmengine - INFO - Epoch(val) [85][ 5/102] eta: 0:00:25 time: 0.1273 data_time: 0.0227 memory: 11783 09/30 15:25:48 - mmengine - INFO - Epoch(val) [85][ 10/102] eta: 0:00:17 time: 0.1273 data_time: 0.0225 memory: 1697 09/30 15:25:48 - mmengine - INFO - Epoch(val) [85][ 15/102] eta: 0:00:13 time: 0.1269 data_time: 0.0221 memory: 1697 09/30 15:25:49 - mmengine - INFO - Epoch(val) [85][ 20/102] eta: 0:00:12 time: 0.1269 data_time: 0.0222 memory: 1697 09/30 15:25:49 - mmengine - INFO - Epoch(val) [85][ 25/102] eta: 0:00:10 time: 0.1269 data_time: 0.0221 memory: 1697 09/30 15:25:50 - mmengine - INFO - Epoch(val) [85][ 30/102] eta: 0:00:09 time: 0.1273 data_time: 0.0223 memory: 1697 09/30 15:25:50 - mmengine - INFO - Epoch(val) [85][ 35/102] eta: 0:00:08 time: 0.1269 data_time: 0.0220 memory: 1697 09/30 15:25:51 - mmengine - INFO - Epoch(val) [85][ 40/102] eta: 0:00:08 time: 0.1268 data_time: 0.0219 memory: 1697 09/30 15:25:51 - mmengine - INFO - Epoch(val) [85][ 45/102] eta: 0:00:07 time: 0.1272 data_time: 0.0221 memory: 1697 09/30 15:25:52 - mmengine - INFO - Epoch(val) [85][ 50/102] eta: 0:00:06 time: 0.1270 data_time: 0.0221 memory: 1697 09/30 15:25:53 - mmengine - INFO - Epoch(val) [85][ 55/102] eta: 0:00:05 time: 0.1122 data_time: 0.0074 memory: 1697 09/30 15:25:53 - mmengine - INFO - Epoch(val) [85][ 60/102] eta: 0:00:05 time: 0.1124 data_time: 0.0077 memory: 1697 09/30 15:25:54 - mmengine - INFO - Epoch(val) [85][ 65/102] eta: 0:00:04 time: 0.1126 data_time: 0.0081 memory: 1697 09/30 15:25:54 - mmengine - INFO - Epoch(val) [85][ 70/102] eta: 0:00:03 time: 0.1126 data_time: 0.0081 memory: 1697 09/30 15:25:55 - mmengine - INFO - Epoch(val) [85][ 75/102] eta: 0:00:03 time: 0.1128 data_time: 0.0082 memory: 1697 09/30 15:25:55 - mmengine - INFO - Epoch(val) [85][ 80/102] eta: 0:00:02 time: 0.1124 data_time: 0.0080 memory: 1697 09/30 15:25:56 - mmengine - INFO - Epoch(val) [85][ 85/102] eta: 0:00:02 time: 0.1128 data_time: 0.0082 memory: 1697 09/30 15:25:57 - mmengine - INFO - Epoch(val) [85][ 90/102] eta: 0:00:01 time: 0.1127 data_time: 0.0083 memory: 1697 09/30 15:25:57 - mmengine - INFO - Epoch(val) [85][ 95/102] eta: 0:00:00 time: 0.1125 data_time: 0.0084 memory: 1697 09/30 15:25:58 - mmengine - INFO - Epoch(val) [85][100/102] eta: 0:00:00 time: 0.1124 data_time: 0.0083 memory: 1697 09/30 15:25:58 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:25:58 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:25:58 - mmengine - INFO - Epoch(val) [85][102/102] data_time: 0.0150 time: 0.1195 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:26:01 - mmengine - INFO - Epoch(train) [86][ 5/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:30 time: 0.2918 data_time: 0.0418 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:02 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:26:02 - mmengine - INFO - Epoch(train) [86][10/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:29 time: 0.2916 data_time: 0.0419 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:03 - mmengine - INFO - Epoch(train) [86][15/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:27 time: 0.2910 data_time: 0.0413 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:05 - mmengine - INFO - Epoch(train) [86][20/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:26 time: 0.2906 data_time: 0.0411 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:06 - mmengine - INFO - Epoch(train) [86][25/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:24 time: 0.2906 data_time: 0.0411 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:07 - mmengine - INFO - Epoch(train) [86][30/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:23 time: 0.2910 data_time: 0.0409 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:09 - mmengine - INFO - Epoch(train) [86][35/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:22 time: 0.2913 data_time: 0.0407 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:10 - mmengine - INFO - Epoch(train) [86][40/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:20 time: 0.2923 data_time: 0.0407 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:11 - mmengine - INFO - Epoch(train) [86][45/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:19 time: 0.2933 data_time: 0.0407 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:13 - mmengine - INFO - Epoch(train) [86][50/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:17 time: 0.2968 data_time: 0.0408 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:14 - mmengine - INFO - Epoch(train) [86][55/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:16 time: 0.2649 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:15 - mmengine - INFO - Epoch(train) [86][60/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:15 time: 0.2662 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:17 - mmengine - INFO - Epoch(train) [86][65/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:13 time: 0.2668 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:18 - mmengine - INFO - Epoch(train) [86][70/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:12 time: 0.2665 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:19 - mmengine - INFO - Epoch(train) [86][75/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:10 time: 0.2662 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:21 - mmengine - INFO - Epoch(train) [86][80/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:09 time: 0.2661 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:22 - mmengine - INFO - Epoch(train) [86][85/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:08 time: 0.2642 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:23 - mmengine - INFO - Epoch(train) [86][90/94] base_lr: 1.5438e-03 lr: 1.5438e-03 eta: 0:06:06 time: 0.2626 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:24 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:26:24 - mmengine - INFO - Saving checkpoint at 86 epochs 09/30 15:26:27 - mmengine - INFO - Epoch(val) [86][ 5/102] eta: 0:00:25 time: 0.1279 data_time: 0.0237 memory: 11783 09/30 15:26:27 - mmengine - INFO - Epoch(val) [86][ 10/102] eta: 0:00:17 time: 0.1275 data_time: 0.0234 memory: 1697 09/30 15:26:28 - mmengine - INFO - Epoch(val) [86][ 15/102] eta: 0:00:14 time: 0.1272 data_time: 0.0231 memory: 1697 09/30 15:26:29 - mmengine - INFO - Epoch(val) [86][ 20/102] eta: 0:00:12 time: 0.1269 data_time: 0.0229 memory: 1697 09/30 15:26:29 - mmengine - INFO - Epoch(val) [86][ 25/102] eta: 0:00:10 time: 0.1267 data_time: 0.0227 memory: 1697 09/30 15:26:30 - mmengine - INFO - Epoch(val) [86][ 30/102] eta: 0:00:09 time: 0.1266 data_time: 0.0228 memory: 1697 09/30 15:26:30 - mmengine - INFO - Epoch(val) [86][ 35/102] eta: 0:00:08 time: 0.1261 data_time: 0.0224 memory: 1697 09/30 15:26:31 - mmengine - INFO - Epoch(val) [86][ 40/102] eta: 0:00:08 time: 0.1262 data_time: 0.0224 memory: 1697 09/30 15:26:31 - mmengine - INFO - Epoch(val) [86][ 45/102] eta: 0:00:07 time: 0.1261 data_time: 0.0223 memory: 1697 09/30 15:26:32 - mmengine - INFO - Epoch(val) [86][ 50/102] eta: 0:00:06 time: 0.1260 data_time: 0.0222 memory: 1697 09/30 15:26:32 - mmengine - INFO - Epoch(val) [86][ 55/102] eta: 0:00:05 time: 0.1106 data_time: 0.0067 memory: 1697 09/30 15:26:33 - mmengine - INFO - Epoch(val) [86][ 60/102] eta: 0:00:05 time: 0.1108 data_time: 0.0069 memory: 1697 09/30 15:26:34 - mmengine - INFO - Epoch(val) [86][ 65/102] eta: 0:00:04 time: 0.1109 data_time: 0.0071 memory: 1697 09/30 15:26:34 - mmengine - INFO - Epoch(val) [86][ 70/102] eta: 0:00:03 time: 0.1110 data_time: 0.0072 memory: 1697 09/30 15:26:35 - mmengine - INFO - Epoch(val) [86][ 75/102] eta: 0:00:03 time: 0.1111 data_time: 0.0073 memory: 1697 09/30 15:26:35 - mmengine - INFO - Epoch(val) [86][ 80/102] eta: 0:00:02 time: 0.1111 data_time: 0.0072 memory: 1697 09/30 15:26:36 - mmengine - INFO - Epoch(val) [86][ 85/102] eta: 0:00:02 time: 0.1113 data_time: 0.0074 memory: 1697 09/30 15:26:36 - mmengine - INFO - Epoch(val) [86][ 90/102] eta: 0:00:01 time: 0.1113 data_time: 0.0074 memory: 1697 09/30 15:26:37 - mmengine - INFO - Epoch(val) [86][ 95/102] eta: 0:00:00 time: 0.1112 data_time: 0.0075 memory: 1697 09/30 15:26:37 - mmengine - INFO - Epoch(val) [86][100/102] eta: 0:00:00 time: 0.1112 data_time: 0.0075 memory: 1697 09/30 15:26:38 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:26:38 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:26:38 - mmengine - INFO - Epoch(val) [86][102/102] data_time: 0.0146 time: 0.1184 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:26:40 - mmengine - INFO - Epoch(train) [87][ 5/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:06:04 time: 0.2845 data_time: 0.0349 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:42 - mmengine - INFO - Epoch(train) [87][10/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:06:02 time: 0.2839 data_time: 0.0345 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:43 - mmengine - INFO - Epoch(train) [87][15/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:06:01 time: 0.2827 data_time: 0.0345 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:44 - mmengine - INFO - Epoch(train) [87][20/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:06:00 time: 0.2825 data_time: 0.0347 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:46 - mmengine - INFO - Epoch(train) [87][25/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:58 time: 0.2816 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:47 - mmengine - INFO - Epoch(train) [87][30/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:57 time: 0.2828 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:48 - mmengine - INFO - Epoch(train) [87][35/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:55 time: 0.2824 data_time: 0.0340 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:50 - mmengine - INFO - Epoch(train) [87][40/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:54 time: 0.2830 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:51 - mmengine - INFO - Epoch(train) [87][45/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:53 time: 0.2849 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:52 - mmengine - INFO - Epoch(train) [87][50/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:51 time: 0.2896 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:54 - mmengine - INFO - Epoch(train) [87][55/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:50 time: 0.2640 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:55 - mmengine - INFO - Epoch(train) [87][60/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:48 time: 0.2646 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:56 - mmengine - INFO - Epoch(train) [87][65/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:47 time: 0.2653 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:58 - mmengine - INFO - Epoch(train) [87][70/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:46 time: 0.2657 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:26:59 - mmengine - INFO - Epoch(train) [87][75/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:44 time: 0.2665 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:00 - mmengine - INFO - Epoch(train) [87][80/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:43 time: 0.2657 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:01 - mmengine - INFO - Epoch(train) [87][85/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:41 time: 0.2651 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:03 - mmengine - INFO - Epoch(train) [87][90/94] base_lr: 1.4406e-03 lr: 1.4406e-03 eta: 0:05:40 time: 0.2641 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:04 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:27:04 - mmengine - INFO - Saving checkpoint at 87 epochs 09/30 15:27:08 - mmengine - INFO - Epoch(val) [87][ 5/102] eta: 0:00:26 time: 0.1268 data_time: 0.0233 memory: 11783 09/30 15:27:08 - mmengine - INFO - Epoch(val) [87][ 10/102] eta: 0:00:17 time: 0.1265 data_time: 0.0230 memory: 1697 09/30 15:27:09 - mmengine - INFO - Epoch(val) [87][ 15/102] eta: 0:00:14 time: 0.1264 data_time: 0.0227 memory: 1697 09/30 15:27:09 - mmengine - INFO - Epoch(val) [87][ 20/102] eta: 0:00:12 time: 0.1261 data_time: 0.0227 memory: 1697 09/30 15:27:10 - mmengine - INFO - Epoch(val) [87][ 25/102] eta: 0:00:10 time: 0.1259 data_time: 0.0226 memory: 1697 09/30 15:27:10 - mmengine - INFO - Epoch(val) [87][ 30/102] eta: 0:00:09 time: 0.1257 data_time: 0.0227 memory: 1697 09/30 15:27:11 - mmengine - INFO - Epoch(val) [87][ 35/102] eta: 0:00:08 time: 0.1256 data_time: 0.0224 memory: 1697 09/30 15:27:12 - mmengine - INFO - Epoch(val) [87][ 40/102] eta: 0:00:08 time: 0.1257 data_time: 0.0226 memory: 1697 09/30 15:27:12 - mmengine - INFO - Epoch(val) [87][ 45/102] eta: 0:00:07 time: 0.1257 data_time: 0.0225 memory: 1697 09/30 15:27:13 - mmengine - INFO - Epoch(val) [87][ 50/102] eta: 0:00:06 time: 0.1255 data_time: 0.0226 memory: 1697 09/30 15:27:13 - mmengine - INFO - Epoch(val) [87][ 55/102] eta: 0:00:05 time: 0.1097 data_time: 0.0068 memory: 1697 09/30 15:27:14 - mmengine - INFO - Epoch(val) [87][ 60/102] eta: 0:00:05 time: 0.1100 data_time: 0.0070 memory: 1697 09/30 15:27:14 - mmengine - INFO - Epoch(val) [87][ 65/102] eta: 0:00:04 time: 0.1104 data_time: 0.0074 memory: 1697 09/30 15:27:15 - mmengine - INFO - Epoch(val) [87][ 70/102] eta: 0:00:03 time: 0.1106 data_time: 0.0074 memory: 1697 09/30 15:27:15 - mmengine - INFO - Epoch(val) [87][ 75/102] eta: 0:00:03 time: 0.1108 data_time: 0.0076 memory: 1697 09/30 15:27:16 - mmengine - INFO - Epoch(val) [87][ 80/102] eta: 0:00:02 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 15:27:17 - mmengine - INFO - Epoch(val) [87][ 85/102] eta: 0:00:02 time: 0.1109 data_time: 0.0076 memory: 1697 09/30 15:27:17 - mmengine - INFO - Epoch(val) [87][ 90/102] eta: 0:00:01 time: 0.1108 data_time: 0.0076 memory: 1697 09/30 15:27:18 - mmengine - INFO - Epoch(val) [87][ 95/102] eta: 0:00:00 time: 0.1108 data_time: 0.0076 memory: 1697 09/30 15:27:18 - mmengine - INFO - Epoch(val) [87][100/102] eta: 0:00:00 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 15:27:18 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:27:18 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:27:18 - mmengine - INFO - Epoch(val) [87][102/102] data_time: 0.0148 time: 0.1180 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:27:21 - mmengine - INFO - Epoch(train) [88][ 5/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:38 time: 0.2806 data_time: 0.0305 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:22 - mmengine - INFO - Epoch(train) [88][10/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:36 time: 0.2811 data_time: 0.0311 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:23 - mmengine - INFO - Epoch(train) [88][15/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:35 time: 0.2812 data_time: 0.0305 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:25 - mmengine - INFO - Epoch(train) [88][20/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:33 time: 0.2810 data_time: 0.0304 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:26 - mmengine - INFO - Epoch(train) [88][25/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:32 time: 0.2810 data_time: 0.0301 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:27 - mmengine - INFO - Epoch(train) [88][30/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:31 time: 0.2807 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:29 - mmengine - INFO - Epoch(train) [88][35/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:29 time: 0.2808 data_time: 0.0302 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:30 - mmengine - INFO - Epoch(train) [88][40/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:28 time: 0.2818 data_time: 0.0304 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:31 - mmengine - INFO - Epoch(train) [88][45/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:26 time: 0.2832 data_time: 0.0304 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:33 - mmengine - INFO - Epoch(train) [88][50/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:25 time: 0.2874 data_time: 0.0306 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:34 - mmengine - INFO - Epoch(train) [88][55/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:24 time: 0.2672 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:35 - mmengine - INFO - Epoch(train) [88][60/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:22 time: 0.2663 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:37 - mmengine - INFO - Epoch(train) [88][65/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:21 time: 0.2665 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:38 - mmengine - INFO - Epoch(train) [88][70/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:19 time: 0.2664 data_time: 0.0102 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:39 - mmengine - INFO - Epoch(train) [88][75/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:18 time: 0.2668 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:41 - mmengine - INFO - Epoch(train) [88][80/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:17 time: 0.2666 data_time: 0.0107 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:42 - mmengine - INFO - Epoch(train) [88][85/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:15 time: 0.2652 data_time: 0.0105 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:43 - mmengine - INFO - Epoch(train) [88][90/94] base_lr: 1.3375e-03 lr: 1.3375e-03 eta: 0:05:14 time: 0.2635 data_time: 0.0103 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:27:44 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:27:44 - mmengine - INFO - Saving checkpoint at 88 epochs 09/30 15:27:47 - mmengine - INFO - Epoch(val) [88][ 5/102] eta: 0:00:25 time: 0.1262 data_time: 0.0226 memory: 11783 09/30 15:27:48 - mmengine - INFO - Epoch(val) [88][ 10/102] eta: 0:00:17 time: 0.1260 data_time: 0.0223 memory: 1697 09/30 15:27:48 - mmengine - INFO - Epoch(val) [88][ 15/102] eta: 0:00:13 time: 0.1255 data_time: 0.0219 memory: 1697 09/30 15:27:49 - mmengine - INFO - Epoch(val) [88][ 20/102] eta: 0:00:12 time: 0.1253 data_time: 0.0217 memory: 1697 09/30 15:27:49 - mmengine - INFO - Epoch(val) [88][ 25/102] eta: 0:00:10 time: 0.1252 data_time: 0.0216 memory: 1697 09/30 15:27:50 - mmengine - INFO - Epoch(val) [88][ 30/102] eta: 0:00:09 time: 0.1254 data_time: 0.0218 memory: 1697 09/30 15:27:50 - mmengine - INFO - Epoch(val) [88][ 35/102] eta: 0:00:08 time: 0.1251 data_time: 0.0215 memory: 1697 09/30 15:27:51 - mmengine - INFO - Epoch(val) [88][ 40/102] eta: 0:00:08 time: 0.1256 data_time: 0.0217 memory: 1697 09/30 15:27:51 - mmengine - INFO - Epoch(val) [88][ 45/102] eta: 0:00:07 time: 0.1258 data_time: 0.0217 memory: 1697 09/30 15:27:52 - mmengine - INFO - Epoch(val) [88][ 50/102] eta: 0:00:06 time: 0.1261 data_time: 0.0218 memory: 1697 09/30 15:27:53 - mmengine - INFO - Epoch(val) [88][ 55/102] eta: 0:00:05 time: 0.1107 data_time: 0.0068 memory: 1697 09/30 15:27:53 - mmengine - INFO - Epoch(val) [88][ 60/102] eta: 0:00:05 time: 0.1108 data_time: 0.0071 memory: 1697 09/30 15:27:54 - mmengine - INFO - Epoch(val) [88][ 65/102] eta: 0:00:04 time: 0.1112 data_time: 0.0074 memory: 1697 09/30 15:27:54 - mmengine - INFO - Epoch(val) [88][ 70/102] eta: 0:00:03 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:27:55 - mmengine - INFO - Epoch(val) [88][ 75/102] eta: 0:00:03 time: 0.1117 data_time: 0.0077 memory: 1697 09/30 15:27:55 - mmengine - INFO - Epoch(val) [88][ 80/102] eta: 0:00:02 time: 0.1117 data_time: 0.0076 memory: 1697 09/30 15:27:56 - mmengine - INFO - Epoch(val) [88][ 85/102] eta: 0:00:02 time: 0.1117 data_time: 0.0077 memory: 1697 09/30 15:27:56 - mmengine - INFO - Epoch(val) [88][ 90/102] eta: 0:00:01 time: 0.1116 data_time: 0.0077 memory: 1697 09/30 15:27:57 - mmengine - INFO - Epoch(val) [88][ 95/102] eta: 0:00:00 time: 0.1115 data_time: 0.0079 memory: 1697 09/30 15:27:58 - mmengine - INFO - Epoch(val) [88][100/102] eta: 0:00:00 time: 0.1111 data_time: 0.0076 memory: 1697 09/30 15:27:58 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:27:58 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:27:58 - mmengine - INFO - Epoch(val) [88][102/102] data_time: 0.0145 time: 0.1183 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:28:01 - mmengine - INFO - Epoch(train) [89][ 5/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:12 time: 0.2969 data_time: 0.0476 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:02 - mmengine - INFO - Epoch(train) [89][10/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:10 time: 0.2979 data_time: 0.0476 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:04 - mmengine - INFO - Epoch(train) [89][15/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:09 time: 0.2974 data_time: 0.0470 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:05 - mmengine - INFO - Epoch(train) [89][20/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:07 time: 0.2968 data_time: 0.0464 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:06 - mmengine - INFO - Epoch(train) [89][25/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:06 time: 0.2972 data_time: 0.0465 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:08 - mmengine - INFO - Epoch(train) [89][30/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:05 time: 0.2965 data_time: 0.0464 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:09 - mmengine - INFO - Epoch(train) [89][35/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:03 time: 0.2967 data_time: 0.0464 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:10 - mmengine - INFO - Epoch(train) [89][40/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:02 time: 0.2977 data_time: 0.0464 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:12 - mmengine - INFO - Epoch(train) [89][45/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:05:00 time: 0.2993 data_time: 0.0464 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:13 - mmengine - INFO - Epoch(train) [89][50/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:59 time: 0.3032 data_time: 0.0465 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:14 - mmengine - INFO - Epoch(train) [89][55/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:58 time: 0.2659 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:16 - mmengine - INFO - Epoch(train) [89][60/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:56 time: 0.2642 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:17 - mmengine - INFO - Epoch(train) [89][65/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:55 time: 0.2648 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:18 - mmengine - INFO - Epoch(train) [89][70/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:53 time: 0.2647 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:20 - mmengine - INFO - Epoch(train) [89][75/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:52 time: 0.2649 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:21 - mmengine - INFO - Epoch(train) [89][80/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:51 time: 0.2650 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:22 - mmengine - INFO - Epoch(train) [89][85/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:49 time: 0.2637 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:23 - mmengine - INFO - Epoch(train) [89][90/94] base_lr: 1.2344e-03 lr: 1.2344e-03 eta: 0:04:48 time: 0.2626 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:24 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:28:24 - mmengine - INFO - Saving checkpoint at 89 epochs 09/30 15:28:27 - mmengine - INFO - Epoch(val) [89][ 5/102] eta: 0:00:26 time: 0.1270 data_time: 0.0231 memory: 11783 09/30 15:28:28 - mmengine - INFO - Epoch(val) [89][ 10/102] eta: 0:00:17 time: 0.1268 data_time: 0.0228 memory: 1697 09/30 15:28:28 - mmengine - INFO - Epoch(val) [89][ 15/102] eta: 0:00:14 time: 0.1265 data_time: 0.0225 memory: 1697 09/30 15:28:29 - mmengine - INFO - Epoch(val) [89][ 20/102] eta: 0:00:12 time: 0.1263 data_time: 0.0224 memory: 1697 09/30 15:28:29 - mmengine - INFO - Epoch(val) [89][ 25/102] eta: 0:00:10 time: 0.1263 data_time: 0.0223 memory: 1697 09/30 15:28:30 - mmengine - INFO - Epoch(val) [89][ 30/102] eta: 0:00:09 time: 0.1266 data_time: 0.0226 memory: 1697 09/30 15:28:30 - mmengine - INFO - Epoch(val) [89][ 35/102] eta: 0:00:08 time: 0.1263 data_time: 0.0222 memory: 1697 09/30 15:28:31 - mmengine - INFO - Epoch(val) [89][ 40/102] eta: 0:00:08 time: 0.1263 data_time: 0.0223 memory: 1697 09/30 15:28:32 - mmengine - INFO - Epoch(val) [89][ 45/102] eta: 0:00:07 time: 0.1264 data_time: 0.0223 memory: 1697 09/30 15:28:32 - mmengine - INFO - Epoch(val) [89][ 50/102] eta: 0:00:06 time: 0.1267 data_time: 0.0224 memory: 1697 09/30 15:28:33 - mmengine - INFO - Epoch(val) [89][ 55/102] eta: 0:00:05 time: 0.1108 data_time: 0.0068 memory: 1697 09/30 15:28:33 - mmengine - INFO - Epoch(val) [89][ 60/102] eta: 0:00:05 time: 0.1109 data_time: 0.0071 memory: 1697 09/30 15:28:34 - mmengine - INFO - Epoch(val) [89][ 65/102] eta: 0:00:04 time: 0.1116 data_time: 0.0074 memory: 1697 09/30 15:28:34 - mmengine - INFO - Epoch(val) [89][ 70/102] eta: 0:00:03 time: 0.1118 data_time: 0.0075 memory: 1697 09/30 15:28:35 - mmengine - INFO - Epoch(val) [89][ 75/102] eta: 0:00:03 time: 0.1119 data_time: 0.0076 memory: 1697 09/30 15:28:35 - mmengine - INFO - Epoch(val) [89][ 80/102] eta: 0:00:02 time: 0.1114 data_time: 0.0074 memory: 1697 09/30 15:28:36 - mmengine - INFO - Epoch(val) [89][ 85/102] eta: 0:00:02 time: 0.1118 data_time: 0.0077 memory: 1697 09/30 15:28:37 - mmengine - INFO - Epoch(val) [89][ 90/102] eta: 0:00:01 time: 0.1115 data_time: 0.0077 memory: 1697 09/30 15:28:37 - mmengine - INFO - Epoch(val) [89][ 95/102] eta: 0:00:00 time: 0.1115 data_time: 0.0078 memory: 1697 09/30 15:28:38 - mmengine - INFO - Epoch(val) [89][100/102] eta: 0:00:00 time: 0.1112 data_time: 0.0076 memory: 1697 09/30 15:28:38 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:28:38 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:28:38 - mmengine - INFO - Epoch(val) [89][102/102] data_time: 0.0148 time: 0.1187 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:28:40 - mmengine - INFO - Epoch(train) [90][ 5/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:45 time: 0.2803 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:42 - mmengine - INFO - Epoch(train) [90][10/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:44 time: 0.2807 data_time: 0.0314 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:43 - mmengine - INFO - Epoch(train) [90][15/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:43 time: 0.2813 data_time: 0.0306 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:44 - mmengine - INFO - Epoch(train) [90][20/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:41 time: 0.2818 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:46 - mmengine - INFO - Epoch(train) [90][25/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:40 time: 0.2820 data_time: 0.0305 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:47 - mmengine - INFO - Epoch(train) [90][30/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:38 time: 0.2816 data_time: 0.0301 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:48 - mmengine - INFO - Epoch(train) [90][35/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:37 time: 0.2818 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:50 - mmengine - INFO - Epoch(train) [90][40/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:36 time: 0.2828 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:51 - mmengine - INFO - Epoch(train) [90][45/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:34 time: 0.2841 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:52 - mmengine - INFO - Epoch(train) [90][50/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:33 time: 0.2887 data_time: 0.0302 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:54 - mmengine - INFO - Epoch(train) [90][55/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:31 time: 0.2674 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:55 - mmengine - INFO - Epoch(train) [90][60/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:30 time: 0.2667 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:56 - mmengine - INFO - Epoch(train) [90][65/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:29 time: 0.2663 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:58 - mmengine - INFO - Epoch(train) [90][70/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:27 time: 0.2662 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:28:59 - mmengine - INFO - Epoch(train) [90][75/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:26 time: 0.2661 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:00 - mmengine - INFO - Epoch(train) [90][80/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:24 time: 0.2660 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:02 - mmengine - INFO - Epoch(train) [90][85/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:23 time: 0.2642 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:03 - mmengine - INFO - Epoch(train) [90][90/94] base_lr: 1.1313e-03 lr: 1.1313e-03 eta: 0:04:22 time: 0.2629 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:04 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:29:04 - mmengine - INFO - Saving checkpoint at 90 epochs 09/30 15:29:06 - mmengine - INFO - Epoch(val) [90][ 5/102] eta: 0:00:22 time: 0.1236 data_time: 0.0202 memory: 11783 09/30 15:29:07 - mmengine - INFO - Epoch(val) [90][ 10/102] eta: 0:00:15 time: 0.1235 data_time: 0.0201 memory: 1697 09/30 15:29:07 - mmengine - INFO - Epoch(val) [90][ 15/102] eta: 0:00:13 time: 0.1231 data_time: 0.0197 memory: 1697 09/30 15:29:08 - mmengine - INFO - Epoch(val) [90][ 20/102] eta: 0:00:11 time: 0.1230 data_time: 0.0197 memory: 1697 09/30 15:29:08 - mmengine - INFO - Epoch(val) [90][ 25/102] eta: 0:00:10 time: 0.1229 data_time: 0.0196 memory: 1697 09/30 15:29:09 - mmengine - INFO - Epoch(val) [90][ 30/102] eta: 0:00:09 time: 0.1228 data_time: 0.0196 memory: 1697 09/30 15:29:09 - mmengine - INFO - Epoch(val) [90][ 35/102] eta: 0:00:08 time: 0.1230 data_time: 0.0194 memory: 1697 09/30 15:29:10 - mmengine - INFO - Epoch(val) [90][ 40/102] eta: 0:00:07 time: 0.1234 data_time: 0.0195 memory: 1697 09/30 15:29:11 - mmengine - INFO - Epoch(val) [90][ 45/102] eta: 0:00:07 time: 0.1231 data_time: 0.0194 memory: 1697 09/30 15:29:11 - mmengine - INFO - Epoch(val) [90][ 50/102] eta: 0:00:06 time: 0.1234 data_time: 0.0195 memory: 1697 09/30 15:29:12 - mmengine - INFO - Epoch(val) [90][ 55/102] eta: 0:00:05 time: 0.1108 data_time: 0.0068 memory: 1697 09/30 15:29:12 - mmengine - INFO - Epoch(val) [90][ 60/102] eta: 0:00:05 time: 0.1109 data_time: 0.0069 memory: 1697 09/30 15:29:13 - mmengine - INFO - Epoch(val) [90][ 65/102] eta: 0:00:04 time: 0.1111 data_time: 0.0072 memory: 1697 09/30 15:29:13 - mmengine - INFO - Epoch(val) [90][ 70/102] eta: 0:00:03 time: 0.1108 data_time: 0.0072 memory: 1697 09/30 15:29:14 - mmengine - INFO - Epoch(val) [90][ 75/102] eta: 0:00:03 time: 0.1109 data_time: 0.0073 memory: 1697 09/30 15:29:14 - mmengine - INFO - Epoch(val) [90][ 80/102] eta: 0:00:02 time: 0.1109 data_time: 0.0072 memory: 1697 09/30 15:29:15 - mmengine - INFO - Epoch(val) [90][ 85/102] eta: 0:00:02 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 15:29:16 - mmengine - INFO - Epoch(val) [90][ 90/102] eta: 0:00:01 time: 0.1103 data_time: 0.0072 memory: 1697 09/30 15:29:16 - mmengine - INFO - Epoch(val) [90][ 95/102] eta: 0:00:00 time: 0.1102 data_time: 0.0073 memory: 1697 09/30 15:29:17 - mmengine - INFO - Epoch(val) [90][100/102] eta: 0:00:00 time: 0.1100 data_time: 0.0071 memory: 1697 09/30 15:29:17 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:29:17 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:29:17 - mmengine - INFO - Epoch(val) [90][102/102] data_time: 0.0131 time: 0.1165 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:29:19 - mmengine - INFO - Epoch(train) [91][ 5/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:19 time: 0.2801 data_time: 0.0313 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:21 - mmengine - INFO - Epoch(train) [91][10/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:18 time: 0.2813 data_time: 0.0315 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:22 - mmengine - INFO - Epoch(train) [91][15/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:16 time: 0.2811 data_time: 0.0311 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:23 - mmengine - INFO - Epoch(train) [91][20/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:15 time: 0.2805 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:25 - mmengine - INFO - Epoch(train) [91][25/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:14 time: 0.2814 data_time: 0.0309 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:26 - mmengine - INFO - Epoch(train) [91][30/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:12 time: 0.2816 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:27 - mmengine - INFO - Epoch(train) [91][35/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:11 time: 0.2816 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:29 - mmengine - INFO - Epoch(train) [91][40/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:10 time: 0.2827 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:30 - mmengine - INFO - Epoch(train) [91][45/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:08 time: 0.2840 data_time: 0.0310 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:31 - mmengine - INFO - Epoch(train) [91][50/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:07 time: 0.2878 data_time: 0.0311 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:33 - mmengine - INFO - Epoch(train) [91][55/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:05 time: 0.2661 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:34 - mmengine - INFO - Epoch(train) [91][60/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:04 time: 0.2649 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:35 - mmengine - INFO - Epoch(train) [91][65/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:03 time: 0.2643 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:37 - mmengine - INFO - Epoch(train) [91][70/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:01 time: 0.2653 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:38 - mmengine - INFO - Epoch(train) [91][75/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:04:00 time: 0.2642 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:39 - mmengine - INFO - Epoch(train) [91][80/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:03:58 time: 0.2638 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:40 - mmengine - INFO - Epoch(train) [91][85/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:03:57 time: 0.2622 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:42 - mmengine - INFO - Epoch(train) [91][90/94] base_lr: 1.0281e-03 lr: 1.0281e-03 eta: 0:03:56 time: 0.2611 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:43 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:29:43 - mmengine - INFO - Saving checkpoint at 91 epochs 09/30 15:29:45 - mmengine - INFO - Epoch(val) [91][ 5/102] eta: 0:00:21 time: 0.1206 data_time: 0.0177 memory: 11783 09/30 15:29:46 - mmengine - INFO - Epoch(val) [91][ 10/102] eta: 0:00:14 time: 0.1202 data_time: 0.0174 memory: 1697 09/30 15:29:46 - mmengine - INFO - Epoch(val) [91][ 15/102] eta: 0:00:12 time: 0.1198 data_time: 0.0170 memory: 1697 09/30 15:29:47 - mmengine - INFO - Epoch(val) [91][ 20/102] eta: 0:00:11 time: 0.1199 data_time: 0.0170 memory: 1697 09/30 15:29:47 - mmengine - INFO - Epoch(val) [91][ 25/102] eta: 0:00:09 time: 0.1196 data_time: 0.0168 memory: 1697 09/30 15:29:48 - mmengine - INFO - Epoch(val) [91][ 30/102] eta: 0:00:09 time: 0.1194 data_time: 0.0168 memory: 1697 09/30 15:29:48 - mmengine - INFO - Epoch(val) [91][ 35/102] eta: 0:00:08 time: 0.1188 data_time: 0.0165 memory: 1697 09/30 15:29:49 - mmengine - INFO - Epoch(val) [91][ 40/102] eta: 0:00:07 time: 0.1189 data_time: 0.0165 memory: 1697 09/30 15:29:49 - mmengine - INFO - Epoch(val) [91][ 45/102] eta: 0:00:06 time: 0.1187 data_time: 0.0164 memory: 1697 09/30 15:29:50 - mmengine - INFO - Epoch(val) [91][ 50/102] eta: 0:00:06 time: 0.1187 data_time: 0.0164 memory: 1697 09/30 15:29:51 - mmengine - INFO - Epoch(val) [91][ 55/102] eta: 0:00:05 time: 0.1080 data_time: 0.0057 memory: 1697 09/30 15:29:51 - mmengine - INFO - Epoch(val) [91][ 60/102] eta: 0:00:04 time: 0.1081 data_time: 0.0060 memory: 1697 09/30 15:29:52 - mmengine - INFO - Epoch(val) [91][ 65/102] eta: 0:00:04 time: 0.1083 data_time: 0.0063 memory: 1697 09/30 15:29:52 - mmengine - INFO - Epoch(val) [91][ 70/102] eta: 0:00:03 time: 0.1080 data_time: 0.0062 memory: 1697 09/30 15:29:53 - mmengine - INFO - Epoch(val) [91][ 75/102] eta: 0:00:03 time: 0.1081 data_time: 0.0064 memory: 1697 09/30 15:29:53 - mmengine - INFO - Epoch(val) [91][ 80/102] eta: 0:00:02 time: 0.1079 data_time: 0.0062 memory: 1697 09/30 15:29:54 - mmengine - INFO - Epoch(val) [91][ 85/102] eta: 0:00:01 time: 0.1082 data_time: 0.0063 memory: 1697 09/30 15:29:54 - mmengine - INFO - Epoch(val) [91][ 90/102] eta: 0:00:01 time: 0.1081 data_time: 0.0063 memory: 1697 09/30 15:29:55 - mmengine - INFO - Epoch(val) [91][ 95/102] eta: 0:00:00 time: 0.1080 data_time: 0.0063 memory: 1697 09/30 15:29:55 - mmengine - INFO - Epoch(val) [91][100/102] eta: 0:00:00 time: 0.1079 data_time: 0.0062 memory: 1697 09/30 15:29:56 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:29:56 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:29:56 - mmengine - INFO - Epoch(val) [91][102/102] data_time: 0.0111 time: 0.1131 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:29:58 - mmengine - INFO - Epoch(train) [92][ 5/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:53 time: 0.2735 data_time: 0.0254 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:29:59 - mmengine - INFO - Epoch(train) [92][10/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:52 time: 0.2744 data_time: 0.0257 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:00 - mmengine - INFO - Epoch(train) [92][15/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:50 time: 0.2742 data_time: 0.0259 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:02 - mmengine - INFO - Epoch(train) [92][20/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:49 time: 0.2739 data_time: 0.0253 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:03 - mmengine - INFO - Epoch(train) [92][25/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:48 time: 0.2736 data_time: 0.0252 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:04 - mmengine - INFO - Epoch(train) [92][30/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:46 time: 0.2730 data_time: 0.0247 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:06 - mmengine - INFO - Epoch(train) [92][35/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:45 time: 0.2731 data_time: 0.0248 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:07 - mmengine - INFO - Epoch(train) [92][40/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:43 time: 0.2748 data_time: 0.0248 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:08 - mmengine - INFO - Epoch(train) [92][45/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:42 time: 0.2759 data_time: 0.0250 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:10 - mmengine - INFO - Epoch(train) [92][50/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:41 time: 0.2804 data_time: 0.0252 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:11 - mmengine - INFO - Epoch(train) [92][55/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:39 time: 0.2637 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:12 - mmengine - INFO - Epoch(train) [92][60/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:38 time: 0.2632 data_time: 0.0086 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:14 - mmengine - INFO - Epoch(train) [92][65/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:36 time: 0.2626 data_time: 0.0083 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:15 - mmengine - INFO - Epoch(train) [92][70/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:35 time: 0.2625 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:16 - mmengine - INFO - Epoch(train) [92][75/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:34 time: 0.2622 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:17 - mmengine - INFO - Epoch(train) [92][80/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:32 time: 0.2620 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:19 - mmengine - INFO - Epoch(train) [92][85/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:31 time: 0.2596 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:20 - mmengine - INFO - Epoch(train) [92][90/94] base_lr: 9.2500e-04 lr: 9.2500e-04 eta: 0:03:29 time: 0.2575 data_time: 0.0087 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:21 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:30:21 - mmengine - INFO - Saving checkpoint at 92 epochs 09/30 15:30:23 - mmengine - INFO - Epoch(val) [92][ 5/102] eta: 0:00:20 time: 0.1176 data_time: 0.0161 memory: 11783 09/30 15:30:24 - mmengine - INFO - Epoch(val) [92][ 10/102] eta: 0:00:14 time: 0.1174 data_time: 0.0159 memory: 1697 09/30 15:30:24 - mmengine - INFO - Epoch(val) [92][ 15/102] eta: 0:00:12 time: 0.1172 data_time: 0.0156 memory: 1697 09/30 15:30:25 - mmengine - INFO - Epoch(val) [92][ 20/102] eta: 0:00:10 time: 0.1172 data_time: 0.0155 memory: 1697 09/30 15:30:25 - mmengine - INFO - Epoch(val) [92][ 25/102] eta: 0:00:09 time: 0.1172 data_time: 0.0155 memory: 1697 09/30 15:30:26 - mmengine - INFO - Epoch(val) [92][ 30/102] eta: 0:00:08 time: 0.1173 data_time: 0.0156 memory: 1697 09/30 15:30:26 - mmengine - INFO - Epoch(val) [92][ 35/102] eta: 0:00:08 time: 0.1172 data_time: 0.0155 memory: 1697 09/30 15:30:27 - mmengine - INFO - Epoch(val) [92][ 40/102] eta: 0:00:07 time: 0.1174 data_time: 0.0156 memory: 1697 09/30 15:30:28 - mmengine - INFO - Epoch(val) [92][ 45/102] eta: 0:00:06 time: 0.1177 data_time: 0.0157 memory: 1697 09/30 15:30:28 - mmengine - INFO - Epoch(val) [92][ 50/102] eta: 0:00:06 time: 0.1177 data_time: 0.0158 memory: 1697 09/30 15:30:29 - mmengine - INFO - Epoch(val) [92][ 55/102] eta: 0:00:05 time: 0.1077 data_time: 0.0058 memory: 1697 09/30 15:30:29 - mmengine - INFO - Epoch(val) [92][ 60/102] eta: 0:00:04 time: 0.1082 data_time: 0.0060 memory: 1697 09/30 15:30:30 - mmengine - INFO - Epoch(val) [92][ 65/102] eta: 0:00:04 time: 0.1084 data_time: 0.0063 memory: 1697 09/30 15:30:30 - mmengine - INFO - Epoch(val) [92][ 70/102] eta: 0:00:03 time: 0.1084 data_time: 0.0063 memory: 1697 09/30 15:30:31 - mmengine - INFO - Epoch(val) [92][ 75/102] eta: 0:00:03 time: 0.1084 data_time: 0.0063 memory: 1697 09/30 15:30:31 - mmengine - INFO - Epoch(val) [92][ 80/102] eta: 0:00:02 time: 0.1081 data_time: 0.0062 memory: 1697 09/30 15:30:32 - mmengine - INFO - Epoch(val) [92][ 85/102] eta: 0:00:01 time: 0.1080 data_time: 0.0062 memory: 1697 09/30 15:30:32 - mmengine - INFO - Epoch(val) [92][ 90/102] eta: 0:00:01 time: 0.1081 data_time: 0.0062 memory: 1697 09/30 15:30:33 - mmengine - INFO - Epoch(val) [92][ 95/102] eta: 0:00:00 time: 0.1079 data_time: 0.0062 memory: 1697 09/30 15:30:33 - mmengine - INFO - Epoch(val) [92][100/102] eta: 0:00:00 time: 0.1076 data_time: 0.0060 memory: 1697 09/30 15:30:34 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:30:34 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:30:34 - mmengine - INFO - Epoch(val) [92][102/102] data_time: 0.0108 time: 0.1125 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:30:36 - mmengine - INFO - Epoch(train) [93][ 5/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:27 time: 0.2726 data_time: 0.0274 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:37 - mmengine - INFO - Epoch(train) [93][10/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:26 time: 0.2722 data_time: 0.0274 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:39 - mmengine - INFO - Epoch(train) [93][15/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:24 time: 0.2715 data_time: 0.0271 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:40 - mmengine - INFO - Epoch(train) [93][20/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:23 time: 0.2721 data_time: 0.0274 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:41 - mmengine - INFO - Epoch(train) [93][25/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:21 time: 0.2720 data_time: 0.0270 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:42 - mmengine - INFO - Epoch(train) [93][30/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:20 time: 0.2723 data_time: 0.0271 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:44 - mmengine - INFO - Epoch(train) [93][35/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:19 time: 0.2725 data_time: 0.0272 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:45 - mmengine - INFO - Epoch(train) [93][40/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:17 time: 0.2743 data_time: 0.0273 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:46 - mmengine - INFO - Epoch(train) [93][45/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:16 time: 0.2767 data_time: 0.0276 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:48 - mmengine - INFO - Epoch(train) [93][50/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:14 time: 0.2811 data_time: 0.0278 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:49 - mmengine - INFO - Epoch(train) [93][55/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:13 time: 0.2624 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:50 - mmengine - INFO - Epoch(train) [93][60/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:12 time: 0.2627 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:52 - mmengine - INFO - Epoch(train) [93][65/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:10 time: 0.2633 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:53 - mmengine - INFO - Epoch(train) [93][70/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:09 time: 0.2629 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:54 - mmengine - INFO - Epoch(train) [93][75/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:07 time: 0.2641 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:56 - mmengine - INFO - Epoch(train) [93][80/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:06 time: 0.2637 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:57 - mmengine - INFO - Epoch(train) [93][85/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:05 time: 0.2624 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:58 - mmengine - INFO - Epoch(train) [93][90/94] base_lr: 8.2188e-04 lr: 8.2188e-04 eta: 0:03:03 time: 0.2615 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:30:59 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:30:59 - mmengine - INFO - Saving checkpoint at 93 epochs 09/30 15:31:01 - mmengine - INFO - Epoch(val) [93][ 5/102] eta: 0:00:20 time: 0.1178 data_time: 0.0161 memory: 11783 09/30 15:31:02 - mmengine - INFO - Epoch(val) [93][ 10/102] eta: 0:00:14 time: 0.1179 data_time: 0.0160 memory: 1697 09/30 15:31:02 - mmengine - INFO - Epoch(val) [93][ 15/102] eta: 0:00:12 time: 0.1178 data_time: 0.0157 memory: 1697 09/30 15:31:03 - mmengine - INFO - Epoch(val) [93][ 20/102] eta: 0:00:11 time: 0.1179 data_time: 0.0158 memory: 1697 09/30 15:31:04 - mmengine - INFO - Epoch(val) [93][ 25/102] eta: 0:00:09 time: 0.1182 data_time: 0.0159 memory: 1697 09/30 15:31:04 - mmengine - INFO - Epoch(val) [93][ 30/102] eta: 0:00:09 time: 0.1229 data_time: 0.0204 memory: 1697 09/30 15:31:05 - mmengine - INFO - Epoch(val) [93][ 35/102] eta: 0:00:08 time: 0.1229 data_time: 0.0203 memory: 1697 09/30 15:31:05 - mmengine - INFO - Epoch(val) [93][ 40/102] eta: 0:00:07 time: 0.1233 data_time: 0.0205 memory: 1697 09/30 15:31:06 - mmengine - INFO - Epoch(val) [93][ 45/102] eta: 0:00:07 time: 0.1237 data_time: 0.0206 memory: 1697 09/30 15:31:06 - mmengine - INFO - Epoch(val) [93][ 50/102] eta: 0:00:06 time: 0.1241 data_time: 0.0209 memory: 1697 09/30 15:31:07 - mmengine - INFO - Epoch(val) [93][ 55/102] eta: 0:00:05 time: 0.1138 data_time: 0.0109 memory: 1697 09/30 15:31:08 - mmengine - INFO - Epoch(val) [93][ 60/102] eta: 0:00:05 time: 0.1140 data_time: 0.0111 memory: 1697 09/30 15:31:08 - mmengine - INFO - Epoch(val) [93][ 65/102] eta: 0:00:04 time: 0.1142 data_time: 0.0114 memory: 1697 09/30 15:31:09 - mmengine - INFO - Epoch(val) [93][ 70/102] eta: 0:00:03 time: 0.1145 data_time: 0.0115 memory: 1697 09/30 15:31:09 - mmengine - INFO - Epoch(val) [93][ 75/102] eta: 0:00:03 time: 0.1147 data_time: 0.0114 memory: 1697 09/30 15:31:10 - mmengine - INFO - Epoch(val) [93][ 80/102] eta: 0:00:02 time: 0.1102 data_time: 0.0070 memory: 1697 09/30 15:31:10 - mmengine - INFO - Epoch(val) [93][ 85/102] eta: 0:00:02 time: 0.1104 data_time: 0.0071 memory: 1697 09/30 15:31:11 - mmengine - INFO - Epoch(val) [93][ 90/102] eta: 0:00:01 time: 0.1104 data_time: 0.0070 memory: 1697 09/30 15:31:11 - mmengine - INFO - Epoch(val) [93][ 95/102] eta: 0:00:00 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 15:31:12 - mmengine - INFO - Epoch(val) [93][100/102] eta: 0:00:00 time: 0.1099 data_time: 0.0069 memory: 1697 09/30 15:31:12 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:31:12 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:31:12 - mmengine - INFO - Epoch(val) [93][102/102] data_time: 0.0137 time: 0.1167 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:31:15 - mmengine - INFO - Epoch(train) [94][ 5/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:03:01 time: 0.2813 data_time: 0.0325 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:16 - mmengine - INFO - Epoch(train) [94][10/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:59 time: 0.2802 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:17 - mmengine - INFO - Epoch(train) [94][15/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:58 time: 0.2807 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:19 - mmengine - INFO - Epoch(train) [94][20/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:57 time: 0.2811 data_time: 0.0325 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:20 - mmengine - INFO - Epoch(train) [94][25/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:55 time: 0.2814 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:21 - mmengine - INFO - Epoch(train) [94][30/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:54 time: 0.2810 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:23 - mmengine - INFO - Epoch(train) [94][35/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:52 time: 0.2817 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:24 - mmengine - INFO - Epoch(train) [94][40/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:51 time: 0.2827 data_time: 0.0324 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:25 - mmengine - INFO - Epoch(train) [94][45/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:50 time: 0.2838 data_time: 0.0325 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:27 - mmengine - INFO - Epoch(train) [94][50/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:48 time: 0.2876 data_time: 0.0326 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:28 - mmengine - INFO - Epoch(train) [94][55/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:47 time: 0.2638 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:29 - mmengine - INFO - Epoch(train) [94][60/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:45 time: 0.2650 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:31 - mmengine - INFO - Epoch(train) [94][65/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:44 time: 0.2646 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:32 - mmengine - INFO - Epoch(train) [94][70/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:43 time: 0.2644 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:33 - mmengine - INFO - Epoch(train) [94][75/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:41 time: 0.2646 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:35 - mmengine - INFO - Epoch(train) [94][80/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:40 time: 0.2643 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:36 - mmengine - INFO - Epoch(train) [94][85/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:38 time: 0.2625 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:37 - mmengine - INFO - Epoch(train) [94][90/94] base_lr: 7.1875e-04 lr: 7.1875e-04 eta: 0:02:37 time: 0.2621 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:38 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:31:38 - mmengine - INFO - Saving checkpoint at 94 epochs 09/30 15:31:41 - mmengine - INFO - Epoch(val) [94][ 5/102] eta: 0:00:22 time: 0.1217 data_time: 0.0184 memory: 11783 09/30 15:31:41 - mmengine - INFO - Epoch(val) [94][ 10/102] eta: 0:00:15 time: 0.1216 data_time: 0.0182 memory: 1697 09/30 15:31:42 - mmengine - INFO - Epoch(val) [94][ 15/102] eta: 0:00:12 time: 0.1214 data_time: 0.0179 memory: 1697 09/30 15:31:42 - mmengine - INFO - Epoch(val) [94][ 20/102] eta: 0:00:11 time: 0.1214 data_time: 0.0180 memory: 1697 09/30 15:31:43 - mmengine - INFO - Epoch(val) [94][ 25/102] eta: 0:00:10 time: 0.1215 data_time: 0.0179 memory: 1697 09/30 15:31:43 - mmengine - INFO - Epoch(val) [94][ 30/102] eta: 0:00:09 time: 0.1216 data_time: 0.0181 memory: 1697 09/30 15:31:44 - mmengine - INFO - Epoch(val) [94][ 35/102] eta: 0:00:08 time: 0.1217 data_time: 0.0181 memory: 1697 09/30 15:31:45 - mmengine - INFO - Epoch(val) [94][ 40/102] eta: 0:00:07 time: 0.1219 data_time: 0.0183 memory: 1697 09/30 15:31:45 - mmengine - INFO - Epoch(val) [94][ 45/102] eta: 0:00:07 time: 0.1221 data_time: 0.0184 memory: 1697 09/30 15:31:46 - mmengine - INFO - Epoch(val) [94][ 50/102] eta: 0:00:06 time: 0.1225 data_time: 0.0184 memory: 1697 09/30 15:31:46 - mmengine - INFO - Epoch(val) [94][ 55/102] eta: 0:00:05 time: 0.1108 data_time: 0.0070 memory: 1697 09/30 15:31:47 - mmengine - INFO - Epoch(val) [94][ 60/102] eta: 0:00:05 time: 0.1109 data_time: 0.0073 memory: 1697 09/30 15:31:47 - mmengine - INFO - Epoch(val) [94][ 65/102] eta: 0:00:04 time: 0.1111 data_time: 0.0076 memory: 1697 09/30 15:31:48 - mmengine - INFO - Epoch(val) [94][ 70/102] eta: 0:00:03 time: 0.1113 data_time: 0.0076 memory: 1697 09/30 15:31:48 - mmengine - INFO - Epoch(val) [94][ 75/102] eta: 0:00:03 time: 0.1114 data_time: 0.0077 memory: 1697 09/30 15:31:49 - mmengine - INFO - Epoch(val) [94][ 80/102] eta: 0:00:02 time: 0.1116 data_time: 0.0076 memory: 1697 09/30 15:31:50 - mmengine - INFO - Epoch(val) [94][ 85/102] eta: 0:00:02 time: 0.1117 data_time: 0.0077 memory: 1697 09/30 15:31:50 - mmengine - INFO - Epoch(val) [94][ 90/102] eta: 0:00:01 time: 0.1118 data_time: 0.0077 memory: 1697 09/30 15:31:51 - mmengine - INFO - Epoch(val) [94][ 95/102] eta: 0:00:00 time: 0.1120 data_time: 0.0078 memory: 1697 09/30 15:31:51 - mmengine - INFO - Epoch(val) [94][100/102] eta: 0:00:00 time: 0.1117 data_time: 0.0077 memory: 1697 09/30 15:31:51 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:31:51 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:31:51 - mmengine - INFO - Epoch(val) [94][102/102] data_time: 0.0129 time: 0.1170 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:31:54 - mmengine - INFO - Epoch(train) [95][ 5/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:35 time: 0.2746 data_time: 0.0249 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:55 - mmengine - INFO - Epoch(train) [95][10/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:33 time: 0.2797 data_time: 0.0307 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:56 - mmengine - INFO - Epoch(train) [95][15/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:32 time: 0.2785 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:58 - mmengine - INFO - Epoch(train) [95][20/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:30 time: 0.2788 data_time: 0.0304 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:31:59 - mmengine - INFO - Epoch(train) [95][25/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:29 time: 0.2786 data_time: 0.0299 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:00 - mmengine - INFO - Epoch(train) [95][30/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:28 time: 0.2786 data_time: 0.0299 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:02 - mmengine - INFO - Epoch(train) [95][35/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:26 time: 0.2787 data_time: 0.0299 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:03 - mmengine - INFO - Epoch(train) [95][40/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:25 time: 0.2810 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:04 - mmengine - INFO - Epoch(train) [95][45/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:24 time: 0.2820 data_time: 0.0301 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:06 - mmengine - INFO - Epoch(train) [95][50/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:22 time: 0.2855 data_time: 0.0301 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:07 - mmengine - INFO - Epoch(train) [95][55/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:21 time: 0.2712 data_time: 0.0150 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:08 - mmengine - INFO - Epoch(train) [95][60/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:19 time: 0.2656 data_time: 0.0092 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:10 - mmengine - INFO - Epoch(train) [95][65/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:18 time: 0.2665 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:11 - mmengine - INFO - Epoch(train) [95][70/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:17 time: 0.2664 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:12 - mmengine - INFO - Epoch(train) [95][75/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:15 time: 0.2668 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:14 - mmengine - INFO - Epoch(train) [95][80/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:14 time: 0.2666 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:15 - mmengine - INFO - Epoch(train) [95][85/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:12 time: 0.2656 data_time: 0.0101 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:16 - mmengine - INFO - Epoch(train) [95][90/94] base_lr: 6.1563e-04 lr: 6.1563e-04 eta: 0:02:11 time: 0.2634 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:17 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:32:17 - mmengine - INFO - Saving checkpoint at 95 epochs 09/30 15:32:20 - mmengine - INFO - Epoch(val) [95][ 5/102] eta: 0:00:25 time: 0.1274 data_time: 0.0231 memory: 11783 09/30 15:32:21 - mmengine - INFO - Epoch(val) [95][ 10/102] eta: 0:00:17 time: 0.1274 data_time: 0.0229 memory: 1697 09/30 15:32:21 - mmengine - INFO - Epoch(val) [95][ 15/102] eta: 0:00:14 time: 0.1271 data_time: 0.0226 memory: 1697 09/30 15:32:22 - mmengine - INFO - Epoch(val) [95][ 20/102] eta: 0:00:12 time: 0.1271 data_time: 0.0225 memory: 1697 09/30 15:32:22 - mmengine - INFO - Epoch(val) [95][ 25/102] eta: 0:00:10 time: 0.1270 data_time: 0.0224 memory: 1697 09/30 15:32:23 - mmengine - INFO - Epoch(val) [95][ 30/102] eta: 0:00:09 time: 0.1269 data_time: 0.0225 memory: 1697 09/30 15:32:23 - mmengine - INFO - Epoch(val) [95][ 35/102] eta: 0:00:08 time: 0.1264 data_time: 0.0222 memory: 1697 09/30 15:32:24 - mmengine - INFO - Epoch(val) [95][ 40/102] eta: 0:00:08 time: 0.1265 data_time: 0.0223 memory: 1697 09/30 15:32:24 - mmengine - INFO - Epoch(val) [95][ 45/102] eta: 0:00:07 time: 0.1267 data_time: 0.0223 memory: 1697 09/30 15:32:25 - mmengine - INFO - Epoch(val) [95][ 50/102] eta: 0:00:06 time: 0.1264 data_time: 0.0223 memory: 1697 09/30 15:32:26 - mmengine - INFO - Epoch(val) [95][ 55/102] eta: 0:00:05 time: 0.1107 data_time: 0.0068 memory: 1697 09/30 15:32:26 - mmengine - INFO - Epoch(val) [95][ 60/102] eta: 0:00:05 time: 0.1108 data_time: 0.0070 memory: 1697 09/30 15:32:27 - mmengine - INFO - Epoch(val) [95][ 65/102] eta: 0:00:04 time: 0.1112 data_time: 0.0073 memory: 1697 09/30 15:32:27 - mmengine - INFO - Epoch(val) [95][ 70/102] eta: 0:00:03 time: 0.1109 data_time: 0.0074 memory: 1697 09/30 15:32:28 - mmengine - INFO - Epoch(val) [95][ 75/102] eta: 0:00:03 time: 0.1109 data_time: 0.0075 memory: 1697 09/30 15:32:28 - mmengine - INFO - Epoch(val) [95][ 80/102] eta: 0:00:02 time: 0.1108 data_time: 0.0074 memory: 1697 09/30 15:32:29 - mmengine - INFO - Epoch(val) [95][ 85/102] eta: 0:00:02 time: 0.1110 data_time: 0.0075 memory: 1697 09/30 15:32:29 - mmengine - INFO - Epoch(val) [95][ 90/102] eta: 0:00:01 time: 0.1108 data_time: 0.0074 memory: 1697 09/30 15:32:30 - mmengine - INFO - Epoch(val) [95][ 95/102] eta: 0:00:00 time: 0.1107 data_time: 0.0075 memory: 1697 09/30 15:32:31 - mmengine - INFO - Epoch(val) [95][100/102] eta: 0:00:00 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:32:31 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:32:31 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:32:31 - mmengine - INFO - Epoch(val) [95][102/102] data_time: 0.0146 time: 0.1183 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:32:33 - mmengine - INFO - Epoch(train) [96][ 5/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:02:09 time: 0.2818 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:35 - mmengine - INFO - Epoch(train) [96][10/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:02:07 time: 0.2819 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:36 - mmengine - INFO - Epoch(train) [96][15/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:02:06 time: 0.2822 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:37 - mmengine - INFO - Epoch(train) [96][20/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:02:04 time: 0.2817 data_time: 0.0327 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:38 - mmengine - INFO - Epoch(train) [96][25/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:02:03 time: 0.2813 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:40 - mmengine - INFO - Epoch(train) [96][30/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:02:02 time: 0.2816 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:41 - mmengine - INFO - Epoch(train) [96][35/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:02:00 time: 0.2814 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:42 - mmengine - INFO - Epoch(train) [96][40/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:59 time: 0.2829 data_time: 0.0321 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:44 - mmengine - INFO - Epoch(train) [96][45/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:57 time: 0.2841 data_time: 0.0322 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:45 - mmengine - INFO - Epoch(train) [96][50/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:56 time: 0.2881 data_time: 0.0323 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:46 - mmengine - INFO - Epoch(train) [96][55/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:55 time: 0.2658 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:48 - mmengine - INFO - Epoch(train) [96][60/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:53 time: 0.2655 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:49 - mmengine - INFO - Epoch(train) [96][65/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:52 time: 0.2654 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:50 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:32:50 - mmengine - INFO - Epoch(train) [96][70/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:50 time: 0.2651 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:52 - mmengine - INFO - Epoch(train) [96][75/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:49 time: 0.2653 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:53 - mmengine - INFO - Epoch(train) [96][80/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:48 time: 0.2644 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:54 - mmengine - INFO - Epoch(train) [96][85/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:46 time: 0.2631 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:56 - mmengine - INFO - Epoch(train) [96][90/94] base_lr: 5.1250e-04 lr: 5.1250e-04 eta: 0:01:45 time: 0.2614 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:32:56 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:32:56 - mmengine - INFO - Saving checkpoint at 96 epochs 09/30 15:32:59 - mmengine - INFO - Epoch(val) [96][ 5/102] eta: 0:00:25 time: 0.1258 data_time: 0.0226 memory: 11783 09/30 15:33:00 - mmengine - INFO - Epoch(val) [96][ 10/102] eta: 0:00:17 time: 0.1254 data_time: 0.0224 memory: 1697 09/30 15:33:00 - mmengine - INFO - Epoch(val) [96][ 15/102] eta: 0:00:13 time: 0.1249 data_time: 0.0220 memory: 1697 09/30 15:33:01 - mmengine - INFO - Epoch(val) [96][ 20/102] eta: 0:00:12 time: 0.1248 data_time: 0.0219 memory: 1697 09/30 15:33:01 - mmengine - INFO - Epoch(val) [96][ 25/102] eta: 0:00:10 time: 0.1246 data_time: 0.0217 memory: 1697 09/30 15:33:02 - mmengine - INFO - Epoch(val) [96][ 30/102] eta: 0:00:09 time: 0.1246 data_time: 0.0218 memory: 1697 09/30 15:33:03 - mmengine - INFO - Epoch(val) [96][ 35/102] eta: 0:00:08 time: 0.1243 data_time: 0.0216 memory: 1697 09/30 15:33:03 - mmengine - INFO - Epoch(val) [96][ 40/102] eta: 0:00:07 time: 0.1244 data_time: 0.0216 memory: 1697 09/30 15:33:04 - mmengine - INFO - Epoch(val) [96][ 45/102] eta: 0:00:07 time: 0.1245 data_time: 0.0217 memory: 1697 09/30 15:33:04 - mmengine - INFO - Epoch(val) [96][ 50/102] eta: 0:00:06 time: 0.1245 data_time: 0.0217 memory: 1697 09/30 15:33:05 - mmengine - INFO - Epoch(val) [96][ 55/102] eta: 0:00:05 time: 0.1094 data_time: 0.0064 memory: 1697 09/30 15:33:05 - mmengine - INFO - Epoch(val) [96][ 60/102] eta: 0:00:05 time: 0.1097 data_time: 0.0067 memory: 1697 09/30 15:33:06 - mmengine - INFO - Epoch(val) [96][ 65/102] eta: 0:00:04 time: 0.1101 data_time: 0.0070 memory: 1697 09/30 15:33:06 - mmengine - INFO - Epoch(val) [96][ 70/102] eta: 0:00:03 time: 0.1099 data_time: 0.0070 memory: 1697 09/30 15:33:07 - mmengine - INFO - Epoch(val) [96][ 75/102] eta: 0:00:03 time: 0.1100 data_time: 0.0071 memory: 1697 09/30 15:33:07 - mmengine - INFO - Epoch(val) [96][ 80/102] eta: 0:00:02 time: 0.1099 data_time: 0.0070 memory: 1697 09/30 15:33:08 - mmengine - INFO - Epoch(val) [96][ 85/102] eta: 0:00:02 time: 0.1099 data_time: 0.0071 memory: 1697 09/30 15:33:09 - mmengine - INFO - Epoch(val) [96][ 90/102] eta: 0:00:01 time: 0.1097 data_time: 0.0071 memory: 1697 09/30 15:33:09 - mmengine - INFO - Epoch(val) [96][ 95/102] eta: 0:00:00 time: 0.1094 data_time: 0.0070 memory: 1697 09/30 15:33:10 - mmengine - INFO - Epoch(val) [96][100/102] eta: 0:00:00 time: 0.1092 data_time: 0.0068 memory: 1697 09/30 15:33:10 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:33:10 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:33:10 - mmengine - INFO - Epoch(val) [96][102/102] data_time: 0.0140 time: 0.1166 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:33:13 - mmengine - INFO - Epoch(train) [97][ 5/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:42 time: 0.2868 data_time: 0.0377 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:14 - mmengine - INFO - Epoch(train) [97][10/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:41 time: 0.2864 data_time: 0.0379 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:15 - mmengine - INFO - Epoch(train) [97][15/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:40 time: 0.2853 data_time: 0.0372 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:17 - mmengine - INFO - Epoch(train) [97][20/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:38 time: 0.2856 data_time: 0.0373 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:18 - mmengine - INFO - Epoch(train) [97][25/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:37 time: 0.2856 data_time: 0.0370 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:19 - mmengine - INFO - Epoch(train) [97][30/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:35 time: 0.2858 data_time: 0.0369 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:20 - mmengine - INFO - Epoch(train) [97][35/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:34 time: 0.2857 data_time: 0.0369 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:22 - mmengine - INFO - Epoch(train) [97][40/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:33 time: 0.2866 data_time: 0.0368 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:23 - mmengine - INFO - Epoch(train) [97][45/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:31 time: 0.2879 data_time: 0.0368 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:24 - mmengine - INFO - Epoch(train) [97][50/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:30 time: 0.2921 data_time: 0.0369 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:26 - mmengine - INFO - Epoch(train) [97][55/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:29 time: 0.2632 data_time: 0.0091 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:27 - mmengine - INFO - Epoch(train) [97][60/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:27 time: 0.2630 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:28 - mmengine - INFO - Epoch(train) [97][65/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:26 time: 0.2643 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:30 - mmengine - INFO - Epoch(train) [97][70/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:24 time: 0.2639 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:31 - mmengine - INFO - Epoch(train) [97][75/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:23 time: 0.2641 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:32 - mmengine - INFO - Epoch(train) [97][80/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:22 time: 0.2638 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:34 - mmengine - INFO - Epoch(train) [97][85/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:20 time: 0.2632 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:35 - mmengine - INFO - Epoch(train) [97][90/94] base_lr: 4.0938e-04 lr: 4.0938e-04 eta: 0:01:19 time: 0.2619 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:36 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:33:36 - mmengine - INFO - Saving checkpoint at 97 epochs 09/30 15:33:38 - mmengine - INFO - Epoch(val) [97][ 5/102] eta: 0:00:24 time: 0.1228 data_time: 0.0204 memory: 11783 09/30 15:33:39 - mmengine - INFO - Epoch(val) [97][ 10/102] eta: 0:00:16 time: 0.1227 data_time: 0.0202 memory: 1697 09/30 15:33:39 - mmengine - INFO - Epoch(val) [97][ 15/102] eta: 0:00:13 time: 0.1225 data_time: 0.0199 memory: 1697 09/30 15:33:40 - mmengine - INFO - Epoch(val) [97][ 20/102] eta: 0:00:11 time: 0.1223 data_time: 0.0200 memory: 1697 09/30 15:33:40 - mmengine - INFO - Epoch(val) [97][ 25/102] eta: 0:00:10 time: 0.1222 data_time: 0.0199 memory: 1697 09/30 15:33:41 - mmengine - INFO - Epoch(val) [97][ 30/102] eta: 0:00:09 time: 0.1226 data_time: 0.0200 memory: 1697 09/30 15:33:42 - mmengine - INFO - Epoch(val) [97][ 35/102] eta: 0:00:08 time: 0.1225 data_time: 0.0198 memory: 1697 09/30 15:33:42 - mmengine - INFO - Epoch(val) [97][ 40/102] eta: 0:00:07 time: 0.1227 data_time: 0.0200 memory: 1697 09/30 15:33:43 - mmengine - INFO - Epoch(val) [97][ 45/102] eta: 0:00:07 time: 0.1229 data_time: 0.0201 memory: 1697 09/30 15:33:43 - mmengine - INFO - Epoch(val) [97][ 50/102] eta: 0:00:06 time: 0.1231 data_time: 0.0201 memory: 1697 09/30 15:33:44 - mmengine - INFO - Epoch(val) [97][ 55/102] eta: 0:00:05 time: 0.1092 data_time: 0.0065 memory: 1697 09/30 15:33:44 - mmengine - INFO - Epoch(val) [97][ 60/102] eta: 0:00:05 time: 0.1093 data_time: 0.0067 memory: 1697 09/30 15:33:45 - mmengine - INFO - Epoch(val) [97][ 65/102] eta: 0:00:04 time: 0.1095 data_time: 0.0070 memory: 1697 09/30 15:33:45 - mmengine - INFO - Epoch(val) [97][ 70/102] eta: 0:00:03 time: 0.1098 data_time: 0.0070 memory: 1697 09/30 15:33:46 - mmengine - INFO - Epoch(val) [97][ 75/102] eta: 0:00:03 time: 0.1100 data_time: 0.0070 memory: 1697 09/30 15:33:47 - mmengine - INFO - Epoch(val) [97][ 80/102] eta: 0:00:02 time: 0.1096 data_time: 0.0069 memory: 1697 09/30 15:33:47 - mmengine - INFO - Epoch(val) [97][ 85/102] eta: 0:00:02 time: 0.1099 data_time: 0.0071 memory: 1697 09/30 15:33:48 - mmengine - INFO - Epoch(val) [97][ 90/102] eta: 0:00:01 time: 0.1100 data_time: 0.0071 memory: 1697 09/30 15:33:48 - mmengine - INFO - Epoch(val) [97][ 95/102] eta: 0:00:00 time: 0.1102 data_time: 0.0071 memory: 1697 09/30 15:33:49 - mmengine - INFO - Epoch(val) [97][100/102] eta: 0:00:00 time: 0.1100 data_time: 0.0070 memory: 1697 09/30 15:33:49 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:33:49 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:33:49 - mmengine - INFO - Epoch(val) [97][102/102] data_time: 0.0134 time: 0.1164 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:33:52 - mmengine - INFO - Epoch(train) [98][ 5/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:16 time: 0.2830 data_time: 0.0348 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:53 - mmengine - INFO - Epoch(train) [98][10/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:15 time: 0.2830 data_time: 0.0347 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:54 - mmengine - INFO - Epoch(train) [98][15/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:14 time: 0.2830 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:56 - mmengine - INFO - Epoch(train) [98][20/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:12 time: 0.2827 data_time: 0.0342 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:57 - mmengine - INFO - Epoch(train) [98][25/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:11 time: 0.2828 data_time: 0.0341 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:58 - mmengine - INFO - Epoch(train) [98][30/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:09 time: 0.2829 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:33:59 - mmengine - INFO - Epoch(train) [98][35/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:08 time: 0.2830 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:01 - mmengine - INFO - Epoch(train) [98][40/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:07 time: 0.2841 data_time: 0.0336 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:02 - mmengine - INFO - Epoch(train) [98][45/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:05 time: 0.2860 data_time: 0.0337 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:03 - mmengine - INFO - Epoch(train) [98][50/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:04 time: 0.2905 data_time: 0.0338 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:05 - mmengine - INFO - Epoch(train) [98][55/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:02 time: 0.2654 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:06 - mmengine - INFO - Epoch(train) [98][60/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:01 time: 0.2658 data_time: 0.0088 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:07 - mmengine - INFO - Epoch(train) [98][65/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:01:00 time: 0.2658 data_time: 0.0093 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:09 - mmengine - INFO - Epoch(train) [98][70/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:00:58 time: 0.2659 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:10 - mmengine - INFO - Epoch(train) [98][75/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:00:57 time: 0.2659 data_time: 0.0094 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:11 - mmengine - INFO - Epoch(train) [98][80/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:00:56 time: 0.2658 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:13 - mmengine - INFO - Epoch(train) [98][85/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:00:54 time: 0.2643 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:14 - mmengine - INFO - Epoch(train) [98][90/94] base_lr: 3.0625e-04 lr: 3.0625e-04 eta: 0:00:53 time: 0.2632 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:15 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:34:15 - mmengine - INFO - Saving checkpoint at 98 epochs 09/30 15:34:18 - mmengine - INFO - Epoch(val) [98][ 5/102] eta: 0:00:22 time: 0.1218 data_time: 0.0188 memory: 11783 09/30 15:34:18 - mmengine - INFO - Epoch(val) [98][ 10/102] eta: 0:00:15 time: 0.1218 data_time: 0.0187 memory: 1697 09/30 15:34:19 - mmengine - INFO - Epoch(val) [98][ 15/102] eta: 0:00:12 time: 0.1215 data_time: 0.0185 memory: 1697 09/30 15:34:19 - mmengine - INFO - Epoch(val) [98][ 20/102] eta: 0:00:11 time: 0.1214 data_time: 0.0185 memory: 1697 09/30 15:34:20 - mmengine - INFO - Epoch(val) [98][ 25/102] eta: 0:00:10 time: 0.1213 data_time: 0.0185 memory: 1697 09/30 15:34:20 - mmengine - INFO - Epoch(val) [98][ 30/102] eta: 0:00:09 time: 0.1216 data_time: 0.0186 memory: 1697 09/30 15:34:21 - mmengine - INFO - Epoch(val) [98][ 35/102] eta: 0:00:08 time: 0.1212 data_time: 0.0182 memory: 1697 09/30 15:34:21 - mmengine - INFO - Epoch(val) [98][ 40/102] eta: 0:00:07 time: 0.1214 data_time: 0.0183 memory: 1697 09/30 15:34:22 - mmengine - INFO - Epoch(val) [98][ 45/102] eta: 0:00:06 time: 0.1215 data_time: 0.0184 memory: 1697 09/30 15:34:22 - mmengine - INFO - Epoch(val) [98][ 50/102] eta: 0:00:06 time: 0.1217 data_time: 0.0185 memory: 1697 09/30 15:34:23 - mmengine - INFO - Epoch(val) [98][ 55/102] eta: 0:00:05 time: 0.1099 data_time: 0.0067 memory: 1697 09/30 15:34:24 - mmengine - INFO - Epoch(val) [98][ 60/102] eta: 0:00:05 time: 0.1102 data_time: 0.0069 memory: 1697 09/30 15:34:24 - mmengine - INFO - Epoch(val) [98][ 65/102] eta: 0:00:04 time: 0.1105 data_time: 0.0072 memory: 1697 09/30 15:34:25 - mmengine - INFO - Epoch(val) [98][ 70/102] eta: 0:00:03 time: 0.1105 data_time: 0.0072 memory: 1697 09/30 15:34:25 - mmengine - INFO - Epoch(val) [98][ 75/102] eta: 0:00:03 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:34:26 - mmengine - INFO - Epoch(val) [98][ 80/102] eta: 0:00:02 time: 0.1104 data_time: 0.0072 memory: 1697 09/30 15:34:26 - mmengine - INFO - Epoch(val) [98][ 85/102] eta: 0:00:01 time: 0.1104 data_time: 0.0073 memory: 1697 09/30 15:34:27 - mmengine - INFO - Epoch(val) [98][ 90/102] eta: 0:00:01 time: 0.1102 data_time: 0.0073 memory: 1697 09/30 15:34:27 - mmengine - INFO - Epoch(val) [98][ 95/102] eta: 0:00:00 time: 0.1103 data_time: 0.0075 memory: 1697 09/30 15:34:28 - mmengine - INFO - Epoch(val) [98][100/102] eta: 0:00:00 time: 0.1099 data_time: 0.0073 memory: 1697 09/30 15:34:28 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:34:28 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:34:28 - mmengine - INFO - Epoch(val) [98][102/102] data_time: 0.0128 time: 0.1156 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:34:31 - mmengine - INFO - Epoch(train) [99][ 5/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:50 time: 0.2802 data_time: 0.0305 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:32 - mmengine - INFO - Epoch(train) [99][10/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:49 time: 0.2796 data_time: 0.0304 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:33 - mmengine - INFO - Epoch(train) [99][15/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:47 time: 0.2796 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:35 - mmengine - INFO - Epoch(train) [99][20/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:46 time: 0.2789 data_time: 0.0299 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:36 - mmengine - INFO - Epoch(train) [99][25/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:45 time: 0.2788 data_time: 0.0298 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:37 - mmengine - INFO - Epoch(train) [99][30/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:43 time: 0.2787 data_time: 0.0299 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:39 - mmengine - INFO - Epoch(train) [99][35/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:42 time: 0.2793 data_time: 0.0296 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:40 - mmengine - INFO - Epoch(train) [99][40/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:41 time: 0.2806 data_time: 0.0299 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:41 - mmengine - INFO - Epoch(train) [99][45/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:39 time: 0.2818 data_time: 0.0300 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:43 - mmengine - INFO - Epoch(train) [99][50/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:38 time: 0.2860 data_time: 0.0302 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:44 - mmengine - INFO - Epoch(train) [99][55/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:36 time: 0.2655 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:45 - mmengine - INFO - Epoch(train) [99][60/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:35 time: 0.2651 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:47 - mmengine - INFO - Epoch(train) [99][65/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:34 time: 0.2657 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:48 - mmengine - INFO - Epoch(train) [99][70/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:32 time: 0.2663 data_time: 0.0098 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:49 - mmengine - INFO - Epoch(train) [99][75/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:31 time: 0.2663 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:50 - mmengine - INFO - Epoch(train) [99][80/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:29 time: 0.2662 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:52 - mmengine - INFO - Epoch(train) [99][85/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:28 time: 0.2643 data_time: 0.0096 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:53 - mmengine - INFO - Epoch(train) [99][90/94] base_lr: 2.0313e-04 lr: 2.0313e-04 eta: 0:00:27 time: 0.2633 data_time: 0.0095 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:34:54 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:34:54 - mmengine - INFO - Saving checkpoint at 99 epochs 09/30 15:34:57 - mmengine - INFO - Epoch(val) [99][ 5/102] eta: 0:00:22 time: 0.1224 data_time: 0.0198 memory: 11783 09/30 15:34:57 - mmengine - INFO - Epoch(val) [99][ 10/102] eta: 0:00:15 time: 0.1223 data_time: 0.0196 memory: 1697 09/30 15:34:58 - mmengine - INFO - Epoch(val) [99][ 15/102] eta: 0:00:13 time: 0.1220 data_time: 0.0192 memory: 1697 09/30 15:34:58 - mmengine - INFO - Epoch(val) [99][ 20/102] eta: 0:00:11 time: 0.1222 data_time: 0.0192 memory: 1697 09/30 15:34:59 - mmengine - INFO - Epoch(val) [99][ 25/102] eta: 0:00:10 time: 0.1219 data_time: 0.0192 memory: 1697 09/30 15:34:59 - mmengine - INFO - Epoch(val) [99][ 30/102] eta: 0:00:09 time: 0.1222 data_time: 0.0193 memory: 1697 09/30 15:35:00 - mmengine - INFO - Epoch(val) [99][ 35/102] eta: 0:00:08 time: 0.1221 data_time: 0.0191 memory: 1697 09/30 15:35:00 - mmengine - INFO - Epoch(val) [99][ 40/102] eta: 0:00:07 time: 0.1220 data_time: 0.0190 memory: 1697 09/30 15:35:01 - mmengine - INFO - Epoch(val) [99][ 45/102] eta: 0:00:07 time: 0.1220 data_time: 0.0190 memory: 1697 09/30 15:35:02 - mmengine - INFO - Epoch(val) [99][ 50/102] eta: 0:00:06 time: 0.1221 data_time: 0.0190 memory: 1697 09/30 15:35:02 - mmengine - INFO - Epoch(val) [99][ 55/102] eta: 0:00:05 time: 0.1095 data_time: 0.0065 memory: 1697 09/30 15:35:03 - mmengine - INFO - Epoch(val) [99][ 60/102] eta: 0:00:05 time: 0.1095 data_time: 0.0066 memory: 1697 09/30 15:35:03 - mmengine - INFO - Epoch(val) [99][ 65/102] eta: 0:00:04 time: 0.1098 data_time: 0.0070 memory: 1697 09/30 15:35:04 - mmengine - INFO - Epoch(val) [99][ 70/102] eta: 0:00:03 time: 0.1095 data_time: 0.0069 memory: 1697 09/30 15:35:04 - mmengine - INFO - Epoch(val) [99][ 75/102] eta: 0:00:03 time: 0.1096 data_time: 0.0070 memory: 1697 09/30 15:35:05 - mmengine - INFO - Epoch(val) [99][ 80/102] eta: 0:00:02 time: 0.1096 data_time: 0.0069 memory: 1697 09/30 15:35:05 - mmengine - INFO - Epoch(val) [99][ 85/102] eta: 0:00:01 time: 0.1097 data_time: 0.0071 memory: 1697 09/30 15:35:06 - mmengine - INFO - Epoch(val) [99][ 90/102] eta: 0:00:01 time: 0.1102 data_time: 0.0072 memory: 1697 09/30 15:35:06 - mmengine - INFO - Epoch(val) [99][ 95/102] eta: 0:00:00 time: 0.1102 data_time: 0.0073 memory: 1697 09/30 15:35:07 - mmengine - INFO - Epoch(val) [99][100/102] eta: 0:00:00 time: 0.1101 data_time: 0.0072 memory: 1697 09/30 15:35:07 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:35:07 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:35:07 - mmengine - INFO - Epoch(val) [99][102/102] data_time: 0.0129 time: 0.1159 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( 09/30 15:35:10 - mmengine - INFO - Epoch(train) [100][ 5/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:24 time: 0.2851 data_time: 0.0352 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:11 - mmengine - INFO - Epoch(train) [100][10/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:23 time: 0.2851 data_time: 0.0352 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:13 - mmengine - INFO - Epoch(train) [100][15/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:21 time: 0.2850 data_time: 0.0347 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:14 - mmengine - INFO - Epoch(train) [100][20/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:20 time: 0.2848 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:15 - mmengine - INFO - Epoch(train) [100][25/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:19 time: 0.2849 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:17 - mmengine - INFO - Epoch(train) [100][30/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:17 time: 0.2849 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:18 - mmengine - INFO - Epoch(train) [100][35/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:16 time: 0.2851 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:19 - mmengine - INFO - Epoch(train) [100][40/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:14 time: 0.2861 data_time: 0.0344 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:21 - mmengine - INFO - Epoch(train) [100][45/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:13 time: 0.2878 data_time: 0.0345 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:22 - mmengine - INFO - Epoch(train) [100][50/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:12 time: 0.2919 data_time: 0.0347 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:23 - mmengine - INFO - Epoch(train) [100][55/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:10 time: 0.2662 data_time: 0.0090 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:25 - mmengine - INFO - Epoch(train) [100][60/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:09 time: 0.2660 data_time: 0.0089 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:26 - mmengine - INFO - Epoch(train) [100][65/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:08 time: 0.2660 data_time: 0.0097 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:27 - mmengine - INFO - Epoch(train) [100][70/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:06 time: 0.2668 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:29 - mmengine - INFO - Epoch(train) [100][75/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:05 time: 0.2663 data_time: 0.0100 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:30 - mmengine - INFO - Epoch(train) [100][80/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:03 time: 0.2657 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:31 - mmengine - INFO - Epoch(train) [100][85/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:02 time: 0.2642 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:32 - mmengine - INFO - Epoch(train) [100][90/94] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 0:00:01 time: 0.2631 data_time: 0.0099 memory: 11783 grad_norm: nan loss: nan loss_cls: nan loss_bbox: 0.0000 loss_centerness: 0.0000 09/30 15:35:33 - mmengine - INFO - Exp name: dynamicvis_b_levirship_mamba_20260930_142938 09/30 15:35:33 - mmengine - INFO - Saving checkpoint at 100 epochs 09/30 15:35:36 - mmengine - INFO - Epoch(val) [100][ 5/102] eta: 0:00:22 time: 0.1222 data_time: 0.0194 memory: 11783 09/30 15:35:36 - mmengine - INFO - Epoch(val) [100][ 10/102] eta: 0:00:15 time: 0.1219 data_time: 0.0191 memory: 1697 09/30 15:35:37 - mmengine - INFO - Epoch(val) [100][ 15/102] eta: 0:00:12 time: 0.1217 data_time: 0.0188 memory: 1697 09/30 15:35:38 - mmengine - INFO - Epoch(val) [100][ 20/102] eta: 0:00:11 time: 0.1219 data_time: 0.0188 memory: 1697 09/30 15:35:38 - mmengine - INFO - Epoch(val) [100][ 25/102] eta: 0:00:10 time: 0.1218 data_time: 0.0187 memory: 1697 09/30 15:35:39 - mmengine - INFO - Epoch(val) [100][ 30/102] eta: 0:00:09 time: 0.1217 data_time: 0.0187 memory: 1697 09/30 15:35:39 - mmengine - INFO - Epoch(val) [100][ 35/102] eta: 0:00:08 time: 0.1212 data_time: 0.0185 memory: 1697 09/30 15:35:40 - mmengine - INFO - Epoch(val) [100][ 40/102] eta: 0:00:07 time: 0.1212 data_time: 0.0185 memory: 1697 09/30 15:35:40 - mmengine - INFO - Epoch(val) [100][ 45/102] eta: 0:00:06 time: 0.1213 data_time: 0.0186 memory: 1697 09/30 15:35:41 - mmengine - INFO - Epoch(val) [100][ 50/102] eta: 0:00:06 time: 0.1215 data_time: 0.0187 memory: 1697 09/30 15:35:41 - mmengine - INFO - Epoch(val) [100][ 55/102] eta: 0:00:05 time: 0.1094 data_time: 0.0065 memory: 1697 09/30 15:35:42 - mmengine - INFO - Epoch(val) [100][ 60/102] eta: 0:00:05 time: 0.1096 data_time: 0.0068 memory: 1697 09/30 15:35:42 - mmengine - INFO - Epoch(val) [100][ 65/102] eta: 0:00:04 time: 0.1100 data_time: 0.0072 memory: 1697 09/30 15:35:43 - mmengine - INFO - Epoch(val) [100][ 70/102] eta: 0:00:03 time: 0.1101 data_time: 0.0073 memory: 1697 09/30 15:35:44 - mmengine - INFO - Epoch(val) [100][ 75/102] eta: 0:00:03 time: 0.1103 data_time: 0.0074 memory: 1697 09/30 15:35:44 - mmengine - INFO - Epoch(val) [100][ 80/102] eta: 0:00:02 time: 0.1102 data_time: 0.0074 memory: 1697 09/30 15:35:45 - mmengine - INFO - Epoch(val) [100][ 85/102] eta: 0:00:01 time: 0.1104 data_time: 0.0075 memory: 1697 09/30 15:35:45 - mmengine - INFO - Epoch(val) [100][ 90/102] eta: 0:00:01 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 15:35:46 - mmengine - INFO - Epoch(val) [100][ 95/102] eta: 0:00:00 time: 0.1107 data_time: 0.0076 memory: 1697 09/30 15:35:46 - mmengine - INFO - Epoch(val) [100][100/102] eta: 0:00:00 time: 0.1107 data_time: 0.0075 memory: 1697 09/30 15:35:47 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:35:47 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:35:47 - mmengine - INFO - Epoch(val) [100][102/102] data_time: 0.0129 time: 0.1160 /marimo/dynamicvis-blackwell-venv/lib/python3.11/site-packages/mmengine/hooks/early_stopping_hook.py:148: UserWarning: Skip early stopping process since the evaluation results (dict_keys([])) do not include `monitor` (coco/bbox_mAP). warnings.warn( loading annotations into memory... Done (t=0.15s) creating index... index created! loading annotations into memory... Done (t=0.11s) creating index... index created! 09/30 15:35:50 - mmengine - INFO - Epoch(test) [ 5/102] eta: 0:00:42 time: 0.4380 data_time: 0.3015 memory: 1697 09/30 15:35:51 - mmengine - INFO - Epoch(test) [ 10/102] eta: 0:00:25 time: 0.2748 data_time: 0.1542 memory: 1697 09/30 15:35:51 - mmengine - INFO - Epoch(test) [ 15/102] eta: 0:00:19 time: 0.2189 data_time: 0.1045 memory: 1697 09/30 15:35:52 - mmengine - INFO - Epoch(test) [ 20/102] eta: 0:00:15 time: 0.1917 data_time: 0.0802 memory: 1697 09/30 15:35:52 - mmengine - INFO - Epoch(test) [ 25/102] eta: 0:00:13 time: 0.1756 data_time: 0.0658 memory: 1697 09/30 15:35:53 - mmengine - INFO - Epoch(test) [ 30/102] eta: 0:00:11 time: 0.1648 data_time: 0.0562 memory: 1697 09/30 15:35:53 - mmengine - INFO - Epoch(test) [ 35/102] eta: 0:00:10 time: 0.1572 data_time: 0.0491 memory: 1697 09/30 15:35:54 - mmengine - INFO - Epoch(test) [ 40/102] eta: 0:00:09 time: 0.1517 data_time: 0.0440 memory: 1697 09/30 15:35:54 - mmengine - INFO - Epoch(test) [ 45/102] eta: 0:00:08 time: 0.1472 data_time: 0.0400 memory: 1697 09/30 15:35:55 - mmengine - INFO - Epoch(test) [ 50/102] eta: 0:00:07 time: 0.1435 data_time: 0.0368 memory: 1697 09/30 15:35:55 - mmengine - INFO - Epoch(test) [ 55/102] eta: 0:00:06 time: 0.1107 data_time: 0.0074 memory: 1697 09/30 15:35:56 - mmengine - INFO - Epoch(test) [ 60/102] eta: 0:00:05 time: 0.1106 data_time: 0.0075 memory: 1697 09/30 15:35:57 - mmengine - INFO - Epoch(test) [ 65/102] eta: 0:00:05 time: 0.1110 data_time: 0.0078 memory: 1697 09/30 15:35:57 - mmengine - INFO - Epoch(test) [ 70/102] eta: 0:00:04 time: 0.1113 data_time: 0.0079 memory: 1697 09/30 15:35:58 - mmengine - INFO - Epoch(test) [ 75/102] eta: 0:00:03 time: 0.1113 data_time: 0.0079 memory: 1697 09/30 15:35:58 - mmengine - INFO - Epoch(test) [ 80/102] eta: 0:00:02 time: 0.1114 data_time: 0.0078 memory: 1697 09/30 15:35:59 - mmengine - INFO - Epoch(test) [ 85/102] eta: 0:00:02 time: 0.1113 data_time: 0.0080 memory: 1697 09/30 15:35:59 - mmengine - INFO - Epoch(test) [ 90/102] eta: 0:00:01 time: 0.1110 data_time: 0.0079 memory: 1697 09/30 15:36:00 - mmengine - INFO - Epoch(test) [ 95/102] eta: 0:00:00 time: 0.1114 data_time: 0.0080 memory: 1697 09/30 15:36:00 - mmengine - INFO - Epoch(test) [100/102] eta: 0:00:00 time: 0.1113 data_time: 0.0079 memory: 1697 09/30 15:36:01 - mmengine - INFO - Evaluating bbox... Loading and preparing results... 09/30 15:36:01 - mmengine - ERROR - /marimo/DynamicVis/mmdet/evaluation/metrics/coco_metric.py - compute_metrics - 467 - The testing results of the whole dataset is empty. 09/30 15:36:01 - mmengine - INFO - Epoch(test) [102/102] data_time: 0.0221 time: 0.1271 Processing Files (0 / 0) : | | 0.00B / 0.00B New Data Upload : | | 0.00B / 0.00B  ...rson_mosaic/epoch_100.pth: 13%|█▎ | 67.1MB / 533MB  ...rson_mosaic/epoch_100.pth: 13%|█▎ | 67.1MB / 533MB  Processing Files (0 / 4) : 12%|█▏ | 67.1MB / 570MB, ???B/s New Data Upload : 100%|█████████▉| 67.1MB / 67.1MB, ???B/s  ...set/annotations/test.json: 98%|█████████▊| 12.9MB / 13.1MB  ...et/annotations/train.json: 99%|█████████▊| 10.7MB / 10.9MB  ...aset/annotations/val.json: 98%|█████████▊| 12.9MB / 13.1MB  ...rson_mosaic/epoch_100.pth: 53%|█████▎ | 284MB / 533MB  ...set/annotations/test.json: 98%|█████████▊| 12.9MB / 13.1MB  ...et/annotations/train.json: 99%|█████████▊| 10.7MB / 10.9MB  ...aset/annotations/val.json: 98%|█████████▊| 12.9MB / 13.1MB  Processing Files (0 / 4) : 56%|█████▋ | 321MB / 570MB, ???B/s New Data Upload : 100%|██████████| 268MB / 268MB, ???B/s  ...rson_mosaic/epoch_100.pth: 81%|████████▏ | 434MB / 533MB  ...set/annotations/test.json: 98%|█████████▊| 12.9MB / 13.1MB  ...et/annotations/train.json: 99%|█████████▊| 10.7MB / 10.9MB  ...aset/annotations/val.json: 98%|█████████▊| 12.9MB / 13.1MB  Processing Files (0 / 4) : 83%|████████▎ | 471MB / 570MB, 45.3MB/s New Data Upload : 86%|████████▌ | 403MB / 470MB, 38.8MB/s  ...rson_mosaic/epoch_100.pth: 97%|█████████▋| 518MB / 533MB  ...set/annotations/test.json: 100%|██████████| 13.1MB / 13.1MB  ...et/annotations/train.json: 100%|██████████| 10.9MB / 10.9MB  ...aset/annotations/val.json: 100%|██████████| 13.1MB / 13.1MB  Processing Files (3 / 4) : 97%|█████████▋| 555MB / 570MB, 52.4MB/s New Data Upload : 100%|██████████| 471MB / 471MB, 44.5MB/s  Processing Files (3 / 4) : 97%|█████████▋| 555MB / 570MB, 52.4MB/s New Data Upload : 100%|██████████| 471MB / 471MB, 44.5MB/s ...rson_mosaic/epoch_100.pth: 97%|█████████▋| 518MB / 533MB ...set/annotations/test.json: 100%|██████████| 13.1MB / 13.1MB ...et/annotations/train.json: 100%|██████████| 10.9MB / 10.9MB ...aset/annotations/val.json: 100%|██████████| 13.1MB / 13.1MB