Hi, I have created a WandB report that is attached to the issue that outlines the exact model and loss logs of the model.
WB_report.pdf
The model I am using is Swin transfomer with Cascade RCNN. From what I deduce, it seems that one of my checkpoints is not being loaded.
It seems that the backbones checkpoint is not being loaded - but the detector can be easily loaded.
Additionally, I have a dataset of about 5K images - divided into 3 classes. The Batch Size = 8; It may be overfitting, maybe not. I can't diagnose the problems 😢
I might also be interpreting the model checkpoints incorrectly; I think that the checkpoints here should be for the whole model?
Some errors:-
Interestingly enough,
2021-10-01 22:08:13,462 - mmdet - INFO - Set random seed to 42, deterministic: True
2021-10-01 22:08:14,210 - mmdet - INFO - load model from: /kaggle/working/checkpoints/cascade_mask_rcnn_swin_small_patch4_window7.pth
Traceback (most recent call last):
File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/registry.py", line 52, in build_from_cfg
return obj_cls(**args)
File "/kaggle/working/Swin-Transformer-Object-Detection/mmdet/models/detectors/cascade_rcnn.py", line 25, in __init__
pretrained=pretrained)
File "/kaggle/working/Swin-Transformer-Object-Detection/mmdet/models/detectors/two_stage.py", line 48, in __init__
self.init_weights(pretrained=pretrained)
File "/kaggle/working/Swin-Transformer-Object-Detection/mmdet/models/detectors/two_stage.py", line 68, in init_weights
self.backbone.init_weights(pretrained=pretrained)
File "/kaggle/working/Swin-Transformer-Object-Detection/mmdet/models/backbones/swin_transformer.py", line 594, in init_weights
load_checkpoint(self, pretrained, strict=False, logger=logger)
File "/kaggle/working/Swin-Transformer-Object-Detection/mmcv_custom/checkpoint.py", line 340, in load_checkpoint
table_current = model.state_dict()[table_key]
KeyError: 'backbone.layers.0.blocks.0.attn.relative_position_bias_table'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "tools/train.py", line 187, in <module>
main()
File "tools/train.py", line 161, in main
test_cfg=cfg.get('test_cfg'))
File "/kaggle/working/Swin-Transformer-Object-Detection/mmdet/models/builder.py", line 77, in build_detector
return build(cfg, DETECTORS, dict(train_cfg=train_cfg, test_cfg=test_cfg))
File "/kaggle/working/Swin-Transformer-Object-Detection/mmdet/models/builder.py", line 34, in build
return build_from_cfg(cfg, registry, default_args)
File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/registry.py", line 55, in build_from_cfg
raise type(e)(f'{obj_cls.__name__}: {e}')
KeyError: "CascadeRCNN: 'backbone.layers.0.blocks.0.attn.relative_position_bias_table'"
it seems that even if I set load_from and model/pre_trained the same checkpoint path, it errors out. Perhaps I am trying the wrong combinations?
Hi, I have created a WandB report that is attached to the issue that outlines the exact model and loss logs of the model. WB_report.pdf
The model I am using is Swin transfomer with Cascade RCNN. From what I deduce, it seems that one of my checkpoints is not being loaded.
It seems that the
backbone
s checkpoint is not being loaded - but the detector can be easily loaded.Additionally, I have a dataset of about 5K images - divided into 3 classes. The Batch Size = 8; It may be overfitting, maybe not. I can't diagnose the problems 😢
I might also be interpreting the model checkpoints incorrectly; I think that the checkpoints here should be for the whole model?
Some errors:-
Interestingly enough,
it seems that even if I set
load_from
andmodel/pre_trained
the same checkpoint path, it errors out. Perhaps I am trying the wrong combinations?Config File:-