Open Andrevmatias opened 3 years ago
Hi, sorry, for super late reply. Where you using Windows?
No, we were using Google Collab Notebooks (Ubuntu 18.04.3 LTS 64-bit).
w32 & w48 not work, either.
PyTorch 1.12, Python 3.9 on Paperspace
learn = get_segmentation_learner(dls=dls, number_classes=2, segmentation_type="Semantic Segmentation",
architecture_name="hrnet", backbone_name="hrnet_w32",
splitter=segmentron_splitter,
loss_func=CustomLoss(),
metrics=[Dice, foreground_acc, JaccardCoeff],
wd=1e-3).to_fp16()
RuntimeError Traceback (most recent call last)
File /usr/local/lib/python3.9/dist-packages/semtorch/models/archs/backbones/build.py:51, in load_backbone_pretrained(model, backbone)
49 weights_path = download(model_urls[backbone], path=weights_path)
---> 51 msg = model.init_weights(pretrained=weights_path)
52 else:
File /usr/local/lib/python3.9/dist-packages/semtorch/models/archs/backbones/hrnet.py:475, in HighResolutionNet.init_weights(self, pretrained)
474 model_dict.update(pretrained_dict)
--> 475 self.load_state_dict(model_dict)
476 return "HRNet backbone wieghts loaded"
File /usr/local/lib/python3.9/dist-packages/torch/nn/modules/module.py:1604, in Module.load_state_dict(self, state_dict, strict)
1603 if len(error_msgs) > 0:
-> 1604 raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
1605 self.__class__.__name__, "\n\t".join(error_msgs)))
1606 return _IncompatibleKeys(missing_keys, unexpected_keys)
complete error message. hrnet-w32-error.txt
After deleting the previous cache file, the notebook can load the hrnet_w32 weights. It seems the PTH cache will always be ~/.cache/torch/checkpoints
.
With
get_segmentation_learner(architecture_name='hrnet', backbone_name='hrnet_w18')
.Using the following callback to save the models during training:
SaveModelCallback(monitor='dice_multi', fname='best_model', with_opt=True)
The results of the predictions after loading "best_model.pth" withlearner.load
are zero-filled masks.The prediction using the learner right after training are correct.