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Using cache found in C:\Users\Administrator/.cache\torch\hub\pytorch_vision_v0.6.0
f:\anaconda3\Lib\site-packages\torchvision\models_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
warnings.warn(
f:\anaconda3\Lib\site-packages\torchvision\models_utils.py:223: UserWarning: Arguments other than a weight enum or None for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing weights=DenseNet201_Weights.IMAGENET1K_V1. You can also use weights=DenseNet201_Weights.DEFAULT to get the most up-to-date weights.
warnings.warn(msg)
Generate LMDB to train_deepgaze3\lmdb_cache\SALICON_train
Output exceeds the size limit. Open the full output data in a text editor
Could you post the entire error message? The ... indicates that part of the message is missing. Also, could you format it as a code block (by clicking the <>-button at the top of the GitHub text editor)?
Using cache found in C:\Users\Administrator/.cache\torch\hub\pytorch_vision_v0.6.0
f:\anaconda3\Lib\site-packages\torchvision\models_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
warnings.warn(
f:\anaconda3\Lib\site-packages\torchvision\models_utils.py:223: UserWarning: Arguments other than a weight enum or
None
for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passingweights=DenseNet201_Weights.IMAGENET1K_V1
. You can also useweights=DenseNet201_Weights.DEFAULT
to get the most up-to-date weights.warnings.warn(msg)
Generate LMDB to train_deepgaze3\lmdb_cache\SALICON_train
Output exceeds the size limit. Open the full output data in a text editor
Error Traceback (most recent call last)
Cell In[12], line 1
----> 1 train_loader = prepare_spatial_dataset(SALICON_train_stimuli, SALICON_train_fixations, SALICON_centerbias, batch_size=4, path=train_directory / 'lmdb_cache' / 'SALICON_train')
2 validation_loader = prepare_spatial_dataset(SALICON_val_stimuli, SALICON_val_fixations, SALICON_centerbias, batch_size=4, path=train_directory / 'lmdb_cache' / 'SALICON_val')
Cell In[4], line 8, in prepare_spatial_dataset(stimuli, fixations, centerbias, batch_size, path)
5 else:
6 lmdb_path = None
----> 8 dataset = ImageDataset(
9 stimuli=stimuli,
10 fixations=fixations,
11 centerbias_model=centerbias,
12 transform=FixationMaskTransform(sparse=False),
13 average='image',
14 lmdb_path=lmdb_path,
15 )
17 loader = torch.utils.data.DataLoader(
18 dataset,
19 batch_sampler=ImageDatasetSampler(dataset, batch_size=batch_size),
20 pin_memory=False,
21 num_workers=0,
22 )
24 return loader
...
345 txn = db.begin(write=True)
346 for idx, stimulus in enumerate(tqdm(stimuli)):
Error: train_deepgaze3\lmdb_cache\SALICON_train: ���̿ռ䲻�㡣
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