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0-sized dataset produces an error when given to DataLoader #206

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0-sized dataset produces an error when given to DataLoader #206

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0-sized dataset produces an error when given to DataLoader
psteinb Mar 4, 2020
f9dd7b1
0-sized dataset produces an error when given to DataLoader
psteinb Mar 4, 2020
6bc4f64
Merge branch 'comment_custom_dataloader' of github.com:psteinb/pytorc…
psteinb Mar 4, 2020
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14 changes: 8 additions & 6 deletions tutorials/01-basics/pytorch_basics/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -137,7 +137,7 @@
class CustomDataset(torch.utils.data.Dataset):
def __init__(self):
# TODO
# 1. Initialize file paths or a list of file names.
# 1. Initialize file paths or a list of file names.
pass
def __getitem__(self, index):
# TODO
Expand All @@ -146,13 +146,15 @@ def __getitem__(self, index):
# 3. Return a data pair (e.g. image and label).
pass
def __len__(self):
# You should change 0 to the total size of your dataset.
return 0
# You should change 0 to something unequal to 0
# (e.g. the total size of your dataset),
# if you want this file to run without errors
return 0

# You can then use the prebuilt data loader.
# You can then use the prebuilt data loader.
custom_dataset = CustomDataset()
train_loader = torch.utils.data.DataLoader(dataset=custom_dataset,
batch_size=64,
batch_size=64,
shuffle=True)


Expand All @@ -167,7 +169,7 @@ def __len__(self):
for param in resnet.parameters():
param.requires_grad = False

# Replace the top layer for finetuning.
# Replace the top layer for finetuning.??
resnet.fc = nn.Linear(resnet.fc.in_features, 100) # 100 is an example.

# Forward pass.
Expand Down