Hi, I’m re-training an inception_v3 using a remote GPU with CUDA device.
I used these transforms for my dataset

train_set = datasets.ImageFolder(
root = “liG”,
transform = transforms.Compose([transforms.ToTensor(),
transforms.RandomRotation(20),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
transforms.Resize(299)]
))
data_loader= torch.utils.data.DataLoader(train_set,
batch_size=5,
shuffle=True,
num_workers=2)
Below is the cell that raises the error:
for X, y in data_loader:
print("Shape of X [N, C, H, W]: ", X.shape)
print("Shape of y: ", y.shape, y.dtype)
break

The error I’m getting is:

TypeError: Caught TypeError in DataLoader worker process 0.
Original Traceback (most recent call last):
File “/opt/conda/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py”, line 202, in _worker_loop
data = fetcher.fetch(index)
File “/opt/conda/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py”, line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File “/opt/conda/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py”, line 44, in 
data = [self.dataset[idx] for idx in possibly_batched_index]
File “/opt/conda/lib/python3.8/site-packages/torchvision/datasets/folder.py”, line 171, in getitem
sample = self.transform(sample)
File “/opt/conda/lib/python3.8/site-packages/torchvision/transforms/transforms.py”, line 60, in call
img = t(img)
File “/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py”, line 881, in _call_impl
result = self.forward(*input, **kwargs)
File “/opt/conda/lib/python3.8/site-packages/torchvision/transforms/transforms.py”, line 1236, in forward
fill = [float(f) for f in fill]
TypeError: ‘NoneType’ object is not iterable