Issue
I am writing a python code in Kaggle notebook for Image Classification. In the training part, I am getting an error
AttributeError Traceback (most recent call last)
<ipython-input-22-052723d8ce9d> in <module>
5 test_loss = 0.0
6 for images,label in enumerate(train_loader):
----> 7 images,label = images.to(cuda),label.to(cuda)
8 optimizer.zero_grad()
9
AttributeError: 'int' object has no attribute 'to'
This is the following code, (I am giving only 2 parts, pls tell if you need more)
train_loader = torch.utils.data.DataLoader(train_data,batch_size = 128,num_workers =0,shuffle =True)
test_loader = torch.utils.data.DataLoader(test_data,batch_size = 64,num_workers =0,shuffle =False)
epoch = 10
for e in range(epoch):
train_loss = 0.0
test_loss = 0.0
for images,label in enumerate(train_loader):
images,label = images.to(cuda),label.to(cuda)
optimizer.zero_grad()
output = model(images)
_,predict = torch.max(output.data, 1)
loss = criterion(output,labels)
loss.backward()
optimizer.step()
train_loss += loss.item()
train_size += label.size(0)
train_success += (predict==label).sum().item()
print("train_accuracy is {.2f}".format(100*(train_success/train_size)) )
Solution
I don't know much about the environment you're working in, but this is what goes wrong:
for images, label in enumerate (train_loader):
Puts whatever is in train_loader into label
, while images
is given a number.
Try this to see what I mean, and to see what goes wrong:
for images, label in enumerate(train_loader):
print(images)
return
And since images
is a number (int), there is no images.to()
method associated with images
Answered By - Ayam
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