How to print the target values using dataloader

vision
1 
          for i, (inputs, targets) in enumerate(data_loader):
        
 
                    with torch.no_grad():
                           inputs = Variable(inputs)
                           targets = Variable(targets)
                           print("targets.data", targets.item())

It doesn’t seem to be giving the target value.

2

What does the print statement show instead?

3

It is printing the index numbers: targets.data tensor([0, 1, 2, 3, 4, 5]), if I print(target)

it gives error:
print(“targets.data”, targets.item())
ValueError: only one element tensors can be converted to Python scalars

, if I print( targets.item())

4

.item() works only on one-element tensors.
What is wrong about print(target)?

5

It seems to print the index not the values

6

Maybe these values are equal to the indices for the current batch.
Could you set shuffle=True in your DataLoader and run your code again or alternatively check the output for multiple target tensors?

7

I used shuffle= True, I get the output as tensor([ 1192, 6908, 1663, 2771, 7581, 10296])

The class ranges from 1 to 84.
Total length if data is 10364

8

Could you post the code for your Dataset?

9 
        data_loader = torch.utils.data.DataLoader(
        test_data,
        batch_size=opt.batch_size,
        shuffle=True,
        num_workers=opt.n_threads,
        pin_memory=True)
    test.test(data_loader, model, opt, test_data.class_names,criterion,test_logger)
    print("done")

test.py looks like:

 for i, (inputs, targets) in enumerate(data_loader):

    with torch.no_grad():
        inputs = Variable(inputs)
        targets = Variable(targets)
        print("targets.data", targets)
        outputs = model(inputs)
10

Could you post the code of test_data, so that we could have a look how your targets are created?