Hi everyone. I’m trying to load a pre-trained model and see its accuracy for a small apple diseases dataset:
import torch
import torchvision
import torchvision.transforms as transforms
from torchvision import datasets, models

transform = transforms.Compose(
    [transforms.ToTensor(),
     transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])

testset = torchvision.datasets.ImageFolder('data/', transform=transforms)     
testloader = torch.utils.data.DataLoader(testset, batch_size=4, shuffle=True, num_workers=2)

"""testset = torchvision.datasets.CIFAR10(root='./data', train=False,
                                       download=True, transform=transform)
testloader = torch.utils.data.DataLoader(testset, batch_size=4,
                                         shuffle=False, num_workers=2)"""

classes = ('Folha Desfolha Precoce', 'Folha Glifosato', 'Folha Magnésio', 'Folha Potássio',
           'Folha Sadia Gala', 'Fruto Alternaria', 'Fruto Bitter Pit', 'Fruto Bitter Pit', 'Fruto Colletotrichum', 
           'Fruto Penicillium')

device = torch.device('cpu')
net = torch.load('applesnet/main.pt', map_location=device)
net.eval()

The problem is when I try to run the code below to measure the accuracy, I get the error
message “TypeError: ‘module’ object is not callable”:
correct = 0
total = 0
with torch.no_grad():
    
    for data in testloader: 
        images, labels = data
        outputs = net(images)
        _, predicted = torch.max(outputs.data, 1)
        total += labels.size(0)
        correct += (predicted == labels).sum().item()

print('Accuracy of the network on the test images: %d %%' % (
    100 * correct / total))

TypeError                                 Traceback (most recent call last)
<ipython-input-10-bc22d0ffcea3> in <module>
      3 with torch.no_grad():
      4 
----> 5     for data in testloader:
      6         images, labels = data
      7         outputs = net(images)

~/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py in __next__(self)
    635                 self.reorder_dict[idx] = batch
    636                 continue
--> 637             return self._process_next_batch(batch)
    638 
    639     next = __next__  # Python 2 compatibility

~/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py in _process_next_batch(self, batch)
    656         self._put_indices()
    657         if isinstance(batch, ExceptionWrapper):
--> 658             raise batch.exc_type(batch.exc_msg)
    659         return batch
    660 

TypeError: Traceback (most recent call last):
  File "/home/gustavo/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 138, in _worker_loop
    samples = collate_fn([dataset[i] for i in batch_indices])
  File "/home/gustavo/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 138, in <listcomp>
    samples = collate_fn([dataset[i] for i in batch_indices])
  File "/home/gustavo/anaconda3/lib/python3.7/site-packages/torchvision/datasets/folder.py", line 103, in __getitem__
    sample = self.transform(sample)
TypeError: 'module' object is not callable

The most strange thing is, when I use the CIFAR-10 dataset instead of this particular dataset, I don’t get this error message.