TypeError: 'int' object is not callable for claculating training accuracy

vision
1

i am using a 3D cnn for feature extraction and svm as a classifier and I am trying to calculate the acuuracy of my training
this is the logique for feature extraction and classification

def train_epoch(model, svm_classifier, train_loader, epoch,device):
    model.eval()  # Use ResNet in evaluation mode for feature extraction
    all_features = []
    all_labels = []

    for images, labels in train_loader:
        images = images.to(device)
        
        with torch.no_grad():  # Extract features without gradients
            features = model(images)
           
        all_features.append(features.cpu().numpy())
        all_labels.append(labels.cpu().numpy())

    # Convert features and labels to numpy arrays for SVM training
    all_features = np.concatenate(all_features, axis=0)
    all_labels = np.concatenate(all_labels, axis=0)

    # Shuffle and train SVM with extracted features
    all_features, all_labels = shuffle(all_features, all_labels)
    svm_classifier.fit(all_features, all_labels)

        # Predict on the training data
    train_predictions = svm_classifier.predict(all_features)
    
    # Calculate training accuracy
    train_accuracy = calculate_accuracy(all_labels, train_predictions)
    print(f"Epoch [{epoch}] - SVM training complete. Training accuracy: {train_accuracy * 100:.2f}%")

and for the accuracy calculation function i used this

`def calculate_accuracy(outputs, targets):
    with torch.no_grad():
        batch_size = targets.size(0)

        _, pred = outputs.topk(1, 1, largest=True, sorted=True)
        pred = pred.t()
        correct = pred.eq(targets.view(1, -1))
        n_correct_elems = correct.float().sum().item()

 return n_correct_elems / batch_size`

then this error occured

batch_size = targets.size(0)
^^^^^^^^^^^^^^^
TypeError: ‘int’ object is not callable
is it because I changed the tensors int np arrays ?

2

Yes, as seen here:

targets = torch.randn(10, 10)

# works
batch_size = targets.size(0)
print(batch_size)
# 10

# fails
targets = targets.numpy()
batch_size = targets.size(0)
# TypeError: 'int' object is not callable

# works but prints the number of elements
batch_size = targets.size
print(batch_size)
# 100

# works
batch_size = targets.shape[0]
print(batch_size)
# 10