def extract_features()

in utils.py [0:0]

• 15 lines of code
• 3 McCabe index (conditional complexity)

def extract_features(extr, device, data_loader):
    extr.eval()
    features = None
    labels = None
    with torch.no_grad():
        for batch_idx, (data, target) in enumerate(data_loader):
            data, target = data.to(device), target.to(device)
            output = extr(data).data.cpu()
            if features is None:
                features = output.squeeze()
                labels = target
            else:
                features = torch.cat([features, output.squeeze()], dim=0)
                labels = torch.cat([labels, target], dim=0)
    return features, labels