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I am learning PyTorch for an image classification task, and I ran into code where someone used a PyTorch Variable() in their function for prediction:

def predict_image(image): image_tensor = test_transforms(image).float() image_tensor = image_tensor.unsqueeze_(0) input = Variable(image_tensor) input = input.to(device) output = model(input) index = output.data.cpu().numpy().argmax() return index

Why do they use Variable() here? (even though it works fine without it.)

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You can safely omit it. Variables are a legacy component of PyTorch, now deprecated, that used to be required for autograd:

Variable (deprecated)

WARNING

The Variable API has been deprecated: Variables are no longer necessary to use autograd with tensors. Autograd automatically supports Tensors with requires_grad set to True. Below please find a quick guide on what has changed:

  • Variable(tensor) and Variable(tensor, requires_grad) still work as expected, but they return Tensors instead of Variables.
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