atch = input_tensor.unsqueeze(0) # create a mini-batch as expected by the model

    # move the input and model to GPU for speed if available
    if torch.cuda.is_available():
        input_batch = input_batch.to(&#39;cuda&#39;)
        model.to(&#39;cuda&#39;)

    with torch.no_grad():
        output = model(input_batch)
        # Tensor of shape 1000, with confidence scores over Imagenet&#39;s 1000 classes
        sm_output = torch.nn.functional.softmax(output[0], dim=0)

    ind = torch.argmax(sm_output