c.py

def get_simple_gradient_expl(model, images, targets, absolute=False):
    images.requires_grad = True
    outputs = model(images)
    outputs = outputs.gather(1, targets.unsqueeze(1))
    grad = torch.autograd.grad(torch.unbind(outputs), images, create_graph=True)[0] # create_graph=True for second order derivative
    expl = grad.abs() if absolute else grad
    return expl