Input to network module is of type torch.autograd.variable.Variable
>>> print(type(input))
<torch.autograd.variable.Variable>

During forward() I unpacked input with .data to use torch.index_select on it.
pix = torch.index_select(input.data), 0, idx)
The output value for the forward() is torch.cuda.FloatTensor.
>>> output = model.forward(input)
>>> print(type(output))
<torch.cuda.FloatTensor>

Will unpacking input affect the flow of gradient during backward()?