INNER CODE UNIT · Python

x

sksq96/pytorch-summary · torchsummary/torchsummary.py:59

    x = [torch.rand(2, *in_size).type(dtype).to(device=device)
         for in_size, dtype in zip(input_size, dtypes)]

    # create properties
    summary = OrderedDict()
    hooks = []

    # register hook
    model.apply(register_hook)

    # make a forward pass
    # print(x.shape)
    model(*x)

    # remove these hooks
    for h in hooks:
        h.remove()

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