m = nn.Identity(
54, 
unused_argument1=0.1, 
unused_argument2=False
)

input = torch.randn(128, 20)
output = m(input)
>>> print(output.size())
torch.Size([128, 20])

class Identity(Module):
    r"""A placeholder identity operator that is argument-insensitive.

    Args:
        args: any argument (unused)
        kwargs: any keyword argument (unused)

    Examples::

        >>> m = nn.Identity(54, unused_argument1=0.1, unused_argument2=False)
        >>> input = torch.randn(128, 20)
        >>> output = m(input)
        >>> print(output.size())
        torch.Size([128, 20])

    """
    def __init__(self, *args, **kwargs):
        super(Identity, self).__init__()

    def forward(self, input: Tensor) -> Tensor:
        return input