def METHOD_NAME(
    input,
    weight,
    bias=None,
    stride=1,
    padding=0,
    output_padding=0,
    groups=1,
    dilation=1,
):
    if could_use_op(input):
        return conv2d_gradfix(
            transpose=True,
            weight_shape=weight.shape,
            stride=stride,
            padding=padding,
            output_padding=output_padding,
            groups=groups,
            dilation=dilation,
        ).apply(input, weight, bias)
    return F.METHOD_NAME(
        input=input,
        weight=weight,
        bias=bias,
        stride=stride,
        padding=padding,
        output_padding=output_padding,
        dilation=dilation,
        groups=groups,
    )