def METHOD_NAME(input, weight, **kwargs):
    stride, padding, dilation, output_padding = _extract_kwargs(kwargs)
    stride = _triple(stride)
    padding = _triple(padding)
    dilation = _triple(dilation)
    output_padding = _triple(output_padding)
    kernel_size = weight.shape[2:]
    d_in, h_in, w_in = input.shape[-3:]
    c_out = weight.shape[1]
    d_out = math.floor((d_in - 1) * stride[0] - 2 * padding[0] + dilation[0] * (kernel_size[0] - 1) +
                       output_padding[0] + 1)
    h_out = math.floor((h_in - 1) * stride[1] - 2 * padding[1] + dilation[1] * (kernel_size[1] - 1) +
                       output_padding[1] + 1)
    w_out = math.floor((w_in - 1) * stride[2] - 2 * padding[2] + dilation[2] * (kernel_size[2] - 1) +
                       output_padding[2] + 1)
    result_shape = input.shape[:-4] + (
        c_out,
        d_out,
        h_out,
        w_out,
    )
    return torch.empty(result_shape, device='meta')