def METHOD_NAME(self, input):
    num_dim = input.dim()
    assert num_dim in [4, 5], f'expected the input to have 4 or 5 dimensions, but got {num_dim} dimensions'
    d_in, h_in, w_in = input.shape[-3:]
    def _convert_int_to_list(item):
        if isinstance(item, int):
            return [item] * 3
        else:
            return item
    padding = _convert_int_to_list(self.padding)
    kernel_size = _convert_int_to_list(self.kernel_size)
    stride = _convert_int_to_list(self.stride)
    d_out = math.floor((d_in + 2 * padding[0] - kernel_size[0]) / stride[0] + 1)
    h_out = math.floor((h_in + 2 * padding[1] - kernel_size[1]) / stride[1] + 1)
    w_out = math.floor((w_in + 2 * padding[2] - kernel_size[2]) / stride[2] + 1)
    result_shape = tuple(input.shape[:-3]) + (
        d_out,
        h_out,
        w_out,
    )
    return torch.empty(result_shape, device='meta')