Fixed #116848

Related to the bug introduced in my previous PR here: https://github.com/pytorch/pytorch/pull/113749/files#diff-a1b077971cddfabfa0071c5162265066e867bc07721816d95b9cbe58431c38e3R3264

Originally, the code was
```python
def upsample_nearestnd(
    x,
    output_size,
    scales_x: Tuple[Optional[float], ...],
    n: int = 2,
    exact: bool = False,
):
   # ...
    scales = [i / o for i, o in zip(i_sizes, o_sizes)]
    for i, scale in enumerate(scales):
        if scale:
            scales[i] = scale
```
which is wrong as `scales_x` is not used but can be provided by the user. The code was working for cases when user provided scale value can be recomputed using `input / output` sizes, e.g. scale=2.0. However, this would fail if input scale is a float value, e.g. 2.3, in this case recomputed scale is a bit different (e.g. 2.292682926829268, depending on input and output size) and can lead to an inconsistent output.
This problem was "fixed" to the following in my previous PR: #113749
```python
def upsample_nearestnd(
    x,
    output_size,
    scales_x: Tuple[Optional[float], ...],
    n: int = 2,
    exact: bool = False,
):
   # ...
    scales = [i / o for i, o in zip(i_sizes, o_sizes)]
    for i, scale in enumerate(scales_x):
        if scale:
            scales[i] = scale
```
however, this leads to a wrong scale value as it should be inverted as (1 / scale).

Pull Request resolved: #117538
Approved by: https://github.com/peterbell10