Fix image_transforms.pad rejecting NumPy-int padding and float constant_values
Author: Sreekant13
Pull request: yes
Labels: name: Code agent slop

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# What does this PR do?

`image_transforms.pad()` builds its `np.pad` arguments via `_expand_for_data_format`, which only accepted a `(before, after)` pair when its first element was a Python `int`. So two valid, documented inputs crash:

```python
import numpy as np
from transformers.image_transforms import pad

# padding amounts derived from an image's .shape are NumPy ints:
pad(image, (np.int64(1), np.int64(2)))        # ValueError: Unsupported format
# constant_values is documented as `float | Iterable[float]`:
pad(image, 1, constant_values=(0.5, 1.0))     # ValueError: Unsupported format
```

`(1, 2)` (Python ints) works, but the equivalent NumPy ints don't and NumPy ints are exactly what you get when padding is computed from array shapes.

The fix distinguishes the nested `((before_h, after_h), (before_w, after_w))` form (first element is a tuple → passed through) from a scalar `(before, after)` pair (applied to both axes), instead of gating on Python `int`. Added regression assertions to `test_pad`.

No linked issue - small self-contained bug fix.

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## Who can review?

@yonigozlan (vision / image processing)

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