Improving image-segmentation pipeline tests. (#19710)

This PR (https://github.com/huggingface/transformers/pull/19367) introduced a few breaking changes:

- Removed an argument `mask_threshold`.
- Broke the default behavior (instance vs panoptic in the function call)
  https://github.com/huggingface/transformers/pull/19367/files#diff-60f846b86fb6a21d4caf60f5b3d593a04accb8f248de3029cccae2ff898c5bc3R119-R120
- Broke the actual masks: https://github.com/huggingface/transformers/pull/1961

This PR is the start of a handful that will aim at bringing back the old
behavior(s).

- tests should not have to specify `task` by default, unless we want to
  modify the behavior and have a lower form of segmentation running)
- `test_small_model_pt` should be working.

This specific PR starts with adding more information to the masks hash
because missing the actual mask was actual easy to miss (the hashes do
change, but it was easy to miss that one code path wasn't properly
updated).

So we go from a simple `hash` to
```
{"hash": #smaller hash, "shape": (h, w), "white_pixels": n}
```

The `shape` should help make sure the interpolation of the mask works
correctly, the `white_pixels` hopefully helps detect big regressions in
their amount when the hash gets modified.

src/transformers/testing_utils.py

@@ -1547,6 +1547,8 @@ def nested_simplify(obj, decimals=3):
 
     if isinstance(obj, list):
         return [nested_simplify(item, decimals) for item in obj]
+    if isinstance(obj, tuple):
+        return tuple([nested_simplify(item, decimals) for item in obj])
     elif isinstance(obj, np.ndarray):
         return nested_simplify(obj.tolist())
     elif isinstance(obj, Mapping):