Add torch version constraint to be equal or less than 2.8.0 to prevent breaking onnx changes in torch 2.9.0 (#6251)

* Pin torch version to 2.8.0 to prevent breaking onnx changes in 2.9.0

The ` 2.9.0` version results in an issue finding `onnxscript`. Pinning the `2.8.0` prevent this error. 

I'm not exactly of the exact root cause but it seems there were some backwards incompatible changes to onnx: https://github.com/pytorch/pytorch/releases/tag/v2.9.0#backwards-incompatible-changes.

Stack trace on exiting training:
```
  File "C:\Users\Samuel\miniconda3\envs\mlagents\lib\site-packages\mlagents\trainers\torch_entities\model_serialization.py", line 164, in export_policy_model
    torch.onnx.export(
  File "C:\Users\Samuel\miniconda3\envs\mlagents\lib\site-packages\torch\onnx\__init__.py", line 282, in export
    from torch.onnx._internal.exporter import _compat
  File "C:\Users\Samuel\miniconda3\envs\mlagents\lib\site-packages\torch\onnx\_internal\exporter\_compat.py", line 16, in <module>
    from torch.onnx._internal.exporter import (
  File "C:\Users\Samuel\miniconda3\envs\mlagents\lib\site-packages\torch\onnx\_internal\exporter\_core.py", line 18, in <module>
    import onnxscript
ModuleNotFoundError: No module named 'onnxscript'
```

* Add torch version constraint to be equal or less than 2.8.0

Previously commit forced only 2.8.0, however adding this constraint is a bit nicer, as I see in some of installation docs sometimes torch 2.2.0 is installed: https://github.com/Unity-Technologies/ml-agents/blob/release_22_docs/docs/Installation.md.

* Update CHANGELOG.md

Author: samt1995

com.unity.ml-agents/CHANGELOG.md

@@ -12,6 +12,7 @@ and this project adheres to
 - Fixed tensor indexing to use correct CHW layout (#6239)
 
 #### ml-agents / ml-agents-envs
+- Set the Torch version constraint to 2.8 (#6251)
 - Fixed CUDA/CPU mismatch in threaded training (#6245)
 
 ## [4.0.0] - 2025-08-15

ml-agents/setup.py

@@ -62,7 +62,7 @@ def run(self):
         "Pillow>=4.2.1",
         "protobuf>=3.6,<3.21",
         "pyyaml>=3.1.0",
-        "torch>=2.1.1",
+        "torch>=2.1.1,<=2.8.0",
         "tensorboard>=2.14",
         # adding six explicit dependency since tensorboard needs it but doesn't declare it as a dep
         "six>=1.16",