[pytorch/pytorch] Integrate with ONNX 1.21.0 release branch

### ROOT CAUSE The issue arises from the need to integrate the new ONNX 1.21.0 release branch into PyTorch to ensure compatibility and functionality. This requires updating PyTorch's dependencies and implementing CPU kernels for any new or updated ONNX operations. ### CODE FIX To integrate the ONNX 1.21.0 release branch into PyTorch, follow these steps: 1. **Update ONNX Dependency in PyTorch:** - Locate the file where PyTorch specifies its dependencies, typically `pytorch/requirements.txt`. - Update the ONNX version to point to the new release branch.

diff
   # pytorch/requirements.txt
   - onnx>=1.20.0
   + onnx@https://github.com/onnx/onnx.git@rel-1.21.0
   


2. **Implement CPU Kernels for New/Updated ONNX Operations:**
   - Identify the new and updated operations from the ONNX 1.21.0 release notes.
   - Add or modify functions in PyTorch's ONNX export code to handle these operations on CPU.

   Example for a new operation `MyNewOp`:

   

   # torch/onnx/export.py
   def _export_my_new_op(*args, **kwargs):
       # Implementation for MyNewOp on CPU
       pass

   # Add the new exporter function to the ONNX export registry
   EXPORTER_REGISTRY.register('MyNewOp', _export_my_new_op)
   


3. **Update Testing:**
   - Add tests to cover the new operations, ensuring they work as expected on CPU.

   

   # tests/test_onnx.py
   def test_my_new_op():
       # Test cases for MyNewOp
       pass
   


4. **Install and Verify with Release Candidate:**
   - Install the ONNX 1.21.0 RC and run PyTorch tests to validate the integration.

   
bash
   pip install -i https://pypi.org/simple/ --pre onnx==1.21.0rc1
   pytest tests/
   


By following these steps, the integration of ONNX 1.21.0 into PyTorch will be smooth, ensuring all new and updated operations are supported and tested.