[ONNX] Refactor op level debugging (#97494)
Fixes #97728
Fixes #98622
Fixes https://github.com/microsoft/onnx-script/issues/393
Provide op_level_debug in exporter which creates randomnied torch.Tensor based on FakeTensorProp real shape as inputs of both torch ops and ONNX symbolic function. The PR leverages on Transformer class to create a new fx.Graph, but shares the same Module with the original one to save memory.
The test is different from [op_correctness_test.py](https://github.com/microsoft/onnx-script/blob/main/onnxscript/tests/function_libs/torch_aten/ops_correctness_test.py) as op_level_debug generating real tensors based on the fake tensors in the model.
Limitation:
1. Some of the trace_only function is not supported due to lack of param_schema which leads to arg/kwargs wronly split and ndarray wrapping. (WARNINGS in SARIF)
2. The ops with dim/indices (INT64) is not supported that they need the information(shape) from other input args. (WARNINGS in SARIF)
3. sym_size and built-in ops are not supported.
4. op_level_debug only labels results in SARIF. It doesn't stop exporter.
5. Introduce ONNX owning FakeTensorProp supports int/float/bool
6. parametrized op_level_debug and dynamic_shapes into FX tests
Pull Request resolved: https://github.com/pytorch/pytorch/pull/97494
Approved by: https://github.com/justinchuby, https://github.com/BowenBao
