[ONNX] Enable data propagation from ONNX to simplify current shape inference (#75307)
**Description**
- Obtain the result (generatedShapeDataByName) from onnx::shape_inference::InferShapesAndDataPropagation. If PyTorch cannot consume latest ONNX shortly, we can still use ONNX node-level shape inference here to obtain those symbolic shape inference data. To keep this POC PR simple, use `onnx::shape_inference::InferShapesAndDataPropagation` here for now
- Utilize Shape and Gather op first
- Next step -- try to utilize it with more ops, in another PR.
ONNX symbolic shape inference support is limited now. Here are the supported ops:
- Shape
- Reshape
- Squeeze
- Unsqueeze
- Cast
- Add
- Sub
- Mul
- Gather
- Slice
- Concat
Will focus on enabling these ops in the exporter first. In the future we can enable more ops in ONNX and then utilize them in the exporter.
**Motivation**
Fixes #75677.
ONNX introduced symbolic shape inference as [data propagation](https://github.com/onnx/onnx/blob/master/docs/proposals/SymbolicShapeInfProposal.md) in version 1.10. This PR uses this functionality to simplify the shape inference code in torch.onnx.
This PR depends on https://github.com/onnx/onnx/pull/3879.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75307
Approved by: https://github.com/garymm, https://github.com/BowenBao
