onnxruntime

Allow defining customized PythonOp shape inferer (#17093)

### Allow defining customized PythonOp shape inferer

For `torch.autograd.Function`, we converted it to PythonOp in MSDomain,
there are two places to do shape inferencing for it:

1. in SymbolicShapeInfer, there is one. 
2. in PythonOp op definition. 

For common PythonOp, since we don't know the relation ship between
inputs and outputs, so we only infer the rank from output ranks, and
generate symbolic dimensions for each dim. While this will introduce
many meaningless symbolic dimensions, sometimes blocking our graph
transformers to do op fusion.

This PR provide a way to define custom shape inferencing for
`torch.autograd.Function` we defined, to propagate the original
dimensions across the PythonOp at the best efforts.

But the 2rd one is not covered yet, we could refine that later. Fixing
1st one is enough for ORTModule training/evaluation.

### Motivation and Context
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