onnxruntime

Optimize 4bit Qlora training (#18131)

### Optimize 4bit Qlora training

Extent existing `MatmulBnb4bit` to its usage in training scenarios. 

The PR includes following changes:
1. Add special `torch.autograd.Function` export logic for
`bitsandbytes.autograd._functions.MatMul4Bit` that is preferred before
common PythonOp exporter.
2. Add `training_mode` optional attribute for op `MatmulBnb4bit`, which
help skip some inference specific logic in implementation.
3. Add `transB` optional attribute, which is by default be 1; setting it
to be 0 is needed by backward usage.

Changing from `PythonOp` to this `MatmulBnb4bit` brings roughly ~2.9%
throughput gains. The reason is:
`bitsandbytes.autograd._functions.MatMul4Bit` has logic
`ctx.save_for_backward`, which would need an additional copy in
PythonOp, otherwise, the tensor might be released by ORT, while backward
op still references it.

Removing the clones also reduce the peak memory consumptions because
`bitsandbytes.autograd._functions.MatMul4Bit` saved tensors that are not
needed in backward compute.