feat(0831): Localize constant ReduceSum axes inside ONNX subfunctions

[vbaddi]

Summary

• Added LocalizeFunctionReduceSumAxesTransform for ONNX subfunction exports.
• Replaced the previous torch.einsum(... reduction ...) workarounds back to equivalent .sum(...) forms across QEff modeling/MoE/blocking code.
• Enabled the ReduceSum axes localization only when use_onnx_subfunctions=True.

We previously used einsum in several reduction patterns to avoid ONNX subfunction export promoting constant ReduceSum axes into FunctionProto inputs. That workaround avoided compiler failures, but it could lower into heavier performance dip's due to lowering of BMM instead of the intended elementwise multiply plus ReduceSum path.

The desired PyTorch source should be able to stay as:

(query * query).sum(dim=-1, keepdim=True)
and export as:
Mul -> ReduceSum <- Constant([-1]) -- inside the ONNX function body.

ONNX Transform Details

LocalizeFunctionReduceSumAxesTransform it rewrites a function input when:

• a node inside an ONNX FunctionProto is ReduceSum
• the ReduceSum axes input is one of the function formal inputs
• every top-level call site passes a compile-time constant for that formal input
• the value is a valid integer scalar or 1-D axes tensor

When eligible, the transform:

• inserts a local Constant node inside the function body
• rewires each matching ReduceSum to use that local constant
• removes the axes formal input from the function signature

[vbaddi]

CI-Ready

[quic-rishinr]

LGTM Thanks!!

[vbaddi]

CI-Ready

[mohiso22]

CI-Ready