onnxruntime

d3746361 - Fix TransposeOptimizer type error on zero-point-less DequantizeLinear (#28716) (#29192)

Fix TransposeOptimizer type error on zero-point-less DequantizeLinear (#28716) (#29192) ### Problem With `graph_optimization_level >= ORT_ENABLE_BASIC`, a model with mixed int8/uint8 QDQ inside a local function fails session init: ``` Type Error: Type (tensor(int8)) of output arg (QuantizeLinear_out0) of node (QuantizeLinear) does not match expected type (tensor(uint8)). ``` ### Root cause The issue's "duplicate NodeArg name" title is a misdiagnosis — `QuantizeLinear_out0` is created exactly once. The real cause: when `TransposeOptimizer` pushes a Transpose through a `DequantizeLinear` that has **no zero-point** (`MakeQDQNodeUnit`), it inserts a new `QuantizeLinear` reusing the DQ's inputs. With no zero-point and no `output_dtype`, ONNX type inference defaults the new Q's output to **uint8**, but the value-info copied from the DQ input is **int8** → `Graph::Resolve()` rejects it. ### Fix In `MakeQDQNodeUnit`, when the DQ has no zero-point, set the inserted Q's `output_dtype` to the DQ input's element type (ONNX domain only — `output_dtype` exists from opset 21; the zero-point path is unchanged). ### Verification Reporter's repro model: ``` ORT_DISABLE_ALL -> OK (before & after) ORT_ENABLE_BASIC -> FAIL (before) -> OK (after) ``` - After the fix, the optimized model passes `onnx.checker.check_model(full_check=True)`; the inserted node now carries `output_dtype=int8`. - Added regression test `TransposeOptimizerTests.TestDequantizeLinearNoZeroPoint` (Transpose → no-zp int8 DequantizeLinear → Transpose; expects the Transposes to cancel). ### Scope ONNX domain, opset 21+ (where `output_dtype` exists). Pre-21 and `com.microsoft` QDQ rely on an explicit zero-point and are unaffected. Fixes #28716