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[QNN EP] Fix 16x16 Conv translation #24729

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Merged
merged 2 commits into from
May 20, 2025

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quic-tirupath
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  • QNN's 16x16 Conv doesn't support asymmetric int16 weight
  • Insert Convert Op to convert from asymmetric uint16 weight to symmetric int16 weight

Description

  • QNN' Conv op doesn't support asymmetric INT16 weights.
  • 16x16 Conv operators in ONNX models fallback to CPU execution provider and reporting higher inference times.
  • Insert a Convert Op to convert asymmetric uint16 weight to symmetric int16 weight to schedule 16x16 Conv's on QNN EP provider.

Motivation and Context

  • This fixes Graph execution failures for models contain 16x16 Conv op on QNN Execution provider
  • This also improves Inference times of model contain 16x16 Conv op

 - QNN's 16x16 Conv doesn't support asymmetric int16 weight
 - Insert Convert Op to convert from asymmetric uint16 weight
   to symmetric int16 weight
@quic-tirupath
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This commit should not impact WebGPU builds. Can someone help to re-trigger the checks?

@HectorSVC HectorSVC added the ep:QNN issues related to QNN exeution provider label May 13, 2025
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/azp run Linux QNN CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI,Windows ARM64 QNN CI Pipeline,Windows GPU Doc Gen CI Pipeline,Windows x64 QNN CI Pipeline

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Azure Pipelines successfully started running 5 pipeline(s).

 - Conv 16x16 is supported on few hardwares
 - Disable Conv 16x16 unit tests for linux platforms
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/azp run Linux QNN CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI,Windows ARM64 QNN CI Pipeline,Windows GPU Doc Gen CI Pipeline,Windows x64 QNN CI Pipeline

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Azure Pipelines successfully started running 5 pipeline(s).

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:shipit:

@HectorSVC HectorSVC merged commit adb05e4 into microsoft:main May 20, 2025
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2 participants