[WebNN] Always execute decomposed *SimplifiedLayerNormalization in FP32 #24437
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Decomposed [Skip]SimplifiedLayerNormalization will lose precision in FP16, we'd like to add cast (to: fp32) ops around it in WebNN EP to ensure its precision rather than manually add cast nodes in each model file.
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@fdwr, thanks for your comments, fixed in new commit, PTAL again. |
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/azp run ONNX Runtime Web CI Pipeline,Windows GPU CI Pipeline,Linux Android Emulator QNN CI Pipeline,Windows GPU WebGPU CI Pipeline,Windows OpenVINO CI Pipeline |
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/azp run Linux CPU CI Pipeline,Linux CPU Minimal Build E2E CI Pipeline,Linux GPU CI Pipeline,Linux GPU TensorRT CI Pipeline,Linux OpenVINO CI Pipeline,Linux QNN CI Pipeline,MacOS CI Pipeline,Windows ARM64 QNN CI Pipeline,Windows CPU CI Pipeline |
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/azp run Windows GPU CUDA CI Pipeline,Windows GPU DML CI Pipeline,Windows GPU Doc Gen CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI |
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/azp run Windows GPU TensorRT CI Pipeline,onnxruntime-binary-size-checks-ci-pipeline,orttraining-linux-ci-pipeline,orttraining-linux-gpu-ci-pipeline,orttraining-ortmodule-distributed,Windows x64 QNN CI Pipeline,Big Models |
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Azure Pipelines successfully started running 3 pipeline(s). |
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Merging since these 5 failures are unrelated, persistent, and pervasive.
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…32 (microsoft#24437) Decomposed [Skip]SimplifiedLayerNormalization will lose precision in FP16, we'd like to add cast (to: fp32) ops around it in WebNN EP to ensure its precision rather than manually add cast nodes in each model file. Signed-off-by: bfilipek <[email protected]>
Decomposed [Skip]SimplifiedLayerNormalization will lose precision in FP16, we'd like to add cast (to: fp32) ops around it in WebNN EP to ensure its precision rather than manually add cast nodes in each model file.