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[webgpu] optimize SkipLayerNormalization operator #24164
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If the sizes of batch_size and sequence_length are ones, split the hidden_size to improve parallelism.
The outputs of SkipLayerNormalization operator in phi3.5 are |
/azp run ONNX Runtime Web CI Pipeline,Windows GPU CI Pipeline,Linux Android Emulator QNN CI Pipeline |
/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 |
/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 |
Azure Pipelines successfully started running 2 pipeline(s). |
/azp run Windows GPU CUDA CI Pipeline,Windows GPU DML CI Pipeline,Windows GPU Doc Gen CI Pipeline, Win_TRT_Minimal_CUDA_Test_CI |
Azure Pipelines successfully started running 3 pipeline(s). |
Azure Pipelines successfully started running 2 pipeline(s). |
Azure Pipelines successfully started running 7 pipeline(s). |
lgtm. |
Updated |
/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 |
Azure Pipelines successfully started running 5 pipeline(s). |
If the sizes of batch_size and sequence_length are ones, split the hidden_size to improve parallelism.
Description
Motivation and Context