[WebNN] Correct behavior of Softmax < opset 13 #26391
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ONNX Softmax operates with different semantics before and after opset 13.
Before opset 13, it normalizes over the flattened range of dimensions
starting from axis to the last dimension. Fix it by reshaping the input
to [M, N] where M = prod(d0..d{axis-1}) and N = prod(d{axis-1}..d{n-1})
and apply softmax along N, then reshaping back to the original shape.
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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 |
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onnxruntime/core/providers/webnn/builders/impl/softmax_op_builder.cc
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Restarting Windows GPU TensorRT test... |
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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,MacOS CI Pipeline,Windows ARM64 QNN CI Pipeline,Windows CPU CI Pipeline |
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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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Hmm, infrastructure issue it appears. Will retry tomorrow. |
3 participants
ONNX Softmax operates with different semantics before and after opset 13. Before opset 13, it normalizes over the flattened range of dimensions starting from axis to the last dimension. Fix it by reshaping the input to [M, N] where M = prod(d0..d{axis-1}) and N = prod(d{axis-1}..d{n-1}) and applying softmax along N, then reshaping back to the original shape.