[WebNN] Remove workarounds for TFLite backend #23406
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The WebNN CPU device type may now target different backends, such as CoreML. Legacy special workarounds for the TFLite backend should be removed and allowed to fail as is, as these are implementation issues. Additionally, the WebNN EP should adhere to the WebNN API conformance. We assume all the WebNN ops should be supported, so remove the WebNN op support status for different device types in webnn-operators.md as well.
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/azp run ONNX Runtime Web CI Pipeline,Windows GPU CI Pipeline,Linux Android Emulator QNN 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 4 pipeline(s). |
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The WebNN CPU device type may now target different backends, such as CoreML. Legacy special workarounds for the TFLite backend should be removed and allowed to fail as is, as these are implementation issues.
Additionally, the WebNN EP should adhere to the WebNN API conformance. We assume all the WebNN ops should be supported, so remove the WebNN op support status for different device types in webnn-operators.md as well.