[WebNN EP] Support subgraph of the control flow nodes #18923
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This PR also makes some processing on the subgraph's initializers. The subgraph doesn't contain all its required initializers, some common initializers are stored in its ancestor graphs. We need to collect all required initializers and re-map to the subgraph.
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/azp run ONNX Runtime Web 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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Azure Pipelines successfully started running 1 pipeline(s). |
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/azp run Windows GPU CI Pipeline,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 |
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Azure Pipelines successfully started running 9 pipeline(s). |
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Azure Pipelines successfully started running 7 pipeline(s). |
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/azp run ONNX Runtime Web CI Pipeline |
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Azure Pipelines successfully started running 1 pipeline(s). |
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/azp run ONNX Runtime Web CI Pipeline |
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Azure Pipelines successfully started running 1 pipeline(s). |
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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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Azure Pipelines successfully started running 9 pipeline(s). |
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/azp run Windows GPU CI Pipeline,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 |
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Azure Pipelines successfully started running 7 pipeline(s). |
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I'm guessing this is for the merged models with encoder/decoder and an |
This PR also makes some processing on the subgraph's initializers. The subgraph doesn't contain all its required initializers, some common initializers are stored in its ancestor graphs. We need to collect all required initializers and re-map to the subgraph.