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Initial PR for NNAPI execution provider - #1220
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| NnapiExecutionProvider::~NnapiExecutionProvider() {} | ||
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| Status NnapiExecutionProvider::CopyTensor(const Tensor& src, Tensor& dst) const { | ||
| if (!(strcmp(src.Location().name, NNAPI) == 0 && strcmp(dst.Location().name, CPU) == 0) && |
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a separate PR will also come to solve the problem of asking execution provider to provide copy tensor function implementation. :).
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| const std::vector<const KernelRegistry*>& /*kernel_registries*/) const { | ||
| // This method is based on that of TRT EP | ||
| // Construct modelproto from graph | ||
| onnxruntime::Model model(graph.Name(), true, ModelMetaData(), IOnnxRuntimeOpSchemaRegistryList(), graph.DomainToVersionMap()); |
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it's necessary to add a "ToProto()" interface in GraphViewer to avoid duplicating this kind of logic in every provider. Let me know if you want to do the refactoring or not, if no, I'll do it later (may after your check-in).
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I'd like to submit a sperate PR to refactor it :)
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Thanks daquexian (@daquexian) ! The initial PR looks good to me. Please resolve the conflicts and let's monitor the CI a little bit to get all CI pass. |
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Ke Zhang (@linkerzhang) Win CPU x64 MKLML CI Pipeline is canceled due to timeout |
Ke Zhang (linkerzhang)
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Dmitri Smirnov (yuslepukhin)
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## Update OrtPerfTuning pass to accept data only using data_config ## Checklist before requesting a review - [x] Add unit tests for this change. - [x] Make sure all tests can pass. - [x] Update documents if necessary. - [x] Lint and apply fixes to your code by running `lintrunner -a` - [ ] Is this a user-facing change? If yes, give a description of this change to be included in the release notes. - [ ] Is this PR including examples changes? If yes, please remember to update [example documentation](https://github.com/microsoft/Olive/blob/main/docs/source/examples.md) in a follow-up PR. ## (Optional) Issue link
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Related issue: #919
It is an initial PR for Android NNAPI execution provider. Currently the
GetSupportedNodesreturns the whole model if the model is supported or an empty vector if the model is unsupported. It will be improved soon.