Wrap server generated yaml files inside et_operator_library (#5777) #5778
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/5778
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…5778) Summary: Pull Request resolved: pytorch#5778 ## This diff This diff is to make the model config codegen flow work on Edge MLHub by enabling the `et_operator_library` API to take a .yaml file. - The code changes in `fbcode/executorch/codegen/codegen.bzl` was copied from a stale diff D61824614 made by Mengwei. That one didn't landed because the owner of SceneX/v5002 model didn't have time to test it. ## Context By design, this is the codegen flow: 1. Use click the "Generate ET model config" button on Edge ML Hub; 2. Two files will be generated, one is a .yaml with a list of kernels, the other is a BUCK file under path `xplat/executorch_model/build/...` that calls `et_operator_library` and pass in the .yaml as a parameter. See D63667456 for an example; 3. A bot would accept and land the diff if CI passes; 4. User can run inference. Reviewed By: larryliu0820 Differential Revision: D63305843
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Summary:
This diff
This diff is to make the model config codegen flow work on Edge MLHub by enabling the
et_operator_libraryAPI to take a .yaml file.fbcode/executorch/codegen/codegen.bzlwas copied from a stale diff D61824614 made by Mengwei. That one didn't landed because the owner of SceneX/v5002 model didn't have time to test it.Context
By design, this is the codegen flow:
xplat/executorch_model/build/...that callset_operator_libraryand pass in the .yaml as a parameter. See D63667456 for an example;Differential Revision: D63305843