Arm backend: Add dump_delegate_data function

[wwwind]

Add dump_delegate_data function

Signed-off-by: Elena Zhelezina [email protected]

cc @digantdesai @freddan80 @per @zingo @oscarandersson8218

[pytorch-bot]

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❌ 2 New Failures, 2 Cancelled Jobs, 5 Unrelated Failures

As of commit dce54c7 with merge base aaf0a4c ():

NEW FAILURES - The following jobs have failed:

• pull / test-eval_llama-mmlu-linux / linux-job (gh)
  RuntimeError: Dataset scripts are no longer supported, but found mmlu_no_train.py
• trunk / test-arm-cortex-m-size-test (bare_metal) / linux-job (gh)
  RuntimeError: Command docker exec -t 6443bdde6179af0d511675ba45f6c663ad3f8f8f84d4839a6b94a09528603d64 /exec failed with exit code 1

CANCELLED JOBS - The following jobs were cancelled. Please retry:

• pull / test-models-linux (mobilebert, portable, linux.2xlarge) / linux-job (gh)
  ##[error]The operation was canceled.
• pull / test-models-linux (mobilebert, xnnpack-quantization-delegation, linux.2xlarge) / linux-job (gh)

BROKEN TRUNK - The following jobs failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

• trunk / test-models-linux-aarch64 (mobilebert, portable, linux.arm64.2xlarge) / linux-job (gh) (trunk failure)
  ##[error]The operation was canceled.
• trunk / test-models-linux-aarch64 (mobilebert, xnnpack-quantization-delegation, linux.arm64.2xlarge) / linux-job (gh) (trunk failure)
  ##[error]The operation was canceled.
• trunk / test-qnn-model (fp32, mb) / linux-job (gh) (trunk failure)
  ##[error]The operation was canceled.
• trunk / unittest-release / linux / linux-job (gh) (trunk failure)
  [ FAILED ] TensorPtrMakerTest.FailedCreateTensorUsingFromBlobWithIllegalStrides
• trunk / unittest-release / macos / macos-job (gh) (trunk failure)
  [ FAILED ] TensorPtrMakerTest.FailedCreateTensorUsingFromBlobWithIllegalStrides

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[JacobSzwejbka]

can you take a TextIO instead? Like Dump_et_program above

edit: Or just any stream really since the data isnt text

[JacobSzwejbka]

Can you not find the blob if its embedded in the flatbuffer section?

[digantdesai]

Thanks @wwwind for the PR.

Is the goal for extracting the blobs is to run a delegate subgraph on a TOSA reference model? If yes, then I don't think I prefer this approach of extracting the blobs and running them.

The main reason is e2e validation. You can have N blobs which will lead to N tosa_ref_sim calls and then you might have to stitch them together manually to see if the entire network worked correctly or not.

Alternatively I propose we can write a tosa runtime which works with tosa partitioner and graph breaks can be handled by portable libs seamlessly. This way you can re-use all the ET infra and have e2e working TOSA PTE :)

[wwwind]

Thank you for the review @digantdesai

Actually, this function is for cases when we don't need e2e flow. We have a graphic use case when we get these blobs as .tosa files and then we have a plugin which implements different bits around it in shaders and pass some data to run subgraphs.

[digantdesai]

Thank you for the review @digantdesai

Actually, this function is for cases when we don't need e2e flow. We have a graphic use case when we get these blobs as .tosa files and then we have a plugin which implements different bits around it in shaders and pass some data to run subgraphs.

Ok. Curious why can't we dump them after generation from preprocess? Extracting feels a bit like going backwards.