Qualcomm AI Engine Direct - QAIRT Visualizer Engagement

[DannyYuyang-quic]

Summary:

• Add QAIRT Visualizer e2e example script.
• Add README for QAIRT Visualizer.
• Integrate QAIRT Visualizer into CI.
• Remove redundant context size log in QnnDlcManager to avoid duplicate log message.
• Remove DLC test case from context extraction, as it has already been covered in the generate optrace test case.

Test plan

python -m backends.qualcomm.tests.test_qnn_delegate TestQNNFloatingPointUtils.test_qnn_backend_generate_optrace -s ${device_id} -H ${host_id} -m ${soc} -b build-android

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/10873

• 📄 Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

❌ 18 New Failures, 2 Unrelated Failures

As of commit 9c27273 with merge base 05383fe ():

NEW FAILURES - The following jobs have failed:

• Build Linux Wheels / pytorch/executorch / build-manywheel-py3_10-cpu (gh)
  Process completed with exit code 1.
• Build Linux Wheels / pytorch/executorch / upload / upload-manywheel-py3_10-cpu (gh)
  Unable to download artifact(s): Artifact not found for name: pytorch_executorch__3.10_cpu_x86_64
• Build macOS Wheels / pytorch/executorch / build-wheel-py3_10-cpu (gh)
  Process completed with exit code 1.
• Build macOS Wheels / pytorch/executorch / upload / upload-wheel-py3_10-cpu (gh)
  Unable to download artifact(s): Artifact not found for name: pytorch_executorch__3.10_cpu_
• Build Presets / apple (ios-simulator) / build (gh)
  RuntimeError: Command bash /Users/runner/work/_temp/exec_script failed with exit code 1
• Build Presets / apple (ios) / build (gh)
• Build Presets / apple (llm) / build (gh)
• Build Presets / apple (macos) / build (gh)
• Build Presets / apple (pybind) / build (gh)
• Build Presets / linux (linux, linux.2xlarge, executorch-ubuntu-22.04-clang12) / build (gh)
  RuntimeError: Command docker exec -t 09d8ecf6d78a39addece6c76ba2dd13eafc6e7e9e02268a5e7557016aa2f5330 /exec failed with exit code 1
• Build Presets / linux (linux, linux.arm64.2xlarge, executorch-ubuntu-22.04-gcc11-aarch64) / build (gh)
  RuntimeError: Command docker exec -t 8a6a8b5b2f541b82903a6b3c2fc5397dfcd4f0965355d964975c854c952b058c /exec failed with exit code 1
• Build Presets / linux (llm, linux.2xlarge, executorch-ubuntu-22.04-clang12) / build (gh)
  RuntimeError: Command docker exec -t 91b7cedc6c2416800003aa89619b3aa27cd76692a34ffbcf96f11f256ef453b3 /exec failed with exit code 1
• Build Presets / linux (llm, linux.arm64.2xlarge, executorch-ubuntu-22.04-gcc11-aarch64) / build (gh)
• Build Presets / linux (pybind, linux.2xlarge, executorch-ubuntu-22.04-clang12) / build (gh)
• Build Presets / linux (pybind, linux.arm64.2xlarge, executorch-ubuntu-22.04-gcc11-aarch64) / build (gh)
  RuntimeError: Command docker exec -t 4d1feb94ec12c3d501ee42b7b6016e80732018be14c35513849503c275c76557 /exec failed with exit code 1
• pull / test-llava-runner-linux / linux-job (gh)
  RuntimeError: Command docker exec -t f6d703227245be052674eabf94fa63a7b87299ef532045931f16e83c5c1f9d9e /exec failed with exit code 139
• pull / test-moshi-linux / linux-job (gh)
  RuntimeError: Command docker exec -t 2a47f8a2094f48c76fb91163cbcae1c0f448cc60c9e09d83f91c49c08e4f872a /exec failed with exit code 1
• pull / test-openvino-linux / linux-job (gh)
  RuntimeError: Command docker exec -t 388aa173a8c7af6c92f6e37929ea5165722a430bc0a6074c7c08cfea5b01dcef /exec failed with exit code 1

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

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

• pull / unittest / linux / linux-job (gh) (trunk failure)
  examples/models/llama/tests/test_export_llama_lib.py::ExportLlamaLibTest::test_has_expected_ops_and_op_counts
• pull / unittest-editable / linux / linux-job (gh) (trunk failure)
  examples/models/llama/tests/test_export_llama_lib.py::ExportLlamaLibTest::test_has_expected_ops_and_op_counts

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[DannyYuyang-quic]

@pytorchbot label "release notes: qualcomm"

[DannyYuyang-quic]

Hi @cccclai,

This PR integrates with the QAIRT Visualizer
With this PR, users can more easily analyze performance bottlenecks from op-trace data through a visualized timeline.
Additionally, it enables direct mapping of cycle costs for each Op onto the QNN Graph, based on the following PR:Qualcomm AI Engine Direct - Support Qnn IR backend in online preparation.

Here are the README and demo script for users:

• backends/qualcomm/debugger/README.md – user guide and documentation
• examples/qualcomm/util_scripts/qairt_visualizer_demo.py – E2E script

Please have a look!
Thanks!!

[larryliu0820]

@cccclai gentle ping

[facebook-github-bot]

@cccclai has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.