Log compile and run commands on successful model tests too. (#17290)

This pulls in my change at
https://github.com/nod-ai/SHARK-TestSuite/pull/227 to add more logging
to these test jobs. Now when a test runs and `--log-cli-level=info` is
set, it will log the compile and run commands as they are launched.
Previously these were only logged on test failure.

Sample logs:
https://github.com/iree-org/iree/actions/runs/8973823928/job/24645200447?pr=17290#step:11:40

```
============================= test session starts ==============================
platform linux -- Python 3.11.9, pytest-8.2.0, pluggy-1.5.0
rootdir: /mnt/share/amdsharks/actions-runner-iree/_work/iree/iree
plugins: xdist-3.6.1, timeout-2.3.1, retry-1.6.2, reportlog-0.4.0
timeout: 1200.0s
timeout method: signal
timeout func_only: False
collected 2 items / 1 deselected / 1 selected

SHARK-TestSuite/iree_tests/pytorch/models/sdxl-scheduled-unet-3-tank/model.mlirbc::gpu_rocm_real_weights 
-------------------------------- live log call ---------------------------------
INFO     root:conftest.py:393 Launching compile command:
cd /mnt/share/amdsharks/actions-runner-iree/_work/iree/iree/SHARK-TestSuite/iree_tests/pytorch/models/sdxl-scheduled-unet-3-tank && iree-compile model.mlirbc --iree-hal-target-backends=rocm --iree-rocm-target-chip=gfx90a --iree-opt-const-eval=false --iree-codegen-transform-dialect-library=/mnt/share/amdsharks/actions-runner-iree/_work/iree/iree/build_tools/pkgci/external_test_suite/attention_and_matmul_spec.mlir --iree-global-opt-propagate-transposes=true --iree-global-opt-enable-fuse-horizontal-contractions=true --iree-flow-enable-aggressive-fusion=true --iree-opt-aggressively-propagate-transposes=true --iree-opt-outer-dim-concat=true --iree-vm-target-truncate-unsupported-floats --iree-llvmgpu-enable-prefetch=true --iree-opt-data-tiling=false --iree-codegen-gpu-native-math-precision=true --iree-codegen-llvmgpu-use-vector-distribution "--iree-preprocessing-pass-pipeline=builtin.module(iree-preprocessing-transpose-convolution-pipeline, util.func(iree-preprocessing-pad-to-intrinsics))" -o model_gpu_rocm_real_weights.vmfb
INFO     root:conftest.py:407 Launching run command:
cd /mnt/share/amdsharks/actions-runner-iree/_work/iree/iree/SHARK-TestSuite/iree_tests/pytorch/models/sdxl-scheduled-unet-3-tank && iree-run-module --module=model_gpu_rocm_real_weights.vmfb --device=hip --parameters=model=real_weights.irpa --module=sdxl_scheduled_unet_pipeline_fp16_rocm.vmfb --input=1x4x1[28](https://github.com/iree-org/iree/actions/runs/8973823928/job/24645200447?pr=17290#step:11:29)x128xf16=@inference_input.0.bin --input=2x64x2048xf16=@inference_input.1.bin --input=2x1280xf16=@inference_input.2.bin --input=1xf16=@inference_input.3.bin --expected_output=1x4x128x128xf16=@inference_output.0.bin --expected_f16_threshold=0.8f --flagfile=real_weights_data_flags.txt
PASSED

============================== slowest durations ===============================
[34](https://github.com/iree-org/iree/actions/runs/8973823928/job/24645200447?pr=17290#step:11:35).50s call     SHARK-TestSuite/iree_tests/pytorch/models/sdxl-scheduled-unet-3-tank/model.mlirbc::gpu_rocm_real_weights

(2 durations < 0.005s hidden.  Use -vv to show these durations.)
=========================== short test summary info ============================
PASSED SHARK-TestSuite/iree_tests/pytorch/models/sdxl-scheduled-unet-3-tank/model.mlirbc::gpu_rocm_real_weights
======================= 1 passed, 1 deselected in 34.54s =======================
```
5 files changed
tree: 01f1188a5178daf0cced33883133d1b0d84e9c8c
  1. .devcontainer/
  2. .github/
  3. build_tools/
  4. compiler/
  5. docs/
  6. experimental/
  7. integrations/
  8. lib/
  9. llvm-external-projects/
  10. runtime/
  11. samples/
  12. tests/
  13. third_party/
  14. tools/
  15. .bazel_to_cmake.cfg.py
  16. .bazelignore
  17. .bazelrc
  18. .bazelversion
  19. .clang-format
  20. .dockerignore
  21. .git-blame-ignore-revs
  22. .gitignore
  23. .gitmodules
  24. .yamllint.yml
  25. AUTHORS
  26. BUILD.bazel
  27. CITATION.cff
  28. CMakeLists.txt
  29. configure_bazel.py
  30. CONTRIBUTING.md
  31. LICENSE
  32. MAINTAINERS.md
  33. README.md
  34. RELEASING.md
  35. WORKSPACE
README.md

IREE: Intermediate Representation Execution Environment

IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.

See our website for project details, user guides, and instructions on building from source.

CI Status IREE Discord Status

Project Status

IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!

Communication Channels

Related Project Channels

  • MLIR topic within LLVM Discourse: IREE is enabled by and heavily relies on MLIR. IREE sometimes is referred to in certain MLIR discussions. Useful if you are also interested in MLIR evolution.

Architecture Overview

IREE Architecture IREE Architecture

See our website for more information.

Presentations and Talks

Community meeting recordings: IREE YouTube channel

  • 2021-06-09: IREE Runtime Design Tech Talk (recording and slides)
  • 2020-08-20: IREE CodeGen: MLIR Open Design Meeting Presentation (recording and slides)
  • 2020-03-18: Interactive HAL IR Walkthrough (recording)
  • 2020-01-31: End-to-end MLIR Workflow in IREE: MLIR Open Design Meeting Presentation (recording and slides)

License

IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.