commit | 854a13e8255164e53e7fa319df84d240a72a013f | [log] [tgz] |
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author | Scott Todd <scott.todd0@gmail.com> | Wed Sep 04 09:08:42 2024 -0700 |
committer | GitHub <noreply@github.com> | Wed Sep 04 09:08:42 2024 -0700 |
tree | 4ff38de7aee14b1a3d1f540b200936ad3e0c7342 | |
parent | f2bf602e52cb933c0beaef8d8d86be6f47776555 [diff] |
Run all framework sanity check tests and organize jobs. (#18420) Fixes https://github.com/iree-org/iree/issues/16624 by running the existing ONNX and PyTorch importer tests _with the packages they need installed_. Sample logs when a test fails: https://github.com/iree-org/iree/actions/runs/10691656074/job/29638920091?pr=18420#step:9:19 ``` Traceback (most recent call last): File "/home/runner/work/iree/iree/compiler/bindings/python/test/extras/fx_importer_test.py", line 8, in <module> from iree.compiler.extras import fx_importer File "/home/runner/work/iree/iree/.venv/lib/python3.11/site-packages/iree/compiler/extras/fx_importer.py", line 138, in <module> from .._mlir_libs._torchMlir import get_int64_max, get_int64_min ModuleNotFoundError: No module named 'iree.compiler._mlir_libs._torchMlir' The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/runner/work/iree/iree/compiler/bindings/python/test/extras/fx_importer_test.py", line [19](https://github.com/iree-org/iree/actions/runs/10691656074/job/29638920091?pr=18420#step:9:20), in <module> raise ModuleNotFoundError( ModuleNotFoundError: Failed to import the fx_importer (for a reason other than torch not being found) Error: Process completed with exit code 1. ``` --- I'm not really satisfied with how these tests are distributed across jobs either before or after these changes, but I think this is a step in a good direction at least. * These tests depend on optional packages (torch, onnx, tensorflow) and disable themselves if those optional packages are not present. * The core project build (CMake/CTest, Python, packaging builds) strives to be modular and not require the entire kitchen sink to function. * Test workflows should make sense for both local development _and_ CI usage. The local development flows here are relatively convoluted and could use some work.
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.
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
Package | Release status |
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GitHub release (stable) | |
GitHub release (nightly) | |
Python iree-compiler | |
Python iree-runtime |
Host platform | Build status |
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Linux | |
macOS | |
Windows |
For the full list of workflows see https://iree.dev/developers/general/github-actions/.
See our website for more information.
Community meeting recordings: IREE YouTube channel
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.