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torch-mlir/test-requirements.txt

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python: separate build- and test-related pip dependencies (#1874) We want to ensure that pip packages required for building torch-mlir should be included in the dependencies of torch-mlir, but we don't want the pip packages required for _testing_ of torch-mlir to be included among the dependencies. To be able to specify and install one set of dependencies and not the other, this patch separates the pip packages into two files: build-requirements.txt and test-requirements.txt. This patch also updates references to the requirements.txt file so that CI builds that run end-to-end tests install test-related pip dependencies while everything else (including WHL builds) sticks to just the build-related pip dependencies. Despite this change, this patch should not affect a torch-mlir developer's workflow. More precisely, since this patch makes the top-level requirements.txt file refer to both build-requirements.txt and test-requirements.txt files, a torch-mlir developer should be able to continue referring to the requirements.txt file without any impact.
2023-02-14 11:22:09 +08:00
pillow
dill
multiprocess
Upstream the ONNX importer. (#2636) This is part 1 of 2, which will also include upstreaming the FX importer. I started with ONNX because it forces some project layout updates and is more self contained/easier as a first step. Deviating somewhat from the RFCs on project layout, I made the following decisions: * Locating the `onnx_importer.py` into `torch_mlir.extras` as Maks already has opened up that namespace and it seemed to fit. Better to have fewer things at that level. * Setup the build so that the root project only contains MLIR Python and pure Python deps (like the importers), but this can be augmented with the `projects/` adding more depending on which features are enabled. * The default build continues to build everything whereas in `TORCH_MLIR_ENABLE_ONLY_MLIR_PYTHON_BINDINGS=1` mode, it builds a `torch-mlir-core` wheel with the pure contents only. `onnx_importer.py` and `importer_smoke_test.py` are almost verbatim copies from SHARK-Turbine. I made some minor local alterations to adapt to paths and generalize the way they interact with the outer project. I expect I can copy these back to Turbine verbatim from here. I also updated the license boilerplate (they have the same license but slightly different project norms for the headers) but retained the correct copyright. Other updates: * Added the ONNX importer unit test (which also can generate test data) in lit, conditioned on the availability of the Python `onnx` package. In a followup once I know everything is stable, I'll add another env var that the CI can set to always enable this so we know conclusively if tests pass. * Moved the ONNX conversion readme to `docs/`. * Renamed CMake option `TORCH_MLIR_ENABLE_ONLY_MLIR_PYTHON_BINDINGS` -> `TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS` and inverted the sense. Made the JitIR importer and LTC options `cmake_dependent_options` for robustness.
2023-12-13 11:02:51 +08:00
onnx==1.15.0