mirror of https://github.com/llvm/torch-mlir
0b46462528
* test: allow spaces in path to Python executable On Windows, the path to the Python binary may contain spaces, so this patch adds quotes around the path to the python executable. Thanks to @sstamenova for suggesting the fix! * python: remove header file that causes Windows build failures Similar to https://reviews.llvm.org/D125284, we can safely remove this header file without affecting the build on either Linux. It is necessary to remove this header file on Windows builds since otherwise it causes build errors. * python: drop `TORCH_API` from function defined in Torch-MLIR `TORCH_API` should apply to functions that are either exported by libtorch.so or ones that are imported from libtorch.so by its downstream consumers (like Torch-MLIR). Neither case applies to the `importJitFunctionAsFuncOp()` function, since it is defined in Torch-MLIR (and thus outside libtorch.so). This patch fixes the problem by dropping `TORCH_API` from that function's declaration. * python: make output of class anotations deterministic The `class-annotator-repr.py` test checks for class annotations in a specific order, but prior to this patch, the order was non-deterministic, since the code iterated on an _unordered_ map. This patch makes the iteration order deterministic through two changes: 1. using a sorted map 2. using the class qualified name instead of the address of the class in memory * test: use Python3_EXECUTABLE as interpreter path for consistency This ensures that tests use the Python3 version that was detected using CMake, instead of whichever python version that happens to be in the PATH variable when invoking the test. * test: fix RUN string The parenthesis syntax does not run on Windows (the shell interprets the `(` character as part of the path). Moreover, the ODR violation in the comment no longer seems to apply. * python: port parallel test framework to Windows Since Windows does not support `fork` natively, Python's `multiprocessing` module needs to use `spawn` on Windows. However, to use `spawn`, the multiprocessing module serializes (or pickles) the worker function and its arguments. Sadly, the multiprocessing module (both the default one in Python and the one that is extended in PyTorch) is unable to serialize lambda functions (see https://stackoverflow.com/a/19985580) for detals. Unfortunately, given how our tests are structured, we require that the function under test is passed as an argument to another function, so we cannot sidestep our use of lambda functions. To resolve this problem, this patch makes use of the `multiprocess` and `dill` Python modules, which together offers a multiprocessing mechanism that can serialize lambda functions. The multiprocess module also offers a process pool, which simplifies the code for our parallel testing framework. |
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| .. | ||
| test | ||
| torch_mlir | ||
| torch_mlir_e2e_test | ||
| CMakeLists.txt | ||
| TorchMLIRModule.cpp | ||