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torch-mlir/requirements.txt

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Revert requirements.txt (#930) https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html is going to be deprecated via pip 22 since it is not html5.
2022-06-11 06:23:12 +08:00
-f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
Set some wheel building optimization options. * Also adds a requirements.txt and updates docs to reference it versus stringy pip install. * Adds doc with instructions on creating a wheel. Fixes #370
2021-10-22 12:18:08 +08:00
--pre
Minor buildsystem fixes (#778) Sets up auto-pinning of latest torch-nightly
2022-04-22 06:53:00 +08:00
torch
Set some wheel building optimization options. * Also adds a requirements.txt and updates docs to reference it versus stringy pip install. * Adds doc with instructions on creating a wheel. Fixes #370
2021-10-22 12:18:08 +08:00
numpy
Add minimal support for Union types. A recent PyTorch commit made ConstantPad2d call a helper function with a `Union[int, float]` type annotated. This commit adds minimal support for representing and dealing with that. https://github.com/pytorch/pytorch/pull/73287 Changes: - Adding support for `!torch.union<T1, T2, T3>`/`Torch::UnionType`, along with the importer and CAPI code. - Add support in isValidSubtype for union types. - Adding a canonicalizer for `torch.derefine` to help simplify some code that derefines to a UnionType (this also fixes #664). There is still more work to do for really supporting UnionType well, such as canonicalizing UnionType's so that they can be compared with pointer equality.
2022-03-30 06:57:31 +08:00
torchvision
Set some wheel building optimization options. * Also adds a requirements.txt and updates docs to reference it versus stringy pip install. * Adds doc with instructions on creating a wheel. Fixes #370
2021-10-22 12:18:08 +08:00
# Build requirements.
pybind11
wheel
Add oneshot release snapshot for test/ondemand (#768) * Add oneshot release snapshot for test/ondemand Add some build scripts to test new release flow based on IREE. Wont affect current builds, once this works well we can plumb it in. Build with manylinux docker * Fixes a few issues found when debugging powderluv's setup. * It is optional to link against Python3_LIBRARIES. Check that and don't do it if they don't exist for this config. * Clean and auditwheel need to operate on sanitized package names. So "torch_mlir" vs "torch-mlir". * Adds a pyproject.toml file that pins the build dependencies needed to detect both Torch and Python (the MLIR Python build was failing to detect because Numpy wasn't in the pip venv). * Commented out auditwheel: These wheels are not PyPi compliant since they weak link to libtorch at runtime. However, they should be fine to deploy to users. * Adds the --extra-index-url to the pip wheel command, allowing PyTorch to be found. * Hack setup.py to remove the _mlir_libs dir before building. This keeps back-to-back versions from accumulating in the wheels for subsequent versions. IREE has a more principled way of doing this, but what I have here should work. Co-authored-by: Stella Laurenzo <stellaraccident@gmail.com>
2022-04-21 17:19:12 +08:00
setuptools
cmake
ninja
Add PyYaml to requirements.txt (#1174) Building on a fresh environment + virtualenv + in-tree build errors out becayse PyYaml isn't installed. Adding to requirements.txt fixes that. Fixes #1173
2022-08-12 00:59:39 +08:00
# Workaround for what should be a torch dep
# See discussion in #1174
pyyaml
Add oneshot release snapshot for test/ondemand (#768) * Add oneshot release snapshot for test/ondemand Add some build scripts to test new release flow based on IREE. Wont affect current builds, once this works well we can plumb it in. Build with manylinux docker * Fixes a few issues found when debugging powderluv's setup. * It is optional to link against Python3_LIBRARIES. Check that and don't do it if they don't exist for this config. * Clean and auditwheel need to operate on sanitized package names. So "torch_mlir" vs "torch-mlir". * Adds a pyproject.toml file that pins the build dependencies needed to detect both Torch and Python (the MLIR Python build was failing to detect because Numpy wasn't in the pip venv). * Commented out auditwheel: These wheels are not PyPi compliant since they weak link to libtorch at runtime. However, they should be fine to deploy to users. * Adds the --extra-index-url to the pip wheel command, allowing PyTorch to be found. * Hack setup.py to remove the _mlir_libs dir before building. This keeps back-to-back versions from accumulating in the wheels for subsequent versions. IREE has a more principled way of doing this, but what I have here should work. Co-authored-by: Stella Laurenzo <stellaraccident@gmail.com>
2022-04-21 17:19:12 +08:00
# Test Requirements
pillow