mirror of
https://github.com/zama-ai/concrete.git
synced 2026-02-09 03:55:04 -05:00
5a2e9460fb
- Docker image to build wheels for linux_x86_64 CPython 3.[8,9,10] with GLIBC >= 2.24 - Specify which Python to use in Makefile - Fix cmake build to handle when libpython isn't available (cmake>3.18)
50 lines
1.5 KiB
Markdown
50 lines
1.5 KiB
Markdown
# Homomorphizer
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The homomorphizer is a compiler that takes a high level computation model and produces a programs that evaluate the model in an homomorphic way.
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## Build the Python Package
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Currently supported platforms:
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- Linux x86_64 for python 3.8, 3.9, and 3.10
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### Linux
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We use the [manylinux](https://github.com/pypa/manylinux) docker images for building python packages for Linux. Those packages should work on distributions that have GLIBC >= 2.24.
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You can use Make to build the python wheels using these docker images:
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```bash
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$ cd compiler
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$ make package_py38 # package_py39 package_py310
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```
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This will build the image for the appropriate python version then copy the wheels out under `/wheels`
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### Build wheels in your environment
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#### Temporary MLIR issue
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Due to an issue with MLIR, you will need to manually add `__init__.py` files to the `mlir` python package after the build.
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```bash
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$ make python-bindings
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$ touch build/tools/zamalang/python_packages/zamalang_core/mlir/__init__.py
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$ touch build/tools/zamalang/python_packages/zamalang_core/mlir/dialects/__init__.py
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```
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#### Build wheel
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Building the wheels is actually simple.
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```bash
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$ pip wheel --no-deps -w ../wheels .
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```
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Depending on the platform you are using (specially Linux), you might need to use `auditwheel` to specify the platform this wheel is targeting. For example, in our build of the package for Linux x86_64 and GLIBC 2.24, we also run:
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```bash
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$ auditwheel repair ../wheels/*.whl --plat manylinux_2_24_x86_64 -w ../wheels
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```
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