mirror of https://github.com/llvm/torch-mlir
Make docker instructions a bit more scoped
I was helping an engineer the other day who was attempting to use the Docker flow for interactive development and ran into countless issues. Add a note that it is not recommended for interactive development, and also move the Docker section down to avoid positioning it as the "default" that people should be using.pull/1428/head
Sean Silva
parent
fa5a8e21a3
commit
8a91e4c962
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@ -22,132 +22,6 @@ python -m pip install --upgrade pip
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python -m pip install -r requirements.txt
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```
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## Docker Builds
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We have preliminary support for building with Docker images. This is a new
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flow and we would like your feedback on how it works for you and please
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feel free to file any feedback or issues.
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Install [Docker Engine](https://docs.docker.com/engine/install/ubuntu/). You don't need Docker Desktop.
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You have three types of builds selectable with the Environment Variable `TM_PACKAGES`:`torch-mlir` the
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Release build, `out-of-tree` where torch-mlir is build with a pre-built MLIR and `in-tree` where torch-mlir
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is built as part of the LLVM project along with MLIR.
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We mount a ccache and pip cache inside the docker container to speed up iterative builds. Iterative
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builds should be as fast as running without docker.
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### In-Tree builds
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Build MLIR and Torch-MLIR together as part of the LLVM repo.
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```shell
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TM_PACKAGES="in-tree" ./build_tools/python_deploy/build_linux_packages.sh
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```
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### Out-of-Tree builds
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Build LLVM/MLIR first and then build Torch-MLIR referencing that build
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```shell
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TM_PACKAGES="out-of-tree" ./build_tools/python_deploy/build_linux_packages.sh
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```
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### Release builds
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Build in a manylinux Docker image so we can upload artifacts to PyPI.
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```shell
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TM_PACKAGES="torch-mlir" ./build_tools/python_deploy/build_linux_packages.sh
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```
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### Mimicing CI+Release builds
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If you wanted to build all the CIs locally
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```shell
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TM_PACKAGES="out-of-tree in-tree" ./build_tools/python_deploy/build_linux_packages.sh
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```
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If you wanted to build all the CIs and the Release builds (just with Python 3.10 since most other Python builds are redundant)
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```shell
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TM_PACKAGES="torch-mlir out-of-tree in-tree" TM_PYTHON_VERSIONS="cp310-cp310" ./build_tools/python_deploy/build_linux_packages.sh
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```
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Note: The Release docker still runs as root so it may generate some files owned by root:root. We hope to move it to run as a user in the future.
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### Cleaning up
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Docker builds tend to leave a wide variety of files around. Luckily most are owned by the user but there are still some that need to be removed
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as superuser.
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```shell
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rm -rf build build_oot llvm-build docker_venv externals/pytorch/build .ccache
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```
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## Building your own Docker image
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If you would like to build your own docker image (usually not necessary). You can run:
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```shell
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cd ./build_tools/docker
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docker build -t your-name/torch-mlir-ci --no-cache .
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```
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### Other configurable environmental variables
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The following additional environmental variables can be used to customie your docker build:
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* Custom Release Docker image:
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Defaults to `stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest`
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```shell
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TM_RELEASE_DOCKER_IMAGE="stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest"
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```
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* Custom CI Docker image:
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Defaults to `powderluv/torch-mlir-ci:latest`. This assumes an Ubuntu LTS like image. You can build your own with `./build_tools/docker/Dockerfile`
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```shell
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TM_CI_DOCKER_IMAGE="powderluv/torch-mlir-ci:latest"
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```
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* Custom Python Versions for Release builds:
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Version of Python to use in Release builds. Ignored in CIs. Defaults to `cp38-cp38 cp39-cp39 cp310-cp310`
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```shell
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TM_PYTHON_VERSIONS="cp38-cp38 cp39-cp39 cp310-cp310"
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```
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* Location to store Release build wheels
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```shell
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TM_OUTPUT_DIR="./build_tools/python_deploy/wheelhouse"
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```
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* What "packages" to build:
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Defaults to torch-mlir. Options are `torch-mlir out-of-tree in-tree`
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```shell
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TM_PACKAGES="torch-mlir out-of-tree in-tree"
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```
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* Use pre-built Pytorch:
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Defaults to using pre-built Pytorch. Setting it to `OFF` builds from source
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```shell
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TM_USE_PYTORCH_BINARY="OFF"
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```
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* Skip running tests
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Skip running tests if you want quick build only iteration. Default set to `OFF`
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```shell
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TM_SKIP_TESTS="OFF"
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```
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## Build Python Packages
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We have preliminary support for building Python packages. This can be done
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with the following commands:
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```
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python -m pip install --upgrade pip
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python -m pip install -r requirements.txt
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CMAKE_GENERATOR=Ninja python setup.py bdist_wheel
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```
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## CMake Build
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Two setups are possible to build: in-tree and out-of-tree. The in-tree setup is the most straightforward, as it will build LLVM dependencies as well.
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@ -300,6 +174,133 @@ Torch-MLIR can also be built using Bazel (apart from the official CMake build) f
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```
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3. Find the built binary at `utils/bazel/bazel-bin/external/torch-mlir/torch-mlir-opt`.
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## Docker Builds
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We have preliminary support for building with Docker images. Currently this
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is not very convenient for day-to-day interactive development and
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debugging flows but is very useful for reproducing failures
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from the CI. This is a new flow and we would like your feedback on how
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it works for you and please feel free to file any feedback or issues.
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Install [Docker Engine](https://docs.docker.com/engine/install/ubuntu/). You don't need Docker Desktop.
|
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|
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You have three types of builds selectable with the Environment Variable `TM_PACKAGES`:`torch-mlir` the
|
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Release build, `out-of-tree` where torch-mlir is build with a pre-built MLIR and `in-tree` where torch-mlir
|
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is built as part of the LLVM project along with MLIR.
|
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|
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We mount a ccache and pip cache inside the docker container to speed up iterative builds. Iterative
|
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builds should be as fast as running without docker.
|
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|
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### In-Tree builds
|
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|
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Build MLIR and Torch-MLIR together as part of the LLVM repo.
|
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|
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```shell
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TM_PACKAGES="in-tree" ./build_tools/python_deploy/build_linux_packages.sh
|
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```
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|
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### Out-of-Tree builds
|
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|
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Build LLVM/MLIR first and then build Torch-MLIR referencing that build
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```shell
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TM_PACKAGES="out-of-tree" ./build_tools/python_deploy/build_linux_packages.sh
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```
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### Release builds
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|
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Build in a manylinux Docker image so we can upload artifacts to PyPI.
|
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|
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```shell
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TM_PACKAGES="torch-mlir" ./build_tools/python_deploy/build_linux_packages.sh
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```
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|
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### Mimicing CI+Release builds
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|
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If you wanted to build all the CIs locally
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|
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```shell
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TM_PACKAGES="out-of-tree in-tree" ./build_tools/python_deploy/build_linux_packages.sh
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```
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|
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If you wanted to build all the CIs and the Release builds (just with Python 3.10 since most other Python builds are redundant)
|
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|
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```shell
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TM_PACKAGES="torch-mlir out-of-tree in-tree" TM_PYTHON_VERSIONS="cp310-cp310" ./build_tools/python_deploy/build_linux_packages.sh
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```
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|
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Note: The Release docker still runs as root so it may generate some files owned by root:root. We hope to move it to run as a user in the future.
|
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|
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### Cleaning up
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|
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Docker builds tend to leave a wide variety of files around. Luckily most are owned by the user but there are still some that need to be removed
|
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as superuser.
|
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|
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```shell
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rm -rf build build_oot llvm-build docker_venv externals/pytorch/build .ccache
|
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```
|
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|
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## Building your own Docker image
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|
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If you would like to build your own docker image (usually not necessary). You can run:
|
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|
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```shell
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cd ./build_tools/docker
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docker build -t your-name/torch-mlir-ci --no-cache .
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```
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### Other configurable environmental variables
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|
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The following additional environmental variables can be used to customie your docker build:
|
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|
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* Custom Release Docker image:
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Defaults to `stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest`
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```shell
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TM_RELEASE_DOCKER_IMAGE="stellaraccident/manylinux2014_x86_64-bazel-5.1.0:latest"
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```
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* Custom CI Docker image:
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Defaults to `powderluv/torch-mlir-ci:latest`. This assumes an Ubuntu LTS like image. You can build your own with `./build_tools/docker/Dockerfile`
|
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```shell
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TM_CI_DOCKER_IMAGE="powderluv/torch-mlir-ci:latest"
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```
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||||
|
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* Custom Python Versions for Release builds:
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||||
Version of Python to use in Release builds. Ignored in CIs. Defaults to `cp38-cp38 cp39-cp39 cp310-cp310`
|
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```shell
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TM_PYTHON_VERSIONS="cp38-cp38 cp39-cp39 cp310-cp310"
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```
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|
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* Location to store Release build wheels
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```shell
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TM_OUTPUT_DIR="./build_tools/python_deploy/wheelhouse"
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||||
```
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|
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* What "packages" to build:
|
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Defaults to torch-mlir. Options are `torch-mlir out-of-tree in-tree`
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```shell
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TM_PACKAGES="torch-mlir out-of-tree in-tree"
|
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```
|
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* Use pre-built Pytorch:
|
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Defaults to using pre-built Pytorch. Setting it to `OFF` builds from source
|
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```shell
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TM_USE_PYTORCH_BINARY="OFF"
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```
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* Skip running tests
|
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Skip running tests if you want quick build only iteration. Default set to `OFF`
|
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```shell
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TM_SKIP_TESTS="OFF"
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```
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|
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|
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## Build Python Packages
|
||||
|
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We have preliminary support for building Python packages. This can be done
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||||
with the following commands:
|
||||
|
||||
```
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python -m pip install --upgrade pip
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python -m pip install -r requirements.txt
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CMAKE_GENERATOR=Ninja python setup.py bdist_wheel
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||||
```
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|
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# Testing
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|
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Loading…
Reference in New Issue