зеркало из https://github.com/microsoft/hi-ml.git
135 строки
3.9 KiB
Makefile
135 строки
3.9 KiB
Makefile
# Make commands for the toolbox users
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# Create a Conda environment for use with both the hi-ml and hi-ml-azure folder
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env:
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conda env create --file hi-ml/environment.yml
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# Make commands that are used in the build pipeline
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# call make for each sub package
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define call_packages
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cd hi-ml && $(MAKE) $(1)
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cd hi-ml-azure && $(MAKE) $(1)
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cd hi-ml-cpath && $(MAKE) $(1)
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cd hi-ml-multimodal && $(MAKE) $(1)
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endef
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define call_pip_packages
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cd hi-ml && $(MAKE) $(1)
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cd hi-ml-azure && $(MAKE) $(1)
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endef
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## Package management
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# pip upgrade.
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# As of PIP version 24.1, conditions like ">1.8.*" are no longer supported, but pytorch lightning
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# in the version we are using is still using this syntax. So we need to restrict the pip versions.
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pip_upgrade:
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python -m pip install --upgrade "pip<24.1"
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# pip upgrade and install build requirements
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pip_build: pip_upgrade
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pip install -r build_requirements.txt
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# pip upgrade and install test requirements
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pip_test: pip_upgrade
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pip install -r test_requirements.txt
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# pip install local packages in editable mode for development and testing
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call_pip_local:
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$(call call_pip_packages,call_pip_local)
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# pip upgrade and install local packages in editable mode
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pip_local: pip_upgrade call_pip_local
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# pip install everything for local development and testing
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pip: pip_build pip_test call_pip_local
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# update current conda environment
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conda_update:
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conda env update -n $(CONDA_DEFAULT_ENV) --file hi-ml/environment.yml
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# Set the conda environment for local development work, that contains all packages need for hi-ml, hi-ml-azure
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# and hi-ml-cpath with hi-ml and hi-ml-azure installed in editable mode
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conda: conda_update call_pip_local
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## Actions
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# clean build artifacts
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clean:
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rm -rf ./.mypy_cache ./.pytest_cache ./coverage ./logs ./outputs
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rm -f ./coverage.txt ./coverage.xml ./most_recent_run.txt
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$(call call_packages,clean)
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# build package, assuming build requirements already installed
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call_build:
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$(call call_pip_packages,call_build)
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# pip install build requirements and build package
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build: pip_build call_build
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# run flake8, assuming test requirements already installed
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flake8:
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$(call call_packages,flake8)
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# run mypy, assuming test requirements already installed
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mypy:
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$(call call_packages,mypy)
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# run black styling, assuming test requirements already installed
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black:
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$(call call_packages,black)
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# run pyright, assuming test requirements already installed
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call_pyright:
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npm install -g pyright
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pyright
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# conda install test requirements and run pyright
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pyright: conda call_pyright
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# run basic checks, assuming test requirements already installed
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check: flake8 mypy black
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# run pytest on package, assuming test requirements already installed
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pytest:
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$(call call_packages,pytest)
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# run pytest fast subset on package, assuming test requirements already installed
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pytest_fast:
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$(call call_pip_packages,pytest_fast)
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# run pytest with coverage on package, and format coverage output as a text file, assuming test requirements already installed
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call_pytest_and_coverage:
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$(call call_pip_packages,call_pytest_and_coverage)
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# install test requirements and run pytest coverage
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pytest_and_coverage: pip_test call_pytest_and_coverage
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# install test requirements and run all tests
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test_all: pip_test flake8 mypy call_pytest_and_coverage
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# build the github format_coverage action
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action:
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cd .github/actions/format_coverage && ncc build index.js --license licenses.txt
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combine: pip_test
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mkdir -p coverage
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cp hi-ml/.coverage coverage/hi-ml-coverage
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cp hi-ml-azure/.coverage coverage/hi-ml-azure-coverage
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cp hi-ml-cpath/.coverage coverage/hi-ml-cpath-coverage
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cp .coveragerc coverage/
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cd coverage && \
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coverage combine hi-ml-coverage hi-ml-azure-coverage hi-ml-cpath-coverage && \
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coverage html && \
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coverage xml && \
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pycobertura show --format text --output coverage.txt coverage.xml
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blobfuse:
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setup/prepare_blobfuse_installation.sh
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sudo apt-get install blobfuse fuse
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mount:
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setup/mount_datastores.sh
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