201 lines
6.6 KiB
Python
201 lines
6.6 KiB
Python
"""Script to create (and optionally install) a `.whl` archive for Keras Core.
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Usage:
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1. Create a `.whl` file in `dist/`:
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```
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python3 pip_build.py
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```
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2. Also install the new package immediately after:
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```
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python3 pip_build.py --install
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```
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"""
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import argparse
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import glob
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import os
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import pathlib
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import shutil
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import namex
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# Needed because importing torch after TF causes the runtime to crash
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import torch # noqa: F401
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package = "keras_core"
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build_directory = "tmp_build_dir"
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dist_directory = "dist"
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to_copy = ["setup.py", "README.md"]
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def ignore_files(_, filenames):
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return [f for f in filenames if f.endswith("_test.py")]
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def copy_source_to_build_directory(root_path):
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# Copy sources (`keras_core/` directory and setup files) to build
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# directory
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os.chdir(root_path)
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os.mkdir(build_directory)
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shutil.copytree(
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package, os.path.join(build_directory, package), ignore=ignore_files
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)
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for fname in to_copy:
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shutil.copy(fname, os.path.join(f"{build_directory}", fname))
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os.chdir(build_directory)
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def run_namex_conversion():
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# Restructure the codebase so that source files live in `keras_core/src`
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namex.convert_codebase(package, code_directory="src")
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# Generate API __init__.py files in `keras_core/`
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namex.generate_api_files(package, code_directory="src", verbose=True)
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def create_legacy_directory():
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# Make keras_core/_tf_keras/ by copying keras_core/
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tf_keras_dirpath = os.path.join(package, "_tf_keras")
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os.makedirs(tf_keras_dirpath)
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with open(os.path.join(package, "__init__.py")) as f:
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init_file = f.read()
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init_file = init_file.replace(
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"from keras_core import _legacy",
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"from keras_core import _tf_keras",
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)
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with open(os.path.join(package, "__init__.py"), "w") as f:
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f.write(init_file)
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with open(os.path.join(tf_keras_dirpath, "__init__.py"), "w") as f:
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f.write(init_file)
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for dirname in os.listdir(package):
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dirpath = os.path.join(package, dirname)
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if os.path.isdir(dirpath) and dirname not in (
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"_legacy",
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"_tf_keras",
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"src",
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):
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shutil.copytree(
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dirpath,
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os.path.join(tf_keras_dirpath, dirname),
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ignore=ignore_files,
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)
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# Copy keras_core/_legacy/ file contents to keras_core/_tf_keras/
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legacy_submodules = [
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path[:-3]
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for path in os.listdir(os.path.join(package, "src", "legacy"))
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if path.endswith(".py")
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]
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legacy_submodules += [
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path
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for path in os.listdir(os.path.join(package, "src", "legacy"))
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if os.path.isdir(os.path.join(package, "src", "legacy", path))
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]
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for root, _, fnames in os.walk(os.path.join(package, "_legacy")):
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for fname in fnames:
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if fname.endswith(".py"):
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legacy_fpath = os.path.join(root, fname)
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tf_keras_root = root.replace("/_legacy", "/_tf_keras")
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core_api_fpath = os.path.join(
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root.replace("/_legacy", ""), fname
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)
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if not os.path.exists(tf_keras_root):
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os.makedirs(tf_keras_root)
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tf_keras_fpath = os.path.join(tf_keras_root, fname)
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with open(legacy_fpath) as f:
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legacy_contents = f.read()
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legacy_contents = legacy_contents.replace(
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"keras_core._legacy", "keras_core._tf_keras"
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)
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if os.path.exists(core_api_fpath):
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with open(core_api_fpath) as f:
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core_api_contents = f.read()
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core_api_contents = core_api_contents.replace(
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"from keras_core import _tf_keras\n", ""
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)
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for legacy_submodule in legacy_submodules:
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core_api_contents = core_api_contents.replace(
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f"from keras_core import {legacy_submodule}\n",
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"",
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)
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core_api_contents = core_api_contents.replace(
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f"keras_core.{legacy_submodule}",
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f"keras_core._tf_keras.{legacy_submodule}",
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)
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legacy_contents = core_api_contents + "\n" + legacy_contents
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with open(tf_keras_fpath, "w") as f:
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f.write(legacy_contents)
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# Delete keras_core/_legacy/
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shutil.rmtree(os.path.join(package, "_legacy"))
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def export_version_string(__version__):
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# Make sure to export the __version__ string
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with open(os.path.join(package, "__init__.py")) as f:
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init_contents = f.read()
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with open(os.path.join(package, "__init__.py"), "w") as f:
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f.write(init_contents + "\n\n" + f'__version__ = "{__version__}"\n')
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def build_and_save_output(root_path, __version__):
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# Build the package
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os.system("python3 -m build")
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# Save the dist files generated by the build process
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os.chdir(root_path)
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if not os.path.exists(dist_directory):
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os.mkdir(dist_directory)
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for fpath in glob.glob(
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os.path.join(build_directory, dist_directory, "*.*")
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):
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shutil.copy(fpath, dist_directory)
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# Find the .whl file path
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whl_path = None
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for fname in os.listdir(dist_directory):
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if __version__ in fname and fname.endswith(".whl"):
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whl_path = os.path.abspath(os.path.join(dist_directory, fname))
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print(f"Build successful. Wheel file available at {whl_path}")
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return whl_path
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def build(root_path):
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if os.path.exists(build_directory):
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raise ValueError(f"Directory already exists: {build_directory}")
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try:
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copy_source_to_build_directory(root_path)
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run_namex_conversion()
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create_legacy_directory()
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from keras_core.src.version import __version__ # noqa: E402
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export_version_string(__version__)
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return build_and_save_output(root_path, __version__)
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finally:
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# Clean up: remove the build directory (no longer needed)
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shutil.rmtree(build_directory)
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def install_whl(whl_fpath):
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print(f"Installing wheel file: {whl_fpath}")
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os.system(f"pip3 install {whl_fpath} --force-reinstall --no-dependencies")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--install",
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action="store_true",
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help="Whether to install the generated wheel file.",
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)
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args = parser.parse_args()
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root_path = pathlib.Path(__file__).parent.resolve()
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whl_path = build(root_path)
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if whl_path and args.install:
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install_whl(whl_path)
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