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# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/main/setup.py
To create the package for pypi.
1. Run `make pre-release` (or `make pre-patch` for a patch release) then run `make fix-copies` to fix the index of the
documentation.
If releasing on a special branch, copy the updated README.md on the main branch for your the commit you will make
for the post-release and run `make fix-copies` on the main branch as well.
2. Run Tests for Amazon Sagemaker. The documentation is located in `./tests/sagemaker/README.md`, otherwise @philschmid.
3. Unpin specific versions from setup.py that use a git install.
4. Checkout the release branch (v<RELEASE>-release, for example v4.19-release), and commit these changes with the
message: "Release: <RELEASE>" and push.
5. Wait for the tests on main to be completed and be green (otherwise revert and fix bugs)
6. Add a tag in git to mark the release: "git tag v<RELEASE> -m 'Adds tag v<RELEASE> for pypi' "
Push the tag to git: git push --tags origin v<RELEASE>-release
7. Build both the sources and the wheel. Do not change anything in setup.py between
creating the wheel and the source distribution (obviously).
For the wheel, run: "python setup.py bdist_wheel" in the top level directory.
(this will build a wheel for the python version you use to build it).
For the sources, run: "python setup.py sdist"
You should now have a /dist directory with both .whl and .tar.gz source versions.
8. Check that everything looks correct by uploading the package to the pypi test server:
twine upload dist/* -r pypitest
(pypi suggest using twine as other methods upload files via plaintext.)
You may have to specify the repository url, use the following command then:
twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
Check that you can install it in a virtualenv by running:
pip install -i https://testpypi.python.org/pypi diffusers
Check you can run the following commands:
python -c "from diffusers import pipeline; classifier = pipeline('text-classification'); print(classifier('What a nice release'))"
python -c "from diffusers import *"
9. Upload the final version to actual pypi:
twine upload dist/* -r pypi
10. Copy the release notes from RELEASE.md to the tag in github once everything is looking hunky-dory.
11. Run `make post-release` (or, for a patch release, `make post-patch`). If you were on a branch for the release,
you need to go back to main before executing this.
"""
import os
import re
from distutils.core import Command
from setuptools import find_packages, setup
# IMPORTANT:
# 1. all dependencies should be listed here with their version requirements if any
# 2. once modified, run: `make deps_table_update` to update src/diffusers/dependency_versions_table.py
_deps = [
"Pillow", # keep the PIL.Image.Resampling deprecation away
"accelerate>=0.11.0",
"compel==0.1.8",
"black~=23.1",
"datasets",
"filelock",
"flax>=0.4.1",
"hf-doc-builder>=0.3.0",
"huggingface-hub>=0.13.2",
"requests-mock==1.10.0",
"importlib_metadata",
"invisible-watermark",
"isort>=5.5.4",
"jax>=0.2.8,!=0.3.2",
"jaxlib>=0.1.65",
"Jinja2",
"k-diffusion>=0.0.12",
"torchsde",
"note_seq",
"librosa",
"numpy",
"omegaconf",
"parameterized",
"protobuf>=3.20.3,<4",
"pytest",
"pytest-timeout",
"pytest-xdist",
"ruff>=0.0.241",
"safetensors",
"sentencepiece>=0.1.91,!=0.1.92",
"scipy",
"onnx",
"regex!=2019.12.17",
"requests",
"tensorboard",
"torch>=1.4",
"torchvision",
"transformers>=4.25.1",
"urllib3<=2.0.0",
]
# this is a lookup table with items like:
#
# tokenizers: "huggingface-hub==0.8.0"
# packaging: "packaging"
#
# some of the values are versioned whereas others aren't.
deps = {b: a for a, b in (re.findall(r"^(([^!=<>~]+)(?:[!=<>~].*)?$)", x)[0] for x in _deps)}
# since we save this data in src/diffusers/dependency_versions_table.py it can be easily accessed from
# anywhere. If you need to quickly access the data from this table in a shell, you can do so easily with:
#
# python -c 'import sys; from diffusers.dependency_versions_table import deps; \
# print(" ".join([ deps[x] for x in sys.argv[1:]]))' tokenizers datasets
#
# Just pass the desired package names to that script as it's shown with 2 packages above.
#
# If diffusers is not yet installed and the work is done from the cloned repo remember to add `PYTHONPATH=src` to the script above
#
# You can then feed this for example to `pip`:
#
# pip install -U $(python -c 'import sys; from diffusers.dependency_versions_table import deps; \
# print(" ".join([ deps[x] for x in sys.argv[1:]]))' tokenizers datasets)
#
def deps_list(*pkgs):
return [deps[pkg] for pkg in pkgs]
class DepsTableUpdateCommand(Command):
"""
A custom distutils command that updates the dependency table.
usage: python setup.py deps_table_update
"""
description = "build runtime dependency table"
user_options = [
# format: (long option, short option, description).
("dep-table-update", None, "updates src/diffusers/dependency_versions_table.py"),
]
def initialize_options(self):
pass
def finalize_options(self):
pass
def run(self):
entries = "\n".join([f' "{k}": "{v}",' for k, v in deps.items()])
content = [
"# THIS FILE HAS BEEN AUTOGENERATED. To update:",
"# 1. modify the `_deps` dict in setup.py",
"# 2. run `make deps_table_update``",
"deps = {",
entries,
"}",
"",
]
target = "src/diffusers/dependency_versions_table.py"
print(f"updating {target}")
with open(target, "w", encoding="utf-8", newline="\n") as f:
f.write("\n".join(content))
extras = {}
extras = {}
extras["quality"] = deps_list("urllib3", "black", "isort", "ruff", "hf-doc-builder")
extras["docs"] = deps_list("hf-doc-builder")
extras["training"] = deps_list("accelerate", "datasets", "protobuf", "tensorboard", "Jinja2")
extras["test"] = deps_list(
"compel",
"datasets",
"Jinja2",
"invisible-watermark",
"k-diffusion",
"librosa",
"omegaconf",
"parameterized",
"pytest",
"pytest-timeout",
"pytest-xdist",
"requests-mock",
"safetensors",
"sentencepiece",
"scipy",
"torchvision",
"transformers",
)
extras["torch"] = deps_list("torch", "accelerate")
if os.name == "nt": # windows
extras["flax"] = [] # jax is not supported on windows
else:
extras["flax"] = deps_list("jax", "jaxlib", "flax")
extras["dev"] = (
extras["quality"] + extras["test"] + extras["training"] + extras["docs"] + extras["torch"] + extras["flax"]
)
install_requires = [
deps["importlib_metadata"],
deps["filelock"],
deps["huggingface-hub"],
deps["numpy"],
deps["regex"],
deps["requests"],
deps["Pillow"],
]
setup(
name="diffusers",
version="0.18.0.dev0", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
description="Diffusers",
long_description=open("README.md", "r", encoding="utf-8").read(),
long_description_content_type="text/markdown",
keywords="deep learning",
license="Apache",
author="The HuggingFace team",
author_email="patrick@huggingface.co",
url="https://github.com/huggingface/diffusers",
package_dir={"": "src"},
packages=find_packages("src"),
include_package_data=True,
python_requires=">=3.7.0",
install_requires=install_requires,
extras_require=extras,
entry_points={"console_scripts": ["diffusers-cli=diffusers.commands.diffusers_cli:main"]},
classifiers=[
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
cmdclass={"deps_table_update": DepsTableUpdateCommand},
)
# Release checklist
# 1. Change the version in __init__.py and setup.py.
# 2. Commit these changes with the message: "Release: Release"
# 3. Add a tag in git to mark the release: "git tag RELEASE -m 'Adds tag RELEASE for pypi' "
# Push the tag to git: git push --tags origin main
# 4. Run the following commands in the top-level directory:
# python setup.py bdist_wheel
# python setup.py sdist
# 5. Upload the package to the pypi test server first:
# twine upload dist/* -r pypitest
# twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
# 6. Check that you can install it in a virtualenv by running:
# pip install -i https://testpypi.python.org/pypi diffusers
# diffusers env
# diffusers test
# 7. Upload the final version to actual pypi:
# twine upload dist/* -r pypi
# 8. Add release notes to the tag in github once everything is looking hunky-dory.
# 9. Update the version in __init__.py, setup.py to the new version "-dev" and push to master
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