diffusers/setup.py at main · superlabs-dev/diffusers · GitHub

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# 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",

"isort>=5.5.4",

"jax>=0.2.8,!=0.3.2",

"jaxlib>=0.1.65",

"Jinja2",

"k-diffusion>=0.0.12",

"librosa",

"numpy",

"parameterized",

"protobuf>=3.20.3,<4",

"pytest",

"pytest-timeout",

"pytest-xdist",

"ruff>=0.0.241",

"safetensors",

"sentencepiece>=0.1.91,!=0.1.92",

"scipy",

"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["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",

"k-diffusion",

"librosa",

"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="0.17.0.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

diffusers/setup.py at main · superlabs-dev/diffusers · GitHub

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