Delete setup.py
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setup.py
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# Copyright 2024 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/main/setup.py
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To create the package for PyPI.
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1. Run `make pre-release` (or `make pre-patch` for a patch release) then run `make fix-copies` to fix the index of the
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documentation.
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If releasing on a special branch, copy the updated README.md on the main branch for the commit you will make
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for the post-release and run `make fix-copies` on the main branch as well.
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2. Unpin specific versions from setup.py that use a git install.
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3. Checkout the release branch (v<RELEASE>-release, for example v4.19-release), and commit these changes with the
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message: "Release: <RELEASE>" and push.
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4. Manually trigger the "Nightly and release tests on main/release branch" workflow from the release branch. Wait for
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the tests to complete. We can safely ignore the known test failures.
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5. Wait for the tests on main to be completed and be green (otherwise revert and fix bugs).
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6. Add a tag in git to mark the release: "git tag v<RELEASE> -m 'Adds tag v<RELEASE> for PyPI'"
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Push the tag to git: git push --tags origin v<RELEASE>-release
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7. Build both the sources and the wheel. Do not change anything in setup.py between
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creating the wheel and the source distribution (obviously).
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For the wheel, run: "python setup.py bdist_wheel" in the top level directory
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(This will build a wheel for the Python version you use to build it).
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For the sources, run: "python setup.py sdist"
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You should now have a /dist directory with both .whl and .tar.gz source versions.
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Long story cut short, you need to run both before you can upload the distribution to the
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test PyPI and the actual PyPI servers:
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python setup.py bdist_wheel && python setup.py sdist
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8. Check that everything looks correct by uploading the package to the PyPI test server:
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twine upload dist/* -r pypitest
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(pypi suggests using twine as other methods upload files via plaintext.)
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You may have to specify the repository url, use the following command then:
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twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
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Check that you can install it in a virtualenv by running:
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pip install -i https://testpypi.python.org/pypi diffusers
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If you are testing from a Colab Notebook, for instance, then do:
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pip install diffusers && pip uninstall diffusers
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pip install -i https://testpypi.python.org/pypi diffusers
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Check you can run the following commands:
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python -c "from diffusers import __version__; print(__version__)"
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python -c "from diffusers import DiffusionPipeline; pipe = DiffusionPipeline.from_pretrained('fusing/unet-ldm-dummy-update'); pipe()"
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python -c "from diffusers import DiffusionPipeline; pipe = DiffusionPipeline.from_pretrained('hf-internal-testing/tiny-stable-diffusion-pipe', safety_checker=None); pipe('ah suh du')"
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python -c "from diffusers import *"
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9. Upload the final version to the actual PyPI:
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twine upload dist/* -r pypi
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10. Prepare the release notes and publish them on GitHub once everything is looking hunky-dory. You can use the following
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Space to fetch all the commits applicable for the release: https://huggingface.co/spaces/sayakpaul/auto-release-notes-diffusers.
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It automatically fetches the correct tag and branch but also provides the option to configure them.
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`tag` should be the previous release tag (v0.26.1, for example), and `branch` should be
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the latest release branch (v0.27.0-release, for example). It denotes all commits that have happened on branch
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v0.27.0-release after the tag v0.26.1 was created.
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11. Run `make post-release` (or, for a patch release, `make post-patch`). If you were on a branch for the release,
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you need to go back to main before executing this.
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"""
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import os
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import re
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import sys
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from setuptools import Command, find_packages, setup
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# IMPORTANT:
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# 1. all dependencies should be listed here with their version requirements if any
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# 2. once modified, run: `make deps_table_update` to update src/diffusers/dependency_versions_table.py
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_deps = [
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"Pillow", # keep the PIL.Image.Resampling deprecation away
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"accelerate>=0.31.0",
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"compel==0.1.8",
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"datasets",
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"filelock",
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"flax>=0.4.1",
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"hf-doc-builder>=0.3.0",
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"huggingface-hub>=0.27.0",
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"requests-mock==1.10.0",
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"importlib_metadata",
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"invisible-watermark>=0.2.0",
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"isort>=5.5.4",
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"jax>=0.4.1",
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"jaxlib>=0.4.1",
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"Jinja2",
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"k-diffusion>=0.0.12",
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"torchsde",
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"note_seq",
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"librosa",
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"numpy",
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"parameterized",
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"peft>=0.15.0",
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"protobuf>=3.20.3,<4",
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"pytest",
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"pytest-timeout",
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"pytest-xdist",
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"python>=3.8.0",
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"ruff==0.9.10",
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"safetensors>=0.3.1",
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"sentencepiece>=0.1.91,!=0.1.92",
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"GitPython<3.1.19",
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"scipy",
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"onnx",
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"optimum_quanto>=0.2.6",
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"gguf>=0.10.0",
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"torchao>=0.7.0",
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"bitsandbytes>=0.43.3",
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"regex!=2019.12.17",
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"requests",
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"tensorboard",
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"tiktoken>=0.7.0",
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"torch>=1.4",
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"torchvision",
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"transformers>=4.41.2",
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"urllib3<=2.0.0",
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"black",
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"phonemizer",
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"opencv-python",
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]
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# this is a lookup table with items like:
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#
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# tokenizers: "huggingface-hub==0.8.0"
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# packaging: "packaging"
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#
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# some of the values are versioned whereas others aren't.
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deps = {b: a for a, b in (re.findall(r"^(([^!=<>~]+)(?:[!=<>~].*)?$)", x)[0] for x in _deps)}
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# since we save this data in src/diffusers/dependency_versions_table.py it can be easily accessed from
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# anywhere. If you need to quickly access the data from this table in a shell, you can do so easily with:
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#
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# python -c 'import sys; from diffusers.dependency_versions_table import deps; \
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# print(" ".join([deps[x] for x in sys.argv[1:]]))' tokenizers datasets
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#
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# Just pass the desired package names to that script as it's shown with 2 packages above.
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#
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# If diffusers is not yet installed and the work is done from the cloned repo remember to add `PYTHONPATH=src` to the script above
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#
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# You can then feed this for example to `pip`:
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#
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# pip install -U $(python -c 'import sys; from diffusers.dependency_versions_table import deps; \
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# print(" ".join([deps[x] for x in sys.argv[1:]]))' tokenizers datasets)
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#
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def deps_list(*pkgs):
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return [deps[pkg] for pkg in pkgs]
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class DepsTableUpdateCommand(Command):
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"""
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A custom command that updates the dependency table.
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usage: python setup.py deps_table_update
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"""
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description = "build runtime dependency table"
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user_options = [
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# format: (long option, short option, description).
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(
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"dep-table-update",
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None,
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"updates src/diffusers/dependency_versions_table.py",
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),
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]
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def initialize_options(self):
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pass
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def finalize_options(self):
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pass
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def run(self):
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entries = "\n".join([f' "{k}": "{v}",' for k, v in deps.items()])
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content = [
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"# THIS FILE HAS BEEN AUTOGENERATED. To update:",
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"# 1. modify the `_deps` dict in setup.py",
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"# 2. run `make deps_table_update`",
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"deps = {",
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entries,
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"}",
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"",
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]
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target = "src/diffusers/dependency_versions_table.py"
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print(f"updating {target}")
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with open(target, "w", encoding="utf-8", newline="\n") as f:
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f.write("\n".join(content))
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extras = {}
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extras["quality"] = deps_list("urllib3", "isort", "ruff", "hf-doc-builder")
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extras["docs"] = deps_list("hf-doc-builder")
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extras["training"] = deps_list("accelerate", "datasets", "protobuf", "tensorboard", "Jinja2", "peft")
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extras["test"] = deps_list(
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"compel",
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"GitPython",
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"datasets",
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"Jinja2",
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"invisible-watermark",
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"k-diffusion",
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"librosa",
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"parameterized",
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"pytest",
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"pytest-timeout",
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"pytest-xdist",
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"requests-mock",
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"safetensors",
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"sentencepiece",
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"scipy",
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"tiktoken",
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"torchvision",
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"transformers",
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"phonemizer",
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)
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extras["torch"] = deps_list("torch", "accelerate")
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extras["bitsandbytes"] = deps_list("bitsandbytes", "accelerate")
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extras["gguf"] = deps_list("gguf", "accelerate")
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extras["optimum_quanto"] = deps_list("optimum_quanto", "accelerate")
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extras["torchao"] = deps_list("torchao", "accelerate")
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if os.name == "nt": # windows
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extras["flax"] = [] # jax is not supported on windows
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else:
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extras["flax"] = deps_list("jax", "jaxlib", "flax")
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extras["dev"] = (
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extras["quality"] + extras["test"] + extras["training"] + extras["docs"] + extras["torch"] + extras["flax"]
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)
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install_requires = [
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deps["importlib_metadata"],
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deps["filelock"],
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deps["huggingface-hub"],
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deps["numpy"],
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deps["regex"],
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deps["requests"],
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deps["safetensors"],
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deps["Pillow"],
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]
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version_range_max = max(sys.version_info[1], 10) + 1
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setup(
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name="diffusers",
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version="0.34.0.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)
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description="State-of-the-art diffusion in PyTorch and JAX.",
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long_description=open("README.md", "r", encoding="utf-8").read(),
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long_description_content_type="text/markdown",
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keywords="deep learning diffusion jax pytorch stable diffusion audioldm",
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license="Apache 2.0 License",
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author="The Hugging Face team (past and future) with the help of all our contributors (https://github.com/huggingface/diffusers/graphs/contributors)",
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author_email="diffusers@huggingface.co",
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url="https://github.com/huggingface/diffusers",
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package_dir={"": "src"},
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packages=find_packages("src"),
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package_data={"diffusers": ["py.typed"]},
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include_package_data=True,
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python_requires=">=3.8.0",
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install_requires=list(install_requires),
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extras_require=extras,
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entry_points={"console_scripts": ["diffusers-cli=diffusers.commands.diffusers_cli:main"]},
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classifiers=[
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"Development Status :: 5 - Production/Stable",
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"Intended Audience :: Developers",
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"Intended Audience :: Education",
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"Intended Audience :: Science/Research",
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"License :: OSI Approved :: Apache Software License",
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"Operating System :: OS Independent",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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"Programming Language :: Python :: 3",
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]
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+ [f"Programming Language :: Python :: 3.{i}" for i in range(8, version_range_max)],
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cmdclass={"deps_table_update": DepsTableUpdateCommand},
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)
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