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	| """ | |
| Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/master/setup.py | |
| To create the package for pypi. | |
| 1. Change the version in __init__.py and setup.py. | |
| 2. Commit these changes with the message: "Release: VERSION" | |
| 3. Add a tag in git to mark the release: "git tag VERSION -m'Adds tag VERSION for pypi' " | |
| Push the tag to git: git push --tags origin master | |
| 4. 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 allennlp directory. | |
| (this will build a wheel for the python version you use to build it - make sure you use python 3.x). | |
| For the sources, run: "python setup.py sdist" | |
| You should now have a /dist directory with both .whl and .tar.gz source versions of allennlp. | |
| 5. 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.) | |
| Check that you can install it in a virtualenv by running: | |
| pip install -i https://testpypi.python.org/pypi allennlp | |
| 6. Upload the final version to actual pypi: | |
| twine upload dist/* -r pypi | |
| 7. Copy the release notes from RELEASE.md to the tag in github once everything is looking hunky-dory. | |
| """ | |
| from io import open | |
| from setuptools import find_packages, setup | |
| setup( | |
| name="pytorch_pretrained_biggan", | |
| version="0.1.0", | |
| author="Thomas Wolf", | |
| author_email="thomas@huggingface.co", | |
| description="PyTorch version of DeepMind's BigGAN model with pre-trained models", | |
| long_description=open("README.md", "r", encoding='utf-8').read(), | |
| long_description_content_type="text/markdown", | |
| keywords='BIGGAN GAN deep learning google deepmind', | |
| license='Apache', | |
| url="https://github.com/huggingface/pytorch-pretrained-BigGAN", | |
| packages=find_packages(exclude=["*.tests", "*.tests.*", | |
| "tests.*", "tests"]), | |
| install_requires=['torch>=0.4.1', | |
| 'numpy', | |
| 'boto3', | |
| 'requests', | |
| 'tqdm'], | |
| tests_require=['pytest'], | |
| entry_points={ | |
| 'console_scripts': [ | |
| "pytorch_pretrained_biggan=pytorch_pretrained_biggan.convert_tf_to_pytorch:main", | |
| ] | |
| }, | |
| classifiers=[ | |
| 'Intended Audience :: Science/Research', | |
| 'License :: OSI Approved :: Apache Software License', | |
| 'Programming Language :: Python :: 3', | |
| 'Topic :: Scientific/Engineering :: Artificial Intelligence', | |
| ], | |
| ) | |
