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e76b79a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from setuptools import setup
with open("esm/version.py") as infile:
exec(infile.read())
with open("README.md") as f:
readme = f.read()
extras = {
"esmfold": [ # OpenFold does not automatically pip install requirements, so we add them here.
"biopython",
"deepspeed==0.5.9",
"dm-tree",
"pytorch-lightning",
"omegaconf",
"ml-collections",
"einops",
"scipy",
]
}
sources = {
"esm": "esm",
"esm.model": "esm/model",
"esm.inverse_folding": "esm/inverse_folding",
"esm.esmfold.v1": "esm/esmfold/v1",
"esm.scripts": "scripts"
}
setup(
name="fair-esm",
version=version,
description="Evolutionary Scale Modeling (esm): Pretrained language models for proteins. From Facebook AI Research.",
long_description=readme,
long_description_content_type="text/markdown",
author="Facebook AI Research",
url="https://github.com/facebookresearch/esm",
license="MIT",
packages=sources.keys(),
package_dir=sources,
extras_require=extras,
data_files=[("source_docs/esm", ["LICENSE", "README.md", "CODE_OF_CONDUCT.rst"])],
zip_safe=True,
entry_points={
"console_scripts": [
"esm-extract=esm.scripts.extract:main",
"esm-fold=esm.scripts.fold:main",
]
},
)
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