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setup.py
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setup.py
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import os
import setuptools
here = os.path.abspath(os.path.dirname(__file__))
with open("README.md", encoding="UTF-8") as fh:
long_description = fh.read()
# Get the code version
version = {}
with open(os.path.join(here, "flaml/version.py")) as fp:
exec(fp.read(), version)
__version__ = version["__version__"]
install_requires = [
"NumPy>=1.17",
]
setuptools.setup(
name="FLAML",
version=__version__,
author="Microsoft Corporation",
author_email="hpo@microsoft.com",
description="A fast library for automated machine learning and tuning",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/microsoft/FLAML",
packages=setuptools.find_packages(include=["flaml*"]),
package_data={
"flaml.default": ["*/*.json"],
},
include_package_data=True,
install_requires=install_requires,
extras_require={
"automl": [
"lightgbm>=2.3.1",
"xgboost>=0.90,<3.0.0",
"scipy>=1.4.1",
"pandas>=1.1.4",
"scikit-learn>=1.0.0",
],
"notebook": [
"jupyter",
],
"spark": [
"pyspark>=3.2.0",
"joblibspark>=0.5.0",
"joblib<=1.3.2",
],
"test": [
"jupyter",
"lightgbm>=2.3.1",
"xgboost>=0.90,<2.0.0",
"scipy>=1.4.1",
"pandas>=1.1.4,<2.0.0; python_version<'3.10'",
"pandas>=1.1.4; python_version>='3.10'",
"scikit-learn>=1.0.0",
"thop",
"pytest>=6.1.1",
"coverage>=5.3",
"pre-commit",
"torch",
"torchvision",
"catboost>=0.26,<1.2; python_version<'3.11'",
"catboost>=0.26; python_version>='3.11'",
"rgf-python",
"optuna>=2.8.0,<=3.6.1",
"openml",
"statsmodels>=0.12.2",
"psutil==5.8.0",
"dataclasses",
"transformers[torch]==4.26",
"datasets",
"nltk<=3.8.1", # 3.8.2 doesn't work with mlflow
"rouge_score",
"hcrystalball==0.1.10",
"seqeval",
"pytorch-forecasting>=0.9.0,<=0.10.1; python_version<'3.11'",
# "pytorch-forecasting==0.10.1; python_version=='3.11'",
"mlflow==2.15.1",
"joblibspark>=0.5.0",
"joblib<=1.3.2",
"nbconvert",
"nbformat",
"ipykernel",
"pytorch-lightning<1.9.1", # test_forecast_panel
"tensorboardX==2.6", # test_forecast_panel
"requests<2.29.0", # https://github.com/docker/docker-py/issues/3113
"packaging",
"pydantic==1.10.9",
"sympy",
"wolframalpha",
"dill", # a drop in replacement of pickle
],
"catboost": [
"catboost>=0.26,<1.2; python_version<'3.11'",
"catboost>=0.26,<=1.2.5; python_version>='3.11'",
],
"blendsearch": [
"optuna>=2.8.0,<=3.6.1",
"packaging",
],
"ray": [
"ray[tune]~=1.13",
],
"azureml": [
"azureml-mlflow",
],
"nni": [
"nni",
],
"vw": [
"vowpalwabbit>=8.10.0, <9.0.0",
"scikit-learn",
],
"hf": [
"transformers[torch]==4.26",
"datasets",
"nltk<=3.8.1",
"rouge_score",
"seqeval",
],
"nlp": [ # for backward compatibility; hf is the new option name
"transformers[torch]==4.26",
"datasets",
"nltk<=3.8.1",
"rouge_score",
"seqeval",
],
"ts_forecast": [
"holidays<0.14", # to prevent installation error for prophet
"prophet>=1.0.1",
"statsmodels>=0.12.2",
"hcrystalball==0.1.10",
],
"forecast": [
"holidays<0.14", # to prevent installation error for prophet
"prophet>=1.0.1",
"statsmodels>=0.12.2",
"hcrystalball==0.1.10",
"pytorch-forecasting>=0.9.0; python_version<'3.11'",
# "pytorch-forecasting==0.10.1; python_version=='3.11'",
"pytorch-lightning==1.9.0",
"tensorboardX==2.6",
],
"benchmark": ["catboost>=0.26", "psutil==5.8.0", "xgboost==1.3.3", "pandas==1.1.4"],
"openai": ["openai==0.27.8", "diskcache"],
"autogen": ["openai==0.27.8", "diskcache", "termcolor"],
"mathchat": ["openai==0.27.8", "diskcache", "termcolor", "sympy", "pydantic==1.10.9", "wolframalpha"],
"retrievechat": [
"openai==0.27.8",
"diskcache",
"termcolor",
"chromadb",
"tiktoken",
"sentence_transformers",
],
"synapse": [
"joblibspark>=0.5.0",
"optuna>=2.8.0,<=3.6.1",
"pyspark>=3.2.0",
],
"autozero": ["scikit-learn", "pandas", "packaging"],
},
classifiers=[
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
# Specify the Python versions you support here.
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
],
python_requires=">=3.8",
)