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setup.py
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setup.py
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"""tensorflow/datasets is a library of datasets ready to use with TensorFlow.
tensorflow/datasets is a library of public datasets ready to use with
TensorFlow. Each dataset definition contains the logic necessary to download and
prepare the dataset, as well as to read it into a model using the
`tf.data.Dataset` API.
Usage outside of TensorFlow is also supported.
See the README on GitHub for further documentation.
"""
import datetime
import itertools
import os
import sys
import pkg_resources
from setuptools import find_packages
from setuptools import setup
if '--nightly' in sys.argv:
nightly = True
sys.argv.remove('--nightly')
else:
nightly = False
project_name = 'tensorflow-datasets'
# To enable importing version.py directly, we add its path to sys.path.
version_path = os.path.join(
os.path.dirname(__file__), 'tensorflow_datasets')
sys.path.append(version_path)
from version import __version__ # pytype: disable=import-error # pylint: disable=g-import-not-at-top
if nightly:
project_name = 'tfds-nightly'
# Version as `X.Y.Z.dev199912312459`
datestring = (os.environ.get('TFDS_NIGHTLY_TIMESTAMP') or
datetime.datetime.now().strftime('%Y%m%d%H%M'))
curr_version = pkg_resources.parse_version(__version__)
__version__ = f'{curr_version.base_version}.dev{datestring}'
DOCLINES = __doc__.split('\n')
REQUIRED_PKGS = [
'absl-py',
'attrs>=18.1.0',
'dill', # TODO(tfds): move to TESTS_REQUIRE.
'future',
'numpy',
'promise',
'protobuf>=3.6.1',
'requests>=2.19.0',
'six',
'tensorflow-metadata',
'termcolor',
'tqdm',
# Standard library backports
'dataclasses;python_version<"3.7"',
'typing_extensions;python_version<"3.8"',
'importlib_resources;python_version<"3.9"',
]
TESTS_REQUIRE = [
'jupyter',
'mako',
'pytest',
'pytest-xdist',
# Lazy-deps required by core
'pandas',
'pydub',
'apache_beam',
# TFDV is only available for Python 3.6
'tensorflow-data-validation;python_version<"3.7"',
# TODO(b/142892342): Re-enable
# 'tensorflow-docs @ git+https://github.com/tensorflow/docs#egg=tensorflow-docs', # pylint: disable=line-too-long
]
# Additional deps for formatting
DEV_REQUIRE = [
'pylint>=2.6.0',
'yapf',
]
# Static files needed by datasets.
DATASET_FILES = [
'image_classification/caltech101_labels.txt',
'image_classification/categories_places365.txt',
'image_classification/cbis_ddsm_calc_distributions.txt',
'image_classification/cbis_ddsm_calc_types.txt',
'image_classification/cbis_ddsm_mass_margins.txt',
'image_classification/cbis_ddsm_mass_shapes.txt',
'image_classification/cbis_ddsm_patch_labels.txt',
'image_classification/dtd_key_attributes.txt',
'image_classification/food-101_classes.txt',
'image_classification/imagenet_resized_labels.txt',
'image_classification/imagenet2012_labels.txt',
'image_classification/imagenet2012_validation_labels.txt',
'image_classification/imagenette_labels.txt',
'image_classification/imagewang_labels.txt',
'image_classification/inaturalist_labels.txt',
'image_classification/inaturalist_supercategories.txt',
'image_classification/plant_leaves_urls.txt',
'image_classification/plantae_k_urls.txt',
'image_classification/quickdraw_labels.txt',
'image_classification/sun397_labels.txt',
'image_classification/sun397_tfds_te.txt',
'image_classification/sun397_tfds_tr.txt',
'image_classification/sun397_tfds_va.txt',
'image_classification/vgg_face2_labels.txt',
'object_detection/open_images_classes_all.txt',
'object_detection/open_images_classes_boxable.txt',
'object_detection/open_images_classes_trainable.txt',
'video/ucf101_labels.txt',
]
# Extra dependencies required by specific datasets
DATASET_EXTRAS = {
# In alphabetical order
'aflw2k3d': ['scipy'],
'c4': ['apache_beam', 'gcld3', 'langdetect', 'nltk', 'tldextract'],
'cats_vs_dogs': ['matplotlib'],
'colorectal_histology': ['Pillow'],
'common_voice': ['pydub'], # and ffmpeg installed
'eurosat': ['scikit-image', 'tifffile', 'imagecodecs'],
'groove': ['pretty_midi', 'pydub'],
'imagenet2012_corrupted': [
# This includes pre-built source; you may need to use an alternative
# route to install OpenCV
'opencv-python',
'scikit-image',
'scipy'
],
'librispeech': ['pydub'], # and ffmpeg installed
# sklearn version required to avoid conflict with librosa from
# https://github.com/scikit-learn/scikit-learn/issues/14485
# See https://github.com/librosa/librosa/issues/1160
'nsynth': ['crepe>=0.0.11', 'librosa', 'scikit-learn==0.20.3'],
'pet_finder': ['pandas'],
'robonet': ['h5py'], # and ffmpeg installed
'svhn': ['scipy'],
'the300w_lp': ['scipy'],
'duke_ultrasound': ['scipy'],
'wider_face': ['Pillow'],
'wikipedia': ['mwparserfromhell', 'apache_beam'],
'lsun': ['tensorflow-io'],
'wsc273': ['bs4', 'lxml'],
}
# Those datasets have dependencies which conflict with the rest of TFDS, so
# running them in an isolated environments.
# See `./oss_scripts/oss_tests.sh` for the isolated test.
ISOLATED_DATASETS = ('nsynth', 'lsun')
# Extra dataset deps are required for the tests
all_dataset_extras = list(itertools.chain.from_iterable(
deps for ds_name, deps in DATASET_EXTRAS.items()
if ds_name not in ISOLATED_DATASETS
))
EXTRAS_REQUIRE = {
'matplotlib': ['matplotlib'],
'tensorflow': ['tensorflow>=2.1'],
'tensorflow-data-validation': ['tensorflow-data-validation'],
# Tests dependencies are installed in ./oss_scripts/oss_pip_install.sh
# and run in ./oss_scripts/oss_tests.sh
'tests-all': TESTS_REQUIRE + all_dataset_extras,
'dev': TESTS_REQUIRE + DEV_REQUIRE,
}
EXTRAS_REQUIRE.update(DATASET_EXTRAS)
setup(
name=project_name,
version=__version__,
description=DOCLINES[0],
long_description='\n'.join(DOCLINES[2:]),
author='Google Inc.',
author_email='[email protected]',
url='https://github.com/tensorflow/datasets',
download_url='https://github.com/tensorflow/datasets/tags',
license='Apache 2.0',
packages=find_packages(),
package_data={
'tensorflow_datasets': DATASET_FILES + [
'scripts/documentation/templates/*',
'url_checksums/*',
'checksums.tsv',
],
},
exclude_package_data={
'tensorflow_datasets': [
'dummy_data/*',
],
},
scripts=[],
install_requires=REQUIRED_PKGS,
python_requires='>=3.6',
extras_require=EXTRAS_REQUIRE,
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: Apache Software License',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3 :: Only',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
],
keywords='tensorflow machine learning datasets',
entry_points={
'console_scripts': [
'tfds = tensorflow_datasets.scripts.cli.main:launch_cli'
],
},
)