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setup.py
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from __future__ import print_function
import sys
import textwrap
from setuptools import setup, find_packages
with open('requirements.txt') as f:
INSTALL_REQUIRES = [l.strip() for l in f.readlines() if l]
TESTS_REQUIRES = ['nose>=1.1.2', 'theano']
setup(name='sklearn-sequence-classifiers',
version='0.2',
description='Sequence classifiers for scikit-learn',
long_description=textwrap.dedent("""\
Sequence classifiers for scikit-learn
=====================================
Convolutional neural network sequence classifier with a scikit-learn interface.
Usage example
-------------
Predicting IMDB review sentiments::
from keras.datasets import imdb
from keras.preprocessing import sequence
from sequence_classifiers import CNNSequenceClassifier
maxlen = 400
(x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=5000)
x_train = sequence.pad_sequences(x_train, maxlen=maxlen)
x_test = sequence.pad_sequences(x_test, maxlen=maxlen)
clf = CNNSequenceClassifier(epochs=2)
clf.fit(x_train, y_train)
print(clf.score(x_test, y_test))
"""),
author='Antti Ajanki',
packages=find_packages(),
install_requires=INSTALL_REQUIRES,
tests_require=TESTS_REQUIRES,
test_suite='nose.collector',
author_email='antti.ajanki@iki.fi',
license='BSD',
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: BSD License',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Topic :: Scientific/Engineering :: Information Analysis',
'Topic :: Software Development :: Libraries'
]
)