Convert to a usable package

access.py → dnc/access.py

@@ -19,11 +19,11 @@
 from __future__ import print_function
 
 import collections
+
 import sonnet as snt
 import tensorflow as tf
 
-import addressing
-import util
+from dnc import addressing
 
 AccessState = collections.namedtuple('AccessState', (
     'memory', 'read_weights', 'write_weights', 'linkage', 'usage'))

access_test.py → dnc/access_test.py

@@ -22,8 +22,7 @@
 import tensorflow as tf
 from tensorflow.python.ops import rnn
 
-import access
-import util
+from dnc import access, util
 
 BATCH_SIZE = 2
 MEMORY_SIZE = 20

addressing.py → dnc/addressing.py

@@ -19,10 +19,11 @@
 from __future__ import print_function
 
 import collections
+
 import sonnet as snt
 import tensorflow as tf
 
-import util
+from dnc import util
 
 # Ensure values are greater than epsilon to avoid numerical instability.
 _EPSILON = 1e-6

addressing_test.py → dnc/addressing_test.py

@@ -22,8 +22,7 @@
 import sonnet as snt
 import tensorflow as tf
 
-import addressing
-import util
+from dnc import addressing, util
 
 
 class WeightedSoftmaxTest(tf.test.TestCase):

dnc.py → dnc/dnc.py

@@ -23,11 +23,12 @@
 from __future__ import print_function
 
 import collections
+
 import numpy as np
 import sonnet as snt
 import tensorflow as tf
 
-import access
+from dnc import access
 
 DNCState = collections.namedtuple('DNCState', ('access_output', 'access_state',
                                                'controller_state'))

train.py → dnc/train.py

@@ -19,10 +19,9 @@
 from __future__ import print_function
 
 import tensorflow as tf
-import sonnet as snt
 
 import dnc
-import repeat_copy
+from dnc import repeat_copy
 
 FLAGS = tf.flags.FLAGS
 

util_test.py → dnc/util_test.py

@@ -21,7 +21,7 @@
 import numpy as np
 import tensorflow as tf
 
-import util
+from dnc import util
 
 
 class BatchInvertPermutation(tf.test.TestCase):

setup.py

@@ -0,0 +1,52 @@
+from setuptools import setup
+
+setup(
+    name='sample',
+
+    # Versions should comply with PEP440.  For a discussion on single-sourcing
+    # the version across setup.py and the project code, see
+    # https://packaging.python.org/en/latest/single_source_version.html
+    version='1.0.0',
+
+    description='Differentiable Neural Computer in Tensorflow',
+    long_description='Differentiable Neural Computer in Tensorflow',
+
+    # The project's main homepage.
+    url='https://github.com/deepmind/dnc',
+
+    # Author details
+    author='Google Inc.',
+
+    # Choose your license
+    license='Apache License 2.0',
+
+    classifiers=[
+        'Development Status :: 4 - Beta',
+
+        'Intended Audience :: Developers',
+        'Intended Audience :: Education',
+        'Intended Audience :: Science/Research',
+
+        'Topic :: Scientific/Engineering :: Mathematics',
+        'Topic :: Software Development :: Libraries',
+        'Topic :: Software Development :: Libraries :: Python Modules',
+
+        'License :: OSI Approved :: Apache Software License',
+
+        'Programming Language :: Python :: 2',
+        'Programming Language :: Python :: 2.7',
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.3',
+        'Programming Language :: Python :: 3.4',
+        'Programming Language :: Python :: 3.5',
+        'Programming Language :: Python :: 3.6',
+    ],
+
+    # What does your project relate to?
+    keywords='tensorflow differentiable neural computer dnc deepmind deep mind sonnet dm-sonnet machine learning',
+
+    # You can just specify the packages manually here if your project is
+    # simple. Or you can use find_packages().
+    packages=['dnc'],
+    install_requires=['dm-sonnet'],
+)