Remove unneeded tensorflow-privacy dependencies.

README.md

@@ -31,14 +31,6 @@ better performance, it is also recommended to install TensorFlow with GPU
 support (detailed instructions on how to do this are available in the TensorFlow
 installation documentation).
 
-In addition to TensorFlow and its dependencies, other prerequisites are:
-
-*   `scipy` >= 0.17
-
-*   `mpmath` (for testing)
-
-*   `tensorflow_datasets` (for the RNN tutorial `lm_dpsgd_tutorial.py` only)
-
 ### Installing TensorFlow Privacy
 
 If you only want to use TensorFlow Privacy as a library, you can simply execute

requirements.txt

@@ -26,7 +26,6 @@ dm-tree==0.1.8
 dp-accounting==0.4.3
 immutabledict~=2.2
 matplotlib~=3.3
-mpmath~=1.2
 numpy~=1.21
 packaging~=22.0
 pandas~=1.4

setup.py

@@ -13,15 +13,14 @@
 # limitations under the License.
 """TensorFlow Privacy library setup file for pip."""
 
-from setuptools import find_packages
-from setuptools import setup
+import setuptools
 
 with open('tensorflow_privacy/version.py') as file:
   globals_dict = {}
   exec(file.read(), globals_dict)  # pylint: disable=exec-used
   VERSION = globals_dict['__version__']
 
-setup(
+setuptools.setup(
     name='tensorflow_privacy',
     version=VERSION,
     url='https://github.com/tensorflow/privacy',
@@ -36,15 +35,13 @@
         'numpy~=1.21',
         'packaging~=22.0',
         'pandas~=1.4',
-        'parameterized~=0.8',
         'scikit-learn>=1.0,==1.*',
         'scipy~=1.9',
         'statsmodels~=0.13',
-        'tensorflow-datasets~=4.5',
         'tensorflow-estimator~=2.4',
         'tensorflow-probability~=0.20.0',
         'tensorflow~=2.4',
         'tf-models-official~=2.13',
     ],
-    packages=find_packages(),
+    packages=setuptools.find_packages(),
 )

tools/test_pip_package.sh

@@ -28,7 +28,7 @@ main() {
   pip install --upgrade pip
   pip --version
 
-  # Publish the pip package.
+  # Test the pip package.
   package="$(ls "dist/"*".whl" | head -n1)"
   pip install --upgrade "${package}"
   pip freeze