Jupyter Continuous Integration

.github/workflows/jupyter.yml

@@ -0,0 +1,50 @@
+name: jupyter
+
+on:
+  push:
+    branches: [ master, shuklak13-patch-1 ]
+  pull_request:
+    branches: [ master, shuklak13-patch-1 ]
+  schedule:
+    - cron:  '0 11 * * *'
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.7]
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v1
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install pip
+      run: |
+        python -m pip install --upgrade pip
+
+    - name: Install TensorFlow ecosystem
+      run: |
+        pip install tensorflow
+        pip install tensorflow_data_validation
+        pip install tensorflow_hub
+        pip install tensorflow-model-analysis
+
+    - name: Install test dependencies
+      run: |
+        pip install nbformat
+        pip install nbconvert
+
+    - name: Set up Jupyter
+      run: |
+        pip install jupyter
+        jupyter nbextension enable --py widgetsnbextension --sys-prefix
+        jupyter nbextension install --py --symlink tensorflow_model_analysis --sys-prefix
+        jupyter nbextension enable --py tensorflow_model_analysis --sys-prefix
+
+    - name: Test Jupyter Notebooks
+      run: python test_runner.py

README.md

@@ -1,5 +1,7 @@
 # Fairness Indicators BETA 
 
+![](https://github.com/tensorflow/fairness-indicators/workflows/jupyter/badge.svg)
+
 ![Fairness_Indicators](https://raw.githubusercontent.com/tensorflow/fairness-indicators/master/fairness_indicators/images/fairnessIndicators.png)
 
 Fairness Indicators is designed to support teams in evaluating, improving, and comparing models for fairness concerns in partnership with the broader Tensorflow toolkit.

notebook_runner.py

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+import nbformat
+import os
+
+from nbconvert.preprocessors import ExecutePreprocessor
+
+
+def run_notebook(notebook_path):
+    nb_name, _ = os.path.splitext(os.path.basename(notebook_path))
+    dirname = os.path.dirname(notebook_path)
+
+    with open(notebook_path) as f:
+        nb = nbformat.read(f, as_version=4)
+
+    proc = ExecutePreprocessor(timeout=None, kernel_name='python3')
+    proc.allow_errors = True
+
+    proc.preprocess(nb, {'metadata': {'path': '/'}})
+    output_path = os.path.join(dirname, '{}_all_output.ipynb'.format(nb_name))
+
+    with open(output_path, mode='wt') as f:
+        nbformat.write(nb, f)
+
+    errors = []
+    for cell in nb.cells:
+        if 'outputs' in cell:
+            for output in cell['outputs']:
+                if output.output_type == 'error':
+                    errors.append(output)
+
+    print('ERRORS')
+    print(type(errors))
+    print(errors)
+
+    return errors

test_runner.py

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+import unittest
+
+import notebook_runner
+
+
+class TestNotebook(unittest.TestCase):
+
+  def test_example(self):
+    errors = notebook_runner.run_notebook(
+        'fairness_indicators/examples/Fairness_Indicators_Example_Colab.ipynb')
+    self.assertEmpty(errors)
+
+  def test_facessd(self):
+    errors = notebook_runner.run_notebook(
+        'fairness_indicators/examples/Facessd_Fairness_Indicators_Example_Colab.ipynb')
+    self.assertEmpty(errors)
+
+  def test_lineage(self):
+    errors = notebook_runner.run_notebook(
+        'fairness_indicators/examples/Fairness_Indicators_Lineage_Case_Study.ipynb')
+    self.assertEmpty(errors)
+
+  def test_tb(self):
+    errors = notebook_runner.run_notebook(
+        'fairness_indicators/examples/Fairness_Indicators_TensorBoard_Plugin_Example_Colab.ipynb')
+    self.assertEmpty(errors)
+
+  def test_tfco_celeba(self):
+    errors = notebook_runner.run_notebook(
+        'fairness_indicators/examples/Fairness_Indicators_TFCO_CelebA_Case_Study.ipynb')
+    self.assertEmpty(errors)
+
+  def test_tfco_wiki(self):
+    errors = notebook_runner.run_notebook(
+        'fairness_indicators/examples/Fairness_Indicators_TFCO_Wiki_Case_Study.ipynb')
+    self.assertEmpty(errors)
+
+  def test_tfhub(self):
+    errors = notebook_runner.run_notebook(
+        'fairness_indicators/examples/Fairness_Indicators_on_TF_Hub_Text_Embeddings.ipynb')
+    self.assertEmpty(errors)
+
+
+if __name__ == '__main__':
+  unittest.main()