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Adding tensorflow and keras so we don't skip tests #449

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Apr 17, 2020
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2 changes: 2 additions & 0 deletions .github/workflows/release.yml
Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,8 @@ jobs:
python -m pip install --upgrade pip
pip install -r requirements.txt
pip install setuptools wheel
pip install tensorflow
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Nit: May be combine into one line? Your call.

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I think it's fine

pip install keras

- name: Run unit tests
run: pytest
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9 changes: 6 additions & 3 deletions CONTRIBUTING.md
Original file line number Diff line number Diff line change
Expand Up @@ -183,14 +183,17 @@ Then set up your Firebase/GCP project as follows:
Firebase Console. Select the "Sign-in method" tab, and enable the
"Email/Password" sign-in method, including the Email link (passwordless
sign-in) option.

3. Enable the IAM API: Go to the
3. Enable the Firebase ML API: Go to the
[Google Developers Console](
https://console.developers.google.com/apis/api/firebaseml.googleapis.com/overview)
and make sure your project is selected. If the API is not already enabled, click Enable.
4. Enable the IAM API: Go to the
[Google Cloud Platform Console](https://console.cloud.google.com) and make
sure your Firebase/GCP project is selected. Select "APIs & Services >
Dashboard" from the main menu, and click the "ENABLE APIS AND SERVICES"
button. Search for and enable the "Identity and Access Management (IAM)
API".
4. Grant your service account the 'Firebase Authentication Admin' role. This is
5. Grant your service account the 'Firebase Authentication Admin' role. This is
required to ensure that exported user records contain the password hashes of
the user accounts:
1. Go to [Google Cloud Platform Console / IAM & admin](https://console.cloud.google.com/iam-admin).
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