ModuleNotFoundError: No module named 'tensorflow_privacy.privacy.membership_inference_attack'

Following the README on the membership inference page yields an error.

I am running TensorFlow Privacy in a Google Colab notebook.

After adding the module with pip through !pip install tensorflow-privacy, I try running the lines specified in the README:

from tensorflow_privacy.privacy.membership_inference_attack import membership_inference_attack as mia

This yields the following error message:

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ModuleNotFoundError                       Traceback (most recent call last)

<ipython-input-10-43809957f96c> in <module>()
      1 # tensorflow privacy mia imports
----> 2 from tensorflow_privacy.privacy.membership_inference_attack import membership_inference_attack as mia
      3 from tensorflow_privacy.privacy.membership_inference_attack.data_structures import AttackInputData
      4 from tensorflow_privacy.privacy.membership_inference_attack.data_structures import SlicingSpec
      5 from tensorflow_privacy.privacy.membership_inference_attack.data_structures import AttackType

ModuleNotFoundError: No module named 'tensorflow_privacy.privacy.membership_inference_attack'


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NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.

To view examples of installing some common dependencies, click the
"Open Examples" button below.
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TensorFlow Privacy seems to be successfully installed before:

Requirement already satisfied: tensorflow-privacy in /usr/local/lib/python3.6/dist-packages (0.2.2)

I would be happy to know how I can keep on using the module. Thank you in advance.

Start with the membership inference README linked in the issue and reproduce the import in a Google Colab environment after installing tensorflow-privacy 0.2.2. Inspect the installed package to compare its contents with the documented module path. Done means the documented example works with the stated installation, or the README clearly identifies the required package version or setup.