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A collection of infrastructure and tools for research in neural network interpretability.

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Lucid

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Lucid is a collection of infrastructure and tools for research in neural network interpretability.

In particular, it provides state of the art implementations of feature visualization techniques, and flexible abstractions that make it very easy to explore new research directions.

Notebooks

Tutorial Notebooks

Building Blocks

Notebooks corresponding to the Building Blocks of Interpretability article







Additional Information

License and Disclaimer

You may use this software under the Apache 2.0 License. See LICENSE.

This project is research code. It is not an official Google product.

Development

Running Tests

Use tox to run the test suite on all supported environments.

To run tests only for a specific module, pass a folder to tox: tox tests/misc/io

To run tests only in a specific environment, pass the environment's identifier via the -e flag: tox -e py27.

After adding dependencies to setup.py, run tox with the --recreate flag to update the environments' dependencies.

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A collection of infrastructure and tools for research in neural network interpretability.

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  • Jupyter Notebook 98.6%
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