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Hosting a Module

TensorFlow Hub supports HTTP based distribution of modules. In particular the protocol allows to use the URL identifying the module both as the documentation of the module and the endpoint to fetch the module.

Protocol

When a URL such as https://example.com/module is used to identify a module to load or instantiate, the module resolver will attempt to download a compressed tarball from the URL after appending a query parameter ?tf-hub-format=compressed.

The query param is to be interpreted as a comma separated list of the module formats that the client is interested in. For now only the "compressed" format is defined.

The compressed format indicates that the client expects a tar.gz archive with the module contents. The root of the archive is the root of the module directory and should contain a SavedModel, as in this example:

# Create a compressed module from a SavedModel directory.
$ tar -cz -f module.tar.gz --owner=0 --group=0 -C /tmp/export-module/ .

# Inspect files inside a compressed module
$ tar -tf module.tar.gz
./
./variables/
./variables/variables.data-00000-of-00001
./variables/variables.index
./assets/
./saved_model.pb

Tarballs for use with the deprecated hub.Module() API from TF1 will also contain a ./tfhub_module.pb file. The hub.load() API for TF2 SavedModels ignores such a file.