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Loads a module from a handle.

Currently this method is fully supported only with Tensorflow 2.x and with modules created by calling tensorflow.saved_model.save(). The method works in both eager and graph modes.

Depending on the type of handle used, the call may involve downloading a Tensorflow Hub module to a local cache location specified by the TFHUB_CACHE_DIR environment variable. If a copy of the module is already present in the TFHUB_CACHE_DIR, the download step is skipped.

Currently, three types of module handles are supported: 1) Smart URL resolvers such as tfhub.dev, e.g.: https://tfhub.dev/google/nnlm-en-dim128/1. 2) A directory on a file system supported by Tensorflow containing module files. This may include a local directory (e.g. /usr/local/mymodule) or a Google Cloud Storage bucket (gs://mymodule). 3) A URL pointing to a TGZ archive of a module, e.g. https://example.com/mymodule.tar.gz.


  • handle: (string) the Module handle to resolve.
  • tags: A set of strings specifying the graph variant to use, if loading from a v1 module.


A trackable object (see tf.saved_model.load() documentation for details).


  • NotImplementedError: If the code is running against incompatible (1.x) version of TF.