Watch talks from the 2019 TensorFlow Dev Summit Watch now

hub.load

hub.load(handle)

Loads a module from a handle.

Currently this method only works with Tensorflow 2.x and can only load 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.

Args:

  • handle: (string) the Module handle to resolve.

Returns:

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

Raises:

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