This is the preferred API to load a Hub module in low-level TensorFlow 2.
Users of higher-level frameworks like Keras should use the framework's
corresponding wrapper, like hub.KerasLayer.
This function is roughly equivalent to the TF2 function
tf.saved_model.load() on the result of hub.resolve(handle). Calling this
function requires TF 1.14 or newer. It can be called both in eager and graph
This function can handle the deprecated TF1 Hub format to the extent
that tf.saved_model.load() in TF2 does. In particular, the returned object
.variables: a list of variables from the loaded object;
.signatures: a dict of TF2 ConcreteFunctions, keyed by signature names,
that take tensor kwargs and return a tensor dict.
However, the information imported by hub.Module into the collections of a
tf.Graph is lost (e.g., regularization losses and update ops).
(string) the Module handle to resolve; see hub.resolve().
A set of strings specifying the graph variant to use, if loading from
a v1 module.
Optional, tf.saved_model.LoadOptions object that specifies
options for loading. This argument can only be used from TensorFlow 2.3
A trackable object (see tf.saved_model.load() documentation for details).
If the code is running against incompatible (1.x)
version of TF.