register_all: Register all
In tfaddons: Interface to 'TensorFlow SIG Addons'

Description Usage Arguments Details Value

1	register_all(keras_objects = TRUE, custom_kernels = TRUE)

`keras_objects`	boolean, 'TRUE' by default. If 'TRUE', register all Keras objects with 'tf$keras$utils$register_keras_serializable(package="Addons")' If set to FALSE, doesn't register any Keras objects of Addons in TensorFlow.
`custom_kernels`	boolean, 'TRUE' by default. If 'TRUE', loads all custom kernels of TensorFlow Addons with 'tf.load_op_library("path/to/so/file.so")'. Loading the SO files register them automatically. If ‘FALSE' doesn’t load and register the shared objects files. Not that it might be useful to turn it off if your installation of Addons doesn't work well with custom ops.

When loading a Keras model that has a TF Addons' function, it is needed for this function to be known by the Keras deserialization process. There are two ways to do this, either do “' tf$keras$models$load_model( "my_model.tf", custom_objects=list("LAMB": tfaddons::optimizer_lamb) ) “' or you can do: “'python register_all() tf$keras$models$load_model("my_model.tf") “' If the model contains custom ops (compiled ops) of TensorFlow Addons, and the graph is loaded with 'tf$saved_model$load', then custom ops need to be registered before to avoid an error of the type: “' tensorflow.python.framework.errors_impl.NotFoundError: Op type not registered '...' in binary running on ... Make sure the Op and Kernel are registered in the binary running in this process. “' In this case, the only way to make sure that the ops are registered is to call this function: “' register_all() tf$saved_model$load("my_model.tf") “' Note that you can call this function multiple times in the same process, it only has an effect the first time. Afterward, it's just a no-op.

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tfaddons documentation built on July 2, 2020, 2:12 a.m.