tfl.lattice_layer.RandomMonotonicInitializer

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Initializes a tfl.layers.Lattice as uniform random monotonic function.

  • The uniform random monotonic function will initilaize the lattice parameters uniformly at random and make it such that the parameters are monotonically increasing for each input.
  • The random parameters will be sampled from [output_min, output_max]

lattice_sizes Lattice sizes of tfl.layers.Lattice to initialize.
output_min Minimum layer output after initialization.
output_max Maximum layer output after initialization.
unimodalities None or unimodal dimensions after initialization. Does not need to match unimodalities of tfl.layers.Lattice.

ValueError If there are invalid hyperparameters.

Methods

from_config

Instantiates an initializer from a configuration dictionary.

Example:

initializer = RandomUniform(-1, 1)
config = initializer.get_config()
initializer = RandomUniform.from_config(config)

Args
config A Python dictionary. It will typically be the output of get_config.

Returns
An Initializer instance.

get_config

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Standard Keras config for serialization.

__call__

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Returns weights of tfl.layers.Lattice layer.

Args
shape Must be: (prod(lattice_sizes), units).
dtype Standard Keras initializer param.
partition_info Standard Keras initializer param. Not used.