tfl.lattice_layer.RandomMonotonicInitializer

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

tfl.lattice_layer.RandomMonotonicInitializer(
    lattice_sizes, output_min, output_max, unimodalities=None
)
  • 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

@classmethod
from_config(
    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, the output of get_config().

Returns
An Initializer instance.

get_config

View source

get_config()

Standard Keras config for serialization.

__call__

View source

__call__(
    shape, dtype=None, partition_info=None
)

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.