tfl.lattice_layer.LatticeConstraints

Constraints for tfl.layers.Lattice layer.

tfl.lattice_layer.LatticeConstraints(
    lattice_sizes, monotonicities=None, unimodalities=None, edgeworth_trusts=None,
    trapezoid_trusts=None, monotonic_dominances=None, range_dominances=None,
    joint_monotonicities=None, joint_unimodalities=None, output_min=None,
    output_max=None, num_projection_iterations=1, enforce_strict_monotonicity=True
)

Applies all constraints to the lattice weights. See tfl.layers.Lattice for more details.

Args
lattice_sizes	Lattice sizes of Lattice layer to constraint.
monotonicities	Same meaning as corresponding parameter of Lattice.
unimodalities	Same meaning as corresponding parameter of Lattice.
edgeworth_trusts	Same meaning as corresponding parameter of Lattice.
trapezoid_trusts	Same meaning as corresponding parameter of Lattice.
monotonic_dominances	Same meaning as corresponding parameter of Lattice.
range_dominances	Same meaning as corresponding parameter of Lattice.
joint_monotonicities	Same meaning as corresponding parameter of Lattice.
joint_unimodalities	Same meaning as corresponding parameter of Lattice.
output_min	Minimum possible output.
output_max	Maximum possible output.
num_projection_iterations	Same meaning as corresponding parameter of Lattice.
enforce_strict_monotonicity	Whether to use approximate projection to ensure that constratins are strictly satisfied.

Raises
ValueError	If weights to project don't correspond to lattice_sizes.

Methods

get_config

View source

get_config()

Standard Keras config for serialization.

__call__

View source

__call__(
    w
)

Applies constraints to w.