View source on GitHub |
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.
Raises | |
---|---|
ValueError
|
If weights to project don't correspond to lattice_sizes .
|
Methods
from_config
@classmethod
from_config( config )
Instantiates a weight constraint from a configuration dictionary.
Example:
constraint = UnitNorm()
config = constraint.get_config()
constraint = UnitNorm.from_config(config)
Args | |
---|---|
config
|
A Python dictionary, the output of get_config .
|
Returns | |
---|---|
A tf.keras.constraints.Constraint instance.
|
get_config
get_config()
Standard Keras config for serialization.
__call__
__call__(
w
)
Applies constraints to w
.