Verifies that all given hyperparameters are consistent.
tfl.lattice_lib.verify_hyperparameters(
lattice_sizes,
units=None,
weights_shape=None,
input_shape=None,
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,
regularization_amount=None,
regularization_info='',
interpolation='hypercube'
)
This function does not inspect weights themselves. Only their shape. Use
assert_constraints()
to assert actual weights against constraints.
See tfl.layers.Lattice
class level comment for detailed description of
arguments.
Args |
lattice_sizes
|
Lattice sizes to check againts.
|
units
|
Units hyperparameter of Lattice layer.
|
weights_shape
|
Shape of tensor which represents Lattice layer weights.
|
input_shape
|
Shape of layer input. Useful only if units is set.
|
monotonicities
|
Monotonicities hyperparameter of Lattice layer.
|
unimodalities
|
Unimodalities hyperparameter of Lattice layer.
|
edgeworth_trusts
|
Edgeworth_trusts hyperparameter of Lattice layer.
|
trapezoid_trusts
|
Trapezoid_trusts hyperparameter of Lattice layer.
|
monotonic_dominances
|
Monotonic dominances hyperparameter of Lattice
layer.
|
range_dominances
|
Range dominances hyperparameter of Lattice layer.
|
joint_monotonicities
|
Joint monotonicities hyperparameter of Lattice
layer.
|
joint_unimodalities
|
Joint unimodalities hyperparameter of Lattice layer.
|
output_min
|
Minimum output of Lattice layer.
|
output_max
|
Maximum output of Lattice layer.
|
regularization_amount
|
Regularization amount for regularizers.
|
regularization_info
|
String which describes regularization_amount .
|
interpolation
|
One of 'simplex' or 'hypercube' interpolation.
|
Raises |
ValueError
|
If something is inconsistent.
|