tfl.categorical_calibration_layer.CategoricalCalibrationConstraints
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Monotonicity and bounds constraints for categorical calibration layer.
tfl.categorical_calibration_layer.CategoricalCalibrationConstraints(
output_min=None, output_max=None, monotonicities=None
)
Updates the weights of CategoricalCalibration layer to satify bound and
monotonicity constraints. The update is an approximate L2 projection into the
constrained parameter space.
Args |
output_min
|
Minimum possible output of categorical function.
|
output_max
|
Maximum possible output of categorical function.
|
monotonicities
|
Monotonicities of CategoricalCalibration layer.
|
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 .
|
get_config
View source
get_config()
Standard Keras config for serialization.
__call__
View source
__call__(
w
)
Applies constraints to w.
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Last updated 2024-08-02 UTC.
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