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.
[null,null,["Last updated 2024-08-02 UTC."],[],[],null,["# tfl.categorical_calibration_layer.CategoricalCalibrationConstraints\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/lattice/blob/v2.1.1/tensorflow_lattice/python/categorical_calibration_layer.py#L289-L332) |\n\nMonotonicity and bounds constraints for categorical calibration layer. \n\n tfl.categorical_calibration_layer.CategoricalCalibrationConstraints(\n output_min=None, output_max=None, monotonicities=None\n )\n\nUpdates the weights of CategoricalCalibration layer to satify bound and\nmonotonicity constraints. The update is an approximate L2 projection into the\nconstrained parameter space.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------------|--------------------------------------------------|\n| `output_min` | Minimum possible output of categorical function. |\n| `output_max` | Maximum possible output of categorical function. |\n| `monotonicities` | Monotonicities of CategoricalCalibration layer. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `from_config`\n\n @classmethod\n from_config(\n config\n )\n\nInstantiates a weight constraint from a configuration dictionary.\n\n#### Example:\n\n constraint = UnitNorm()\n config = constraint.get_config()\n constraint = UnitNorm.from_config(config)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------|--------------------------------------------------|\n| `config` | A Python dictionary, the output of `get_config`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A [`tf.keras.constraints.Constraint`](https://www.tensorflow.org/api_docs/python/tf/keras/constraints/Constraint) instance. ||\n\n\u003cbr /\u003e\n\n### `get_config`\n\n[View source](https://github.com/tensorflow/lattice/blob/v2.1.1/tensorflow_lattice/python/categorical_calibration_layer.py#L326-L332) \n\n get_config()\n\nStandard Keras config for serialization.\n\n### `__call__`\n\n[View source](https://github.com/tensorflow/lattice/blob/v2.1.1/tensorflow_lattice/python/categorical_calibration_layer.py#L318-L324) \n\n __call__(\n w\n )\n\nApplies constraints to w."]]
View source on GitHub