keras/keras_core/constraints/__init__.py
2023-04-21 10:00:32 -07:00

59 lines
1.8 KiB
Python

import inspect
from keras_core.api_export import keras_core_export
from keras_core.constraints.constraints import Constraint
from keras_core.constraints.constraints import MaxNorm
from keras_core.constraints.constraints import MinMaxNorm
from keras_core.constraints.constraints import NonNeg
from keras_core.constraints.constraints import UnitNorm
from keras_core.saving import serialization_lib
from keras_core.utils.naming import to_snake_case
ALL_OBJECTS = {
Constraint,
MaxNorm,
MinMaxNorm,
NonNeg,
UnitNorm,
}
ALL_OBJECTS_DICT = {cls.__name__: cls for cls in ALL_OBJECTS}
ALL_OBJECTS_DICT.update(
{to_snake_case(cls.__name__): cls for cls in ALL_OBJECTS}
)
@keras_core_export("keras_core.constraints.serialize")
def serialize(constraint):
return serialization_lib.serialize_keras_object(constraint)
@keras_core_export("keras_core.initializers.deserialize")
def deserialize(config, custom_objects=None):
"""Return a Keras constraint object via its config."""
return serialization_lib.deserialize_keras_object(
config,
module_objects=ALL_OBJECTS_DICT,
custom_objects=custom_objects,
)
@keras_core_export("keras_core.constraints.get")
def get(identifier):
"""Retrieve a Keras constraint object via an identifier."""
if identifier is None:
return None
if isinstance(identifier, dict):
return deserialize(identifier)
elif isinstance(identifier, str):
config = {"class_name": str(identifier), "config": {}}
return deserialize(config)
elif callable(identifier):
if inspect.isclass(identifier):
identifier = identifier()
return identifier
else:
raise ValueError(
f"Could not interpret constraint object identifier: {identifier}"
)