50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
from keras_core.api_export import keras_core_export
|
|
from keras_core.losses.loss import Loss
|
|
from keras_core.losses.losses import LossFunctionWrapper
|
|
from keras_core.losses.losses import MeanSquaredError
|
|
|
|
|
|
@keras_core_export("keras_core.losses.get")
|
|
def get(identifier):
|
|
"""Retrieves a Keras loss as a `function`/`Loss` class instance.
|
|
|
|
The `identifier` may be the string name of a loss function or `Loss` class.
|
|
|
|
>>> loss = losses.get("categorical_crossentropy")
|
|
>>> type(loss)
|
|
<class 'function'>
|
|
>>> loss = losses.get("CategoricalCrossentropy")
|
|
>>> type(loss)
|
|
<class '...CategoricalCrossentropy'>
|
|
|
|
You can also specify `config` of the loss to this function by passing dict
|
|
containing `class_name` and `config` as an identifier. Also note that the
|
|
`class_name` must map to a `Loss` class
|
|
|
|
>>> identifier = {"class_name": "CategoricalCrossentropy",
|
|
... "config": {"from_logits": True}}
|
|
>>> loss = losses.get(identifier)
|
|
>>> type(loss)
|
|
<class '...CategoricalCrossentropy'>
|
|
|
|
Args:
|
|
identifier: A loss identifier. One of None or string name of a loss
|
|
function/class or loss configuration dictionary or a loss function or a
|
|
loss class instance.
|
|
|
|
Returns:
|
|
A Keras loss as a `function`/ `Loss` class instance.
|
|
"""
|
|
if identifier is None:
|
|
return None
|
|
if isinstance(identifier, str):
|
|
identifier = str(identifier)
|
|
return deserialize(identifier)
|
|
if isinstance(identifier, dict):
|
|
return deserialize(identifier)
|
|
if callable(identifier):
|
|
return identifier
|
|
raise ValueError(
|
|
f"Could not interpret loss function identifier: {identifier}"
|
|
)
|