keras/keras_core/metrics/__init__.py
2023-04-18 14:49:38 -07:00

50 lines
1.8 KiB
Python

from keras_core.api_export import keras_core_export
from keras_core.metrics.metric import Metric
from keras_core.metrics.reduction_metrics import Mean
from keras_core.metrics.reduction_metrics import MeanMetricWrapper
from keras_core.metrics.reduction_metrics import Sum
from keras_core.metrics.regression_metrics import MeanSquaredError
@keras_core_export("keras_core.metrics.get")
def get(identifier):
"""Retrieves a Keras metric as a `function`/`Metric` class instance.
The `identifier` may be the string name of a metric function or class.
>>> metric = metrics.get("categorical_crossentropy")
>>> type(metric)
<class 'function'>
>>> metric = metrics.get("CategoricalCrossentropy")
>>> type(metric)
<class '...metrics.CategoricalCrossentropy'>
You can also specify `config` of the metric to this function by passing dict
containing `class_name` and `config` as an identifier. Also note that the
`class_name` must map to a `Metric` class
>>> identifier = {"class_name": "CategoricalCrossentropy",
... "config": {"from_logits": True}}
>>> metric = metrics.get(identifier)
>>> type(metric)
<class '...metrics.CategoricalCrossentropy'>
Args:
identifier: A metric identifier. One of None or string name of a metric
function/class or metric configuration dictionary or a metric function
or a metric class instance
Returns:
A Keras metric as a `function`/ `Metric` class instance.
"""
if isinstance(identifier, dict):
return deserialize(identifier)
elif isinstance(identifier, str):
# TODO
# return deserialize(str(identifier))
return globals()[identifier]
elif callable(identifier):
return identifier
else:
raise ValueError(f"Could not interpret metric identifier: {identifier}")