W3cubDocs

tf.keras.losses.CategoricalHinge

Computes the categorical hinge loss between y_true & y_pred.

Inherits From: Loss

tf.keras.losses.CategoricalHinge(
    reduction='sum_over_batch_size',
    name='categorical_hinge'
)

loss = maximum(neg - pos + 1, 0)

where neg=maximum((1-y_true)*y_pred) and pos=sum(y_true*y_pred)

Args
`reduction`	Type of reduction to apply to the loss. In almost all cases this should be `"sum_over_batch_size"`. Supported options are `"sum"`, `"sum_over_batch_size"` or `None`.
`name`	Optional name for the loss instance.

call(
    y_true, y_pred
)

@classmethod
from_config(
    config
)

get_config()

__call__(
    y_true, y_pred, sample_weight=None
)

Call self as a function.

© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/losses/CategoricalHinge