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tf.keras.losses.LogCosh

Computes the logarithm of the hyperbolic cosine of the prediction error.

Inherits From: Loss

tf.keras.losses.LogCosh(
    reduction='sum_over_batch_size', name='log_cosh'
)

error = y_pred - y_true
logcosh = mean(log((exp(error) + exp(-error))/2), axis=-1)`

where x is the error y_pred - y_true.

Args
`reduction`	Type of reduction to apply to loss. Options are `"sum"`, `"sum_over_batch_size"` or `None`. Defaults to `"sum_over_batch_size"`.
`name`	Optional name for the 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/LogCosh