tf.keras.losses.LogCosh | TensorFlow v2.16.1 (original) (raw)
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'
)
Formula:
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. |
Methods
call
call(
y_true, y_pred
)
from_config
@classmethod
from_config( config )
get_config
get_config()
__call__
__call__(
y_true, y_pred, sample_weight=None
)
Call self as a function.
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Last updated 2024-06-07 UTC.