tf.keras.losses.logcosh

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Logarithm of the hyperbolic cosine of the prediction error.

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Main aliases

tf.losses.logcosh

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.losses.logcosh, tf.compat.v2.keras.losses.logcosh, tf.compat.v2.losses.logcosh

tf.keras.losses.logcosh(
    y_true, y_pred
)

log(cosh(x)) is approximately equal to (x ** 2) / 2 for small x and to abs(x) - log(2) for large x. This means that 'logcosh' works mostly like the mean squared error, but will not be so strongly affected by the occasional wildly incorrect prediction.

Arguments:

y_true: tensor of true targets.
y_pred: tensor of predicted targets.

Returns:

Tensor with one scalar loss entry per sample.