tf.keras.metrics.LogCoshError

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

Inherits From: Mean, Metric, Layer, Module

logcosh = log((exp(x) + exp(-x))/2), where x is the error (y_pred - y_true)

name (Optional) string name of the metric instance.
dtype (Optional) data type of the metric result.

Standalone usage:

m = tf.keras.metrics.LogCoshError()
m.update_state([[0, 1], [0, 0]], [[1, 1], [0, 0]])
m.result().numpy()
0.10844523
m.reset_state()
m.update_state([[0, 1], [0, 0]], [[1, 1], [0, 0]],
               sample_weight=[1, 0])
m.result().numpy()
0.21689045

Usage with compile() API:

model.compile(optimizer='sgd',
              loss='mse',
              metrics=[tf.keras.metrics.LogCoshError()])

Methods

reset_state

View source

Resets all of the metric state variables.

This function is called between epochs/steps, when a metric is evaluated during training.

result