tf.keras.losses.KLD

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Computes Kullback-Leibler divergence loss between y_true and y_pred.

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

loss = y_true * log(y_true / y_pred)

See: https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence

Usage:

loss = tf.keras.losses.KLD([.4, .9, .2], [.5, .8, .12])
print('Loss: ', loss.numpy())  # Loss: 0.11891246
Args
y_true Tensor of true targets.
y_pred Tensor of predicted targets.
Returns
A Tensor with loss.
Raises
TypeError If y_true cannot be cast to the y_pred.dtype.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/losses/KLD