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:

Returns:

A Tensor with loss.

Raises: