tf.distributions.kl_divergence

Aliases:

• tf.contrib.distributions.kl_divergence
• tf.distributions.kl_divergence

tf.distributions.kl_divergence(
    distribution_a,
    distribution_b,
    allow_nan_stats=True,
    name=None
)

Defined in tensorflow/python/ops/distributions/kullback_leibler.py.

See the guide: Statistical Distributions (contrib) > Kullback-Leibler Divergence

Get the KL-divergence KL(distribution_a || distribution_b).

If there is no KL method registered specifically for type(distribution_a) and type(distribution_b), then the class hierarchies of these types are searched.

If one KL method is registered between any pairs of classes in these two parent hierarchies, it is used.

If more than one such registered method exists, the method whose registered classes have the shortest sum MRO paths to the input types is used.

If more than one such shortest path exists, the first method identified in the search is used (favoring a shorter MRO distance to type(distribution_a)).

Args:

• distribution_a: The first distribution.
• distribution_b: The second distribution.
• allow_nan_stats: Python bool, default True. When True, statistics (e.g., mean, mode, variance) use the value "NaN" to indicate the result is undefined. When False, an exception is raised if one or more of the statistic's batch members are undefined.
• name: Python str name prefixed to Ops created by this class.

Returns:

A Tensor with the batchwise KL-divergence between distribution_a and distribution_b.

Raises:

• NotImplementedError: If no KL method is defined for distribution types of distribution_a and distribution_b.