tf.contrib.distributions.Exponential.name Name prepended to all ops created by this Distribution.

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.batch_shape(name='batch_shape') Shape of a single sample from a single

tf.contrib.distributions.MultivariateNormalFull.get_event_shape() Shape of a single sample from a single batch as a TensorShape

tf.contrib.distributions.Beta.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats

tf.contrib.distributions.ExponentialWithSoftplusLam.variance(name='variance') Variance.

tf.contrib.bayesflow.stochastic_tensor.Chi2WithAbsDfTensor.entropy(name='entropy')

tf.contrib.distributions.Chi2.log_cdf(value, name='log_cdf') Log cumulative distribution function. Given

tf.contrib.bayesflow.stochastic_tensor.QuantizedDistributionTensor.value_type

tf.contrib.distributions.ExponentialWithSoftplusLam.sample(sample_shape=(), seed=None, name='sample') Generate samples of the

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.is_reparameterized