class tf.contrib.bayesflow.stochastic_tensor.SampleAndReshapeValue Ask the StochasticTensor for n samples and reshape the result

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

tf.contrib.distributions.Exponential.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes

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

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

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.log_survival_function(value, name='log_survival_function') Log survival

tf.contrib.learn.monitors.CaptureVariable.every_n_post_step(step, session) Callback after a step is finished or end()

tf.contrib.distributions.MultivariateNormalFull.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.contrib.distributions.StudentT.pmf(value, name='pmf') Probability mass function. Args:

tf.contrib.distributions.BetaWithSoftplusAB.parameters Dictionary of parameters used by this Distribution.