class tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor MultivariateNormalDiagPlusVDVTTensor

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.graph

tf.contrib.distributions.DirichletMultinomial.log_prob(value, name='log_prob') Log probability density/mass function (depending

tf.unique(x, out_idx=None, name=None) Finds unique elements in a 1-D tensor. This operation returns

class tf.contrib.learn.monitors.NanLoss NaN Loss monitor. Monitors loss and stops training if

tf.contrib.distributions.BetaWithSoftplusAB.dtype The DType of Tensors handled by this Distribution

tf.contrib.learn.monitors.ValidationMonitor.epoch_end(epoch) End epoch. Args:

tf.contrib.graph_editor.copy_with_input_replacements(sgv, replacement_ts, dst_graph=None, dst_scope='', src_scope='', reuse_dst_scope=False)

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.pmf(value, name='pmf') Probability mass function.

tf.contrib.distributions.LaplaceWithSoftplusScale.event_shape(name='event_shape') Shape of a single sample from a single batch