tf.contrib.bayesflow.stochastic_tensor.StudentTWithAbsDfSoftplusSigmaTensor.clone(name=None, **dist_args)

tf.contrib.graph_editor.matcher.input_ops(*args) Add input matches.

tf.contrib.graph_editor.ControlOutputs.__init__(graph) Create a dictionary of control-output dependencies.

tf.contrib.distributions.WishartFull.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D

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

tf.contrib.bayesflow.stochastic_tensor.InverseGammaWithSoftplusAlphaBetaTensor.value(name='value')

tf.contrib.distributions.WishartCholesky.scale_operator_pd Wishart distribution scale matrix as an OperatorPD.

class tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor MultivariateNormalDiagTensor is a

tf.contrib.training.NextQueuedSequenceBatch.sequence_count An int32 vector, length batch_size: the sequence count

tf.contrib.training.SequenceQueueingStateSaver.name