tf.contrib.bayesflow.stochastic_tensor.InverseGammaWithSoftplusAlphaBetaTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.GammaWithSoftplusAlphaBetaTensor.distribution

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

bool tensorflow::TensorShape::operator==(const TensorShape &b) const

tf.is_non_decreasing(x, name=None) Returns True if x is non-decreasing. Elements

tf.contrib.framework.get_graph_from_inputs(op_input_list, graph=None) Returns the appropriate graph to use for the given inputs

tf.contrib.distributions.Mixture.get_batch_shape() Shape of a single sample from a single event index as a TensorShape

tf.contrib.framework.model_variable(*args, **kwargs) Gets an existing model variable with these parameters or creates a new one

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

tf.contrib.distributions.Dirichlet.entropy(name='entropy') Shanon entropy in nats.