class tf.FixedLenFeature Configuration for parsing a fixed-length input feature. To treat sparse

tf.contrib.graph_editor.get_walks_union_ops(forward_seed_ops, backward_seed_ops, forward_inclusive=True, backward_inclusive=True, within_ops=None, control_inputs=False

tf.contrib.learn.monitors.CaptureVariable.post_step(step, session)

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

tf.contrib.distributions.DirichletMultinomial.pdf(value, name='pdf') Probability density function. Args:

tf.contrib.bayesflow.stochastic_tensor.BernoulliWithSigmoidPTensor.value_type

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

class tf.contrib.rnn.GRUBlockCell Block GRU cell implementation. The implementation is based on:

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

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.survival_function(value, name='survival_function') Survival function.