tf.contrib.distributions.NormalWithSoftplusSigma.sample_n(n, seed=None, name='sample_n') Generate n samples.

tf.contrib.graph_editor.bypass(sgv) Bypass the given subgraph by connecting its inputs to its outputs.

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

tf.contrib.crf.CrfForwardRnnCell.output_size

tf.contrib.distributions.Laplace.scale Distribution parameter for scale.

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

class tf.contrib.learn.monitors.PrintTensor Prints given tensors every N steps. This is an EveryN

tf.contrib.distributions.MultivariateNormalDiag.mean(name='mean') Mean.

tf.contrib.distributions.MultivariateNormalDiag.prob(value, name='prob') Probability density/mass function (depending on

tf.contrib.training.NextQueuedSequenceBatch.sequence An int32 vector, length batch_size: the sequence index of each