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

tf.contrib.bayesflow.stochastic_tensor.StudentTWithAbsDfSoftplusSigmaTensor.name

tf.contrib.distributions.Normal.__init__(mu, sigma, validate_args=False, allow_nan_stats=True, name='Normal') Construct Normal

tf.contrib.distributions.BetaWithSoftplusAB.parameters Dictionary of parameters used by this Distribution.

tf.contrib.distributions.Laplace.allow_nan_stats Python boolean describing behavior when a stat is undefined.

tf.contrib.distributions.Multinomial.pmf(value, name='pmf') Probability mass function. Args:

tf.contrib.bayesflow.stochastic_tensor.InverseGammaWithSoftplusAlphaBetaTensor.distribution

class tf.contrib.learn.monitors.EveryN Base class for monitors that execute callbacks every N steps. This

tf.contrib.learn.monitors.CaptureVariable.every_n_post_step(step, session) Callback after a step is finished or end()