tf.contrib.distributions.Chi2WithAbsDf.alpha Shape parameter.

tf.contrib.distributions.Mixture.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the

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

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.distribution

tf.contrib.learn.monitors.CheckpointSaver.end(session=None)

tf.contrib.learn.monitors.GraphDump.begin(max_steps=None)

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.allow_nan_stats Python boolean describing behavior when a stat

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.sample(sample_shape=(), seed=None, name='sample') Generate samples

tf.contrib.bayesflow.stochastic_graph.surrogate_loss(sample_losses, stochastic_tensors=None, name='SurrogateLoss') Surrogate loss

tf.contrib.distributions.Gamma.log_survival_function(value, name='log_survival_function') Log survival function.