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

virtual Status tensorflow::Env::GetSymbolFromLibrary(void *handle, const char *symbol_name, void **symbol)=0

tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.value_type

tf.contrib.learn.monitors.SummarySaver.every_n_post_step(step, session) Callback after a step is finished or end() is called. Args: step: int, the current value of the global step. session: Session object.

bool tensorflow::Status::operator==(const Status &x) const

DataType tensorflow::Tensor::dtype() const Returns the data type.

tf.contrib.learn.monitors.ValidationMonitor.run_on_all_workers

tf.contrib.bayesflow.stochastic_tensor.SampleAndReshapeValue.pushed_above(unused_value_type)

tf.contrib.distributions.Mixture.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.loss(final_loss, name='Loss')