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.

void tensorflow::EnvWrapper::SchedClosure(std::function< void()> closure) override

tf.TensorArray.write(index, value, name=None) Write value into index index of the TensorArray. Args: index: 0-D. int32 scalar with the index to write to. value: N-D. Tensor of type dtype. The Tensor to write to this index. name: A name for the operation (optional). Returns: A new TensorArray object with flow that ensures the write occurs. Use this object all for subsequent operations. Raises: ValueError: if there are more writers than specified.

class tf.contrib.learn.monitors.BaseMonitor Base class for Monitors. Defines basic interfaces of Monitors. Monitors can either be run on all workers or, more commonly, restricted to run exclusively on the elected chief worker.

tf.contrib.learn.TensorFlowRNNClassifier.save(path) Saves checkpoints and graph to given path. Args: path: Folder to save model to.

tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.value_type

tf.contrib.bayesflow.stochastic_tensor.MultinomialTensor.name

tf.contrib.learn.monitors.LoggingTrainable.set_estimator(estimator) A setter called automatically by the target estimator. If the estimator is locked, this method does nothing. Args: estimator: the estimator that this monitor monitors. Raises: ValueError: if the estimator is None.

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.contrib.bayesflow.stochastic_tensor.LaplaceWithSoftplusScaleTensor.graph