class tf.contrib.bayesflow.stochastic_tensor.CategoricalTensor CategoricalTensor is a StochasticTensor backed by the distribution Categorical.

tf.contrib.learn.RunConfig.is_chief

tf.contrib.framework.get_variables_to_restore(include=None, exclude=None) Gets the list of the variables to restore. Args: include: an optional list/tuple of scope strings for filtering which variables from the VARIABLES collection to include. None would include all the variables. exclude: an optional list/tuple of scope strings for filtering which variables from the VARIABLES collection to exclude. None it would not exclude any. Returns: a list of variables to restore. Raises: TypeError:

tf.contrib.distributions.WishartCholesky.log_normalizing_constant(name='log_normalizing_constant') Computes the log normalizing constant, log(Z).

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.input_dict

tf.contrib.distributions.Exponential.dtype The DType of Tensors handled by this Distribution.

class tf.contrib.training.NextQueuedSequenceBatch NextQueuedSequenceBatch stores deferred SequenceQueueingStateSaver data. This class is instantiated by SequenceQueueingStateSaver and is accessible via its next_batch property.

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

tf.contrib.learn.monitors.EveryN.epoch_end(epoch) End epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've not begun an epoch, or epoch number does not match.

bool tensorflow::TensorShape::operator==(const TensorShape &b) const