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

tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.entropy(name='entropy')

tf.TensorArray.close(name=None) Close the current TensorArray.

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

tf.contrib.distributions.Categorical.__init__(logits, dtype=tf.int32, validate_args=False, allow_nan_stats=True, name='Categorical') Initialize Categorical distributions using class log-probabilities. Args: logits: An N-D Tensor, N >= 1, representing the log probabilities of a set of Categorical distributions. The first N - 1 dimensions index into a batch of independent distributions and the last dimension indexes into the classes. dtype: The type of the event samples (default: int32). v

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