tf.train.limit_epochs(tensor, num_epochs=None, name=None) Returns tensor num_epochs times and then raises an OutOfRange error. Args: tensor: Any Tensor. num_epochs: A positive integer (optional). If specified, limits the number of steps the output tensor may be evaluated. name: A name for the operations (optional). Returns: tensor or OutOfRange. Raises: ValueError: if num_epochs is invalid.

tf.TFRecordReader.num_records_produced(name=None) Returns the number of records this reader has produced. This is the same as the number of Read executions that have succeeded. Args: name: A name for the operation (optional). Returns: An int64 Tensor.

tf.train.input_producer(input_tensor, element_shape=None, num_epochs=None, shuffle=True, seed=None, capacity=32, shared_name=None, summary_name=None, name=None) Output the rows of input_tensor to a queue for an input pipeline. Args: input_tensor: A tensor with the rows to produce. Must be at least one-dimensional. Must either have a fully-defined shape, or element_shape must be defined. element_shape: (Optional.) A TensorShape representing the shape of a row of input_tensor, if it cannot be

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

tf.contrib.distributions.MultivariateNormalCholesky.log_sigma_det(name='log_sigma_det') Log of determinant of covariance matrix.

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

tf.contrib.learn.DNNRegressor.get_variable_names() Returns list of all variable names in this model. Returns: List of names.

class tf.ReaderBase Base class for different Reader types, that produce a record every step. Conceptually, Readers convert string 'work units' into records (key, value pairs). Typically the 'work units' are filenames and the records are extracted from the contents of those files. We want a single record produced per step, but a work unit can correspond to many records. Therefore we introduce some decoupling using a queue. The queue contains the work units and the Reader dequeues from the queue

void tensorflow::TensorShape::set_dim(int d, int64 size) Modifies the size of the dimension d to be size REQUIRES: 0 <= d < dims() REQUIRES: size >= 0

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)