tf.contrib.distributions.TransformedDistribution.is_reparameterized

tf.contrib.distributions.InverseGamma.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D Tensor. The product of the dimensions of the batch_shape is the number of independent distributions of this kind the instance represents. Args: name: name to give to the op Returns: batch_shape: Tensor.

tf.contrib.graph_editor.get_tensors(graph) get all the tensors which are input or output of an op in the graph. Args: graph: a tf.Graph. Returns: A list of tf.Tensor. Raises: TypeError: if graph is not a tf.Graph.

tf.WholeFileReader.read_up_to(queue, num_records, name=None) Returns up to num_records (key, value pairs) produced by a reader. Will dequeue a work unit from queue if necessary (e.g., when the Reader needs to start reading from a new file since it has finished with the previous file). It may return less than num_records even before the last batch. Args: queue: A Queue or a mutable string Tensor representing a handle to a Queue, with string work items. num_records: Number of records to read.

tf.contrib.distributions.ExponentialWithSoftplusLam.name Name prepended to all ops created by this Distribution.

tf.contrib.framework.has_arg_scope(func) Checks whether a func has been decorated with @add_arg_scope or not. Args: func: function to check. Returns: a boolean.

tf.contrib.learn.DNNRegressor.weights_

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.sample_n(n, seed=None, name='sample_n') Generate n samples. Additional documentation from Gamma: See the documentation for tf.random_gamma for more details. Args: n: Scalar Tensor of type int32 or int64, the number of observations to sample. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with a prepended dimension (n,). Raises: TypeError: if n is not an integer type.

tf.contrib.distributions.InverseGamma.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.

tf.contrib.distributions.WishartFull.entropy(name='entropy') Shanon entropy in nats.