tf.contrib.distributions.Exponential.sample_n(n, seed=None, name='sample_n') Generate n samples.

tf.nn.rnn_cell.LSTMStateTuple.h Alias for field number 1

tf.contrib.bayesflow.stochastic_tensor.DirichletMultinomialTensor.mean(name='mean')

tf.QueueBase.enqueue(vals, name=None) Enqueues one element to this queue. If the queue is full

tf.contrib.distributions.Mixture.get_event_shape() Shape of a single sample from a single batch as a TensorShape

tf.contrib.graph_editor.make_list_of_op(ops, check_graph=True, allow_graph=True, ignore_ts=False) Convert ops to a list of tf

tf.contrib.learn.monitors.ExportMonitor.run_on_all_workers

tf.contrib.distributions.Dirichlet.std(name='std') Standard deviation.

tf.foldr(fn, elems, initializer=None, parallel_iterations=10, back_prop=True, swap_memory=False, name=None) foldr on the list

tf.where(input, name=None) Returns locations of true values in a boolean tensor. This operation