tf.nn.rnn_cell.BasicRNNCell.state_size

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

tf.ones_like(tensor, dtype=None, name=None, optimize=True) Creates a tensor with all elements set to 1. Given

tf.contrib.learn.Estimator.__init__(model_fn=None, model_dir=None, config=None, params=None, feature_engineering_fn=None) Constructs

tf.contrib.framework.model_variable(*args, **kwargs) Gets an existing model variable with these parameters or creates a new one

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.sample(sample_shape=(), seed=None, name='sample') Generate samples

tf.contrib.losses.get_regularization_losses(scope=None) Gets the regularization losses. Args:

tf.OpError.__str__()

tf.contrib.distributions.MultivariateNormalDiag.mode(name='mode') Mode.

tf.contrib.framework.get_or_create_global_step(graph=None) Returns and create (if necessary) the global step variable.