tf.contrib.distributions.Dirichlet.mode(name='mode') Mode. Additional documentation from Dirichlet: Note that the mode for the Dirichlet distribution is only defined when alpha > 1. This returns the mode when alpha > 1, and NaN otherwise. If self.allow_nan_stats is False, an exception will be raised rather than returning NaN.

tf.contrib.rnn.GRUBlockCell.__call__(x, h_prev, scope=None) GRU cell.

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

tf.contrib.distributions.Poisson.sample_n(n, seed=None, name='sample_n') Generate n samples. 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.BetaWithSoftplusAB.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.contrib.framework.VariableDeviceChooser.__call__(op)

tf.nn.rnn_cell.BasicRNNCell.state_size

tf.contrib.distributions.MultivariateNormalCholesky.prob(value, name='prob') Probability density/mass function (depending on is_continuous). Additional documentation from _MultivariateNormalOperatorPD: x is a batch vector with compatible shape if x is a Tensor whose shape can be broadcast up to either: self.batch_shape + self.event_shape or [M1,...,Mm] + self.batch_shape + self.event_shape Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of sh

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

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.mean(name='mean') Mean. Additional documentation from StudentT: The mean of Student's T equals mu if df > 1, otherwise it is NaN. If self.allow_nan_stats=True, then an exception will be raised rather than returning NaN.