tf.self_adjoint_eig(tensor, name=None) Computes the eigen decomposition of a batch of self-adjoint matrices. Computes the eigenvalues and eigenvectors of the innermost N-by-N matrices in tensor such that tensor[...,:,:] * v[..., :,i] = e[..., i] * v[...,:,i], for i=0...N-1. Args: tensor: Tensor of shape [..., N, N]. Only the lower triangular part of each inner inner matrix is referenced. name: string, optional name of the operation. Returns: e: Eigenvalues. Shape is [..., N]. v: Eigenvec

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

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

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

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

tf.contrib.distributions.StudentT.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.distributions.MultivariateNormalDiag.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.QueueBase.queue_ref The underlying queue reference.

tf.contrib.distributions.InverseGamma.is_continuous

tf.contrib.bayesflow.stochastic_tensor.GammaWithSoftplusAlphaBetaTensor.value(name='value')