tf.contrib.distributions.WishartFull.variance(name='variance') Variance.

tf.contrib.util.make_ndarray(tensor) Create a numpy ndarray from a tensor. Create a numpy ndarray with the same shape and data as the tensor. Args: tensor: A TensorProto. Returns: A numpy array with the tensor contents. Raises: TypeError: if tensor has unsupported type.

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

tf.contrib.bayesflow.stochastic_tensor.GammaTensor.clone(name=None, **dist_args)

bool tensorflow::PartialTensorShape::IsValid(const TensorShapeProto &proto) Returns true iff proto is a valid partial tensor shape.

tf.nn.rnn_cell.OutputProjectionWrapper.state_size

tf.contrib.distributions.MultivariateNormalCholesky.is_continuous

tf.contrib.bayesflow.stochastic_tensor.Chi2WithAbsDfTensor.graph

tf.contrib.distributions.Exponential.lam

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.graph