tf.contrib.distributions.WishartCholesky.mean_log_det(name='mean_log_det') Computes E[log(det(X))] under this Wishart distribution.

tf.contrib.distributions.WishartFull.prob(value, name='prob') Probability density/mass function (depending on is_continuous). Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.distributions.GammaWithSoftplusAlphaBeta.beta Inverse scale parameter.

tf.contrib.bayesflow.stochastic_tensor.BernoulliTensor.value_type

int64 tensorflow::Tensor::NumElements() const Convenience accessor for the tensor shape.

tf.contrib.learn.DNNRegressor.dnn_bias_ Returns bias of deep neural network part.

tf.contrib.distributions.WishartCholesky.mean(name='mean') Mean.

tf.contrib.learn.monitors.GraphDump.end(session=None) Callback at the end of training/evaluation. Args: session: A tf.Session object that can be used to run ops. Raises: ValueError: if we've not begun a run.

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

TTypes<T>::ConstVec tensorflow::Tensor::vec() const Const versions of all the methods above.