tf.contrib.distributions.ExponentialWithSoftplusLam.is_reparameterized

tf.contrib.learn.LinearRegressor.dnn_weights_ Returns weights of deep neural network part.

tf.contrib.distributions.ExponentialWithSoftplusLam.log_prob(value, name='log_prob') Log probability density/mass function (depending

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.validate_args Python boolean indicated possibly expensive checks are enabled

tf.contrib.framework.convert_to_tensor_or_sparse_tensor(value, dtype=None, name=None, as_ref=False) Converts value to a

tf.contrib.distributions.DirichletMultinomial.variance(name='variance') Variance. Additional documentation

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

tf.contrib.learn.monitors.CaptureVariable.epoch_end(epoch) End epoch. Args:

tf.contrib.distributions.Multinomial.is_continuous

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.name