tf.contrib.learn.monitors.EveryN.epoch_end()

tf.contrib.learn.monitors.EveryN.epoch_end(epoch) End epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've not begun an epoch, or epoch number does not match.

tensorflow::TensorShape::operator==()

bool tensorflow::TensorShape::operator==(const TensorShape &b) const

tf.contrib.distributions.Dirichlet.variance()

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

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalFullTensor.input_dict

tf.contrib.distributions.DirichletMultinomial.is_reparameterized

tf.contrib.graph_editor.SubGraphView.__str__()

tf.contrib.bayesflow.stochastic_tensor.BetaWithSoftplusABTensor.dtype

tf.contrib.distributions.TransformedDistribution.variance()

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

tf.contrib.bayesflow.stochastic_tensor.GammaWithSoftplusAlphaBetaTensor.input_dict

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.loss()

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.loss(final_loss, name='Loss')