virtual Status tensorflow::Session::Close(const RunOptions &run_options)

tf.contrib.bayesflow.stochastic_tensor.SampleAndReshapeValue.stop_gradient

class tf.VarLenFeature Configuration for parsing a variable-length input feature. Fields: dtype: Data type of input.

TTypes< T, NDIMS >::UnalignedConstTensor tensorflow::Tensor::unaligned_shaped(gtl::ArraySlice< int64 > new_sizes) const

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

tf.nn.rnn_cell.DropoutWrapper.__call__(inputs, state, scope=None) Run the cell with the declared dropouts.

class tf.contrib.distributions.Categorical Categorical distribution. The categorical distribution is parameterized by the log-probabilities of a set of classes.

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.entropy(name='entropy')

tf.contrib.learn.monitors.SummarySaver.every_n_step_end(step, outputs)

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