tf.contrib.graph_editor.matcher.input_ops(*args) Add input matches.

tf.contrib.distributions.MultivariateNormalCholesky.log_pdf(value, name='log_pdf') Log probability density function.

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

tf.contrib.distributions.Categorical.get_batch_shape() Shape of a single sample from a single event index as a TensorShape

tf.matrix_diag(diagonal, name=None) Returns a batched diagonal tensor with a given batched diagonal values.

tf.contrib.learn.monitors.StopAtStep.run_on_all_workers

tf.edit_distance(hypothesis, truth, normalize=True, name='edit_distance') Computes the Levenshtein distance between sequences

tf.contrib.distributions.Normal.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor

tf.cholesky_solve(chol, rhs, name=None) Solves systems of linear eqns A X = RHS, given Cholesky factorizations.

tf.contrib.learn.extract_pandas_data(data) Extract data from pandas.DataFrame for predictors. Given