tf.contrib.distributions.ExponentialWithSoftplusLam.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of

tf.contrib.distributions.Normal.prob(value, name='prob') Probability density/mass function (depending on is_continuous)

tf.contrib.distributions.WishartCholesky.parameters Dictionary of parameters used by this Distribution.

tf.nn.rnn_cell.InputProjectionWrapper.output_size

tf.contrib.learn.monitors.EveryN.every_n_step_end(step, outputs) Callback after every n'th step finished. This

tf.contrib.graph_editor.reroute_b2a_ts(ts0, ts1, can_modify=None, cannot_modify=None) For each tensor's pair, replace the end

tf.contrib.metrics.aggregate_metrics(*value_update_tuples) Aggregates the metric value tensors and update ops into two lists.

tf.contrib.distributions.BernoulliWithSigmoidP.is_continuous

tf.contrib.learn.TensorFlowEstimator.evaluate(x=None, y=None, input_fn=None, feed_fn=None, batch_size=None, steps=None, metrics=None, name=None)

tf.contrib.distributions.DirichletMultinomial.cdf(value, name='cdf') Cumulative distribution function. Given