class tf.contrib.rnn.GRUBlockCell Block GRU cell implementation. The implementation is based on:

tf.contrib.learn.monitors.NanLoss.step_end(step, output) Overrides BaseMonitor.step_end. When

tf.contrib.learn.LinearRegressor.get_params(deep=True) Get parameters for this estimator. Args:

tf.contrib.learn.BaseEstimator.get_variable_names() Returns list of all variable names in this model.

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.TransformedDistribution.inverse Inverse function of transform, y => x.

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

tf.contrib.distributions.Bernoulli.get_event_shape() Shape of a single sample from a single batch as a TensorShape

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

tf.contrib.distributions.BetaWithSoftplusAB.name Name prepended to all ops created by this Distribution.