tf.contrib.learn.monitors.LoggingTrainable.every_n_step_begin(step)

tf.assert_proper_iterable(values) Static assert that values is a "proper" iterable. Ops

tf.contrib.distributions.Laplace.sample_n(n, seed=None, name='sample_n') Generate n samples.

tf.contrib.training.NextQueuedSequenceBatch.sequences A dict mapping keys of input_sequences to split and rebatched

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.allow_nan_stats Python boolean describing behavior when a stat

class tf.contrib.distributions.QuantizedDistribution Distribution representing the quantization Y = ceiling(X).

tf.contrib.distributions.NormalWithSoftplusSigma.is_continuous

tf.contrib.distributions.MultivariateNormalDiag.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified

tf.contrib.learn.monitors.ExportMonitor.run_on_all_workers

tf.contrib.learn.monitors.EveryN.epoch_end(epoch) End epoch. Args: