tf.contrib.distributions.BernoulliWithSigmoidP.__init__(p=None, dtype=tf.int32, validate_args=False, allow_nan_stats=True, name='BernoulliWithSigmoidP')

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

tf.contrib.framework.create_global_step(graph=None) Create global step tensor in graph. Args:

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.mean(name='mean') Mean. Additional documentation

tf.contrib.learn.LinearRegressor.dnn_weights_ Returns weights of deep neural network part.

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.is_continuous

tf.contrib.learn.monitors.CheckpointSaver.post_step(step, session)

tf.contrib.learn.monitors.SummarySaver.run_on_all_workers

tf.contrib.distributions.Exponential.__init__(lam, validate_args=False, allow_nan_stats=True, name='Exponential') Construct Exponential

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