tf.contrib.bayesflow.stochastic_tensor.ObservedStochasticTensor.mean(name='mean')

tf.contrib.learn.monitors.BaseMonitor.end(session=None) Callback at the end of training/evaluation. Args: session: A tf.Session object that can be used to run ops. Raises: ValueError: if we've not begun a run.

tf.contrib.bayesflow.stochastic_tensor.StudentTWithAbsDfSoftplusSigmaTensor.value_type

tf.contrib.learn.monitors.StopAtStep.end(session=None) Callback at the end of training/evaluation. Args: session: A tf.Session object that can be used to run ops. Raises: ValueError: if we've not begun a run.

tf.contrib.learn.LinearClassifier.fit(x=None, y=None, input_fn=None, steps=None, batch_size=None, monitors=None, max_steps=None) See trainable.Trainable.

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

class tf.contrib.learn.monitors.NanLoss NaN Loss monitor. Monitors loss and stops training if loss is NaN. Can either fail with exception or just stop training.

tf.contrib.distributions.NormalWithSoftplusSigma.std(name='std') Standard deviation.

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.mode(name='mode') Mode.

tf.contrib.distributions.NormalWithSoftplusSigma.mode(name='mode') Mode.