tf.contrib.distributions.Mixture.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.loss(final_loss, name='Loss')

tf.contrib.distributions.Distribution.is_reparameterized

tf.contrib.learn.monitors.PrintTensor.set_estimator(estimator) A setter called automatically by the target estimator. If the estimator is locked, this method does nothing. Args: estimator: the estimator that this monitor monitors. Raises: ValueError: if the estimator is None.

tf.contrib.learn.TensorFlowEstimator.config

tf.contrib.distributions.Dirichlet.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.distributions.BetaWithSoftplusAB.log_prob(value, name='log_prob') Log probability density/mass function (depending on is_continuous). Args: value: float or double Tensor. name: The name to give this op. Returns: log_prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

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

tf.contrib.distributions.Bernoulli.entropy(name='entropy') Shanon entropy in nats.

tf.contrib.distributions.Normal.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.