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.bayesflow.stochastic_tensor.BetaWithSoftplusABTensor.value(name='value')

tf.inv(x, name=None) Computes the reciprocal of x element-wise. I.e., \(y = 1 / x\). Args: x: A Tensor. Must be one of the following types: half, float32, float64, int32, int64, complex64, complex128. name: A name for the operation (optional). Returns: A Tensor. Has the same type as x.

tf.contrib.bayesflow.stochastic_tensor.CategoricalTensor.clone(name=None, **dist_args)

tf.contrib.distributions.NormalWithSoftplusSigma.variance(name='variance') Variance.

tf.contrib.distributions.MultivariateNormalDiag.log_sigma_det(name='log_sigma_det') Log of determinant of covariance matrix.