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

tf.contrib.learn.BaseEstimator.get_variable_names() Returns list of all variable names in this model. Returns: List of names.

tf.contrib.distributions.WishartCholesky.is_continuous

class tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor MultivariateNormalDiagWithSoftplusStDevTensor is a StochasticTensor backed by the distribution MultivariateNormalDiagWithSoftplusStDev.

tf.contrib.framework.reduce_sum_n(tensors, name=None) Reduce tensors to a scalar sum. This reduces each tensor in tensors to a scalar via tf.reduce_sum, then adds them via tf.add_n. Args: tensors: List of tensors, all of the same numeric type. name: Tensor name, and scope for all other ops. Returns: Total loss tensor, or None if no losses have been configured. Raises: ValueError: if losses is missing or empty.

tf.contrib.distributions.BetaWithSoftplusAB.mode(name='mode') Mode. Additional documentation from Beta: Note that the mode for the Beta distribution is only defined when a > 1, b > 1. This returns the mode when a > 1 and b > 1, and NaN otherwise. If self.allow_nan_stats is False, an exception will be raised rather than returning NaN.

Env* tensorflow::SessionOptions::env The environment to use.

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

class tf.contrib.learn.monitors.CaptureVariable Captures a variable's values into a collection. This monitor is useful for unit testing. You should exercise caution when using this monitor in production, since it never discards values. This is an EveryN monitor and has consistent semantic for every_n and first_n.

class tf.contrib.distributions.Normal The scalar Normal distribution with mean and stddev parameters mu, sigma.