class tf.contrib.distributions.Beta Beta distribution. This distribution is parameterized by a and b which are shape parameters.

tf.contrib.graph_editor.SubGraphView.inputs The input tensors of this subgraph view.

class tf.contrib.distributions.MultivariateNormalDiagPlusVDVT The multivariate normal distribution on R^k. Every batch member of this distribution is defined by a mean and a lightweight covariance matrix C.

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

tf.contrib.distributions.WishartCholesky.log_cdf(value, name='log_cdf') Log cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: log_cdf(x) := Log[ P[X <= x] ] Often, a numerical approximation can be used for log_cdf(x) that yields a more accurate answer than simply taking the logarithm of the cdf when x << -1. Args: value: float or double Tensor. name: The name to give this op. Returns: logcdf: a Tensor of shape sample_shape(x)

tf.contrib.distributions.Gamma.pdf(value, name='pdf') Probability density function. Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if not is_continuous.

tf.contrib.distributions.MultivariateNormalCholesky.name Name prepended to all ops created by this Distribution.

tf.contrib.distributions.Binomial.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.

tf.contrib.graph_editor.select_ops(*args, **kwargs) Helper to select operations. Args: *args: list of 1) regular expressions (compiled or not) or 2) (array of) tf.Operation. tf.Tensor instances are silently ignored. **kwargs: 'graph': tf.Graph in which to perform the regex query.This is required when using regex. 'positive_filter': an elem if selected only if positive_filter(elem) is True. This is optional. 'restrict_ops_regex': a regular expression is ignored if it doesn't start with the su

tf.contrib.graph_editor.get_ops_ios(ops, control_inputs=False, control_outputs=None, control_ios=None) Return all the tf.Operation which are connected to an op in ops. Args: ops: an object convertible to a list of tf.Operation. control_inputs: A boolean indicating whether control inputs are enabled. control_outputs: An instance of util.ControlOutputs or None. If not None, control outputs are enabled. control_ios: An instance of util.ControlOutputs or None. If not None, both control inputs