tf.contrib.distributions.MultivariateNormalDiag.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats return +/- infinity when it makes sense. E.g., the variance of a Cauchy distribution is infinity. However, sometimes the statistic is undefined, e.g., if a distribution's pdf does not achieve a maximum within the support of the distribution, the mode is undefined. If the mean is undefined, then by definition the variance is undefined. E.g. the mean for Student's T

tf.contrib.distributions.Laplace.mean(name='mean') Mean.

tf.contrib.graph_editor.detach_inputs(sgv, control_inputs=False) Detach the inputs of a subgraph view. Args: sgv: the subgraph view to be detached. This argument is converted to a subgraph using the same rules as the function subgraph.make_view. Note that sgv is modified in place. control_inputs: if True control_inputs are also detached. Returns: A tuple (sgv, input_placeholders) where sgv is a new subgraph view of the detached subgraph; input_placeholders is a list of the created input pl

tf.contrib.graph_editor.detach(sgv, control_inputs=False, control_outputs=None, control_ios=None) Detach both the inputs and the outputs of a subgraph view. Args: sgv: the subgraph view to be detached. This argument is converted to a subgraph using the same rules as the function subgraph.make_view. Note that sgv is modified in place. control_inputs: A boolean indicating whether control inputs are enabled. control_outputs: An instance of util.ControlOutputs or None. If not None, control outp

bool tensorflow::Tensor::IsSameSize(const Tensor &b) const

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalFullTensor.distribution

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.value_type

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.value_type

tf.contrib.distributions.Beta.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

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