tf.contrib.distributions.NormalWithSoftplusSigma.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D Tensor. The product of the dimensions of the batch_shape is the number of independent distributions of this kind the instance represents. Args: name: name to give to the op Returns: batch_shape: Tensor.

tf.Session.graph The graph that was launched in this session.

tf.contrib.distributions.Poisson.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the desired shape of a call to sample(). Subclasses should override static method _param_shapes. Args: sample_shape: Tensor or python list/tuple. Desired shape of a call to sample(). name: name to prepend ops with. Returns: dict of parameter name to Tensor shapes.

tf.errors.DeadlineExceededError.__init__(node_def, op, message) Creates a DeadlineExceededError.

tf.contrib.distributions.NormalWithSoftplusSigma.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.

tf.contrib.bayesflow.stochastic_tensor.StudentTWithAbsDfSoftplusSigmaTensor.graph

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

tf.contrib.distributions.Chi2.df

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

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