tf.contrib.graph_editor.ph(dtype, shape=None, scope=None) Create a tf.placeholder for the Graph Editor. Note

tf.contrib.distributions.Categorical.get_batch_shape() Shape of a single sample from a single event index as a TensorShape

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.distributions.TransformedDistribution.dtype The DType of Tensors handled by this Distribution

tf.contrib.distributions.ExponentialWithSoftplusLam.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape)

tf.betainc(a, b, x, name=None) Compute the regularized incomplete beta integral \(I_x(a, b)\). The

tf.contrib.bayesflow.stochastic_tensor.Chi2Tensor.dtype

tf.contrib.distributions.Distribution.std(name='std') Standard deviation.

tf.contrib.distributions.Categorical.log_cdf(value, name='log_cdf') Log cumulative distribution function. Given

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.dtype