Options to configure a Thread . Note that the options are all hints, and the underlying implementation may choose to ignore it.

TTypes< T, NDIMS >::ConstTensor tensorflow::Tensor::flat_inner_dims() const

tf.mod(x, y, name=None) Returns element-wise remainder of division. NOTE: Mod

tf.scan(fn, elems, initializer=None, parallel_iterations=10, back_prop=True, swap_memory=False, infer_shape=True, name=None) scan

tf.contrib.bayesflow.stochastic_tensor.StudentTWithAbsDfSoftplusSigmaTensor.clone(name=None, **dist_args)

tf.contrib.bayesflow.entropy.entropy_shannon(p, z=None, n=None, seed=None, form=None, name='entropy_shannon') Monte Carlo or deterministic

tf.contrib.distributions.Categorical.entropy(name='entropy') Shanon entropy in nats.

tf.contrib.learn.TensorFlowEstimator.predict(x, axis=1, batch_size=None) Predict class or regression for x.

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

tf.contrib.distributions.NormalWithSoftplusSigma.log_prob(value, name='log_prob') Log probability density/mass function (depending