tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.loss(final_loss, name='Loss')

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.input_dict

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.graph

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

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.dtype

tf.contrib.bayesflow.stochastic_tensor.StudentTTensor.distribution

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

class tf.contrib.bayesflow.stochastic_tensor.StudentTTensor StudentTTensor is a StochasticTensor backed by the distribution StudentT.

tf.contrib.bayesflow.stochastic_tensor.StochasticTensor.__init__(dist_cls, name=None, dist_value_type=None, loss_fn=score_function, **dist_args) Construct a StochasticTensor. StochasticTensor will instantiate a distribution from dist_cls and dist_args and its value method will return the same value each time it is called. What value is returned is controlled by the dist_value_type (defaults to SampleAndReshapeValue). Some distributions' sample functions are not differentiable (e.g. a sample fr

tf.contrib.bayesflow.stochastic_tensor.StochasticTensor.value_type