tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.dtype

tf.contrib.distributions.Distribution.mode(name='mode') Mode.

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.graph

tf.contrib.distributions.Normal.mode(name='mode') Mode.

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

tf.contrib.bayesflow.stochastic_tensor.BinomialTensor.value_type

tf.sparse_to_dense(sparse_indices, output_shape, sparse_values, default_value=0, validate_indices=True, name=None) Converts a

tf.contrib.distributions.Gamma.survival_function(value, name='survival_function') Survival function. Given

tf.erf(x, name=None) Computes the Gauss error function of x element-wise. Args:

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