Classes and helper functions for creating Stochastic Tensors.
StochasticTensor objects wrap
Distribution objects. Their values may be samples from the underlying distribution, or the distribution mean (as governed by
value_type). These objects provide a
loss method for use when sampling from a non-reparameterized distribution. The
lossmethod is used in conjunction with
stochastic_graph.surrogate_loss to produce a single differentiable loss in stochastic graphs having both continuous and discrete stochastic nodes.
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