tf.contrib.bayesflow.stochastic_tensor.BaseStochasticTensor.loss()

tf.contrib.bayesflow.stochastic_tensor.BaseStochasticTensor.loss(sample_loss)

Returns the term to add to the surrogate loss.

This method is called by surrogate_loss. The input sample_loss should have already had stop_gradient applied to it. This is because the surrogate_loss usually provides a Monte Carlo sample term of the form differentiable_surrogate * sample_loss where sample_loss is considered constant with respect to the input for purposes of the gradient.

Args:

• sample_loss: Tensor, sample loss downstream of this StochasticTensor.

Returns:

Either None or a Tensor.