class_docstr: Action distribution P(a1, a2) = P(a1) * P(a2 | a1)
code: def deterministic_sample(self):
      # First, sample a1.
      a1_dist = self._a1_distribution()
      a1 = a1_dist.deterministic_sample()
  
      # Sample a2 conditioned on a1.
      a2_dist = self._a2_distribution(a1)
      a2 = a2_dist.deterministic_sample()
      self._action_logp = a1_dist.logp(a1) + a2_dist.logp(a2)
  
      # Return the action tuple.
      return (a1, a2)
  
imports: from ray.rllib.models.tf.tf_action_dist import Categorical, ActionDistribution
  from ray.rllib.models.torch.torch_action_dist import TorchCategorical, TorchDistributionWrapper
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
label_desc: Use image node_id 1 for calling the BinaryAutoregressiveDistribution obj's underlying member method code with example usage: obj.deterministic_sample() and returns: a1,  a2