class_docstr: Action distribution P(a1, a2) = P(a1) * P(a2 | a1)
code: def logp(self, actions):
      a1, a2 = actions[:, 0], actions[:, 1]
      a1_vec = tf.expand_dims(tf.cast(a1, tf.float32), 1)
      a1_logits, a2_logits = self.model.action_model(
          [self.inputs, a1_vec]
      )
      return Categorical(a1_logits).logp(a1) + Categorical(
          a2_logits
      ).logp(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 3 for calling the BinaryAutoregressiveDistribution obj's underlying member method code with example usage: obj.logp(actions) and returns: unknown