code: def from_logits(
      behaviour_policy_logits,
      target_policy_logits,
      actions,
      discounts,
      rewards,
      values,
      bootstrap_value,
      dist_class=Categorical,
      model=None,
      clip_rho_threshold=1.0,
      clip_pg_rho_threshold=1.0,
      name="vtrace_from_logits",
  ):
      """multi_from_logits wrapper used only for tests"""
  
      res = multi_from_logits(
          [behaviour_policy_logits],
          [target_policy_logits],
          [actions],
          discounts,
          rewards,
          values,
          bootstrap_value,
          dist_class,
          model,
          clip_rho_threshold=clip_rho_threshold,
          clip_pg_rho_threshold=clip_pg_rho_threshold,
          name=name,
      )
  
      return VTraceFromLogitsReturns(
          vs=res.vs,
          pg_advantages=res.pg_advantages,
          log_rhos=res.log_rhos,
          behaviour_action_log_probs=tf.squeeze(
              res.behaviour_action_log_probs, axis=0
          ),
          target_action_log_probs=tf.squeeze(
              res.target_action_log_probs, axis=0
          ),
      )
  
file_path: ray/rllib/algorithms/impala/vtrace_tf.py
imports: import collections
  from ray.rllib.models.tf.tf_action_dist import Categorical
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 3 for calling a global function with example usage: from_logits(behaviour_policy_logits, target_policy_logits, actions, discounts, rewards, values, bootstrap_value, dist_class, model, clip_rho_threshold, clip_pg_rho_threshold, name) and returns: VTraceFromLogitsReturns