code: def create_action_fingerprints(
      trackers: List["DialogueStateTracker"], domain: "Domain"
  ) -> Dict[Text, ActionFingerprint]:
      """Fingerprint each action using the events it created during train.
  
      This allows us to emit warnings when the model is used
      if an action does things it hasn't done during training,
      or if rules are incomplete.
  
      Args:
          trackers: the list of trackers
          domain: the domain
  
      Returns:
          a nested dictionary of action names and slots and active loops
              that this action sets
      """
      events_after_actions = _find_events_after_actions(trackers)
      if not events_after_actions:
          return {}
  
      # take into account only featurized slots
      featurized_slots = {
          slot.name for slot in domain.slots if slot.has_features()
      }
      action_fingerprints: Dict[Text, ActionFingerprint] = {}
      for (
          action_name,
          events_after_action,
      ) in events_after_actions.items():
          slots = list(
              set(
                  event.key
                  for event in events_after_action
                  if isinstance(event, SlotSet)
              ).intersection(featurized_slots)
          )
          active_loops = list(
              set(
                  event.name
                  for event in events_after_action
                  if isinstance(event, ActiveLoop)
              )
          )
          action_fingerprints[action_name] = ActionFingerprint(
              slots, active_loops
          )
  
      return action_fingerprints
  
file_path: rasa/rasa/core/training/training.py
imports: import dataclasses
  from typing import DefaultDict, Dict, List, Optional, Set, Text, TYPE_CHECKING
  from collections import defaultdict
  from rasa.shared.core.events import ActionExecuted, UserUttered
  from rasa.shared.core.events import SlotSet, ActiveLoop
label_desc: Use image node_id 2 for calling a global function with example usage: create_action_fingerprints(trackers, domain) and returns: action_fingerprints, dict