class_docstr: Generates trackers from training data.
class_docstr_tok: ["Generates","trackers","from","training","data","."]
docstr: Find start checkpoint name given end checkpoint name of a cycle.
docstr_tok: ["Find","start","checkpoint","name","given","end","checkpoint","name","of","a","cycle","."]
code: def _find_start_checkpoint_name(self, end_name: Text) -> Text:
      """Find start checkpoint name given end checkpoint name of a cycle."""
      return self.story_graph.story_end_checkpoints.get(
          end_name, end_name
      )
  
imports: from collections import defaultdict, namedtuple, deque
  import copy
  import logging
  import random
  from contextlib import contextmanager
  from tqdm import tqdm
  from typing import Optional, List, Text, Set, Dict, Tuple, Deque, DefaultDict, Any, Iterable, Generator
  from rasa.shared.constants import DOCS_URL_STORIES
  from rasa.shared.core.constants import SHOULD_NOT_BE_SET
  from rasa.shared.core.domain import Domain, State
  from rasa.shared.core.events import ActionExecuted, UserUttered, ActionReverted, UserUtteranceReverted, Restarted, Event, SlotSet, ActiveLoop
  from rasa.shared.core.trackers import DialogueStateTracker, FrozenState
  from rasa.shared.core.slots import Slot
  from rasa.shared.core.training_data.structures import StoryGraph, STORY_START, StoryStep, RuleStep, GENERATED_CHECKPOINT_PREFIX
  from rasa.shared.utils.io import is_logging_disabled
  import rasa.shared.utils.io
label_desc: Use image node_id 9 for calling the TrainingDataGenerator obj's underlying member method code with example usage: obj._find_start_checkpoint_name(end_name) and returns: self