code: def __init__(
      self,
      key: str,
      category: str,
      title: str,
      actions: List[str],
      log_key_prefix: Optional[str] = None,
  ):
      super().__init__(key)
      self.log_key_prefix = log_key_prefix or f"{category}/{title}"
      self.actions = actions
      SummaryWriterContext.add_custom_scalars_multilinechart(
          [
              f"{self.log_key_prefix}/{action_name}/mean"
              for action_name in actions
          ],
          category=category,
          title=title,
      )
  
imports: import logging
  from collections import deque
  from typing import Any, Callable, Deque, Dict, List, Optional
  import numpy
  import torch
  from reagent.core.tensorboardX import SummaryWriterContext
  from reagent.core.tracker import Aggregator
label_desc: Use image node_id 1 to create a new TensorBoardActionHistogramAndMeanAggregator object from inherited base classes: TensorAggregator with example: obj = TensorBoardActionHistogramAndMeanAggregator(key, category, title, actions, log_key_prefix)