class_docstr: Counting the frequency of each action. Actions are indexed from `0` to
  `len(actions) - 1`. The input is assumed to contain action index.
class_docstr_tok: ["Counting","the","frequency","of","each","action",".","Actions","are","indexed","from","`","0","`","to","`","len","(","actions",")","-","1","`",".","The","input","is","assumed","to","contain","action","index","."]
code: def __init__(self, key: str, actions: List[str]):
      super().__init__(key)
      self.actions = actions
      self.values: Dict[str, List[int]] = {
          action: [] for action in actions
      }
  
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 ActionCountAggregator object from inherited base classes: TensorAggregator with example: obj = ActionCountAggregator(key, actions)