class_docstr: Reader object that loads experiences from JSON file chunks.
  
  The input files will be read from in random order.
class_docstr_tok: ["Reader","object","that","loads","experiences","from","JSON","file","chunks",".","The","input","files","will","be","read","from","in","random","order","."]
code: def _from_json(self, data: str) -> SampleBatchType:
      if isinstance(data, bytes):  # smart_open S3 doesn't respect "r"
          data = data.decode("utf-8")
      json_data = json.loads(data)
      return from_json_data(json_data, self.ioctx.worker)
  
imports: import glob
  import json
  import logging
  import math
  import numpy
  import os
  from pathlib import Path
  import random
  import re
  import tree
  from typing import List, Optional, TYPE_CHECKING, Union
  from urllib.parse import urlparse
  import zipfile
  from ray.rllib.offline.input_reader import InputReader
  from ray.rllib.offline.io_context import IOContext
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID, MultiAgentBatch, SampleBatch, concat_samples, convert_ma_batch_to_sample_batch
  from ray.rllib.utils.annotations import override, PublicAPI, DeveloperAPI
  from ray.rllib.utils.compression import unpack_if_needed
  from ray.rllib.utils.spaces.space_utils import clip_action, normalize_action
  from ray.rllib.utils.typing import Any, FileType, SampleBatchType
label_desc: Use image node_id 9 for calling the JsonReader obj's underlying member method code with example usage: obj._from_json(data) and returns: from_json_data