class_docstr: Implementation. Captures batches in JSON format, returns
  also in JSON format.
docstr: Joins the instances of a batch of JSON objects
code: def _batch_from_json(self, data_rows):
      """
      Joins the instances of a batch of JSON objects
      """
      mini_batches = [
          self._from_json(data_row) for data_row in data_rows
      ]
      lengths = [len(mini_batch) for mini_batch in mini_batches]
      full_batch = list(chain.from_iterable(mini_batches))
      return lengths, full_batch
  
file_path: serve/ts/torch_handler/request_envelope/json.py
imports: import json
  from base64 import b64decode
  from itertools import chain
  from .base import BaseEnvelope
label_desc: Use image node_id 3 for calling the JSONEnvelope obj's underlying member method code with example usage: obj._batch_from_json(data_rows) and returns: lengths,  full_batch