class_docstr: Processor for a QA dataset, expected in SQuAD format.
  
  Args:
      data_file: data file path
      mode: TRAINING_MODE/EVALUATION_MODE/INFERENCE_MODE
          for creating training/evaluation/inference dataset
code: def __init__(self, data_file: str, mode: str):
      self.data_file = data_file
      self.mode = mode
  
      # Memoizes documents to reduce memory use (as the same document is often used for many questions)
      self.doc_id = 0
      self.context_text_to_doc_id = {}
      self.doc_id_to_context_text = {}
  
file_path: NeMo/nemo/collections/nlp/data/question_answering/data_processor/qa_processing.py
imports: import ijson
  import numpy
  from nemo.collections.nlp.data.data_utils import DataProcessor
  from nemo.collections.nlp.data.question_answering.input_example.qa_input_example import QAExample
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new QAProcessor object from inherited base classes: DataProcessor with example: obj = QAProcessor(data_file, mode)