class_docstr: Base class for Data Processing for all data sources
  
  Data Processor is designed to be Model-independent (but Data-dependent) so that
      - Encourages experimentation with a variety of models             (BERT-style; GPT-style; T5-style),             which have different tokenization/preprocessing requirements
      - Facilitates experiments with a variety of data sources, 
         as data is processed into a common format
      
  Roles 
      1. Processes raw files into Dialogue Input Examples. 
      2. Keeps all possibly relevant information from the raw files, which 
          the Dataset class can then determine which labels to use
code: def __init__(self):
      raise NotImplementedError()
  
file_path: NeMo/nemo/collections/nlp/data/dialogue/data_processor/data_processor.py
imports: import random
  from nemo.collections.nlp.data.data_utils.data_preprocessing import DataProcessor
label_desc: Use image node_id 1 to create a new DialogueDataProcessor object from inherited base classes: DataProcessor with example: obj = DialogueDataProcessor()