docstr: Formats training prompt based on self.input_field_type
  
  Training example: 
      e.g. response: <response> # input_label_type = response
      e.g. utterance: <utterance> # input_label_type = utterance
      e.g. passage: <passage> utterance: <utterance> # input_label_type = passage+utterance
docstr_tok: ["Formats","training","prompt","based","on","self.input_field_type","Training","example",":","e.g",".","response",":","<","response",">","#","input_label_type","=","response","e.g",".","utterance",":","<","utterance",">","#","input_label_type","=","utterance","e.g",".","passage",":","<","passage",">","utterance",":","<","utterance",">","#","input_label_type","=","passage+utterance"]
code: def format_prompt(self, ex):
      """
      Formats training prompt based on self.input_field_type
  
      Training example:
          e.g. response: <response> # input_label_type = response
          e.g. utterance: <utterance> # input_label_type = utterance
          e.g. passage: <passage> utterance: <utterance> # input_label_type = passage+utterance
      """
      parts = self.input_label_type.split("+")
      input_sentence = " ".join(
          [part + ": " + ex["labels"][part] for part in parts]
      )
      return input_sentence
  
file_path: NeMo/nemo/collections/nlp/data/dialogue/dataset/dialogue_s2s_generation_dataset.py
imports: import torch
  from nemo.collections.nlp.data.dialogue.dataset.dialogue_dataset import DialogueDataset
label_desc: Use image node_id 7 for calling the DialogueS2SGenerationDataset obj's underlying member method code with example usage: obj.format_prompt(ex) and returns: input_sentence