class_docstr: Dataset for training a Nearest Neighbour model for zero shot intent recognition.
docstr: Args:
      dataset_split: dataset split
      dialogues_processor: Data generator for dialogues
      tokenizer: tokenizer to split text into sub-word tokens
code: def __init__(
      self,
      dataset_split: str,
      dialogues_processor: object,
      tokenizer,
      cfg,
  ):
      """
      Args:
          dataset_split: dataset split
          dialogues_processor: Data generator for dialogues
          tokenizer: tokenizer to split text into sub-word tokens
      """
      self.cfg = cfg
      self.tokenizer = tokenizer
      self.raw_features = dialogues_processor.get_dialog_examples(
          dataset_split
      )
      self.max_n = self.find_max_n_candidates()
      self.examples = self._create_examples(self.raw_features)
  
file_path: NeMo/nemo/collections/nlp/data/dialogue/dataset/dialogue_nearest_neighbour_dataset.py
imports: import torch
  from nemo.collections.nlp.data.dialogue.dataset.dialogue_dataset import DialogueDataset
label_desc: Use image node_id 1 to create a new DialogueNearestNeighbourDataset object from inherited base classes: DialogueDataset with example: obj = DialogueNearestNeighbourDataset(dataset_split, dialogues_processor, tokenizer, cfg)