class_docstr: Convert the raw data to the standard format supported by
  IntentSlotDataDesc.
  
  By default, the None label for slots is 'O'.
  
  IntentSlotDataDesc requires two files:
  
      input_file: file to sequence + label.
          the first line is header (sentence [tab] label)
          each line should be [sentence][tab][label]
  
      slot_file: file to slot labels, each line corresponding to
          slot labels for a sentence in input_file. No header.
  
  To keep the mapping from label index to label consistent during
  training and inferencing we require the following files:
      dicts.intents.csv: each line is an intent. The first line
          corresponding to the 0 intent label, the second line
          corresponding to the 1 intent label, and so on.
  
      dicts.slots.csv: each line is a slot. The first line
          corresponding to the 0 slot label, the second line
          corresponding to the 1 slot label, and so on.
  
  Args:
      data_dir: the directory of the dataset
      modes: ['train', 'test', 'dev'],
      none_slot_label: the label for slots that aren't identified defaulted to 'O'
      pad_label: the int used for padding. If set to -1, it'll be set to the whatever the None label is.
docstr: Return Intent and slot dictionaries
docstr_tok: ["Return","Intent","and","slot","dictionaries"]
code: def intent_slot_dicts(data_dir):
      """
      Return Intent and slot dictionaries
      """
      intent_dict_file = data_dir + "/dict.intents.csv"
      slot_dict_file = data_dir + "/dict.slots.csv"
  
      intents_labels = open(intent_dict_file, "r").readlines()
      intents_labels = [
          line.strip() for line in intents_labels if line.strip()
      ]
  
      slots_labels = open(slot_dict_file, "r").readlines()
      slots_labels = [
          line.strip() for line in slots_labels if line.strip()
      ]
  
      return intents_labels, slots_labels
  
imports: import itertools
  from typing import List
  from nemo.collections.nlp.data.data_utils.data_preprocessing import fill_class_weights, get_freq_weights, get_label_stats, if_exist
  from nemo.utils import logging
label_desc: Use image node_id 3 for calling the IntentSlotDataDesc obj's underlying member method code with example usage: obj.intent_slot_dicts(data_dir) and returns: intents_labels,  slots_labels