docstr: converts text to sequence of IDs using tacatron2 text_to_sequence
  with english cleaners to transform text and standardize input
  (ex: lowercasing, expanding abbreviations and numbers, etc.)
  returns an Numpy array
docstr_tok: ["converts","text","to","sequence","of","IDs","using","tacatron2","text_to_sequence","with","english","cleaners","to","transform","text","and","standardize","input","(","ex",":","lowercasing",",","expanding","abbreviations","and","numbers",",","etc",".",")","returns","an","Numpy","array"]
code: def preprocess(self, data):
      """
      converts text to sequence of IDs using tacatron2 text_to_sequence
      with english cleaners to transform text and standardize input
      (ex: lowercasing, expanding abbreviations and numbers, etc.)
      returns an Numpy array
      """
      text = data[0].get("data")
      if text is None:
          text = data[0].get("body")
      text = text.decode("utf-8")
  
      sequence = np.array(
          self.tacotron2_model.text_to_sequence(
              text, ["english_cleaners"]
          )
      )[None, :]
      sequence = torch.from_numpy(sequence).to(
          device=self.device, dtype=torch.int64
      )
  
      return sequence
  
file_path: serve/examples/text_to_speech_synthesizer/waveglow_handler.py
imports: import logging
  import os
  import uuid
  import zipfile
  import numpy
  import torch
  from scipy.io.wavfile import write
  from waveglow_model import WaveGlow
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 5 for calling the WaveGlowSpeechSynthesizer obj's underlying member method code with example usage: obj.preprocess(data) and returns: sequence