class_docstr: Base class for all TTS models that turn text into a spectrogram 
class_docstr_tok: ["Base","class","for","all","TTS","models","that","turn","text","into","a","spectrogram"]
docstr: A helper function that accepts raw python strings and turns them into a tensor. The tensor should have 2
  dimensions. The first is the batch, which should be of size 1. The second should represent time. The tensor
  should represent either tokenized or embedded text, depending on the model.
  
  Note that some models have `normalize` parameter in this function which will apply normalizer if it is available.
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code: def parse(self, str_input: str, **kwargs) -> "torch.tensor":
      """
      A helper function that accepts raw python strings and turns them into a tensor. The tensor should have 2
      dimensions. The first is the batch, which should be of size 1. The second should represent time. The tensor
      should represent either tokenized or embedded text, depending on the model.
  
      Note that some models have `normalize` parameter in this function which will apply normalizer if it is available.
      """
  
imports: import json
  from abc import ABC, abstractmethod
  from contextlib import ExitStack, contextmanager
  from typing import List, Optional
  import torch
  from omegaconf import DictConfig
  from tqdm import tqdm
  from nemo.collections.tts.parts.utils.helpers import OperationMode
  from nemo.core.classes import ModelPT
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.neural_types.elements import AudioSignal
  from nemo.core.neural_types.neural_type import NeuralType
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 1 for calling the SpectrogramGenerator obj's underlying member method code with example usage: obj.parse(str_input) without return types