code: def __init__(
      self,
      task,
      sentence_avg,
      use_guided_attention_loss,
      guided_attention_loss_sigma,
      bce_pos_weight,
      ctc_weight,
  ):
      super().__init__(task)
      self.sentence_avg = sentence_avg
      self.bce_pos_weight = bce_pos_weight
  
      self.guided_attn = None
      if use_guided_attention_loss:
          self.guided_attn = GuidedAttentionLoss(
              guided_attention_loss_sigma
          )
      self.ctc_weight = ctc_weight
  
imports: import logging
  from dataclasses import dataclass, field
  from functools import lru_cache
  from typing import Any, Dict, List
  import torch
  import torch.nn.functional
  from omegaconf import II
  from fairseq import utils
  from fairseq.logging import metrics
  from fairseq.criterions import FairseqCriterion, register_criterion
  from fairseq.data.data_utils import lengths_to_mask
  from fairseq.dataclass import FairseqDataclass
label_desc: Use image node_id 1 to create a new Tacotron2Criterion object from inherited base classes: FairseqCriterion with example: obj = Tacotron2Criterion(task, sentence_avg, use_guided_attention_loss, guided_attention_loss_sigma, bce_pos_weight, ctc_weight)