code: def average_utterance_prosody(  # pylint: disable=no-self-use
      self, u_prosody_pred: torch.Tensor, src_mask: torch.Tensor
  ) -> torch.Tensor:
      lengths = ((~src_mask) * 1.0).sum(1)
      u_prosody_pred = u_prosody_pred.sum(
          1, keepdim=True
      ) / lengths.view(-1, 1, 1)
      return u_prosody_pred
  
imports: from typing import Callable, Dict, Tuple
  import torch
  import torch.nn.functional
  from coqpit import Coqpit
  from torch import nn
  from TTS.tts.layers.delightful_tts.conformer import Conformer
  from TTS.tts.layers.delightful_tts.encoders import PhonemeLevelProsodyEncoder, UtteranceLevelProsodyEncoder, get_mask_from_lengths
  from TTS.tts.layers.delightful_tts.energy_adaptor import EnergyAdaptor
  from TTS.tts.layers.delightful_tts.networks import EmbeddingPadded, positional_encoding
  from TTS.tts.layers.delightful_tts.phoneme_prosody_predictor import PhonemeProsodyPredictor
  from TTS.tts.layers.delightful_tts.pitch_adaptor import PitchAdaptor
  from TTS.tts.layers.delightful_tts.variance_predictor import VariancePredictor
  from TTS.tts.layers.generic.aligner import AlignmentNetwork
  from TTS.tts.utils.helpers import generate_path, maximum_path, sequence_mask
label_desc: Use image node_id 11 for calling the AcousticModel obj's underlying member method code with example usage: obj.average_utterance_prosody(u_prosody_pred, src_mask) and returns: u_prosody_pred