code: def forward(self, pitch_predicted, pitch_tgt, len):
      dur_mask = mask_from_lens(len, max_len=pitch_tgt.size(1))
      ldiff = pitch_tgt.size(1) - pitch_predicted.size(1)
      pitch_predicted = F.pad(
          pitch_predicted, (0, ldiff, 0, 0), value=0.0
      )
      pitch_loss = F.mse_loss(
          pitch_tgt, pitch_predicted, reduction="none"
      )
      pitch_loss = (pitch_loss * dur_mask).sum() / dur_mask.sum()
      pitch_loss *= self.loss_scale
  
      return pitch_loss
  
imports: import torch
  import torch.nn.functional
  from nemo.collections.tts.modules.transformer import mask_from_lens
  from nemo.core.classes import Loss, typecheck
  from nemo.core.neural_types.elements import LengthsType, LossType, MelSpectrogramType, RegressionValuesType, TokenDurationType, TokenLogDurationType
  from nemo.core.neural_types.neural_type import NeuralType
label_desc: Use image node_id 4 for calling the PitchLoss obj's underlying member method code with example usage: obj.forward(pitch_predicted, pitch_tgt, len) and returns: pitch_loss