class_docstr: Loss to keep SpectrogramEnhancer from generating extra sounds.
  L1 distance on x0.25 Mel scale (20 bins for typical 80-bin scale)
class_docstr_tok: ["Loss","to","keep","SpectrogramEnhancer","from","generating","extra","sounds",".","L1","distance","on","x0.25","Mel","scale","(","20","bins","for","typical","80-bin","scale",")"]
code: def __init__(self, weight: float = 10):
      super().__init__()
      self.weight = weight
  
file_path: NeMo/nemo/collections/tts/losses/spectrogram_enhancer_losses.py
imports: import torch
  import torch.nn.functional
  from einops import rearrange
  from torch.autograd import grad
  from nemo.collections.tts.parts.utils.helpers import mask_sequence_tensor
label_desc: Use image node_id 1 to create a new ConsistencyLoss object from inherited base classes: torch.nn with example: obj = ConsistencyLoss(weight)