code: def compute_loss(self) -> Tensor:
      num_entries = self.num_codebooks * self.num_codebook_entries
  
      return (num_entries - self.prob_perplexity) / num_entries
  
imports: from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from typing import Optional, Tuple, final
  import torch
  import torch.nn
  from torch import Tensor
  from torch.nn import Module, Parameter
  from torch.nn.functional import gumbel_softmax
  from fairseq2.nn.projection import Linear
  from fairseq2.typing import DataType, Device, finaloverride
label_desc: Use image node_id 1 for calling the GumbelVectorQuantizerOutput obj's underlying member method code with example usage: obj.compute_loss() and returns: unknown