class_docstr: Holds the output of a vector quantizer.
class_docstr_tok: ["Holds","the","output","of","a","vector","quantizer","."]
docstr: Compute the loss.
docstr_tok: ["Compute","the","loss","."]
code: def compute_loss(self) -> Tensor:
      """Compute the loss."""
  
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 VectorQuantizerOutput obj's underlying member method code with example usage: obj.compute_loss() without return types