code: def get_trainable_parameters(self) -> Iterator[torch.nn.Parameter]:
      yield from self.parameters()
  
imports: import logging
  from abc import abstractmethod
  from typing import Dict, Iterator, Literal, Optional, Tuple, Union
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from einops import rearrange
  from torch import einsum
  from .base import AbstractRegularizer, measure_perplexity
label_desc: Use image node_id 5 for calling the AbstractQuantizer obj's underlying member method code with example usage: obj.get_trainable_parameters() without return types