code: def _apply_weight_decay(self, variables):
      if self.weight_decay is None:
          return
  
      torch._foreach_mul_(
          [v.value for v in variables if self._use_weight_decay(v)],
          1 - self.weight_decay * self._get_current_learning_rate(),
      )
  
file_path: keras/keras/backend/torch/optimizers/torch_optimizer.py
imports: import torch
  from keras import optimizers
  from keras.optimizers.base_optimizer import BaseOptimizer
  from keras.utils import torch_utils
label_desc: Use image node_id 2 for calling the TorchOptimizer obj's underlying member method code with example usage: obj._apply_weight_decay(variables) without return types