code: def _backend_update_step(
      self, grads, trainable_variables, learning_rate
  ):
      self._parallel_update_step(
          grads,
          trainable_variables,
          learning_rate,
      )
  
file_path: keras/keras/backend/torch/optimizers/torch_parallel_optimizer.py
imports: import torch
  from keras.optimizers.base_optimizer import BaseOptimizer
  from keras.utils import torch_utils
label_desc: Use image node_id 1 for calling the TorchParallelOptimizer obj's underlying member method code with example usage: obj._backend_update_step(grads, trainable_variables, learning_rate) without return types