code: def _sgd_optimizer(c: OptimizerConfigs):
      return torch.optim.SGD(
          c.parameters,
          c.learning_rate,
          c.momentum,
          weight_decay=c.weight_decay,
      )
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/optimizers/configs.py
imports: from typing import Tuple
  import torch
  from labml.configs import BaseConfigs, option, meta_config
  from labml_nn.optimizers import WeightDecay
label_desc: Use image node_id 2 for calling a global function with example usage: _sgd_optimizer(c) and returns: torch