code: def get_rmsprop_optimizer(
      parameters,
      lr,
      alpha,
      weight_decay,
      momentum,
      eps,
      bn_weight_decay=False,
  ):
      bn_params = [v for n, v in parameters if "bn" in n]
      rest_params = [v for n, v in parameters if not "bn" in n]
  
      params = [
          {
              "params": bn_params,
              "weight_decay": weight_decay if bn_weight_decay else 0,
          },
          {"params": rest_params, "weight_decay": weight_decay},
      ]
  
      optimizer = torch.optim.RMSprop(
          params,
          lr=lr,
          alpha=alpha,
          weight_decay=weight_decay,
          momentum=momentum,
          eps=eps,
      )
  
      return optimizer
  
file_path: DALI/docs/examples/use_cases/pytorch/efficientnet/image_classification/optimizers.py
imports: import math
  import numpy
  import torch
  from torch import optim
label_desc: Use image node_id 3 for calling a global function with example usage: get_rmsprop_optimizer(parameters, lr, alpha, weight_decay, momentum, eps, bn_weight_decay) and returns: optimizer