code: def lr_linear_policy(base_lr, warmup_length, epochs):
      def _lr_fn(iteration, epoch):
          if epoch < warmup_length:
              lr = base_lr * (epoch + 1) / warmup_length
          else:
              e = epoch - warmup_length
              es = epochs - warmup_length
              lr = base_lr * (1 - (e / es))
          return lr
  
      return lr_policy(_lr_fn)
  
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 6 for calling a global function with example usage: lr_linear_policy(base_lr, warmup_length, epochs) and returns: lr_policy, lr