code: def adjust_learning_rate(lr, step, optimizer, epoch):
      scale = 0.457305051927326
      lr = lr * (scale ** (epoch // step))
      print("lr: {}".format(lr))
      if (epoch != 0) & (epoch % step == 0):
          print("Change lr")
          for param_group in optimizer.param_groups:
              param_group["lr"] = param_group["lr"] * scale
  
file_path: insightface/recognition/idmmd/utils.py
imports: import os
  import numpy
  import torch
  import torch.nn.functional
label_desc: Use image node_id 11 for calling a global function with example usage: adjust_learning_rate(lr, step, optimizer, epoch) without return types