code: def build_lambda_sche(opti, config):
      if config.get("decay_step") is not None:
          lr_lbmd = lambda e: max(
              config.lr_decay ** (e / config.decay_step),
              config.lowest_decay,
          )
          scheduler = torch.optim.lr_scheduler.LambdaLR(opti, lr_lbmd)
      else:
          raise NotImplementedError()
      return scheduler
  
imports: import numpy
  import matplotlib.pyplot
  from mpl_toolkits.mplot3d import Axes3D
  import random
  import torch
  import torch.nn
  import torch.nn.functional
  import os
  from collections import abc
label_desc: Use image node_id 4 for calling a global function with example usage: build_lambda_sche(opti, config) and returns: scheduler