code: def conv_initialize(self, initialize):
      if "warm_start" in list(initialize.keys()):
          warm_start_l = initialize["warm_start"]
          warm_start_gfo = []
          for warm_start in warm_start_l:
              para_gfo = self.conv_para(warm_start)
              warm_start_gfo.append(para_gfo)
  
          initialize["warm_start"] = warm_start_gfo
  
      return initialize
  
file_path: Hyperactive/hyperactive/optimizers/hyper_gradient_conv.py
imports: import numpy
  import pandas
label_desc: Use image node_id 9 for calling the HyperGradientConv obj's underlying member method code with example usage: obj.conv_initialize(initialize) and returns: initialize