code: def conv_para(self, para_hyper):
      para_gfo = {}
      for para in self.s_space.dim_keys:
          value_hyper = para_hyper[para]
          space_dim = list(self.s_space.func2str[para])
  
          if self.s_space.data_types[para] == "number":
              value_gfo = np.abs(
                  value_hyper - np.array(space_dim)
              ).argmin()
          else:
              value_hyper = self.value_func2str(value_hyper)
  
              if value_hyper in space_dim:
                  value_gfo = space_dim.index(value_hyper)
              else:
                  raise ValueError(
                      "'{}' was not found in '{}'".format(
                          value_hyper, para
                      )
                  )
  
          para_gfo[para] = value_gfo
      return para_gfo
  
file_path: Hyperactive/hyperactive/optimizers/hyper_gradient_conv.py
imports: import numpy
  import pandas
label_desc: Use image node_id 8 for calling the HyperGradientConv obj's underlying member method code with example usage: obj.conv_para(para_hyper) and returns: para_gfo