code: def adjust_dynamic_range(data, drange_in, drange_out):
      if drange_in != drange_out:
          scale = (
              np.float32(drange_out[1]) - np.float32(drange_out[0])
          ) / (np.float32(drange_in[1]) - np.float32(drange_in[0]))
          bias = (
              np.float32(drange_out[0])
              - np.float32(drange_in[0]) * scale
          )
          data = data * scale + bias
      return data
  
file_path: insightface/reconstruction/ostec/external/stylegan2/training/misc.py
imports: import os
  import pickle
  import numpy
  import PIL.Image
  import PIL.ImageFont
  import dnnlib
label_desc: Use image node_id 4 for calling a global function with example usage: adjust_dynamic_range(data, drange_in, drange_out) and returns: data