text: import conv_net_sound
  import conv_net_sound_weight
  img_nrows, img_ncols = 505, 1025
  input_shape = [330491]
  model_old = conv_net_sound_weight.conv_net(input_shape=input_shape, class_n = 16)
  model_old.load_weights('./top_weight.h5')
  model_new = conv_net_sound.conv_net(input_shape=(img_nrows, img_ncols, 1), class_n=None)
  model_old_dict = dict([(layer.name, layer) for layer in model_old.layers])
  model_new_dict = dict([(layer.name, layer) for layer in model_new.layers])
  for lname in model_old_dict:
      for rname in model_new_dict:
          if lname == rname:
              try:
                  model_new_dict[rname].set_weights(model_old_dict[lname].get_weights())
              except:
                  print lname
                  continue
  
  model_new.save_weights('./conv_net.h5')
  
  