code: def save_npz(save_list=None, name='model.npz', sess=None):
      
      logging.info("[*] Saving TL params into %s" % name)
      if save_list is None:
          save_list = []
  
      save_list_var = []
      if sess:
          save_list_var = sess.run(save_list)
      else:
          try:
              save_list_var.extend([v.eval() for v in save_list])
          except Exception:
              logging.info(
                  " Fail to save model, Hint: pass the session into this function, tl.files.save_npz(network.all_params, name='model.npz', sess=sess)"
              )
      np.savez(name, params=save_list_var)
      save_list_var = None
      del save_list_var
      logging.info("[*] Saved")
docs: Input parameters and the file name, save parameters into .npz file. Use tl.utils.load_npz() to restore.
  
      Parameters
      ----------
      save_list : list of tensor
          A list of parameters (tensor) to be saved.
      name : str
          The name of the `.npz` file.
      sess : None or Session
          Session may be required in some case.
  
      Examples
      --------
      Save model to npz
  
      >>> tl.files.save_npz(network.all_params, name='model.npz', sess=sess)
  
      Load model from npz (Method 1)
  
      >>> load_params = tl.files.load_npz(name='model.npz')
      >>> tl.files.assign_params(sess, load_params, network)
  
      Load model from npz (Method 2)
  
      >>> tl.files.load_and_assign_npz(sess=sess, name='model.npz', network=network)
  
      Notes
      -----
      If you got session issues, you can change the value.eval() to value.eval(session=sess)
  
      References
      ----------
      `Saving dictionary using numpy <http://stackoverflow.com/questions/22315595/saving-dictionary-of-header-information-using-numpy-savez>`__