code: def convert(model_path: str, out_file: str):
      
      print('Converting', model_path, 'to', out_file, '...')
  
      import tensorflow as tf
      from precise.model import load_precise_model
      from keras import backend as K
  
      out_dir, filename = split(out_file)
      out_dir = out_dir or '.'
      os.makedirs(out_dir, exist_ok=True)
  
      K.set_learning_phase(0)
      model = load_precise_model(model_path)
  
      out_name = 'net_output'
      tf.identity(model.output, name=out_name)
      print('Output node name:', out_name)
      print('Output folder:', out_dir)
  
      sess = K.get_session()
  
      # Write the graph in human readable
      tf.train.write_graph(sess.graph.as_graph_def(), out_dir, filename + 'txt', as_text=True)
      print('Saved readable graph to:', filename + 'txt')
  
      # Write the graph in binary .pb file
      from tensorflow.python.framework import graph_util
      from tensorflow.python.framework import graph_io
  
      cgraph = graph_util.convert_variables_to_constants(sess, sess.graph.as_graph_def(), [out_name])
      graph_io.write_graph(cgraph, out_dir, filename, as_text=False)
  
      if isfile(model_path + '.params'):
          copyfile(model_path + '.params', out_file + '.params')
  
      print('Saved graph to:', filename)
  
      del sess
docs: Converts an HD5F file from Keras to a .pb for use with TensorFlow
  
      Args:
          model_path: location of Keras model
          out_file: location to write protobuf