保存：
saver = tf.train.Saver() saver.save(sess, './model/model.ckpt', global_step=i)读取：
model_dir = "./model/" # 文件路径 reader = tf.train.NewCheckpointReader(tf.train.get_checkpoint_state(model_dir).model_checkpoint_path) data_dict = reader.get_variable_to_shape_map() for key in data_dict: # Print tensor name and values print("tensor_name: ", key) print(reader.get_tensor(key)) # save f = open('./model/tensor.txt', 'a') f.write(key) f.write(str(reader.get_tensor(key))) f.write('\r\n') f.close()