如何用python对TFOD2 pipeline.config文件进行读写？

import tensorflow as tf
from google.protobuf import text_format
from object_detection.protos import pipeline_pb2

def read_pipeline_config(config_path):
    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    with tf.io.gfile.GFile(config_path, 'r') as f:
        proto_str = f.read()
        text_format.Merge(proto_str, pipeline_config)
    return pipeline_config

def write_pipeline_config(config_path, pipeline_config):
    config_text = text_format.MessageToString(pipeline_config)
    with tf.io.gfile.GFile(config_path, 'w') as f:
        f.write(config_text)

# 读取pipeline.config文件
config_path = 'path/to/pipeline.config'
pipeline_config = read_pipeline_config(config_path)

# 对pipeline_config进行修改
pipeline_config.model.ssd.num_classes = 10
pipeline_config.train_config.batch_size = 32

# 写入修改后的pipeline.config文件
write_pipeline_config(config_path, pipeline_config)