如何使用Python和TensorFlow服务模型调用特定的模型版本？

import tensorflow as tf
from tensorflow import keras

# 创建gRPC连接
channel = grpc.insecure_channel('localhost:8500')

# 创建TensorFlow Serving的客户端
stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)

# 创建请求消息
request = predict_pb2.PredictRequest()

# 设置模型名称和版本号
request.model_spec.name = 'model_name'
request.model_spec.version.value = model_version

# 设置输入数据
request.inputs['input_name'].CopyFrom(tf.make_tensor_proto(input_data))

# 发送请求
response = stub.Predict(request, timeout)

# 解析预测结果
output_data = tf.make_ndarray(response.outputs['output_name'])