如何使用 Python 在 Unified AI Platform 上删除部署到端点的模型？

问题描述

我已在 Unified Cloud AI Platform 上成功创建了一个端点，并为其部署了两个 Model - Model B 和 Model C，分别具有 20% 和 80% 的流量。我之前部署了第三个 Model - Model A，现在它的流量为 0%。

现在，在 Cloud Console（用户界面）上，我可以选择取消部署此 Model A，并且我可以成功执行此操作。但是我无法弄清楚如何使用 Python 客户端 API 来做到这一点。

here 上提供的文档不足以理解我们如何做到这一点。任何帮助将不胜感激。

解决方法

AI Platform Unified 的文档尚未提供有关如何在端点中取消部署模型的示例。您现在可以参考可用服务的 AI platform unified rpc reference。代码如下：

注意：在运行代码之前，不要忘记更新 end_point（端点 ID）、项目（项目 ID）、model_id 的值。

from google.cloud import aiplatform
from google.cloud import aiplatform_v1


def undeploy_model_in_endpoint(
    end_point: str,project: str,model_id: str,location: str = "us-central1",api_endpoint: str = "us-central1-aiplatform.googleapis.com",timeout: int = 7200,):
    # The AI Platform services require regional API endpoints.
    client_options = {"api_endpoint": api_endpoint}
    # Initialize client that will be used to create and send requests.
    # This client only needs to be created once,and can be reused for multiple requests.
    client = aiplatform.gapic.EndpointServiceClient(client_options=client_options)
    client_model = aiplatform_v1.services.model_service.ModelServiceClient(client_options=client_options)

    # Get deployed_model_id
    model_name = f'projects/{project}/locations/{location}/models/{model_id}'
    model_request = aiplatform_v1.types.GetModelRequest(name=model_name)
    model_info = client_model.get_model(request=model_request)
    deployed_models_info = model_info.deployed_models
    deployed_model_id=model_info.deployed_models[0].deployed_model_id

    name=f'projects/{project}/locations/{location}/endpoints/{end_point}'

    undeploy_request = aiplatform_v1.types.UndeployModelRequest(endpoint=name,deployed_model_id=deployed_model_id)
    client.undeploy_model(request=undeploy_request)

undeploy_model_in_endpoint(end_point='your-endpoint-id',project='your-project-id',model_id='your-model-id')