模型不支持Google顶点AI - 400 'dedicated_resources‘

Question

我试图使用Python在Google平台上部署一个与顶点AI一起训练的文本分类模型。

from google.cloud import aiplatform

import os

os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "<key location>"

def create_endpoint(
    project_id: str,
    display_name: str,
    location: str,
    sync: bool = True,
):
    endpoint = aiplatform.Endpoint.create(
        display_name=display_name, project=project_id, location=location,
    )

    print(endpoint.display_name)
    print(endpoint.resource_name)
    return endpoint

def deploy_model(project_id, location, model_id):
    model_location = "projects/{}/locations/{}/models/{}".format(project_id, location, model_id)

    print("Initializing Vertex AI")
    aiplatform.init(project=project_id, location=location)

    print("Getting model from {}".format(model_location))
    model = aiplatform.Model(model_location)

    print("Creating endpoint.")
    endpoint = create_endpoint(project_id, "{}_endpoint".format(model_id), location)

    print("Deploying endpoint")
    endpoint.deploy(
        model,
        machine_type="n1-standard-4",
        min_replica_count=1,
        max_replica_count=5,
        accelerator_type='NVIDIA_TESLA_K80',
        accelerator_count=1
    )

    return endpoint

endpoint = deploy_model(
    "<project name>",
    "us-central1",
    "<model id>",
)

不幸的是，当我运行这段代码时，我会在触发endpoint.deploy之后收到这个错误：google.api_core.exceptions.InvalidArgument: 400 'dedicated_resources' is not supported for Model...，后面跟着模型位置。

注意我用<***>交换了值以隐藏本地工作区变量的位置。

Answer 1

您会遇到错误，因为无法将自定义机器分配给文本分类模型。只有自定义模型和AutoML表格模型可以按照文档使用自定义机器。对于AutoML模型，除了表格模型之外，顶点AI会自动配置机器类型。

如果要使用经过自定义培训的模型或AutoML表格模型来提供在线预测，则必须在将模型资源部署为DeployedModel到终结点时指定计算机类型。对于其他automatically.模型的类型，顶点AI配置机器类型 AutoML

解决这一问题的方法是删除endpoint.deploy()上与机器相关的参数，您应该能够部署模型。

print("Deploying endpoint")
endpoint.deploy(model)