问题

I'm providing the translated code section:

我正在尝试实现代码以启动 Vertex 中的自定义作业。

我使用 `gcloud` 来启动自定义作业没有问题：

gcloud ai custom-jobs --project my_project_id create --region=europe-west1 --display-name="train model based on custom container" --worker-pool-spec=machine-type=n1-standard-4,replica-count=1,container-image-uri=europe-west1-docker.pkg.dev/my_project_id/my-repo/my-custom-prototype:latest

我没有找到官方的 .NET 代码示例，但尝试模仿 [其他人在 Python 中执行的方式][1]，同时 ChatGPT 生成了类似的代码示例：

```csharp
var projectId = "my_project_id";
var locationId = "europe-west1";
var client = await JobServiceClient.CreateAsync();

var createCustomJobRequest = new CreateCustomJobRequest
{
  ParentAsLocationName = new LocationName(projectId, locationId),
  CustomJob = new CustomJob
  {
    DisplayName = "train model based on custom container",
    JobSpec = new CustomJobSpec()
    {
      WorkerPoolSpecs =
      {
        new WorkerPoolSpec
        {
          MachineSpec = new MachineSpec
          {
            MachineType = "n1-standard-4"
          },
          ReplicaCount = 1,
          ContainerSpec = new ContainerSpec()
          {
            ImageUri = "europe-west1-docker.pkg.dev/my_project_id/my-repo/my-custom-prototype:latest"
          }
        }
      }
    }
  }
};

var result3 = await client.CreateCustomJobAsync(createCustomJobRequest); // exception thrown here

不幸的是，我收到一个异常：

Grpc.Core.RpcException: 'Status(StatusCode="Unimplemented", Detail="Bad gRPC response. HTTP status code: 404")'

我尝试过但失败了的事情：

1. 使用接受 CustomJob 和 Parent 而不是 CreateCustomJobRequest 对象的 CreateCustomJobAsync() 方法的重载。
2. 使用 JobServiceClientBuilder 而不是 JobServiceClient.CreateAsync()，并将 Endpoint 参数设置为 europe-west1-aiplatform.googleapis.com。

我缺少什么，以便在 Vertex AI 中启动自定义作业？

Please note that this is a direct translation of the code portion you provided.

<details>
<summary>英文:</summary>

I&#39;m trying to implement code to start a custom job in Vertex.

I have no problem starting a custom job using `gcloud`:

gcloud ai custom-jobs --project my_project_id create --region=europe-west1 --display-name="train model based on custom container" --worker-pool-spec=machine-type=n1-standard-4,replica-count=1,container-image-uri=europe-west1-docker.pkg.dev/my_project_id/my-repo/my-custom-prototype:latest

I've not been able to find official code sample for .NET but tried to mimick [someone else doing it in Python][1] plus ChatGPT produced a similar code sample:

var projectId = "my_project_id";
var locationId = "europe-west1";
var client = await JobServiceClient.CreateAsync();

var createCustomJobRequest = new CreateCustomJobRequest
{
ParentAsLocationName = new LocationName(projectId, locationId),
CustomJob = new CustomJob
{
DisplayName = "train model based on custom container",
JobSpec = new CustomJobSpec()
{
WorkerPoolSpecs =
{
new WorkerPoolSpec
{
MachineSpec = new MachineSpec
{
MachineType = "n1-standard-4"
},
ReplicaCount = 1,
ContainerSpec = new ContainerSpec()
{
ImageUri = "europe-west1-docker.pkg.dev/my_project_id/my-repo/my-custom-prototype:latest"
}
}
}
}
}
};

var result3 = await client.CreateCustomJobAsync(createCustomJobRequest); // exception thrown here

Unfortunately, I get an exception back:

Grpc.Core.RpcException: 'Status(StatusCode="Unimplemented", Detail="Bad gRPC response. HTTP status code: 404")'

Things I've tried and failed
1) Used the overload of `CreateCustomJobAsync()` that takes a `CustomJob` and a `Parent` instead of a `CreateCustomJobRequest` object.
2) Used `JobServiceClientBuilder` instead of `JobServiceClient.CreateAsync()` and set the `Endpoint` argument as `europe-west1-aiplatform.googleapis.com`.

What am I missing to get a custom job started in Vertex AI?


  [1]: https://stackoverflow.com/questions/73154492/vertex-ai-custom-job-cannot-launch-it-via-python

</details>


# 答案1
**得分**: 1

I should have digged a bit more around `JobServiceClientBuilder`. Specifically, when using the builder's `client` object to start a job I actually got a different message back:

```plaintext
Grpc.Core.RpcException
  HResult=0x80131500
  Message=Status(StatusCode="PermissionDenied", Detail="Permission 'aiplatform.customJobs.create' denied on resource '//aiplatform.googleapis.com/projects/my_project_id/locations/europe-west1' (or it may not exist).")
  Source=Google.Api.Gax.Grpc

While the message was somewhat clear I wasn't sure if it was the right error message, like how Unimplemented didn't make sense so I dismissed this one too.

Anyway, since writing the question I thought that gcloud and SDK authentication may be different. It turns out that the active user in the command line (the * next to the user in gcloud auth list) is my own credential while the environment variable GOOGLE_APPLICATION_CREDENTIAL is referencing a service account. Once I added the role Vertex AI Administrator to the service account I was finally able to start a job.

So, use JobServiceClient.CreateAsync() if the sa behind GOOGLE_APPLICATION_CREDENTIAL has the right permission. If you need to use another sa then instantiate a JobServiceClient like so:

var client = await new JobServiceClientBuilder
{
	Endpoint = "europe-west1-aiplatform.googleapis.com",
	GoogleCredential = GoogleCredential.FromFile(@"your-service-account.json")
}.BuildAsync();

I know the latter is "standard GCP authentication" knowledge, it just didn't come to my mind immediately.

Grpc.Core.RpcException
  HResult=0x80131500
  Message=Status(StatusCode="PermissionDenied", Detail="Permission 'aiplatform.customJobs.create' denied on resource '//aiplatform.googleapis.com/projects/my_project_id/locations/europe-west1' (or it may not exist).")
  Source=Google.Api.Gax.Grpc

var client = await new JobServiceClientBuilder
{
	Endpoint = "europe-west1-aiplatform.googleapis.com",
	GoogleCredential = GoogleCredential.FromFile(@"your-service-account.json")
}.BuildAsync();

答案2

得分: 0

我不确定为什么为OP提供适当的权限会解决问题，但代码存在不同的问题，导致了模糊的错误消息。根据客户端库文档，Vertex AI需要使用区域化的终端节点，因此客户端应该被构建以反映将要访问的资源。在这种情况下，代码如下：

var client = await new JobServiceClientBuilder
{
    Endpoint = "europe-west1-aiplatform.googleapis.com"
}.BuildAsync();

... 显然，如果您在多个区域使用资源，您可以使用插值字符串文字使其动态化。但是您确实需要为不同的区域使用不同的客户端。

希望我们可以在将来减少这种模糊错误。

var client = await new JobServiceClientBuilder
{
    Endpoint = "europe-west1-aiplatform.googleapis.com"
}.BuildAsync();