如何在顶点AI中利用XGBoost模型的批量预测保留实体标识符

from google.cloud import aiplatform

# 初始化客户端
client = aiplatform.gapic.JobServiceClient()

# 定义批量预测任务参数
batch_prediction_job = {
    "display_name": "xgboost-batch-prediction",
    "model": "projects/your-project-id/models/your-model-id",
    "input_data": {
        "gcs_source": {
            "input_uris": ["gs://your-bucket/data.csv"]
        }
    },
    "output_data": {
        "gcs_destination": {
            "output_uri_prefix": "gs://your-bucket/predictions/"
        }
    },
    "job_spec": {
        "worker_pool_specs": [
            {
                "machine_spec": {
                    "machine_type": "n1-standard-4"
                },
                "replica_count": 1,
                "container_spec": {
                    "image_uri": "gcr.io/cloud-ml-base/xgboost-gpu",
                    "args": ["--input-data", "$INPUT_FILE", "--output-data", "$OUTPUT_FILE"]
                }
            }
        ]
    }
}

# 提交批量预测任务
parent = client.common_location_path("your-project-id", "us-central1")
response = client.create_batch_prediction_job(parent=parent, batch_prediction_job=batch_prediction_job)
print(f"Batch prediction job created: {response.name}")