创建端点配置

拥有模型后，请使用 CreateEndpointConfig 创建端点配置。Amazon SageMaker 托管服务使用此配置来部署模型。在配置中，您可以标识使用和创建的一个或多个模型 CreateModel，以部署您希望 Amazon 预置 SageMaker 的资源。指定 AsyncInferenceConfig 对象并为 OutputConfig 提供输出 Amazon S3 位置。您可以选择指定用于发送预测结果通知的 Amazon SNS 主题。有关亚马逊SNS主题的更多信息，请参阅配置亚马逊SNS。

以下示例演示了如何使用 AWS SDK for Python (Boto3)创建端点配置:

import datetime
from time import gmtime, strftime

# Create an endpoint config name. Here we create one based on the date  
# so it we can search endpoints based on creation time.
endpoint_config_name = f"XGBoostEndpointConfig-{strftime('%Y-%m-%d-%H-%M-%S', gmtime())}"

# The name of the model that you want to host. This is the name that you specified when creating the model.
model_name='<The_name_of_your_model>'

create_endpoint_config_response = sagemaker_client.create_endpoint_config(
    EndpointConfigName=endpoint_config_name, # You will specify this name in a CreateEndpoint request.
    # List of ProductionVariant objects, one for each model that you want to host at this endpoint.
    ProductionVariants=[
        {
            "VariantName": "variant1", # The name of the production variant.
            "ModelName": model_name, 
            "InstanceType": "ml.m5.xlarge", # Specify the compute instance type.
            "InitialInstanceCount": 1 # Number of instances to launch initially.
        }
    ],
    AsyncInferenceConfig={
        "OutputConfig": {
            # Location to upload response outputs when no location is provided in the request.
            "S3OutputPath": f"s3://{s3_bucket}/{bucket_prefix}/output"
            # (Optional) specify Amazon SNS topics
            "NotificationConfig": {
                "SuccessTopic": "arn:aws:sns:aws-region:account-id:topic-name",
                "ErrorTopic": "arn:aws:sns:aws-region:account-id:topic-name",
            }
        },
        "ClientConfig": {
            # (Optional) Specify the max number of inflight invocations per instance
            # If no value is provided, Amazon SageMaker will choose an optimal value for you
            "MaxConcurrentInvocationsPerInstance": 4
        }
    }
)

print(f"Created EndpointConfig: {create_endpoint_config_response['EndpointConfigArn']}")

在上述示例中，您为 AsyncInferenceConfig 字段的 OutputConfig 指定以下键：

您还可以在 AsyncInferenceConfig 字段中为 ClientConfig 指定以下可选参数：