doc-exports/docs/modelarts/umn/modelarts_23_0219.html

Specifications for Custom Images Used for Importing Models

When creating an image using locally developed models, ensure that they meet the specifications defined by ModelArts.

Specifications for Custom Images Used for Model Management

• Custom images cannot contain malicious code.
• The size of a custom image cannot exceed 30 GB.
• External port of images

  The external service port of the image must be 8080. The inference interface must be consistent with the URL defined by apis in the config.json file. The inference interface can be directly accessed when the image is started. The following is an example of accessing the mnist image. The image contains the model trained with the mnist dataset. The model can identify handwritten digits in images. In this example, listen_ip indicates the IP address of the container.

  • Sample request: curl -X POST \ http://{listen_ip}:8080/ \ -F images=@seven.jpg
  • Sample response

    {"mnist_result": 7}

• Health check port

  A custom image must provide a health check interface for ModelArts to call. The health check interface is configured in the config.json file. For details, see the model configuration file compilation description. A sample health check interface is as follows:

  • URI

    GET /health

  • Sample request: curl -X GET \ http://{listen_ip}:8080/health
  • Sample response

    {"health": "true"}

  • Status code

    Table 1 Status code

    Status Code	Message	Description
    200	OK	Successful request

• Log file output

  To ensure that the log content can be displayed normally, the logs must be standard output.

• Image boot file

  To deploy a batch service, set the boot file of an image to /home/run.sh and use CMD to set the default boot path. The following is a sample Dockerfile.

  CMD /bin/sh /home/run.sh

• Image dependencies

  To deploy a batch service, install component packages such as Python, JRE/JDK, and ZIP in the image.

Parent topic: For Importing Models