How Do I Check Whether an Error Is Caused by a Model When a Real-Time Service Is Running But Prediction Failed?

Symptom

A running real-time service is used for prediction. After a prediction request is initiated, the received response does not meet the expectation. It is difficult to determine whether the issue is caused by the model.

Possible Cause

After a real-time service is started, either of the following methods can be used for prediction:

• Method 1: Perform prediction on the Prediction tab of the service details page.
• Method 2: Obtain the API URL on the Usage Guides tab of the service details page, and use cURL or Postman for prediction.

This issue may occur after an inference request is initiated, regardless of whether method 1 or 2 is used.

An inference request is finally sent to the model. The issue may be caused by an error occurred when the model processed the inference request. Determine whether the issue is caused by the model, which facilitates rapid fault locating.

Solution

No matter whether method 1 or 2 is used, obtain the response header and body of the inference request.

• If method 1 is used, obtain the response to the inference request through the developer tool of the browser. Take Google Chrome as an example. Press F12 to open the developer tool, click the Network tab and then Predict. The response to the inference request is displayed on the Network tab page.
  Figure 1 Response to an inference request
  

  Find the inference request in the Name pane. The URL of the inference request contains keyword /v1/infers. View the complete URL in the Headers pane. Obtain the response in Headers and Response.

• If method 2 is used, obtain the response header and body through different tools. For example, run the cURL command and use -I to obtain the response header.

If Server in the obtained response header is ModelArts and the response body does not contain a ModelArts.XXXX error code, the response is returned by the model. If the response is not as expected, the issue is caused by the model.

Summary and Suggestions

A model can be imported from a container image, OBS, or AI Gallery. The following provides common troubleshooting methods for each model source:

• For a model imported from a container image, the cause of the issue varies depending on the custom image. Check model logs to identify the cause.
• For a model imported from OBS, if the response you received contains an MR error code, for example, MR.0105, view logs on the Logs tab of the real-time service details page to identify the cause.
• For a model imported from AI Gallery, consult the publisher of the model for the cause.