启动您的 Amazon Lookout for Vision 模型

更改以下值：

aws lookoutvision start-model --project-name "project name"\
  --model-version model version\
  --min-inference-units minimum number of units\
  --max-inference-units max number of units \
  --profile lookoutvision-access

此代码取自 AWS 文档 SDK 示例 GitHub 存储库。请在此处查看完整示例。

    @staticmethod
    def start_model(
            lookoutvision_client, project_name, model_version, min_inference_units, max_inference_units = None):
        """
        Starts the hosting of a Lookout for Vision model.

        :param lookoutvision_client: A Boto3 Lookout for Vision client.
        :param project_name:  The name of the project that contains the version of the
                              model that you want to start hosting.
        :param model_version: The version of the model that you want to start hosting.
        :param min_inference_units: The number of inference units to use for hosting.
        :param max_inference_units: (Optional) The maximum number of inference units that
        Lookout for Vision can use to automatically scale the model.
        """
        try:
            logger.info(
                "Starting model version %s for project %s", model_version, project_name)
            
            if max_inference_units is None:
                lookoutvision_client.start_model(
                    ProjectName = project_name,
                    ModelVersion = model_version,
                    MinInferenceUnits = min_inference_units)

            else:
                lookoutvision_client.start_model(
                    ProjectName = project_name,
                    ModelVersion = model_version,
                    MinInferenceUnits = min_inference_units,
                    MaxInferenceUnits = max_inference_units)

            print("Starting hosting...")

            status = ""
            finished = False

            # Wait until hosted or failed.
            while finished is False:
                model_description = lookoutvision_client.describe_model(
                    ProjectName=project_name, ModelVersion=model_version)
                status = model_description["ModelDescription"]["Status"]

                if status == "STARTING_HOSTING":
                    logger.info("Host starting in progress...")
                    time.sleep(10)
                    continue

                if status == "HOSTED":
                    logger.info("Model is hosted and ready for use.")
                    finished = True
                    continue

                logger.info("Model hosting failed and the model can't be used.")
                finished = True

            if status != "HOSTED":
                logger.error("Error hosting model: %s", status)
                raise Exception(f"Error hosting model: {status}")
        except ClientError:
            logger.exception("Couldn't host model.")
            raise

此代码取自 AWS 文档 SDK 示例 GitHub 存储库。请在此处查看完整示例。

/**
 * Starts hosting an Amazon Lookout for Vision model. Returns when the model has
 * started or if hosting fails. You are charged for the amount of time that a
 * model is hosted. To stop hosting a model, use the StopModel operation.
 * 
 * @param lfvClient   An Amazon Lookout for Vision client.
 * @param projectName The name of the project that contains the model that you
 *                    want to host.
 * @modelVersion The version of the model that you want to host.
 * @minInferenceUnits The number of inference units to use for hosting.
 * @maxInferenceUnits The maximum number of inference units that Lookout for
 *                    Vision can use for automatically scaling the model. If the
 *                    value is null, automatic scaling doesn't happen.
 * @return ModelDescription The description of the model, which includes the
 *         model hosting status.
 */
public static ModelDescription startModel(LookoutVisionClient lfvClient, String projectName, String modelVersion,
        Integer minInferenceUnits, Integer maxInferenceUnits) throws LookoutVisionException, InterruptedException {

    logger.log(Level.INFO, "Starting Model version {0} for project {1}.",
            new Object[] { modelVersion, projectName });

    StartModelRequest startModelRequest = null;

    if (maxInferenceUnits == null) {

        startModelRequest = StartModelRequest.builder().projectName(projectName).modelVersion(modelVersion)
                .minInferenceUnits(minInferenceUnits).build();
    } else {
        startModelRequest = StartModelRequest.builder().projectName(projectName).modelVersion(modelVersion)
                .minInferenceUnits(minInferenceUnits).maxInferenceUnits(maxInferenceUnits).build();
    }

    // Start hosting the model.
    lfvClient.startModel(startModelRequest);

    DescribeModelRequest describeModelRequest = DescribeModelRequest.builder().projectName(projectName)
            .modelVersion(modelVersion).build();

    ModelDescription modelDescription = null;

    boolean finished = false;
    // Wait until model is hosted or failure occurs.
    do {

        modelDescription = lfvClient.describeModel(describeModelRequest).modelDescription();

        switch (modelDescription.status()) {

        case HOSTED:
            logger.log(Level.INFO, "Model version {0} for project {1} is running.",
                    new Object[] { modelVersion, projectName });
            finished = true;
            break;

        case STARTING_HOSTING:
            logger.log(Level.INFO, "Model version {0} for project {1} is starting.",
                    new Object[] { modelVersion, projectName });

            TimeUnit.SECONDS.sleep(60);

            break;
        case HOSTING_FAILED:
            logger.log(Level.SEVERE, "Hosting failed for model version {0} for project {1}.",
                    new Object[] { modelVersion, projectName });
            finished = true;
            break;

        default:
            logger.log(Level.SEVERE, "Unexpected error when hosting model version {0} for project {1}: {2}.",
                    new Object[] { projectName, modelVersion, modelDescription.status() });
            finished = true;
            break;

        }

    } while (!finished);

    logger.log(Level.INFO, "Finished starting model version {0} for project {1} status: {2}",
            new Object[] { modelVersion, projectName, modelDescription.statusMessage() });

    return modelDescription;

}