This document is the API specification for the AWS AI toolkit for DJL.
The aws-ai module contains classes that make it easy for DJL to access AWS services.
You can use this toolkit to load models from AWS S3 bucket directly:
// Set model zoo search path system property. The value can be // comma delimited url string. You can add multiple s3 url. // The S3 url should point to a folder in your s3 bucket. // In current implementation, DJL will only download files directly // in that folder. The archive file like .zip, .tar.gz, .tgz, .tar.z // files will be extracted automatically. This is useful for the models // that are created by AWS SageMaker. // The folder name will be interpreted as artifactId and modelName. // If your model file has a different name then the folder name, you // need use query string to tell DJL which model you want to load. System.setProperty("ai.djl.repository.zoo.location", "s3://djl-misc/test/models/resnet18?model_name=resent18_v1"); Criteria<Image, Classifications> criteria = Criteria.builder() .optApplication(Application.CV.IMAGE_CLASSIFICATION) .setTypes(Image.class, Classifications.class) .optArtifactId("ai.djl.localmodelzoo:resnet18") .optProgress(new ProgressBar()) .build(); ZooModel<Image, Classifications> model = criteria.loadModel();
Package | Description |
---|---|
ai.djl.aws.s3 |
Contains a built-in implementation of Repository class that can be used for loading models from
AWS S3 bucket directly.
|
ai.djl.aws.sagemaker |
Contains a utility classes to deploy model on Amazon SageMaker.
|