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AWS AI toolkit for DJL

Overview

The aws-ai module contains classes that make it easy for DJL to access AWS services.

Load model from AWS S3 bucket

With this module, you can easily load model from AWS S3 bucket. As long as you include this module in your project, ModelZoo class can load models from your s3 bucket.

The following pseudocode demonstrates how to load model from S3:

    Criteria<Image, Classifications> criteria =
        Criteria.builder()
                .optApplication(Application.CV.IMAGE_CLASSIFICATION)
                .setTypes(Image.class, Classifications.class)
                .optModelUrls("s3://djl-misc/test/models/resnet18")
                .optModelName("resent18_v1")
                .optProgress(new ProgressBar())
                .build();

    ZooModel<Image, Classifications> model = criteria.loadModel();

See How to load a model for more detail.

If you want to customize your AWS credentials and region, you can manually register a customized S3RepositoryFactory:

    S3Client client = S3Client.builder()
        .credentialsProvider(provider)
        .region(Region.US_EAST_1)
        .build();

    Repository.registerRepositoryFactory(new S3RepositoryFactory(client));

Documentation

The latest javadocs can be found on the djl.ai website.

You can also build the latest javadocs locally using the following command:

./gradlew javadoc

The javadocs output is built in the build/doc/javadoc folder.

Installation

You can pull the module from the central Maven repository by including the following dependency in your pom.xml file:

<dependency>
    <groupId>ai.djl.aws</groupId>
    <artifactId>aws-ai</artifactId>
    <version>0.14.0</version>
</dependency>