deepjavalibrary / djl

Deep Java Library (DJL) Overview Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and functions like any other regular Java library. You don't have to be machine learning/deep learning expert to get started. You can use your existing Java expertise as an on-ramp to learn and use machine learning and deep learning. You can use your favorite IDE to build, train, and deploy your models. DJL makes it easy to integrate these models with your Java applications. Because DJL is deep learning engine agnostic, you don't have to make a choice between engines when creating your projects. You can switch engines at any point. To ensure the best performance, DJL also provides automatic CPU/GPU choice based on hardware configuration. DJL's ergonomic API interface is designed to guide you with best practices to accomplish deep learning tasks. The following pseudocode demonstrates running inference: The following pseudocode demonstrates running training: Getting Started Resources • Documentation • DJL's D2L Book • JavaDoc API Reference Release Notes • 0.36.0 (Code) • 0.35.1 (Code) • 0.33.0 (Code) • 0.32.0 (Code) • 0.31.1 (Code) • 0.30.0 (Code) • +29 releases Building From Source To build from source, begin by checking out the code. Once you have checked out the code locally, you can build it as follows using Gradle: To increase build speed, you can use the following command to skip unit tests: Importing into eclipse to import source project into eclipse in eclipse file->import->gradle->existing gradle project **Note:** please set your workspace text encoding setting to UTF-8 Community You can read our guide to community forums, following DJL, issues, discussions, and RFCs to figure out the best way to share and find content from the DJL community. Join our slack channel to get in touch with the development team, for questions and discussions. Follow our X (formerly Twitter) to see updates about new content, features, and releases. 关注我们 知乎专栏 获取DJL最新的内容！ Useful Links • DJL Website • Documentation • DJL Demos • Dive into Deep Learning Book Java version License This project is licensed under the Apache-2.0 License.