DJL - TensorFlow engine implementation¶
This module contains the Deep Java Library (DJL) EngineProvider for TensorFlow.
We don't recommend that developers use classes in this module directly. Use of these classes will couple your code with TensorFlow and make switching between frameworks difficult.
Currently training is not supported.
The latest javadocs can be found on the djl.ai website.
You can also build the latest javadocs locally using the following command:
# for Linux/macOS: ./gradlew javadoc # for Windows: ..\..\gradlew javadoc
The javadocs output is built in the
You can pull the TensorFlow engine from the central Maven repository by including the following dependency:
<dependency> <groupId>ai.djl.tensorflow</groupId> <artifactId>tensorflow-engine</artifactId> <version>0.10.0</version> <scope>runtime</scope> </dependency>
tensorflow-engine library, you may also need to include the TensorFlow native library in your project.
Install TensorFlow native library¶
We offer an automatic option that will download the native libraries into cache folder the first time you run DJL. It will automatically determine the appropriate jars for your system based on the platform and GPU support.
<dependency> <groupId>ai.djl.tensorflow</groupId> <artifactId>tensorflow-native-auto</artifactId> <version>2.3.1</version> <scope>runtime</scope> </dependency>