Anton Dmitriev created IGNITE-10202:
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Summary: ML: Create a POC of TensorFlow model inference in Java
Key: IGNITE-10202
URL: https://issues.apache.org/jira/browse/IGNITE-10202
Project: Ignite
Issue Type: Sub-task
Components: ml
Affects Versions: 2.8
Reporter: Anton Dmitriev
Assignee: Anton Dmitriev
Fix For: 2.8
TensorFlow models are represented internally as computation graphs that are
saved as a Protobuf objects with some kind of metadata. TensorFlow provides a
good API for Python that allows to work with them, but Java API is very poor.
TensorFlow allows to import computation graph in Java API and manipulate it
using low-level API and it looks like a one way to make model inference in
Java. Another way is based on the fact that the most popular way to build a
TensorFlow model is using of the Keras API. It allows to save model in _.h5_
format that can be imported into Java using Deeplearning4J.
So, the goal of this task is to *prepare a POC that demonstrates*:
* How to import TensorFlow model into Java and make inference using TensorFlow
Java API.
* How to import TensorFlow model into Java and make inference using
Deeplearning4J.
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