Anton Dmitriev created IGNITE-10202:
---------------------------------------

             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.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

Reply via email to