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https://issues.apache.org/jira/browse/IGNITE-10202?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Anton Dmitriev updated IGNITE-10202:
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Description:
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.
was:
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.
> 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
> Priority: Major
> 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.
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