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From "Anton Dmitriev (JIRA)" <j...@apache.org>
Subject [jira] [Created] (IGNITE-10234) ML: Create a skeleton for model inference in Apache Ignite
Date Tue, 13 Nov 2018 10:49:00 GMT
Anton Dmitriev created IGNITE-10234:

             Summary: ML: Create a skeleton for model inference in Apache Ignite
                 Key: IGNITE-10234
                 URL: https://issues.apache.org/jira/browse/IGNITE-10234
             Project: Ignite
          Issue Type: Sub-task
          Components: ml
    Affects Versions: 2.8
            Reporter: Anton Dmitriev
            Assignee: Anton Dmitriev
             Fix For: 2.8

To support model inference in Apache Ignite for our models as well as for loaded foreign models
we need a common inference workflow. 

This workflow should isolate model _inference/using_ from model _training/saving_. User should
be able to:
* *Load/Unload any possible model (that can be represented as a function).*
_This part assumes that user specifies any underlying model, a bridge that allows to interact
with it and a signature of the model (accepted parameters, returned value)._

* *Access a list of loaded models.*
_Used should be able to access a list of loaded models, models that can be used for inference
without any additional manipulations. In terms of future Cloud part it will be a table of
models user can use in Web UI and start using it._

* *Start/Stop distributed infrastructure for inference utilizing cluster resources.*
_Single inference is actually a single function call. We want to utilize all cluster resources,
so we need to replicate the model and start services that are ready to use the model for inference
on every node._

* *Perform inference on top of started infrastructure.*
_There are should be a gateway that allows to use a single entry point to perform inference
utilizing started on the previous step distributed service infrastructure._

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