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Fully Configurable TensorFlow Models #29

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3 of 5 tasks
3ygun opened this issue Jun 14, 2017 · 1 comment
Open
3 of 5 tasks

Fully Configurable TensorFlow Models #29

3ygun opened this issue Jun 14, 2017 · 1 comment

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@3ygun
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3ygun commented Jun 14, 2017

Goal

Allow for the Android app to use any TensorFlow model with a supplied configuration file for retrieving the weights and biases. (Most of the big points on #28)

Parts

  • Complete Android TensorFlow (with wifi & refractoring changes) #32 basic TensorFlow in the app

  • Add ability for server to supply the fields to get the weight values trainable parameters

  • Add ability for app to get & send all the fields supplied by the server

  • Test that everything is happening

  • Supply a program (set of python methods) to CrowdML supervisors that will populate the .json configuration data needed

    • Should give named parameters from the graph/model and populate the feature sizes etc.
    • Something like call:
    def generateCrowdMLTFConfig(session):
        ...
@tylermzeller
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Bullets 2 and 3 have been updated with the current work I have implemented. I should have a PR soon.

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