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NAS + RL

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<img align=”center” width=”350” height=”200” src=”https://i.ibb.co/4Zf5mvG/logo.png” alt=”convstruct-github-logo” border=”0”>

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[<img align=”center” src=”https://i.ibb.co/zmFZZDW/hero-banner.png” alt=”convstruct-hero-banner” border=”0”>](###Convstruct-roadmap)

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###Convstruct 1.1 is here :zap: :zap:

1.1 is an architecture update as well as the addition of reinforcement learning to the topology search. </br> [View full release notes](https://convstruct.org)

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<img align=”right” width=”250” height=”250” src=”https://i.ibb.co/x8WJmPS/convstruct-icon.png”>

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Convstruct is an open source Python framework, containing four functions to create your own topology search for:

• Computer vision models <br> • NLP/NLU models <br> • Reinforcement learning models

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Convstruct, cs, seamlessly works alongside Tensorflow, tf, when your creating your AI models. Code your loss function and optimizer and let Convstruct do the rest.

<img align=”center” src=”https://i.ibb.co/QjHf2vv/main-2.png” alt=”convstruct-functions-banner” border=”0”>

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###Getting started with the python package?

• Install using pip: pip install convstruct <br> • Import Convstruct inside your python file.

###Getting started with the codebase?

• Clone this repo to your local machine using https://github.com/convstruct/convstruct <br> • Run pip install requirements.text in the cloned repo to make sure all Convstruct dependencies are installed on your local machine. <br> • Import Convstruct inside your python file.

> Convstruct 1.1 supports only Python 3.6 and Tensorflow 1.14

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###Convstruct roadmap The roadmap provides a high-level visual of what has been done and what is planned next for Convstruct.

<img align=”center” src=”https://i.ibb.co/RCcntFy/main-3.png” alt=”convstruct-roadmap-banner” border=”0”>

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For inquiries into Convstruct contact: [hello@convstruct.org](hello@convstruct.org)

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