Skip to main content

NAS + RL

Project description

<br> <br> <br> <br>

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

<br> <br> <br> <br>

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

<br>

###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)

<br>

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

<br>

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

<br> <br>

<br>

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”>

<br>

<br>

###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

<br>

###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”>

<br> <br>

<br>

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

<br> <br>

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

convstruct-1.1.0.tar.gz (16.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

convstruct-1.1.0-py3-none-any.whl (18.7 kB view details)

Uploaded Python 3

File details

Details for the file convstruct-1.1.0.tar.gz.

File metadata

  • Download URL: convstruct-1.1.0.tar.gz
  • Upload date:
  • Size: 16.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.3 pkginfo/1.8.2 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.6.8

File hashes

Hashes for convstruct-1.1.0.tar.gz
Algorithm Hash digest
SHA256 1da000d9262bdd672eb6d0179ec7ed2c4e84fe54955803feed88660dc6770406
MD5 1d8ac5531af4090903c18652dc130278
BLAKE2b-256 e378cd2714382f2997d2fe9f10e398db5ed401032b65ff36f121b37a5971855c

See more details on using hashes here.

File details

Details for the file convstruct-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: convstruct-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 18.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.3 pkginfo/1.8.2 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.6.8

File hashes

Hashes for convstruct-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 563cb2aa0e6b683784d384c4f9b76c804202a93ea3bdedbc977ed05336731b9a
MD5 1f10322a835b4f223a41cb47b5aebb07
BLAKE2b-256 6d5959b3807eaba20dd975713afa5af1d0469a37349dd8344cad381437b5ded2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page