NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch

Overview

NuPIC Studio Logo NuPIC Studio *nix Build Status

NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch, train it, collect statistics, and share it among the members of the community. It is not just a visualization tool but an HTM builder, debugger and laboratory for experiments. It is ideal for newbies with little intimacy with NuPIC code as well as experts that wish a better productivity. Among its features and advantages:

  • Users can open, save, or change their "HTM projects" or of other developers. A typical project contains data to be trained, neural network configuration, statistics, etc, which can be shared to be analysed or integrated with other projects.
  • The HTM engine is the own original NuPIC libray (Python distribution). This means no port, no bindings, no re-implementation, etc. So any changes in the original nupic source can be immediatedly viewed. This helps users that wish test improvements like new encoders or even hierarchy, attention, and motor integration.

Screenshot

For more information, see numenta.org or the NuPIC Studio wiki.

Installation

Currently supported platforms:

  • Windows
  • Linux (32/64bit)
  • Mac OSX

Dependencies:

  • Python (2.7 or later)
  • PIP
  • NuPIC
  • NumPy
  • PyQt5

User instructions

If you want only use it, simply do this:

pip install nupic_studio

Note: Dear *nix users, if you get a "permission denied" error when using pip, you may add the --user flag to install to a location in your home directory, which should resolve any permissions issues. Doing this, you may need to add this location to your PATH and PYTHONPATH. Alternatively, you can run pip with 'sudo'.

Once it is installed, you can execute the app using:

nupic_studio

and then click on Open Project button to open any example to getting started with NuPIC.

Developer instructions

If you want develop, debug, or simply test NuPIC Studio, clone it and follow the instructions:

Using command line

This assumes the NUPIC_STUDIO environment variable is set to the directory where the NuPIC Studio source code exists.

cd $NUPIC_STUDIO
python setup.py build
python setup.py develop

Using an IDE

The following instructions will work in the most Python IDEs:

  • Open your IDE.
  • Open a project specifying the $NUPIC_STUDIO repository folder as location.
  • Click with mouse right button on setup.py file listed on project files and select Run command on pop-up menu. This will call the build process. Check output panel to see the result.
  • If the build was successful, just click on program.py and voilà!

If you don't have a favourite Python IDE, this article can help you to choose one: http://pedrokroger.net/choosing-best-python-ide/

Owner
HTM Community
Home for community-led HTM repositories.
HTM Community
The official code of "SCROLLS: Standardized CompaRison Over Long Language Sequences".

SCROLLS This repository contains the official code of the paper: "SCROLLS: Standardized CompaRison Over Long Language Sequences". Links Official Websi

TAU NLP Group 39 Dec 23, 2022
QQ Browser 2021 AI Algorithm Competition Track 1 1st Place Program

QQ Browser 2021 AI Algorithm Competition Track 1 1st Place Program

249 Jan 03, 2023
NeRF Meta-Learning with PyTorch

NeRF Meta Learning With PyTorch nerf-meta is a PyTorch re-implementation of NeRF experiments from the paper "Learned Initializations for Optimizing Co

Sanowar Raihan 78 Dec 18, 2022
Implementation of ICLR 2020 paper "Revisiting Self-Training for Neural Sequence Generation"

Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi

Junxian He 45 Dec 31, 2022
StyleSwin: Transformer-based GAN for High-resolution Image Generation

StyleSwin This repo is the official implementation of "StyleSwin: Transformer-based GAN for High-resolution Image Generation". By Bowen Zhang, Shuyang

Microsoft 349 Dec 28, 2022
Next-gen Rowhammer fuzzer that uses non-uniform, frequency-based patterns.

Blacksmith Rowhammer Fuzzer This repository provides the code accompanying the paper Blacksmith: Scalable Rowhammering in the Frequency Domain that is

Computer Security Group @ ETH Zurich 173 Nov 16, 2022
Automatically replace ONNX's RandomNormal node with Constant node.

onnx-remove-random-normal This is a script to replace RandomNormal node with Constant node. Example Imagine that we have something ONNX model like the

Masashi Shibata 1 Dec 11, 2021
Implementations of paper Controlling Directions Orthogonal to a Classifier

Classifier Orthogonalization Implementations of paper Controlling Directions Orthogonal to a Classifier , ICLR 2022, Yilun Xu, Hao He, Tianxiao Shen,

Yilun Xu 33 Dec 01, 2022
《Train in Germany, Test in The USA: Making 3D Object Detectors Generalize》(CVPR 2020)

Train in Germany, Test in The USA: Making 3D Object Detectors Generalize This paper has been accpeted by Conference on Computer Vision and Pattern Rec

Xiangyu Chen 101 Jan 02, 2023
Sequence Modeling with Structured State Spaces

Structured State Spaces for Sequence Modeling This repository provides implementations and experiments for the following papers. S4 Efficiently Modeli

HazyResearch 896 Jan 01, 2023
Survival analysis in Python

What is survival analysis and why should I learn it? Survival analysis was originally developed and applied heavily by the actuarial and medical commu

Cameron Davidson-Pilon 2k Jan 08, 2023
PyTorch implementations of Generative Adversarial Networks.

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

Erik Linder-Norén 13.4k Jan 08, 2023
The official MegEngine implementation of the ICCV 2021 paper: GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning

[ICCV 2021] GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning This is the official implementation of our ICCV2021 paper GyroFlow. Our pres

MEGVII Research 36 Sep 07, 2022
This repository provides an efficient PyTorch-based library for training deep models.

s3sec Test AWS S3 buckets for read/write/delete access This tool was developed to quickly test a list of s3 buckets for public read, write and delete

Bytedance Inc. 123 Jan 05, 2023
CrossMLP - The repository offers the official implementation of our BMVC 2021 paper (oral) in PyTorch.

CrossMLP Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation Bin Ren1, Hao Tang2, Nicu Sebe1. 1University of Trento, Italy, 2ETH, Switzerla

Bingoren 16 Jul 27, 2022
Face recognition. Redefined.

FaceFinder Use a powerful CNN to identify faces in images! TABLE OF CONTENTS About The Project Built With Getting Started Prerequisites Installation U

BleepLogger 20 Jun 16, 2021
Implementation of TabTransformer, attention network for tabular data, in Pytorch

Tab Transformer Implementation of Tab Transformer, attention network for tabular data, in Pytorch. This simple architecture came within a hair's bread

Phil Wang 420 Jan 05, 2023
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data

This repository is the official PyTorch implementation of Meta-Balance. Find the paper on arxiv MetaBalance: High-Performance Neural Networks for Clas

Arpit Bansal 20 Oct 18, 2021
An official repository for Paper "Uformer: A General U-Shaped Transformer for Image Restoration".

Uformer: A General U-Shaped Transformer for Image Restoration Zhendong Wang, Xiaodong Cun, Jianmin Bao and Jianzhuang Liu Paper: https://arxiv.org/abs

Zhendong Wang 497 Dec 22, 2022
Source Code for Simulations in the Publication "Can the brain use waves to solve planning problems?"

Code for Simulations in the Publication Can the brain use waves to solve planning problems? Installing Required Python Packages Please use Python vers

EMD Group 2 Jul 01, 2022