Fast sparse deep learning on CPUs

Overview

SPARSEDNN

**If you want to use this repo, please send me an email: [email protected], or raise a Github issue. **

Fast sparse deep learning on CPUs. This is the kernel library generator described in the paper: https://arxiv.org/abs/2101.07948

Python API: python fastsparse.py. Minimal required dependencies. Should work anywhere.

C++ API: check out driver_cpu.cpp, or run autotune_cpu_random.sh 128 128 128 0. This requires cnpy to read numpy files, so make sure that you can link to cnpy.

Python API has some bad overhead due to using ctypes. This is noticeable for smaller matrices but not really noticeable for large matrices. The benchmarkings done in the Arxiv paper was all done with the C++ API.

Work that is not yet open sourced: kernel generator for sparse convolutions (as described in the Arxiv paper) using implicit convolution, lightweight inference engine to get end-to-end results, sparse int8 kernels. If interested in any of this please email.

FAQs:

  1. How does this compare to Neuralmagic? Last time I checked the deepsparse library does not allow you to run kernel-level benchmarks. If you care about end to end neural network acceleration, you should definitely go with Neuralmagic if they happen to support your model.
  2. Future work? This is not exactly along the lines of my PhD thesis so I work on this sparingly. If you want to contribute to this repo you could make a Pytorch or Tensorflow custom op with the Python or C++ API. However it's unclear how gradients would work, and you will have to compile this op with the fixed sparsity pattern, something that the current Pytorch/Tensorflow frameworks might not support that well.
Owner
Ziheng Wang
Ziheng Wang
Keras attention models including botnet,CoaT,CoAtNet,CMT,cotnet,halonet,resnest,resnext,resnetd,volo,mlp-mixer,resmlp,gmlp,levit

Keras_cv_attention_models Keras_cv_attention_models Usage Basic Usage Layers Model surgery AotNet ResNetD ResNeXt ResNetQ BotNet VOLO ResNeSt HaloNet

319 Dec 28, 2022
Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency[ECCV 2020]

Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency(ECCV 2020) This is an official python implementati

304 Jan 03, 2023
Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

Aesara 898 Jan 07, 2023
A small fun project using python OpenCV, mediapipe, and pydirectinput

Here I tried a small fun project using python OpenCV, mediapipe, and pydirectinput. Here we can control moves car game when yellow color come to right box (press key 'd') left box (press key 'a') lef

Sameh Elisha 3 Nov 17, 2022
SwinTrack: A Simple and Strong Baseline for Transformer Tracking

SwinTrack This is the official repo for SwinTrack. A Simple and Strong Baseline Prerequisites Environment conda (recommended) conda create -y -n SwinT

LitingLin 196 Jan 04, 2023
YOLTv5 rapidly detects objects in arbitrarily large aerial or satellite images that far exceed the ~600×600 pixel size typically ingested by deep learning object detection frameworks

YOLTv5 rapidly detects objects in arbitrarily large aerial or satellite images that far exceed the ~600×600 pixel size typically ingested by deep learning object detection frameworks.

Adam Van Etten 145 Jan 01, 2023
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).

NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti

Wonyong Jeong 15 Nov 21, 2022
Talk covering the features of skorch

Skorch Talk Skorch - A Union of Scikit-learn and PyTorch Presentation The slides can be downloaded at: download link. Google Colab Part One - MNIST Pa

Thomas J. Fan 3 Oct 20, 2020
[CVPR 2021] Pytorch implementation of Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs

Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs In this work, we propose a framework HijackGAN, which enables non-linear latent space travers

Hui-Po Wang 46 Sep 05, 2022
TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-Captured Scenarios

TPH-YOLOv5 This repo is the implementation of "TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-Captured

cv516Buaa 439 Dec 22, 2022
[CVPR21] LightTrack: Finding Lightweight Neural Network for Object Tracking via One-Shot Architecture Search

LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search The official implementation of the paper LightTra

Multimedia Research 290 Dec 24, 2022
Jittor implementation of PCT:Point Cloud Transformer

PCT: Point Cloud Transformer This is a Jittor implementation of PCT: Point Cloud Transformer.

MenghaoGuo 547 Jan 03, 2023
Open-source Monocular Python HawkEye for Tennis

Tennis Tracking 🎾 Objectives Track the ball Detect court lines Detect the players To track the ball we used TrackNet - deep learning network for trac

ArtLabs 188 Jan 08, 2023
GAN-based 3D human pose estimation model for 3DV'17 paper

Tensorflow implementation for 3DV 2017 conference paper "Adversarially Parameterized Optimization for 3D Human Pose Estimation". @inproceedings{jack20

Dominic Jack 15 Feb 27, 2021
Linescanning - Package for (pre)processing of anatomical and (linescanning) fMRI data

line scanning repository This repository contains all of the tools used during the acquisition and postprocessing of line scanning data at the Spinoza

Jurjen Heij 4 Sep 14, 2022
Fastquant - Backtest and optimize your trading strategies with only 3 lines of code!

fastquant 🤓 Bringing backtesting to the mainstream fastquant allows you to easily backtest investment strategies with as few as 3 lines of python cod

Lorenzo Ampil 1k Dec 29, 2022
Implementation of SETR model, Original paper: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.

SETR - Pytorch Since the original paper (Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.) has no official

zhaohu xing 112 Dec 16, 2022
This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize over continuous domains by Brandon Amos

Tutorial on Amortized Optimization This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize

Meta Research 144 Dec 26, 2022
OBG-FCN - implementation of 'Object Boundary Guided Semantic Segmentation'

OBG-FCN This repository is to reproduce the implementation of 'Object Boundary Guided Semantic Segmentation' in http://arxiv.org/abs/1603.09742 Object

Jiu XU 3 Mar 11, 2019
StorSeismic: An approach to pre-train a neural network to store seismic data features

StorSeismic: An approach to pre-train a neural network to store seismic data features This repository contains codes and resources to reproduce experi

Seismic Wave Analysis Group 11 Dec 05, 2022