Quantized models with python

Overview

quantized-network

download .pth files to qmodels/:

googlenet : https://download.pytorch.org/models/quantized/googlenet_fbgemm-c00238cf.pth

inception_v3 : https://download.pytorch.org/models/quantized/inception_v3_google_fbgemm-71447a44.pth

mobilenet_v2 : https://download.pytorch.org/models/quantized/mobilenet_v2_qnnpack_37f702c5.pth

mobilenet_v3_large : https://download.pytorch.org/models/quantized/mobilenet_v3_large_qnnpack-5bcacf28.pth

resnet18 : https://download.pytorch.org/models/quantized/resnet18_fbgemm_16fa66dd.pth

resnet50 : https://download.pytorch.org/models/quantized/resnet50_fbgemm_bf931d71.pth

resnext101 : https://download.pytorch.org/models/quantized/resnext101_32x8_fbgemm_09835ccf.pth

shufflenetv2_x1.0 : https://download.pytorch.org/models/quantized/shufflenetv2_x1_fbgemm-db332c57.pth

ghostnet : https://1drv.ms/u/s!Ahqo_6nBJPIHhloNb-Rg2uXs38MU?e=Smakww

To do some operations before convolution layer in these networks:

  1. Ghostnet can do some operations on the feature maps of the inter-layer by manipulating the Class ConvX in the operations.py

  2. And other works shoud modifies the Class Comp in operations.py

Run instructions

python validate.py --data --model --actbit <8 or 16 for ghostnet>

# python validate.py --model mobilenet_v3_large --data ./imagenet

# python validate.py --model resnet_18 --data ./imagenet

# python validate.py --model resnet_50 --data ./imagenet

# python validate.py --model resnext_101 --data ./imagenet

# python validate.py --model googlenet --data ./imagenet

# python validate.py --model shufflenet_v2 --data ./imagenet

# python validate.py --model inception_v3 --data ./imagenet

# python validate.py --model mobilenet_v2 --data ./imagenet

# python validate.py --model ghostnet --data ./imagenet --actbit 8
Owner
adreamxcj
adreamxcj
Official PyTorch Implementation of Mask-aware IoU and maYOLACT Detector [BMVC2021]

The official implementation of Mask-aware IoU and maYOLACT detector. Our implementation is based on mmdetection. Mask-aware IoU for Anchor Assignment

Kemal Oksuz 46 Sep 29, 2022
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
Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

Translated in 🇰🇷 Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on

Ludwig 8.7k Dec 31, 2022
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code

sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ

Jonathan Shobrook 305 Dec 21, 2022
Next-Best-View Estimation based on Deep Reinforcement Learning for Active Object Classification

next_best_view_rl Setup Clone the repository: git clone --recurse-submodules ... In 'third_party/zed-ros-wrapper': git checkout devel Install mujoco `

Christian Korbach 1 Feb 15, 2022
Pytorch implementation of the paper Time-series Generative Adversarial Networks

TimeGAN-pytorch Pytorch implementation of the paper Time-series Generative Adversarial Networks presented at NeurIPS'19. Jinsung Yoon, Daniel Jarrett

Zhiwei ZHANG 21 Nov 24, 2022
OptaPlanner wrappers for Python. Currently significantly slower than OptaPlanner in Java or Kotlin.

OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference S

OptaPy 211 Jan 02, 2023
Trading Strategies for Freqtrade

Freqtrade Strategies Strategies for Freqtrade, developed primarily in a partnership between @werkkrew and @JimmyNixx from the Freqtrade Discord. Use t

Bryan Chain 242 Jan 07, 2023
A unified framework to jointly model images, text, and human attention traces.

connect-caption-and-trace This repository contains the reference code for our paper Connecting What to Say With Where to Look by Modeling Human Attent

Meta Research 73 Oct 24, 2022
An implementation of the [Hierarchical (Sig-Wasserstein) GAN] algorithm for large dimensional Time Series Generation

Hierarchical GAN for large dimensional financial market data Implementation This repository is an implementation of the [Hierarchical (Sig-Wasserstein

11 Nov 29, 2022
Background Matting: The World is Your Green Screen

Background Matting: The World is Your Green Screen By Soumyadip Sengupta, Vivek Jayaram, Brian Curless, Steve Seitz, and Ira Kemelmacher-Shlizerman Th

Soumyadip Sengupta 4.6k Jan 04, 2023
Pytorch based library to rank predicted bounding boxes using text/image user's prompts.

pytorch_clip_bbox: Implementation of the CLIP guided bbox ranking for Object Detection. Pytorch based library to rank predicted bounding boxes using t

Sergei Belousov 50 Nov 27, 2022
Classification of EEG data using Deep Learning

Graduation-Project Classification of EEG data using Deep Learning Epilepsy is the most common neurological disease in the world. Epilepsy occurs as a

Osman Alpaydın 5 Jun 24, 2022
Fbone (Flask bone) is a Flask (Python microframework) starter/template/bootstrap/boilerplate application.

Fbone (Flask bone) is a Flask (Python microframework) starter/template/bootstrap/boilerplate application.

Wilson 1.7k Dec 30, 2022
Neural Logic Inductive Learning

Neural Logic Inductive Learning This is the implementation of the Neural Logic Inductive Learning model (NLIL) proposed in the ICLR 2020 paper: Learn

36 Nov 28, 2022
Faune proche - Retrieval of Faune-France data near a google maps location

faune_proche Récupération des données de Faune-France près d'un lieu google maps

4 Feb 15, 2022
Official implementation of "MetaSDF: Meta-learning Signed Distance Functions"

MetaSDF: Meta-learning Signed Distance Functions Project Page | Paper | Data Vincent Sitzmann*, Eric Ryan Chan*, Richard Tucker, Noah Snavely Gordon W

Vincent Sitzmann 100 Jan 01, 2023
Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).

Self-supervised Graph-level Representation Learning with Local and Global Structure Introduction This project is an implementation of ``Self-supervise

MilaGraph 50 Dec 09, 2022
A small library for creating and manipulating custom JAX Pytree classes

Treeo A small library for creating and manipulating custom JAX Pytree classes Light-weight: has no dependencies other than jax. Compatible: Treeo Tree

Cristian Garcia 58 Nov 23, 2022
Unofficial pytorch implementation of 'Image Inpainting for Irregular Holes Using Partial Convolutions'

pytorch-inpainting-with-partial-conv Official implementation is released by the authors. Note that this is an ongoing re-implementation and I cannot f

Naoto Inoue 525 Jan 01, 2023