A Lighting Pytorch Framework for Recommendation System, Easy-to-use and Easy-to-extend.

Related tags

Deep Learningpytorchctrrecommendation-algorithm
Overview

Torch-RecHub

A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.

安装

pip install torch-rechub

主要特性

  • scikit-learn风格易用的API（fit、predict），即插即用

  • 训练过程与模型定义解耦，易拓展，可针对不同类型的模型设置不同的训练机制

  • 使用Pytorch原生Dataset、DataLoader，易修改，自定义数据

  • 高度模块化，支持常见Layer（MLP、FM、FFM、target-attention、self-attention、transformer等），容易调用组装成新模型

  • 支持常见排序模型（WideDeep、DeepFM、DIN、DCN、xDeepFM等）

  • 支持常见召回模型（DSSM、YoutubeDNN、MIND、SARSRec等）

  • 丰富的多任务学习支持

    • SharedBottom、ESMM、MMOE、PLE、AITM等模型
    • GradNorm、UWL等动态loss加权机制

  • 聚焦更生态化的推荐场景

    • 冷启动
    • 延迟反馈
    • 去偏

  • 支持丰富的训练机制（对比学习、蒸馏学习等）

  • 第三方高性能开源Trainer支持（Pytorch Lighting等）

  • 更多模型正在开发中

快速使用

from torch_rechub.rmodels.ranking import WideDeep, DeepFM, DIN
from torch_rechub.trainers import CTRTrainer
from torch_rechub.basic.utils import DataGenerator

dg = DataGenerator(x, y)
train_dataloader, val_dataloader, test_dataloader = dg.generate_dataloader()

model = DeepFM(deep_features=deep_features, fm_features=fm_features, mlp_params={"dims": [256, 128], "dropout": 0.2, "activation": "relu"})

ctr_trainer = CTRTrainer(model)
ctr_trainer.fit(train_dataloader, val_dataloader)
auc = ctr_trainer.evaluate(ctr_trainer.model, test_dataloader)

多任务学习

from torch_rechub.models.multi_task import SharedBottom, ESMM, MMOE, PLE, AITM
from torch_rechub.trainers import MTLTrainer

model = MMOE(features, task_types, n_expert=3, expert_params={"dims": [64,32,16]}, tower_params_list=[{"dims": [8]}, {"dims": [8]}])

ctr_trainer = MTLTrainer(model)
ctr_trainer.fit(train_dataloader, val_dataloader)
auc = ctr_trainer.evaluate(ctr_trainer.model, test_dataloader)

Note:

所有模型均在大多数论文提及的多个知名公开数据集中测试，达到或者接近论文性能。

使用案例：Examples

每个数据集将会提供

  • 一个使用脚本，包含样本生成、模型训练与测试，并提供一套测评所用参数。
  • 一个预处理脚本，将原始数据进行预处理，转化成csv。
  • 数据格式参考文件（100条）。
  • 全量数据，统一的csv文件，提供高速网盘下载链接和原始数据链接。

初步规划TODO清单

Owner
Mincai Lai
Mincai Lai
GitHub Repository
This is the code for Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning

This is the code for Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning It includes /bert, which is the original BERT repos

Mitchell Gordon 11 Nov 15, 2022
Pytorch implementation of the paper SPICE: Semantic Pseudo-labeling for Image Clustering

SPICE: Semantic Pseudo-labeling for Image Clustering By Chuang Niu and Ge Wang This is a Pytorch implementation of the paper. (In updating) SOTA on 5

Chuang Niu 154 Dec 15, 2022
Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks

Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks Stable Neural ODE with Lyapunov-Stable Equilibrium

Kang Qiyu 8 Dec 12, 2022
Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"

About this repository This repo contains an Pytorch implementation for the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Netwo

wxDai 7 Oct 14, 2022
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics

FusionNet_Pytorch FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics Requirements Pytorch 0.1.11 Pyt

Choi Gunho 102 Dec 13, 2022
Perform zero-order Hankel Transform for an 1D array (float or real valued).

perform zero-order Hankel Transform for an 1D array (float or real valued). An discrete form of Parseval theorem is guaranteed. Suit for iterative problems.

1 Jan 17, 2022
ReferFormer - Official Implementation of ReferFormer

The official implementation of the paper: Language as Queries for Referring Vide

Jonas Wu 232 Dec 29, 2022
DNA sequence classification by Deep Neural Network

DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ

Mohammed Jawwadul Islam Fida 0 Aug 02, 2022
An SE(3)-invariant autoencoder for generating the periodic structure of materials

Crystal Diffusion Variational AutoEncoder This software implementes Crystal Diffusion Variational AutoEncoder (CDVAE), which generates the periodic st

Tian Xie 94 Dec 10, 2022
Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration

This repo is for the paper: Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration The DAC environment is based on the Dynam

Carola Doerr 1 Aug 19, 2022
NFT-Price-Prediction-CNN - Using visual feature extraction, prices of NFTs are predicted via CNN (Alexnet and Resnet) architectures.

NFT-Price-Prediction-CNN - Using visual feature extraction, prices of NFTs are predicted via CNN (Alexnet and Resnet) architectures.

5 Nov 03, 2022
Utilities and information for the signals.numer.ai tournament

dsignals Utilities and information for the signals.numer.ai tournament using eodhistoricaldata.com eodhistoricaldata.com provides excellent historical

Degerhan Usluel 23 Dec 18, 2022
This is the repository for CVPR2021 Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales

Intro This is the repository for CVPR2021 Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales Vehicle Sam

39 Jul 21, 2022
⚡ H2G-Net for Semantic Segmentation of Histopathological Images

H2G-Net This repository contains the code relevant for the proposed design H2G-Net, which was introduced in the manuscript "Hybrid guiding: A multi-re

André Pedersen 8 Nov 24, 2022
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation

Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation Introduction This is a PyTorch

XMed-Lab 30 Sep 23, 2022
FasterAI: A library to make smaller and faster models with FastAI.

Fasterai fasterai is a library created to make neural network smaller and faster. It essentially relies on common compression techniques for networks

Nathan Hubens 193 Jan 01, 2023
Key information extraction from invoice document with Graph Convolution Network

Key Information Extraction from Scanned Invoices Key information extraction from invoice document with Graph Convolution Network Related blog post fro

Phan Hoang 39 Dec 16, 2022
A list of all named GANs!

The GAN Zoo Every week, new GAN papers are coming out and it's hard to keep track of them all, not to mention the incredibly creative ways in which re

Avinash Hindupur 12.9k Jan 08, 2023
Over-the-Air Ensemble Inference with Model Privacy

Over-the-Air Ensemble Inference with Model Privacy This repository contains simulations for our private ensemble inference method. Installation Instal

Selim Firat Yilmaz 1 Jun 29, 2022
Implementation of "Debiasing Item-to-Item Recommendations With Small Annotated Datasets" (RecSys '20)

Debiasing Item-to-Item Recommendations With Small Annotated Datasets This is the code for our RecSys '20 paper. Other materials can be found here: Ful

Microsoft 34 Aug 10, 2022