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

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
This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Motion .

ROSEFusion 🌹 This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Moti

219 Dec 27, 2022
How to Predict Stock Prices Easily Demo

How-to-Predict-Stock-Prices-Easily-Demo How to Predict Stock Prices Easily - Intro to Deep Learning #7 by Siraj Raval on Youtube ##Overview This is th

Siraj Raval 752 Nov 16, 2022
PyTorch Implementation for AAAI'21 "Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection"

UMS for Multi-turn Response Selection Implements the model described in the following paper Do Response Selection Models Really Know What's Next? Utte

Taesun Whang 47 Nov 22, 2022
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1

Baris Gecer 190 Dec 29, 2022
Source code for the paper "PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction" in ACL2021

PLOME:Pre-training with Misspelled Knowledge for Chinese Spelling Correction (ACL2021) This repository provides the code and data of the work in ACL20

197 Nov 26, 2022
Additional environments compatible with OpenAI gym

Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning A codebase for training reinforcement learning policies for quad

Zhehui Huang 40 Dec 06, 2022
Pytorch implementation of AREL

Status: Archive (code is provided as-is, no updates expected) Agent-Temporal Attention for Reward Redistribution in Episodic Multi-Agent Reinforcement

8 Nov 25, 2022
A PyTorch implementation of EfficientDet.

A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights

Ross Wightman 1.4k Jan 07, 2023
Code release for "Transferable Semantic Augmentation for Domain Adaptation" (CVPR 2021)

Transferable Semantic Augmentation for Domain Adaptation Code release for "Transferable Semantic Augmentation for Domain Adaptation" (CVPR 2021) Paper

66 Dec 16, 2022
A light-weight image labelling tool for Python designed for creating segmentation data sets.

An image labelling tool for creating segmentation data sets, for Django and Flask.

117 Nov 21, 2022
Code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning".

0. Introduction This repository contains the source code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning". Notes The netwo

NetX Group 68 Nov 24, 2022
YoHa - A practical hand tracking engine.

YoHa - A practical hand tracking engine.

2k Jan 06, 2023
LightningFSL: Pytorch-Lightning implementations of Few-Shot Learning models.

LightningFSL: Few-Shot Learning with Pytorch-Lightning In this repo, a number of pytorch-lightning implementations of FSL algorithms are provided, inc

Xu Luo 76 Dec 11, 2022
Classifying cat and dog images using Kaggle dataset

PyTorch Image Classification Classifies an image as containing either a dog or a cat (using Kaggle's public dataset), but could easily be extended to

Robert Coleman 74 Nov 22, 2022
Fairness Metrics: All you need to know

Fairness Metrics: All you need to know Testing machine learning software for ethical bias has become a pressing current concern. Recent research has p

Anonymous2020 1 Jan 17, 2022
A Lighting Pytorch Framework for Recommendation System, Easy-to-use and Easy-to-extend.

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

Mincai Lai 67 Jan 04, 2023
[NeurIPS 2021] Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples | ⛰️⚠️

Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples This repository is the official implementation of "Tow

Sungyoon Lee 4 Jul 12, 2022
Semantic Segmentation in Pytorch. Network include: FCN、FCN_ResNet、SegNet、UNet、BiSeNet、BiSeNetV2、PSPNet、DeepLabv3_plus、 HRNet、DDRNet

🚀 If it helps you, click a star! ⭐ Update log 2020.12.10 Project structure adjustment, the previous code has been deleted, the adjustment will be re-

Deeachain 269 Jan 04, 2023
Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗

urban_road_filter: a real-time LIDAR-based urban road and sidewalk detection algorithm for autonomous vehicles Dependency ROS (tested with Kinetic and

JKK - Vehicle Industry Research Center 180 Dec 12, 2022
Official implementation of the paper "AAVAE: Augmentation-AugmentedVariational Autoencoders"

AAVAE Official implementation of the paper "AAVAE: Augmentation-AugmentedVariational Autoencoders" Abstract Recent methods for self-supervised learnin

Grid AI Labs 48 Dec 12, 2022