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
Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data 🌈

Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat

Dominik Schmidt 31 Dec 21, 2022
Paper Title: Heterogeneous Knowledge Distillation for Simultaneous Infrared-Visible Image Fusion and Super-Resolution

HKDnet Paper Title: "Heterogeneous Knowledge Distillation for Simultaneous Infrared-Visible Image Fusion and Super-Resolution" Email:

wasteland 11 Nov 12, 2022
Train DeepLab for Semantic Image Segmentation

Train DeepLab for Semantic Image Segmentation Martin Kersner, [email protected]

Martin Kersner 172 Dec 14, 2022
PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility

PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility Jae Yong Lee, Joseph DeGol, Chuhang Zou, Derek Hoiem Installation To install nece

31 Apr 19, 2022
PyTorch code for the ICCV'21 paper: "Always Be Dreaming: A New Approach for Class-Incremental Learning"

Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning PyTorch code for the ICCV 2021 paper: Always Be Dreaming: A New Approach f

49 Dec 21, 2022
SCAAML is a deep learning framwork dedicated to side-channel attacks run on top of TensorFlow 2.x.

SCAAML (Side Channel Attacks Assisted with Machine Learning) is a deep learning framwork dedicated to side-channel attacks. It is written in python and run on top of TensorFlow 2.x.

Google 69 Dec 21, 2022
Dados coletados e programas desenvolvidos no processo de iniciação científica

Iniciacao_cientifica_FAPESP_2020-14845-6 Dados coletados e programas desenvolvidos no processo de iniciação científica Os arquivos .py são os programa

1 Jan 10, 2022
Implementation for the paper SMPLicit: Topology-aware Generative Model for Clothed People (CVPR 2021)

SMPLicit: Topology-aware Generative Model for Clothed People [Project] [arXiv] License Software Copyright License for non-commercial scientific resear

Enric Corona 225 Dec 13, 2022
Revealing and Protecting Labels in Distributed Training

Revealing and Protecting Labels in Distributed Training

Google Interns 0 Nov 09, 2022
Application of K-means algorithm on a music dataset after a dimensionality reduction with PCA

PCA for dimensionality reduction combined with Kmeans Goal The Goal of this notebook is to apply a dimensionality reduction on a big dataset in order

Arturo Ghinassi 0 Sep 17, 2022
ZeroGen: Efficient Zero-shot Learning via Dataset Generation

ZEROGEN This repository contains the code for our paper “ZeroGen: Efficient Zero

Jiacheng Ye 31 Dec 30, 2022
Learning Features with Parameter-Free Layers (ICLR 2022)

Learning Features with Parameter-Free Layers (ICLR 2022) Dongyoon Han, YoungJoon Yoo, Beomyoung Kim, Byeongho Heo | Paper NAVER AI Lab, NAVER CLOVA Up

NAVER AI 65 Dec 07, 2022
UCSD Oasis platform

oasis UCSD Oasis platform Local project setup Install Docker Compose and make sure you have Pip installed Clone the project and go to the project fold

InSTEDD 4 Jun 16, 2021
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.

Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras. Implementation of various Deep Image Segmentation mo

Divam Gupta 2.6k Jan 05, 2023
Implementation for Panoptic-PolarNet (CVPR 2021)

Panoptic-PolarNet This is the official implementation of Panoptic-PolarNet. [ArXiv paper] Introduction Panoptic-PolarNet is a fast and robust LiDAR po

Zixiang Zhou 126 Jan 01, 2023
计算机视觉中用到的注意力模块和其他即插即用模块PyTorch Implementation Collection of Attention Module and Plug&Play Module

PyTorch实现多种计算机视觉中网络设计中用到的Attention机制,还收集了一些即插即用模块。由于能力有限精力有限,可能很多模块并没有包括进来,有任何的建议或者改进,可以提交issue或者进行PR。

PJDong 599 Dec 23, 2022
🕺Full body detection and tracking

Pose-Detection 🤔 Overview Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign

Abbas Ataei 20 Nov 21, 2022
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p

Yu Meng 60 Dec 30, 2022
3ds-Ghidra-Scripts - Ghidra scripts to help with 3ds reverse engineering

3ds Ghidra Scripts These are ghidra scripts to help with 3ds reverse engineering

Zak 7 May 23, 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