MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets
Introduction
MTReclib provides a PyTorch implementation of multi-task recommendation models and common datasets. Currently, we implmented 7 multi-task recommendation models to enable fair comparison and boost the development of multi-task recommendation algorithms. The currently supported algorithms include:
Datasets
For the processed dataset, you should directly put the dataset in ‘./data/’ and unpack it. For the original dataset, you should put it in ‘./data/’ and run ‘python preprocess.py –dataset_name NL’.
Requirements
- Python 3.6
- PyTorch > 1.10
- pandas
- numpy
- tqdm
Run
Parameter Configuration:
- dataset_name: choose a dataset in [‘AliExpress_NL’, ‘AliExpress_FR’, ‘AliExpress_ES’, ‘AliExpress_US’], default for
AliExpress_NL - dataset_path: default for
./data - model_name: choose a model in [‘singletask’, ‘sharedbottom’, ‘omoe’, ‘mmoe’,