DETSMCL

This repository contains the official implementation for the paper: Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning.

Requirements

The recommended requirements for DETSMCL are specified as follows:

• Python 3.6/3.8
• torch==1.10.3
• torchvision==0.11.2
• scikit_learn==0.24.2
• scipy==1.6.1
• numpy==1.21.5
• numpy-base==1.23.5
• pandas==1.0.1
• Bottleneck==1.3.1

The dependencies can be installed by:

pip install -r requirements.txt

Data

The datasets can be obtained and put into datasets/ folder in the following way:

• 3 ETT datasets should be placed at datasets/ETTh1.csv, datasets/ETTh2.csv and datasets/ETTm1.csv.
• Electricity dataset should be preprocessed using datasets/preprocess_electricity.py and placed at datasets/electricity.csv.

Usage

To train and evaluate DETSMCL on a dataset, run the following command:

python train.py <dataset_name> <run_name> --loader <loader> --batch-size <batch_size> --repr-dims <repr_dims> --gpu <gpu> --eval