zredlined / timegan-pytorch

This repository holds the code for the reimplementation of TimeGAN (Yoon et al., NIPS2019) using PyTorch

timegan-pytorch

This repository holds the code for the reimplementation of TimeGAN (Yoon et al., NIPS2019) using PyTorch. Some of the code was derived from the original implementation here.

Getting Started

Installing Requirements

This implementation assumes Python3.8 and a Linux environment with a GPU is used.

cat requirements.txt | xargs -n 1 pip install --upgrade

Directory Hierarchy

data/                         # the folder holding the datasets and preprocessing files
  ├ data_preprocessing.py     # the data preprocessing functions
  └ stock.csv                 # the example stock data derived from the original repo
metrics/                      # the folder holding the metric functions for evaluating the model
  ├ dataset.py                # the dataset class for feature predicting and one-step ahead predicting
  ├ general_rnn.py            # the model for fitting the dataset during TSTR evaluation
  ├ metric_utils.py           # the main function for evaluating TSTR
  └ visualization.py          # PCA and t-SNE implementation for time series taken from the original repo
models/                       # the code for the model
output/                       # the output of the model
main.py                       # the main code for training and evaluating TSTR of the model
requirements.txt              # requirements for running code
run.sh                        # the bash script for running model
visualization.ipynb           # jupyter notebook for running visualization of original and synthetic data