test - taewook

'''
---taewook/test Auto Generate Code---
Author		: taewook
Project Name: test
Project Link: https://blockai.kr/taewook/test (BlockAI)
Create Date	: 2023-11-28

---Requirements---
# 사용자의 환경(OS, CUDA 등)에 따라 라이브러리 버전을 맞춰주세요
pip install torch==2.0 torchvision==0.15.2 torchtext==0.15.2 torchaudio==2.0.2
pip install pytorch-lightning==2.0.4
pip install tqdm
pip install pandas
pip install scikit-learn

---Folder Structure---
--📂 data
--📄 test.py
--📄 test.ipynb
--📄 requirements.txt
'''

import os
import argparse
import copy
import random
from glob import glob

from tqdm import tqdm
import numpy as np
import pandas as pd
from sklearn import preprocessing
from sklearn.model_selection import train_test_split

import torch
import pytorch_lightning as pl

path_sep = os.sep


# https://pytorch.org/tutorials/beginner/basics/data_tutorial.html#creating-a-custom-dataset-for-your-files
class Dataset(torch.utils.data.Dataset):
        pass


# https://pytorch-lightning.readthedocs.io/en/stable/extensions/datamodules.html
class Dataloader(pl.LightningDataModule):
        pass


# https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html
class Model(pl.LightningModule):
    def __init__(self):
        super().__init__()
        self.save_hyperparameters()
        pass


if __name__ == '__main__':
    # https://docs.python.org/ko/3/library/argparse.html
    # 하이퍼 파라미터 등 각종 설정값을 입력받습니다
    # 터미널 실행 예시 : python3 run.py --batch_size=64 ...
    # 실행 시 '--batch_size=64' 같은 인자를 입력하지 않으면 default 값이 기본으로 실행됩니다
    parser = argparse.ArgumentParser()
    parser.add_argument('--data_folder', default='data')
    parser.add_argument('--batch_size', default=3)
    parser.add_argument('--max_epoch', default=1)
    parser.add_argument('--shuffle', default=True)
    parser.add_argument('--train_ratio', default=0.99)
    args = parser.parse_args()

    dataloader = Dataloader(args.data_folder, args.batch_size, args.train_ratio, args.shuffle)
    model = Model()
    # https://pytorch-lightning.readthedocs.io/en/stable/common/trainer.html
    # 학습 및 추론을 위한 Trainer 설정
    trainer = pl.Trainer(accelerator='gpu', devices=1, max_epochs=args.max_epoch)
    trainer.fit(model=model, datamodule=dataloader)
    # trainer.test(model=model, datamodule=dataloader)
    # predictions = trainer.predict(model=model, datamodule=dataloader)