import csv

import json

import logging

import os

import pickle

import random

import numpy as np

import torch

""" TODO: update if necessary """

# path to the root project directory on the local machine

project_path = os.path.abspath(os.path.join(os.path.dirname(os.path.realpath(__file__)), os.pardir))

# project name, i.e., llemr

project_name = os.path.basename(project_path)

# path to the root project directory on the remote machine (default to local path)

remote_project_path = project_path

# path to the raw data directory on the remote machine

raw_data_path = os.path.join(remote_project_path, "raw_data")

# path to the processed data directory on the remote machine

processed_data_path = os.path.join(remote_project_path, "processed_data")

def set_seed(seed):

    random.seed(seed)

    np.random.seed(seed)

    torch.manual_seed(seed)

    if torch.cuda.is_available():

        torch.cuda.manual_seed(seed)

        torch.cuda.manual_seed_all(seed)

        torch.backends.cudnn.deterministic = True

        torch.backends.cudnn.benchmark = False

    os.environ["PYTHONHASHSEED"] = str(seed)

def read_csv(filename):

    logging.info(f"Reading from {filename}")

    data = []

    with open(filename, "r") as file:

        csv_reader = csv.DictReader(file, delimiter=",")

        for row in csv_reader:

            data.append(row)

    header = list(data[0].keys())

    return header, data

def read_txt(filename):

    logging.info(f"Reading from {filename}")

    data = []

    with open(filename, "r") as file:

        lines = file.read().splitlines()

        for line in lines:

            data.append(line)

    return data

def write_txt(filename, data):

    logging.info(f"Writing to {filename}")

    with open(filename, "w") as file:

        for line in data:

            file.write(line + "\n")

    return

def read_json(filename):

    logging.info(f"Reading from {filename}")

    with open(filename, "r") as file:

        data = json.load(file)

    return data

def write_json(filename, data):

    logging.info(f"Writing to {filename}")

    with open(filename, "w") as file:

        json.dump(data, file)

    return

def create_directory(directory):

    if not os.path.exists(directory):

        logging.info(f"Creating directory {directory}")

        os.makedirs(directory)

def load_pickle(filename):

    logging.info(f"Data loaded from {filename}")

    with open(filename, "rb") as f:

        return pickle.load(f)

def dump_pickle(data, filename):

    logging.info(f"Data saved to {filename}")

    with open(filename, "wb") as f:

        pickle.dump(data, f)

def count_parameters(model):

    return sum(p.numel() for p in model.parameters() if p.requires_grad)

if __name__ == "__main__":

    set_seed(0)

    print(project_path)

    print(project_name)

    print(remote_root)

    print(remote_project_path)

    print(raw_data_path)

    print(processed_data_path)