utils.py

import os
import random
import math
import numpy as np
import pandas as pd 

import torch
from torch.nn import init


def set_seed(seed):
    # for reproducibility. 
    # note that pytorch is not completely reproducible 
    # https://pytorch.org/docs/stable/notes/randomness.html  
    torch.backends.cudnn.benchmark = False
    torch.backends.cudnn.deterministic = True
    random.seed(seed)
    os.environ['PYTHONHASHSEED'] = str(seed)
    np.random.seed(seed)
    torch.initial_seed() # dataloader multi processing 
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)
    torch.cuda.manual_seed_all(seed)
    return None


# https://github.com/sehkmg/tsvprint/blob/master/utils.py
def dict2tsv(res, file_name):
    if not os.path.exists(file_name):
        with open(file_name, 'a') as f:
            f.write('\t'.join(list(res.keys())))
            f.write('\n')

    with open(file_name, 'a') as f:
        f.write('\t'.join([str(r) for r in list(res.values())]))
        f.write('\n')