misc.py

import json
import os
import random
from datetime import date

import numpy as np
import torch
import torch.backends.cudnn as cudnn


def _get_experiment_index(experiment_path):
    idx = 0
    while os.path.exists(experiment_path + "_" + str(idx)):
        idx += 1
    return idx


def create_experiment_export_folder(args):
    experiment_dir, experiment_description = args.experiment_dir, args.experiment_description
    if not os.path.exists(experiment_dir):
        os.mkdir(experiment_dir)
    experiment_path = get_name_of_experiment_path(experiment_dir, experiment_description)
    print(os.path.abspath(experiment_path))
    os.mkdir(experiment_path)
    print("folder created: " + os.path.abspath(experiment_path))
    return experiment_path


def export_experiments_config_as_json(args, experiment_path):
    with open(os.path.join(experiment_path, 'config.json'), 'w') as outfile:
        json.dump(vars(args), outfile, indent=2)


def get_name_of_experiment_path(experiment_dir, experiment_description):
    experiment_path = os.path.join(experiment_dir, (experiment_description + "_" + str(date.today())))
    idx = _get_experiment_index(experiment_path)
    experiment_path = experiment_path + "_" + str(idx)
    return experiment_path


def fix_random_seed_as(random_seed):
    if random_seed == -1:
        random_seed = np.random.randint(100000)
        print("RANDOM SEED: {}".format(random_seed))

    random.seed(random_seed)
    torch.manual_seed(random_seed)
    torch.cuda.manual_seed_all(random_seed)
    np.random.seed(random_seed)
    cudnn.deterministic = True
    cudnn.benchmark = False


def set_up_gpu(args):
    os.environ['CUDA_VISIBLE_DEVICES'] = args.device_idx
    args.num_gpu = len(args.device_idx.split(","))
    args.device = 'cuda' if torch.cuda.is_available() else 'cpu'