def set_logging(opt):
    """
    Generate the folder in which everything is saved.
    If opt.savename is given, folder will take on said name.
    If not, a name based on the start time is provided.
    If the folder already exists, it will by iterated until it can be created without
    deleting existing data.
    The current opt.save_path will be extended to account for the new save_folder name.

    Args:
        opt: argparse.Namespace, contains all training-specific parameters.
    Returns:
        Nothing!
    """
    checkfolder = opt.save_path + "/" + str(opt.iter)

    # Create start-time-based name if opt.savename is not give.
    if opt.savename == "":
        date = datetime.datetime.now()
        checkfolder = opt.save_path + "/" + str(opt.iter)

    # If folder already exists, iterate over it until is doesn't.
    # counter     = 1
    # while os.path.exists(checkfolder):
    #     checkfolder = opt.save_path+'/'+opt.savename+'_'+str(counter)
    #     counter += 1

    # Create Folder
    if not os.path.exists(checkfolder):
        os.makedirs(checkfolder)
    opt.save_path = checkfolder

    # Store training parameters as text and pickle in said folder.
    with open(opt.save_path + "/Parameter_Info.txt", "w") as f:
        f.write(gimme_save_string(opt))
    pkl.dump(opt, open(opt.save_path + "/hypa.pkl", "wb"))

    Generate the folder in which everything is saved.
    If opt.savename is given, folder will take on said name.
    If not, a name based on the start time is provided.
    If the folder already exists, it will by iterated until it can be created without
    deleting existing data.
    The current opt.save_path will be extended to account for the new save_folder name.

    Args:
        opt: argparse.Namespace, contains all training-specific parameters.
    Returns:
        Nothing!
    
examples/pytorch/hilander/PSS/Smooth_AP/src/auxiliaries.py