| import os | |
| import math | |
| import json | |
| import argparse | |
| import subprocess | |
| from collections import OrderedDict | |
| from new_to_old_format_data_path import output_sampling_probs_new_format | |
| SPLIT = [0, 0.949, 0.999, 1.0] | |
| def calc_multinomial_sampling_prob_with_penalty(dataset_size, alpha=.5): | |
| """ | |
| Calculate multinomial probability distribution based on https://arxiv.org/pdf/1901.07291.pdf (section 3.1) | |
| :dataset_size: A dictionary contains the size (value) of each of the language (key). | |
| """ | |
| tot_size = 0 | |
| probs = OrderedDict() | |
| for lang, size in dataset_size.items(): | |
| tot_size += size | |
| for lang, size in dataset_size.items(): | |
| probs[lang] = size / tot_size | |
| pen_prob = OrderedDict() | |
| tot_pen_prob = 0.0 | |
| for lang, prob in probs.items(): | |
| tot_pen_prob += (prob ** alpha) | |
| sum_ = 0.0 | |
| for lang, prob in probs.items(): | |
| pen_prob[lang] = (prob ** alpha) / tot_pen_prob | |
| sum_ += pen_prob[lang] | |
| assert math.fabs(1 - sum_) < 1e-6 | |
| return pen_prob | |
| def get_size_stats(args): | |
| """ | |
| Calculate size for each of the iterator. | |
| It recusively iterate though a directory to find a specific extension file and report their size in preferred format. | |
| """ | |
| lang_size_dict = {} | |
| for (dirpath, dirnames, filenames) in os.walk(args.data_folder_path): | |
| for filename in filenames: | |
| if not (filename.startswith(args.name_prefix) and filename.endswith(args.extension_name)): | |
| continue | |
| full_file_path = os.path.join(dirpath, filename) | |
| lang_size = subprocess.check_output("du -s {}".format(full_file_path), shell=True) | |
| lang_size = int(lang_size.decode("utf-8").split("\t")[0]) | |
| if args.size_format == 'KB': | |
| _conv = 1 | |
| elif args.size_format == 'MB': | |
| _conv = 1024 | |
| elif args.size_format == 'GB': | |
| _conv = 1024 * 1024 | |
| elif args.size_format == 'TB': | |
| _conv = 1024 * 1024 * 1024 | |
| lang_size_ = round(lang_size / float(_conv), 2) | |
| lang_size_dict[full_file_path] = lang_size_ | |
| return lang_size_dict | |
| def print_stat(args, lang_size_dict, value_name='size'): | |
| """ | |
| Print size statistics. | |
| """ | |
| lang_list = sorted([(k, v) for k, v in lang_size_dict.items()], key=lambda tup: tup[1]) | |
| total_size = 0 | |
| print("\nLanguage : ({})".format(value_name)) | |
| print("-" * 20) | |
| for lang, size in lang_list: | |
| print("{} : {}".format(lang, size)) | |
| total_size += size | |
| print("-" * 20) | |
| print("Total size : {}".format(total_size)) | |
| def removesuffix(string, suffix): | |
| if string.endswith(suffix): | |
| string = string[:-len(suffix)] | |
| return string | |
| def main(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--data-folder-path', type=str, required=True, | |
| help='Path to the data folder') | |
| parser.add_argument('--size-format', type=str, required=True, | |
| help='Calculation will be done in byte, mega-byte, giga-byte or tera-byte', | |
| choices=['KB', 'MB', 'GB', 'TB']) | |
| parser.add_argument('--alpha', type=float, required=True, | |
| help='Sampling penalty.') | |
| parser.add_argument('--output-dir', type=str, required=True, | |
| help='Output directory where sampling prob_dict will be saved.') | |
| parser.add_argument('--name-prefix', type=str, required=True, | |
| help='File name prefix to match. Combination of `--name-prefix` and --extension-name will be used to select file.') | |
| parser.add_argument('--extension-name', type=str, required=True, | |
| help='Extension of the file to match. Combination of `--name-prefix` and --extension-name will be used to select file') | |
| parser.add_argument('--old-format', action="store_true", | |
| help='Legacy option') | |
| args = parser.parse_args() | |
| size_dict = get_size_stats(args) | |
| print_stat(args, size_dict, value_name=args.size_format) | |
| sampling_probability = calc_multinomial_sampling_prob_with_penalty( | |
| size_dict, alpha=args.alpha | |
| ) | |
| print_stat(args, sampling_probability, 'probability') | |
| total_contrib = 0 | |
| print("\nLanguage : Per epoch contribution in {}".format(args.size_format)) | |
| print("-" * 50) | |
| for lang, prob in sampling_probability.items(): | |
| sampling_probability[lang] = (prob, size_dict[lang]) | |
| lang_contrib_size = round(size_dict[lang] * prob, 2) | |
| print("{} : {} ({} -> {})".format(lang, prob, size_dict[lang], lang_contrib_size)) | |
| total_contrib += lang_contrib_size | |
| print("-" * 50) | |
| print("Total size : {}".format(total_contrib)) | |
| open(os.path.join(args.output_dir, 'iterator_selection_prob.{}.json'.format(args.alpha)), "w").write( | |
| json.dumps(sampling_probability, indent=4) | |
| ) | |
| if args.old_format: | |
| with open(os.path.join(args.output_dir, "dataset_probabilities.{}.txt".format(args.alpha)), "w") as fout: | |
| fout.write( | |
| " ".join([f"{prob[0]} {removesuffix(path, '.bin')}" for path, prob in sampling_probability.items()])) | |
| pass | |
| else: | |
| output_sampling_probs_new_format(sampling_probability, args.output_dir, args.alpha) | |
| if __name__ == '__main__': | |
| main() | |