train_valid_split.py

import os
import json
import tqdm
import functools
import collections
import multiprocessing


def extract_domains(filename):
    domains = set()
    with open(filename) as f:
        for line in f:
            line = json.loads(line.strip())
            domains.add(line["domain"])
    return filename, list(domains)


def valid_train_split(filename, mapping=None):
    previous_domain = ""
    train = []
    valid = []
    domain_data = {"questions": [], "pages": set()}
    counter = 0
    with open(filename) as f:
        for line_txt in f:
            counter += 1
            line = json.loads(line_txt.strip())
            domain = line["domain"]
            if domain != previous_domain and previous_domain != "":
                if len(mapping[previous_domain]) > 1:
                    train.extend(domain_data["questions"])
                elif len(valid) > 2000:
                    train.extend(domain_data["questions"])
                elif len(domain_data["pages"]) > 1:
                    train.extend(domain_data["questions"])
                elif len(domain_data["questions"]) < 15:
                    train.extend(domain_data["questions"])
                else:
                    valid.extend(domain_data["questions"])
                domain_data = {"questions": [], "pages": set()}
            domain_data["questions"].append(line_txt.strip())
            domain_data["pages"].add(line["domain_index"])
            previous_domain = domain
        train.extend(domain_data["questions"])
    assert len(train) + len(valid) == counter
    return train, valid, filename


data = [f"data/{e}" for e in os.listdir("data") if e.endswith(".json")]
with multiprocessing.Pool(os.cpu_count()) as p:
    domain_count = collections.defaultdict(list)
    for filename, domains in tqdm.tqdm(p.imap_unordered(extract_domains, data)):
        language = filename.split(".")[1]
        for domain in domains:
            domain_count[domain].append(language)


with multiprocessing.Pool(os.cpu_count()) as p:
    fn = functools.partial(valid_train_split, mapping=domain_count)
    for train, valid, filename in tqdm.tqdm(p.imap_unordered(fn, data)):
        train_filename = filename.replace("data/", "data/train/")
        with open(train_filename, "w+") as f:
            train = "\n".join(train)
            f.write(train) 
        valid_filename = filename.replace("data/", "data/valid/")
        with open(valid_filename, "w+") as f:
            valid = "\n".join(valid)
            f.write(valid)