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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)
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