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Change from concurrent.futures to multiprocessing #354

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Change from concurrent.futures to multiprocessing #354

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18 changes: 14 additions & 4 deletions libmultilabel/nn/data_utils.py
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Original file line number Diff line number Diff line change
@@ -1,8 +1,10 @@
import csv
import gc
import logging
import multiprocessing as mp
import os
import warnings
from concurrent.futures import ProcessPoolExecutor
from math import sqrt, floor

import pandas as pd
import torch
Expand Down Expand Up @@ -176,9 +178,17 @@ def _load_raw_data(data, is_test=False, tokenize_text=True, remove_no_label_data

data["label"] = data["label"].astype(str).map(lambda s: s.split())
if tokenize_text:
# multiprocessing requires serializable objects
with ProcessPoolExecutor() as executor:
data["text"] = pd.Series(tqdm(executor.map(tokenize, data["text"]), total=len(data["text"])))
# fork is the fastest start method
start_method = "fork"
if start_method in mp.get_all_start_methods():
cpu_count = len(os.sched_getaffinity(0)) if hasattr(os, "sched_getaffinity") else os.cpu_count()
processes = floor(sqrt(cpu_count))
with mp.get_context(start_method).Pool(processes=processes) as p:
# imap has worse performance compared to map
# tqdm should not be used as map blocks the main process
data["text"] = pd.Series(p.map(tokenize, data["text"]))
else:
data["text"] = data["text"].map(tokenize)
data = data.to_dict("records")
if not is_test:
num_no_label_data = sum(1 for d in data if len(d["label"]) == 0)
Expand Down