File size: 2,395 Bytes
ab8be8f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import multiprocessing
import time
import numpy as np
import pandas as pd
from torch.utils.data import Dataset, DataLoader
from qlib.rl.utils.data_queue import DataQueue
class DummyDataset(Dataset):
def __init__(self, length):
self.length = length
def __getitem__(self, index):
assert 0 <= index < self.length
return pd.DataFrame(np.random.randint(0, 100, size=(index + 1, 4)), columns=list("ABCD"))
def __len__(self):
return self.length
def _worker(dataloader, collector):
# for i in range(3):
for i, data in enumerate(dataloader):
collector.put(len(data))
def _queue_to_list(queue):
result = []
while not queue.empty():
result.append(queue.get())
return result
def test_pytorch_dataloader():
dataset = DummyDataset(100)
dataloader = DataLoader(dataset, batch_size=None, num_workers=1)
queue = multiprocessing.Queue()
_worker(dataloader, queue)
assert len(set(_queue_to_list(queue))) == 100
def test_multiprocess_shared_dataloader():
dataset = DummyDataset(100)
with DataQueue(dataset, producer_num_workers=1) as data_queue:
queue = multiprocessing.Queue()
processes = []
for _ in range(3):
processes.append(multiprocessing.Process(target=_worker, args=(data_queue, queue)))
processes[-1].start()
for p in processes:
p.join()
assert len(set(_queue_to_list(queue))) == 100
def test_exit_on_crash_finite():
def _exit_finite():
dataset = DummyDataset(100)
with DataQueue(dataset, producer_num_workers=4) as data_queue:
time.sleep(3)
raise ValueError
# https://stackoverflow.com/questions/34506638/how-to-register-atexit-function-in-pythons-multiprocessing-subprocess
process = multiprocessing.Process(target=_exit_finite)
process.start()
process.join()
def test_exit_on_crash_infinite():
def _exit_infinite():
dataset = DummyDataset(100)
with DataQueue(dataset, repeat=-1, queue_maxsize=100) as data_queue:
time.sleep(3)
raise ValueError
process = multiprocessing.Process(target=_exit_infinite)
process.start()
process.join()
if __name__ == "__main__":
test_multiprocess_shared_dataloader()
|