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from torch.utils.data import DataLoader
from torchio.data import UniformSampler
from torchio import SubjectsDataset, Queue, DATA
from torchio.utils import create_dummy_dataset
from ..utils import TorchioTestCase
class TestQueue(TorchioTestCase):
"""Tests for `queue` module."""
def setUp(self):
super().setUp()
self.subjects_list = create_dummy_dataset(
num_images=10,
size_range=(10, 20),
directory=self.dir,
suffix='.nii',
force=False,
)
def run_queue(self, num_workers, **kwargs):
subjects_dataset = SubjectsDataset(self.subjects_list)
patch_size = 10
sampler = UniformSampler(patch_size)
queue_dataset = Queue(
subjects_dataset,
max_length=6,
samples_per_volume=2,
sampler=sampler,
**kwargs,
_ = str(queue_dataset)
batch_loader = DataLoader(queue_dataset, batch_size=4)
for batch in batch_loader:
_ = batch['one_modality'][DATA]
_ = batch['segmentation'][DATA]
def test_queue(self):
self.run_queue(num_workers=0)
def test_queue_multiprocessing(self):
self.run_queue(num_workers=2)
def test_queue_no_start_background(self):
self.run_queue(num_workers=0, start_background=False)
fepegar /
torchio
