File size: 1,725 Bytes
07fcdfe | 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 | import unittest
import torch
torch.set_num_threads(4)
from pdgrapher import Dataset
import torch
import os
torch.set_num_threads(5)
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
class TestDataset(unittest.TestCase):
def test_single_fold(self):
# test creation
dataset = Dataset(
forward_path="data/processed/torch_data/real_lognorm/data_forward_A549.pt",
backward_path="data/processed/torch_data/real_lognorm/data_backward_A549.pt",
splits_path="data/splits/genetic/A549/random/1fold/splits.pt"
)
# test dataloaders
dataloaders = dataset.get_dataloaders()
self.assertEqual(len(dataloaders), 6)
def test_multiple_folds(self):
# test creation
dataset = Dataset(
forward_path="data/processed/torch_data/real_lognorm/data_forward_A549.pt",
backward_path="data/processed/torch_data/real_lognorm/data_backward_A549.pt",
splits_path="data/splits/genetic/A549/random/5fold/splits.pt",
)
# test dataloaders for all folds
for fold_idx in range(1, dataset.num_of_folds + 1):
dataset.prepare_fold(fold_idx)
dataloaders = dataset.get_dataloaders()
self.assertEqual(len(dataloaders), 6)
# test invalid fold_idx
with self.assertRaises(ValueError):
dataset.prepare_fold(-1)
with self.assertRaises(ValueError):
dataset.prepare_fold(1.2)
with self.assertRaises(ValueError):
dataset.prepare_fold(dataset.num_of_folds+1)
if __name__ == "__main__":
unittest.TestLoader.sortTestMethodsUsing = None
unittest.main()
|