✅ [Pass] pytest of new structure

tests/test_model/test_yolo.py

@@ -1,20 +1,20 @@
 import sys
+from pathlib import Path
 
-import pytest
 import torch
 from hydra import compose, initialize
-from hydra.core.global_hydra import GlobalHydra
-from omegaconf import DictConfig, OmegaConf
+from omegaconf import OmegaConf
 
-sys.path.append("./")
-from model.yolo import YOLO, get_model
+project_root = Path(__file__).resolve().parent.parent.parent
+sys.path.append(str(project_root))
 
-config_path = "../../config/model"
+from yolo.model.yolo import YOLO, get_model
+
+config_path = "../../yolo/config/model"
 config_name = "v7-base"
 
 
 def test_build_model():
-
     with initialize(config_path=config_path, version_base=None):
         model_cfg = compose(config_name=config_name)
         OmegaConf.set_struct(model_cfg, False)

tests/test_utils/test_dataaugment.py

@@ -1,12 +1,15 @@
 import sys
+from pathlib import Path
 
 import pytest
 import torch
 from PIL import Image
 from torchvision.transforms import functional as TF
 
-sys.path.append("./")
-from utils.data_augment import Compose, HorizontalFlip, Mosaic, VerticalFlip
+project_root = Path(__file__).resolve().parent.parent.parent
+sys.path.append(str(project_root))
+
+from yolo.utils.data_augment import Compose, HorizontalFlip, Mosaic, VerticalFlip
 
 
 def test_horizontal_flip():

tests/test_utils/test_loss.py

@@ -0,0 +1,41 @@
+import sys
+from pathlib import Path
+
+import pytest
+import torch
+from hydra import compose, initialize
+
+project_root = Path(__file__).resolve().parent.parent.parent
+sys.path.append(str(project_root))
+
+from yolo.utils.loss import YOLOLoss
+
+
+@pytest.fixture
+def cfg():
+    with initialize(config_path="../../yolo/config", version_base=None):
+        cfg = compose(config_name="config")
+    return cfg
+
+
+@pytest.fixture
+def loss_function(cfg) -> YOLOLoss:
+    return YOLOLoss(cfg)
+
+
+@pytest.fixture
+def data():
+    [[torch.zeros]]
+    targets = torch.zeros(20, 6, device=torch.device("cuda"))
+    predicts = [
+        [torch.zeros(1, 144, 80 // i, 80 // i, device=torch.device("cuda")) for i in [1, 2, 4]] for _ in range(2)
+    ]
+    return predicts, targets
+
+
+def test_yolo_loss(loss_function, data):
+    predicts, targets = data
+    loss_iou, loss_dfl, loss_cls = loss_function(predicts, targets)
+    assert torch.isnan(loss_iou)
+    assert torch.isnan(loss_dfl)
+    assert torch.isinf(loss_cls)