Move tests outside package (#104)

tests/test_model.py

@@ -0,0 +1,73 @@
+import torch
+
+from ultralytics.yolo import YOLO
+
+
+def test_model_forward():
+    model = YOLO()
+    model.new("yolov8n-seg.yaml")
+    img = torch.rand(512 * 512 * 3).view(1, 3, 512, 512)
+    model.forward(img)
+    model(img)
+
+
+def test_model_info():
+    model = YOLO()
+    model.new("yolov8n.yaml")
+    model.info()
+    model.load("balloon-detect.pt")
+    model.info(verbose=True)
+
+
+def test_model_fuse():
+    model = YOLO()
+    model.new("yolov8n.yaml")
+    model.fuse()
+    model.load("balloon-detect.pt")
+    model.fuse()
+
+
+def test_visualize_preds():
+    model = YOLO()
+    model.load("balloon-segment.pt")
+    model.predict(source="ultralytics/assets")
+
+
+def test_val():
+    model = YOLO()
+    model.load("balloon-segment.pt")
+    model.val(data="coco128-seg.yaml", imgsz=32)
+
+
+def test_model_resume():
+    model = YOLO()
+    model.new("yolov8n-seg.yaml")
+    model.train(epochs=1, imgsz=32, data="coco128-seg.yaml")
+    try:
+        model.resume(task="segment")
+    except AssertionError:
+        print("Successfully caught resume assert!")
+
+
+def test_model_train_pretrained():
+    model = YOLO()
+    model.load("balloon-detect.pt")
+    model.train(data="coco128.yaml", epochs=1, imgsz=32)
+    model.new("yolov8n.yaml")
+    model.train(data="coco128.yaml", epochs=1, imgsz=32)
+    img = torch.rand(512 * 512 * 3).view(1, 3, 512, 512)
+    model(img)
+
+
+def test():
+    test_model_forward()
+    test_model_info()
+    test_model_fuse()
+    test_visualize_preds()
+    test_val()
+    test_model_resume()
+    test_model_train_pretrained()
+
+
+if __name__ == "__main__":
+    test()