Fixed RTDETR GFLOPs bug (#7309)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/utils/torch_utils.py

@@ -274,16 +274,26 @@ def model_info_for_loggers(trainer):
 
 def get_flops(model, imgsz=640):
     """Return a YOLO model's FLOPs."""
+    if not thop:
+        return 0.0  # if not installed return 0.0 GFLOPs
+
     try:
         model = de_parallel(model)
         p = next(model.parameters())
-        stride = max(int(model.stride.max()), 32) if hasattr(model, 'stride') else 32  # max stride
-        im = torch.empty((1, p.shape[1], stride, stride), device=p.device)  # input image in BCHW format
-        flops = thop.profile(deepcopy(model), inputs=[im], verbose=False)[0] / 1E9 * 2 if thop else 0  # stride GFLOPs
-        imgsz = imgsz if isinstance(imgsz, list) else [imgsz, imgsz]  # expand if int/float
-        return flops * imgsz[0] / stride * imgsz[1] / stride  # 640x640 GFLOPs
+        if not isinstance(imgsz, list):
+            imgsz = [imgsz, imgsz]  # expand if int/float
+        try:
+            # Use stride size for input tensor
+            stride = max(int(model.stride.max()), 32) if hasattr(model, 'stride') else 32  # max stride
+            im = torch.empty((1, p.shape[1], stride, stride), device=p.device)  # input image in BCHW format
+            flops = thop.profile(deepcopy(model), inputs=[im], verbose=False)[0] / 1E9 * 2  # stride GFLOPs
+            return flops * imgsz[0] / stride * imgsz[1] / stride  # imgsz GFLOPs
+        except Exception:
+            # Use actual image size for input tensor (i.e. required for RTDETR models)
+            im = torch.empty((1, p.shape[1], *imgsz), device=p.device)  # input image in BCHW format
+            return thop.profile(deepcopy(model), inputs=[im], verbose=False)[0] / 1E9 * 2  # imgsz GFLOPs
     except Exception:
-        return 0
+        return 0.0
 
 
 def get_flops_with_torch_profiler(model, imgsz=640):