FLOPS min stride 32 (#2276)

utils/torch_utils.py

@@ -205,7 +205,7 @@ def model_info(model, verbose=False, img_size=640):
 
     try:  # FLOPS
         from thop import profile
-        stride = int(model.stride.max()) if hasattr(model, 'stride') else 32
+        stride = max(int(model.stride.max()), 32) if hasattr(model, 'stride') else 32
         img = torch.zeros((1, model.yaml.get('ch', 3), stride, stride), device=next(model.parameters()).device)  # input
         flops = profile(deepcopy(model), inputs=(img,), verbose=False)[0] / 1E9 * 2  # stride GFLOPS
         img_size = img_size if isinstance(img_size, list) else [img_size, img_size]  # expand if int/float