torch.empty() for speed improvements (#9025)

`torch.empty()` for speed improvement

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

models/common.py

@@ -531,7 +531,7 @@ class DetectMultiBackend(nn.Module):
         # Warmup model by running inference once
         warmup_types = self.pt, self.jit, self.onnx, self.engine, self.saved_model, self.pb
         if any(warmup_types) and self.device.type != 'cpu':
-            im = torch.zeros(*imgsz, dtype=torch.half if self.fp16 else torch.float, device=self.device)  # input
+            im = torch.empty(*imgsz, dtype=torch.half if self.fp16 else torch.float, device=self.device)  # input
             for _ in range(2 if self.jit else 1):  #
                 self.forward(im)  # warmup
 
@@ -600,7 +600,7 @@ class AutoShape(nn.Module):
 
         dt = (Profile(), Profile(), Profile())
         with dt[0]:
-            p = next(self.model.parameters()) if self.pt else torch.zeros(1, device=self.model.device)  # param
+            p = next(self.model.parameters()) if self.pt else torch.empty(1, device=self.model.device)  # param
             autocast = self.amp and (p.device.type != 'cpu')  # Automatic Mixed Precision (AMP) inference
             if isinstance(ims, torch.Tensor):  # torch
                 with amp.autocast(autocast):