zero-mAP fix 3 (ultralytics#9058)

* zero-mAP fix 3

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

* Update torch_utils.py

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

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update torch_utils.py

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

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

utils/torch_utils.py

@@ -412,7 +412,6 @@ def __init__(self, model, decay=0.9999, tau=2000, updates=0):
         for p in self.ema.parameters():
             p.requires_grad_(False)
 
-    @smart_inference_mode()
     def update(self, model):
         # Update EMA parameters
         self.updates += 1
@@ -423,7 +422,7 @@ def update(self, model):
             if v.dtype.is_floating_point:  # true for FP16 and FP32
                 v *= d
                 v += (1 - d) * msd[k].detach()
-        assert v.dtype == msd[k].dtype == torch.float32, f'EMA {v.dtype} and model {msd[k]} must be updated in FP32'
+        assert v.dtype == msd[k].detach().dtype == torch.float32, f'EMA {v.dtype} and model {msd[k]} must both be FP32'
 
     def update_attr(self, model, include=(), exclude=('process_group', 'reducer')):
         # Update EMA attributes