EMA FP32 assert classification bug fix (#9016)

* Return EMA float on classification val

* verbose val fix

* EMA check

utils/torch_utils.py

@@ -408,8 +408,6 @@ class ModelEMA:
     def __init__(self, model, decay=0.9999, tau=2000, updates=0):
         # Create EMA
         self.ema = deepcopy(de_parallel(model)).eval()  # FP32 EMA
-        # if next(model.parameters()).device.type != 'cpu':
-        #     self.ema.half()  # FP16 EMA
         self.updates = updates  # number of EMA updates
         self.decay = lambda x: decay * (1 - math.exp(-x / tau))  # decay exponential ramp (to help early epochs)
         for p in self.ema.parameters():
@@ -423,9 +421,10 @@ class ModelEMA:
 
         msd = de_parallel(model).state_dict()  # model state_dict
         for k, v in self.ema.state_dict().items():
-            if v.dtype.is_floating_point:
+            if v.dtype.is_floating_point:  # true for FP16 and FP32
                 v *= d
-                v += (1 - d) * msd[k].detach()
+                v += (1 - d) * msd[k]
+        assert v.dtype == msd[k].dtype == torch.float32, f'EMA {v.dtype} and model {msd[k]} must be updated in FP32'
 
     def update_attr(self, model, include=(), exclude=('process_group', 'reducer')):
         # Update EMA attributes