Refactor for simplification (#9054)

* Refactor for simplification

* cleanup

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

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

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

utils/torch_utils.py

@@ -45,11 +45,10 @@ def smart_inference_mode(torch_1_9=check_version(torch.__version__, '1.9.0')):
 def smartCrossEntropyLoss(label_smoothing=0.0):
     # Returns nn.CrossEntropyLoss with label smoothing enabled for torch>=1.10.0
     if check_version(torch.__version__, '1.10.0'):
-        return nn.CrossEntropyLoss(label_smoothing=label_smoothing)  # loss function
-    else:
-        if label_smoothing > 0:
-            LOGGER.warning(f'WARNING: label smoothing {label_smoothing} requires torch>=1.10.0')
-        return nn.CrossEntropyLoss()  # loss function
+        return nn.CrossEntropyLoss(label_smoothing=label_smoothing)
+    if label_smoothing > 0:
+        LOGGER.warning(f'WARNING: label smoothing {label_smoothing} requires torch>=1.10.0')
+    return nn.CrossEntropyLoss()
 
 
 def smart_DDP(model):
@@ -118,7 +117,7 @@ def select_device(device='', batch_size=0, newline=True):
         assert torch.cuda.is_available() and torch.cuda.device_count() >= len(device.replace(',', '')), \
             f"Invalid CUDA '--device {device}' requested, use '--device cpu' or pass valid CUDA device(s)"
 
-    if not (cpu or mps) and torch.cuda.is_available():  # prefer GPU if available
+    if not cpu and not mps and torch.cuda.is_available():  # prefer GPU if available
         devices = device.split(',') if device else '0'  # range(torch.cuda.device_count())  # i.e. 0,1,6,7
         n = len(devices)  # device count
         if n > 1 and batch_size > 0:  # check batch_size is divisible by device_count