yolov3 and tacotron2: add support for xpu devices

torchbenchmark/models/tacotron2/train_tacotron2.py

@@ -71,7 +71,15 @@ def prepare_directories_and_logger(output_directory, log_directory, rank):
 
 
 def load_model(hparams):
-    model = Tacotron2(hparams).cuda()
+    use_xpu =  torch.xpu.is_available()
+    use_cuda =  torch.cuda.is_available()
+    if use_xpu:
+       device = 'xpu'
+    elif use_cuda:
+       device = 'cuda'
+    else:
+       device = 'cpu'
+    model = Tacotron2(hparams).to(device)
     if hparams.fp16_run:
         model.decoder.attention_layer.score_mask_value = finfo('float16').min
 

torchbenchmark/models/yolov3/yolo_utils/torch_utils.py

@@ -26,13 +26,17 @@ def init_seeds(seed=0):
 def select_device(device='', apex=False, batch_size=None):
     # device = 'cpu' or '0' or '0,1,2,3'
     cpu_request = device.lower() == 'cpu'
-    if device and not cpu_request:  # if device requested other than 'cpu'
+    xpu_request = device.lower() == 'xpu'
+    if device and not cpu_request and not xpu_request:  # if device requested other than 'cpu' and 'xpu'
         os.environ['CUDA_VISIBLE_DEVICES'] = device  # set environment variable
         assert torch.cuda.is_available(), 'CUDA unavailable, invalid device %s requested' % device  # check availablity
 
-    cuda = False if cpu_request else torch.cuda.is_available()
+    cuda = False if cpu_request or xpu_request else torch.cuda.is_available()
     if cuda:
         return torch.device(f"cuda:{torch.cuda.current_device()}")
+    if xpu_request:
+        print('Using XPU')
+        return torch.device('xpu')
 
     print('Using CPU')
     return torch.device('cpu')