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python benchmarks/dynamo/torchbench.py --accuracy --bfloat16 -d xpu -n10 --training --only yolov3 --backend=inductor
Traceback (most recent call last): File "/home/sdp/actions-runner/_work/torch-xpu-ops/pytorch/benchmarks/dynamo/common.py", line 4886, in run ) = runner.load_model( File "/home/sdp/actions-runner/_work/torch-xpu-ops/pytorch/benchmarks/dynamo/torchbench.py", line 312, in load_model benchmark = benchmark_cls( File "/home/sdp/actions-runner/_work/torch-xpu-ops/benchmark/torchbenchmark/util/model.py", line 24, in call obj = type.call(cls, *args, **kwargs) File "/home/sdp/actions-runner/_work/torch-xpu-ops/benchmark/torchbenchmark/models/yolov3/init.py", line 58, in init self.training_loop, self.model, self.example_inputs = prepare_training_loop( File "/home/sdp/actions-runner/_work/torch-xpu-ops/benchmark/torchbenchmark/models/yolov3/yolo_train.py", line 630, in prepare_training_loop device = torch_utils.select_device( File "/home/sdp/actions-runner/_work/torch-xpu-ops/benchmark/torchbenchmark/models/yolov3/yolo_utils/torch_utils.py", line 31, in select_device assert torch.cuda.is_available(), 'CUDA unavailable, invalid device %s requested' % device # check availablity AssertionError: CUDA unavailable, invalid device xpu requested
https://github.com/pytorch/benchmark/blob/766a5e3a189384659fd35a68c3b17b88c761aaac/torchbenchmark/models/yolov3/yolo_utils/torch_utils.py#L28-L31
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' os.environ['CUDA_VISIBLE_DEVICES'] = device # set environment variable assert torch.cuda.is_available(), 'CUDA unavailable, invalid device %s requested' % device # check availablity
Torchbench: 766a5e3a189384659fd35a68c3b17b88c761aaac
The text was updated successfully, but these errors were encountered:
Skipped in CI & Nightly test #1230
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Skip yolo3 (#1230)
2037a43
Temporary WA for #1229
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🐛 Describe the bug
python benchmarks/dynamo/torchbench.py --accuracy --bfloat16 -d xpu -n10 --training --only yolov3 --backend=inductor
https://github.com/pytorch/benchmark/blob/766a5e3a189384659fd35a68c3b17b88c761aaac/torchbenchmark/models/yolov3/yolo_utils/torch_utils.py#L28-L31
Versions
Torchbench: 766a5e3a189384659fd35a68c3b17b88c761aaac
The text was updated successfully, but these errors were encountered: