updates
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@ -18,7 +18,7 @@ def select_device(force_cpu=False):
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if cuda:
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if cuda:
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try: # Mixed precision training https://github.com/NVIDIA/apex
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try: # Mixed precision training https://github.com/NVIDIA/apex
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from apex import amp
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from apex import amp
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apex_str = ' with Apex'
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apex_str = 'with Apex '
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except:
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except:
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apex_str = ''
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apex_str = ''
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@ -27,13 +27,12 @@ def select_device(force_cpu=False):
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ng = torch.cuda.device_count()
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ng = torch.cuda.device_count()
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x = [torch.cuda.get_device_properties(i) for i in range(ng)]
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x = [torch.cuda.get_device_properties(i) for i in range(ng)]
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cuda_str = 'Using CUDA ' + apex_str
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cuda_str = 'Using CUDA ' + apex_str
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print("%sdevice0 _CudaDeviceProperties(name='%s', total_memory=%dMB)" %
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for i in range(0, ng):
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(cuda_str, x[0].name, x[0].total_memory / c))
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if ng == 1:
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if ng > 0:
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# torch.cuda.set_device(0) # OPTIONAL: Set GPU ID
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# torch.cuda.set_device(0) # OPTIONAL: Set GPU ID
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cuda_str = ' ' * len(cuda_str)
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for i in range(1, ng):
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print("%sdevice%g _CudaDeviceProperties(name='%s', total_memory=%dMB)" %
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print("%sdevice%g _CudaDeviceProperties(name='%s', total_memory=%dMB)" %
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(cuda_str, i, x[i].name, x[i].total_memory / c))
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(' ' * len(cuda_str), i, x[i].name, x[i].total_memory / c))
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print('') # skip a line
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print('') # skip a line
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return device
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return device
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