updates
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@ -3,8 +3,8 @@
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# batch=1
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# subdivisions=1
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# Training
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batch=64
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subdivisions=32
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batch=16
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subdivisions=8
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width=608
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height=608
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channels=3
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@ -26,7 +26,7 @@ def select_device(force_cpu=False):
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c = 1024 ** 2 # bytes to MB
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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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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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(cuda_str, x[0].name, x[0].total_memory / c))
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if ng > 0:
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