update ieemoo-ai-isempty.py.
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@ -82,7 +82,7 @@ class Predictor(object):
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# self.model = torch.load(self.args.pretrained_model)
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# self.model = torch.load(self.args.pretrained_model)
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# else:
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# else:
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# self.model = torch.load(self.args.pretrained_model,map_location='cpu')
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# self.model = torch.load(self.args.pretrained_model,map_location='cpu')
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self.model = torch.load(self.args.pretrained_model)
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self.model = torch.load(self.args.pretrained_model,map_location=torch.device('cpu'))
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self.model.eval()
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self.model.eval()
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self.model.to("cuda")
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self.model.to("cuda")
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@ -95,8 +95,8 @@ class Predictor(object):
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else:
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else:
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with torch.no_grad():
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with torch.no_grad():
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x = self.test_transform(img_data)
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x = self.test_transform(img_data)
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if torch.cuda.is_available():
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# if torch.cuda.is_available():
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x = x.cuda()
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# x = x.cuda()
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part_logits = self.model(x.unsqueeze(0))
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part_logits = self.model(x.unsqueeze(0))
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probs = torch.nn.Softmax(dim=-1)(part_logits)
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probs = torch.nn.Softmax(dim=-1)(part_logits)
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topN = torch.argsort(probs, dim=-1, descending=True).tolist()
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topN = torch.argsort(probs, dim=-1, descending=True).tolist()
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