|  | @ -106,7 +106,7 @@ class Isc(NNOperator): | 
		
	
		
			
				|  |  |             img = img if self.skip_tfms else self.tfms(img) |  |  |             img = img if self.skip_tfms else self.tfms(img) | 
		
	
		
			
				|  |  |             img_list.append(img) |  |  |             img_list.append(img) | 
		
	
		
			
				|  |  |         inputs = torch.stack(img_list) |  |  |         inputs = torch.stack(img_list) | 
		
	
		
			
				|  |  |         inputs = inputs.to(self.device) |  |  |  | 
		
	
		
			
				|  |  |  |  |  |         inputs = inputs | 
		
	
		
			
				|  |  |         features = self.model(inputs) |  |  |         features = self.model(inputs) | 
		
	
		
			
				|  |  |         features = features.to('cpu') |  |  |         features = features.to('cpu') | 
		
	
		
			
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				|  | @ -138,7 +138,7 @@ class Isc(NNOperator): | 
		
	
		
			
				|  |  |                 path = path + '.onnx' |  |  |                 path = path + '.onnx' | 
		
	
		
			
				|  |  |             else: |  |  |             else: | 
		
	
		
			
				|  |  |                 raise ValueError(f'Invalid format {format}.') |  |  |                 raise ValueError(f'Invalid format {format}.') | 
		
	
		
			
				|  |  |         dummy_input = torch.rand(1, 3, 224, 224).to(self.device) |  |  |  | 
		
	
		
			
				|  |  |  |  |  |         dummy_input = torch.rand(1, 3, 224, 224) | 
		
	
		
			
				|  |  |         if format == 'pytorch': |  |  |         if format == 'pytorch': | 
		
	
		
			
				|  |  |             torch.save(self._model, path) |  |  |             torch.save(self._model, path) | 
		
	
		
			
				|  |  |         elif format == 'torchscript': |  |  |         elif format == 'torchscript': | 
		
	
	
		
			
				|  | @ -153,7 +153,7 @@ class Isc(NNOperator): | 
		
	
		
			
				|  |  |                 raise RuntimeError(f'Fail to save as torchscript: {e}.') |  |  |                 raise RuntimeError(f'Fail to save as torchscript: {e}.') | 
		
	
		
			
				|  |  |         elif format == 'onnx': |  |  |         elif format == 'onnx': | 
		
	
		
			
				|  |  |             try: |  |  |             try: | 
		
	
		
			
				|  |  |                 torch.onnx.export(self._model, |  |  |  | 
		
	
		
			
				|  |  |  |  |  |                 torch.onnx.export(self._model.to('cpu'), | 
		
	
		
			
				|  |  |                                   dummy_input, |  |  |                                   dummy_input, | 
		
	
		
			
				|  |  |                                   path, |  |  |                                   path, | 
		
	
		
			
				|  |  |                                   input_names=['input_0'], |  |  |                                   input_names=['input_0'], | 
		
	
	
		
			
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