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TestOneHot.test_one_hot()   A

↳ Parent: tests.transforms.preprocessing.test_onehot

Complexity

Conditions 1

Size

Total Lines 4
Code Lines 4

Duplication

Lines 0
Ratio 0 %

Importance

Changes 0
Metric Value
eloc 4
dl 0
loc 4
rs 10
c 0
b 0
f 0
cc 1
nop 1
1 
import torch
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import torchio as tio
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from ...utils import TorchioTestCase
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class TestOneHot(TorchioTestCase):

            


            
                                                                                                            
                                                                
            
                                    
            
            

                
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    """Tests for `OneHot`."""

            


            
                                                                        
                            
            
                                    
            
            

                
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    def test_one_hot(self):

            


            
                                                                        
                            
            
                                    
            
            

                
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        image = self.sample_subject.label

            


            
                                                                        
                            
            
                                    
            
            

                
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        one_hot = tio.OneHot(num_classes=3)(image)

            


            
                                                                        
                            
            
                                    
            
            

                
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        assert one_hot.num_channels == 3

            


            
                                                                                                            
                            
            
                                    
            
            

                
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    def test_multichannel(self):

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        label_map = tio.LabelMap(tensor=torch.rand(2, 3, 3, 3) > 1)

            


            
                                                                                                            
                            
            
                                    
            
            

                
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        with self.assertRaises(RuntimeError):

            


            
                                                                                                            
                                                                
            
                                    
            
            

                
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            tio.OneHot()(label_map)

            


            
                                                        
            
                                    
            
            

                
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