original_docstring: 
          Overall shape augmentation,(applying for both image and mask)
          
docstring: Overall shape augmentation,(applying for both image and mask)
docstring_tokens: Overall shape augmentation ( applying for both image and mask )
code: def call(self, inputs, labels):
          augmented = tf.concat((inputs, labels), axis=-1)
          """
          Overall shape augmentation,(applying for both image and mask)
          """
          for _aug, _prob in [self.rotate, self.flip, self.trans, self.scale]:
              if random.random() < _prob:
                  augmented = _aug(augmented)
          inputs, labels = augmented[:, :, :3], augmented[:, :, -1]
  
          """
          Image(inputs) only augmentations (pixel-wise)
          """
          for _aug, _prob in [self.hue, self.gau2d]:
              if random.random() < _prob:
                  inputs = _aug(inputs)
          return inputs, labels
code_tokens: def call ( self , inputs , labels ) : augmented = tf . concat ( ( inputs , labels ) , axis = - 1 ) for _aug , _prob in [ self . rotate , self . flip , self . trans , self . scale ] : if random . random ( ) < _prob : augmented = _aug ( augmented ) inputs , labels = augmented [ : , : , : 3 ] , augmented [ : , : , - 1 ] """
          Image(inputs) only augmentations (pixel-wise)
          """ for _aug , _prob in [ self . hue , self . gau2d ] : if random . random ( ) < _prob : inputs = _aug ( inputs ) return inputs , labels
short_docstring: Overall shape augmentation,(applying for both image and mask)
short_docstring_tokens: Overall shape augmentation ( applying for both image and mask )
comment: """
          Overall shape augmentation,(applying for both image and mask)
          """$SEP$"""
          Image(inputs) only augmentations (pixel-wise)
          """