parameters: (image_path)
return_statement: return np.expand_dims(transforms(image_path), axis=0)
docstring: preprocess input image file to np.ndarray
  
      Args:
          image_path(str): Path of input image file
  
      Returns:
          ProcessedImage(numpy.ndarray): A numpy.ndarray
                  variable which shape is (1, 3, 192, 192)
docstring_summary: preprocess input image file to np.ndarray
docstring_tokens: preprocess input image file to np . ndarray
function: def preprocess(image_path):
      ''' preprocess input image file to np.ndarray
  
      Args:
          image_path(str): Path of input image file
  
      Returns:
          ProcessedImage(numpy.ndarray): A numpy.ndarray
                  variable which shape is (1, 3, 192, 192)
      '''
      transforms = T.Compose([
          T.Resize((192, 192)),
          T.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
      ],
          to_rgb=True)
      return np.expand_dims(transforms(image_path), axis=0)
function_tokens: def preprocess ( image_path ) : transforms = T . Compose ( [ T . Resize ( ( 192 , 192 ) ) , T . Normalize ( mean = [ 0.5 , 0.5 , 0.5 ] , std = [ 0.5 , 0.5 , 0.5 ] ) ] , to_rgb = True ) return np . expand_dims ( transforms ( image_path ) , axis = 0 )