original_docstring: 
      CAREFUL! - this method uses a file as input instead of the path - so the
      position of the reader will be remembered outside of context of this method.
      :param image_file: the open file containing the images
      :return: a single image
      
docstring: CAREFUL. - this method uses a file as input instead of the path - so the
  position of the reader will be remembered outside of context of this method.
docstring_tokens: CAREFUL . - this method uses a file as input instead of the path - so the position of the reader will be remembered outside of context of this method .
code: def read_single_image(image_file):
      """
      CAREFUL! - this method uses a file as input instead of the path - so the
      position of the reader will be remembered outside of context of this method.
      :param image_file: the open file containing the images
      :return: a single image
      """
      # read a single image, count determines the number of uint8's to read
      image = np.fromfile(image_file, dtype=np.uint8, count=SIZE)
      # force into image matrix
      image = np.reshape(image, (3, 96, 96))
      # transpose to standard format
      # You might want to comment this line or reverse the shuffle
      # if you will use a learning algorithm like CNN, since they like
      # their channels separated.
      image = np.transpose(image, (2, 1, 0))
      return image
code_tokens: def read_single_image ( image_file ) : image = np . fromfile ( image_file , dtype = np . uint8 , count = SIZE ) image = np . reshape ( image , ( 3 , 96 , 96 ) ) image = np . transpose ( image , ( 2 , 1 , 0 ) ) return image
short_docstring: CAREFUL!
short_docstring_tokens: CAREFUL!
comment: """
      CAREFUL! - this method uses a file as input instead of the path - so the
      position of the reader will be remembered outside of context of this method.
      :param image_file: the open file containing the images
      :return: a single image
      """$SEP$# read a single image, count determines the number of uint8's to read$SEP$# force into image matrix$SEP$# transpose to standard format$SEP$# You might want to comment this line or reverse the shuffle$SEP$# if you will use a learning algorithm like CNN, since they like$SEP$# their channels separated.