                   show_min: bool = True, show_mean: bool = True, show_max: bool = True) -> None:
          self._times: Dict[str, List[float]] = {}
          self._steps: Dict[str, float] = {}
          self._interval = 1
  
      def step_start(self, name: str, record: bool = True) -> None:
          """ Start the timer for the given step name.
  
 
</s> remove     def __init__(self):
 </s> add     def __init__(self,
                 show_min: bool = True, show_mean: bool = True, show_max: bool = True) -> None: </s> remove             _min = f"{np.min(val):.{decimal_places}f}"
            avg = f"{np.mean(val):.{decimal_places}f}"
            _max = f"{np.max(val):.{decimal_places}f}"
 </s> add  </s> remove             print(f"{self._format_column(key, name_col)}{self._format_column(num, items_col)}"
                  f"{self._format_column(_min, time_col)}{self._format_column(avg, time_col)}"
                  f"{self._format_column(_max, time_col)}")
 </s> add             contents = f"{self._format_column(key, name_col)}{self._format_column(num, items_col)}"
            if self._display["min"]:
                _min = f"{np.min(val):.{decimal_places}f}"
                contents += f"{self._format_column(_min, time_col)}"
            if self._display["mean"]:
                avg = f"{np.mean(val):.{decimal_places}f}"
                contents += f"{self._format_column(avg, time_col)}"
            if self._display["max"]:
                _max = f"{np.max(val):.{decimal_places}f}"
                contents += f"{self._format_column(_max, time_col)}"
            print(contents) </s> remove         self._process_size = max([model.input_shape[1]] + [img[1]
                                 for img in model.output_shapes[0]])
 </s> add         self._process_size = max(img[1]
                                 for img in model.model.input_shape + model.model.output_shape)
        self._display = dict(min=show_min, mean=show_mean, max=show_max)
                   show_min: bool = True, show_mean: bool = True, show_max: bool = True) -> None:
          self._times: Dict[str, List[float]] = {}
          self._steps: Dict[str, float] = {}
          self._interval = 1
        self._display = dict(min=show_min, mean=show_mean, max=show_max)
  
      def step_start(self, name: str, record: bool = True) -> None:
          """ Start the timer for the given step name.
  
keep keep keep add keep keep keep keep
 bugfixes:
  - lib.training: Correct  input + output size for pre-existing models
  - lib.align.detected_faces - fix trace logging
  - lib.util.debug_times 
lib/utils.py