              assert self._placeholder is not None
              placeholder = np.concatenate([np.expand_dims(self._placeholder, 0)] * remainder)
              samples = np.concatenate((samples, placeholder))
  
          display = np.vstack([np.hstack(cast(Sequence, samples[row * cols: (row + 1) * cols]))
                               for row in range(rows)])
          logger.debug("display shape: %s", display.shape)
          return Image.fromarray(display)
  
      def load_latest_preview(self, thumbnail_size: int, frame_dims: Tuple[int, int]) -> bool:
 
</s> remove     def load_latest_preview(self, thumbnail_size: int, frame_dims: Tuple[int, int]) -> bool:
 </s> add     def load_latest_preview(self, thumbnail_size: int, frame_dims: tuple[int, int]) -> bool: </s> remove     def _place_previews(self, frame_dims: Tuple[int, int]) -> Image.Image:
 </s> add     def _place_previews(self, frame_dims: tuple[int, int]) -> Image.Image: </s> remove     def _generate_weights(cls, channel: Dict[str, float], domain: np.ndarray) -> tf.Tensor:
 </s> add     def _generate_weights(cls, channel: dict[str, float], domain: np.ndarray) -> tf.Tensor: </s> remove                               image_files: List[str],
                              frame_dims: Tuple[int, int],
 </s> add                               image_files: list[str],
                              frame_dims: tuple[int, int], </s> remove             x_center = (cast(int, face.left) + face.right) / 2.0
            y_center = (cast(int, face.top) + face.bottom) / 2.0 - cast(int, face.height) * 0.12
            scale = (cast(int, face.width) + cast(int, face.height)) * self.reference_scale
            center_scale[index, :, 0] = np.full(68, x_center, dtype='float32')
            center_scale[index, :, 1] = np.full(68, y_center, dtype='float32')
 </s> add             x_ctr = (T.cast(int, face.left) + face.right) / 2.0
            y_ctr = (T.cast(int, face.top) + face.bottom) / 2.0 - T.cast(int, face.height) * 0.12
            scale = (T.cast(int, face.width) + T.cast(int, face.height)) * self.reference_scale
            center_scale[index, :, 0] = np.full(68, x_ctr, dtype='float32')
            center_scale[index, :, 1] = np.full(68, y_ctr, dtype='float32')
        display = np.vstack([np.hstack(T.cast("Sequence", samples[row * cols: (row + 1) * cols]))
              assert self._placeholder is not None
              placeholder = np.concatenate([np.expand_dims(self._placeholder, 0)] * remainder)
              samples = np.concatenate((samples, placeholder))
  
        display = np.vstack([np.hstack(T.cast("Sequence", samples[row * cols: (row + 1) * cols]))
                               for row in range(rows)])
          logger.debug("display shape: %s", display.shape)
          return Image.fromarray(display)
  
      def load_latest_preview(self, thumbnail_size: int, frame_dims: Tuple[int, int]) -> bool:
keep keep keep keep replace keep keep keep keep keep
 Rebase code (#1326)

* Remove tensorflow_probability requirement

* setup.py - fix progress bars

* requirements.txt: Remove pre python 3.9 packages

* update apple requirements.txt

* update INSTALL.md

* Remove python<3.9 code

* setup.py - fix Windows Installer

* typing: python3.9 compliant

* Update pytest and readthedocs python versions

* typing fixes

* Python Version updates
  - Reduce max version to 3.10
  - Default to 3.10 in installers
  - Remove incompatible 3.11 tests

* Update dependencies

* Downgrade imageio dep for Windows

* typing: merge optional unions and fixes

* Updates
  - min python version 3.10
  - typing to python 3.10 spec
  - remove pre-tf2.10 code
  - Add conda tests

* train: re-enable optimizer saving

* Update dockerfiles

* Update setup.py
  - Apple Conda deps to setup.py
  - Better Cuda + dependency handling

* bugfix: Patch logging to prevent Autograph errors

* Update dockerfiles

* Setup.py - Setup.py - stdout to utf-8

* Add more OSes to github Actions

* suppress mac-os end to end test 
lib/gui/utils/image.py