                          break
                      pbar.update(len(buffer))
                      out_file.write(buffer)
          zip_file.close()
 
</s> remove                         self.save_now = True
 </s> add                         self._save_now = True </s> remove                 if self.stop:
 </s> add                 if self._stop: </s> remove                 if self.args.pingpong:
 </s> add                 if self._args.pingpong: </s> remove                     self.save_now = True
 </s> add                     self._save_now = True
        pbar.close()
                          break
                      pbar.update(len(buffer))
                      out_file.write(buffer)
          zip_file.close()
        pbar.close()
keep keep keep add
 Smart Masks - Training Implementation (#914)

* Smart Masks - Training

- Reinstate smart mask training code
- Reinstate mask_type back to model.config
- change 'replicate_input_mask to 'learn_mask'
- Add learn mask option
- Add mask loading from alignments to plugins.train.trainer
- Add mask_blur and mask threshold options
- _base.py - Pass mask options through training_opts dict
- plugins.train.model - check for mask_type not None for learn_mask and penalized_mask_loss
- Limit alignments loading to just those faces that appear in the training folder
- Raise error if not all training images have an alignment, and alignment file is required
- lib.training_data - Mask generation code
- lib.faces_detect - cv2 dimension stripping bugfix
- Remove cv2 linting code

* Update mask helptext in cli.py

* Fix Warp to Landmarks
Remove SHA1 hashing from training data

* Update mask training config

* Capture missing masks at training init

* lib.image.read_image_batch - Return filenames with batch for ordering

* scripts.train - Documentation

* plugins.train.trainer - documentation

* Ensure backward compatibility.
Fix convert for new predicted masks

* Update removed masks to components for legacy models. 
lib/utils.py