fix flux hires

modules/loader.py

@@ -56,6 +56,15 @@ import diffusers.loaders.single_file # pylint: disable=W0611,C0411
 logging.getLogger("diffusers.loaders.single_file").setLevel(logging.ERROR)
 from tqdm.rich import tqdm # pylint: disable=W0611,C0411
 diffusers.loaders.single_file.logging.tqdm = partial(tqdm, unit='C')
+
+import tqdm as tqdm_lib
+class _tqdm_cls:
+    def __call__(self, *args, **kwargs):
+        bar_format = 'Diffusers {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m' + '{desc}' + '\x1b[0m'
+        return tqdm_lib.tqdm(*args, bar_format=bar_format, ncols=80, colour='#327fba', **kwargs)
+
+transformers.utils.logging.tqdm = _tqdm_cls()
+diffusers.pipelines.pipeline_utils.logging.tqdm = _tqdm_cls()
 timer.startup.record("diffusers")
 
 def get_packages():

modules/processing_callbacks.py

@@ -85,7 +85,7 @@ def diffusers_callback(pipe, step: int, timestep: int, kwargs: dict):
                     kwargs[key] = kwargs[key].chunk(2)[-1]
     try:
         if hasattr(pipe, "_unpack_latents") and hasattr(pipe, "vae_scale_factor"): # FLUX
-            if p.hr_resize_mode > 0 and (p.hr_upscaler != 'None' or p.hr_resize_mode == 5):
+            if p.hr_resize_mode > 0 and (p.hr_upscaler != 'None' or p.hr_resize_mode == 5) and p.is_hr_pass:
                 width = max(getattr(p, 'width', 0), getattr(p, 'hr_upscale_to_x', 0))
                 height = max(getattr(p, 'height', 0), getattr(p, 'hr_upscale_to_y', 0))
             else:

modules/processing_class.py

@@ -313,7 +313,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         self.script_args = []
 
     def init(self, all_prompts=None, all_seeds=None, all_subseeds=None):
-        if self.init_images is not None and len(self.init_images) > 0:
+        if hasattr(self, 'init_images') and self.init_images is not None and len(self.init_images) > 0:
             if self.width is None or self.width == 0:
                 self.width = int(8 * (self.init_images[0].width * self.scale_by // 8))
             if self.height is None or self.height == 0:

modules/processing_diffusers.py

@@ -179,6 +179,8 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
             shared.state.job_count = 2 * p.n_iter
             shared.sd_model = sd_models.set_diffuser_pipe(shared.sd_model, sd_models.DiffusersTaskType.IMAGE_2_IMAGE)
             shared.log.info(f'HiRes: class={shared.sd_model.__class__.__name__} sampler="{p.hr_sampler_name}"')
+            if 'Upscale' in shared.sd_model.__class__.__name__ or 'Flux in shared.sd_refiner.__class__.__name__':
+                output.images = processing_vae.vae_decode(latents=output.images, model=shared.sd_model, full_quality=p.full_quality, output_type='pil', width=p.width, height=p.height)
             if p.is_control and hasattr(p, 'task_args') and p.task_args.get('image', None) is not None:
                 if hasattr(shared.sd_model, "vae") and output.images is not None and len(output.images) > 0:
                     output.images = processing_vae.vae_decode(latents=output.images, model=shared.sd_model, full_quality=p.full_quality, output_type='pil', width=p.hr_upscale_to_x, height=p.hr_upscale_to_y) # controlnet cannnot deal with latent input