Merge branch 'DC-AE' of github.com:lawrence-cj/diffusers into DC-AE

Author: chenjy2003

src/diffusers/pipelines/flux/pipeline_flux_img2img.py

@@ -20,7 +20,7 @@
 from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5TokenizerFast
 
 from ...image_processor import PipelineImageInput, VaeImageProcessor
-from ...loaders import FluxLoraLoaderMixin, TextualInversionLoaderMixin
+from ...loaders import FluxLoraLoaderMixin, FromSingleFileMixin, TextualInversionLoaderMixin
 from ...models.autoencoders import AutoencoderKL
 from ...models.transformers import FluxTransformer2DModel
 from ...schedulers import FlowMatchEulerDiscreteScheduler
@@ -159,7 +159,7 @@ def retrieve_timesteps(
     return timesteps, num_inference_steps
 
 
-class FluxImg2ImgPipeline(DiffusionPipeline, FluxLoraLoaderMixin):
+class FluxImg2ImgPipeline(DiffusionPipeline, FluxLoraLoaderMixin, FromSingleFileMixin):
     r"""
     The Flux pipeline for image inpainting.
 

src/diffusers/pipelines/pag/pipeline_pag_sd_img2img.py

@@ -1063,6 +1063,9 @@ def __call__(
                     prompt_embeds = callback_outputs.pop("prompt_embeds", prompt_embeds)
                     negative_prompt_embeds = callback_outputs.pop("negative_prompt_embeds", negative_prompt_embeds)
 
+                if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):
+                    progress_bar.update()
+
         if not output_type == "latent":
             image = self.vae.decode(latents / self.vae.config.scaling_factor, return_dict=False, generator=generator)[
                 0