[Refactor] Initialize class members inside init method

src/diffusers/pipelines/allegro/pipeline_allegro.py

@@ -198,6 +198,10 @@ def __init__(
         scheduler: KarrasDiffusionSchedulers,
     ):
         super().__init__()
+        self._guidance_scale = 7.5
+        self._num_timesteps = 0
+        self._current_timestep = None
+        self._interrupt = False
 
         self.register_modules(
             tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, transformer=transformer, scheduler=scheduler
@@ -843,8 +847,6 @@ def __call__(
             negative_prompt_attention_mask,
         )
         self._guidance_scale = guidance_scale
-        self._current_timestep = None
-        self._interrupt = False
 
         # 2. Default height and width to transformer
         if prompt is not None and isinstance(prompt, str):

src/diffusers/pipelines/animatediff/pipeline_animatediff.py

@@ -136,6 +136,11 @@ def __init__(
         image_encoder: CLIPVisionModelWithProjection = None,
     ):
         super().__init__()
+        self._guidance_scale = 7.5
+        self._clip_skip = None
+        self._cross_attention_kwargs = None
+        self._num_timesteps = 0
+        self._interrupt = False
         if isinstance(unet, UNet2DConditionModel):
             unet = UNetMotionModel.from_unet2d(unet, motion_adapter)
 
@@ -714,7 +719,6 @@ def __call__(
         self._guidance_scale = guidance_scale
         self._clip_skip = clip_skip
         self._cross_attention_kwargs = cross_attention_kwargs
-        self._interrupt = False
 
         # 2. Define call parameters
         if prompt is not None and isinstance(prompt, (str, dict)):

src/diffusers/pipelines/animatediff/pipeline_animatediff_controlnet.py

@@ -172,6 +172,11 @@ def __init__(
         image_encoder: Optional[CLIPVisionModelWithProjection] = None,
     ):
         super().__init__()
+        self._guidance_scale = 7.5
+        self._clip_skip = None
+        self._cross_attention_kwargs = None
+        self._num_timesteps = 0
+        self._interrupt = False
         if isinstance(unet, UNet2DConditionModel):
             unet = UNetMotionModel.from_unet2d(unet, motion_adapter)
 
@@ -877,7 +882,6 @@ def __call__(
         self._guidance_scale = guidance_scale
         self._clip_skip = clip_skip
         self._cross_attention_kwargs = cross_attention_kwargs
-        self._interrupt = False
 
         # 2. Define call parameters
         if prompt is not None and isinstance(prompt, (str, dict)):

src/diffusers/pipelines/animatediff/pipeline_animatediff_sdxl.py

@@ -299,6 +299,13 @@ def __init__(
         force_zeros_for_empty_prompt: bool = True,
     ):
         super().__init__()
+        self._guidance_scale = 5.0
+        self._guidance_rescale = 0.0
+        self._clip_skip = None
+        self._cross_attention_kwargs = None
+        self._denoising_end = None
+        self._num_timesteps = 0
+        self._interrupt = False
 
         if isinstance(unet, UNet2DConditionModel):
             unet = UNetMotionModel.from_unet2d(unet, motion_adapter)
@@ -1083,7 +1090,6 @@ def __call__(
         self._clip_skip = clip_skip
         self._cross_attention_kwargs = cross_attention_kwargs
         self._denoising_end = denoising_end
-        self._interrupt = False
 
         # 2. Define call parameters
         if prompt is not None and isinstance(prompt, str):

src/diffusers/pipelines/animatediff/pipeline_animatediff_sparsectrl.py

@@ -184,6 +184,10 @@ def __init__(
         image_encoder: CLIPVisionModelWithProjection = None,
     ):
         super().__init__()
+        self._guidance_scale = 7.5
+        self._clip_skip = None
+        self._cross_attention_kwargs = None
+        self._num_timesteps = 0
         if isinstance(unet, UNet2DConditionModel):
             unet = UNetMotionModel.from_unet2d(unet, motion_adapter)
 

src/diffusers/pipelines/animatediff/pipeline_animatediff_video2video.py

@@ -239,6 +239,11 @@ def __init__(
         image_encoder: CLIPVisionModelWithProjection = None,
     ):
         super().__init__()
+        self._guidance_scale = 7.5
+        self._clip_skip = None
+        self._cross_attention_kwargs = None
+        self._num_timesteps = 0
+        self._interrupt = False
         if isinstance(unet, UNet2DConditionModel):
             unet = UNetMotionModel.from_unet2d(unet, motion_adapter)
 
@@ -883,7 +888,6 @@ def __call__(
         self._guidance_scale = guidance_scale
         self._clip_skip = clip_skip
         self._cross_attention_kwargs = cross_attention_kwargs
-        self._interrupt = False
 
         # 2. Define call parameters
         if prompt is not None and isinstance(prompt, (str, dict)):

src/diffusers/pipelines/animatediff/pipeline_animatediff_video2video_controlnet.py

@@ -262,6 +262,11 @@ def __init__(
         image_encoder: CLIPVisionModelWithProjection = None,
     ):
         super().__init__()
+        self._guidance_scale = 7.5
+        self._clip_skip = None
+        self._cross_attention_kwargs = None
+        self._num_timesteps = 0
+        self._interrupt = False
         if isinstance(unet, UNet2DConditionModel):
             unet = UNetMotionModel.from_unet2d(unet, motion_adapter)
 
@@ -1086,7 +1091,6 @@ def __call__(
         self._guidance_scale = guidance_scale
         self._clip_skip = clip_skip
         self._cross_attention_kwargs = cross_attention_kwargs
-        self._interrupt = False
 
         # 2. Define call parameters
         if prompt is not None and isinstance(prompt, (str, dict)):

src/diffusers/pipelines/aura_flow/pipeline_aura_flow.py

@@ -154,6 +154,9 @@ def __init__(
         scheduler: FlowMatchEulerDiscreteScheduler,
     ):
         super().__init__()
+        self._guidance_scale = 3.5
+        self._attention_kwargs = None
+        self._num_timesteps = 0
 
         self.register_modules(
             tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, transformer=transformer, scheduler=scheduler

src/diffusers/pipelines/bria/pipeline_bria.py

@@ -123,6 +123,12 @@ def __init__(
         image_encoder: CLIPVisionModelWithProjection = None,
         feature_extractor: CLIPImageProcessor = None,
     ):
+        super().__init__()
+        self._guidance_scale = 5.0
+        self._attention_kwargs = None
+        self._interrupt = False
+        self._num_timesteps = 0
+
         self.register_modules(
             vae=vae,
             text_encoder=text_encoder,

src/diffusers/pipelines/bria_fibo/pipeline_bria_fibo.py

@@ -107,6 +107,11 @@ def __init__(
             scheduler=scheduler,
         )
 
+        self._guidance_scale = 5.0
+        self._joint_attention_kwargs = None
+        self._interrupt = False
+        self._num_timesteps = 0
+
         self.vae_scale_factor = 16
         self.image_processor = VaeImageProcessor(vae_scale_factor=self.vae_scale_factor * 2)
         self.default_sample_size = 64

src/diffusers/pipelines/chroma/pipeline_chroma.py

@@ -190,6 +190,11 @@ def __init__(
         feature_extractor: CLIPImageProcessor = None,
     ):
         super().__init__()
+        self._guidance_scale = 5.0
+        self._joint_attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
+        self._num_timesteps = 0
 
         self.register_modules(
             vae=vae,

src/diffusers/pipelines/chroma/pipeline_chroma_img2img.py

@@ -202,6 +202,11 @@ def __init__(
         feature_extractor: CLIPImageProcessor = None,
     ):
         super().__init__()
+        self._guidance_scale = 5.0
+        self._joint_attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
+        self._num_timesteps = 0
 
         self.register_modules(
             vae=vae,

src/diffusers/pipelines/chronoedit/pipeline_chronoedit.py

@@ -167,6 +167,11 @@ def __init__(
     ):
         super().__init__()
 
+        self._guidance_scale = 5.0
+        self._attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
+        self._num_timesteps = 0
         self.register_modules(
             vae=vae,
             text_encoder=text_encoder,

src/diffusers/pipelines/cogvideo/pipeline_cogvideox.py

@@ -185,6 +185,11 @@ def __init__(
         scheduler: Union[CogVideoXDDIMScheduler, CogVideoXDPMScheduler],
     ):
         super().__init__()
+        self._guidance_scale = 6
+        self._num_timesteps = 0
+        self._attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
 
         self.register_modules(
             tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, transformer=transformer, scheduler=scheduler
@@ -631,8 +636,6 @@ def __call__(
         )
         self._guidance_scale = guidance_scale
         self._attention_kwargs = attention_kwargs
-        self._current_timestep = None
-        self._interrupt = False
 
         # 2. Default call parameters
         if prompt is not None and isinstance(prompt, str):
@@ -737,7 +740,7 @@ def __call__(
 
                 # perform guidance
                 if use_dynamic_cfg:
-                    self._guidance_scale = 1 + guidance_scale * (
+                    self._guidance_scale = 6 + guidance_scale * (
                         (1 - math.cos(math.pi * ((num_inference_steps - t.item()) / num_inference_steps) ** 5.0)) / 2
                     )
                 if do_classifier_free_guidance:

src/diffusers/pipelines/cogvideo/pipeline_cogvideox_fun_control.py

@@ -192,6 +192,11 @@ def __init__(
         scheduler: KarrasDiffusionSchedulers,
     ):
         super().__init__()
+        self._guidance_scale = 6
+        self._num_timesteps = 0
+        self._attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
 
         self.register_modules(
             tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, transformer=transformer, scheduler=scheduler
@@ -684,8 +689,6 @@ def __call__(
         )
         self._guidance_scale = guidance_scale
         self._attention_kwargs = attention_kwargs
-        self._current_timestep = None
-        self._interrupt = False
 
         # 2. Default call parameters
         if prompt is not None and isinstance(prompt, str):
@@ -803,7 +806,7 @@ def __call__(
 
                 # perform guidance
                 if use_dynamic_cfg:
-                    self._guidance_scale = 1 + guidance_scale * (
+                    self._guidance_scale = 6 + guidance_scale * (
                         (1 - math.cos(math.pi * ((num_inference_steps - t.item()) / num_inference_steps) ** 5.0)) / 2
                     )
                 if do_classifier_free_guidance:

src/diffusers/pipelines/cogvideo/pipeline_cogvideox_image2video.py

@@ -198,6 +198,11 @@ def __init__(
         scheduler: Union[CogVideoXDDIMScheduler, CogVideoXDPMScheduler],
     ):
         super().__init__()
+        self._guidance_scale = 6
+        self._num_timesteps = 0
+        self._attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
 
         self.register_modules(
             tokenizer=tokenizer,
@@ -728,9 +733,7 @@ def __call__(
             negative_prompt_embeds=negative_prompt_embeds,
         )
         self._guidance_scale = guidance_scale
-        self._current_timestep = None
         self._attention_kwargs = attention_kwargs
-        self._interrupt = False
 
         # 2. Default call parameters
         if prompt is not None and isinstance(prompt, str):
@@ -847,7 +850,7 @@ def __call__(
 
                 # perform guidance
                 if use_dynamic_cfg:
-                    self._guidance_scale = 1 + guidance_scale * (
+                    self._guidance_scale = 6 + guidance_scale * (
                         (1 - math.cos(math.pi * ((num_inference_steps - t.item()) / num_inference_steps) ** 5.0)) / 2
                     )
                 if do_classifier_free_guidance:

src/diffusers/pipelines/cogvideo/pipeline_cogvideox_video2video.py

@@ -207,6 +207,11 @@ def __init__(
         scheduler: Union[CogVideoXDDIMScheduler, CogVideoXDPMScheduler],
     ):
         super().__init__()
+        self._guidance_scale = 6
+        self._num_timesteps = 0
+        self._attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
 
         self.register_modules(
             tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, transformer=transformer, scheduler=scheduler
@@ -704,8 +709,6 @@ def __call__(
         )
         self._guidance_scale = guidance_scale
         self._attention_kwargs = attention_kwargs
-        self._current_timestep = None
-        self._interrupt = False
 
         # 2. Default call parameters
         if prompt is not None and isinstance(prompt, str):
@@ -818,7 +821,7 @@ def __call__(
 
                 # perform guidance
                 if use_dynamic_cfg:
-                    self._guidance_scale = 1 + guidance_scale * (
+                    self._guidance_scale = 6 + guidance_scale * (
                         (1 - math.cos(math.pi * ((num_inference_steps - t.item()) / num_inference_steps) ** 5.0)) / 2
                     )
                 if do_classifier_free_guidance:

src/diffusers/pipelines/cogview3/pipeline_cogview3plus.py

@@ -156,6 +156,9 @@ def __init__(
         scheduler: Union[CogVideoXDDIMScheduler, CogVideoXDPMScheduler],
     ):
         super().__init__()
+        self._guidance_scale = 5.0
+        self._num_timesteps = 0
+        self._interrupt = False
 
         self.register_modules(
             tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, transformer=transformer, scheduler=scheduler
@@ -534,7 +537,6 @@ def __call__(
             negative_prompt_embeds,
         )
         self._guidance_scale = guidance_scale
-        self._interrupt = False
 
         # 2. Default call parameters
         if prompt is not None and isinstance(prompt, str):

src/diffusers/pipelines/cogview4/pipeline_cogview4.py

@@ -168,6 +168,11 @@ def __init__(
         scheduler: FlowMatchEulerDiscreteScheduler,
     ):
         super().__init__()
+        self._guidance_scale = 5.0
+        self._num_timesteps = 0
+        self._attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
 
         self.register_modules(
             tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, transformer=transformer, scheduler=scheduler
@@ -535,8 +540,6 @@ def __call__(
         )
         self._guidance_scale = guidance_scale
         self._attention_kwargs = attention_kwargs
-        self._current_timestep = None
-        self._interrupt = False
 
         # Default call parameters
         if prompt is not None and isinstance(prompt, str):

src/diffusers/pipelines/cogview4/pipeline_cogview4_control.py

@@ -170,6 +170,11 @@ def __init__(
         scheduler: FlowMatchEulerDiscreteScheduler,
     ):
         super().__init__()
+        self._guidance_scale = 5.0
+        self._num_timesteps = 0
+        self._attention_kwargs = None
+        self._current_timestep = None
+        self._interrupt = False
 
         self.register_modules(
             tokenizer=tokenizer, text_encoder=text_encoder, vae=vae, transformer=transformer, scheduler=scheduler
@@ -567,8 +572,6 @@ def __call__(
         )
         self._guidance_scale = guidance_scale
         self._attention_kwargs = attention_kwargs
-        self._current_timestep = None
-        self._interrupt = False
 
         # Default call parameters
         if prompt is not None and isinstance(prompt, str):