remove fluxcontrolmixin

src/diffusers/pipelines/flux/pipeline_flux_control.py

@@ -30,7 +30,7 @@ from ...utils import (
 )
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
-from .pipeline_flux_utils import FluxControlMixin, calculate_shift, retrieve_timesteps
+from .pipeline_flux_utils import FluxMixin, calculate_shift, retrieve_timesteps
 from .pipeline_output import FluxPipelineOutput
 
 
@@ -81,7 +81,7 @@ EXAMPLE_DOC_STRING = """
 
 class FluxControlPipeline(
     DiffusionPipeline,
-    FluxControlMixin,
+    FluxMixin,
     FluxLoraLoaderMixin,
     FromSingleFileMixin,
     TextualInversionLoaderMixin,
@@ -235,6 +235,41 @@ class FluxControlPipeline(
 
         return latents, latent_image_ids
 
+    # Copied from diffusers.pipelines.controlnet_sd3.pipeline_stable_diffusion_3_controlnet.StableDiffusion3ControlNetPipeline.prepare_image
+    def prepare_image(
+        self,
+        image,
+        width,
+        height,
+        batch_size,
+        num_images_per_prompt,
+        device,
+        dtype,
+        do_classifier_free_guidance=False,
+        guess_mode=False,
+    ):
+        if isinstance(image, torch.Tensor):
+            pass
+        else:
+            image = self.image_processor.preprocess(image, height=height, width=width)
+
+        image_batch_size = image.shape[0]
+
+        if image_batch_size == 1:
+            repeat_by = batch_size
+        else:
+            # image batch size is the same as prompt batch size
+            repeat_by = num_images_per_prompt
+
+        image = image.repeat_interleave(repeat_by, dim=0)
+
+        image = image.to(device=device, dtype=dtype)
+
+        if do_classifier_free_guidance and not guess_mode:
+            image = torch.cat([image] * 2)
+
+        return image
+
     @torch.no_grad()
     @replace_example_docstring(EXAMPLE_DOC_STRING)
     def __call__(

src/diffusers/pipelines/flux/pipeline_flux_control_img2img.py

@@ -26,7 +26,7 @@ from ...schedulers import FlowMatchEulerDiscreteScheduler
 from ...utils import is_torch_xla_available, logging, replace_example_docstring
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
-from .pipeline_flux_utils import FluxControlMixin, calculate_shift, retrieve_latents, retrieve_timesteps
+from .pipeline_flux_utils import FluxMixin, calculate_shift, retrieve_latents, retrieve_timesteps
 from .pipeline_output import FluxPipelineOutput
 
 
@@ -80,7 +80,7 @@ EXAMPLE_DOC_STRING = """
 """
 
 
-class FluxControlImg2ImgPipeline(DiffusionPipeline, FluxControlMixin, FluxLoraLoaderMixin, FromSingleFileMixin):
+class FluxControlImg2ImgPipeline(DiffusionPipeline, FluxMixin, FluxLoraLoaderMixin, FromSingleFileMixin):
     r"""
     The Flux pipeline for image inpainting.
 

src/diffusers/pipelines/flux/pipeline_flux_control_inpaint.py

@@ -35,7 +35,7 @@ from ...schedulers import FlowMatchEulerDiscreteScheduler
 from ...utils import is_torch_xla_available, logging, replace_example_docstring
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
-from .pipeline_flux_utils import FluxControlMixin, calculate_shift, retrieve_latents, retrieve_timesteps
+from .pipeline_flux_utils import FluxMixin, calculate_shift, retrieve_latents, retrieve_timesteps
 from .pipeline_output import FluxPipelineOutput
 
 
@@ -108,7 +108,7 @@ EXAMPLE_DOC_STRING = """
 
 class FluxControlInpaintPipeline(
     DiffusionPipeline,
-    FluxControlMixin,
+    FluxMixin,
     FluxLoraLoaderMixin,
     FromSingleFileMixin,
     TextualInversionLoaderMixin,

src/diffusers/pipelines/flux/pipeline_flux_controlnet.py

@@ -34,7 +34,7 @@ from ...schedulers import FlowMatchEulerDiscreteScheduler
 from ...utils import is_torch_xla_available, logging, replace_example_docstring
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
-from .pipeline_flux_utils import FluxControlMixin, calculate_shift, retrieve_latents, retrieve_timesteps
+from .pipeline_flux_utils import FluxMixin, calculate_shift, retrieve_latents, retrieve_timesteps
 from .pipeline_output import FluxPipelineOutput
 
 
@@ -80,7 +80,7 @@ EXAMPLE_DOC_STRING = """
 
 
 class FluxControlNetPipeline(
-    DiffusionPipeline, FluxControlMixin, FluxLoraLoaderMixin, FromSingleFileMixin, FluxIPAdapterMixin
+    DiffusionPipeline, FluxMixin, FluxLoraLoaderMixin, FromSingleFileMixin, FluxIPAdapterMixin
 ):
     r"""
     The Flux pipeline for text-to-image generation.

src/diffusers/pipelines/flux/pipeline_flux_controlnet_image_to_image.py

@@ -18,7 +18,7 @@ from ...schedulers import FlowMatchEulerDiscreteScheduler
 from ...utils import is_torch_xla_available, logging, replace_example_docstring
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
-from .pipeline_flux_utils import FluxControlMixin, calculate_shift, retrieve_latents, retrieve_timesteps
+from .pipeline_flux_utils import FluxMixin, calculate_shift, retrieve_latents, retrieve_timesteps
 from .pipeline_output import FluxPipelineOutput
 
 
@@ -74,7 +74,7 @@ EXAMPLE_DOC_STRING = """
 """
 
 
-class FluxControlNetImg2ImgPipeline(DiffusionPipeline, FluxControlMixin, FluxLoraLoaderMixin, FromSingleFileMixin):
+class FluxControlNetImg2ImgPipeline(DiffusionPipeline, FluxMixin, FluxLoraLoaderMixin, FromSingleFileMixin):
     r"""
     The Flux controlnet pipeline for image-to-image generation.
 

src/diffusers/pipelines/flux/pipeline_flux_controlnet_inpainting.py

@@ -19,7 +19,7 @@ from ...schedulers import FlowMatchEulerDiscreteScheduler
 from ...utils import is_torch_xla_available, logging, replace_example_docstring
 from ...utils.torch_utils import randn_tensor
 from ..pipeline_utils import DiffusionPipeline
-from .pipeline_flux_utils import FluxControlMixin, calculate_shift, retrieve_latents, retrieve_timesteps
+from .pipeline_flux_utils import FluxMixin, calculate_shift, retrieve_latents, retrieve_timesteps
 from .pipeline_output import FluxPipelineOutput
 
 
@@ -76,7 +76,7 @@ EXAMPLE_DOC_STRING = """
 """
 
 
-class FluxControlNetInpaintPipeline(DiffusionPipeline, FluxControlMixin, FluxLoraLoaderMixin, FromSingleFileMixin):
+class FluxControlNetInpaintPipeline(DiffusionPipeline, FluxMixin, FluxLoraLoaderMixin, FromSingleFileMixin):
     r"""
     The Flux controlnet pipeline for inpainting.
 

src/diffusers/pipelines/flux/pipeline_flux_utils.py

@@ -394,40 +394,3 @@ class FluxMixin:
         prompt_embeds = prompt_embeds.view(batch_size * num_images_per_prompt, -1)
 
         return prompt_embeds
-
-
-class FluxControlMixin(FluxMixin):
-    # Copied from diffusers.pipelines.controlnet_sd3.pipeline_stable_diffusion_3_controlnet.StableDiffusion3ControlNetPipeline.prepare_image
-    def prepare_image(
-        self,
-        image,
-        width,
-        height,
-        batch_size,
-        num_images_per_prompt,
-        device,
-        dtype,
-        do_classifier_free_guidance=False,
-        guess_mode=False,
-    ):
-        if isinstance(image, torch.Tensor):
-            pass
-        else:
-            image = self.image_processor.preprocess(image, height=height, width=width)
-
-        image_batch_size = image.shape[0]
-
-        if image_batch_size == 1:
-            repeat_by = batch_size
-        else:
-            # image batch size is the same as prompt batch size
-            repeat_by = num_images_per_prompt
-
-        image = image.repeat_interleave(repeat_by, dim=0)
-
-        image = image.to(device=device, dtype=dtype)
-
-        if do_classifier_free_guidance and not guess_mode:
-            image = torch.cat([image] * 2)
-
-        return image