Merge changes

examples/community/regional_prompting_stable_diffusion.py

@@ -467,8 +467,6 @@ def make_emblist(self, prompts):
 
 
 def split_dims(xs, height, width):
-    xs = xs
-
     def repeat_div(x, y):
         while y > 0:
             x = math.ceil(x / 2)

src/diffusers/__init__.py

@@ -288,6 +288,7 @@
             "StableCascadePriorPipeline",
             "StableDiffusion3ControlNetPipeline",
             "StableDiffusion3Img2ImgPipeline",
+            "StableDiffusion3InpaintPipeline",
             "StableDiffusion3Pipeline",
             "StableDiffusionAdapterPipeline",
             "StableDiffusionAttendAndExcitePipeline",
@@ -690,6 +691,7 @@
             StableCascadePriorPipeline,
             StableDiffusion3ControlNetPipeline,
             StableDiffusion3Img2ImgPipeline,
+            StableDiffusion3InpaintPipeline,
             StableDiffusion3Pipeline,
             StableDiffusionAdapterPipeline,
             StableDiffusionAttendAndExcitePipeline,

src/diffusers/models/attention_processor.py

@@ -1112,9 +1112,7 @@ def __call__(
         key = key.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)
         value = value.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)
 
-        hidden_states = hidden_states = F.scaled_dot_product_attention(
-            query, key, value, dropout_p=0.0, is_causal=False
-        )
+        hidden_states = F.scaled_dot_product_attention(query, key, value, dropout_p=0.0, is_causal=False)
         hidden_states = hidden_states.transpose(1, 2).reshape(batch_size, -1, attn.heads * head_dim)
         hidden_states = hidden_states.to(query.dtype)
 

src/diffusers/models/controlnet_sd3.py

@@ -308,8 +308,6 @@ def forward(
                     "Passing `scale` via `joint_attention_kwargs` when not using the PEFT backend is ineffective."
                 )
 
-        height, width = hidden_states.shape[-2:]
-
         hidden_states = self.pos_embed(hidden_states)  # takes care of adding positional embeddings too.
         temb = self.time_text_embed(timestep, pooled_projections)
         encoder_hidden_states = self.context_embedder(encoder_hidden_states)

src/diffusers/models/unets/unet_stable_cascade.py

@@ -478,9 +478,7 @@ def custom_forward(*inputs):
                                 create_custom_forward(block), x, r_embed, use_reentrant=False
                             )
                         else:
-                            x = x = torch.utils.checkpoint.checkpoint(
-                                create_custom_forward(block), use_reentrant=False
-                            )
+                            x = torch.utils.checkpoint.checkpoint(create_custom_forward(block), use_reentrant=False)
                     if i < len(repmap):
                         x = repmap[i](x)
                 level_outputs.insert(0, x)

src/diffusers/pipelines/__init__.py

@@ -243,7 +243,11 @@
             "StableDiffusionLDM3DPipeline",
         ]
     )
-    _import_structure["stable_diffusion_3"] = ["StableDiffusion3Pipeline", "StableDiffusion3Img2ImgPipeline"]
+    _import_structure["stable_diffusion_3"] = [
+        "StableDiffusion3Pipeline",
+        "StableDiffusion3Img2ImgPipeline",
+        "StableDiffusion3InpaintPipeline",
+    ]
     _import_structure["stable_diffusion_attend_and_excite"] = ["StableDiffusionAttendAndExcitePipeline"]
     _import_structure["stable_diffusion_safe"] = ["StableDiffusionPipelineSafe"]
     _import_structure["stable_diffusion_sag"] = ["StableDiffusionSAGPipeline"]
@@ -523,7 +527,11 @@
             StableUnCLIPImg2ImgPipeline,
             StableUnCLIPPipeline,
         )
-        from .stable_diffusion_3 import StableDiffusion3Img2ImgPipeline, StableDiffusion3Pipeline
+        from .stable_diffusion_3 import (
+            StableDiffusion3Img2ImgPipeline,
+            StableDiffusion3InpaintPipeline,
+            StableDiffusion3Pipeline,
+        )
         from .stable_diffusion_attend_and_excite import StableDiffusionAttendAndExcitePipeline
         from .stable_diffusion_diffedit import StableDiffusionDiffEditPipeline
         from .stable_diffusion_gligen import StableDiffusionGLIGENPipeline, StableDiffusionGLIGENTextImagePipeline

src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py

@@ -661,7 +661,6 @@ def __call__(
                         noise_guidance_edit_tmp = torch.einsum(
                             "cb,cbijk->bijk", concept_weights_tmp, noise_guidance_edit_tmp
                         )
-                        noise_guidance_edit_tmp = noise_guidance_edit_tmp
                         noise_guidance = noise_guidance + noise_guidance_edit_tmp
 
                         self.sem_guidance[i] = noise_guidance_edit_tmp.detach().cpu()

src/diffusers/pipelines/stable_diffusion_3/__init__.py

@@ -25,6 +25,7 @@
 else:
     _import_structure["pipeline_stable_diffusion_3"] = ["StableDiffusion3Pipeline"]
     _import_structure["pipeline_stable_diffusion_3_img2img"] = ["StableDiffusion3Img2ImgPipeline"]
+    _import_structure["pipeline_stable_diffusion_3_inpaint"] = ["StableDiffusion3InpaintPipeline"]
 
 if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
     try:
@@ -35,6 +36,7 @@
     else:
         from .pipeline_stable_diffusion_3 import StableDiffusion3Pipeline
         from .pipeline_stable_diffusion_3_img2img import StableDiffusion3Img2ImgPipeline
+        from .pipeline_stable_diffusion_3_inpaint import StableDiffusion3InpaintPipeline
 
 else:
     import sys