Merge branch 'main' into patch-1

src/diffusers/pipelines/controlnet_sd3/pipeline_stable_diffusion_3_controlnet.py

@@ -513,6 +513,7 @@ def check_inputs(
         pooled_prompt_embeds=None,
         negative_pooled_prompt_embeds=None,
         callback_on_step_end_tensor_inputs=None,
+        max_sequence_length=None,
     ):
         if height % 8 != 0 or width % 8 != 0:
             raise ValueError(f"`height` and `width` have to be divisible by 8 but are {height} and {width}.")
@@ -584,6 +585,9 @@ def check_inputs(
                 "If `negative_prompt_embeds` are provided, `negative_pooled_prompt_embeds` also have to be passed. Make sure to generate `negative_pooled_prompt_embeds` from the same text encoder that was used to generate `negative_prompt_embeds`."
             )
 
+        if max_sequence_length is not None and max_sequence_length > 512:
+            raise ValueError(f"`max_sequence_length` cannot be greater than 512 but is {max_sequence_length}")
+
     # Copied from diffusers.pipelines.stable_diffusion_3.pipeline_stable_diffusion_3.StableDiffusion3Pipeline.prepare_latents
     def prepare_latents(
         self,
@@ -710,6 +714,7 @@ def __call__(
         clip_skip: Optional[int] = None,
         callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None,
         callback_on_step_end_tensor_inputs: List[str] = ["latents"],
+        max_sequence_length: int = 256,
     ):
         r"""
         Function invoked when calling the pipeline for generation.
@@ -811,6 +816,7 @@ def __call__(
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
                 `._callback_tensor_inputs` attribute of your pipeline class.
+            max_sequence_length (`int` defaults to 256): Maximum sequence length to use with the `prompt`.
 
         Examples:
 
@@ -850,6 +856,7 @@ def __call__(
             pooled_prompt_embeds=pooled_prompt_embeds,
             negative_pooled_prompt_embeds=negative_pooled_prompt_embeds,
             callback_on_step_end_tensor_inputs=callback_on_step_end_tensor_inputs,
+            max_sequence_length=max_sequence_length,
         )
 
         self._guidance_scale = guidance_scale
@@ -888,6 +895,7 @@ def __call__(
             device=device,
             clip_skip=self.clip_skip,
             num_images_per_prompt=num_images_per_prompt,
+            max_sequence_length=max_sequence_length,
         )
 
         if self.do_classifier_free_guidance: