Stable Diffusion XL ControlNet

ControlNet can also be applied to the more advanced Stable Diffusion XL (SDXL) model, allowing for high-resolution image generation with precise structural guidance from condition images. Optimum RBLN provides accelerated SDXL ControlNet pipelines for RBLN NPUs.

Supported Pipelines

• Text-to-Image with SDXL ControlNet: Generate high-resolution images from text prompts, guided by a control image using an SDXL base model.
• Image-to-Image with SDXL ControlNet: Modify an existing image based on a text prompt and a control image using an SDXL base model.

Important: Batch Size Configuration for Guidance Scale

Batch Size and Guidance Scale (SDXL)

As with other SDXL pipelines, using ControlNet SDXL pipelines with guidance_scale > 1.0 doubles the effective batch size of the UNet and the ControlNet model.

Ensure the batch_size specified in the unet and controlnet sections of your RBLNStableDiffusionXLControlNetPipelineConfig matches the expected runtime batch size (typically 2 × the inference batch size if guidance_scale > 1.0). Omitting these will result in automatic doubling based on the pipeline's batch_size.

API Reference

Classes

RBLNStableDiffusionXLControlNetPipeline

Bases: RBLNDiffusionMixin, StableDiffusionXLControlNetPipeline

RBLN-accelerated implementation of Stable Diffusion XL pipeline with ControlNet for high-resolution guided text-to-image generation.

This pipeline compiles Stable Diffusion XL and ControlNet models to run efficiently on RBLN NPUs, enabling high-performance inference for generating high-quality images with precise structural control and enhanced detail preservation.

Functions

from_pretrained(model_id, *, export=None, model_save_dir=None, rbln_config={}, lora_ids=None, lora_weights_names=None, lora_scales=None, **kwargs) classmethod

Load a pretrained diffusion pipeline from a model checkpoint, with optional compilation for RBLN NPUs.

This method has two distinct operating modes

• When export=True: Takes a PyTorch-based diffusion model, compiles it for RBLN NPUs, and loads the compiled model
• When export=False: Loads an already compiled RBLN model from model_id without recompilation

It supports various diffusion pipelines including Stable Diffusion, Kandinsky, ControlNet, and other diffusers-based models.

Parameters:

Name	Type	Description	Default
model_id	`str`	The model ID or path to the pretrained model to load. Can be either: A model ID from the HuggingFace Hub A local path to a saved model directory	required
export	bool	If True, takes a PyTorch model from model_id and compiles it for RBLN NPU execution. If False, loads an already compiled RBLN model from model_id without recompilation.	None
model_save_dir	Optional[PathLike]	Directory to save the compiled model artifacts. Only used when export=True. If not provided and export=True, a temporary directory is used.	None
rbln_config	Dict[str, Any]	Configuration options for RBLN compilation. Can include settings for specific submodules such as text_encoder, unet, and vae. Configuration can be tailored to the specific pipeline being compiled.	{}
lora_ids	Optional[Union[str, List[str]]]	LoRA adapter ID(s) to load and apply before compilation. LoRA weights are fused into the model weights during compilation. Only used when export=True.	None
lora_weights_names	Optional[Union[str, List[str]]]	Names of specific LoRA weight files to load, corresponding to lora_ids. Only used when export=True.	None
lora_scales	Optional[Union[float, List[float]]]	Scaling factor(s) to apply to the LoRA adapter(s). Only used when export=True.	None
kwargs	Any	Additional arguments to pass to the underlying diffusion pipeline constructor or the RBLN compilation process. These may include parameters specific to individual submodules or the particular diffusion pipeline being used.	{}

Returns:

Type	Description
RBLNDiffusionMixin	A compiled or loaded diffusion pipeline that can be used for inference on RBLN NPU. The returned object is an instance of the class that called this method, inheriting from RBLNDiffusionMixin.

Functions

Classes

RBLNStableDiffusionXLControlNetImg2ImgPipeline

Bases: RBLNDiffusionMixin, StableDiffusionXLControlNetImg2ImgPipeline

RBLN-accelerated implementation of Stable Diffusion XL pipeline with ControlNet for high-resolution guided image-to-image generation.

This pipeline compiles Stable Diffusion XL and ControlNet models to run efficiently on RBLN NPUs, enabling high-performance inference for transforming input images with precise structural control and enhanced quality preservation.

Functions

from_pretrained(model_id, *, export=None, model_save_dir=None, rbln_config={}, lora_ids=None, lora_weights_names=None, lora_scales=None, **kwargs) classmethod

Load a pretrained diffusion pipeline from a model checkpoint, with optional compilation for RBLN NPUs.

This method has two distinct operating modes

• When export=True: Takes a PyTorch-based diffusion model, compiles it for RBLN NPUs, and loads the compiled model
• When export=False: Loads an already compiled RBLN model from model_id without recompilation

It supports various diffusion pipelines including Stable Diffusion, Kandinsky, ControlNet, and other diffusers-based models.

Parameters:

Name	Type	Description	Default
model_id	`str`	The model ID or path to the pretrained model to load. Can be either: A model ID from the HuggingFace Hub A local path to a saved model directory	required
export	bool	If True, takes a PyTorch model from model_id and compiles it for RBLN NPU execution. If False, loads an already compiled RBLN model from model_id without recompilation.	None
model_save_dir	Optional[PathLike]	Directory to save the compiled model artifacts. Only used when export=True. If not provided and export=True, a temporary directory is used.	None
rbln_config	Dict[str, Any]	Configuration options for RBLN compilation. Can include settings for specific submodules such as text_encoder, unet, and vae. Configuration can be tailored to the specific pipeline being compiled.	{}
lora_ids	Optional[Union[str, List[str]]]	LoRA adapter ID(s) to load and apply before compilation. LoRA weights are fused into the model weights during compilation. Only used when export=True.	None
lora_weights_names	Optional[Union[str, List[str]]]	Names of specific LoRA weight files to load, corresponding to lora_ids. Only used when export=True.	None
lora_scales	Optional[Union[float, List[float]]]	Scaling factor(s) to apply to the LoRA adapter(s). Only used when export=True.	None
kwargs	Any	Additional arguments to pass to the underlying diffusion pipeline constructor or the RBLN compilation process. These may include parameters specific to individual submodules or the particular diffusion pipeline being used.	{}

Returns:

Type	Description
RBLNDiffusionMixin	A compiled or loaded diffusion pipeline that can be used for inference on RBLN NPU. The returned object is an instance of the class that called this method, inheriting from RBLNDiffusionMixin.

Functions

Classes

RBLNStableDiffusionXLControlNetPipelineBaseConfig

Bases: RBLNModelConfig

Base configuration for Stable Diffusion XL ControlNet pipelines.

Functions

__init__(text_encoder=None, text_encoder_2=None, unet=None, vae=None, controlnet=None, *, batch_size=None, img_height=None, img_width=None, height=None, width=None, sample_size=None, image_size=None, guidance_scale=None, **kwargs)

Parameters:

Name	Type	Description	Default
text_encoder	Optional[RBLNCLIPTextModelConfig]	Configuration for the primary text encoder. Initialized as RBLNCLIPTextModelConfig if not provided.	None
text_encoder_2	Optional[RBLNCLIPTextModelWithProjectionConfig]	Configuration for the secondary text encoder. Initialized as RBLNCLIPTextModelWithProjectionConfig if not provided.	None
unet	Optional[RBLNUNet2DConditionModelConfig]	Configuration for the UNet model component. Initialized as RBLNUNet2DConditionModelConfig if not provided.	None
vae	Optional[RBLNAutoencoderKLConfig]	Configuration for the VAE model component. Initialized as RBLNAutoencoderKLConfig if not provided.	None
controlnet	Optional[RBLNControlNetModelConfig]	Configuration for the ControlNet model component. Initialized as RBLNControlNetModelConfig if not provided.	None
batch_size	Optional[int]	Batch size for inference, applied to all submodules.	None
img_height	Optional[int]	Height of the generated images.	None
img_width	Optional[int]	Width of the generated images.	None
height	Optional[int]	Height of the generated images.	None
width	Optional[int]	Width of the generated images.	None
sample_size	Optional[Tuple[int, int]]	Spatial dimensions for the UNet model.	None
image_size	Optional[Tuple[int, int]]	Alternative way to specify image dimensions. Cannot be used together with img_height/img_width.	None
guidance_scale	Optional[float]	Scale for classifier-free guidance.	None
kwargs	Any	Additional arguments passed to the parent RBLNModelConfig.	{}

Raises:

Type	Description
ValueError	If both image_size and img_height/img_width are provided.

Note

When guidance_scale > 1.0, the UNet batch size is automatically doubled to accommodate classifier-free guidance.

load(path, **kwargs) classmethod

Load a RBLNModelConfig from a path.

Parameters:

Name	Type	Description	Default
path	str	Path to the RBLNModelConfig file or directory containing the config file.	required
kwargs	Any	Additional keyword arguments to override configuration values. Keys starting with 'rbln_' will have the prefix removed and be used to update the configuration.	{}

Returns:

Name	Type	Description
RBLNModelConfig	RBLNModelConfig	The loaded configuration instance.

Note

This method loads the configuration from the specified path and applies any provided overrides. If the loaded configuration class doesn't match the expected class, a warning will be logged.

RBLNStableDiffusionXLControlNetPipelineConfig

Bases: RBLNStableDiffusionXLControlNetPipelineBaseConfig

Configuration for Stable Diffusion XL ControlNet pipeline.

Functions

__init__(text_encoder=None, text_encoder_2=None, unet=None, vae=None, controlnet=None, *, batch_size=None, img_height=None, img_width=None, height=None, width=None, sample_size=None, image_size=None, guidance_scale=None, **kwargs)

Parameters:

Name	Type	Description	Default
text_encoder	Optional[RBLNCLIPTextModelConfig]	Configuration for the primary text encoder. Initialized as RBLNCLIPTextModelConfig if not provided.	None
text_encoder_2	Optional[RBLNCLIPTextModelWithProjectionConfig]	Configuration for the secondary text encoder. Initialized as RBLNCLIPTextModelWithProjectionConfig if not provided.	None
unet	Optional[RBLNUNet2DConditionModelConfig]	Configuration for the UNet model component. Initialized as RBLNUNet2DConditionModelConfig if not provided.	None
vae	Optional[RBLNAutoencoderKLConfig]	Configuration for the VAE model component. Initialized as RBLNAutoencoderKLConfig if not provided.	None
controlnet	Optional[RBLNControlNetModelConfig]	Configuration for the ControlNet model component. Initialized as RBLNControlNetModelConfig if not provided.	None
batch_size	Optional[int]	Batch size for inference, applied to all submodules.	None
img_height	Optional[int]	Height of the generated images.	None
img_width	Optional[int]	Width of the generated images.	None
height	Optional[int]	Height of the generated images.	None
width	Optional[int]	Width of the generated images.	None
sample_size	Optional[Tuple[int, int]]	Spatial dimensions for the UNet model.	None
image_size	Optional[Tuple[int, int]]	Alternative way to specify image dimensions. Cannot be used together with img_height/img_width.	None
guidance_scale	Optional[float]	Scale for classifier-free guidance.	None
kwargs	Any	Additional arguments passed to the parent RBLNModelConfig.	{}

Raises:

Type	Description
ValueError	If both image_size and img_height/img_width are provided.

Note

When guidance_scale > 1.0, the UNet batch size is automatically doubled to accommodate classifier-free guidance.

load(path, **kwargs) classmethod

Load a RBLNModelConfig from a path.

Parameters:

Name	Type	Description	Default
path	str	Path to the RBLNModelConfig file or directory containing the config file.	required
kwargs	Any	Additional keyword arguments to override configuration values. Keys starting with 'rbln_' will have the prefix removed and be used to update the configuration.	{}

Returns:

Name	Type	Description
RBLNModelConfig	RBLNModelConfig	The loaded configuration instance.

Note

This method loads the configuration from the specified path and applies any provided overrides. If the loaded configuration class doesn't match the expected class, a warning will be logged.

RBLNStableDiffusionXLControlNetImg2ImgPipelineConfig

Bases: RBLNStableDiffusionXLControlNetPipelineBaseConfig

Configuration for Stable Diffusion XL ControlNet image-to-image pipeline.

Functions

__init__(text_encoder=None, text_encoder_2=None, unet=None, vae=None, controlnet=None, *, batch_size=None, img_height=None, img_width=None, height=None, width=None, sample_size=None, image_size=None, guidance_scale=None, **kwargs)

Parameters:

Name	Type	Description	Default
text_encoder	Optional[RBLNCLIPTextModelConfig]	Configuration for the primary text encoder. Initialized as RBLNCLIPTextModelConfig if not provided.	None
text_encoder_2	Optional[RBLNCLIPTextModelWithProjectionConfig]	Configuration for the secondary text encoder. Initialized as RBLNCLIPTextModelWithProjectionConfig if not provided.	None
unet	Optional[RBLNUNet2DConditionModelConfig]	Configuration for the UNet model component. Initialized as RBLNUNet2DConditionModelConfig if not provided.	None
vae	Optional[RBLNAutoencoderKLConfig]	Configuration for the VAE model component. Initialized as RBLNAutoencoderKLConfig if not provided.	None
controlnet	Optional[RBLNControlNetModelConfig]	Configuration for the ControlNet model component. Initialized as RBLNControlNetModelConfig if not provided.	None
batch_size	Optional[int]	Batch size for inference, applied to all submodules.	None
img_height	Optional[int]	Height of the generated images.	None
img_width	Optional[int]	Width of the generated images.	None
height	Optional[int]	Height of the generated images.	None
width	Optional[int]	Width of the generated images.	None
sample_size	Optional[Tuple[int, int]]	Spatial dimensions for the UNet model.	None
image_size	Optional[Tuple[int, int]]	Alternative way to specify image dimensions. Cannot be used together with img_height/img_width.	None
guidance_scale	Optional[float]	Scale for classifier-free guidance.	None
kwargs	Any	Additional arguments passed to the parent RBLNModelConfig.	{}

Raises:

Type	Description
ValueError	If both image_size and img_height/img_width are provided.

Note

When guidance_scale > 1.0, the UNet batch size is automatically doubled to accommodate classifier-free guidance.

load(path, **kwargs) classmethod

Load a RBLNModelConfig from a path.

Parameters:

Name	Type	Description	Default
path	str	Path to the RBLNModelConfig file or directory containing the config file.	required
kwargs	Any	Additional keyword arguments to override configuration values. Keys starting with 'rbln_' will have the prefix removed and be used to update the configuration.	{}

Returns:

Name	Type	Description
RBLNModelConfig	RBLNModelConfig	The loaded configuration instance.

Note

This method loads the configuration from the specified path and applies any provided overrides. If the loaded configuration class doesn't match the expected class, a warning will be logged.