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Stable Diffusion 3용 멀티모달 확산 트랜스포머 (MMDiT)

RBLNSD3Transformer2DModel은 Stable Diffusion 3 모델에서 사용되는 핵심 트랜스포머 블록의 RBLN 최적화 버전입니다.

이 모델은 이전 Stable Diffusion 버전에서 사용된 UNet 아키텍처를 대체합니다. 여러 텍스트 인코더의 풀링된 임베딩 및 타임스텝 정보와 함께 잠재 이미지 표현을 처리하여 확산 프로세스를 수행합니다.

Key Class

파이프라인 내 사용법

일반적으로 RBLNSD3Transformer2DModel과 직접 상호 작용하지 않습니다. 대신, RBLNStableDiffusion3Pipeline과 같은 RBLN Stable Diffusion 3 파이프라인의 일부로 자동 로드 및 관리됩니다.

RBLN SD3 파이프라인을 구성할 때 파이프라인 설정 객체의 transformer 인수를 통해 트랜스포머에 대한 특정 설정을 전달할 수 있습니다:

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from optimum.rbln import RBLNStableDiffusion3PipelineConfig

# 예시: 트랜스포머에 특정 배치 크기를 사용하여 파이프라인 구성
config = RBLNStableDiffusion3PipelineConfig(
    batch_size=1, # 파이프라인 추론 배치 크기
    img_height=1024,
    img_width=1024,
    transformer=dict(
        batch_size=2 # 트랜스포머 배치 크기 (예: CFG를 위해 2배)
    )
)

# ... 이 설정을 사용하여 파이프라인 로드 ...

트랜스포머의 배치 크기에 대한 guidance scale 영향 처리를 포함한 파이프라인 사용 및 구성에 대한 자세한 내용은 Stable Diffusion 3 파이프라인 문서를 참조하십시오.

API 참조

Classes

RBLNSD3Transformer2DModel

Bases: RBLNModel

RBLN wrapper for the Stable Diffusion 3 MMDiT Transformer model.

Functions

from_pretrained(model_id, export=False, rbln_config=None, **kwargs) classmethod

The from_pretrained() function is utilized in its standard form as in the HuggingFace transformers library. User can use this function to load a pre-trained model from the HuggingFace library and convert it to a RBLN model to be run on RBLN NPUs.

Parameters:

Name Type Description Default
model_id Union[str, Path]

The model id of the pre-trained model to be loaded. It can be downloaded from the HuggingFace model hub or a local path, or a model id of a compiled model using the RBLN Compiler.

 required
export bool

A boolean flag to indicate whether the model should be compiled.

 False
rbln_config Optional[Union[Dict, RBLNModelConfig]]

Configuration for RBLN model compilation and runtime. This can be provided as a dictionary or an instance of the model's configuration class (e.g., RBLNLlamaForCausalLMConfig for Llama models). For detailed configuration options, see the specific model's configuration class documentation.

 None
kwargs Dict[str, Any]

Additional keyword arguments. Arguments with the prefix 'rbln_' are passed to rbln_config, while the remaining arguments are passed to the HuggingFace library.

 {}

Returns:

Type Description
Self

A RBLN model instance ready for inference on RBLN NPU devices.
from_model(model, *, rbln_config=None, **kwargs) classmethod

Converts and compiles a pre-trained HuggingFace library model into a RBLN model. This method performs the actual model conversion and compilation process.

Parameters:

Name Type Description Default
model PreTrainedModel

The PyTorch model to be compiled. The object must be an instance of the HuggingFace transformers PreTrainedModel class.

 required
rbln_config Optional[Union[Dict, RBLNModelConfig]]

Configuration for RBLN model compilation and runtime. This can be provided as a dictionary or an instance of the model's configuration class (e.g., RBLNLlamaForCausalLMConfig for Llama models). For detailed configuration options, see the specific model's configuration class documentation.

 None
kwargs Dict[str, Any]

Additional keyword arguments. Arguments with the prefix 'rbln_' are passed to rbln_config, while the remaining arguments are passed to the HuggingFace library.

 {}

The method performs the following steps:

  1. Compiles the PyTorch model into an optimized RBLN graph
  2. Configures the model for the specified NPU device
  3. Creates the necessary runtime objects if requested
  4. Saves the compiled model and configurations

Returns:

Type Description
Self

A RBLN model instance ready for inference on RBLN NPU devices.
save_pretrained(save_directory)

Saves a model and its configuration file to a directory, so that it can be re-loaded using the [from_pretrained] class method.

Parameters:

Name Type Description Default
save_directory Union[str, PathLike]

The directory to save the model and its configuration files. Will be created if it doesn't exist.

 required

Classes

RBLNSD3Transformer2DModelConfig

Bases: RBLNModelConfig

Configuration class for RBLN Stable Diffusion 3 Transformer models.

Functions

__init__(batch_size=None, sample_size=None, prompt_embed_length=None, **kwargs)

Parameters:

Name Type Description Default
batch_size Optional[int]

The batch size for inference. Defaults to 1.

 None
sample_size Optional[Union[int, Tuple[int, int]]]

The spatial dimensions (height, width) of the input latent samples. If an integer is provided, it's used for both height and width.

 None
prompt_embed_length Optional[int]

The length of the embedded prompt vectors that will be used to condition the transformer model.

 None
**kwargs Dict[str, Any]

Additional arguments passed to the parent RBLNModelConfig.

 {}