Function remote_decode

src/diffusers/utils/remote_utils.py:190–336

Hugging Face Hybrid Inference that allow running VAE decode remotely. Args: endpoint (`str`): Endpoint for Remote Decode. tensor (`torch.Tensor`): Tensor to be decoded. processor (`VaeImageProcessor` or `VideoProcessor`, *optional*):

(
    endpoint: str,
    tensor: "torch.Tensor",
    processor: "VaeImageProcessor" | "VideoProcessor" | None = None,
    do_scaling: bool = True,
    scaling_factor: float | None = None,
    shift_factor: float | None = None,
    output_type: Literal["mp4", "pil", "pt"] = "pil",
    return_type: Literal["mp4", "pil", "pt"] = "pil",
    image_format: Literal["png", "jpg"] = "jpg",
    partial_postprocess: bool = False,
    input_tensor_type: Literal["binary"] = "binary",
    output_tensor_type: Literal["binary"] = "binary",
    height: int | None = None,
    width: int | None = None,
)

def remote_decode(
    endpoint: str,
    tensor: "torch.Tensor",
    processor: "VaeImageProcessor" | "VideoProcessor" | None = None,
    do_scaling: bool = True,
    scaling_factor: float | None = None,
    shift_factor: float | None = None,
    output_type: Literal["mp4", "pil", "pt"] = "pil",
    return_type: Literal["mp4", "pil", "pt"] = "pil",
    image_format: Literal["png", "jpg"] = "jpg",
    partial_postprocess: bool = False,
    input_tensor_type: Literal["binary"] = "binary",
    output_tensor_type: Literal["binary"] = "binary",
    height: int | None = None,
    width: int | None = None,
) -> Image.Image | list[Image.Image] | bytes | "torch.Tensor":
    """
    Hugging Face Hybrid Inference that allow running VAE decode remotely.

    Args:
        endpoint (`str`):
            Endpoint for Remote Decode.
        tensor (`torch.Tensor`):
            Tensor to be decoded.
        processor (`VaeImageProcessor` or `VideoProcessor`, *optional*):
            Used with `return_type="pt"`, and `return_type="pil"` for Video models.
        do_scaling (`bool`, default `True`, *optional*):
            **DEPRECATED**. **pass `scaling_factor`/`shift_factor` instead.** **still set
            do_scaling=None/do_scaling=False for no scaling until option is removed** When `True` scaling e.g. `latents
            / self.vae.config.scaling_factor` is applied remotely. If `False`, input must be passed with scaling
            applied.
        scaling_factor (`float`, *optional*):
            Scaling is applied when passed e.g. [`latents /
            self.vae.config.scaling_factor`](https://github.com/huggingface/diffusers/blob/7007febae5cff000d4df9059d9cf35133e8b2ca9/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py#L1083C37-L1083C77).
            - SD v1: 0.18215
            - SD XL: 0.13025
            - Flux: 0.3611
            If `None`, input must be passed with scaling applied.
        shift_factor (`float`, *optional*):
            Shift is applied when passed e.g. `latents + self.vae.config.shift_factor`.
            - Flux: 0.1159
            If `None`, input must be passed with scaling applied.
        output_type (`"mp4"` or `"pil"` or `"pt", default `"pil"):
            **Endpoint** output type. Subject to change. Report feedback on preferred type.

            `"mp4": Supported by video models. Endpoint returns `bytes` of video. `"pil"`: Supported by image and video
            models.
                Image models: Endpoint returns `bytes` of an image in `image_format`. Video models: Endpoint returns
                `torch.Tensor` with partial `postprocessing` applied.
                    Requires `processor` as a flag (any `None` value will work).
            `"pt"`: Support by image and video models. Endpoint returns `torch.Tensor`.
                With `partial_postprocess=True` the tensor is postprocessed `uint8` image tensor.

            Recommendations:
                `"pt"` with `partial_postprocess=True` is the smallest transfer for full quality. `"pt"` with
                `partial_postprocess=False` is the most compatible with third party code. `"pil"` with
                `image_format="jpg"` is the smallest transfer overall.