diffusers/pr_12652/zh/hybrid_inference/api_reference.md

混合推理 API 参考

远程解码[[diffusers.utils.remote_decode]]

diffusers.utils.remote_decode[[diffusers.utils.remote_decode]]

Source

Hugging Face Hybrid Inference that allow running VAE decode remotely.

Parameters:

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. - 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 bytesof video."pil": Supported by image and video models. Image models: Endpoint returns bytesof an image inimage_format. Video models: Endpoint returns torch.Tensorwith partialpostprocessingapplied. Requiresprocessoras a flag (anyNonevalue will work)."pt": Support by image and video models. Endpoint returns torch.Tensor. With partial_postprocess=Truethe tensor is postprocesseduint8image tensor. Recommendations:"pt"withpartial_postprocess=Trueis the smallest transfer for full quality."pt"withpartial_postprocess=Falseis the most compatible with third party code."pil"withimage_format="jpg"` is the smallest transfer overall.

return_type ("mp4" or "pil" or "pt", default "pil") : Function return type. "mp4": Function returns bytesof video."pil": Function returns PIL.Image.Image. With output_type="pil" no further processing is applied. With output_type="pt" a PIL.Image.Imageis created.partial_postprocess=False processoris required.partial_postprocess=True processoris **not** required."pt": Function returns torch.Tensor. processoris **not** required.partial_postprocess=Falsetensor isfloat16orbfloat16, without denormalization. partial_postprocess=Truetensor isuint8`, denormalized.

image_format ("png" or "jpg", default jpg) : Used with output_type="pil". Endpoint returns jpg or png.

partial_postprocess (bool, default False) : Used with output_type="pt". partial_postprocess=False tensor is float16 or bfloat16, without denormalization. partial_postprocess=True tensor is uint8, denormalized.

input_tensor_type ("binary", default "binary") : Tensor transfer type.

output_tensor_type ("binary", default "binary") : Tensor transfer type.

height (int, optional) : Required for "packed" latents.

width (int, optional) : Required for "packed" latents.

Returns:

output (Image.Image or list[Image.Image] or bytes or torch.Tensor).

远程编码[[diffusers.utils.remote_utils.remote_encode]]

diffusers.utils.remote_utils.remote_encode[[diffusers.utils.remote_utils.remote_encode]]

Source

Hugging Face Hybrid Inference that allow running VAE encode remotely.

Parameters:

endpoint (str) : Endpoint for Remote Decode.

image (torch.Tensor or PIL.Image.Image) : Image to be encoded.

scaling_factor (float, optional) : Scaling is applied when passed e.g. latents * self.vae.config.scaling_factor. - 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.

Returns:

output (torch.Tensor).