Buckets:
| # Remote inference | |
| Remote inference provides access to an [Inference Endpoint](https://huggingface.co/docs/inference-endpoints/index) to offload local generation requirements for decoding and encoding. | |
| ## remote_decode[[diffusers.utils.remote_decode]] | |
| - **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. | |
| - **return_type** (`"mp4"` or `"pil"` or `"pt", default `"pil") -- | |
| **Function** return type. | |
| `"mp4": Function returns `bytes` of video. `"pil"`: Function returns `PIL.Image.Image`. | |
| With `output_type="pil" no further processing is applied. With `output_type="pt" a `PIL.Image.Image` is | |
| created. | |
| `partial_postprocess=False` `processor` is required. `partial_postprocess=True` `processor` is | |
| **not** required. | |
| `"pt"`: Function returns `torch.Tensor`. | |
| `processor` is **not** required. `partial_postprocess=False` tensor is `float16` or `bfloat16`, without | |
| denormalization. `partial_postprocess=True` tensor is `uint8`, 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.output (`Image.Image` or `list[Image.Image]` or `bytes` or `torch.Tensor`). | |
| Hugging Face Hybrid Inference that allow running VAE decode remotely. | |
| ## remote_encode[[diffusers.utils.remote_utils.remote_encode]] | |
| - **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.output (`torch.Tensor`). | |
| Hugging Face Hybrid Inference that allow running VAE encode remotely. | |
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