+h>#|SSKrSSKrSSKJrJrJrJrJr SSKrSSK J r SSK J r J r \ "5(aOSSKrSSKJr SSKJr \ "5(aSSKr\R*\R,\R.\R0S .rSS KJr S \S \4S jrS+S\SSS\\SS\S\\ S\\ S\SS\SS\SS\S\SS\SS\\!S \\!4S!jjr"S,S"\RFS\\SS\SS\SS\4 S#jjr$S-SSS\\SS\S\\ S\\ S\SS\SS\S\\!S \\!4S$jjr%S+S\SSS\\SS\S\\ S\\ S\SS\SS\SS\S\SS\SS\\!S \\!S \\R6\\R6\S44S%jjr&S.S\S&\S\R64S\\ S\\ 4S'jjr'S"\RF4S(jr(S.S&\S\R64S\\ S\\ 4S)jjr)S.S\S&\S\R64S\\ S\\ S S4 S*jjr*g)/N)ListLiteralOptionalUnioncast) deprecate)is_safetensors_availableis_torch_available)VaeImageProcessor)VideoProcessor)float16float32bfloat16uint8)ImagedatareturncURS5(agURS5(agURS5(dURS5(agURS5(ag g ) NsjpegsPNG  pngsGIF87asGIF89agifsBMbmpunknown) startswith)rs V/home/james-whalen/.local/lib/python3.13/site-packages/diffusers/utils/remote_utils.pydetect_image_typer.s\ {## - . .  # #ty'A'A    binaryendpointtensorz torch.Tensor processor)r r do_scalingscaling_factor shift_factor output_type)mp4pilpt return_type image_format)rjpgpartial_postprocessinput_tensor_typeoutput_tensor_typeheightwidthcURS:XaU cU c [S5eUS:Xa3US:Xa-U (d&[U[[45(d [S5eU(aUc [ SSSS S 9 ggg) Nz1`height` and `width` required for packed latents.r*r)z`processor` is required.r$1.0.0zQ`do_scaling` is deprecated, pass `scaling_factor` and `shift_factor` if required.F standard_warn)ndim ValueError isinstancer rr )r!r"r#r$r%r&r'r+r,r.r/r0r1r2s rcheck_inputs_decoder;:sy {{aFNu}LMMt 5 #9'8.&IJJ344n,   _  -zrresponsecUS:Xd US:XaoUblURnURn[R"US5nUSn[Un [ R "[U5U S9RU5nUS:XaU(aZUS:XaJWV s/sH'n [R"U R55PM) n n [U 5S:XaU Sn U $US:XaWn W $UbUS:XaWn U $[U[5(a4[[ [RUR#WSS9S5n U $[[RUR%WSS9S5n U $US:XaiUS:XacUc`[R&"[(R*"UR55R-S 5n [/UR5n XlU $US:XaUbUS:XavWR3SS S S5R55R5S -R75R9S 5V s/sHn [R"U 5PM n n U $US:XaWn W $US:XaUS:Xa URn W $s sn fs sn f)Nr*r)shapedtyper?rr)r'RGBr r4rr()contentheadersjsonloads DTYPE_MAPtorch frombuffer bytearrayreshaper fromarraynumpylenr:rrrpostprocess_video postprocessopenioBytesIOconvertrformatpermutefloatroundastype) r<r#r'r+r. output_tensor parametersr>r? torch_dtypeimageoutputdetected_formats rpostprocess_decoder`\sd{e3 8M (( %%  :g./7#& ((=)AU]]^cd d e#FSTmU%//%++-8mTv;!##AYF> M=$&: M7 K4$7&4 M1i88!U[[)!33Mu3UVWXF. 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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. 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. Returns: output (`Image.Image` or `List[Image.Image]` or `bytes` or `torch.Tensor`). base64zinput_tensor_type='base64'r5z9input_tensor_type='base64' is deprecated. Using `binary`.Fr6r zoutput_tensor_type='base64'z:output_tensor_type='base64' is deprecated. 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