3j>SSKJr SSKrSSKrSSKJrJr SSKrSSKJ r SSK J r J r \ "5(aOSSK r SSKJr SS KJr \ "5(aSSKr\ R(\ R*\ R,\ R.S .rSS KJr SS jrSSS jjrSSSjjrSSSjjrSSSjjrSSSjjr SSjr!SS Sjjr"SS!Sjjr#g)") annotationsN)Literalcast) deprecate)is_safetensors_availableis_torch_available)VaeImageProcessor)VideoProcessor)float16float32bfloat16uint8)ImagecURS5(agURS5(agURS5(dURS5(agURS5(ag g ) NsjpegsPNG  pngsGIF87asGIF89agifsBMbmpunknown) startswith)datas V/home/wildlama/miniconda3/lib/python3.13/site-packages/diffusers/utils/remote_utils.pydetect_image_typer0s\ {## - . .  # #ty'A'A    cURS: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.ptpilz`processor` is required. do_scaling1.0.0zQ`do_scaling` is deprecated, pass `scaling_factor` and `shift_factor` if required.F standard_warn)ndim ValueError isinstancer r r)endpointtensor processorr!scaling_factor shift_factor output_type return_type image_formatpartial_postprocessinput_tensor_typeoutput_tensor_typeheightwidths rcheck_inputs_decoder5<sy {{aFNu}LMMt 5 #9'8.&IJJ344n,   _  -zrcUS: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 $s sn fs sn f)Nrr shapedtyper8rr)r-RGBr rrmp4)contentheadersjsonloads DTYPE_MAPtorch frombuffer bytearrayreshaper fromarraynumpylenr'r rlistpostprocess_video postprocessopenioBytesIOconvertrformatpermutefloatroundastype) responser*r-r.r0 output_tensor parametersr7r8 torch_dtypeimageoutputdetected_formats rpostprocess_decoder\^sd{e3 8M (( %%  :g./7#& ((=)AU]]^cd d e#FSTmU%//%++-8mTv;!##AYF> M=$&: M7 K4$7&4 M1i88!U[[)!33Mu3UVWXF. M%" !--m-OPQRF$ M  +"69;LBJJx'7'789AA%H+H,<,<='  M  )"7 % ,33Aq!Q?EEGMMORUU\\^eefmnnE&n  M D "F M  +"6!! MCU2s .I?7 Jc 0n UUU[UR5[UR5R S5SS.n U(aUbX;S'U(aUbXKS'U(aUcX+S'OU(a UcUcX+S'Ub U bXS'XS'S U S 'S U S 'US :XaUS :Xa UcSU S 'O US :XaUS:Xa UcSU S 'O US:XaSU S '[ R RUS5n XU S.$)N.)r/r-r0r7r8r+r,r!r3r4z tensor/binaryz Content-TypeAcceptr jpgz image/jpegrz image/pngr<z text/plainr)rparamsr>)rIr7strr8split safetensorsrB_tobytes) r)r*r!r+r,r-r/r0r3r4r>rW tensor_datas rprepare_decoderis)G$"2fll#V\\"((-b1 Jn0'5#$l.%1>"n,#-< .<3G#-<  e/%8#7-GN'GHe  5):K(  ,%"7IK' JJrcFU S:Xa[SSSSS9 Sn U S:Xa[SSS SS9 Sn [UUUUUUUUUU U U U U 5 [UUUUUUUU U U S 9 n[R"U40UD6nUR (d[ UR55e[UUUUU S 9nU$) aQ 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. 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'r"z9input_tensor_type='base64' is deprecated. Using `binary`.Fr#binaryzoutput_tensor_type='base64'z:output_tensor_type='base64' is deprecated. Using `binary`.) r)r*r!r+r,r-r/r0r3r4)rUr*r-r.r0) rr5rirequestspostok RuntimeErrorr?r\)r(r)r*r!r+r,r-r.r/r0r1r2r3r4kwargsrUrZs r remote_decoderrsxH$ (  G  %X% )  H  &  %!!/ F}}X00H ;;8==?++ / F Mrcg)N)r(rYr+r,s rcheck_inputs_encoderuSs  rcURnURn[R"US5nUSn[Un[ R "[U5US9RU5nU$)Nr7r8r9) r=r>r?r@rArBrCrDrE)rUrVrWr7r8rXs rpostprocess_encoderw\sj$$M!!J JJz'* +E w EE"K$$Y}%=[QYYZ_`M rc0n0nUbXS'UbX$S'[U[R5(aq[RR UR 5S5n[ UR5US'[UR5RS5SUS'O5[R"5nURUSS 9 UR5nXTUS .$) Nr+r,r)r7r^r_r8PNG)rPrb)r'rBTensorrfrg contiguousrIr7rdr8rerMrNsavegetvalue)rYr+r,r>rWrbuffers rprepare_encoderhs GJ!'5#$%1>"%&&  ))%*:*:*rsi # (F30!! ====NN I @D#'!%/4/4*/ %+3,4   =   !    - - (  ) *     H@D/4/4 % 22<2-2- 2  2n@D#'!%/4*/ %(K (K<(K(K! (K  (K - (K((K(K (K (K\@D#'!%/4/4*/ %+3,4RR R=R R ! R  R-R-R(RR)R*R R R>Rp$(!%   ' !     $(!%D 'D DD2$(!% -- '-!- -  -r