fTh+SrSSKJrJr SSKJr SSKJrJrJ r SSK J r J r J r Jr SSKJrJr SSKJr \R("\5r"S S \ S S 9rS \4SjrSr"SS\ 5rS/rg)z Processor class for Pixtral. )ListUnion) BatchFeature) ImageInputis_valid_image load_image)ProcessingKwargsProcessorMixinUnpack!_validate_images_text_input_order)PreTokenizedInput TextInput)loggingc(\rSrSrSS00SS0S.rSrg) PixtralProcessorKwargspaddingFreturn_tensorspt) text_kwargs images_kwargs common_kwargsN)__name__ __module__ __qualname____firstlineno__ _defaults__static_attributes__rf/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/pixtral/processing_pixtral.pyrrs$ u  d Ir!rF)totalreturncR[U[5=(a URS5$)Nhttp) isinstancestr startswith)vals r"is_urlr+,s c3  :CNN6$::r!c<[U5=(d [U5$N)r+r)elems r"is_image_or_image_urlr/1s $< />$//r!c ^\rSrSrSrSS/r/SQrSrSrSS\ S \ 4U4S jjjr SS \ S \ \ \\\ \\4S \\S\4SjjrSrSr\S5rSrU=r$)PixtralProcessor5a Constructs a Pixtral processor which wraps a Pixtral image processor and a Pixtral tokenizer into a single processor. [`PixtralProcessor`] offers all the functionalities of [`CLIPImageProcessor`] and [`LlamaTokenizerFast`]. See the [`~PixtralProcessor.__call__`] and [`~PixtralProcessor.decode`] for more information. Args: image_processor ([`PixtralImageProcessor`], *optional*): The image processor is a required input. tokenizer ([`LlamaTokenizerFast`], *optional*): The tokenizer is a required input. patch_size (`int`, *optional*, defaults to 16): Patch size from the vision tower. spatial_merge_size (`int`, *optional*, defaults to 1): The downsampling factor for the spatial merge operation. chat_template (`str`, *optional*): A Jinja template which will be used to convert lists of messages in a chat into a tokenizable string. image_token (`str`, *optional*, defaults to `"[IMG]"`): Special token used to denote image location. image_break_token (`str`, *optional*, defaults to `"[IMG_BREAK]"`): Special token used to denote the end of a line of pixels in an image. image_end_token (`str`, *optional*, defaults to `"[IMG_END]"`): Special token used to denote the end of an image input. image_processor tokenizer) chat_template patch_sizespatial_merge_size image_tokenimage_break_tokenimage_end_tokenAutoImageProcessor AutoTokenizerr6r7c  >X0lX@lX`lURUR5UlXplXl[T U]!XUS9 g)N)r5) r6r7r8convert_tokens_to_idsimage_token_idr9r:super__init__) selfr3r4r6r7r5r8r9r:kwargs __class__s r"rAPixtralProcessor.__init__[sM%"4&'==d>N>NO!2. =Qr!imagestextrCr$c [X5upUR"[4SURR0UD6nUR UR -nUGb[U5(aU/nO[U[[45(a[US5(aOw[U[[45(aQ[US[[45(a3[USS5(aUVV s/sH oHoPM M nnn O [S5eUV s/sH%n [U [5(a [U 5OU PM' nn UR"U4SU0USD6n O0n [U[5(aU/nO8[U[5(d#[US[5(d [S5eUn U RS5Gb'[!U S 5n /n /nUGHnUR"U;a[%U 5unnUU-nUU-nUR"/U-UR&/-/U-nUVVs/sHoHnUPM M nnnUR(US 'S R+U5nUR-U5 UR/UR"S S 5nUR"U;aMS U;a,UR1S5nUR/S US 5nS U;aM,U R-U5 GM USR1SS5nUR"U 40USD6nUR3U US/S9 [50UEU EUS9$s sn nfs sn fs snnf)a Main method to prepare for the model one or several sequences(s) and image(s). This method forwards the `text` and `kwargs` arguments to LlamaTokenizerFast's [`~LlamaTokenizerFast.__call__`] if `text` is not `None` to encode the text. To prepare the image(s), this method forwards the `images` and `kwrags` arguments to CLIPImageProcessor's [`~CLIPImageProcessor.__call__`] if `images` is not `None`. Please refer to the docstring of the above two methods for more information. Args: images (`PIL.Image.Image`, `np.ndarray`, `torch.Tensor`, `List[PIL.Image.Image]`, `List[np.ndarray]`, `List[torch.Tensor]`): The image or batch of images to be prepared. Each image can be a PIL image, NumPy array or PyTorch tensor. Both channels-first and channels-last formats are supported. text (`str`, `List[str]`, `List[List[str]]`): The sequence or batch of sequences to be encoded. Each sequence can be a string or a list of strings (pretokenized string). If the sequences are provided as list of strings (pretokenized), you must set `is_split_into_words=True` (to lift the ambiguity with a batch of sequences). return_tensors (`str` or [`~utils.TensorType`], *optional*): If set, will return tensors of a particular framework. Acceptable values are: - `'tf'`: Return TensorFlow `tf.constant` objects. - `'pt'`: Return PyTorch `torch.Tensor` objects. - `'np'`: Return NumPy `np.ndarray` objects. - `'jax'`: Return JAX `jnp.ndarray` objects. Returns: [`BatchFeature`]: A [`BatchFeature`] with the following fields: - **input_ids** -- List of token ids to be fed to a model. Returned when `text` is not `None`. - **attention_mask** -- List of indices specifying which tokens should be attended to by the model (when `return_attention_mask=True` or if *"attention_mask"* is in `self.model_input_names` and if `text` is not `None`). - **pixel_values** -- Pixel values to be fed to a model. Returned when `images` is not `None`. tokenizer_init_kwargsNrzdInvalid input images. Please provide a single image, a list of images, or a list of lists of images.r6rzAInvalid input text. Please provide a string, or a list of strings pixel_values image_sizesz rrimage) modalities)data tensor_type)r _merge_kwargsrr4 init_kwargsr6r7r/r'listtuple ValueErrorr(r r3getiterr8nextr9r:joinappendreplacepop_check_special_mm_tokensr)rBrFrGaudiovideosrC output_kwargsr6sublistrOim image_inputsprompt_stringsrKreplace_stringssampleheightwidthnum_height_tokensnum_width_tokensreplace_tokensitem replace_strr text_inputss r"__call__PixtralProcessor.__call__osTR9F ** " "&.."<"<  __t'>'>>  $V,, FT5M227LVTUY7W7W6D%=11vay4-88)&)A,77/5KvG7%%7%vK zOUUf 2s(;(;jnCfFU//p:pQ^_nQopLL dC 6DD$'' 47C0H0H`a a   N + 7|M:;KN O&&&0$($5MFE(.*(<%', ':$))*-==AWAW@XX&)&*N;I%].wU\TdU\d.N%])-)=)=N2&"$''."9K#**;7#^^D,<,!% @ @&*&:&:&L&L#DMM"7"UVWWr!)r9r:r8r?r6r7)NNrNNz[IMG]z [IMG_BREAK]z [IMG_END])NNNN)rrrr__doc__ attributes valid_kwargsimage_processor_classtokenizer_classintrArrrrrr rrrqrtrypropertyr|r __classcell__)rDs@r"r1r15s2$[1JL1%O"#'#R R  RR,"^b k^k^I0$y/4HYCZZ[k^ /0 k^ k^\<6XXr!r1N)rtypingrrfeature_extraction_utilsr image_utilsrrr processing_utilsr r r r tokenization_utils_baserrutilsr get_loggerrloggerrboolr+r/r1__all__rr!r"rsq4AAkkC   H % -U ;4; 0|X~|X~  r!