rh4dZddlmZddlZddlmZddlmZm Z m Z ddl m Z m Z mZmZddlmZmZdd lmZmZerd d lmZej0eZGd d e dZdefdZdZGddeZdgZ y)z Processor class for Pixtral. )UnionN) BatchFeature) ImageInputis_valid_image load_image)MultiModalDataProcessingKwargsProcessorMixinUnpack)PreTokenizedInput TextInput)is_vision_availablelogging)get_resize_output_image_sizec"eZdZdddiddidZy)PixtralProcessorKwargsF)paddingreturn_mm_token_type_idsreturn_tensorspt) text_kwargs images_kwargs common_kwargsN)__name__ __module__ __qualname__ _defaults/var/www/html/ai-insurance-compliance-backend/venv/lib/python3.12/site-packages/transformers/models/pixtral/processing_pixtral.pyrr*s%(-  d Ir!rF)totalreturncHt|txr|jdS)Nhttp) isinstancestr startswith)vals r"is_urlr+8s c3  :CNN6$::r!c2t|xs t|SN)r+r)elems r"is_image_or_image_urlr/=s $< />$//r!c eZdZdZddgZdZdZ ddedeffd Z dd e d e e e e e e e fd eed efd ZddZdZdZedZxZS)PixtralProcessorab 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 tokenizerAutoImageProcessor AutoTokenizer patch_sizespatial_merge_sizec  ||_||_||_|j|j|_||_||_|j|j|_|j|j |_|j|j |_|j|j|jg|_ t |-|||y)N) chat_template) r6r7 image_tokenconvert_tokens_to_idsimage_token_idimage_break_tokenimage_end_tokenimage_break_token_idimage_end_token_id image_idssuper__init__) selfr2r3r6r7r9r:r=r>kwargs __class__s r"rCzPixtralProcessor.__init___s%"4&'==d>N>NO!2.'==d>N>NO$-$C$CDDZDZ$[!"+"A"A$BVBV"W--t/H/H$JaJab )=Qr!imagestextrEr$c |jtfd|jji|}|j|j z}|t |r|g}nt|ttfrt |drndt|ttfrCt|dttfr*t |ddr|D cgc] }|D]} |  }}} n td|D cgc]} t| tr t| n| !}} |j|fd|i|d} ni} t|tr|g}n.t|tst|dts td|} | jdt!| d } g} g}|D]}|j"|vrt%| \}}||z}||z}|j"g|z|j&gzg|z}|Dcgc] }|D]}| }}}|j(|d <d j+|}|j-||j/|j"d d }|j"|vrd |vr)|j1d}|j/d |d }d |vr)| j-||dj1dd}|dj1dd}|j| fi|dddi}|j3| |dg|rft5j6|d}t5j8|d}d |t5j:||j<<|j?|d<tAi|| |Scc} }wcc} wcc}}w)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 rrrrFimage) modalities input_idsmm_token_type_ids)data tensor_type)! _merge_kwargsrr3 init_kwargsr6r7r/r'listtuple ValueErrorr(rr2 TypeErrorgetiterr:nextr=r>joinappendreplacepop_check_special_mm_tokensnparray zeros_likeisinrAtolistr)rDrGrHaudiovideosrE output_kwargsr6sublistrOim image_inputsprompt_stringsrLreplace_stringssampleheightwidthnum_height_tokensnum_width_tokensreplace_tokensitem replace_strrr text_inputs array_idsrRs r"__call__zPixtralProcessor.__call__wsR+** " "&.."<"<  __t'>'>>  $V, FT5M27LVTUY7W6D%=1vay4-8)&)A,7/5KG7K%%K%KK zOUU 2s(;jnCUFU/4//p:pQ^_nQopLL dC 6DD$' 47C0H_` `   N + 7|M:;KN O .&&&0$($5MFE(.*(<%', ':$))*-==AWAW@XX&)&*N;I%]wU\%]Td%]d%]N%])-)=)=N2&"$''."9K#**;7#^^D,<,  '')9A)=AR(RS T"#c+&6 6    4D[lm n, ,,r!c:|jj|i|S)z This method forwards all its arguments to LlamaTokenizerFast's [`~PreTrainedTokenizer.batch_decode`]. Please refer to the docstring of this method for more information. )r3 batch_decoderDargsrEs r"rzPixtralProcessor.batch_decodes +t~~**D;F;;r!c:|jj|i|S)z This method forwards all its arguments to LlamaTokenizerFast's [`~PreTrainedTokenizer.decode`]. Please refer to the docstring of this method for more information. )r3decoders r"rzPixtralProcessor.decodes %t~~$$d5f55r!c|jj}|jj}ttj ||zSr-)r3model_input_namesr2rWdictfromkeys)rDtokenizer_input_namesimage_processor_input_namess r"rz"PixtralProcessor.model_input_namessA!% @ @&*&:&:&L&L#DMM"7:U"UVWWr!)NNrNz[IMG]z [IMG_BREAK]z [IMG_END])NNNNr-)rrr__doc__ attributesimage_processor_classtokenizer_classintrCrrrr rWr rrrzrrrpropertyr __classcell__)rFs@r"r1r1As2$[1J0%O"#'#R R  R4"^b q^q^I0$y/4HYCZZ[q^ /0 q^ q^f"-J<6XXr!r1)!rtypingrnumpyrcfeature_extraction_utilsr image_utilsrrrprocessing_utilsr r r r tokenization_utils_baser rutilsrrimage_processing_pixtralr get_loggerrloggerrboolr+r/r1__all__r r!r"rs4AA D1F   H % -U ;4; 0bX~bXJ  r!