fTh-!SrSSKJrJr SSKJr SSKJr SSKJ r J r J r J r SSK JrJr SSKJr \R$"\5rS r"S S \ S S 9r"SS\ S S 9r"SS\ 5rS/rg)z Processor class for Janus. )ListUnion) BatchFeature) ImageInput)ProcessingKwargsProcessorMixin TextKwargsUnpack)PreTokenizedInput TextInput)loggingzYou are a helpful language and vision assistant. You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language. c \rSrSr%\\S'Srg)JanusTextKwargs(generation_modeN)__name__ __module__ __qualname____firstlineno__str__annotations____static_attributes__rb/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/janus/processing_janus.pyrr(srrF)totalc4\rSrSr%\\S'SSS.SS0S.rS rg ) JanusProcessorKwargs, text_kwargsFtext)paddingrreturn_tensorspt)r! common_kwargsrN)rrrrrr _defaultsrrrrrr,s  #(VD*D1Irrc ^\rSrSrSrSS/rSS/rSrSrSU4S jjr SS \ \ \ \ \ \ \ 4S \S \\S \4SjjrSrSrS \4Sjr\S5rSrU=r$)JanusProcessor4a Constructs a Janus processor which wraps a Janus Image Processor and a Llama tokenizer into a single processor. [`JanusProcessor`] offers all the functionalities of [`JanusImageProcessor`] and [`LlamaTokenizerFast`]. See the [`~JanusProcessor.__call__`] and [`~JanusProcessor.decode`] for more information. Args: image_processor ([`JanusImageProcessor`]): The image processor is a required input. tokenizer ([`LlamaTokenizerFast`]): The tokenizer is a required input. chat_template (`str`, *optional*): A Jinja template which will be used to convert lists of messages in a chat into a tokenizable string. use_default_system_prompt (`str`, *optional*, defaults to `False`): Use default system prompt for Text Generation. image_processor tokenizer chat_templateuse_default_system_promptJanusImageProcessorLlamaTokenizerFastc >SUlURUlURUlURUlX@l[TU]!XUS9 g)Ni@)r-) num_image_tokens image_token boi_tokenimage_start_token eoi_tokenimage_end_tokenr.super__init__)selfr+r,r-r.kwargs __class__s rr9JanusProcessor.__init__KsM #$00!*!4!4(22)B& =Qrr"imagesr;returnc UR"[4SURR0UD6nUcUc [ S5eUbV[ U[ 5(aU/nO=[ U[[45(a[SU55(d [ S5eUSRS5n/nURURUR--UR-n UHdn U RURU 5n UR (aUS:Xa ["U -n US:XaXR- n UR%U 5 Mf UR"U40USD6n Ub#US:waUR&"S S U0US D6S U S '[)U S 9$)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 JanusImageProcessor's [`~JanusImageProcessor.__call__`] if `images` is not `None`. Please refer to the doctsring of the above two methods for more information. Args: 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). 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. 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_kwargsz'You must specify either text or images.c3B# UHn[U[5v M g7fN) isinstancer).0ts r *JanusProcessor.__call__..s=_Z^UVjC>P>PZ^szAInvalid input text. Please provide a string, or a list of stringsr!rr"imager> images_kwargs pixel_values)datar) _merge_kwargsrr, init_kwargs ValueErrorrDrlisttupleallpopr5r3r2r7replacer.DEFAULT_SYSTEM_PROMPTappendr+r) r:r"r>videosaudior; output_kwargsrprompt_stringsone_img_tokenspromptrLs r__call__JanusProcessor.__call__TsP**  8<8R8R V\  r;s rrhJanusProcessor.postprocesss ##//A&AArcURRnURRn[[R X-55$rC)r,model_input_namesr+rPdictfromkeys)r:tokenizer_input_namesimage_processor_input_namess rrk JanusProcessor.model_input_namess< $ @ @&*&:&:&L&L#DMM"7"UVWWr)r7r5r3r2r.)NF)NNNN)rrrr__doc__ attributes valid_kwargsimage_processor_classtokenizer_classr9rr r rrr rrr]r`rerhpropertyrkr __classcell__)r<s@rr)r)4s"$[1J#%@AL1*OR_c! J'I0$y/4HYCZZ[J'J' -. J' J'X<6B*BXXrr)N)rqtypingrrfeature_extraction_utilsr image_utilsrprocessing_utilsrr r r tokenization_utils_baser r utilsr get_loggerrloggerrUrrr)__all__rrrrsz4%TT   H %Nj+5EX^EXP  r