
    rh                          d Z ddlmZ ddlmZ ddlmZ ddlmZm	Z	m
Z
mZ ddlmZmZ ddlmZ  ej"                  e      Zd	Z G d
 de
d      Z G d ded      Z G d de	      ZdgZy)z
Processor class for Janus.
    )Union   )BatchFeature)
ImageInput)ProcessingKwargsProcessorMixin
TextKwargsUnpack)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                       e Zd ZU eed<   y)JanusTextKwargsgeneration_modeN)__name__
__module____qualname__str__annotations__     }/var/www/html/ai-insurance-compliance-backend/venv/lib/python3.12/site-packages/transformers/models/janus/processing_janus.pyr   r   %   s    r   r   F)totalc                   ,    e Zd ZU eed<   dddddidZy)	JanusProcessorKwargstext_kwargsFtext)paddingr   return_tensorspt)r   common_kwargsN)r   r   r   r   r   	_defaultsr   r   r   r   r   )   s      #(VD*D1Ir   r   c            	            e Zd ZdZddgZdZdZd fd	Z	 	 	 	 ddee	e
ee	   ee
   f   ded	ee   d
efdZd Zd ZdefdZed        Z xZS )JanusProcessora7  
    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JanusImageProcessorLlamaTokenizerFastc                     d| _         |j                  | _        |j                  | _        |j                  | _        || _        t        | !  |||       y )Ni@  )chat_template)	num_image_tokensimage_token	boi_tokenimage_start_token	eoi_tokenimage_end_tokenuse_default_system_promptsuper__init__)selfr%   r&   r*   r1   kwargs	__class__s         r   r3   zJanusProcessor.__init__G   sQ     #$00!*!4!4(22)B&)=Qr   r   imagesr5   returnc                     | j                   t        fd| j                  j                  i|}||t	        d      |Gt        |t              r|g}n3t        |t        t        f      rt        d |D              st	        d      |d   j                  d      }g }| j                  | j                  | j                  z  z   | j                  z   }	|D ]]  }
|
j                  | j                  |	      }
| j                   r|dk(  r	t"        |
z   }
|dk(  r|
| j                  z  }
|j%                  |
       _  | j                  |fi |d   }|"|dk7  r | j&                  dd	|i|d
   d   |d<   t)        |      S )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.c              3   <   K   | ]  }t        |t                y wN)
isinstancer   ).0ts     r   	<genexpr>z*JanusProcessor.__call__.<locals>.<genexpr>   s     =_UVjC>P=_s   zAInvalid input text. Please provide a string, or a list of stringsr   r   r   imager7   images_kwargspixel_values)datar   )_merge_kwargsr   r&   init_kwargs
ValueErrorr=   r   listtupleallpopr.   r,   r+   r0   replacer1   DEFAULT_SYSTEM_PROMPTappendr%   r   )r4   r   r7   videosaudior5   output_kwargsr   prompt_stringsone_img_tokenspromptrD   s               r   __call__zJanusProcessor.__call__P   s   P +** 
8<8R8R
V\
 <FNFGG$$v e}5#=_Z^=_:_ !dee'6::;LM //43C3CdF[F[3[\_c_s_ss 	*F^^D$4$4nEF--/V2K.7')$000!!&)	* t~~nMm0LM /W"<#74#7#7#hv#hWfIg#h$D  &&r   c                 :     | j                   j                  |i |S )z
        This method forwards all its arguments to LlamaTokenizerFast's [`~PreTrainedTokenizer.batch_decode`]. Please
        refer to the docstring of this method for more information.
        )r&   batch_decoder4   argsr5   s      r   rW   zJanusProcessor.batch_decode   s     
 +t~~**D;F;;r   c                 :     | j                   j                  |i |S )z
        This method forwards all its arguments to LlamaTokenizerFast's [`~PreTrainedTokenizer.decode`]. Please refer to
        the docstring of this method for more information.
        )r&   decoderX   s      r   r[   zJanusProcessor.decode   s     
 %t~~$$d5f55r   c                 <     | j                   j                  |fi |S )z
        Forwards all arguments to the image processor's `postprocess` method.
        Refer to the original method's docstring for more details.
        )r%   postprocess)r4   r7   r5   s      r   r]   zJanusProcessor.postprocess   s"    
 0t##//A&AAr   c                     | j                   j                  }| j                  j                  }t        t        j                  ||z               S r<   )r&   model_input_namesr%   rH   dictfromkeys)r4   tokenizer_input_namesimage_processor_input_namess      r   r_   z JanusProcessor.model_input_names   s?     $ @ @&*&:&:&L&L#DMM"7:U"UVWWr   )NF)NNNN)r   r   r   __doc__
attributesimage_processor_classtokenizer_classr3   r   r   r   rH   r   r
   r   r   rU   rW   r[   r]   propertyr_   __classcell__)r6   s   @r   r$   r$   1   s    " $[1J1*OR _c!J'I0$y/4HYCZZ[J' J' -.J' 
J'X<6B* B X Xr   r$   N)rd   typingr   feature_extraction_utilsr   image_utilsr   processing_utilsr   r   r	   r
   tokenization_utils_baser   r   utilsr   
get_loggerr   loggerrM   r   r   r$   __all__r   r   r   <module>rs      sx     4 % T T C  
		H	%N j +5 DX^ DXN 
r   