`ix. dZddlmZmZddlZddlmZddlm Z m Z ddl m Z m Z mZmZddlmZmZdd lmZmZerd d lmZejeZGd d e dZdefdZdZGddeZdgZ dS)z Processor class for Pixtral. )OptionalUnionN) BatchFeature) ImageInputis_valid_image)MultiModalDataProcessingKwargsProcessorMixinUnpack)PreTokenizedInput TextInput)is_vision_availablelogging)get_resize_output_image_sizec$eZdZdddiddidZdS)PixtralProcessorKwargsF)paddingreturn_mm_token_type_idsreturn_tensorspt) text_kwargs images_kwargs common_kwargsN)__name__ __module__ __qualname__ _defaults/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/transformers/models/pixtral/processing_pixtral.pyrr*s;(-   d  IIIr!rF)totalreturncVt|to|dS)Nhttp) isinstancestr startswith)vals r"is_urlr+8s# c3   :CNN6$:$::r!c>t|pt|SN)r+r)elems r"is_image_or_image_urlr/=s $<< />$///r!c eZdZdZddgZdZdZ dd ed effd Z dde e de e e ee ee fdeedefdZddZedZxZS)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 AutoTokenizerNr[IMG] [IMG_BREAK] [IMG_END] patch_sizespatial_merge_sizec  ||_||_||_||j|_||_||_||j|_||j|_||j|_|j|j|jg|_ t |||dS)N) chat_template) r:r; image_tokenconvert_tokens_to_idsimage_token_idimage_break_tokenimage_end_tokenimage_break_token_idimage_end_token_id image_idssuper__init__) selfr2r3r:r;r=r>rArBkwargs __class__s r"rGzPixtralProcessor.__init___s%"4&'==d>NOO!2.'==d>NOO$-$C$CDDZ$[$[!"+"A"A$BV"W"W-t/H$Jab )=QQQQQr!imagestextrIr$c V|jtfd|jji|}|j|jz}||j|fd|i|d}ni}t|tr|g}n?t|ts*t|dtstd|} | d t|d} g} g} |D]} |j | vrt| \} }| |z}||z}|j g|z|jgzg|z}d |D}|j|d <d |}| || |j d d } |j | vd | vr0| d}| d |d } d | v0| | |ddd}|ddd}|j| fi|dddi}|| |dg|rht-j|d}t-j|d}d |t-j||j<||d<t9i|||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 `kwargs` 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_kwargsNr:rrzAInvalid input text. 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