Ë
    ÜÓ^jü  ã                   óØ   — d dl mZ ddlmZ ddlmZmZ ddlmZm	Z	  ej                  e«      Z ed¬«      e G d	„ d
e«      «       «       Z ed¬«      e G d„ de«      «       «       Zd
dgZy)é    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringÚloggingé   )ÚCONFIG_MAPPINGÚ
AutoConfigz$HuggingFaceTB/SmolVLM2-2.2B-Instruct)Ú
checkpointc                   óò   — e Zd ZU dZdZdZdZeed<   dZ	eed<   dZ
eed	<   d
Zeed<   dZeed<   dZeee   z  eeef   z  ed<   dZeee   z  eeef   z  ed<   dZeed<   dZeed<   dZeez  ed<   dZeed<   y)ÚSmolVLMVisionConfiga  
    Example:

    ```python
    >>> from transformers.models.smolvlm.modeling_smolvlm import SmolVLMVisionTransformer
    >>> from transformers.models.smolvlm.configuration_smolvlm import SmolVLMVisionConfig

    >>> # Initializing a SmolVLMVisionConfig with google/siglip-so400m-patch14-384 style configuration
    >>> configuration = SmolVLMVisionConfig()

    >>> # Initializing a SmolVLMVisionTransformer (with random weights) from the google/siglip-so400m-patch14-384 style configuration
    >>> model = SmolVLMVisionTransformer(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```Úsmolvlm_visionÚvision_configi€  Úhidden_sizei   Úintermediate_sizeé   Únum_hidden_layersé   Únum_attention_headsr   Únum_channelséà   Ú
image_sizeé    Ú
patch_sizeÚgelu_pytorch_tanhÚ
hidden_actg�íµ ÷Æ°>Úlayer_norm_epsg        Úattention_dropoutg{®Gáz”?Úinitializer_rangeN)Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚbase_config_keyr   ÚintÚ__annotations__r   r   r   r   r   ÚlistÚtupler   r   Ústrr   Úfloatr   r   © ó    ú|/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/smolvlm/configuration_smolvlm.pyr   r   !   s´   … ñð" "€JØ%€Oà€K�ÓØ!Ð�sÓ!ØÐ�sÓØ!Ð˜Ó!Ø€L�#ÓØ47€J��d˜3‘i‘ %¨¨S¨¡/Ñ1Ó7Ø46€J��d˜3‘i‘ %¨¨S¨¡/Ñ1Ó6Ø)€J�Ó)Ø €N�EÓ Ø%(Ð�u˜s‘{Ó(Ø#Ð�uÔ#r-   r   c                   ó²   ‡ — e Zd ZU dZdZeedœZdZe	e
d<   dZee
d<   dZe	e
d	<   d
Zeez  d
z  e
d<   d
Zeez  d
z  e
d<   dZee
d<   dZed
z  e
d<   ˆ fd„Zˆ xZS )ÚSmolVLMConfigaÆ  
    scale_factor (`int`, *optional*, defaults to 2):
        The scale factor for the image encoder.

    Example:
    ```python
    >>> from transformers import SmolVLMModel, SmolVLMConfig
    >>> # Initializing configuration
    >>> configuration = SmolVLMConfig()
    >>> # Initializing a model from the configuration
    >>> model = SmolVLMModel(configuration)
    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```Úsmolvlm)Útext_configr   TÚ	use_cacheiõ Úimage_token_idFÚtie_word_embeddingsNr   r2   r   Úscale_factoriô Úpad_token_idc                 óJ  •— | j                   €%t        «       | _         t        j                  d«       n4t	        | j                   t
        «      rt        di | j                   ¤Ž| _         t	        | j                  t
        «      rT| j                  j                  dd«      | j                  d<   t        | j                  d      di | j                  ¤Ž| _        n@| j                  €4t        j                  d«       t        d   d| j                  ¬«      | _        t        ‰| �,  di |¤Ž y )Nz2vision_config is None, using default vision configr$   Úllamaz4text_config is None, using default Llama text configgñhãˆµøä>)Úrms_norm_epsr7   r,   )r   r   ÚloggerÚinfoÚ
isinstanceÚdictr2   Úgetr	   r7   ÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s     €r.   rA   zSmolVLMConfig.__post_init__b   sñ   ø€ Ø×ÑÐ%Ü!4Ó!6ˆDÔÜ�K‰KÐLÕMÜ˜×*Ñ*¬DÔ1Ü!4Ñ!J°t×7IÑ7IÑ!JˆDÔä�d×&Ñ&¬Ô-Ø-1×-=Ñ-=×-AÑ-AÀ,ÐPWÓ-XˆD×Ñ˜\Ñ*Ü-¨d×.>Ñ.>¸|Ñ.LÑMÑaÐPT×P`ÑP`ÑaˆDÕØ×ÑÐ%Ü�K‰KÐNÔOÜ-¨gÑ6Ø!Ø!×.Ñ.ô ˆDÔô
 	‰ÑÑ' Ó'r-   )r    r!   r"   r#   r$   r
   r   Úsub_configsr3   Úboolr'   r4   r&   r5   r   r>   r   r2   r6   r7   rA   Ú__classcell__)rD   s   @r.   r0   r0   E   s…   ø… ñð €JØ",Ð?RÑS€Kà€IˆtÓØ €N�CÓ Ø %Ð˜Ó%Ø48€M�4Ð*Ñ*¨TÑ1Ó8Ø26€K�Ð(Ñ(¨4Ñ/Ó6Ø€L�#ÓØ&€L�#˜‘*Ó&÷(ð (r-   r0   N)Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Úautor	   r
   Ú
get_loggerr    r;   r   r0   Ú__all__r,   r-   r.   ú<module>rN      s‹   ðõ. /å 3ß ,ß -ð 
ˆ×	Ñ	˜HÓ	%€ñ ÐAÔBØô$Ð*ó $ó ó Cð$ñD ÐAÔBØô,(Ð$ó ,(ó ó Cð,(ð^ ! /Ð
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