§
    ‚ŠtjÂ
  ã                   ó„   — d Z ddlmZ ddlmZ ddlmZ  ed¬¦  «        e G d„ d	e¦  «        ¦   «         ¦   «         Zd	gZd
S )zTrOCR model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringz microsoft/trocr-base-handwritten)Ú
checkpointc                   ó®  — e Zd ZU dZdZdgZddddœ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	d<   dZee	d<   dZeez  e	d<   dZeez  e	d<   dZee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<   dZee	d <   dZee	d!<   dZee	d"<   d#Zed$z  e	d%<   d&Zed$z  e	d'<   dZee e         z  d$z  e	d(<   d$Z!ed$z  e	d)<   dZ"ee	d*<   dZ#ee	d+<   d$S ),ÚTrOCRConfigaó  
    use_learned_position_embeddings (`bool`, *optional*, defaults to `True`):
        Whether or not to use learned position embeddings. If not, sinusoidal position embeddings will be used.
    layernorm_embedding (`bool`, *optional*, defaults to `True`):
        Whether or not to use a layernorm after the word + position embeddings.

    Example:

    ```python
    >>> from transformers import TrOCRConfig, TrOCRForCausalLM

    >>> # Initializing a TrOCR-base style configuration
    >>> configuration = TrOCRConfig()

    >>> # Initializing a model (with random weights) from the TrOCR-base style configuration
    >>> model = TrOCRForCausalLM(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```ÚtrocrÚpast_key_valuesÚdecoder_attention_headsÚd_modelÚdecoder_layers)Únum_attention_headsÚhidden_sizeÚnum_hidden_layersiYÄ  Ú
vocab_sizei   é   é   i   Údecoder_ffn_dimÚgeluÚactivation_functioni   Úmax_position_embeddingsgš™™™™™¹?Údropoutg        Úattention_dropoutÚactivation_dropouté   Údecoder_start_token_idg{®Gáz”?Úinit_stdÚdecoder_layerdropTÚ	use_cacheFÚscale_embeddingÚuse_learned_position_embeddingsÚlayernorm_embeddingé   NÚpad_token_idr   Úbos_token_idÚeos_token_idÚcross_attention_hidden_sizeÚ
is_decoderÚtie_word_embeddings)$Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚkeys_to_ignore_at_inferenceÚattribute_mapr   ÚintÚ__annotations__r   r   r   r   r   Ústrr   r   Úfloatr   r   r   r   r   r    Úboolr!   r"   r#   r%   r&   r'   Úlistr(   r)   r*   © ó    úk/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/trocr/configuration_trocr.pyr	   r	      sç  € € € € € € ðð ð* €JØ#4Ð"5Ðà8Ø Ø-ðð €Mð €J�ÐÐÑØ€GˆSÐÐÑØ€N�CÐÐÑØ#%Ð˜SÐ%Ð%Ñ%Ø€O�SÐÐÑØ%Ð˜Ð%Ð%Ñ%Ø#&Ð˜SÐ&Ð&Ñ&Ø€GˆU�S‰[ÐÐÑØ%(Ð�u˜s‘{Ð(Ð(Ñ(Ø&)Ð˜ ™Ð)Ð)Ñ)Ø"#Ð˜CÐ#Ð#Ñ#Ø€HˆeÐÐÑØ%(Ð�u˜s‘{Ð(Ð(Ñ(Ø€IˆtÐÐÑØ!€O�TÐ!Ð!Ñ!Ø,0Ð# TÐ0Ð0Ñ0Ø $Ð˜Ð$Ð$Ñ$Ø €L�#˜‘*Ð Ð Ñ Ø €L�#˜‘*Ð Ð Ñ Ø+,€L�#˜˜Sœ	‘/ DÑ(Ð,Ð,Ñ,Ø.2Ð  t¡Ð2Ð2Ñ2Ø€J�ÐÐÑØ $Ð˜Ð$Ð$Ñ$Ð$Ð$r9   r	   N)	r.   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r8   r9   r:   ú<module>r?      s¡   ðð  Ð à .Ð .Ð .Ð .Ð .Ð .à 3Ð 3Ð 3Ð 3Ð 3Ð 3Ø #Ð #Ð #Ð #Ð #Ð #ð €Ð=Ð>Ñ>Ô>Øð4%ð 4%ð 4%ð 4%ð 4%Ð"ñ 4%ô 4%ñ „ñ ?Ô>ð4%ðn ˆ/€€€r9   