Ë
    ÜÓ^jI  ã                   óž   — d Z ddlmZ ddlmZ ddlmZ ddlmZm	Z	  e	j                  e«      Z ed¬«      e G d	„ d
e«      «       «       Zd
gZy)zMistral model configurationé    )Ústricté   )ÚPreTrainedConfig)ÚRopeParameters)Úauto_docstringÚloggingzmistralai/Mistral-7B-v0.1)Ú
checkpointc                   ó®  ‡ — e Zd ZU dZdZdgZddddddddœZdgdgfd	d
gd	gfd	gd	gfdœZdZe	e
d<   dZe	e
d<   dZe	e
d<   dZe	e
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d<   dZe	e
d<   dZe	dz  e
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d<   dZee
d<   dZee
d <   d!Zee
d"<   dZe	dz  e
d#<   d$Ze	dz  e
d%<   d&Ze	ee	   z  dz  e
d'<   d(Zee
d)<   dZee z  dz  e
d*<   dZ!e	dz  e
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d-<   ˆ fd.„Z#ˆ xZ$S )/ÚMistralConfigaˆ  
    Example:

    ```python
    >>> from transformers import MistralModel, MistralConfig

    >>> # Initializing a Mistral 7B style configuration
    >>> configuration = MistralConfig()

    >>> # Initializing a model from the Mistral 7B style configuration
    >>> model = MistralModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```ÚmistralÚpast_key_valuesÚcolwiseÚrowwise)zlayers.*.self_attn.q_projzlayers.*.self_attn.k_projzlayers.*.self_attn.v_projzlayers.*.self_attn.o_projzlayers.*.mlp.gate_projzlayers.*.mlp.up_projzlayers.*.mlp.down_projÚ	input_idsÚinputs_embedsÚhidden_statesÚattention_mask)Úembed_tokensÚlayersÚnormi }  Ú
vocab_sizei   Úhidden_sizei 8  Úintermediate_sizeé    Únum_hidden_layersÚnum_attention_headsé   Únum_key_value_headsNÚhead_dimÚsiluÚ
hidden_acti   Úmax_position_embeddingsg{®Gáz”?Úinitializer_rangeg�íµ ÷Æ°>Úrms_norm_epsTÚ	use_cacheÚpad_token_idé   Úbos_token_idé   Úeos_token_idFÚtie_word_embeddingsÚrope_parametersÚsliding_windowg        Úattention_dropoutc                 óú   •— | j                   �| j                   n| j                  | j                  z  | _         | j                  €| j                  | _        d|v rt        j                  d«       t        ‰| �  di |¤ŽS )NÚlayer_typesz�Detected Mistral model with layer_types. Consider using AutoModel or Ministral classes instead to enable alternating attention compatibility.© )r   r   r   r   ÚloggerÚwarning_onceÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s     €ú|/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/mistral/configuration_mistral.pyr5   zMistralConfig.__post_init__S   sv   ø€ Ø)-¯©Ð)B˜ŸšÈ×HXÑHXÐ\`×\tÑ\tÑHtˆŒØ×#Ñ#Ð+Ø'+×'?Ñ'?ˆDÔ$à˜FÑ"Ü×Ñð `ôô ‰wÑ$Ñ. vÑ.Ð.ó    )%Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚkeys_to_ignore_at_inferenceÚbase_model_tp_planÚbase_model_pp_planr   ÚintÚ__annotations__r   r   r   r   r   r   r!   Ústrr"   r#   Úfloatr$   r%   Úboolr&   r(   r*   Úlistr+   r,   r   Údictr-   r.   r5   Ú__classcell__)r8   s   @r9   r   r      sj  ø… ñð  €JØ#4Ð"5Ðð &/Ø%.Ø%.Ø%.Ø"+Ø )Ø"+ñÐð &˜¨Ð(9Ð:Ø#Ð%5Ð6¸Ð8IÐJØ!Ð" _Ð$5Ð6ñÐð €J�ÓØ€K�ÓØ"Ð�sÓ"ØÐ�sÓØ!Ð˜Ó!Ø Ð˜Ó Ø€Hˆc�D‰jÓØ€J�ÓØ#,Ð˜SÓ,Ø#Ð�uÓ#Ø€L�%ÓØ€IˆtÓØ#€L�#˜‘*Ó#Ø €L�#˜‘*Ó Ø+,€L�#˜˜S™	‘/ DÑ(Ó,Ø %Ð˜Ó%Ø48€O�^ dÑ*¨TÑ1Ó8Ø!%€N�C˜$‘JÓ%Ø%(Ð�u˜s‘{Ó(÷	/ð 	/r:   r   N)r>   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úmodeling_rope_utilsr   Úutilsr   r   Ú
get_loggerr;   r2   r   Ú__all__r1   r:   r9   ú<module>rQ      sb   ðñ "å .å 3Ý 1ß ,ð 
ˆ×	Ñ	˜HÓ	%€ñ Ð6Ô7Øô@/Ð$ó @/ó ó 8ð@/ðF Ð
�r:   