Ë
    ÛÓ^j¶  ã                   ój   — 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y
)zCANINE model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringzgoogle/canine-s)Ú
checkpointc                   óJ  — e Zd ZU 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z  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ed<   dZeed <   d!Zeed"<   dZeed#<   d$Zeed%<   y)&ÚCanineConfiga.  
    downsampling_rate (`int`, *optional*, defaults to 4):
        The rate at which to downsample the original character sequence length before applying the deep Transformer
        encoder.
    upsampling_kernel_size (`int`, *optional*, defaults to 4):
        The kernel size (i.e. the number of characters in each window) of the convolutional projection layer when
        projecting back from `hidden_size`*2 to `hidden_size`.
    num_hash_functions (`int`, *optional*, defaults to 8):
        The number of hash functions to use. Each hash function has its own embedding matrix.
    num_hash_buckets (`int`, *optional*, defaults to 16384):
        The number of hash buckets to use.
    local_transformer_stride (`int`, *optional*, defaults to 128):
        The stride of the local attention of the first shallow Transformer encoder. Defaults to 128 for good
        TPU/XLA memory alignment.

    Example:

    ```python
    >>> from transformers import CanineConfig, CanineModel

    >>> # Initializing a CANINE google/canine-s style configuration
    >>> configuration = CanineConfig()

    >>> # Initializing a model (with random weights) from the google/canine-s style configuration
    >>> model = CanineModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```Úcaninei   Úhidden_sizeé   Únum_hidden_layersÚnum_attention_headsi   Úintermediate_sizeÚgeluÚ
hidden_actgš™™™™™¹?Úhidden_dropout_probÚattention_probs_dropout_probi @  Úmax_position_embeddingsé   Útype_vocab_sizeg{®Gáz”?Úinitializer_rangegê-�™—q=Úlayer_norm_epsr   NÚpad_token_idi à  Úbos_token_idià  Úeos_token_idé   Údownsampling_rateÚupsampling_kernel_sizeé   Únum_hash_functionsÚnum_hash_bucketsé€   Úlocal_transformer_stride)Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typer   ÚintÚ__annotations__r   r   r   r   Ústrr   Úfloatr   r   r   r   r   r   r   r   Úlistr   r   r    r!   r#   © ó    úz/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/canine/configuration_canine.pyr	   r	      sõ   … ñð< €Jà€K�ÓØÐ�sÓØ!Ð˜Ó!Ø!Ð�sÓ!Ø€J�ÓØ'*Ð˜ ™Ó*Ø03Ð  %¨#¡+Ó3Ø#(Ð˜SÓ(Ø€O�SÓØ#Ð�uÓ#Ø!€N�EÓ!Ø €L�#˜‘*Ó Ø%€L�#˜‘*Ó%Ø+1€L�#˜˜S™	‘/ DÑ(Ó1ØÐ�sÓØ"#Ð˜CÓ#ØÐ˜ÓØ!Ð�cÓ!Ø$'Ð˜cÔ'r/   r	   N)	r'   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r.   r/   r0   ú<module>r5      sH   ðñ !å .å 3Ý #ñ Ð,Ô-Øô3(Ð#ó 3(ó ó .ð3(ðl Ð
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