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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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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d"<   d#Zee   eed$f   z  ed%<   d&Z ee   eed$f   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/<   d0Z&eed1<   y2)3ÚData2VecVisionConfigay  
    use_mask_token (`bool`, *optional*, defaults to `False`):
        Whether to use a mask token for masked image modeling.
    use_shared_relative_position_bias (`bool`, *optional*, defaults to `False`):
        Whether to use the same relative position embeddings across all self-attention layers of the Transformer.
    use_mean_pooling (`bool`, *optional*, defaults to `True`):
        Whether to mean pool the final hidden states of the patches instead of using the final hidden state of the
        CLS token, before applying the classification head.
    pool_scales (`tuple[int]`, *optional*, defaults to `[1, 2, 3, 6]`):
        Pooling scales used in Pooling Pyramid Module applied on the last feature map.
    use_auxiliary_head (`bool`, *optional*, defaults to `True`):
        Whether to use an auxiliary head during training.
    auxiliary_loss_weight (`float`, *optional*, defaults to 0.4):
        Weight of the cross-entropy loss of the auxiliary head.
    auxiliary_channels (`int`, *optional*, defaults to 256):
        Number of channels to use in the auxiliary head.
    auxiliary_num_convs (`int`, *optional*, defaults to 1):
        Number of convolutional layers to use in the auxiliary head.
    auxiliary_concat_input (`bool`, *optional*, defaults to `False`):
        Whether to concatenate the output of the auxiliary head with the input before the classification layer.

    Example:

    ```python
    >>> from transformers import Data2VecVisionConfig, Data2VecVisionModel

    >>> # Initializing a Data2VecVision data2vec_vision-base-patch16-224-in22k style configuration
    >>> configuration = Data2VecVisionConfig()

    >>> # Initializing a model (with random weights) from the data2vec_vision-base-patch16-224-in22k style configuration
    >>> model = Data2VecVisionModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```zdata2vec-visioni   Úhidden_sizeé   Únum_hidden_layersÚnum_attention_headsi   Úintermediate_sizeÚgeluÚ
hidden_actg        Úhidden_dropout_probÚattention_probs_dropout_probg{®Gáz”?Úinitializer_rangegê-�™—q=Úlayer_norm_epséà   Ú
image_sizeé   Ú
patch_sizer   Únum_channelsFÚuse_mask_tokenÚ use_absolute_position_embeddingsÚuse_relative_position_biasÚ!use_shared_relative_position_biasgš™™™™™¹?Úlayer_scale_init_valueÚdrop_path_rateTÚuse_mean_pooling)r   é   é   é   .Úout_indices)é   é   r   é   Úpool_scalesÚuse_auxiliary_headgš™™™™™Ù?Úauxiliary_loss_weighté   Úauxiliary_channelsr%   Úauxiliary_num_convsÚauxiliary_concat_inputéÿ   Úsemantic_loss_ignore_indexN)'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   ÚlistÚtupler   r   r   Úboolr   r   r   r   r   r    r$   r(   r)   r*   r,   r-   r.   r0   © ó    ú…/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/data2vec/configuration_data2vec_vision.pyr	   r	      s†  … ñ"ðH #€Jà€K�ÓØÐ�sÓØ!Ð˜Ó!Ø!Ð�sÓ!Ø€J�ÓØ'*Ð˜ ™Ó*Ø03Ð  %¨#¡+Ó3Ø#Ð�uÓ#Ø!€N�EÓ!Ø47€J��d˜3‘i‘ %¨¨S¨¡/Ñ1Ó7Ø46€J��d˜3‘i‘ %¨¨S¨¡/Ñ1Ó6Ø€L�#ÓØ €N�DÓ Ø-2Ð$ dÓ2Ø',Ð Ó,Ø.3Ð% tÓ3Ø$'Ð˜EÓ'Ø"%€N�E˜C‘KÓ%Ø!Ð�dÓ!Ø/<€K��c‘˜U 3¨ 8™_Ñ,Ó<Ø/;€K��c‘˜U 3¨ 8™_Ñ,Ó;Ø#Ð˜Ó#Ø#&Ð˜5Ó&Ø!Ð˜Ó!Ø Ð˜Ó Ø#(Ð˜DÓ(Ø&)Ð Ô)r>   r	   N)	r4   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r=   r>   r?   ú<module>rD      sK   ðñ )å .å 3Ý #ñ Ð:Ô;ØôA*Ð+ó A*ó ó <ðA*ðH "Ð
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