Ë
    ÜÓ^j¶  ã                   óx   — d Z ddlmZ ddlmZ ddlmZ ddlmZ  ed¬«      e G d	„ d
ee«      «       «       Z	d
gZ
y)z$Swin Transformer model configurationé    )Ústricté   )ÚBackboneConfigMixin)ÚPreTrainedConfig)Úauto_docstringz&microsoft/swin-tiny-patch4-window7-224)Ú
checkpointc                   óÐ  ‡ — e Zd ZU dZdZdddœZdZeee   z  e	eef   z  e
d<   dZeee   z  e	eef   z  e
d	<   d
Zee
d<   dZee
d<   dZee   e	edf   z  e
d<   dZee   e	edf   z  e
d<   dZee
d<   dZeez  e
d<   dZee
d<   dZeez  e
d<   dZeez  e
d<   dZeez  e
d<   dZee
d<   dZee
d <   d!Zee
d"<   d#Zee
d$<   d%Zee
d&<   d'Zee   d'z  e
d(<   d'Zee   d'z  e
d)<   ˆ fd*„Z ˆ xZ!S )+Ú
SwinConfigaÆ  
    depths (`list(int)`, *optional*, defaults to `[2, 2, 6, 2]`):
        Depth of each layer in the Transformer encoder.
    num_heads (`list(int)`, *optional*, defaults to `[3, 6, 12, 24]`):
        Number of attention heads in each layer of the Transformer encoder.
    window_size (`int`, *optional*, defaults to 7):
        Size of windows.
    encoder_stride (`int`, *optional*, defaults to 32):
        Factor to increase the spatial resolution by in the decoder head for masked image modeling.

    Example:

    ```python
    >>> from transformers import SwinConfig, SwinModel

    >>> # Initializing a Swin microsoft/swin-tiny-patch4-window7-224 style configuration
    >>> configuration = SwinConfig()

    >>> # Initializing a model (with random weights) from the microsoft/swin-tiny-patch4-window7-224 style configuration
    >>> model = SwinModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```ÚswinÚ	num_headsÚ
num_layers)Únum_attention_headsÚnum_hidden_layerséà   Ú
image_sizeé   Ú
patch_sizer   Únum_channelsé`   Ú	embed_dim)é   r   é   r   .Údepths)r   r   é   é   é   Úwindow_sizeg      @Ú	mlp_ratioTÚqkv_biasg        Úhidden_dropout_probÚattention_probs_dropout_probgš™™™™™¹?Údrop_path_rateÚgeluÚ
hidden_actFÚuse_absolute_embeddingsg{®Gáz”?Úinitializer_rangegñhãˆµøä>Úlayer_norm_epsé    Úencoder_strideNÚ_out_featuresÚ_out_indicesc                 ó¬  •— t        | j                  «      | _        t        | j                  dt        | j                  «      dz
  z  z  «      | _        dgt        dt        | j                  «      dz   «      D �cg c]  }d|› �‘Œ	 c}z   | _        | j                  |j                  dd «      |j                  dd «      ¬«       t        ‰| �,  di |¤Ž y c c}w )	Nr   é   ÚstemÚstageÚout_indicesÚout_features)r0   r1   © )Úlenr   r   Úintr   Úhidden_sizeÚrangeÚstage_namesÚ"set_output_features_output_indicesÚpopÚsuperÚ__post_init__)ÚselfÚkwargsÚidxÚ	__class__s      €úv/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/swin/configuration_swin.pyr;   zSwinConfig.__post_init__N   s¼   ø€ Ü˜dŸk™kÓ*ˆŒô ˜tŸ~™~°´c¸$¿+¹+Ó6FÈÑ6JÑ0KÑKÓLˆÔØ"˜8ÄÀaÌÈTÏ[É[ÓIYÐ\]ÑI]Ó@^Ö&_¸¨¨s¨e¢}Ò&_Ñ_ˆÔØ×/Ñ/ØŸ
™
 =°$Ó7ÀfÇjÁjÐQ_ÐaeÓFfð 	0ô 	
ô 	‰ÑÑ' Ó'ùò	 '`s   Á8C)"Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚattribute_mapr   r4   ÚlistÚtupleÚ__annotations__r   r   r   r   r   r   r   Úfloatr   Úboolr    r!   r"   r$   Ústrr%   r&   r'   r)   r*   r+   r;   Ú__classcell__)r?   s   @r@   r
   r
      sZ  ø… ñð2 €Jð  +Ø)ñ€Mð
 58€J��d˜3‘i‘ %¨¨S¨¡/Ñ1Ó7Ø45€J��d˜3‘i‘ %¨¨S¨¡/Ñ1Ó5Ø€L�#ÓØ€IˆsÓØ*6€FˆD�‰I˜˜c 3˜h™Ñ'Ó6Ø-;€Iˆt�C‰y˜5  c ™?Ñ*Ó;Ø€K�ÓØ €Iˆu�s‰{Ó Ø€HˆdÓØ'*Ð˜ ™Ó*Ø03Ð  %¨#¡+Ó3Ø"%€N�E˜C‘KÓ%Ø€J�ÓØ$)Ð˜TÓ)Ø#Ð�uÓ#Ø €N�EÓ Ø€N�CÓØ&*€M�4˜‘9˜tÑ#Ó*Ø%)€L�$�s‘)˜dÑ"Ó)÷	(ð 	(ó    r
   N)rD   Úhuggingface_hub.dataclassesr   Úbackbone_utilsr   Úconfiguration_utilsr   Úutilsr   r
   Ú__all__r2   rN   r@   ú<module>rT      sN   ðñ +å .å 1Ý 3Ý #ñ ÐCÔDØô>(Ð$Ð&6ó >(ó ó Eð>(ðB ˆ.�rN   