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S )z'Swin2SR Transformer model configurationé    )Ústricté   )ÚPreTrainedConfig)Úauto_docstringz caidas/swin2sr-classicalsr-x2-64)Ú
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    num_channels_out (`int`, *optional*, defaults to `num_channels`):
        The number of output channels. If not set, it will be set to `num_channels`.
    depths (`list(int)`, *optional*, defaults to `[6, 6, 6, 6, 6, 6]`):
        Depth of each layer in the Transformer encoder.
    num_heads (`list(int)`, *optional*, defaults to `[6, 6, 6, 6, 6, 6]`):
        Number of attention heads in each layer of the Transformer encoder.
    window_size (`int`, *optional*, defaults to 8):
        Size of windows.
    upscale (`int`, *optional*, defaults to 2):
        The upscale factor for the image. 2/3/4/8 for image super resolution, 1 for denoising and compress artifact
        reduction
    img_range (`float`, *optional*, defaults to 1.0):
        The range of the values of the input image.
    resi_connection (`str`, *optional*, defaults to `"1conv"`):
        The convolutional block to use before the residual connection in each stage.
    upsampler (`str`, *optional*, defaults to `"pixelshuffle"`):
        The reconstruction reconstruction module. Can be 'pixelshuffle'/'pixelshuffledirect'/'nearest+conv'/None.

    Example:

    ```python
    >>> from transformers import Swin2SRConfig, Swin2SRModel

    >>> # Initializing a Swin2SR caidas/swin2sr-classicalsr-x2-64 style configuration
    >>> configuration = Swin2SRConfig()

    >>> # Initializing a model (with random weights) from the caidas/swin2sr-classicalsr-x2-64 style configuration
    >>> model = Swin2SRModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```Úswin2srÚ	embed_dimÚ	num_headsÚ
num_layers)Úhidden_sizeÚnum_attention_headsÚnum_hidden_layersé@   Ú
image_sizeé   Ú
patch_sizer   Únum_channelsNÚnum_channels_outé´   )é   r   r   r   r   r   .Údepthsé   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upscaleg      ð?Ú	img_rangeÚ1convÚresi_connectionÚpixelshuffleÚ	upsamplerc                 ó    •— | j         €| j        n| j         | _         t          | j        ¦  «        | _         t          ¦   «         j        di |¤Ž d S )N© )r   r   Úlenr   r   ÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s     €úo/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/swin2sr/configuration_swin2sr.pyr1   zSwin2SRConfig.__post_init__Y   sS   ø€ Ø59Ô5JÐ5R Ô 1Ð 1ÐX\ÔXmˆÔÝ˜dœkÑ*Ô*ˆŒØ�‰ŒÔÐ'Ð' Ð'Ð'Ð'Ð'Ð'ó    )$Ú__name__Ú
__module__Ú__qualname__Ú__doc__Ú
model_typeÚattribute_mapr   ÚintÚlistÚtupleÚ__annotations__r   r   r   r   r   r   r   r   Úfloatr   Úboolr   r   r    r"   Ústrr#   r$   r%   r'   r(   r*   r,   r1   Ú__classcell__)r4   s   @r5   r	   r	      s  ø€ € € € € € ð ð  ðD €Jð #Ø*Ø)ðð €Mð 57€J��d˜3”i‘ %¨¨S¨¤/Ñ1Ð6Ð6Ñ6Ø45€J��d˜3”i‘ %¨¨S¨¤/Ñ1Ð5Ð5Ñ5Ø€L�#ÐÐÑØ#'Ð�c˜D‘jÐ'Ð'Ñ'Ø€IˆsÐÐÑØ*<€FˆD�ŒI˜˜c 3˜hœÑ'Ð<Ð<Ñ<Ø-?€Iˆt�CŒy˜5  c œ?Ñ*Ð?Ð?Ñ?Ø€K�ÐÐÑØ€IˆuÐÐÑØ€HˆdÐÐÑØ'*Ð˜ ™Ð*Ð*Ñ*Ø03Ð  %¨#¡+Ð3Ð3Ñ3Ø"%€N�E˜C‘KÐ%Ð%Ñ%Ø€J�ÐÐÑØ$)Ð˜TÐ)Ð)Ñ)Ø#Ð�uÐ#Ð#Ñ#Ø €N�EÐ Ð Ñ Ø€GˆSÐÐÑØ€IˆuÐÐÑØ"€O�SÐ"Ð"Ñ"Ø#€IˆsÐ#Ð#Ñ#ð(ð (ð (ð (ð (ð (ð (ð (ð (r6   r	   N)	r:   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r	   Ú__all__r.   r6   r5   ú<module>rI      sª   ðð .Ð -à .Ð .Ð .Ð .Ð .Ð .à 3Ð 3Ð 3Ð 3Ð 3Ð 3Ø #Ð #Ð #Ð #Ð #Ð #ð €Ð=Ð>Ñ>Ô>ØðD(ð D(ð D(ð D(ð D(Ð$ñ D(ô D(ñ „ñ ?Ô>ðD(ðN Ð
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