ó
    qyüiû  ã                   ór   • S r SSKJr  SSKJr  SSKJr  SSKJr  \" SS9\ " S	 S
\\5      5       5       r	S
/r
g)zTextNet model configurationé    )Ústricté   )ÚBackboneConfigMixin)ÚPreTrainedConfig)Úauto_docstringzczczup/textnet-base)Ú
checkpointc                   ó>  ^ • \ rS rSr% SrSrSr\\S'   Sr	\\S'   Sr
\\S'   S	r\\S
'   Sr\\S'   Sr\\   \\\4   -  \-  \S'   Sr\S-  \S'   Sr\S-  \S'   Sr\\   \\S4   -  \S'   Sr\\S'   Sr\\S'   Sr\\   S-  \S'   Sr\\   S-  \S'   U 4S jrSrU =r$ )ÚTextNetConfigé   a/  
stem_kernel_size (`int`, *optional*, defaults to 3):
    The kernel size for the initial convolution layer.
stem_stride (`int`, *optional*, defaults to 2):
    The stride for the initial convolution layer.
stem_num_channels (`int`, *optional*, defaults to 3):
    The num of channels in input for the initial convolution layer.
stem_out_channels (`int`, *optional*, defaults to 64):
    The num of channels in out for the initial convolution layer.
stem_act_func (`str`, *optional*, defaults to `"relu"`):
    The activation function for the initial convolution layer.
conv_layer_kernel_sizes (`list[list[list[int]]]`, *optional*):
    A list of stage-wise kernel sizes. If `None`, defaults to:
    `[[[3, 3], [3, 3], [3, 3]], [[3, 3], [1, 3], [3, 3], [3, 1]], [[3, 3], [3, 3], [3, 1], [1, 3]], [[3, 3], [3, 1], [1, 3], [3, 3]]]`.
conv_layer_strides (`list[list[int]]`, *optional*):
    A list of stage-wise strides. If `None`, defaults to:
    `[[1, 2, 1], [2, 1, 1, 1], [2, 1, 1, 1], [2, 1, 1, 1]]`.

Examples:

```python
>>> from transformers import TextNetConfig, TextNetBackbone

>>> # Initializing a TextNetConfig
>>> configuration = TextNetConfig()

>>> # Initializing a model (with random weights)
>>> model = TextNetBackbone(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Útextnetr   Ústem_kernel_sizeé   Ústem_strideÚstem_num_channelsé@   Ústem_out_channelsÚreluÚstem_act_func)é€  r   Ú
image_sizeNÚconv_layer_kernel_sizesÚconv_layer_strides)r   r   é€   é   i   .Úhidden_sizesgñhãˆµøä>Úbatch_norm_epsg{®Gáz”?Úinitializer_rangeÚ_out_featuresÚ_out_indicesc                 ó  >• U R                   c8  SS/SS/SS//SS/SS/SS/SS//SS/SS/SS/SS//SS/SS/SS/SS///U l         U R                  c  / SQ/ SQ/ SQ/ SQ/U l        U R                    Vs/ s H  n[        U5      PM     snU l        S/[	        SS5       Vs/ s H  nSU 3PM
     sn-   U l        U R                  UR                  SS 5      UR                  S	S 5      S
9  [        TU ]$  " S0 UD6  g s  snf s  snf )Nr   é   )r!   r   r!   )r   r!   r!   r!   Ústemé   ÚstageÚout_indicesÚout_features)r%   r&   © )
r   r   ÚlenÚdepthsÚrangeÚstage_namesÚ"set_output_features_output_indicesÚpopÚsuperÚ__post_init__)ÚselfÚkwargsÚlayerÚidxÚ	__class__s       €Ún/home/mande/repo/quber/.venv/lib/python3.13/site-packages/transformers/models/textnet/configuration_textnet.pyr/   ÚTextNetConfig.__post_init__K   s9  ø€ Ø×'Ñ'Ñ/à�Q�˜!˜Q˜ ! Q Ð(Ø�Q�˜!˜Q˜ ! Q ¨!¨Q¨Ð0Ø�Q�˜!˜Q˜ ! Q ¨!¨Q¨Ð0Ø�Q�˜!˜Q˜ ! Q ¨!¨Q¨Ð0ð	,ˆDÔ(ð ×"Ñ"Ñ*Ú'0²,ÂÊlÐ&[ˆDÔ#à/3×/KÒ/KÓLÒ/K e”s˜5–zÑ/KÑLˆŒØ"˜8ÄÀaÈÄÓ&LÂ¸¨¨s¨e£}ÁÑ&LÑLˆÔØ×/Ñ/ØŸ
™
 =°$Ó7ÀfÇjÁjÐQ_ÐaeÓFfð 	0ñ 	
ô 	‰ÒÑ' Ó'ùò MùÚ&Ls   Á5C<Â"D)r   r   r)   r+   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typer   ÚintÚ__annotations__r   r   r   r   Ústrr   ÚlistÚtupler   r   r   r   Úfloatr   r   r   r/   Ú__static_attributes__Ú__classcell__)r4   s   @r5   r
   r
      sã   ø‡ ñðB €JàÐ�cÓØ€K�ÓØÐ�sÓØÐ�sÓØ€M�3ÓØ4>€J��S‘	˜E # s (™OÑ+¨cÑ1Ó>Ø+/Ð˜T D™[Ó/Ø&*Ð˜˜t™Ó*Ø0G€L�$�s‘)˜e C¨ H™oÑ-ÓGØ €N�EÓ Ø#Ð�uÓ#Ø&*€M�4˜‘9˜tÑ#Ó*Ø%)€L�$�s‘)˜dÑ"Ó)÷(ó (ó    r
   N)r;   Úhuggingface_hub.dataclassesr   Úbackbone_utilsr   Úconfiguration_utilsr   Úutilsr   r
   Ú__all__r'   rE   r5   Ú<module>rK      sQ   ðñ "å .å 1Ý 3Ý #ñ Ð0Ñ1ØôB(Ð'Ð)9ó B(ó ó 2ðB(ðJ Ð
�rE   