+
    œ°³jû  ã                   óz   € R t ^ RIHt ^RIHt ^RIHt ^RIHt ]! RR7      ] ! R R]]4      4       4       t	R.t
R	# )
zTextNet model configuration)Ústrict)ÚBackboneConfigMixin)ÚPreTrainedConfig)Úauto_docstringzczczup/textnet-base)Ú
checkpointc                   óz   a a€ ] tR t^t oRtRt^t^t^t^@t	Rt
R
tRtRtRtRtRtRtRtV 3R ltV3R ltR	tVtV ;t# )ÚTextNetConfiga/  
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textnetÚreluNgñhãˆµøä>g{®Gáz”?c                ó  <€ V P                   f9   ^^.^^.^^..^^.^^.^^.^^..^^.^^.^^.^^..^^.^^.^^.^^...V n         V P                  f   . RO. RO. RO. RO.V n        V P                    Uu. uF  p\        V4      NK  	  upV n        R.\	        ^^4       Uu. uF  pRV 2NK
  	  up,           V n        V P                  VP                  RR 4      VP                  RR 4      R7       \        SV `$  ! R/ VB  R # u upi u upi )	NÚstemÚstageÚout_indicesÚout_features)r   r   )é   é   r   )r   r   r   r   © )
Úconv_layer_kernel_sizesÚconv_layer_stridesÚlenÚdepthsÚrangeÚstage_namesÚ"set_output_features_output_indicesÚpopÚsuperÚ__post_init__)ÚselfÚkwargsÚlayerÚidxÚ	__class__s   &,  €Úr/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/textnet/configuration_textnet.pyr   ÚTextNetConfig.__post_init__K   s9  ø€ Ø×'Ñ'Ò/à�Q�˜!˜Q˜ ! Q Ð(Ø�Q�˜!˜Q˜ ! Q ¨!¨Q¨Ð0Ø�Q�˜!˜Q˜ ! Q ¨!¨Q¨Ð0Ø�Q�˜!˜Q˜ ! Q ¨!¨Q¨Ð0ð	,ˆDÔ(ð ×"Ñ"Ò*Ú'0²,ÂÊlÐ&[ˆDÔ#à/3×/KÒ/KÓLÑ/K e”s˜5–zÑ/KÑLˆŒØ"˜8ÄÀaÈÄÓ&LÁ¸¨¨s¨e£}ÁÑ&LÕLˆÔØ×/Ñ/ØŸ
™
 =°$Ó7ÀfÇjÁjÐQ_ÐaeÓFfð 	0ô 	
ô 	‰ÒÑ' Ô'ùò MùÚ&Ls   Á7DÂ#D	c                óˆ  <€ V ^8„  d   Qh/ S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[S[ ,          S[S[ S[ 3,          ,          S[ ,          ;R&   S[R,          ;R&   S[R,          ;R	&   S[S[ ,          S[S[ R
3,          ,          ;R&   S[;R&   S[;R&   S[S[,          R,          ;R&   S[S[ ,          R,          ;R&   # )r   Ústem_kernel_sizeÚstem_strideÚstem_num_channelsÚstem_out_channelsÚstem_act_funcÚ
image_sizeNr   r   .Úhidden_sizesÚbatch_norm_epsÚinitializer_rangeÚ_out_featuresÚ_out_indices)ÚintÚstrÚlistÚtupleÚfloat)ÚformatÚ__classdict__s   "€r"   Ú__annotate__ÚTextNetConfig.__annotate__   s	  ø‡ ‚ ñL ÑñM ñN ÑñO ñP ÑñQ ñR ÑñS ñT ÑñU ñV ‘S•	™E¡#¡s (�OÕ+©cÕ1Ñ>ñW ñX " D�[Ñ/ñY ñZ ˜t�Ñ*ñ[ ñ\ ‘s•)™e¡C¨ H�oÕ-ÑGñ] ñ^ Ñ ñ_ ñ` Ñ#ña ñb ™•9˜tÕ#Ñ*ñc ñd ‘s•)˜dÕ"Ñ)òe ó    )r   r   r   r   )é€  r:   )é@   r;   é€   é   i   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typer%   r&   r'   r(   r)   r*   r   r   r+   r,   r-   r.   r/   r   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__Ú__classcell__)r!   r6   s   @@r"   r   r      sf   ù‡ € ñðB €JàÐØ€KØÐØÐØ€MØ4>€JØ+/ÐØ&*ÐØ0G€LØ €NØ#ÐØ&*€MØ%)€Lõ(÷i … r9   r   N)rB   Úhuggingface_hub.dataclassesr   Úbackbone_utilsr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r   r9   r"   Ú<module>rM      sQ   ðñ "å .å 1Ý 3Ý #ñ Ð0Ô1ØôB(Ð'Ð)9ó B(ó ó 2ðB(ðJ Ð
‚r9   