+
    œ°³j9  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DINOv2 model configuration)Ústrict)ÚBackboneConfigMixin)ÚPreTrainedConfig)Úauto_docstringzfacebook/dinov2-base)Ú
checkpointc                   óš   a a€ ] tR t^t oRtRtRt^t^t^t	Rt
RtRtRtRt^àt^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Dinov2Configa�  
layerscale_value (`float`, *optional*, defaults to 1.0):
    Initial value to use for layer scale.
use_swiglu_ffn (`bool`, *optional*, defaults to `False`):
    Whether to use the SwiGLU feedforward neural network.
apply_layernorm (`bool`, *optional*, defaults to `True`):
    Whether to apply layer normalization to the feature maps in case the model is used as backbone.
reshape_hidden_states (`bool`, *optional*, defaults to `True`):
    Whether to reshape the feature maps to 4D tensors of shape `(batch_size, hidden_size, height, width)` in
    case the model is used as backbone. If `False`, the feature maps will be 3D tensors of shape `(batch_size,
    seq_len, hidden_size)`.
use_mask_token (`bool`, *optional*, defaults to `True`):
    Whether to use mask_token in embeddings.

Example:

```python
>>> from transformers import Dinov2Config, Dinov2Model

>>> # Initializing a Dinov2 dinov2-base style configuration
>>> configuration = Dinov2Config()

>>> # Initializing a model (with random weights) from the dinov2-base style configuration
>>> model = Dinov2Model(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Údinov2i   Úgelug        g{®Gáz”?g�íµ ÷Æ°>Tg      ð?FNc                ó  <€ R .\        ^V P                  ^,           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 )ÚstemÚstageÚout_indicesNÚout_features)r   r   © )ÚrangeÚnum_hidden_layersÚstage_namesÚ"set_output_features_output_indicesÚpopÚsuperÚ__post_init__)ÚselfÚkwargsÚidxÚ	__class__s   &, €Úp/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/dinov2/configuration_dinov2.pyr   ÚDinov2Config.__post_init__O   s„   ø€ Ø"˜8ÄÀaÈ×I_ÑI_ÐbcÕIcÔ@dÓ&eÑ@d¸¨¨s¨e£}Ñ@dÑ&eÕeˆÔØ×/Ñ/ØŸ
™
 =°$Ó7ÀfÇjÁjÐQ_ÐaeÓFfð 	0ô 	
ô 	‰ÒÑ' Ô'ùò	 'fs   £Bc                ó  <€ V ^8„  d   Qh/ S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[S[ ,          ;R&   S[S[ ,          ;R&   S[;R&   S[;R	&   S[ S[S[ ,          ,          S[S[ S[ 3,          ,          ;R
&   S[ S[S[ ,          ,          S[S[ S[ 3,          ,          ;R&   S[ ;R&   S[;R&   S[;R&   S[S[ ,          ;R&   S[;R&   S[S[,          R,          ;R&   S[S[ ,          R,          ;R&   S[;R&   S[;R&   S[;R&   # )é   Úhidden_sizer   Únum_attention_headsÚ	mlp_ratioÚ
hidden_actÚhidden_dropout_probÚattention_probs_dropout_probÚinitializer_rangeÚlayer_norm_epsÚ
image_sizeÚ
patch_sizeÚnum_channelsÚqkv_biasÚlayerscale_valueÚdrop_path_rateÚuse_swiglu_ffnNÚ_out_featuresÚ_out_indicesÚapply_layernormÚreshape_hidden_statesÚuse_mask_token)ÚintÚstrÚfloatÚlistÚtupleÚbool)ÚformatÚ__classdict__s   "€r   Ú__annotate__ÚDinov2Config.__annotate__   sˆ  ø‡ ‚ ñD ÑñE ñF ÑñG ñH Ñ!ñI ñJ ÑñK ñL ÑñM ñN ¡�Ñ*ñO ñP #(©#¥+Ñ3ñQ ñR Ñ#ñS ñT Ñ ñU ñV ‘d™3•i•¡%©©S¨¥/Õ1Ñ7ñW ñX ‘d™3•i•¡%©©S¨¥/Õ1Ñ6ñY ñZ Ññ[ ñ\ Ññ] ñ^ Ñ!ñ_ ñ` ™C•KÑ%ña ñb Ñ ñc ñd ™•9˜tÕ#Ñ*ñe ñf ‘s•)˜dÕ"Ñ)ñg ñh Ñ ñi ñj  Ñ&ñk ñl Ñòm ó    )r   ) Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typer    r   r!   r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r,   r-   r.   r/   r0   r1   r2   r3   r   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__Ú__classcell__)r   r;   s   @@r   r   r      sŽ   ù‡ € ñð: €Jà€KØÐØ!ÐØ€IØ€JØ'*ÐØ03Ð Ø#ÐØ €NØ47€JØ46€JØ€LØ€HØ!ÐØ"%€NØ €NØ&*€MØ%)€LØ €OØ"&ÐØ€Nõ(÷q … r>   r   N)rC   Úhuggingface_hub.dataclassesr   Úbackbone_utilsr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r   r>   r   Ú<module>rN      sN   ðñ !å .å 1Ý 3Ý #ñ Ð1Ô2Øô;(Ð&Ð(8ó ;(ó ó 3ð;(ð| Ð
‚r>   