+
    œ°³jA	  ã                   ól   € R 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I-JEPA model configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringzfacebook/ijepa_vith14_1k)Ú
checkpointc                   ó‚   a a€ ] tR t^t oRtRtRt^t^tRt	Rt
RtRtRtRt^àt^t^tR	tR
tRtV 3R ltV3R ltRtVtV ;t# )ÚIJepaConfigam  
pooler_output_size (`int`, *optional*):
    Dimensionality of the pooler layer. If None, defaults to `hidden_size`.
pooler_act (`str`, *optional*, defaults to `"tanh"`):
    The activation function to be used by the pooler.

Example:

```python
>>> from transformers import IJepaConfig, IJepaModel

>>> # Initializing a IJEPA ijepa-base-patch16-224 style configuration
>>> configuration = IJepaConfig()

>>> # Initializing a model (with random weights) from the ijepa-base-patch16-224 style configuration
>>> model = IJepaModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Úijepai   i   Úgelug        g{®Gáz”?gê-�™—q=TNÚtanhc                ó†   <€ V P                   '       d   V P                   MV P                  V n         \        SV `  ! R/ VB  R # )N© )Úpooler_output_sizeÚhidden_sizeÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s   &,€Ún/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/ijepa/configuration_ijepa.pyr   ÚIJepaConfig.__post_init__@   s5   ø€ Ø=A×=T×=TÐ=T $×"9Ò"9ÐZ^×ZjÑZjˆÔÜ‰ÒÑ' Ô'ó    c                óˆ  <€ V ^8„  d   Qh/ S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[S[ ,          ;R&   S[S[ ,          ;R&   S[;R&   S[;R	&   S[ S[S[ ,          ,          S[S[ S[ 3,          ,          ;R
&   S[ S[S[ ,          ,          S[S[ S[ 3,          ,          ;R&   S[ ;R&   S[;R&   S[ R,          ;R&   S[;R&   # )é   r   Únum_hidden_layersÚnum_attention_headsÚintermediate_sizeÚ
hidden_actÚhidden_dropout_probÚattention_probs_dropout_probÚinitializer_rangeÚlayer_norm_epsÚ
image_sizeÚ
patch_sizeÚnum_channelsÚqkv_biasNr   Ú
pooler_act)ÚintÚstrÚfloatÚlistÚtupleÚbool)ÚformatÚ__classdict__s   "€r   Ú__annotate__ÚIJepaConfig.__annotate__   s  ø‡ ‚ ñ4 Ññ5 ñ6 Ññ7 ñ8 Ñ!ñ9 ñ: Ñ!ñ; ñ< Ññ= ñ> ¡�Ñ*ñ? ñ@ #(©#¥+Ñ3ñA ñB Ñ#ñC ñD Ñ!ñE ñF ‘d™3•i•¡%©©S¨¥/Õ1Ñ7ñG ñH ‘d™3•i•¡%©©S¨¥/Õ1Ñ6ñI ñJ ÑñK ñL ÑñM ñN ˜d�
Ñ)ñO ñP ÑòQ r   )r   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typer   r   r   r   r   r   r   r   r    r!   r"   r#   r$   r   r%   r   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__Ú__classcell__)r   r-   s   @@r   r   r      sp   ù‡ € ñð* €Jà€KØÐØ!ÐØ!ÐØ€JØ'*ÐØ03Ð Ø#ÐØ!€NØ47€JØ46€JØ€LØ€HØ%)ÐØ€Jõ(÷U … r   r   N)	r4   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r   r   r   Ú<module>r>      sG   ðñ !å .å 3Ý #ñ Ð5Ô6Øô*(Ð"ó *(ó ó 7ð*(ðZ ˆ/‚r   