+
    œ°³j›  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VJEPA 2 model configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringzfacebook/vjepa2-vitl-fpc64-256)Ú
checkpointc                   ó�   a € ] tR t^t o RtRt^tRt^@t^t	Rt
^t^t^tRtRtRtRtRtR	tR
tRt^tRt^t^t^
tRtRtV 3R ltRtV tR# )ÚVJEPA2ConfigaG  
crop_size (`int`, *optional*, defaults to 256):
    Input resolution of the model
frames_per_clip (`int`, *optional*, defaults to 64):
    The number of frames the model has been pretrained with. Does not impact inference.
tubelet_size (`int`, *optional*, defaults to 2):
    The number of temporal frames used for a single rastor, check paper for more information.
num_pooler_layers (`int`, *optional*, defaults to 3):
    The number of self-attention layers in the pooler.
pred_hidden_size (`int`, *optional*, defaults to 384):
    Dimensionality of the predictor layers
pred_num_attention_heads (`int`, *optional*, defaults to 12):
    Number of attention heads for each attention layer in the Predictor
pred_num_hidden_layers (`int`, *optional*, defaults to 12):
    Number of hidden layers in the Predictor
pred_num_mask_tokens (`int`, *optional*, defaults to 10):
    Define the number of mask tokens to use in the Predictor
pred_zero_init_mask_tokens (`bool`, *optional*, defaults to `True`):
    Initialize the mask tokens in the predictor with 0.
pred_mlp_ratio (`float`, *optional*, defaults to 4.0):
    Ratio of the hidden size of the MLPs used in Predictor relative to the `pred_hidden_size`.

Example:

```python
>>> from transformers import VJEPA2Config, VJEPA2Model

>>> # Initializing a VJEPA2 vjepa2-vitl-fpc64-256 style configuration
>>> configuration = VJEPA2Config()

>>> # Initializing a model (with random weights) from the vjepa2-vitl-fpc64-256  style configuration
>>> model = VJEPA2Model(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Úvjepa2é   i   g        g      @g�íµ ÷Æ°>TÚgelug{®Gáz”?i€  c                óÄ  <€ V ^8„  d   Qh/ S[ S[S[ ,          ,          S[S[ S[ 3,          ,          ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[S[ ,          ;R	&   S[ S[,          ;R
&   S[;R&   S[;R&   S[S[ ,          ;R&   S[;R&   S[;R&   S[S[ ,          ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[ S[,          ;R&   # )é   Ú
patch_sizeÚ	crop_sizeÚframes_per_clipÚtubelet_sizeÚhidden_sizeÚin_chansÚnum_attention_headsÚnum_hidden_layersÚdrop_path_rateÚ	mlp_ratioÚlayer_norm_epsÚqkv_biasÚattention_probs_dropout_probÚ
hidden_actÚinitializer_rangeÚattention_dropoutÚnum_pooler_layersÚpred_hidden_sizeÚpred_num_attention_headsÚpred_num_hidden_layersÚpred_num_mask_tokensÚpred_zero_init_mask_tokensÚpred_mlp_ratio)ÚintÚlistÚtupleÚfloatÚboolÚstr)ÚformatÚ__classdict__s   "€Úp/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/vjepa2/configuration_vjepa2.pyÚ__annotate__ÚVJEPA2Config.__annotate__   s‡  ø‡ ‚ ñT ‘d™3•i•¡%©©S¨¥/Õ1Ñ6ñU ñV ÑñW ñX ÑñY ñZ Ññ[ ñ\ Ññ] ñ^ Ññ_ ñ` Ñ!ña ñb Ññc ñd ™C•KÑ%ñe ñf ‘U�{Ñ ñg ñh Ñ ñi ñj Ññk ñl #(©#¥+Ñ3ñm ñn Ñño ñp Ñ#ñq ñr ™s•{Ñ(ñs ñt Ññu ñv Ññw ñx "Ñ&ñy ñz  Ñ$ñ{ ñ| Ñ"ñ} ñ~ !%Ñ+ñ ñ@ ™%•KÑ%òA ó    © N) Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typer   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r    r!   r"   r#   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__)r+   s   @r,   r   r      s˜   ø‡ € ñ#ðJ €Jà46€JØ€IØ€OØ€LØ€KØ€HØ!ÐØÐØ"%€NØ €IØ €NØ€HØ03Ð Ø€JØ#ÐØ%(ÐØÐØÐØ$&ÐØ"$ÐØ "ÐØ'+ÐØ"%€N÷A ƒ r/   r   N)	r5   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r0   r/   r,   Ú<module>r>      sH   ðñ "å .å 3Ý #ñ Ð;Ô<Øô>&Ð#ó >&ó ó =ð>&ðB Ð
‚r/   