+
    œ°³jÞ	  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FNet model configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringzgoogle/fnet-base)Ú
checkpointc                   ót   a € ] tR t^t o RtRtRtRt^tRt	Rt
RtRt^tR	tR
tRtRt^t^t^tRtV 3R ltRtV tR# )Ú
FNetConfiga¬  
use_tpu_fourier_optimizations (`bool`, *optional*, defaults to `False`):
    Determines whether to use TPU optimized FFTs. If `True`, the model will favor axis-wise FFTs transforms.
    Set to `False` for GPU/CPU hardware, in which case n-dimensional FFTs are used.
tpu_short_seq_length (`int`, *optional*, defaults to 512):
    The sequence length that is expected by the model when using TPUs. This will be used to initialize the DFT
    matrix only when *use_tpu_fourier_optimizations* is set to `True` and the input sequence is shorter than or
    equal to 4096 tokens.

Example:

```python
>>> from transformers import FNetConfig, FNetModel

>>> # Initializing a FNet fnet-base style configuration
>>> configuration = FNetConfig()

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

>>> # Accessing the model configuration
>>> configuration = model.config
```Úfneti }  i   i   Úgelu_newgš™™™™™¹?i   g{®Gáz”?gê-�™—q=FTc                ó4  <€ V ^8„  d   Qh/ S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[S[ ,          ;R&   S[ ;R&   S[ ;R&   S[;R	&   S[;R
&   S[;R&   S[ ;R&   S[ R,          ;R&   S[ R,          ;R&   S[ S[S[ ,          ,          R,          ;R&   S[;R&   # )é   Ú
vocab_sizeÚhidden_sizeÚnum_hidden_layersÚintermediate_sizeÚ
hidden_actÚhidden_dropout_probÚmax_position_embeddingsÚtype_vocab_sizeÚinitializer_rangeÚlayer_norm_epsÚuse_tpu_fourier_optimizationsÚtpu_short_seq_lengthNÚpad_token_idÚbos_token_idÚeos_token_idÚtie_word_embeddings)ÚintÚstrÚfloatÚboolÚlist)ÚformatÚ__classdict__s   "€Úl/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/fnet/configuration_fnet.pyÚ__annotate__ÚFNetConfig.__annotate__   s  ø‡ ‚ ñ: Ññ; ñ< Ññ= ñ> Ññ? ñ@ Ñ!ñA ñB Ñ ñC ñD ¡�Ñ*ñE ñF !Ñ&ñG ñH ÑñI ñJ Ñ#ñK ñL Ñ!ñM ñN $(Ñ/ñO ñP Ñ#ñQ ñR ˜•*Ñ ñS ñT ˜•*Ñ ñU ñV ™™S�	•/ DÕ(Ñ,ñW ñX Ñ$òY 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   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__)r"   s   @r#   r   r      sq   ø‡ € ñð0 €Jà€JØ€KØÐØ!ÐØ €JØ'*ÐØ#&ÐØ€OØ#ÐØ!€NØ*/Ð!Ø #ÐØ €LØ €LØ+,€LØ $Ð÷Y ƒ r&   r   N)	r,   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r'   r&   r#   Ú<module>r5      sG   ðñ å .å 3Ý #ñ Ð-Ô.Øô*%Ð!ó *%ó ó /ð*%ðZ ˆ.‚r&   