+
    œ°³jÆ
  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MRA model configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringzuw-madison/mra-base-512-4)Ú
checkpointc                   óˆ   a € ] tR t^t o RtRtRtRt^t^t	Rt
RtRtRtRt^tR	tR
t^tRt^ t^ t^t^ t^tRtRtV 3R ltRtV tR# )Ú	MraConfigaâ  
block_per_row (`int`, *optional*, defaults to 4):
    Used to set the budget for the high resolution scale.
approx_mode (`str`, *optional*, defaults to `"full"`):
    Controls whether both low and high resolution approximations are used. Set to `"full"` for both low and
    high resolution and `"sparse"` for only low resolution.
initial_prior_first_n_blocks (`int`, *optional*, defaults to 0):
    The initial number of blocks for which high resolution is used.
initial_prior_diagonal_n_blocks (`int`, *optional*, defaults to 0):
    The number of diagonal blocks for which high resolution is used.

Example:

```python
>>> from transformers import MraConfig, MraModel

>>> # Initializing a Mra uw-madison/mra-base-512-4 style configuration
>>> configuration = MraConfig()

>>> # Initializing a model (with random weights) from the uw-madison/mra-base-512-4 style configuration
>>> model = MraModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```ÚmraiYÄ  i   i   Úgelugš™™™™™¹?i   g{®Gáz”?gñhãˆµøä>ÚfullFTc                ó€  <€ V ^8„  d   Qh/ S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[;R&   S[S[ ,          ;R&   S[S[ ,          ;R&   S[ ;R	&   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&   S[;R&   # )é   Ú
vocab_sizeÚhidden_sizeÚnum_hidden_layersÚnum_attention_headsÚintermediate_sizeÚ
hidden_actÚhidden_dropout_probÚattention_probs_dropout_probÚmax_position_embeddingsÚtype_vocab_sizeÚinitializer_rangeÚlayer_norm_epsÚblock_per_rowÚapprox_modeÚinitial_prior_first_n_blocksÚinitial_prior_diagonal_n_blocksNÚpad_token_idÚbos_token_idÚeos_token_idÚadd_cross_attentionÚtie_word_embeddings)ÚintÚstrÚfloatÚlistÚbool)ÚformatÚ__classdict__s   "€Új/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/mra/configuration_mra.pyÚ__annotate__ÚMraConfig.__annotate__   s[  ø‡ ‚ ñ> Ññ? ñ@ ÑñA ñB ÑñC ñD Ñ!ñE ñF Ñ!ñG ñH ÑñI ñJ ¡�Ñ*ñK ñL #(©#¥+Ñ3ñM ñN !Ñ&ñO ñP ÑñQ ñR Ñ#ñS ñT Ñ ñU ñV ÑñW ñX ÑñY ñZ #&Ñ)ñ[ ñ\ &)Ñ,ñ] ñ^ ˜•*Ñ ñ_ ñ` ˜•*Ñ ña ñb ™™S�	•/ DÕ(Ñ,ñc ñd Ñ%ñe ñf Ñ$òg 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!   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__)r(   s   @r)   r   r      s�   ø‡ € ñð4 €Jà€JØ€KØÐØ!ÐØ!ÐØ€JØ'*ÐØ03Ð Ø#&ÐØ€OØ#ÐØ €NØ€MØ€KØ()Ð Ø+,Ð#Ø €LØ €LØ+,€LØ %ÐØ $Ð÷g ƒ r,   r   N)	r2   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6Ô7Øô1%Ð ó 1%ó ó 8ð1%ðh ˆ-‚r,   