+
    œ°³jõ  ã                   ót   € R t ^ RI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MAMBA2 configurationN)Ústrict)ÚPreTrainedConfig)Úauto_docstringzstate-spaces/mamba2-2.8b)Ú
checkpointc                   óØ   a a€ ] tR t^t oRtRt^€t^@tRtRt	^€t
^@tRt^t^ t^t^t^t^tRtRtRtR	tRtR
tRtR	tRtR]! R4      3tRtRtRt Rt!V 3R lt"R t#]$R 4       t%V3R lt&Rt'Vt(V ;t)# )ÚMamba2ConfigaX  
layer_norm_epsilon (`float`, *optional*, defaults to 1e-05):
    The epsilon to use in the layer normalization layers..
expand (`int`, *optional*, defaults to 2):
    Expanding factor used to determine the intermediate size.
n_groups (`int`, *optional*, defaults to 8):
    Number of groups for the evolution matrices of mamba 2.
use_bias (`bool`, *optional*, defaults to `False`):
    Whether or not to use bias in ["in_proj", "out_proj"] of the mixer block
use_conv_bias (`bool`, *optional*, defaults to `True`):
    Whether or not to use bias in the convolution layer of the mixer block.
residual_in_fp32 (`bool`, *optional*, defaults to `True`):
    Whether or not residuals should be in `float32`. If set to `False` residuals will keep the same `dtype` as the rest of the model
rescale_prenorm_residual (`bool`, *optional*, defaults to `False`):
    Whether or not to rescale `out_proj` weights when initializing.
chunk_size (`int`, *optional*, defaults to 256):
    Size of the chunks that will comprise the sequence.

Example:

```python
>>> from transformers import Mamba2Config, Mamba2Model

>>> # Initializing a Mamba2 configuration
>>> configuration = Mamba2Config()

>>> # Initializing a model (with random weights) from the configuration
>>> model = Mamba2Model(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Úmamba2i €  i   gñhãˆµøä>FTÚsilugš™™™™™¹?Úautogü©ñÒMbP?g-Cëâ6?g        Úinfé   c                óº   <€ V P                   R 8X  d(   \        P                  ! V P                  ^,          4      MV P                   V n         \        SV `  ! R/ VB  R# )r
   N© )Útime_step_rankÚmathÚceilÚhidden_sizeÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s   &,€Úp/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/mamba2/configuration_mamba2.pyr   ÚMamba2Config.__post_init__Z   sJ   ø€ à04×0CÑ0CÀvÔ0MŒD�IŠI�d×&Ñ&¨Õ+Ô,ÐSW×SfÑSfð 	Ôô 	‰ÒÑ' Ô'ó    c                ó  € V P                   V P                  ,          V P                  V P                  ,          8w  dI   \	        RV P                   V P                  ,           RV P                  V P                  ,           R24      hR# )zOPart of `@strict`-powered validation. Validates the architecture of the config.z2Inconsistent configuration: hidden_size * expand (z#) must equal num_heads * head_dim (z).N)r   ÚexpandÚ	num_headsÚhead_dimÚ
ValueError©r   s   &r   Úvalidate_architectureÚ"Mamba2Config.validate_architecture`   sr   € à×Ñ˜tŸ{™{Õ*°·±ÀÇÁÕ0NÔOÜðØ×$Ñ$ t§{¡{Õ2Ð3ð 4Ø—N‘N T§]¡]Õ2Ð3°2ð7óð ñ Pr   c                ó*   € R .V P                   ,          # )Úlinear_attention)Únum_hidden_layersr    s   &r   Úlayer_typesÚMamba2Config.layer_typesi   s   € à"Ð# d×&<Ñ&<Õ<Ð<r   c                óì  <€ V ^8„  d   Qh/ 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&   S[ ;R&   S[;R&   S[;R&   S[;R&   S[;R&   S[;R&   S[S[ ,          ;R&   S[;R&   S[;R&   S[;R&   S[S[,          S[S[R3,          ,          ;R&   S[;R&   S[;R&   S[ ;R&   S[;R&   # )é   r   r   Ú
vocab_sizer   Ú
state_sizer%   Úlayer_norm_epsilonNÚpad_token_idÚbos_token_idÚeos_token_idr   Úconv_kernelÚn_groupsÚuse_biasÚuse_conv_biasÚ
hidden_actÚinitializer_rangeÚresidual_in_fp32r   Útime_step_minÚtime_step_maxÚtime_step_floor.Útime_step_limitÚrescale_prenorm_residualÚ	use_cacheÚ
chunk_sizeÚtie_word_embeddings)ÚintÚfloatÚlistÚboolÚstrÚtuple)ÚformatÚ__classdict__s   "€r   Ú__annotate__ÚMamba2Config.__annotate__   sÄ  ø‡ ‚ ñL ÑñM 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^ ™™S�	•/ DÕ(Ñ,ñ_ ñ` �Oña ñb Ññc ñd Ññe ñf Ññg ñh Ññi ñj Ññk ñl Ñ"ñm ñn Ñ!ño ñp ™#•IÑ&ñq ñr Ñ ñs ñt Ññu ñv Ñ!ñw ñx ™%•[¡5©°¨Õ#4Õ4ÑJñy ñz #Ñ*ñ{ ñ| Ññ} ñ~ Ññ ñ@ Ñ%òA 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   r0   r1   r2   r3   r4   r5   r6   r   r7   r8   r9   r@   r:   r;   r<   r=   r>   r   r!   Úpropertyr&   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__Ú__classcell__)r   rF   s   @@r   r   r      sÎ   ù‡ € ñðB €Jà€IØ€HØ€JØ€KØ€JØÐØ $ÐØ €LØ €LØ+,€LØ€FØ€KØ€HØ€HØ€MØ€JØ"ÐØ!ÐØ &€NØ €MØ€MØ!€OØ8;¹UÀ5»\Ð7J€OØ%*ÐØ€IØ€JØ %Ðõ(òð ñ=ó ð=÷e … r   r   )
rM   r   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r   r   r   Ú<module>rX      sN   ðñ ã å .å 3Ý #ñ Ð5Ô6ØôQ=Ð#ó Q=ó ó 7ðQ=ðh Ð
‚r   