+
    œ°³jí
  ã                   ó|   € R t ^ RI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Dac model configurationN)Ústrict)ÚPreTrainedConfig)Úauto_docstringzdescript/dac_16khz)Ú
checkpointc                   óŠ   a a€ ] tR t^t oRtRt^@tRtRt^	t	Rt
^tRtRtRtRtV 3R	 lt]V3R
 lR l4       tV3R ltRtVtV ;t# )Ú	DacConfiga”  
downsampling_ratios (`list[int]`, *optional*, defaults to `[2, 4, 8, 8]`):
    Ratios for downsampling in the encoder. These are used in reverse order for upsampling in the decoder.
quantizer_dropout (`bool`, *optional*, defaults to 0):
    Whether to apply dropout to the quantizer.
commitment_loss_weight (float, *optional*, defaults to 0.25):
    Weight of the commitment loss term in the VQVAE loss function.
codebook_loss_weight (float, *optional*, defaults to 1.0):
    Weight of the codebook loss term in the VQVAE loss function.

Example:

```python
>>> from transformers import DacModel, DacConfig

>>> # Initializing a "descript/dac_16khz" style configuration
>>> configuration = DacConfig()

>>> # Initializing a model (with random weights) from the "descript/dac_16khz" style configuration
>>> model = DacModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Údaci   i   g        g      Ð?g      ð?i€>  c                ó  <€ V P                   R R R1,          V n        V P                  ^\        V P                   4      ,          ,          V n        \        \        P                  ! V P                   4      4      V n        \        SV `(  ! R/ VB  R # )Néÿÿÿÿ© )Údownsampling_ratiosÚupsampling_ratiosÚencoder_hidden_sizeÚlenÚhidden_sizeÚintÚnpÚprodÚ
hop_lengthÚsuperÚ__post_init__)ÚselfÚkwargsÚ	__class__s   &,€Új/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/dac/configuration_dac.pyr   ÚDacConfig.__post_init__B   sh   ø€ Ø!%×!9Ñ!9¹$¸B¸$Õ!?ˆÔØ×3Ñ3°q¼CÀ×@XÑ@XÓ<YÕ7YÕZˆÔÜœbŸgšg d×&>Ñ&>Ó?Ó@ˆŒÜ‰ÒÑ' Ô'ó    c                ó    <€ V ^8„  d   QhRS[ /# )é   Úreturn)r   )ÚformatÚ__classdict__s   "€r   Ú__annotate__ÚDacConfig.__annotate__I   s   ø€ ÷ :ñ :™Cñ :r   c                ó�   € \         P                  ! V P                  4      p\        P                  ! V P
                  V,          4      # )N)r   r   r   ÚmathÚceilÚsampling_rate)r   r   s   & r   Ú
frame_rateÚDacConfig.frame_rateH   s0   € ä—W’W˜T×3Ñ3Ó4ˆ
Ü�yŠy˜×+Ñ+¨jÕ8Ó9Ð9r   c                óÖ   <€ V ^8„  d   Qh/ S[ ;R&   S[S[ ,          S[S[ R3,          ,          ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[ ;R&   S[S[ ,          ;R&   S[;R	&   S[;R
&   S[ ;R&   # )r   r   .r   Údecoder_hidden_sizeÚn_codebooksÚcodebook_sizeÚcodebook_dimÚquantizer_dropoutÚcommitment_loss_weightÚcodebook_loss_weightr'   )r   ÚlistÚtupleÚfloat)r    r!   s   "€r   r"   r#      s¬   ø‡ ‚ ñ< Ñ!ñ= ñ> ™c�¡U©3°¨8¥_Õ4ÑCñ? ñ@ Ñ#ñA ñB ÑñC ñD ÑñE ñF ÑñG ñH ™s•{Ñ(ñI ñJ "Ñ(ñK ñL  Ñ%ñM ñN ÑòO r   )r   r   r   )r   é   é   r6   )Ú__name__Ú
__module__Ú__qualname__Ú__firstlineno__Ú__doc__Ú
model_typer   r   r+   r,   r-   r.   r/   r0   r1   r'   r   Úpropertyr(   Ú__annotate_func__Ú__static_attributes__Ú__classdictcell__Ú__classcell__)r   r!   s   @@r   r   r      sj   ù‡ € ñð2 €Jà!ÐØ7CÐØ#ÐØ€KØ€MØ€LØ%(ÐØ$(ÐØ"%ÐØ€Mõ(ð ÷:ó ð:÷a … r   r   )r;   r%   Únumpyr   Úhuggingface_hub.dataclassesr   Úconfiguration_utilsr   Úutilsr   r   Ú__all__r   r   r   Ú<module>rG      sM   ðñ ã ã Ý .å 3Ý #ñ Ð/Ô0Øô0:Ð ó 0:ó ó 1ð0:ðf ˆ-‚r   