
    i                     j    d Z ddlmZ ddlmZ ddlmZ  ed      e G d d	e                    Zd	gZy
)zX-MOD configuration    )strict   )PreTrainedConfig)auto_docstringzfacebook/xmod-base)
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eed	<   d
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XmodConfigaP  
    pre_norm (`bool`, *optional*, defaults to `False`):
        Whether to apply layer normalization before each block.
    adapter_reduction_factor (`int` or `float`, *optional*, defaults to 2):
        The factor by which the dimensionality of the adapter is reduced relative to `hidden_size`.
    adapter_layer_norm (`bool`, *optional*, defaults to `False`):
        Whether to apply a new layer normalization before the adapter modules (shared across all adapters).
    adapter_reuse_layer_norm (`bool`, *optional*, defaults to `True`):
        Whether to reuse the second layer normalization and apply it before the adapter modules as well.
    ln_before_adapter (`bool`, *optional*, defaults to `True`):
        Whether to apply the layer normalization before the residual connection around the adapter module.
    languages (`Iterable[str]`, *optional*, defaults to `["en_XX"]`):
        An iterable of language codes for which adapter modules should be initialized.
    default_language (`str`, *optional*):
        Language code of a default language. It will be assumed that the input is in this language if no language
        codes are explicitly passed to the forward method.

    Examples:

    ```python
    >>> from transformers import XmodConfig, XmodModel

    >>> # Initializing an X-MOD facebook/xmod-base style configuration
    >>> configuration = XmodConfig()

    >>> # Initializing a model (with random weights) from the facebook/xmod-base style configuration
    >>> model = XmodModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```xmodi:w  
vocab_sizei   hidden_size   num_hidden_layersnum_attention_headsi   intermediate_sizegelu
hidden_actg?hidden_dropout_probattention_probs_dropout_probi   max_position_embeddings   type_vocab_sizeg{Gz?initializer_rangeg-q=layer_norm_eps   Npad_token_idr   bos_token_ideos_token_idT	use_cacheclassifier_dropoutFpre_normadapter_reduction_factoradapter_layer_normadapter_reuse_layer_normln_before_adapter)en_XX.	languagesdefault_language
is_decoderadd_cross_attentiontie_word_embeddings)'__name__
__module____qualname____doc__
model_typer   int__annotations__r   r   r   r   r   strr   floatr   r   r   r   r   r   r   r   listr   boolr   r    r!   r"   r#   r$   r&   tupler'   r(   r)   r*        |/var/www/vps2.regionflexible.com/Desarrollo/venv/lib/python3.12/site-packages/transformers/models/xmod/configuration_xmod.pyr	   r	      sg   @ JJKs!!!s!J'**03 %#+3#&S&OS#u#!NE! L#*  L#* +,L#S	/D(,It-1d*1Hd$%c%$$%)d)"t"-7ItCy5c?*7#'cDj'J %% $$r8   r	   N)	r.   huggingface_hub.dataclassesr   configuration_utilsr   utilsr   r	   __all__r7   r8   r9   <module>r>      sG     . 3 # /0=%! =%  1=%@ .r8   