
    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SqueezeBERT model configuration    )strict   )PreTrainedConfig)auto_docstringzsqueezebert/squeezebert-uncased)
checkpointc                      e Zd ZU dZdZdZeed<   dZeed<   dZ	eed<   dZ
eed	<   d
Zeed<   dZeed<   dZeez  ed<   dZeez  ed<   dZeed<   dZeed<   dZeed<   dZeed<   dZedz  ed<   dZedz  ed<   dZeee   z  dz  ed<   dZeed<   dZeed <   dZeed!<   dZeed"<   d#Zeed$<   dZeed%<   dZeed&<   d'Z e!ed(<   y))SqueezeBertConfiga6  
    q_groups (`int`, *optional*, defaults to 4):
        The number of groups in Q layer.
    k_groups (`int`, *optional*, defaults to 4):
        The number of groups in K layer.
    v_groups (`int`, *optional*, defaults to 4):
        The number of groups in V layer.
    post_attention_groups (`int`, *optional*, defaults to 1):
        The number of groups in the first feed forward network layer.
    intermediate_groups (`int`, *optional*, defaults to 4):
        The number of groups in the second feed forward network layer.
    output_groups (`int`, *optional*, defaults to 4):
        The number of groups in the third feed forward network layer.

    Examples:

    ```python
    >>> from transformers import SqueezeBertConfig, SqueezeBertModel

    >>> # Initializing a SqueezeBERT configuration
    >>> configuration = SqueezeBertConfig()

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

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```
    squeezeberti: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_epsr   Npad_token_idbos_token_ideos_token_idembedding_size   q_groupsk_groupsv_groups   post_attention_groupsintermediate_groupsoutput_groupsT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   r   r    r!   r#   r$   r%   r&   bool     /var/www/vps2.regionflexible.com/Desarrollo/venv/lib/python3.12/site-packages/transformers/models/squeezebert/configuration_squeezebert.pyr	   r	      s   < JJKs!!!s!J'**03 %#+3#&S&OS#u#!NE! L#* #L#*#+/L#S	/D(/NCHcHcHc!"3"  M3 $$r3   r	   N)	r*   huggingface_hub.dataclassesr   configuration_utilsr   utilsr   r	   __all__r2   r3   r4   <module>r9      sH    & . 3 # <=7%( 7%  >7%t 
r3   