
    Z j0                     d    S r SSKJr  SSKJr  SSKJr  \" SS9\ " S S	\5      5       5       rS	/rg
)zDeBERTa model configuration    )strict   )PreTrainedConfig)auto_docstringzmicrosoft/deberta-base)
checkpointc                     ^  \ rS rSr% SrSrSr\\S'   Sr	\\S'   Sr
\\S	'   Sr\\S
'   Sr\\S'   Sr\\S'   Sr\\-  \S'   Sr\\-  \S'   Sr\\S'   Sr\\S'   Sr\\S'   Sr\\S'   Sr\\S'   Sr\\S'   Sr\S-  \S'   Sr\S-  \S '   Sr\\\   -  S-  \S!'   S"r\\S#'   Sr\\\   -  S-  \S$'   S%r\\-  \S&'   Sr \\S''   S"r!\\S('   S"r"\\S)'   U 4S* jr#S+r$U =r%$ ),DebertaConfig   a  
relative_attention (`bool`, *optional*, defaults to `False`):
    Whether use relative position encoding.
max_relative_positions (`int`, *optional*, defaults to -1):
    The range of relative positions `[-max_position_embeddings, max_position_embeddings]`. Use the same value
    as `max_position_embeddings`.
position_biased_input (`bool`, *optional*, defaults to `True`):
    Whether add absolute position embedding to content embedding.
pos_att_type (`list[str]`, *optional*):
    The type of relative position attention, it can be a combination of `["p2c", "c2p"]`, e.g. `["p2c"]`,
    `["p2c", "c2p"]`.
pooler_dropout (`float`, *optional*, defaults to `0`):
    Dropout rate in the pooler module.
pooler_hidden_act (`str`, *optional*, defaults to `"gelu"`):
    Activation function used in the dropout module.
legacy (`bool`, *optional*, defaults to `True`):
    Whether or not the model should use the legacy `LegacyDebertaOnlyMLMHead`, which does not work properly
    for mask infilling tasks.

Example:

```python
>>> from transformers import DebertaConfig, DebertaModel

>>> # Initializing a DeBERTa microsoft/deberta-base style configuration
>>> configuration = DebertaConfig()

>>> # Initializing a model (with random weights) from the microsoft/deberta-base style configuration
>>> model = DebertaModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```debertaiY  
vocab_sizei   hidden_size   num_hidden_layersnum_attention_headsi   intermediate_sizegelu
hidden_actg?hidden_dropout_probattention_probs_dropout_probi   max_position_embeddingsr   type_vocab_sizeg{Gz?initializer_rangegHz>layer_norm_epsFrelative_attentionmax_relative_positionsNpad_token_idbos_token_ideos_token_idTposition_biased_inputpos_att_typeg        pooler_dropoutpooler_hidden_actlegacytie_word_embeddingsc                 H  > [        U R                  [        5      (       aL  U R                  R                  5       R	                  S5       Vs/ s H  o"R                  5       PM     snU l        UR                  SU R                  5      U l        [        TU ](  " S0 UD6  g s  snf )N|pooler_hidden_size )
isinstancer!   strlowersplitstripgetr   r(   super__post_init__)selfkwargsx	__class__s      ڂ/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/deberta/configuration_deberta.pyr1   DebertaConfig.__post_init__U   s~    d''--484E4E4K4K4M4S4STW4X Y4Xq4X YD"(**-A4CSCS"T'' !Zs   B)r(   r!   )&__name__
__module____qualname____firstlineno____doc__
model_typer   int__annotations__r   r   r   r   r   r+   r   floatr   r   r   r   r   r   boolr   r   r   r   listr    r!   r"   r#   r$   r%   r1   __static_attributes____classcell__)r5   s   @r6   r	   r	      s:    D JJKs!!!s!J'**03 %#+3#&S&OS#u# NE $$"$C$ L#* #L#*#+/L#S	/D(/"&4&+/L#S	/D(/"%NECK%#s#FD $$( (    r	   N)	r<   huggingface_hub.dataclassesr   configuration_utilsr   utilsr   r	   __all__r)   rE   r6   <module>rJ      sK    " . 3 # 34C($ C(  5C(L 
rE   