
    Z j	                     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LiLT configuration    )strict   )PreTrainedConfig)auto_docstringz!SCUT-DLVCLab/lilt-roberta-en-base)
checkpointc                   P   \ 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'   Sr\S-  \S'   Sr\\\   -  S-  \S'   Sr\\-  S-  \S'   S r\\S!'   S"r\\S#'   S$rg)%
LiltConfig   a  
channel_shrink_ratio (`int`, *optional*, defaults to 4):
    The shrink ratio compared to the `hidden_size` for the channel dimension of the layout embeddings.
max_2d_position_embeddings (`int`, *optional*, defaults to 1024):
    The maximum value that the 2D position embedding might ever be used with. Typically set this to something
    large just in case (e.g., 1024).

Examples:

```python
>>> from transformers import LiltConfig, LiltModel

>>> # Initializing a LiLT SCUT-DLVCLab/lilt-roberta-en-base style configuration
>>> configuration = LiltConfig()
>>> # Randomly initializing a model from the SCUT-DLVCLab/lilt-roberta-en-base style configuration
>>> model = LiltModel(configuration)
>>> # Accessing the model configuration
>>> configuration = model.config
```lilti: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classifier_dropout   channel_shrink_ratioi   max_2d_position_embeddings )__name__
__module____qualname____firstlineno____doc__
model_typer   int__annotations__r   r   r   r   r   strr   floatr   r   r   r   r   r   r   r   listr   r    r!   __static_attributes__r"       |/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/lilt/configuration_lilt.pyr	   r	      s    ( JJKs!!!s!J'**03 %#+3#&S&OS#u#!NE! L#* #L#*#+/L#S	/D(/-1d*1 !#!&**r/   r	   N)	r'   huggingface_hub.dataclassesr   configuration_utilsr   utilsr   r	   __all__r"   r/   r0   <module>r5      sH     . 3 # >?(+! (+  @(+V .r/   