
    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MRA model configuration    )strict   )PreTrainedConfig)auto_docstringzuw-madison/mra-base-512-4)
checkpointc                   n   \ 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r\\S '   Sr\S!-  \S"'   Sr\S!-  \S#'   S$r\\\   -  S!-  \S%'   S&r\\S''   S(r \\S)'   S*r!g!)+	MraConfig   a  
block_per_row (`int`, *optional*, defaults to 4):
    Used to set the budget for the high resolution scale.
approx_mode (`str`, *optional*, defaults to `"full"`):
    Controls whether both low and high resolution approximations are used. Set to `"full"` for both low and
    high resolution and `"sparse"` for only low resolution.
initial_prior_first_n_blocks (`int`, *optional*, defaults to 0):
    The initial number of blocks for which high resolution is used.
initial_prior_diagonal_n_blocks (`int`, *optional*, defaults to 0):
    The number of diagonal blocks for which high resolution is used.

Example:

```python
>>> from transformers import MraConfig, MraModel

>>> # Initializing a Mra uw-madison/mra-base-512-4 style configuration
>>> configuration = MraConfig()

>>> # Initializing a model (with random weights) from the uw-madison/mra-base-512-4 style configuration
>>> model = MraModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```mraiY  
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_rangegh㈵>layer_norm_eps   block_per_rowfullapprox_moder   initial_prior_first_n_blocksinitial_prior_diagonal_n_blocksNpad_token_idbos_token_id   eos_token_idFadd_cross_attentionTtie_word_embeddings )"__name__
__module____qualname____firstlineno____doc__
model_typer   int__annotations__r   r   r   r   r   strr   floatr   r   r   r   r   r   r   r   r    r!   r"   r$   listr%   boolr&   __static_attributes__r'       z/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/mra/configuration_mra.pyr	   r	      s   4 JJKs!!!s!J'**03 %#+3#&S&OS#u# NE M3K() #)+,#S, L#*  L#* +,L#S	/D(, %% $$r5   r	   N)	r,   huggingface_hub.dataclassesr   configuration_utilsr   utilsr   r	   __all__r'   r5   r6   <module>r;      sG     . 3 # 671%  1%  81%h -r5   