
    fTh                     `    S r SSKJr  SSKJr  \R
                  " \5      r " S S\5      rS/r	g)zLUKE configuration   )PretrainedConfig)loggingc                   Z   ^  \ rS rSrSrSr                   SU 4S jjrSrU =r$ )
LukeConfig   a4  
This is the configuration class to store the configuration of a [`LukeModel`]. It is used to instantiate a LUKE
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
defaults will yield a similar configuration to that of the LUKE
[studio-ousia/luke-base](https://huggingface.co/studio-ousia/luke-base) architecture.

Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information.


Args:
    vocab_size (`int`, *optional*, defaults to 50267):
        Vocabulary size of the LUKE model. Defines the number of different tokens that can be represented by the
        `inputs_ids` passed when calling [`LukeModel`].
    entity_vocab_size (`int`, *optional*, defaults to 500000):
        Entity vocabulary size of the LUKE model. Defines the number of different entities that can be represented
        by the `entity_ids` passed when calling [`LukeModel`].
    hidden_size (`int`, *optional*, defaults to 768):
        Dimensionality of the encoder layers and the pooler layer.
    entity_emb_size (`int`, *optional*, defaults to 256):
        The number of dimensions of the entity embedding.
    num_hidden_layers (`int`, *optional*, defaults to 12):
        Number of hidden layers in the Transformer encoder.
    num_attention_heads (`int`, *optional*, defaults to 12):
        Number of attention heads for each attention layer in the Transformer encoder.
    intermediate_size (`int`, *optional*, defaults to 3072):
        Dimensionality of the "intermediate" (often named feed-forward) layer in the Transformer encoder.
    hidden_act (`str` or `Callable`, *optional*, defaults to `"gelu"`):
        The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
        `"relu"`, `"silu"` and `"gelu_new"` are supported.
    hidden_dropout_prob (`float`, *optional*, defaults to 0.1):
        The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
    attention_probs_dropout_prob (`float`, *optional*, defaults to 0.1):
        The dropout ratio for the attention probabilities.
    max_position_embeddings (`int`, *optional*, defaults to 512):
        The maximum sequence length that this model might ever be used with. Typically set this to something large
        just in case (e.g., 512 or 1024 or 2048).
    type_vocab_size (`int`, *optional*, defaults to 2):
        The vocabulary size of the `token_type_ids` passed when calling [`LukeModel`].
    initializer_range (`float`, *optional*, defaults to 0.02):
        The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
    layer_norm_eps (`float`, *optional*, defaults to 1e-12):
        The epsilon used by the layer normalization layers.
    use_entity_aware_attention (`bool`, *optional*, defaults to `True`):
        Whether or not the model should use the entity-aware self-attention mechanism proposed in [LUKE: Deep
        Contextualized Entity Representations with Entity-aware Self-attention (Yamada et
        al.)](https://arxiv.org/abs/2010.01057).
    classifier_dropout (`float`, *optional*):
        The dropout ratio for the classification head.
    pad_token_id (`int`, *optional*, defaults to 1):
        Padding token id.
    bos_token_id (`int`, *optional*, defaults to 0):
        Beginning of stream token id.
    eos_token_id (`int`, *optional*, defaults to 2):
        End of stream token id.

Examples:

```python
>>> from transformers import LukeConfig, LukeModel

>>> # Initializing a LUKE configuration
>>> configuration = LukeConfig()

>>> # Initializing a model from the configuration
>>> model = LukeModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```lukec                    > [         TU ]  " SUUUS.UD6  Xl        X l        X0l        X@l        XPl        X`l        Xl        Xpl	        Xl
        Xl        Xl        Xl        Xl        Xl        Xl        UU l        g)zConstructs LukeConfig.)pad_token_idbos_token_ideos_token_idN )super__init__
vocab_sizeentity_vocab_sizehidden_sizeentity_emb_sizenum_hidden_layersnum_attention_heads
hidden_actintermediate_sizehidden_dropout_probattention_probs_dropout_probmax_position_embeddingstype_vocab_sizeinitializer_rangelayer_norm_epsuse_entity_aware_attentionclassifier_dropout)selfr   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r
   r   r   kwargs	__class__s                        c/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/luke/configuration_luke.pyr   LukeConfig.__init__b   s    0 	sl\hslrs$!2&.!2#6 $!2#6 ,H)'>$.!2,*D'"4    )r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   )i[  i  i         r'   i   gelu皙?r)   i      g{Gz?g-q=TN       r*   )	__name__
__module____qualname____firstlineno____doc__
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