
    fTh                     p    S r SSKJrJr  SSKJr  SSKJr  \R                  " \	5      r
 " S S\5      rS/rg)	zLED model configuration    )ListUnion   )PretrainedConfig)loggingc                      ^  \ rS rSrSrSrSSSSS.r                         SS	\\\	   \	4   4U 4S
 jjjr
SrU =r$ )	LEDConfig   a  
This is the configuration class to store the configuration of a [`LEDModel`]. It is used to instantiate an LED
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 LED
[allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) 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 50265):
        Vocabulary size of the LED model. Defines the number of different tokens that can be represented by the
        `inputs_ids` passed when calling [`LEDModel`] or [`TFLEDModel`].
    d_model (`int`, *optional*, defaults to 1024):
        Dimensionality of the layers and the pooler layer.
    encoder_layers (`int`, *optional*, defaults to 12):
        Number of encoder layers.
    decoder_layers (`int`, *optional*, defaults to 12):
        Number of decoder layers.
    encoder_attention_heads (`int`, *optional*, defaults to 16):
        Number of attention heads for each attention layer in the Transformer encoder.
    decoder_attention_heads (`int`, *optional*, defaults to 16):
        Number of attention heads for each attention layer in the Transformer decoder.
    decoder_ffn_dim (`int`, *optional*, defaults to 4096):
        Dimensionality of the "intermediate" (often named feed-forward) layer in decoder.
    encoder_ffn_dim (`int`, *optional*, defaults to 4096):
        Dimensionality of the "intermediate" (often named feed-forward) layer in decoder.
    activation_function (`str` or `function`, *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.
    dropout (`float`, *optional*, defaults to 0.1):
        The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
    attention_dropout (`float`, *optional*, defaults to 0.0):
        The dropout ratio for the attention probabilities.
    activation_dropout (`float`, *optional*, defaults to 0.0):
        The dropout ratio for activations inside the fully connected layer.
    classifier_dropout (`float`, *optional*, defaults to 0.0):
        The dropout ratio for classifier.
    max_encoder_position_embeddings (`int`, *optional*, defaults to 16384):
        The maximum sequence length that the encoder might ever be used with.
    max_decoder_position_embeddings (`int`, *optional*, defaults to 16384):
        The maximum sequence length that the decoder might ever be used with.
    init_std (`float`, *optional*, defaults to 0.02):
        The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
    encoder_layerdrop (`float`, *optional*, defaults to 0.0):
        The LayerDrop probability for the encoder. See the [LayerDrop paper](see https://arxiv.org/abs/1909.11556)
        for more details.
    decoder_layerdrop (`float`, *optional*, defaults to 0.0):
        The LayerDrop probability for the decoder. See the [LayerDrop paper](see https://arxiv.org/abs/1909.11556)
        for more details.
    use_cache (`bool`, *optional*, defaults to `True`):
        Whether or not the model should return the last key/values attentions (not used by all models)

Example:

```python
>>> from transformers import LEDModel, LEDConfig

>>> # Initializing a LED allenai/led-base-16384 style configuration
>>> configuration = LEDConfig()

>>> # Initializing a model from the allenai/led-base-16384 style configuration
>>> model = LEDModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```ledencoder_attention_headsd_modelattention_dropoutinit_std)num_attention_headshidden_sizeattention_probs_dropout_probinitializer_rangeattention_windowc           	      :  > Xl         X l        X0l        Xl        XPl        X@l        X`l        Xl        Xpl        Xl	        UU l
        UU l        UU l        Xl        UU l        Xl        Xl        UU l        Xl        X@l        UU l        [*        TU ]X  " SUUUUUS.UD6  g )N)pad_token_idbos_token_ideos_token_idis_encoder_decoderdecoder_start_token_id )
vocab_sizemax_encoder_position_embeddingsmax_decoder_position_embeddingsr   encoder_ffn_dimencoder_layersr   decoder_ffn_dimdecoder_layersdecoder_attention_headsdropoutr   activation_dropoutactivation_functionr   encoder_layerdropdecoder_layerdropclassifier_dropout	use_cachenum_hidden_layersr   super__init__)selfr   r   r   r    r   r   r"   r!   r#   r'   r(   r*   r   r&   r   r$   r   r%   r   r   r)   r   r   r   r   kwargs	__class__s                              a/var/www/auris/envauris/lib/python3.13/site-packages/transformers/models/led/configuration_led.pyr-   LEDConfig.__init__h   s    : %/N,/N,.,'>$.,'>$!2"4#6  !2!2"4"!/ 0 	
%%%1#9	
 	
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