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    ZhM                     @   s@   d Z ddlmZ ddlmZ eeZG dd deZdgZ	dS )zPEGASUS model configuration   )PretrainedConfig)loggingc                       s   e Zd ZdZdZdgZdddZ					
				
																d fdd	Zede	fddZ
ede	fddZ  ZS )PegasusConfiga  
    This is the configuration class to store the configuration of a [`PegasusModel`]. It is used to instantiate an
    PEGASUS 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 PEGASUS
    [google/pegasus-large](https://huggingface.co/google/pegasus-large) 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 PEGASUS model. Defines the number of different tokens that can be represented by the
            `inputs_ids` passed when calling [`PegasusModel`] or [`TFPegasusModel`].
        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.
        max_position_embeddings (`int`, *optional*, defaults to 1024):
            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).
        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.
        scale_embedding (`bool`, *optional*, defaults to `False`):
            Scale embeddings by diving by sqrt(d_model).
        use_cache (`bool`, *optional*, defaults to `True`):
            Whether or not the model should return the last key/values attentions (not used by all models)
        forced_eos_token_id (`int`, *optional*, defaults to 1):
            The id of the token to force as the last generated token when `max_length` is reached. Usually set to
            `eos_token_id`.

    Example:

    ```python
    >>> from transformers import PegasusConfig, PegasusModel

    >>> # Initializing a PEGASUS google/pegasus-large style configuration
    >>> configuration = PegasusConfig()

    >>> # Initializing a model (with random weights) from the google/pegasus-large style configuration
    >>> model = PegasusModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```ZpegasusZpast_key_valuesencoder_attention_headsd_model)num_attention_headshidden_sizeY                      Tgelu皙?{Gz?    F   c                    s   || _ || _|| _|| _|| _|| _|| _|| _|| _|| _	|| _
|| _|| _|| _|	| _|
| _|| _|| _|| _t jd|||||d| d S )N)pad_token_ideos_token_idis_encoder_decoderdecoder_start_token_idforced_eos_token_id )
vocab_sizemax_position_embeddingsr   encoder_ffn_dimencoder_layersr   decoder_ffn_dimdecoder_layersdecoder_attention_headsdropoutattention_dropoutactivation_dropoutactivation_functioninit_stdencoder_layerdropdecoder_layerdrop	use_cacheZnum_hidden_layersscale_embedding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   kwargs	__class__r   `/var/www/auris/lib/python3.10/site-packages/transformers/models/pegasus/configuration_pegasus.pyr+   d   s8   
zPegasusConfig.__init__returnc                 C      | j S N)r   r,   r   r   r0   r         z!PegasusConfig.num_attention_headsc                 C   r2   r3   )r   r4   r   r   r0   r      r5   zPegasusConfig.hidden_size)r	   r
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   r   r   r   r   r   Fr   r   r   )__name__
__module____qualname____doc__Z
model_typeZkeys_to_ignore_at_inferenceZattribute_mapr+   propertyintr   r   __classcell__r   r   r.   r0   r      sB    G
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r9   Zconfiguration_utilsr   utilsr   Z
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