
     `i!                     b    d dl mZ ddlmZmZ  G d de          Z G d de          ZddgZdS )	   )PretrainedConfig   )CONFIG_MAPPING
AutoConfigc                   N     e Zd ZdZdZddddddZ	 	 	 	 	 	 	 	 	 	 	 d fd	Z xZS )VoxtralEncoderConfiga`
  
    This is the configuration class to store the configuration of a [`VoxtralEncoder`]. It is used to instantiate a
    Voxtral audio encoder according to the specified arguments, defining the model architecture. Instantiating a
    configuration with the defaults will yield a similar configuration to that of the audio encoder of the Voxtral
    architecture.

    e.g. [mistralai/Voxtral-Mini-3B-2507](https://huggingface.co/mistralai/Voxtral-Mini-3B-2507)

    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 51866):
            Vocabulary size of the model.
        hidden_size (`int`, *optional*, defaults to 1280):
            Dimensionality of the hidden representations.
        intermediate_size (`int`, *optional*, defaults to 5120):
            Dimension of the MLP representations.
        num_hidden_layers (`int`, *optional*, defaults to 32):
            Number of hidden layers in the Transformer encoder.
        num_attention_heads (`int`, *optional*, defaults to 20):
            Number of attention heads for each attention layer in the Transformer encoder.
        scale_embedding (`bool`, *optional*, defaults to `False`):
            Scale embeddings by dividing by sqrt(hidden_size) if True.
        activation_function (`str`, *optional*, defaults to `"gelu"`):
            The non-linear activation function (function or string) in the encoder and pooler. If string, "gelu",
        num_mel_bins (`int`, *optional*, defaults to 128):
            Number of mel features used per input features. Should correspond to the value used in the
            `VoxtralProcessor` class.
        max_source_positions (`int`, *optional*, defaults to 1500):
            The maximum sequence length of log-mel filter-bank features that this model might ever be used with.
        initializer_range (`float`, *optional*, defaults to 0.02):
            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
        attention_dropout (`float`, *optional*, defaults to 0.0):
            The dropout ratio for the attention probabilities.

    ```python
    >>> from transformers import VoxtralEncoderConfig, VoxtralEncoder

    >>> # Initializing a VoxtralEncoderConfig
    >>> configuration = VoxtralEncoderConfig()

    >>> # Initializing a VoxtralEncoder (with random weights)
    >>> model = VoxtralEncoder(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```voxtral_encoderhidden_sizenum_hidden_layersnum_attention_headsintermediate_size	layerdrop)d_modelencoder_layersencoder_attention_headsencoder_ffn_dimencoder_layerdrop               Fgelu     {Gz?        c                      t                      j        di | || _        || _        || _        || _        || _        || _        || _        || _	        |	| _
        |
| _        d| _        d| _        d| _        || _        d S )Nr    )super__init__
vocab_sizer
   r   r   r   scale_embeddingactivation_functionnum_mel_binsmax_source_positionsinitializer_rangedropoutr   activation_dropoutattention_dropout)selfr"   r
   r   r   r   r#   r$   r%   r&   r'   r*   kwargs	__class__s                /home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/transformers/models/voxtral/configuration_voxtral.pyr!   zVoxtralEncoderConfig.__init__P   s     	""6"""$&!2!2#6 .#6 ($8!!2
 "%!2    )r   r   r   r   r   Fr   r   r   r   r   )__name__
__module____qualname____doc__
model_typeattribute_mapr!   __classcell__r-   s   @r.   r   r      s        / /b #J !-#8.( M "!$3 $3 $3 $3 $3 $3 $3 $3 $3 $3r/   r   c                   T     e Zd ZdZdZeedZddddddd	d
ddd
Z	 	 	 	 d fd	Z xZ	S )VoxtralConfiga3  
    This is the configuration class to store the configuration of a [`VoxtralForConditionalGeneration`]. It is used to instantiate an
    Voxtral 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 Voxtral-Mini-3B.

    e.g. [mistralai/Voxtral-Mini-3B-2507](https://huggingface.co/mistralai/Voxtral-Mini-3B-2507)

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

    Args:
        audio_config (`Union[AutoConfig, dict]`, *optional*):
            The config object or dictionary of the audio encoder.
        text_config (`Union[AutoConfig, dict]`, *optional*):
            The config object or dictionary of the text model.
        audio_token_id (`int`, *optional*):
            The image token index to encode the image prompt.
        projector_hidden_act (`str`, *optional*, defaults to `"gelu"`):
            The activation function (function or string) in the multi-modal projector.

    ```python
    >>> from transformers import VoxtralForConditionalGeneration, VoxtralConfig

    >>> # Initializing a Voxtral configuration
    >>> configuration = VoxtralConfig(audio_token_id=24, projector_hidden_act="gelu")

    >>> # Initializing a 3B model with random weights
    >>> model = VoxtralForConditionalGeneration(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```voxtral)text_configaudio_configi   i   i          gh㈵>Tg    חAr   )
r"   r
   r   r   num_key_value_headsmax_position_embeddingsrms_norm_eps	use_cache
rope_thetahead_dimNr   c                 .   t          |t                    r2|                    dd          |d<   t          |d                  di |}n|t          d                     }|| _        t          |t                    r;|                    dd          |d<   t          |d                  di i | j        |}n|t          d         di | j        }|| _        |j        | _        |j        | _        || _	        || _
         t                      j        di | d S )Nr4   r	   llamar   )
isinstancedictgetr   r<   _default_text_config_kwargsr;   r"   r
   audio_token_idprojector_hidden_actr    r!   )r+   r<   r;   rK   rL   r,   r-   s         r.   r!   zVoxtralConfig.__init__   sC    lD)) 	?)5)9)9,HY)Z)ZL&),|*DEUUUULL!)*;<>>L(k4(( 	V(3g(N(NK%(\)BC  ET5EE KK  (1UUD4TUUK&%0&2,$8!""6"""""r/   )NNNr   )
r0   r1   r2   r3   r4   r   sub_configsrJ   r!   r6   r7   s   @r.   r9   r9   w   s         B J",jIIK ! #)!# # ## # # # # # # # # #r/   r9   N)configuration_utilsr   autor   r   r   r9   __all__r   r/   r.   <module>rQ      s     4 3 3 3 3 3 - - - - - - - -`3 `3 `3 `3 `3+ `3 `3 `3FO# O# O# O# O#$ O# O# O#d "?
3r/   