
    qi#                         d dl mZ d dlmZ ddlmZmZ  ej                  e      Z	 G d de      Z
 G d de      ZddgZy	)
   )PretrainedConfig)logging   )CONFIG_MAPPING
AutoConfigc                   R     e Zd ZdZdZddddddZ	 	 	 	 	 	 	 	 	 	 	 	 	 d
 fd		Z xZS )AudioFlamingo3EncoderConfiga  
    This is the configuration class to store the configuration of an [`AudioFlamingo3Encoder`]. It is used to instantiate an
    AudioFlamingo3 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 AudioFlamingo3
    architecture.

    e.g. [nvidia/audio-flamingo-3-hf](https://huggingface.co/nvidia/audio-flamingo-3-hf)

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

    Args:
        num_mel_bins (`int`, *optional*, defaults to 128):
            Number of mel features used per input features. Should correspond to the value used in the
            `AudioFlamingo3Processor` class.
        num_hidden_layers (`int`, *optional*, defaults to 32):
            Number of encoder layers.
        num_attention_heads (`int`, *optional*, defaults to 20):
            Number of attention heads for each attention layer in the Transformer encoder.
        intermediate_size (`int`, *optional*, defaults to 5120):
            Dimensionality of the "intermediate" (often named feed-forward) layer in encoder.
        layerdrop (`float`, *optional*, defaults to 0.0):
            The LayerDrop probability for the encoder. See the [LayerDrop paper](https://huggingface.co/papers/1909.11556)
            for more details.
        activation_function (`str`, *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_size (`int`, *optional*, defaults to 1280):
            Dimensionality of the layers.
        dropout (`float`, *optional*, defaults to 0.0):
            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.
        initializer_range (`float`, *optional*, defaults to 0.02):
            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
        scale_embedding (`bool`, *optional*, defaults to `False`):
            Scale embeddings by dividing by sqrt(hidden_size).
        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.

    Example:

    ```python
    >>> from transformers import AudioFlamingo3EncoderConfig, AudioFlamingo3Encoder

    >>> # Initializing an AudioFlamingo3EncoderConfig
    >>> configuration = AudioFlamingo3EncoderConfig()

    >>> # Initializing an AudioFlamingo3Encoder (with random weights)
    >>> model = AudioFlamingo3Encoder(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```audioflamingo3_encoderhidden_sizenum_hidden_layersnum_attention_headsintermediate_size	layerdrop)d_modelencoder_layersencoder_attention_headsencoder_ffn_dimencoder_layerdropc                     t        |   di | || _        || _        || _        || _        || _        || _        |	| _        |
| _	        || _
        || _        || _        || _        || _        || _        y )N )super__init__num_mel_binsr   r   r   r   dropoutattention_dropoutactivation_dropoutactivation_functioninitializer_ranger   scale_embeddingmax_source_positions)selfr   r   r   r   r   r   r   r   r   r   r   r   r    kwargs	__class__s                  q/opt/pipecat/venv/lib/python3.12/site-packages/transformers/models/audioflamingo3/configuration_audioflamingo3.pyr   z$AudioFlamingo3EncoderConfig.__init__\   s    " 	"6"(&!2#6 !2!2"4#6 !2"!2.$8!    )          i           gelui   r)   r)   r)   g{Gz?Fi  )__name__
__module____qualname____doc__
model_typeattribute_mapr   __classcell__r#   s   @r$   r	   r	      s[    7r *J !-#8.(M "! 9  9r%   r	   c                   <     e Zd ZdZdZeedZ	 	 	 	 	 d fd	Z xZ	S )AudioFlamingo3Configa  
    This is the configuration class to store the configuration of an [`AudioFlamingo3ForConditionalGeneration`]. It is used to instantiate an
    AudioFlamingo3 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 AudioFlamingo3.

    e.g. [nvidia/audio-flamingo-3-hf](https://huggingface.co/nvidia/audio-flamingo-3-hf)

    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[AudioFlamingo3EncoderConfig, dict]`, *optional*, defaults to `AudioFlamingo3EncoderConfig`):
            The config object or dictionary of the audio backbone.
        text_config (`Union[AutoConfig, dict]`, *optional*, defaults to `Qwen2Config`):
            The config object or dictionary of the text backbone.
        audio_token_id (`int`, *optional*, defaults to 151669):
            The audio token index to encode the audio prompt.
        projector_hidden_act (`str`, *optional*, defaults to `"gelu"`):
            Activation function used in the projector.
        projector_bias (`bool`, *optional*, defaults to `True`):
            Whether to include bias terms in the projector.

    Example:

    ```python
    >>> from transformers import AudioFlamingo3ForConditionalGeneration, AudioFlamingo3Config, AudioFlamingo3EncoderConfig, Qwen2Config

    >>> # Initializing an AudioFlamingo3Encoder config
    >>> audio_config = AudioFlamingo3EncoderConfig()

    >>> # Initializing a Qwen2 config
    >>> text_config = Qwen2Config()

    >>> # Initializing an AudioFlamingo3 configuration
    >>> configuration = AudioFlamingo3Config(audio_config, text_config)

    >>> # Initializing a model from the audioflamingo3 style configuration
    >>> model = AudioFlamingo3ForConditionalGeneration(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```audioflamingo3)audio_configtext_configc                    || _         t        |t              r'|j                  dd      |d<   t	        |d      di |}n|t	        d          }|| _        t        |t              r'|j                  dd      |d<   t	        |d      di |}n|t	        d          }|| _        || _        || _        t        | (  di | y )Nr/   r
   qwen2r   )audio_token_id
isinstancedictgetr   r6   r7   projector_hidden_actprojector_biasr   r   )r!   r6   r7   r:   r>   r?   r"   r#   s          r$   r   zAudioFlamingo3Config.__init__   s     -lD))5)9)9,H`)aL&),|*DEUUL!)*BCEL(k4((3g(NK%(\)BCRkRK (13K&$8!,"6"r%   )NNiuP r*   T)
r+   r,   r-   r.   r/   r	   r   sub_configsr   r1   r2   s   @r$   r4   r4      s8    )V "J3!K ## #r%   r4   N)configuration_utilsr   utilsr   autor   r   
get_loggerr+   loggerr	   r4   __all__r   r%   r$   <module>rG      sQ     4  - 
		H	%d9"2 d9NO#+ O#d "#@
Ar%   