
    sg(                     l    d dl mZ d dlmZ  ej                  e      Z G d de      Z G d de      Zy)   )PretrainedConfig)loggingc                   B     e Zd ZdZdZdZ	 	 	 	 	 	 	 	 	 	 	 d fd	Z xZS )GitVisionConfiga
  
    This is the configuration class to store the configuration of a [`GitVisionModel`]. It is used to instantiate a GIT
    vision 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 vision encoder of the GIT
    [microsoft/git-base](https://huggingface.co/microsoft/git-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:
        hidden_size (`int`, *optional*, defaults to 768):
            Dimensionality of the encoder layers and the pooler layer.
        intermediate_size (`int`, *optional*, defaults to 3072):
            Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
        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.
        image_size (`int`, *optional*, defaults to 224):
            The size (resolution) of each image.
        patch_size (`int`, *optional*, defaults to 16):
            The size (resolution) of each patch.
        hidden_act (`str` or `function`, *optional*, defaults to `"quick_gelu"`):
            The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
            `"relu"`, `"selu"` and `"gelu_new"` `"quick_gelu"` are supported.
        layer_norm_eps (`float`, *optional*, defaults to 1e-5):
            The epsilon used by the layer normalization layers.
        attention_dropout (`float`, *optional*, defaults to 0.0):
            The dropout ratio for the attention probabilities.
        initializer_range (`float`, *optional*, defaults to 0.02):
            The standard deviation of the truncated_normal_initializer for initializing all weight matrices.

    Example:

    ```python
    >>> from transformers import GitVisionConfig, GitVisionModel

    >>> # Initializing a GitVisionConfig with microsoft/git-base style configuration
    >>> configuration = GitVisionConfig()

    >>> # Initializing a GitVisionModel (with random weights) from the microsoft/git-base style configuration
    >>> model = GitVisionModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```git_vision_modelvision_configc                     t        |   di | || _        || _        || _        || _        || _        || _        || _        || _	        |
| _
        |	| _        || _        y )N )super__init__hidden_sizeintermediate_sizenum_hidden_layersnum_attention_headsnum_channels
patch_size
image_sizeinitializer_rangeattention_dropoutlayer_norm_eps
hidden_act)selfr   r   r   r   r   r   r   r   r   r   r   kwargs	__class__s                \/var/www/html/venv/lib/python3.12/site-packages/transformers/models/git/configuration_git.pyr   zGitVisionConfig.__init__K   sj     	"6"&!2!2#6 ($$!2!2,$    )         r   r         
quick_gelugh㈵>g        {Gz?)__name__
__module____qualname____doc__
model_typebase_config_keyr   __classcell__r   s   @r   r   r      sB    -^ $J%O % %r   r   c                   V     e Zd ZdZdZdeiZ	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 d fd	Z xZS )	GitConfiga  
    This is the configuration class to store the configuration of a [`GitModel`]. It is used to instantiate a GIT 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 GIT
    [microsoft/git-base](https://huggingface.co/microsoft/git-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:
        vision_config (`dict`, *optional*):
            Dictionary of configuration options used to initialize [`GitVisionConfig`].
        vocab_size (`int`, *optional*, defaults to 30522):
            Vocabulary size of the GIT model. Defines the number of different tokens that can be represented by the
            `inputs_ids` passed when calling [`GitModel`].
        hidden_size (`int`, *optional*, defaults to 768):
            Dimensionality of the encoder layers and the pooler layer.
        num_hidden_layers (`int`, *optional*, defaults to 6):
            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 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).
        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.
        position_embedding_type (`str`, *optional*, defaults to `"absolute"`):
            Type of position embedding. Choose one of `"absolute"`, `"relative_key"`, `"relative_key_query"`. For
            positional embeddings use `"absolute"`. For more information on `"relative_key"`, please refer to
            [Self-Attention with Relative Position Representations (Shaw et al.)](https://arxiv.org/abs/1803.02155).
            For more information on `"relative_key_query"`, please refer to *Method 4* in [Improve Transformer Models
            with Better Relative Position Embeddings (Huang et al.)](https://arxiv.org/abs/2009.13658).
        use_cache (`bool`, *optional*, defaults to `True`):
            Whether or not the model should return the last key/values attentions (not used by all models).
        num_image_with_embedding (`int`, *optional*):
            The number of temporal embeddings to add, in case the model is used for video captioning/VQA.

    Examples:

    ```python
    >>> from transformers import GitConfig, GitModel

    >>> # Initializing a GIT microsoft/git-base style configuration
    >>> configuration = GitConfig()

    >>> # Initializing a model (with random weights) from the microsoft/git-base style configuration
    >>> model = GitModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```gitr   c                 l   t        |   d|||d| |i }t        j                  d       t	        di || _        || _        || _        || _        || _	        || _
        || _        || _        |	| _        |
| _        || _        || _        || _        || _        || _        || _        || _        || _        y )N)bos_token_ideos_token_idpad_token_idzLvision_config is None. initializing the GitVisionConfig with default values.r
   )r   r   loggerinfor   r   
vocab_sizer   r   r   r   r   hidden_dropout_probattention_probs_dropout_probmax_position_embeddingsr   r   position_embedding_type	use_cachetie_word_embeddingsnum_image_with_embeddingr0   r1   )r   r   r5   r   r   r   r   r   r6   r7   r8   r   r   r2   r9   r:   r;   r0   r1   r<   r   r   s                        r   r   zGitConfig.__init__   s    . 	sl\hslrs MKKfg,=}=$&!2#6 $!2#6 ,H)'>$!2,'>$"#6 (@%((r   )Ni:w  r      r   r   gelu皙?r?   i   r#   g-q=    absoluteTFe   f   N)	r$   r%   r&   r'   r(   r   sub_configsr   r*   r+   s   @r   r-   r-   i   s_    =~ J"O4K %( $ *!!%)/) /)r   r-   N)	configuration_utilsr   utilsr   
get_loggerr$   r3   r   r-   r
   r   r   <module>rH      s@   " 4  
		H	%N%& N%br)  r)r   