
    %	&h                         d Z ddlmZ ddlmZ ddlmZ ddlmZ ddl	m
Z
 ddlmZ  ej                  e      Z G d	 d
e      Z G d de
      Zd
dgZy)zDeiT model configuration    OrderedDict)Mapping)version   )PretrainedConfig)
OnnxConfig)loggingc                   H     e Zd ZdZdZ	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 d fd	Z xZS )
DeiTConfiga  
    This is the configuration class to store the configuration of a [`DeiTModel`]. It is used to instantiate an DeiT
    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 DeiT
    [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224)
    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.
        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.
        intermediate_size (`int`, *optional*, defaults to 3072):
            Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
        hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`):
            The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
            `"relu"`, `"selu"` and `"gelu_new"` are supported.
        hidden_dropout_prob (`float`, *optional*, defaults to 0.0):
            The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.
        attention_probs_dropout_prob (`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.
        layer_norm_eps (`float`, *optional*, defaults to 1e-12):
            The epsilon used by the layer normalization layers.
        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.
        num_channels (`int`, *optional*, defaults to 3):
            The number of input channels.
        qkv_bias (`bool`, *optional*, defaults to `True`):
            Whether to add a bias to the queries, keys and values.
        encoder_stride (`int`, *optional*, defaults to 16):
            Factor to increase the spatial resolution by in the decoder head for masked image modeling.
        pooler_output_size (`int`, *optional*):
           Dimensionality of the pooler layer. If None, defaults to `hidden_size`.
        pooler_act (`str`, *optional*, defaults to `"tanh"`):
           The activation function to be used by the pooler. Keys of ACT2FN are supported for Flax and
           Pytorch, and elements of https://www.tensorflow.org/api_docs/python/tf/keras/activations are
           supported for Tensorflow.

    Example:

    ```python
    >>> from transformers import DeiTConfig, DeiTModel

    >>> # Initializing a DeiT deit-base-distilled-patch16-224 style configuration
    >>> configuration = DeiTConfig()

    >>> # Initializing a model (with random weights) from the deit-base-distilled-patch16-224 style configuration
    >>> model = DeiTModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```deitc                    t        |   di | || _        || _        || _        || _        || _        || _        || _        || _	        |	| _
        |
| _        || _        || _        || _        || _        |r|n|| _        || _        y )N )super__init__hidden_sizenum_hidden_layersnum_attention_headsintermediate_size
hidden_acthidden_dropout_probattention_probs_dropout_probinitializer_rangelayer_norm_eps
image_size
patch_sizenum_channelsqkv_biasencoder_stridepooler_output_size
pooler_act)selfr   r   r   r   r   r   r   r   r   r   r   r   r   r   r    r!   kwargs	__class__s                     /var/www/pru.catia.catastroantioquia-mas.com/valormas/lib/python3.12/site-packages/transformers/models/deit/configuration_deit.pyr   zDeiTConfig.__init__`   s    ( 	"6"&!2#6 !2$#6 ,H)!2,$$( ,8J"4P[$    )i      r'   i   gelu        r)   g{Gz?g-q=      r   Tr+   Ntanh)__name__
__module____qualname____doc__
model_typer   __classcell__)r$   s   @r%   r   r      sL    =~ J %(#%% %%r&   r   c                   p    e Zd Z ej                  d      Zedeeee	ef   f   fd       Z
edefd       Zy)DeiTOnnxConfigz1.11returnc                 (    t        ddddddfg      S )Npixel_valuesbatchr   heightwidth)r         r   r   r"   s    r%   inputszDeiTOnnxConfig.inputs   s&    WHQX!YZ
 	
r&   c                      y)Ng-C6?r   r=   s    r%   atol_for_validationz"DeiTOnnxConfig.atol_for_validation   s    r&   N)r-   r.   r/   r   parsetorch_onnx_minimum_versionpropertyr   strintr>   floatr@   r   r&   r%   r4   r4      sZ    !.v!6
WS#X%6 67 
 
 U  r&   r4   N)r0   collectionsr   typingr   	packagingr   configuration_utilsr   onnxr	   utilsr
   
get_loggerr-   loggerr   r4   __all__r   r&   r%   <module>rP      sY     #   3   
		H	%g%! g%TZ   )
*r&   