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 ddlmZ ddlmZ  ej        e          Z G d	 d
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          Z G d de          ZdS )zPvt model configuration    OrderedDict)CallableListMapping)version   )PretrainedConfig)
OnnxConfig)loggingc            %           e Zd ZdZdZdddg dg dg dg d	g d	g d
g dddddddddfdedededee         dee         dee         dee         dee         dee         dee         deee	f         de
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d"ed#ef$ fd$Z xZS )%	PvtConfigaM  
    This is the configuration class to store the configuration of a [`PvtModel`]. It is used to instantiate an Pvt
    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 Pvt
    [Xrenya/pvt-tiny-224](https://huggingface.co/Xrenya/pvt-tiny-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:
        image_size (`int`, *optional*, defaults to 224):
            The input image size
        num_channels (`int`, *optional*, defaults to 3):
            The number of input channels.
        num_encoder_blocks (`int`, *optional*, defaults to 4):
            The number of encoder blocks (i.e. stages in the Mix Transformer encoder).
        depths (`List[int]`, *optional*, defaults to `[2, 2, 2, 2]`):
            The number of layers in each encoder block.
        sequence_reduction_ratios (`List[int]`, *optional*, defaults to `[8, 4, 2, 1]`):
            Sequence reduction ratios in each encoder block.
        hidden_sizes (`List[int]`, *optional*, defaults to `[64, 128, 320, 512]`):
            Dimension of each of the encoder blocks.
        patch_sizes (`List[int]`, *optional*, defaults to `[4, 2, 2, 2]`):
            Patch size before each encoder block.
        strides (`List[int]`, *optional*, defaults to `[4, 2, 2, 2]`):
            Stride before each encoder block.
        num_attention_heads (`List[int]`, *optional*, defaults to `[1, 2, 5, 8]`):
            Number of attention heads for each attention layer in each block of the Transformer encoder.
        mlp_ratios (`List[int]`, *optional*, defaults to `[8, 8, 4, 4]`):
            Ratio of the size of the hidden layer compared to the size of the input layer of the Mix FFNs in the
            encoder blocks.
        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.
        drop_path_rate (`float`, *optional*, defaults to 0.0):
            The dropout probability for stochastic depth, used in the blocks of the Transformer encoder.
        layer_norm_eps (`float`, *optional*, defaults to 1e-06):
            The epsilon used by the layer normalization layers.
        qkv_bias (`bool`, *optional*, defaults to `True`):
            Whether or not a learnable bias should be added to the queries, keys and values.
        num_labels ('int', *optional*, defaults to 1000):
            The number of classes.
    Example:

    ```python
    >>> from transformers import PvtModel, PvtConfig

    >>> # Initializing a PVT Xrenya/pvt-tiny-224 style configuration
    >>> configuration = PvtConfig()

    >>> # Initializing a model from the Xrenya/pvt-tiny-224 style configuration
    >>> model = PvtModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```pvt   r	      )   r   r   r   )   r   r      )@      i@  i   )r   r   r   r   )r   r      r   )r   r   r   r   gelug        g{Gz?gư>Ti  
image_sizenum_channelsnum_encoder_blocksdepthssequence_reduction_ratioshidden_sizespatch_sizesstridesnum_attention_heads
mlp_ratios
hidden_acthidden_dropout_probattention_probs_dropout_probinitializer_rangedrop_path_ratelayer_norm_epsqkv_bias
num_labelsc                 6    t                      j        di | || _        || _        || _        || _        || _        || _        || _        || _	        |
| _
        |	| _        || _        || _        || _        || _        || _        || _        || _        || _        d S )N )super__init__r   r   r   r   r   r   r   r    r"   r!   r#   r$   r%   r&   r'   r(   r*   r)   )selfr   r   r   r   r   r   r   r    r!   r"   r#   r$   r%   r&   r'   r(   r)   r*   kwargs	__class__s                       e/var/www/html/ai-engine/env/lib/python3.11/site-packages/transformers/models/pvt/configuration_pvt.pyr.   zPvtConfig.__init__b   s    , 	""6"""$("4)B&(&$#6 $#6 ,H)!2,,$     )__name__
__module____qualname____doc__
model_typeintr   r   strr   floatboolr.   __classcell__)r1   s   @r2   r   r       s       = =~ J "#(LL/;||"5"5"5!-)\\)5 ,-3%(.1#' # $')! )!)! )!  	)!
 S	)! $(9)! 3i)! #Y)! c)! "#Y)! I)! CM*)! #)! ',)! !)!  !)!" #)!$ %)!& ')! )! )! )! )! )! )! )! )! )!r3   r   c                       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ede	fd            ZdS )PvtOnnxConfigz1.11returnc                 0    t          ddddddfg          S )Npixel_valuesbatchr   heightwidth)r   r   r   r	   r   r/   s    r2   inputszPvtOnnxConfig.inputs   s.    WHQX!Y!YZ
 
 	
r3   c                     dS )Ng-C6?r,   rF   s    r2   atol_for_validationz!PvtOnnxConfig.atol_for_validation   s    tr3   c                     dS )N   r,   rF   s    r2   default_onnx_opsetz PvtOnnxConfig.default_onnx_opset   s    rr3   N)r4   r5   r6   r   parsetorch_onnx_minimum_versionpropertyr   r:   r9   rG   r;   rI   rL   r,   r3   r2   r?   r?      s        !.v!6!6
WS#X%6 67 
 
 
 X
 U    X C    X  r3   r?   N)r7   collectionsr   typingr   r   r   	packagingr   configuration_utilsr
   onnxr   utilsr   
get_loggerr4   loggerr   r?   r,   r3   r2   <module>rX      s  "   # # # # # # * * * * * * * * * *       3 3 3 3 3 3             
	H	%	%k! k! k! k! k!  k! k! k!\    J     r3   