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 ddlmZmZ ddlmZmZmZ  ej$                  e      Z G d d	e	      Z G d
 de      Zy)zLayoutLM model configuration    OrderedDict)AnyListMappingOptional   )PretrainedConfigPreTrainedTokenizer)
OnnxConfigPatchingSpec)
TensorTypeis_torch_availableloggingc                   H     e Zd ZdZdZ	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 d fd	Z xZS )LayoutLMConfiga  
    This is the configuration class to store the configuration of a [`LayoutLMModel`]. It is used to instantiate a
    LayoutLM 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 LayoutLM
    [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) architecture.

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


    Args:
        vocab_size (`int`, *optional*, defaults to 30522):
            Vocabulary size of the LayoutLM model. Defines the different tokens that can be represented by the
            *inputs_ids* passed to the forward method of [`LayoutLMModel`].
        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"`, `"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 512):
            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).
        type_vocab_size (`int`, *optional*, defaults to 2):
            The vocabulary size of the `token_type_ids` passed into [`LayoutLMModel`].
        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.
        pad_token_id (`int`, *optional*, defaults to 0):
            The value used to pad input_ids.
        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). Only
            relevant if `config.is_decoder=True`.
        max_2d_position_embeddings (`int`, *optional*, defaults to 1024):
            The maximum value that the 2D position embedding might ever used. Typically set this to something large
            just in case (e.g., 1024).

    Examples:

    ```python
    >>> from transformers import LayoutLMConfig, LayoutLMModel

    >>> # Initializing a LayoutLM configuration
    >>> configuration = LayoutLMConfig()

    >>> # Initializing a model (with random weights) from the configuration
    >>> model = LayoutLMModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```layoutlmc                     t        |   dd|i| || _        || _        || _        || _        || _        || _        || _        || _	        |	| _
        |
| _        || _        || _        || _        || _        || _        y )Npad_token_id )super__init__
vocab_sizehidden_sizenum_hidden_layersnum_attention_heads
hidden_actintermediate_sizehidden_dropout_probattention_probs_dropout_probmax_position_embeddingstype_vocab_sizeinitializer_rangelayer_norm_epsposition_embedding_type	use_cachemax_2d_position_embeddings)selfr   r   r   r   r   r   r   r    r!   r"   r#   r$   r   r%   r&   r'   kwargs	__class__s                     f/var/www/html/venv/lib/python3.12/site-packages/transformers/models/layoutlm/configuration_layoutlm.pyr   zLayoutLMConfig.__init__c   s    ( 	=l=f=$&!2#6 $!2#6 ,H)'>$.!2,'>$"*D'    )i:w  i      r-   i   gelu皙?r/   i      g{Gz?g-q=r   absoluteTi   )__name__
__module____qualname____doc__
model_typer   __classcell__r*   s   @r+   r   r      sO    BH J %( # *#'##E #Er,   r   c                        e Zd Z	 	 ddededee   f fdZede	ee	e
ef   f   fd       Z	 	 	 	 ddede
d	e
d
edee   de	eef   f fdZ xZS )LayoutLMOnnxConfigconfigtaskpatching_specsc                 R    t         |   |||       |j                  dz
  | _        y )N)r<   r=      )r   r   r'   max_2d_positions)r(   r;   r<   r=   r*   s       r+   r   zLayoutLMOnnxConfig.__init__   s,     	d>J & A AA Er,   returnc           	      H    t        ddddfddddfddddfddddfg      S )N	input_idsbatchsequence)r   r?   bboxattention_masktoken_type_idsr   )r(   s    r+   inputszLayoutLMOnnxConfig.inputs   sH    'j9:W45!w:#>?!w:#>?	
 	
r,   	tokenizer
batch_size
seq_lengthis_pair	frameworkc                     t         	|   |||||      }g d}|t        j                  k(  st	        d      t               st        d      ddl}|d   j                  \  }}|j                  g |g|z        j                  |dd      |d	<   |S )
a  
        Generate inputs to provide to the ONNX exporter for the specific framework

        Args:
            tokenizer: The tokenizer associated with this model configuration
            batch_size: The batch size (int) to export the model for (-1 means dynamic axis)
            seq_length: The sequence length (int) to export the model for (-1 means dynamic axis)
            is_pair: Indicate if the input is a pair (sentence 1, sentence 2)
            framework: The framework (optional) the tokenizer will generate tensor for

        Returns:
            Mapping[str, Tensor] holding the kwargs to provide to the model's forward function
        )rK   rL   rM   rN   )0   T   I      zCExporting LayoutLM to ONNX is currently only supported for PyTorch.z7Cannot generate dummy inputs without PyTorch installed.r   NrC   r?   rF   )r   generate_dummy_inputsr   PYTORCHNotImplementedErrorr   
ValueErrortorchshapetensortile)
r(   rJ   rK   rL   rM   rN   
input_dictboxrX   r*   s
            r+   rT   z(LayoutLMOnnxConfig.generate_dummy_inputs   s    , W2*W`i 3 


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   strr   r   r   propertyr   intrI   r   boolr   r   r   rT   r7   r8   s   @r+   r:   r:      s     -1	F F F \*	F 
WS#X%6 67 
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   r   onnxr   r   utilsr   r   r   
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