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    T^(h®  ã                   ó`   — d Z ddlmZ ddlmZ  ej
                  e«      Z G d„ de«      ZdgZ	y)zMarkupLM model configurationé   )ÚPretrainedConfig)Úloggingc                   óX   ‡ — e Zd ZdZdZ	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 dˆ fd„	Zˆ xZS )ÚMarkupLMConfiga  
    This is the configuration class to store the configuration of a [`MarkupLMModel`]. It is used to instantiate a
    MarkupLM 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 MarkupLM
    [microsoft/markuplm-base](https://huggingface.co/microsoft/markuplm-base) 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 MarkupLM model. Defines the different tokens that can be represented by the
            *inputs_ids* passed to the forward method of [`MarkupLMModel`].
        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 [`MarkupLMModel`].
        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.
        max_tree_id_unit_embeddings (`int`, *optional*, defaults to 1024):
            The maximum value that the tree id unit embedding might ever use. Typically set this to something large
            just in case (e.g., 1024).
        max_xpath_tag_unit_embeddings (`int`, *optional*, defaults to 256):
            The maximum value that the xpath tag unit embedding might ever use. Typically set this to something large
            just in case (e.g., 256).
        max_xpath_subs_unit_embeddings (`int`, *optional*, defaults to 1024):
            The maximum value that the xpath subscript unit embedding might ever use. Typically set this to something
            large just in case (e.g., 1024).
        tag_pad_id (`int`, *optional*, defaults to 216):
            The id of the padding token in the xpath tags.
        subs_pad_id (`int`, *optional*, defaults to 1001):
            The id of the padding token in the xpath subscripts.
        xpath_tag_unit_hidden_size (`int`, *optional*, defaults to 32):
            The hidden size of each tree id unit. One complete tree index will have
            (50*xpath_tag_unit_hidden_size)-dim.
        max_depth (`int`, *optional*, defaults to 50):
            The maximum depth in xpath.

    Examples:

    ```python
    >>> from transformers import MarkupLMModel, MarkupLMConfig

    >>> # Initializing a MarkupLM microsoft/markuplm-base style configuration
    >>> configuration = MarkupLMConfig()

    >>> # Initializing a model from the microsoft/markuplm-base style configuration
    >>> model = MarkupLMModel(configuration)

    >>> # Accessing the model configuration
    >>> configuration = model.config
    ```Úmarkuplmc                 óR  •— t        ‰| �  d|||dœ|¤Ž || _        || _        || _        || _        || _        || _        || _        || _	        |	| _
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