
    fTh                     `    S r SSKJr  SSKJr  \R
                  " \5      r " S S\5      rS/r	g)zBros model configuration   )PretrainedConfig)loggingc                   V   ^  \ rS rSrSrSr                 SU 4S jjrSrU =r$ )
BrosConfig   a,  
This is the configuration class to store the configuration of a [`BrosModel`] or a [`TFBrosModel`]. It is used to
instantiate a Bros 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 Bros
[jinho8345/bros-base-uncased](https://huggingface.co/jinho8345/bros-base-uncased) architecture.

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

Args:
    vocab_size (`int`, *optional*, defaults to 30522):
        Vocabulary size of the Bros model. Defines the number of different tokens that can be represented by the
        `inputs_ids` passed when calling [`BrosModel`] or [`TFBrosModel`].
    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" (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 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 when calling [`BrosModel`] or [`TFBrosModel`].
    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 index of the padding token in the token vocabulary.
    dim_bbox (`int`, *optional*, defaults to 8):
        The dimension of the bounding box coordinates. (x0, y1, x1, y0, x1, y1, x0, y1)
    bbox_scale (`float`, *optional*, defaults to 100.0):
        The scale factor of the bounding box coordinates.
    n_relations (`int`, *optional*, defaults to 1):
        The number of relations for SpadeEE(entity extraction), SpadeEL(entity linking) head.
    classifier_dropout_prob (`float`, *optional*, defaults to 0.1):
        The dropout ratio for the classifier head.


Examples:

```python
>>> from transformers import BrosConfig, BrosModel

>>> # Initializing a BROS jinho8345/bros-base-uncased style configuration
>>> configuration = BrosConfig()

>>> # Initializing a model from the jinho8345/bros-base-uncased style configuration
>>> model = BrosModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
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vocab_sizehidden_sizenum_hidden_layersnum_attention_headsintermediate_size
hidden_acthidden_dropout_probattention_probs_dropout_probmax_position_embeddingstype_vocab_sizeinitializer_rangelayer_norm_epspad_token_id    )super__init__dim_bbox
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