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R# )	zLayoutLMv2 model configuration)Ústrict)ÚPreTrainedConfig)Úauto_docstringÚis_detectron2_availableNz!microsoft/layoutlmv2-base-uncased)Ú
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  
max_2d_position_embeddings (`int`, *optional*, defaults to 1024):
    The maximum value that the 2D position embedding might ever be used with. Typically set this to something
    large just in case (e.g., 1024).
max_rel_pos (`int`, *optional*, defaults to 128):
    The maximum number of relative positions to be used in the self-attention mechanism.
rel_pos_bins (`int`, *optional*, defaults to 32):
    The number of relative position bins to be used in the self-attention mechanism.
fast_qkv (`bool`, *optional*, defaults to `True`):
    Whether or not to use a single matrix for the queries, keys, values in the self-attention layers.
max_rel_2d_pos (`int`, *optional*, defaults to 256):
    The maximum number of relative 2D positions in the self-attention mechanism.
rel_2d_pos_bins (`int`, *optional*, defaults to 64):
    The number of 2D relative position bins in the self-attention mechanism.
convert_sync_batchnorm (`bool`, *optional*, defaults to `True`):
    Whether or not to convert batch normalization layers to synchronized batch normalization layers.
image_feature_pool_shape (`list[int]`, *optional*, defaults to `[7, 7, 256]`):
    The shape of the average-pooled feature map.
coordinate_size (`int`, *optional*, defaults to 128):
    Dimension of the coordinate embeddings.
shape_size (`int`, *optional*, defaults to 128):
    Dimension of the width and height embeddings.
has_relative_attention_bias (`bool`, *optional*, defaults to `True`):
    Whether or not to use a relative attention bias in the self-attention mechanism.
has_spatial_attention_bias (`bool`, *optional*, defaults to `True`):
    Whether or not to use a spatial attention bias in the self-attention mechanism.
has_visual_segment_embedding (`bool`, *optional*, defaults to `False`):
    Whether or not to add visual segment embeddings.
detectron2_config_args (`dict`, *optional*):
    Dictionary containing the configuration arguments of the Detectron2 visual backbone. Refer to [this
    file](https://github.com/microsoft/unilm/blob/master/layoutlmft/layoutlmft/models/layoutlmv2/detectron2_config.py)
    for details regarding default values.

Example:

```python
>>> from transformers import LayoutLMv2Config, LayoutLMv2Model

>>> # Initializing a LayoutLMv2 microsoft/layoutlmv2-base-uncased style configuration
>>> configuration = LayoutLMv2Config()

>>> # Initializing a model (with random weights) from the microsoft/layoutlmv2-base-uncased style configuration
>>> model = LayoutLMv2Model(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```Ú
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