






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase__       		=  logging.get_logger(__name__)

lowerCamelCase__       		=  {
    """microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
    """microsoft/markuplm-large""": """https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json""",
}




class       snake_case__ (				A_):

       '''simple docstring'''
       lowerCamelCase				:					str								=			"markuplm"



       def __init__(				self      ,    a__=3_05_22      ,    a__=7_68      ,    a__=12      ,    a__=12      ,    a__=30_72      ,    a__="gelu"      ,    a__=0.1      ,    a__=0.1      ,    a__=5_12      ,    a__=2      ,    a__=0.02      ,    a__=1e-12      ,    a__=0      ,    a__=0      ,    a__=2      ,    a__=2_56      ,    a__=10_24      ,    a__=2_16      ,    a__=10_01      ,    a__=32      ,    a__=50      ,    a__="absolute"      ,    a__=True      ,    a__=None      ,    **a__      ,    )			->   int:






            '''simple docstring'''





            super().__init__(
                pad_token_id=a__      ,    bos_token_id=a__      ,    eos_token_id=a__      ,    **a__      ,    )
            __snake_case      :str 							=    vocab_size
            __snake_case      :Union[str, Any] 							=    hidden_size
            __snake_case      :List[Any] 							=    num_hidden_layers
            __snake_case      :Any 							=    num_attention_heads
            __snake_case      :Union[str, Any] 							=    hidden_act
            __snake_case      :Optional[int] 							=    intermediate_size
            __snake_case      :Optional[int] 							=    hidden_dropout_prob
            __snake_case      :Union[str, Any] 							=    attention_probs_dropout_prob
            __snake_case      :List[Any] 							=    max_position_embeddings
            __snake_case      :Optional[int] 							=    type_vocab_size
            __snake_case      :int 							=    initializer_range
            __snake_case      :Tuple 							=    layer_norm_eps
            __snake_case      :str 							=    position_embedding_type
            __snake_case      :List[Any] 							=    use_cache
            __snake_case      :Tuple 							=    classifier_dropout
            # additional properties
            __snake_case      :Tuple 							=    max_depth
            __snake_case      :List[Any] 							=    max_xpath_tag_unit_embeddings
            __snake_case      :Optional[int] 							=    max_xpath_subs_unit_embeddings
            __snake_case      :Tuple 							=    tag_pad_id
            __snake_case      :int 							=    subs_pad_id
            __snake_case      :Optional[int] 							=    xpath_unit_hidden_size






"""simple docstring"""
import warnings

from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor


UpperCAmelCase				=						logging.get_logger(__name__)




class 	lowercase__				(					A_				):





   def __init__(							self      ,   *SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)  ->  None:
      warnings.warn(
          """The class ImageGPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
          """ Please use ImageGPTImageProcessor instead."""      ,   SCREAMING_SNAKE_CASE      ,   )
      super().__init__(*SCREAMING_SNAKE_CASE      ,   **SCREAMING_SNAKE_CASE)

