



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


UpperCamelCase__ =						logging.get_logger(__name__)

UpperCamelCase__ =						{
    "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 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			lowercase__      :  Optional[int]      =			"""markuplm"""





			def __init__(				self	:       Dict			,     lowercase	:       Union[str, Any]=30_522			,     lowercase	:       Dict=768			,     lowercase	:       List[Any]=12			,     lowercase	:       List[Any]=12			,     lowercase	:       Any=3_072			,     lowercase	:       str="gelu"			,     lowercase	:       Any=0.1			,     lowercase	:       Tuple=0.1			,     lowercase	:       Dict=512			,     lowercase	:       Any=2			,     lowercase	:       List[str]=0.02			,     lowercase	:       str=1E-1_2			,     lowercase	:       Optional[Any]=0			,     lowercase	:       Tuple=0			,     lowercase	:       Union[str, Any]=2			,     lowercase	:       Any=256			,     lowercase	:       Optional[int]=1_024			,     lowercase	:       List[Any]=216			,     lowercase	:       Dict=1_001			,     lowercase	:       List[Any]=32			,     lowercase	:       str=50			,     lowercase	:       List[str]="absolute"			,     lowercase	:       Optional[int]=True			,     lowercase	:       Dict=None			,     **lowercase	:       int			,     )						->					Any:
									"""simple docstring"""







									super().__init__(
									    pad_token_id=lowercase			,     bos_token_id=lowercase			,     eos_token_id=lowercase			,     **lowercase			,     )
									__lowercase					=				vocab_size
									__lowercase					=				hidden_size
									__lowercase					=				num_hidden_layers
									__lowercase					=				num_attention_heads
									__lowercase					=				hidden_act
									__lowercase					=				intermediate_size
									__lowercase					=				hidden_dropout_prob
									__lowercase					=				attention_probs_dropout_prob
									__lowercase					=				max_position_embeddings
									__lowercase					=				type_vocab_size
									__lowercase					=				initializer_range
									__lowercase					=				layer_norm_eps
									__lowercase					=				position_embedding_type
									__lowercase					=				use_cache
									__lowercase					=				classifier_dropout
									# additional properties
									__lowercase					=				max_depth
									__lowercase					=				max_xpath_tag_unit_embeddings
									__lowercase					=				max_xpath_subs_unit_embeddings
									__lowercase					=				tag_pad_id
									__lowercase					=				subs_pad_id
									__lowercase					=				xpath_unit_hidden_size










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__ =						{
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "LukeForEntityClassification",
			    "LukeForEntityPairClassification",
			    "LukeForEntitySpanClassification",
			    "LukeForMultipleChoice",
			    "LukeForQuestionAnswering",
			    "LukeForSequenceClassification",
			    "LukeForTokenClassification",
			    "LukeForMaskedLM",
			    "LukeModel",
			    "LukePreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
			from .tokenization_luke import LukeTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_luke import (
						    LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    LukeForEntityClassification,
						    LukeForEntityPairClassification,
						    LukeForEntitySpanClassification,
						    LukeForMaskedLM,
						    LukeForMultipleChoice,
						    LukeForQuestionAnswering,
						    LukeForSequenceClassification,
						    LukeForTokenClassification,
						    LukeModel,
						    LukePreTrainedModel,
						)

else:
			import sys

			UpperCamelCase__ =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





