
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      A__							(     lowerCAmelCase_	):
				lowercase			    =  'markuplm'






				def __init__(						self					:      List[str]    ,     a					:      Optional[Any]=30_522    ,     a					:      int=768    ,     a					:      Tuple=12    ,     a					:      Union[str, Any]=12    ,     a					:      List[str]=3_072    ,     a					:      int="gelu"    ,     a					:      Dict=0.1    ,     a					:      List[str]=0.1    ,     a					:      Tuple=512    ,     a					:      Dict=2    ,     a					:      Tuple=0.0_2    ,     a					:      Dict=1E-12    ,     a					:      Dict=0    ,     a					:      Union[str, Any]=0    ,     a					:      List[str]=2    ,     a					:      Any=256    ,     a					:      int=1_024    ,     a					:      Dict=216    ,     a					:      Union[str, Any]=1_001    ,     a					:      Tuple=32    ,     a					:      List[Any]=50    ,     a					:      Optional[int]="absolute"    ,     a					:      Union[str, Any]=True    ,     a					:      List[Any]=None    ,     **a					:      Optional[int]    ,     ):






							'''simple docstring'''







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



'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__lowercase	:						str       =	{
    'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
    'configuration_data2vec_text': [
        'DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Data2VecTextConfig',
        'Data2VecTextOnnxConfig',
    ],
    'configuration_data2vec_vision': [
        'DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Data2VecVisionConfig',
        'Data2VecVisionOnnxConfig',
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						str       =	[
	    'DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'Data2VecAudioForAudioFrameClassification',
	    'Data2VecAudioForCTC',
	    'Data2VecAudioForSequenceClassification',
	    'Data2VecAudioForXVector',
	    'Data2VecAudioModel',
	    'Data2VecAudioPreTrainedModel',
	]
	__lowercase	:						Tuple       =	[
	    'DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'Data2VecTextForCausalLM',
	    'Data2VecTextForMaskedLM',
	    'Data2VecTextForMultipleChoice',
	    'Data2VecTextForQuestionAnswering',
	    'Data2VecTextForSequenceClassification',
	    'Data2VecTextForTokenClassification',
	    'Data2VecTextModel',
	    'Data2VecTextPreTrainedModel',
	]
	__lowercase	:						Dict       =	[
	    'DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'Data2VecVisionForImageClassification',
	    'Data2VecVisionForMaskedImageModeling',
	    'Data2VecVisionForSemanticSegmentation',
	    'Data2VecVisionModel',
	    'Data2VecVisionPreTrainedModel',
	]

if is_tf_available():
	__lowercase	:						Optional[Any]       =	[
	    'TFData2VecVisionForImageClassification',
	    'TFData2VecVisionForSemanticSegmentation',
	    'TFData2VecVisionModel',
	    'TFData2VecVisionPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
	from .configuration_dataavec_text import (
	    DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    DataaVecTextConfig,
	    DataaVecTextOnnxConfig,
	)
	from .configuration_dataavec_vision import (
	    DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    DataaVecVisionConfig,
	    DataaVecVisionOnnxConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_dataavec_audio import (
		    DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DataaVecAudioForAudioFrameClassification,
		    DataaVecAudioForCTC,
		    DataaVecAudioForSequenceClassification,
		    DataaVecAudioForXVector,
		    DataaVecAudioModel,
		    DataaVecAudioPreTrainedModel,
		)
		from .modeling_dataavec_text import (
		    DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DataaVecTextForCausalLM,
		    DataaVecTextForMaskedLM,
		    DataaVecTextForMultipleChoice,
		    DataaVecTextForQuestionAnswering,
		    DataaVecTextForSequenceClassification,
		    DataaVecTextForTokenClassification,
		    DataaVecTextModel,
		    DataaVecTextPreTrainedModel,
		)
		from .modeling_dataavec_vision import (
		    DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DataaVecVisionForImageClassification,
		    DataaVecVisionForMaskedImageModeling,
		    DataaVecVisionForSemanticSegmentation,
		    DataaVecVisionModel,
		    DataaVecVisionPreTrainedModel,
		)
	if is_tf_available():
		from .modeling_tf_dataavec_vision import (
		    TFDataaVecVisionForImageClassification,
		    TFDataaVecVisionForSemanticSegmentation,
		    TFDataaVecVisionModel,
		    TFDataaVecVisionPreTrainedModel,
		)

else:
	import sys

	__lowercase	:						int       =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



