


from typing import TYPE_CHECKING

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


snake_case__  				=			{
    'configuration_markuplm': ['MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MarkupLMConfig'],
    'feature_extraction_markuplm': ['MarkupLMFeatureExtractor'],
    'processing_markuplm': ['MarkupLMProcessor'],
    'tokenization_markuplm': ['MarkupLMTokenizer'],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			snake_case__  				=			['MarkupLMTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			snake_case__  				=			[
			    'MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'MarkupLMForQuestionAnswering',
			    'MarkupLMForSequenceClassification',
			    'MarkupLMForTokenClassification',
			    'MarkupLMModel',
			    'MarkupLMPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
			from .feature_extraction_markuplm import MarkupLMFeatureExtractor
			from .processing_markuplm import MarkupLMProcessor
			from .tokenization_markuplm import MarkupLMTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_markuplm_fast import MarkupLMTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_markuplm import (
						    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
						    MarkupLMForQuestionAnswering,
						    MarkupLMForSequenceClassification,
						    MarkupLMForTokenClassification,
						    MarkupLMModel,
						    MarkupLMPreTrainedModel,
						)


else:
			import sys

			snake_case__  				=			_LazyModule(__name__, globals()['__file__'], _import_structure)







'''simple docstring'''
from .hash_table import HashTable



class _A	(     __SCREAMING_SNAKE_CASE     ):





		def __init__(  self			,							*__UpperCAmelCase			,							**__UpperCAmelCase					)							->  List[Any]:

					'''simple docstring'''
					super().__init__(*__UpperCAmelCase			,							**__UpperCAmelCase					)





		def 				__A							(  self			,							__UpperCAmelCase			,							__UpperCAmelCase=None					)							->  str:

					'''simple docstring'''
					__UpperCAmelCase :   List[str]    					=  1
					__UpperCAmelCase :   Optional[Any]    					=  self.hash_function(key + i * i					)

					while self.values[new_key] is not None and self.values[new_key] != key:
								i += 1
								__UpperCAmelCase :   str    					=  (
								    self.hash_function(key + i * i					)
								    if not self.balanced_factor() >= self.lim_charge
								    else None
								)

								if new_key is None:
											break

					return new_key




