'''simple docstring'''


from .number_theory.prime_numbers import next_prime






class 	__SCREAMING_SNAKE_CASE		:







  '''simple docstring'''






  def __init__(					self ,						snake_case_ ,						snake_case_ = None ,						snake_case_ = None ,						):




       '''simple docstring'''

       UpperCAmelCase_				:  Any  = size_table
       UpperCAmelCase_				:  List[Any]  = [None] * self.size_table
       UpperCAmelCase_				:  int  = 0.75 if lim_charge is None else lim_charge
       UpperCAmelCase_				:  Optional[Any]  = 1 if charge_factor is None else charge_factor
       UpperCAmelCase_				:  list  = []
       UpperCAmelCase_				:  dict  = {}


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       return self._keys


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       return sum(1 for slot in self.values if slot is not None		) / (
           self.size_table * self.charge_factor
       )


  def _UpperCamelCase	(					self ,						snake_case_		):




       '''simple docstring'''

       return key % self.size_table


  def _UpperCamelCase	(					self ,						snake_case_		):




       '''simple docstring'''

       print(F'''step {step_ord}'''		)
       print(list(range(len(self.values		)		)		)		)
       print(self.values		)


  def _UpperCamelCase	(					self ,						snake_case_		):




       '''simple docstring'''

       UpperCAmelCase_				:  Optional[int]  = 1
       UpperCAmelCase_				:  Any  = values
       for value in values:
            self.insert_data(snake_case_		)
            self._step_by_step(snake_case_		)
            i += 1


  def _UpperCamelCase	(					self ,						snake_case_ ,						snake_case_		):




       '''simple docstring'''

       UpperCAmelCase_				:  Optional[int]  = data
       UpperCAmelCase_				:  Any  = data


  def _UpperCamelCase	(					self ,						snake_case_ ,						snake_case_=None		):




       '''simple docstring'''

       UpperCAmelCase_				:  Tuple  = self.hash_function(key + 1		)

       while self.values[new_key] is not None and self.values[new_key] != key:
            if self.values.count(snake_case_		) > 0:
                 UpperCAmelCase_				:  Dict  = self.hash_function(new_key + 1		)
            else:
                 UpperCAmelCase_				:  Optional[Any]  = None
                 break

       return new_key


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Dict  = [value for value in self.values if value is not None]
       UpperCAmelCase_				:  List[Any]  = next_prime(self.size_table ,						factor=2		)
       self._keys.clear()
       UpperCAmelCase_				:  Any  = [None] * self.size_table  # hell's pointers D: don't DRY ;/
       for value in survivor_values:
            self.insert_data(snake_case_		)






  def _UpperCamelCase	(					self ,						snake_case_		):




       '''simple docstring'''

       UpperCAmelCase_				:  List[Any]  = self.hash_function(snake_case_		)

       if self.values[key] is None:
            self._set_value(snake_case_ ,						snake_case_		)

       elif self.values[key] == data:
            pass

       else:
            UpperCAmelCase_				:  Optional[Any]  = self._collision_resolution(snake_case_ ,						snake_case_		)
            if collision_resolution is not None:
                 self._set_value(snake_case_ ,						snake_case_		)
            else:
                 self.rehashing()
                 self.insert_data(snake_case_		)









from typing import TYPE_CHECKING

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


lowerCAmelCase__             =		{
    """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:
							lowerCAmelCase__             =		["""MarkupLMTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__             =		[
							    """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

							lowerCAmelCase__             =		_LazyModule(__name__, globals()["""__file__"""], _import_structure)




