

from .number_theory.prime_numbers import next_prime


class     lowerCAmelCase				:


       '''simple docstring'''







       def __init__(	self					:  Dict						,	__snake_case					:  int						,	__snake_case					:  int | None = None						,	__snake_case					:  float | None = None						,	)   -> None:







        '''simple docstring'''

        lowerCamelCase      						=    size_table
        lowerCamelCase      						=    [None] * self.size_table
        lowerCamelCase      						=    0.75 if lim_charge is None else lim_charge
        lowerCamelCase      						=    1 if charge_factor is None else charge_factor
        lowerCamelCase      						=    []
        lowerCamelCase      						=    {}

       def   lowerCamelCase__						(	self					:  List[str]     )   -> int:







        '''simple docstring'''

        return self._keys

       def   lowerCamelCase__						(	self					:  Any     )   -> Optional[Any]:







        '''simple docstring'''

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

       def   lowerCamelCase__						(	self					:  List[str]						,	__snake_case					:  Union[str, Any]     )   -> Dict:







        '''simple docstring'''

        return key % self.size_table

       def   lowerCamelCase__						(	self					:  Dict						,	__snake_case					:  Optional[Any]     )   -> str:







        '''simple docstring'''

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

       def   lowerCamelCase__						(	self					:  Dict						,	__snake_case					:  int     )   -> Any:







        '''simple docstring'''

        lowerCamelCase      						=    1
        lowerCamelCase      						=    values
        for value in values:
         self.insert_data(__snake_case     )
         self._step_by_step(__snake_case     )
         i += 1

       def   lowerCamelCase__						(	self					:  Any						,	__snake_case					:  Union[str, Any]						,	__snake_case					:  Optional[int]     )   -> Tuple:







        '''simple docstring'''

        lowerCamelCase      						=    data
        lowerCamelCase      						=    data

       def   lowerCamelCase__						(	self					:  str						,	__snake_case					:  Dict						,	__snake_case					:  Any=None     )   -> Tuple:







        '''simple docstring'''

        lowerCamelCase      						=    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:
          lowerCamelCase      						=    self.hash_function(new_key + 1     )
         else:
          lowerCamelCase      						=    None
          break

        return new_key

       def   lowerCamelCase__						(	self					:  Optional[int]     )   -> Optional[Any]:







        '''simple docstring'''

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





       def   lowerCamelCase__						(	self					:  List[str]						,	__snake_case					:  int     )   -> Union[str, Any]:







        '''simple docstring'''

        lowerCamelCase      						=    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:
         lowerCamelCase      						=    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_sentencepiece_available, is_torch_available


_lowerCAmelCase :	Optional[Any]     				=    {
    'configuration_xlm_prophetnet': ['XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMProphetNetConfig'],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _lowerCAmelCase :	Optional[Any]     				=    ['XLMProphetNetTokenizer']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _lowerCAmelCase :	List[str]     				=    [
         'XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST',
         'XLMProphetNetDecoder',
         'XLMProphetNetEncoder',
         'XLMProphetNetForCausalLM',
         'XLMProphetNetForConditionalGeneration',
         'XLMProphetNetModel',
         'XLMProphetNetPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_xlm_prophetnet import (
              XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              XLMProphetNetDecoder,
              XLMProphetNetEncoder,
              XLMProphetNetForCausalLM,
              XLMProphetNetForConditionalGeneration,
              XLMProphetNetModel,
              XLMProphetNetPreTrainedModel,
          )

else:
     import sys

     _lowerCAmelCase :	List[Any]     				=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




