
"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_a	 =							{
    'configuration_led': ['LED_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LEDConfig'],
    'tokenization_led': ['LEDTokenizer'],
}

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

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_a	 =							[
				    'LED_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'LEDForConditionalGeneration',
				    'LEDForQuestionAnswering',
				    'LEDForSequenceClassification',
				    'LEDModel',
				    'LEDPreTrainedModel',
				]


try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_a	 =							['TFLEDForConditionalGeneration', 'TFLEDModel', 'TFLEDPreTrainedModel']


if TYPE_CHECKING:
				from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
				from .tokenization_led import LEDTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_led_fast import LEDTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_led import (
								    LED_PRETRAINED_MODEL_ARCHIVE_LIST,
								    LEDForConditionalGeneration,
								    LEDForQuestionAnswering,
								    LEDForSequenceClassification,
								    LEDModel,
								    LEDPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
				import sys

				_a	 =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




"""simple docstring"""





from .hash_table import HashTable


class A_			(lowercase__   ):




  '''simple docstring'''







  def __init__(	self       ,     *lowercase_       ,     **lowercase_						):

     """simple docstring"""
     super().__init__(*lowercase_       ,     **lowercase_						)







  def  UpperCamelCase__      (	self       ,     lowercase_       ,     lowercase_=None						):

     """simple docstring"""
     UpperCAmelCase_      :      Tuple      =					1
     UpperCAmelCase_      :      List[str]      =					self.hash_function(key + i * i						)

     while self.values[new_key] is not None and self.values[new_key] != key:
        i += 1
        UpperCAmelCase_      :      List[Any]      =					(
            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


