
"""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 hashlib import mda, shaaaa

_a	 =							(shaaaa, mda)


class A_			:




  '''simple docstring'''







  def __init__(	self       ,     lowercase_ = 8						):

     """simple docstring"""
     UpperCAmelCase_      :      List[str]      =					0B0
     UpperCAmelCase_      :      Union[str, Any]      =					size







  def  UpperCamelCase__      (	self       ,     lowercase_						):

     """simple docstring"""
     UpperCAmelCase_      :      Union[str, Any]      =					self.hash_(lowercase_						)
     self.bitarray |= h







  def  UpperCamelCase__      (	self       ,     lowercase_						):

     """simple docstring"""
     UpperCAmelCase_      :      Optional[int]      =					self.hash_(lowercase_						)
     return (h & self.bitarray) == h







  def __contains__(	self       ,     lowercase_						):

     """simple docstring"""
     return self.exists(lowercase_						)







  def  UpperCamelCase__      (	self       ,     lowercase_						):

     """simple docstring"""
     UpperCAmelCase_      :      str      =					bin(lowercase_						)[2:]
     return res.zfill(self.size						)







  @property
  def  UpperCamelCase__      (	self						):

     """simple docstring"""
     return self.format_bin(self.bitarray						)







  def  UpperCamelCase__      (	self       ,     lowercase_						):

     """simple docstring"""
     UpperCAmelCase_      :      List[str]      =					0B0
     for func in HASH_FUNCTIONS:
        UpperCAmelCase_      :      str      =					(
            int.from_bytes(func(value.encode()						).digest()       ,     "little"						) % self.size
        )
        res |= 2**position
     return res







  def  UpperCamelCase__      (	self       ,     lowercase_						):

     """simple docstring"""
     return self.format_bin(self.hash_(lowercase_						)						)







  @property
  def  UpperCamelCase__      (	self						):

     """simple docstring"""
     UpperCAmelCase_      :      Optional[Any]      =					bin(self.bitarray						).count("1"						)
     return (n_ones / self.size) ** len(lowercase_						)


