'''simple docstring'''


from typing import TYPE_CHECKING

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


snake_case__	:     List[str]      =    {
    '''configuration_dpr''': ['''DPR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPRConfig'''],
    '''tokenization_dpr''': [
        '''DPRContextEncoderTokenizer''',
        '''DPRQuestionEncoderTokenizer''',
        '''DPRReaderOutput''',
        '''DPRReaderTokenizer''',
    ],
}


try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__	:     Optional[Any]      =    [
     '''DPRContextEncoderTokenizerFast''',
     '''DPRQuestionEncoderTokenizerFast''',
     '''DPRReaderTokenizerFast''',
 ]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__	:     Any      =    [
     '''DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''DPRContextEncoder''',
     '''DPRPretrainedContextEncoder''',
     '''DPRPreTrainedModel''',
     '''DPRPretrainedQuestionEncoder''',
     '''DPRPretrainedReader''',
     '''DPRQuestionEncoder''',
     '''DPRReader''',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__	:     Optional[Any]      =    [
     '''TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TFDPRContextEncoder''',
     '''TFDPRPretrainedContextEncoder''',
     '''TFDPRPretrainedQuestionEncoder''',
     '''TFDPRPretrainedReader''',
     '''TFDPRQuestionEncoder''',
     '''TFDPRReader''',
 ]


if TYPE_CHECKING:
 from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
 from .tokenization_dpr import (
     DPRContextEncoderTokenizer,
     DPRQuestionEncoderTokenizer,
     DPRReaderOutput,
     DPRReaderTokenizer,
 )

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_dpr_fast import (
      DPRContextEncoderTokenizerFast,
      DPRQuestionEncoderTokenizerFast,
      DPRReaderTokenizerFast,
  )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_dpr import (
      DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
      DPRContextEncoder,
      DPRPretrainedContextEncoder,
      DPRPreTrainedModel,
      DPRPretrainedQuestionEncoder,
      DPRPretrainedReader,
      DPRQuestionEncoder,
      DPRReader,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_dpr import (
      TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFDPRContextEncoder,
      TFDPRPretrainedContextEncoder,
      TFDPRPretrainedQuestionEncoder,
      TFDPRPretrainedReader,
      TFDPRQuestionEncoder,
      TFDPRReader,
  )

else:
 import sys

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







'''simple docstring'''


from itertools import combinations, product


def    _lowerCamelCase       ( lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int  ):



     """simple docstring"""





     if xa == ya == 0 or xa == ya == 0:
          return False
     UpperCAmelCase_				:  Union[str, Any]  = xa * xa + ya * ya
     UpperCAmelCase_				:  str  = xa * xa + ya * ya
     UpperCAmelCase_				:  str  = (xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
     return (
         a_square + b_square == c_square
         or a_square + c_square == b_square
         or b_square + c_square == a_square
     )


def    _lowerCamelCase       ( lowerCamelCase_   :				int = 50  ):



     """simple docstring"""





     return sum(
         1
         for pta, pta in combinations(product(range(limit + 1  )      ,	repeat=2  )      ,	2  )
         if is_right(*lowerCamelCase_      ,	*lowerCamelCase_  )  )


if __name__ == "__main__":
 print(f'''{solution() = }''')






