code: 
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  lowerCAmelCase__	:  Dict 		={
      '''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:
  			lowerCAmelCase__	:  Optional[Any] 		=[
  			    '''DPRContextEncoderTokenizerFast''',
  			    '''DPRQuestionEncoderTokenizerFast''',
  			    '''DPRReaderTokenizerFast''',
  			]
  
  try:
  			if not is_torch_available():
  						raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  			pass
  else:
  			lowerCAmelCase__	:  List[str] 		=[
  			    '''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:
  			lowerCAmelCase__	:  Tuple 		=[
  			    '''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
  
  			lowerCAmelCase__	:  int 		=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
  
style_context: 
  
  
  
  from itertools import combinations, product
  
  
  
  
  
  
  def 			__lowercase     (				a__							,     a__							,     a__							,     a__     )       ->				bool:
  							if xa == ya == 0 or xa == ya == 0:
  														return False
  							__SCREAMING_SNAKE_CASE								=      xa * xa + ya * ya
  							__SCREAMING_SNAKE_CASE								=      xa * xa + ya * ya
  							__SCREAMING_SNAKE_CASE								=      (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 			__lowercase     (				a__ = 50     )       ->				int:
  							return sum(
  							    1
  							    for pta, pta in combinations(product(range(limit + 1     )							,     repeat=2     )							,     2     )
  							    if is_right(*a__							,     *a__     )     )
  
  
  if __name__ == "__main__":
  			print(F'''{solution() = }''')
  
  
  
  
  
  
  