


'''simple docstring'''



from itertools import combinations, product




def       _a      (		_lowercase   :      Tuple     ,   _lowercase   :      int     ,   _lowercase   :      Dict     ,   _lowercase   :      Any    ):





     '''simple docstring'''






     if xa == ya == 0 or xa == ya == 0:
          return False
     __UpperCAmelCase      :					List[Any]    				=     xa * xa + ya * ya
     __UpperCAmelCase      :					Any    				=     xa * xa + ya * ya
     __UpperCAmelCase      :					int    				=     (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       _a      (		_lowercase   :      Any = 50    ):





     '''simple docstring'''






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


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






"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a__       :  List[Any]       		=					{
    """configuration_realm""": ["""REALM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RealmConfig"""],
    """tokenization_realm""": ["""RealmTokenizer"""],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__       :  Union[str, Any]       		=					["""RealmTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__       :  Dict       		=					[
       """REALM_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """RealmEmbedder""",
       """RealmForOpenQA""",
       """RealmKnowledgeAugEncoder""",
       """RealmPreTrainedModel""",
       """RealmReader""",
       """RealmScorer""",
       """load_tf_weights_in_realm""",
   ]
   a__       :  Any       		=					["""RealmRetriever"""]


if TYPE_CHECKING:
   from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
   from .tokenization_realm import RealmTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_realm import RealmTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_realm import (
          REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
          RealmEmbedder,
          RealmForOpenQA,
          RealmKnowledgeAugEncoder,
          RealmPreTrainedModel,
          RealmReader,
          RealmScorer,
          load_tf_weights_in_realm,
      )
      from .retrieval_realm import RealmRetriever


else:
   import sys

   a__       :  Any       		=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

