

'''simple docstring'''







from __future__ import annotations

import typing
from collections import Counter
def  UpperCAmelCase__      ( UpperCAmelCase__			)     ->     typing.Counter[int]:
       A_		   = Counter()
       for base in range(1,    max_perimeter + 1			):
              for perpendicular in range(UpperCAmelCase__,    max_perimeter + 1			):
                     A_		   = (base * base + perpendicular * perpendicular) ** 0.5
                     if hypotenuse == int(UpperCAmelCase__			):
                            A_		   = int(base + perpendicular + hypotenuse			)
                            if perimeter > max_perimeter:
                                   continue
                            triplets[perimeter] += 1
       return triplets
def  UpperCAmelCase__      ( UpperCAmelCase__ = 10_00			)     ->     int:
       A_		   = pythagorean_triple(UpperCAmelCase__			)
       return triplets.most_common(1			)[0][0]


if __name__ == "__main__":
     print(f"""Perimeter {solution()} has maximum solutions""")



'''simple docstring'''







from typing import TYPE_CHECKING

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


__lowerCamelCase						    =      {
    '''configuration_blenderbot''': [
        '''BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlenderbotConfig''',
        '''BlenderbotOnnxConfig''',
    ],
    '''tokenization_blenderbot''': ['''BlenderbotTokenizer'''],
}

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						    =      [
          '''BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''BlenderbotForCausalLM''',
          '''BlenderbotForConditionalGeneration''',
          '''BlenderbotModel''',
          '''BlenderbotPreTrainedModel''',
      ]


try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						    =      [
          '''TFBlenderbotForConditionalGeneration''',
          '''TFBlenderbotModel''',
          '''TFBlenderbotPreTrainedModel''',
      ]


try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						    =      [
          '''FlaxBlenderbotForConditionalGeneration''',
          '''FlaxBlenderbotModel''',
          '''FlaxBlenderbotPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_blenderbot import (
          BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
          BlenderbotConfig,
          BlenderbotOnnxConfig,
      )
      from .tokenization_blenderbot import BlenderbotTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_blenderbot import (
                BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
                BlenderbotForCausalLM,
                BlenderbotForConditionalGeneration,
                BlenderbotModel,
                BlenderbotPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_blenderbot import (
                TFBlenderbotForConditionalGeneration,
                TFBlenderbotModel,
                TFBlenderbotPreTrainedModel,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flax_blenderbot import (
                FlaxBlenderbotForConditionalGeneration,
                FlaxBlenderbotModel,
                FlaxBlenderbotPreTrainedModel,
            )

else:
      import sys

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