




from __future__ import annotations

import typing
from collections import Counter







def 				lowerCAmelCase_	(     snake_case_     ):
      _A							:     typing.Counter[int]			=						Counter()
      for base in range(1,max_perimeter + 1     ):
            for perpendicular in range(snake_case_,max_perimeter + 1     ):
                  _A							:     Any			=						(base * base + perpendicular * perpendicular) ** 0.5
                  if hypotenuse == int(snake_case_     ):
                        _A							:     int			=						int(base + perpendicular + hypotenuse     )
                        if perimeter > max_perimeter:
                              continue
                        triplets[perimeter] += 1
      return triplets







def 				lowerCAmelCase_	(     snake_case_ = 1000     ):
      _A							:     int			=						pythagorean_triple(snake_case_     )
      return triplets.most_common(1     )[0][0]


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







from typing import TYPE_CHECKING

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


UpperCAmelCase_									=	{
    'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'VisionEncoderDecoderOnnxConfig']
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase_									=	['VisionEncoderDecoderModel']

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase_									=	['TFVisionEncoderDecoderModel']

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase_									=	['FlaxVisionEncoderDecoderModel']

if TYPE_CHECKING:
       from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig, VisionEncoderDecoderOnnxConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel

else:
       import sys

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

