from __future__ import annotations

import typing
from collections import Counter




def 				UpperCamelCase						(       __lowercase						: int	):
		'''simple docstring'''




		A_		:				List[Any]     =      Counter()
		for base in range(1						,max_perimeter + 1	):
				for perpendicular in range(__lowerCAmelCase						,max_perimeter + 1	):
						A_		:				Any     =      (base * base + perpendicular * perpendicular) ** 0.5
						if hypotenuse == int(__lowerCAmelCase	):
								A_		:				List[Any]     =      int(base + perpendicular + hypotenuse	)
								if perimeter > max_perimeter:
										continue
								triplets[perimeter] += 1
		return triplets




def 				UpperCamelCase						(       __lowercase						: int = 10_00	):
		'''simple docstring'''




		A_		:				Optional[Any]     =      pythagorean_triple(__lowerCAmelCase	)
		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_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_A   =     {}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A   =     ["NllbTokenizer"]

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A   =     ["NllbTokenizerFast"]


if TYPE_CHECKING:
			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_nllb import NllbTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_nllb_fast import NllbTokenizerFast

else:
			import sys

			_A   =     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



