



"""simple docstring"""






from __future__ import annotations

import typing
from collections import Counter






def 					snake_case__       (		__lowerCamelCase    :   int     ):
			"""simple docstring"""
			lowerCamelCase__		:		List[str]		     =Counter()
			for base in range(1							,		max_perimeter + 1     ):
						for perpendicular in range(_UpperCamelCase							,		max_perimeter + 1     ):
									lowerCamelCase__		:		Any		     =(base * base + perpendicular * perpendicular) ** 0.5
									if hypotenuse == int(_UpperCamelCase     ):
												lowerCamelCase__		:		str		     =int(base + perpendicular + hypotenuse     )
												if perimeter > max_perimeter:
															continue
												triplets[perimeter] += 1
			return triplets






def 					snake_case__       (		__lowerCamelCase    :   int = 1000     ):
			"""simple docstring"""
			lowerCamelCase__		:		Any		     =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_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


_lowercase			:			Any										=						{
    "configuration_trocr": ["TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP", "TrOCRConfig"],
    "processing_trocr": ["TrOCRProcessor"],
}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase			:			List[Any]										=						[
		    "TROCR_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "TrOCRForCausalLM",
		    "TrOCRPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
		from .processing_trocr import TrOCRProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
		import sys

		_lowercase			:			Tuple										=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




