


"""simple docstring"""




from typing import TYPE_CHECKING

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


lowercase_			     =  {
    """configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfig"""],
}
try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_			     =  ["""BloomTokenizerFast"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_			     =  [
				    """BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """BloomForCausalLM""",
				    """BloomModel""",
				    """BloomPreTrainedModel""",
				    """BloomForSequenceClassification""",
				    """BloomForTokenClassification""",
				    """BloomForQuestionAnswering""",
				]

if TYPE_CHECKING:
				from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_bloom_fast import BloomTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_bloom import (
								    BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BloomForCausalLM,
								    BloomForQuestionAnswering,
								    BloomForSequenceClassification,
								    BloomForTokenClassification,
								    BloomModel,
								    BloomPreTrainedModel,
								)

else:
				import sys

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











'''simple docstring'''






from __future__ import annotations

import typing
from collections import Counter




def     snake_case_					(     lowerCAmelCase_		)->		typing.Counter[int]:





       '''simple docstring'''


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




def     snake_case_					(     lowerCAmelCase_ = 1000		)->		int:





       '''simple docstring'''


       _UpperCAmelCase  :						int			     = pythagorean_triple(lowerCAmelCase_		)
       return triplets.most_common(1		)[0][0]


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



