"""simple docstring"""





from collections import defaultdict
from math import ceil, sqrt


def      lowerCamelCase_(__SCREAMING_SNAKE_CASE = 1_000_000     ,	__SCREAMING_SNAKE_CASE = 10  )->    str:
							_SCREAMING_SNAKE_CASE		:						defaultdict			  =    defaultdict(__lowercase  )

							for outer_width in range(3     ,	(t_limit // 4) + 2  ):
														if outer_width * outer_width > t_limit:
																					_SCREAMING_SNAKE_CASE		:						Any			  =    max(
																					    ceil(sqrt(outer_width * outer_width - t_limit  )  )     ,	1  )
														else:
																					_SCREAMING_SNAKE_CASE		:						List[Any]			  =    1

														hole_width_lower_bound += (outer_width - hole_width_lower_bound) % 2

														for hole_width in range(__lowercase     ,	outer_width - 1     ,	2  ):
																					count[outer_width * outer_width - hole_width * hole_width] += 1

							return sum(1 for n in count.values() if 1 <= n <= 10  )


if __name__ == "__main__":
			print(F"{solution() = }")



"""simple docstring"""





from typing import TYPE_CHECKING

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


lowerCAmelCase_     =	{'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechConfig''']}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase_     =	[
			    '''UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''UniSpeechForCTC''',
			    '''UniSpeechForPreTraining''',
			    '''UniSpeechForSequenceClassification''',
			    '''UniSpeechModel''',
			    '''UniSpeechPreTrainedModel''',
			]

if TYPE_CHECKING:
			from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_unispeech import (
						    UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
						    UniSpeechForCTC,
						    UniSpeechForPreTraining,
						    UniSpeechForSequenceClassification,
						    UniSpeechModel,
						    UniSpeechPreTrainedModel,
						)

else:
			import sys

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


