from __future__ import annotations


def SCREAMING_SNAKE_CASE					(  lowercase_:						int					):
       _UpperCamelCase  :							Optional[Any]	    =	{1}
       _UpperCamelCase  :							Dict	    =	[1]
       for _ in range(2		,    depth + 1					):
              _UpperCamelCase  :							int	    =	[*previous_coefficients, 0]
              _UpperCamelCase  :							Tuple	    =	[0, *previous_coefficients]
              _UpperCamelCase  :							Tuple	    =	[]
              for x, y in zip(lowercase_		,    lowercase_					):
                     coefficients.add(x + y					)
                     previous_coefficients.append(x + y					)
       return coefficients


def SCREAMING_SNAKE_CASE					(  lowercase_:						set[int]					):
       _UpperCamelCase  :							str	    =	set()
       for number in unique_coefficients:
              _UpperCamelCase  :							Dict	    =	2
              _UpperCamelCase  :							int	    =	number
              while divisor**2 <= copy_number:
                     _UpperCamelCase  :							Optional[int]	    =	0
                     while copy_number % divisor == 0:
                            copy_number //= divisor
                            multiplicity += 1
                     if multiplicity >= 2:
                            non_squarefrees.add(lowercase_					)
                            break
                     divisor += 1

       return unique_coefficients.difference(lowercase_					)


def SCREAMING_SNAKE_CASE					(  lowercase_:						int = 51					):
       _UpperCamelCase  :							Optional[Any]	    =	get_pascal_triangle_unique_coefficients(lowercase_					)
       _UpperCamelCase  :							int	    =	get_squarefrees(lowercase_					)
       return sum(lowercase_					)


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








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase :				List[Any]							={"""configuration_qdqbert""": ["""QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """QDQBertConfig"""]}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase :				Dict							=[
	    """QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """QDQBertForMaskedLM""",
	    """QDQBertForMultipleChoice""",
	    """QDQBertForNextSentencePrediction""",
	    """QDQBertForQuestionAnswering""",
	    """QDQBertForSequenceClassification""",
	    """QDQBertForTokenClassification""",
	    """QDQBertLayer""",
	    """QDQBertLMHeadModel""",
	    """QDQBertModel""",
	    """QDQBertPreTrainedModel""",
	    """load_tf_weights_in_qdqbert""",
	]


if TYPE_CHECKING:
	from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_qdqbert import (
		    QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    QDQBertForMaskedLM,
		    QDQBertForMultipleChoice,
		    QDQBertForNextSentencePrediction,
		    QDQBertForQuestionAnswering,
		    QDQBertForSequenceClassification,
		    QDQBertForTokenClassification,
		    QDQBertLayer,
		    QDQBertLMHeadModel,
		    QDQBertModel,
		    QDQBertPreTrainedModel,
		    load_tf_weights_in_qdqbert,
		)


else:
	import sys

	UpperCAmelCase :				Optional[Any]							=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
