




from __future__ import annotations






def    snake_case   (				A     )				->				set[int]:




	'''simple docstring'''


	lowerCamelCase_				:						List[str]				  =				{1}
	lowerCamelCase_				:						Tuple				  =				[1]
	for _ in range(2		,  depth + 1     ):
		lowerCamelCase_				:						Optional[Any]				  =				[*previous_coefficients, 0]
		lowerCamelCase_				:						List[str]				  =				[0, *previous_coefficients]
		lowerCamelCase_				:						Dict				  =				[]
		for x, y in zip(A		,  A     ):
			coefficients.add(x + y     )
			previous_coefficients.append(x + y     )
	return coefficients






def    snake_case   (				A     )				->				set[int]:




	'''simple docstring'''


	lowerCamelCase_				:						int				  =				set()
	for number in unique_coefficients:
		lowerCamelCase_				:						List[str]				  =				2
		lowerCamelCase_				:						Any				  =				number
		while divisor**2 <= copy_number:
			lowerCamelCase_				:						int				  =				0
			while copy_number % divisor == 0:
				copy_number //= divisor
				multiplicity += 1
			if multiplicity >= 2:
				non_squarefrees.add(A     )
				break
			divisor += 1

	return unique_coefficients.difference(A     )






def    snake_case   (				A = 51     )				->				int:




	'''simple docstring'''


	lowerCamelCase_				:						Optional[Any]				  =				get_pascal_triangle_unique_coefficients(A     )
	lowerCamelCase_				:						Tuple				  =				get_squarefrees(A     )
	return sum(A     )


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


"""simple docstring"""
from typing import TYPE_CHECKING

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


lowercase		:    Tuple			=       {
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    int			=       ['CodeGenTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Optional[int]			=       [
			    'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'CodeGenForCausalLM',
			    'CodeGenModel',
			    'CodeGenPreTrainedModel',
			]

if TYPE_CHECKING:
			from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
			from .tokenization_codegen import CodeGenTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_codegen_fast import CodeGenTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_codegen import (
						    CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CodeGenForCausalLM,
						    CodeGenModel,
						    CodeGenPreTrainedModel,
						)

else:
			import sys

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