from __future__ import annotations






def    UpperCAmelCase__(						lowerCamelCase_  ):



			"""simple docstring"""





			_snake_case              =      {1}
			_snake_case              =      [1]
			for _ in range(2							,	depth + 1  ):
						_snake_case              =      [*previous_coefficients, 0]
						_snake_case              =      [0, *previous_coefficients]
						_snake_case              =      []
						for x, y in zip(snake_case_							,	snake_case_  ):
									coefficients.add(x + y  )
									previous_coefficients.append(x + y  )
			return coefficients






def    UpperCAmelCase__(						lowerCamelCase_  ):



			"""simple docstring"""





			_snake_case              =      set()
			for number in unique_coefficients:
						_snake_case              =      2
						_snake_case              =      number
						while divisor**2 <= copy_number:
									_snake_case              =      0
									while copy_number % divisor == 0:
												copy_number //= divisor
												multiplicity += 1
									if multiplicity >= 2:
												non_squarefrees.add(snake_case_  )
												break
									divisor += 1

			return unique_coefficients.difference(snake_case_  )






def    UpperCAmelCase__(						lowerCamelCase_ = 51  ):



			"""simple docstring"""





			_snake_case              =      get_pascal_triangle_unique_coefficients(snake_case_  )
			_snake_case              =      get_squarefrees(snake_case_  )
			return sum(snake_case_  )


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





import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property

class 	_SCREAMING_SNAKE_CASE							(     unittest.TestCase							):






		"""simple docstring"""







		@cached_property
		def 				_a				(			self    :				Tuple   ):






					"""simple docstring"""
					return BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B"   )



		@cached_property
		def 				_a				(			self    :				Tuple   ):






					"""simple docstring"""
					return BlenderbotTokenizerFast.from_pretrained("facebook/blenderbot-3B"   )



		def 				_a				(			self    :				Optional[Any]   ):






					"""simple docstring"""
					_snake_case              =      self.tokenizer_ab
					_snake_case              =      " I am a small frog."
					_snake_case              =      tok([src_text]  ,					padding=__SCREAMING_SNAKE_CASE  ,					truncation=__SCREAMING_SNAKE_CASE   )["input_ids"]
					_snake_case              =      tok.batch_decode(__SCREAMING_SNAKE_CASE  ,					skip_special_tokens=__SCREAMING_SNAKE_CASE  ,					clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE   )[0]
					assert src_text == decoded



		def 				_a				(			self    :				str   ):






					"""simple docstring"""
					_snake_case              =      self.rust_tokenizer_ab
					_snake_case              =      " I am a small frog."
					_snake_case              =      tok([src_text]  ,					padding=__SCREAMING_SNAKE_CASE  ,					truncation=__SCREAMING_SNAKE_CASE   )["input_ids"]
					_snake_case              =      tok.batch_decode(__SCREAMING_SNAKE_CASE  ,					skip_special_tokens=__SCREAMING_SNAKE_CASE  ,					clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE   )[0]
					assert src_text == decoded



		def 				_a				(			self    :				Optional[Any]   ):






					"""simple docstring"""
					assert self.tokenizer_ab.add_prefix_space
					assert self.tokenizer_ab([" Sam", "Sam"]   ).input_ids == [[5_502, 2], [5_502, 2]]







		def 				_a				(			self    :				str   ):






					"""simple docstring"""
					assert self.rust_tokenizer_ab.add_prefix_space
					assert self.rust_tokenizer_ab([" Sam", "Sam"]   ).input_ids == [[5_502, 2], [5_502, 2]]

