





'''simple docstring'''






from __future__ import annotations
def      UpperCamelCase__   (	lowerCAmelCase						):





      """simple docstring"""


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





      """simple docstring"""


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

      return unique_coefficients.difference(lowerCAmelCase						)
def      UpperCamelCase__   (	lowerCAmelCase = 51						):





      """simple docstring"""


      _lowerCAmelCase							  =							get_pascal_triangle_unique_coefficients(lowerCAmelCase						)
      _lowerCAmelCase							  =							get_squarefrees(lowerCAmelCase						)
      return sum(lowerCAmelCase						)


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






'''simple docstring'''






import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig




class 				UpperCAmelCase  (    snake_case_     ):
      _lowercase:    str		  =     CustomConfig




      def __init__(    self    :				Optional[int]    ,    __snake_case    :				Tuple						)       ->   Optional[Any]:
            super().__init__(__snake_case						)
            _lowerCAmelCase							  =							torch.nn.Linear(config.hidden_size    ,    config.hidden_size						)




      def        lowercase__					(    self    :				Dict    ,    __snake_case    :				List[Any]						)       ->   Dict:
            return self.linear(__snake_case						)




      def        lowercase__					(    self    :				List[Any]    ,    __snake_case    :				int						)       ->   Any:
            pass




class 				UpperCAmelCase  (    snake_case_     ):
      _lowercase:    List[str]		  =     NoSuperInitConfig




      def __init__(    self    :				List[str]    ,    __snake_case    :				List[str]						)       ->   int:
            super().__init__(__snake_case						)
            _lowerCAmelCase							  =							torch.nn.Linear(config.attribute    ,    config.attribute						)




      def        lowercase__					(    self    :				List[str]    ,    __snake_case    :				Dict						)       ->   Any:
            return self.linear(__snake_case						)




      def        lowercase__					(    self    :				Optional[int]    ,    __snake_case    :				List[Any]						)       ->   Dict:
            pass






