code: from __future__ import annotations
  def 				__lowercase	(						lowerCamelCase__					)				->set[int]:
  
    '''simple docstring'''
  
  
  
  
    a__     		=     {1}
    a__     		=     [1]
    for _ in range(2 ,				depth + 1					):
      a__     		=     [*previous_coefficients, 0]
      a__     		=     [0, *previous_coefficients]
      a__     		=     []
      for x, y in zip(lowercase__ ,				lowercase__					):
        coefficients.add(x + y					)
        previous_coefficients.append(x + y					)
    return coefficients
  def 				__lowercase	(						lowerCamelCase__					)				->set[int]:
  
    '''simple docstring'''
  
  
  
  
    a__     		=     set()
    for number in unique_coefficients:
      a__     		=     2
      a__     		=     number
      while divisor**2 <= copy_number:
        a__     		=     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 				__lowercase	(						lowerCamelCase__ = 51					)				->int:
  
    '''simple docstring'''
  
  
  
  
    a__     		=     get_pascal_triangle_unique_coefficients(lowercase__					)
    a__     		=     get_squarefrees(lowercase__					)
    return sum(lowercase__					)
  
  
  if __name__ == "__main__":
       print(F"""{solution() = }""")
  
  
style_context: from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_sentencepiece_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  _SCREAMING_SNAKE_CASE   						=    {
      """configuration_open_llama""": ["""OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OpenLlamaConfig"""],
  }
  
  try:
       if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _SCREAMING_SNAKE_CASE   						=    ["""LlamaTokenizer"""]
  
  try:
       if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _SCREAMING_SNAKE_CASE   						=    ["""LlamaTokenizerFast"""]
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _SCREAMING_SNAKE_CASE   						=    [
           """OpenLlamaForCausalLM""",
           """OpenLlamaModel""",
           """OpenLlamaPreTrainedModel""",
           """OpenLlamaForSequenceClassification""",
       ]
  
  
  if TYPE_CHECKING:
       from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig
  
       try:
            if not is_sentencepiece_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from transformers import LlamaTokenizer
  
       try:
            if not is_tokenizers_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from transformers import LlamaTokenizerFast
  
       try:
            if not is_torch_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .modeling_open_llama import (
                OpenLlamaForCausalLM,
                OpenLlamaForSequenceClassification,
                OpenLlamaModel,
                OpenLlamaPreTrainedModel,
            )
  
  
  else:
       import sys
  
       _SCREAMING_SNAKE_CASE   						=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  