






'''simple docstring'''
from __future__ import annotations




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




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




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase							):


   """simple docstring"""




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

   return unique_coefficients.difference(_UpperCamelCase							)




def 						__SCREAMING_SNAKE_CASE   (					_UpperCamelCase = 51							):


   """simple docstring"""




   lowercase_		:      Dict          =       get_pascal_triangle_unique_coefficients(_UpperCamelCase							)
   lowercase_		:      List[Any]          =       get_squarefrees(_UpperCamelCase							)
   return sum(_UpperCamelCase							)


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












'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


UpperCamelCase__	=     {
    'configuration_unispeech_sat': ['UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechSatConfig'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__	=     [
     'UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'UniSpeechSatForAudioFrameClassification',
     'UniSpeechSatForCTC',
     'UniSpeechSatForPreTraining',
     'UniSpeechSatForSequenceClassification',
     'UniSpeechSatForXVector',
     'UniSpeechSatModel',
     'UniSpeechSatPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_unispeech_sat import (
      UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
      UniSpeechSatForAudioFrameClassification,
      UniSpeechSatForCTC,
      UniSpeechSatForPreTraining,
      UniSpeechSatForSequenceClassification,
      UniSpeechSatForXVector,
      UniSpeechSatModel,
      UniSpeechSatPreTrainedModel,
  )

else:
 import sys

 UpperCamelCase__	=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




