





'''simple docstring'''

from __future__ import annotations




def  _a     (				lowerCAmelCase_						):





      """simple docstring"""



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




def  _a     (				lowerCAmelCase_						):





      """simple docstring"""



      _snake_case		:						List[str]         =  set()
      for number in unique_coefficients:
            _snake_case		:						List[Any]         =  2
            _snake_case		:						List[Any]         =  number
            while divisor**2 <= copy_number:
                  _snake_case		:						Optional[int]         =  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  _a     (				lowerCAmelCase_ = 51						):





      """simple docstring"""



      _snake_case		:						Dict         =  get_pascal_triangle_unique_coefficients(lowerCAmelCase_						)
      _snake_case		:						Optional[int]         =  get_squarefrees(lowerCAmelCase_						)
      return sum(lowerCAmelCase_						)


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









'''simple docstring'''

from typing import TYPE_CHECKING

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


UpperCAmelCase       :		Dict		=				{'configuration_hubert': ['HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'HubertConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase       :		Union[str, Any]		=				[
       'HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'HubertForCTC',
       'HubertForSequenceClassification',
       'HubertModel',
       'HubertPreTrainedModel',
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase       :		Optional[int]		=				[
       'TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TFHubertForCTC',
       'TFHubertModel',
       'TFHubertPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_hubert import (
          HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          HubertForCTC,
          HubertForSequenceClassification,
          HubertModel,
          HubertPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_hubert import (
          TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFHubertForCTC,
          TFHubertModel,
          TFHubertPreTrainedModel,
      )


else:
   import sys

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


