'''simple docstring'''
import math



def  __lowerCamelCase       (      _UpperCamelCase  :  int					):


      '''simple docstring'''


      return math.sqrt(_UpperCamelCase					) * math.sqrt(_UpperCamelCase					) == num



def  __lowerCamelCase       (      _UpperCamelCase  :  int					):


      '''simple docstring'''


      UpperCAmelCase_            =  0
      UpperCAmelCase_            =  n
      while left <= right:
            UpperCAmelCase_            =  (left + right) // 2
            if mid**2 == n:
                  return True
            elif mid**2 > n:
                  UpperCAmelCase_            =  mid - 1
            else:
                  UpperCAmelCase_            =  mid + 1
      return False


if __name__ == "__main__":
      import doctest

      doctest.testmod()






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

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


lowercase__  :      Optional[Any]        =					{
    "configuration_encodec": [
        "ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EncodecConfig",
    ],
    "feature_extraction_encodec": ["EncodecFeatureExtractor"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__  :      List[str]        =					[
          "ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST",
          "EncodecModel",
          "EncodecPreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_encodec import (
          ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
          EncodecConfig,
      )
      from .feature_extraction_encodec import EncodecFeatureExtractor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_encodec import (
                ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
                EncodecModel,
                EncodecPreTrainedModel,
            )

else:
      import sys

      lowercase__  :      str        =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





