


from typing import TYPE_CHECKING

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


__lowerCamelCase   	=  {'''configuration_hubert''': ['''HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''HubertConfig''']}

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


try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase   	=  [
           '''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

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









import math
from timeit import timeit





def 							lowerCamelCase    (							UpperCAmelCase_	:      int      )->			int:

       """simple docstring"""




       a			   =0
       a			   =abs(UpperCAmelCase_      )
       while True:
              a			   =n // 10
              digits += 1
              if n == 0:
                     break
       return digits





def 							lowerCamelCase    (							UpperCAmelCase_	:      int      )->			int:

       """simple docstring"""




       return 1 if n == 0 else math.floor(math.log(abs(UpperCAmelCase_      )   ,       10      ) + 1      )





def 							lowerCamelCase    (							UpperCAmelCase_	:      int      )->			int:

       """simple docstring"""




       return len(str(abs(UpperCAmelCase_      )      )      )





def 							lowerCamelCase    (							)->			None:

       """simple docstring"""




       from collections.abc import Callable

       def benchmark_a_function(UpperCAmelCase_	:      Callable   ,       UpperCAmelCase_	:      int      ) -> None:
              a			   =F'''{func.__name__}({value})'''
              a			   =timeit(F'''__main__.{call}'''   ,       setup="""import __main__"""      )
              print(F'''{call}: {func(UpperCAmelCase_      )} -- {timing} seconds'''      )

       for value in (26_2144, 1125_8999_0684_2624, 126_7650_6002_2822_9401_4967_0320_5376):
              for func in (num_digits, num_digits_fast, num_digits_faster):
                     benchmark_a_function(UpperCAmelCase_   ,       UpperCAmelCase_      )
              print()


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    benchmark()
