

"""simple docstring"""



from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_					:	Union[str, Any]							  =						{
    'configuration_whisper': ['WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'WhisperConfig', 'WhisperOnnxConfig'],
    'feature_extraction_whisper': ['WhisperFeatureExtractor'],
    'processing_whisper': ['WhisperProcessor'],
    'tokenization_whisper': ['WhisperTokenizer'],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_					:	Tuple							  =						['WhisperTokenizerFast']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_					:	List[str]							  =						[
     'WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'WhisperForConditionalGeneration',
     'WhisperModel',
     'WhisperPreTrainedModel',
     'WhisperForAudioClassification',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_					:	str							  =						[
     'TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFWhisperForConditionalGeneration',
     'TFWhisperModel',
     'TFWhisperPreTrainedModel',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_					:	Union[str, Any]							  =						[
     'FlaxWhisperForConditionalGeneration',
     'FlaxWhisperModel',
     'FlaxWhisperPreTrainedModel',
     'FlaxWhisperForAudioClassification',
 ]


if TYPE_CHECKING:
 from .configuration_whisper import WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP, WhisperConfig, WhisperOnnxConfig
 from .feature_extraction_whisper import WhisperFeatureExtractor
 from .processing_whisper import WhisperProcessor
 from .tokenization_whisper import WhisperTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_whisper_fast import WhisperTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_whisper import (
      WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
      WhisperForAudioClassification,
      WhisperForConditionalGeneration,
      WhisperModel,
      WhisperPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_whisper import (
      TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFWhisperForConditionalGeneration,
      TFWhisperModel,
      TFWhisperPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_whisper import (
      FlaxWhisperForAudioClassification,
      FlaxWhisperForConditionalGeneration,
      FlaxWhisperModel,
      FlaxWhisperPreTrainedModel,
  )

else:
 import sys

 SCREAMING_SNAKE_CASE_					:	str							  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)









"""simple docstring"""



from collections.abc import Callable





def  _snake_case     (    UpperCAmelCase_  :					Callable[[float], float]					,   UpperCAmelCase_  :					float					,   UpperCAmelCase_  :					float			):
     A__										=  a
     A__										=  b
     if function(UpperCAmelCase_			) == 0:  # one of the a or b is a root for the function
          return a
     elif function(UpperCAmelCase_			) == 0:
          return b
     elif (
         function(UpperCAmelCase_			) * function(UpperCAmelCase_			) > 0
     ):  # if none of these are root and they are both positive or negative,
          # then this algorithm can't find the root
          raise ValueError("""could not find root in given interval."""			)
     else:
          A__										=  start + (end - start) / 2.0
          while abs(start - mid			) > 10**-7:  # until precisely equals to 10^-7
               if function(UpperCAmelCase_			) == 0:
                    return mid
               elif function(UpperCAmelCase_			) * function(UpperCAmelCase_			) < 0:
                    A__										=  mid
               else:
                    A__										=  mid
               A__										=  start + (end - start) / 2.0
          return mid





def  _snake_case     (    UpperCAmelCase_  :					float			):
     return x**3 - 2 * x - 5


if __name__ == "__main__":
 print(bisection(f, 1, 1_0_0_0))

 import doctest

 doctest.testmod()






