


from typing import TYPE_CHECKING

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


_snake_case			 =	{
    '''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:
   _snake_case			 =	['''WhisperTokenizerFast''']

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

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

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case			 =	[
       '''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

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









'''simple docstring'''





from math import ceil





def       __a      (  _UpperCamelCase:       int = 1_001       )		->					int:

     """simple docstring"""




     _snake_case				= 1

     for i in range(1   ,		int(ceil(n / 2.0       )       )       ):
          _snake_case				= 2 * i + 1
          _snake_case				= 2 * i
          _snake_case				= total + 4 * odd**2 - 6 * even

     return total


if __name__ == "__main__":
   import sys

   if len(sys.argv) == 1:
      print(solution())
   else:
      try:
         UpperCamelCase_		:     int          =		int(sys.argv[1])
         print(solution(n))
      except ValueError:
         print('''Invalid entry - please enter a number''')


