




'''simple docstring'''







from typing import TYPE_CHECKING

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


A     ={
    '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:
   A     =['WhisperTokenizerFast']

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

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

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

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











'''simple docstring'''







def  _lowerCamelCase				( lowercase						:      bytes						)	->	str:
				return "".join([hex(lowercase						)[2:].zfill(2						).upper() for byte in list(lowercase						)]						)






def  _lowerCamelCase				( lowercase						:      str						)	->	bytes:
				# Check data validity, following RFC3548
				# https://www.ietf.org/rfc/rfc3548.txt
				if (len(lowercase						) % 2) != 0:
								raise ValueError(
								    "Base16 encoded data is invalid:\nData does not have an even number of hex digits."						)
				# Check the character set - the standard base16 alphabet
				# is uppercase according to RFC3548 section 6
				if not set(lowercase						) <= set("0123456789ABCDEF"						):
								raise ValueError(
								    "Base16 encoded data is invalid:\nData is not uppercase hex or it contains invalid characters."						)
				# For every two hexadecimal digits (= a byte), turn it into an integer.
				# Then, string the result together into bytes, and return it.
				return bytes(int(data[i] + data[i + 1]    ,							16						) for i in range(0    ,							len(lowercase						)    ,							2						)						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
