
"""simple docstring"""
from typing import TYPE_CHECKING

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


lowercase_       :						Optional[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:
    lowercase_       :						Tuple     					=	['''WhisperTokenizerFast''']

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

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

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

    lowercase_       :						Tuple     					=	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





"""simple docstring"""
import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer





def    _lowerCAmelCase    (     lowerCamelCase__							:							str,						lowerCamelCase__							:							str,						**lowerCamelCase__							:							Optional[Any]				)  ->    Union[str, Any]:
  _SCREAMING_SNAKE_CASE   :				Dict							    = AutoConfig.from_pretrained(lowerCamelCase__,						**lowerCamelCase__				)
  _SCREAMING_SNAKE_CASE   :				List[str]							    = AutoModelForSeqaSeqLM.from_config(lowerCamelCase__				)
  model.save_pretrained(lowerCamelCase__				)
  AutoTokenizer.from_pretrained(lowerCamelCase__				).save_pretrained(lowerCamelCase__				)
  return model


if __name__ == "__main__":
      fire.Fire(save_randomly_initialized_version)



