






"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_tf_available,
    is_torch_available,
)


__A		:       Optional[int]  				=		{
    '''configuration_speech_to_text''': ['''SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Speech2TextConfig'''],
    '''processing_speech_to_text''': ['''Speech2TextProcessor'''],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:       Tuple  				=		['''Speech2TextTokenizer''']

try:
						if not is_speech_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:       List[str]  				=		['''Speech2TextFeatureExtractor''']

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:       List[Any]  				=		[
						    '''TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFSpeech2TextForConditionalGeneration''',
						    '''TFSpeech2TextModel''',
						    '''TFSpeech2TextPreTrainedModel''',
						]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__A		:       List[Any]  				=		[
						    '''SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''Speech2TextForConditionalGeneration''',
						    '''Speech2TextModel''',
						    '''Speech2TextPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_speech_to_text import SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextConfig
						from .processing_speech_to_text import SpeechaTextProcessor

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_speech_to_text import SpeechaTextTokenizer

						try:
												if not is_speech_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_speech_to_text import SpeechaTextFeatureExtractor

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_speech_to_text import (
												    TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFSpeechaTextForConditionalGeneration,
												    TFSpeechaTextModel,
												    TFSpeechaTextPreTrainedModel,
												)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_speech_to_text import (
												    SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SpeechaTextForConditionalGeneration,
												    SpeechaTextModel,
												    SpeechaTextPreTrainedModel,
												)

else:
						import sys

						__A		:       int  				=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands






def    lowerCamelCase__				(				):




			"""simple docstring"""


			lowerCAmelCase_						=	ArgumentParser("Transformers CLI tool"    ,							usage="transformers-cli <command> [<args>]"				)
			lowerCAmelCase_						=	parser.add_subparsers(help="transformers-cli command helpers"				)

			# Register commands
			ConvertCommand.register_subcommand(__lowerCAmelCase				)
			DownloadCommand.register_subcommand(__lowerCAmelCase				)
			EnvironmentCommand.register_subcommand(__lowerCAmelCase				)
			RunCommand.register_subcommand(__lowerCAmelCase				)
			ServeCommand.register_subcommand(__lowerCAmelCase				)
			UserCommands.register_subcommand(__lowerCAmelCase				)
			AddNewModelCommand.register_subcommand(__lowerCAmelCase				)
			AddNewModelLikeCommand.register_subcommand(__lowerCAmelCase				)
			LfsCommands.register_subcommand(__lowerCAmelCase				)
			PTtoTFCommand.register_subcommand(__lowerCAmelCase				)

			# Let's go
			lowerCAmelCase_						=	parser.parse_args()

			if not hasattr(__lowerCAmelCase    ,							"func"				):
						parser.print_help()
						exit(1				)

			# Run
			lowerCAmelCase_						=	args.func(__lowerCAmelCase				)
			service.run()


if __name__ == "__main__":
			main()



