


"""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__       :							str        =  {
    '''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__       :							Any        =  ['''Speech2TextTokenizer''']

try:
		if not is_speech_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__       :							Union[str, Any]        =  ['''Speech2TextFeatureExtractor''']

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

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__       :							str        =  [
		    '''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__       :							str        =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




"""simple docstring"""







from __future__ import annotations




def      UpperCAmelCase__ (lowerCAmelCase_     ):




					'''simple docstring'''


					if len(lowerCAmelCase_     ) < 2:
										raise ValueError("Monogons and Digons are not polygons in the Euclidean space"     )
					if any(i <= 0 for i in nums     ):
										raise ValueError("All values must be greater than 0"     )
					__SCREAMING_SNAKE_CASE		     =       nums.copy()
					copy_nums.sort()
					return copy_nums[-1] < sum(copy_nums[:-1]     )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
