



def 			a		( _UpperCAmelCase				:   str		):







		'''simple docstring'''





		__UpperCAmelCase       :	Tuple						=      str(_UpperCAmelCase		).strip()
		if not bin_string:
				raise ValueError('''Empty string was passed to the function'''		)
		__UpperCAmelCase       :	Any						=      bin_string[0] == '''-'''
		if is_negative:
				__UpperCAmelCase       :	Optional[int]						=      bin_string[1:]
		if not all(char in '''01''' for char in bin_string		):
				raise ValueError('''Non-binary value was passed to the function'''		)
		__UpperCAmelCase       :	Dict						=      0
		for char in bin_string:
				__UpperCAmelCase       :	Union[str, Any]						=      2 * decimal_number + int(_UpperCAmelCase		)
		return -decimal_number if is_negative else decimal_number


if __name__ == "__main__":
				from doctest import testmod

				testmod()










from typing import TYPE_CHECKING

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


__A       ={
    "configuration_speech_to_text_2": ["SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Speech2Text2Config"],
    "processing_speech_to_text_2": ["Speech2Text2Processor"],
    "tokenization_speech_to_text_2": ["Speech2Text2Tokenizer"],
}


try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A       =[
				    "SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "Speech2Text2ForCausalLM",
				    "Speech2Text2PreTrainedModel",
				]


if TYPE_CHECKING:
				from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
				from .processing_speech_to_text_a import SpeechaTextaProcessor
				from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_speech_to_text_a import (
								    SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SpeechaTextaForCausalLM,
								    SpeechaTextaPreTrainedModel,
								)

else:
				import sys

				__A       =_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





