





'''simple docstring'''







from .balanced_parentheses import balanced_parentheses
from .stack import Stack





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      str )			->						int:
						return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(SCREAMING_SNAKE_CASE__,      -1 )





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      str )			->						str:
						if not balanced_parentheses(SCREAMING_SNAKE_CASE__ ):
												raise ValueError('''Mismatched parentheses''' )
						UpperCAmelCase_      :   Stack[str]      =	Stack()
						UpperCAmelCase_      :   str      =	[]
						for char in expression_str:
												if char.isalpha() or char.isdigit():
																		postfix.append(SCREAMING_SNAKE_CASE__ )
												elif char == "(":
																		stack.push(SCREAMING_SNAKE_CASE__ )
												elif char == ")":
																		while not stack.is_empty() and stack.peek() != "(":
																								postfix.append(stack.pop() )
																		stack.pop()
												else:
																		while not stack.is_empty() and precedence(SCREAMING_SNAKE_CASE__ ) <= precedence(stack.peek() ):
																								postfix.append(stack.pop() )
																		stack.push(SCREAMING_SNAKE_CASE__ )
						while not stack.is_empty():
												postfix.append(stack.pop() )
						return " ".join(SCREAMING_SNAKE_CASE__ )


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

					testmod()
					snake_case_  :							Union[str, Any]            =	"a+b*(c^d-e)^(f+g*h)-i"

					print("Infix to Postfix Notation demonstration:\n")
					print("Infix notation: " + expression)
					print("Postfix notation: " + infix_to_postfix(expression))










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__)





