



'''simple docstring'''
snake_case_  	=  "Alexander Joslin"

import operator as op

from .stack import Stack






def A__   (					UpperCAmelCase_							):
						_UpperCamelCase :		List[str]			    =       {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}

						_UpperCamelCase :		Any			    =       Stack()
						_UpperCamelCase :		Tuple			    =       Stack()

						for i in equation:
												if i.isdigit():
																		# RULE 1
																		operand_stack.push(int(__A							)							)
												elif i in operators:
																		# RULE 2
																		operator_stack.push(__A							)
												elif i == ")":
																		# RULE 4
																		_UpperCamelCase :		Tuple			    =       operator_stack.peek()
																		operator_stack.pop()
																		_UpperCamelCase :		Dict			    =       operand_stack.peek()
																		operand_stack.pop()
																		_UpperCamelCase :		Dict			    =       operand_stack.peek()
																		operand_stack.pop()

																		_UpperCamelCase :		List[str]			    =       operators[opr](__A  ,  __A							)
																		operand_stack.push(__A							)

    # RULE 5
						return operand_stack.peek()


if __name__ == "__main__":
					snake_case_  	=  "(5 + ((4 * 2) * (2 + 3)))"
					# answer = 45
					print(F"""{equation} = {dijkstras_two_stack_algorithm(equation)}""")







'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


snake_case_			:     Any  	=  {
    'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
    'tokenization_mvp': ['MvpTokenizer'],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     Dict  	=  ['MvpTokenizerFast']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     List[Any]  	=  [
					    'MVP_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MvpForCausalLM',
					    'MvpForConditionalGeneration',
					    'MvpForQuestionAnswering',
					    'MvpForSequenceClassification',
					    'MvpModel',
					    'MvpPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
					from .tokenization_mvp import MvpTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_mvp_fast import MvpTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_mvp import (
										    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MvpForCausalLM,
										    MvpForConditionalGeneration,
										    MvpForQuestionAnswering,
										    MvpForSequenceClassification,
										    MvpModel,
										    MvpPreTrainedModel,
										)

else:
					import sys

					snake_case_			:     Optional[Any]  	=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


