


'''simple docstring'''






from .balanced_parentheses import balanced_parentheses
from .stack import Stack


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


def A_					(				__SCREAMING_SNAKE_CASE :					str       )     ->  str:
					if not balanced_parentheses(__SCREAMING_SNAKE_CASE       ):
										raise ValueError('''Mismatched parentheses'''       )
					__SCREAMING_SNAKE_CASE					:							Stack[str]			   = Stack()
					__SCREAMING_SNAKE_CASE					:							Optional[Any]			   = []
					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()
						_A      =     """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))






'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A      =     {
    """configuration_decision_transformer""": [
        """DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """DecisionTransformerConfig""",
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_A      =     [
						    """DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """DecisionTransformerGPT2Model""",
						    """DecisionTransformerGPT2PreTrainedModel""",
						    """DecisionTransformerModel""",
						    """DecisionTransformerPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_decision_transformer import (
						    DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    DecisionTransformerConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_decision_transformer import (
												    DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DecisionTransformerGPTaModel,
												    DecisionTransformerGPTaPreTrainedModel,
												    DecisionTransformerModel,
												    DecisionTransformerPreTrainedModel,
												)


else:
						import sys

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


