



'''simple docstring'''







from .balanced_parentheses import balanced_parentheses
from .stack import Stack
def 			_lowerCAmelCase(      UpperCAmelCase_      :	List[str]						) ->							Any:
							return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(_SCREAMING_SNAKE_CASE					, -1						)
def 			_lowerCAmelCase(      UpperCAmelCase_      :	List[Any]						) ->							List[str]:


							if not balanced_parentheses(_SCREAMING_SNAKE_CASE						):
														raise ValueError("""Mismatched parentheses"""						)
							lowerCAmelCase__  =   Stack()
							lowerCAmelCase__  =   []
							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()
		_UpperCamelCase  						=			"""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_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase__        =      {
    '''configuration_openai''': ['''OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''OpenAIGPTConfig'''],
    '''tokenization_openai''': ['''OpenAIGPTTokenizer'''],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__        =      ['''OpenAIGPTTokenizerFast''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__        =      [
						    '''OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''OpenAIGPTDoubleHeadsModel''',
						    '''OpenAIGPTForSequenceClassification''',
						    '''OpenAIGPTLMHeadModel''',
						    '''OpenAIGPTModel''',
						    '''OpenAIGPTPreTrainedModel''',
						    '''load_tf_weights_in_openai_gpt''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__        =      [
						    '''TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFOpenAIGPTDoubleHeadsModel''',
						    '''TFOpenAIGPTForSequenceClassification''',
						    '''TFOpenAIGPTLMHeadModel''',
						    '''TFOpenAIGPTMainLayer''',
						    '''TFOpenAIGPTModel''',
						    '''TFOpenAIGPTPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_openai import OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenAIGPTConfig
						from .tokenization_openai import OpenAIGPTTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_openai_fast import OpenAIGPTTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_openai import (
												    OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    OpenAIGPTDoubleHeadsModel,
												    OpenAIGPTForSequenceClassification,
												    OpenAIGPTLMHeadModel,
												    OpenAIGPTModel,
												    OpenAIGPTPreTrainedModel,
												    load_tf_weights_in_openai_gpt,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_openai import (
												    TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFOpenAIGPTDoubleHeadsModel,
												    TFOpenAIGPTForSequenceClassification,
												    TFOpenAIGPTLMHeadModel,
												    TFOpenAIGPTMainLayer,
												    TFOpenAIGPTModel,
												    TFOpenAIGPTPreTrainedModel,
												)

else:
						import sys

						lowerCAmelCase__        =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






