





def     _lowerCAmelCase		(  _lowerCAmelCase     ):
   '''simple docstring'''


   A_     :				int			      =	[]
   A_     :				int			      =	[]
   A_     :				List[Any]			      =	{
       """^""": 3,
       """*""": 2,
       """/""": 2,
       """%""": 2,
       """+""": 1,
       """-""": 1,
   }  # Priority of each operator
   A_     :				List[Any]			      =	len(_lowerCAmelCase     ) if (len(_lowerCAmelCase     ) > 7) else 7

   # Print table header for output
   print(
       """Symbol""".center(8     )  ,"""Stack""".center(_lowerCAmelCase     )  ,"""Postfix""".center(_lowerCAmelCase     )  ,sep=""" | """  ,)
   print("""-""" * (print_width * 3 + 7)     )

   for x in infix:
      if x.isalpha() or x.isdigit():
         post_fix.append(_lowerCAmelCase     )  # if x is Alphabet / Digit, add it to Postfix
      elif x == "(":
         stack.append(_lowerCAmelCase     )  # if x is "(" push to Stack
      elif x == ")":  # if x is ")" pop stack until "(" is encountered
         while stack[-1] != "(":
            post_fix.append(stack.pop()     )  # Pop stack & add the content to Postfix
         stack.pop()
      else:
         if len(_lowerCAmelCase     ) == 0:
            stack.append(_lowerCAmelCase     )  # If stack is empty, push x to stack
         else:  # while priority of x is not > priority of element in the stack
            while len(_lowerCAmelCase     ) > 0 and priority[x] <= priority[stack[-1]]:
               post_fix.append(stack.pop()     )  # pop stack & add to Postfix
            stack.append(_lowerCAmelCase     )  # push x to stack

      print(
          x.center(8     )  ,("""""".join(_lowerCAmelCase     )).ljust(_lowerCAmelCase     )  ,("""""".join(_lowerCAmelCase     )).ljust(_lowerCAmelCase     )  ,sep=""" | """  ,)  # Output in tabular format

   while len(_lowerCAmelCase     ) > 0:  # while stack is not empty
      post_fix.append(stack.pop()     )  # pop stack & add to Postfix
      print(
          """ """.center(8     )  ,("""""".join(_lowerCAmelCase     )).ljust(_lowerCAmelCase     )  ,("""""".join(_lowerCAmelCase     )).ljust(_lowerCAmelCase     )  ,sep=""" | """  ,)  # Output in tabular format

   return "".join(_lowerCAmelCase     )  # return Postfix as str



def     _lowerCAmelCase		(  _lowerCAmelCase     ):
   '''simple docstring'''


   A_     :				str			      =	list(infix[::-1]     )  # reverse the infix equation

   for i in range(len(_lowerCAmelCase     )     ):
      if infix[i] == "(":
         A_     :				Optional[int]			      =	""")"""  # change "(" to ")"
      elif infix[i] == ")":
         A_     :				Union[str, Any]			      =	"""("""  # change ")" to "("

   return (infix_2_postfix("""""".join(_lowerCAmelCase     )     ))[
       ::-1
   ]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
      _lowerCAmelCase 				=     input("""\nEnter an Infix Equation = """)  # Input an Infix equation
      _lowerCAmelCase 				=     """""".join(Infix.split())  # Remove spaces from the input
      print("""\n\t""", Infix, """(Infix) -> """, infix_2_prefix(Infix), """(Prefix)""")













from . import __version__

# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
    CLOUDFRONT_DISTRIB_PREFIX,
    CONFIG_NAME,
    DISABLE_TELEMETRY,
    DUMMY_INPUTS,
    DUMMY_MASK,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    FEATURE_EXTRACTOR_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_PREFIX,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    MODEL_CARD_NAME,
    MULTIPLE_CHOICE_DUMMY_INPUTS,
    PYTORCH_PRETRAINED_BERT_CACHE,
    PYTORCH_TRANSFORMERS_CACHE,
    S3_BUCKET_PREFIX,
    SENTENCEPIECE_UNDERLINE,
    SPIECE_UNDERLINE,
    TF2_WEIGHTS_NAME,
    TF_WEIGHTS_NAME,
    TORCH_FX_REQUIRED_VERSION,
    TRANSFORMERS_CACHE,
    TRANSFORMERS_DYNAMIC_MODULE_NAME,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    WEIGHTS_INDEX_NAME,
    WEIGHTS_NAME,
    ContextManagers,
    DummyObject,
    EntryNotFoundError,
    ExplicitEnum,
    ModelOutput,
    PaddingStrategy,
    PushToHubMixin,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    TensorType,
    _LazyModule,
    add_code_sample_docstrings,
    add_end_docstrings,
    add_start_docstrings,
    add_start_docstrings_to_model_forward,
    cached_property,
    copy_func,
    default_cache_path,
    define_sagemaker_information,
    get_cached_models,
    get_file_from_repo,
    get_full_repo_name,
    get_torch_version,
    has_file,
    http_user_agent,
    is_apex_available,
    is_bsa_available,
    is_coloredlogs_available,
    is_datasets_available,
    is_detectrona_available,
    is_faiss_available,
    is_flax_available,
    is_ftfy_available,
    is_in_notebook,
    is_ipex_available,
    is_librosa_available,
    is_offline_mode,
    is_onnx_available,
    is_pandas_available,
    is_phonemizer_available,
    is_protobuf_available,
    is_psutil_available,
    is_pyanvml_available,
    is_pyctcdecode_available,
    is_pytesseract_available,
    is_pytorch_quantization_available,
    is_rjieba_available,
    is_sagemaker_dp_enabled,
    is_sagemaker_mp_enabled,
    is_scipy_available,
    is_sentencepiece_available,
    is_seqio_available,
    is_sklearn_available,
    is_soundfile_availble,
    is_spacy_available,
    is_speech_available,
    is_tensor,
    is_tensorflow_probability_available,
    is_tfaonnx_available,
    is_tf_available,
    is_timm_available,
    is_tokenizers_available,
    is_torch_available,
    is_torch_bfaa_available,
    is_torch_cuda_available,
    is_torch_fx_available,
    is_torch_fx_proxy,
    is_torch_mps_available,
    is_torch_tfaa_available,
    is_torch_tpu_available,
    is_torchaudio_available,
    is_training_run_on_sagemaker,
    is_vision_available,
    replace_return_docstrings,
    requires_backends,
    to_numpy,
    to_py_obj,
    torch_only_method,
)






