



import os

from bleurt import score  # From: git+https://github.com/google-research/bleurt.git

import datasets


a_						:     Any	     =		datasets.logging.get_logger(__name__)


a_						:     Union[str, Any]	     =		'\\n@inproceedings{bleurt,\n  title={BLEURT: Learning Robust Metrics for Text Generation},\n  author={Thibault Sellam and Dipanjan Das and Ankur P. Parikh},\n  booktitle={ACL},\n  year={2020},\n  url={https://arxiv.org/abs/2004.04696}\n}\n'

a_						:     int	     =		'\\nBLEURT a learnt evaluation metric for Natural Language Generation. It is built using multiple phases of transfer learning starting from a pretrained BERT model (Devlin et al. 2018)\nand then employing another pre-training phrase using synthetic data. Finally it is trained on WMT human annotations. You may run BLEURT out-of-the-box or fine-tune\nit for your specific application (the latter is expected to perform better).\n\nSee the project\'s README at https://github.com/google-research/bleurt#readme for more information.\n'

a_						:     Optional[Any]	     =		'\nBLEURT score.\n\nArgs:\n    `predictions` (list of str): prediction/candidate sentences\n    `references` (list of str): reference sentences\n    `checkpoint` BLEURT checkpoint. Will default to BLEURT-tiny if None.\n\nReturns:\n    \'scores\': List of scores.\nExamples:\n\n    >>> predictions = ["hello there", "general kenobi"]\n    >>> references = ["hello there", "general kenobi"]\n    >>> bleurt = datasets.load_metric("bleurt")\n    >>> results = bleurt.compute(predictions=predictions, references=references)\n    >>> print([round(v, 2) for v in results["scores"]])\n    [1.03, 1.04]\n'

a_						:     int	     =		{
    'bleurt-tiny-128': 'https://storage.googleapis.com/bleurt-oss/bleurt-tiny-128.zip',
    'bleurt-tiny-512': 'https://storage.googleapis.com/bleurt-oss/bleurt-tiny-512.zip',
    'bleurt-base-128': 'https://storage.googleapis.com/bleurt-oss/bleurt-base-128.zip',
    'bleurt-base-512': 'https://storage.googleapis.com/bleurt-oss/bleurt-base-512.zip',
    'bleurt-large-128': 'https://storage.googleapis.com/bleurt-oss/bleurt-large-128.zip',
    'bleurt-large-512': 'https://storage.googleapis.com/bleurt-oss/bleurt-large-512.zip',
    'BLEURT-20-D3': 'https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D3.zip',
    'BLEURT-20-D6': 'https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D6.zip',
    'BLEURT-20-D12': 'https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D12.zip',
    'BLEURT-20': 'https://storage.googleapis.com/bleurt-oss-21/BLEURT-20.zip',
}





@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION       ,    _KWARGS_DESCRIPTION)
class    lowerCamelCase__  (						datasets.Metric):
     """simple docstring"""



     def 						_a      (self    ):






           '''simple docstring'''



           return datasets.MetricInfo(
               description=_DESCRIPTION				,			citation=_CITATION				,			homepage="https://github.com/google-research/bleurt"				,			inputs_description=_KWARGS_DESCRIPTION				,			features=datasets.Features(
                   {
                       "predictions": datasets.Value("string"				,			id="sequence"    ),
                       "references": datasets.Value("string"				,			id="sequence"    ),
                   }    )				,			codebase_urls=["https://github.com/google-research/bleurt"]				,			reference_urls=["https://github.com/google-research/bleurt", "https://arxiv.org/abs/2004.04696"]				,			)







     def 						_a      (self				,			__a    ):






           '''simple docstring'''



           if self.config_name == "default":
                 logger.warning(
                     "Using default BLEURT-Base checkpoint for sequence maximum length 128. "
                     "You can use a bigger model for better results with e.g.: datasets.load_metric('bleurt', 'bleurt-large-512')."    )
                 lowerCamelCase								=		"bleurt-base-128"

           if self.config_name.lower() in CHECKPOINT_URLS:
                 lowerCamelCase								=		self.config_name.lower()

           elif self.config_name.upper() in CHECKPOINT_URLS:
                 lowerCamelCase								=		self.config_name.upper()

           else:
                 raise KeyError(
                     F"""{self.config_name} model not found. You should supply the name of a model checkpoint for bleurt in {CHECKPOINT_URLS.keys()}"""    )

           # download the model checkpoint specified by self.config_name and set up the scorer
           lowerCamelCase								=		dl_manager.download_and_extract(CHECKPOINT_URLS[checkpoint_name]    )
           lowerCamelCase								=		score.BleurtScorer(os.path.join(__a				,			__a    )    )







     def 						_a      (self				,			__a				,			__a    ):






           '''simple docstring'''



           lowerCamelCase								=		self.scorer.score(references=__a				,			candidates=__a    )
           return {"scores": scores}








def     __lowercase(	UpperCAmelCase__ ):


      """simple docstring"""



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

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

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

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

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

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

def     __lowercase(	UpperCAmelCase__ ):


      """simple docstring"""



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

      for i in range(len(UpperCAmelCase__ ) ):
            if infix[i] == "(":
                  lowerCamelCase								=		")"  # change "(" to ")"
            elif infix[i] == ")":
                  lowerCamelCase								=		"("  # change ")" to "("

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


if __name__ == "__main__":
     a_						:     str	     =		input('\nEnter an Infix Equation = ')  # Input an Infix equation
     a_						:     List[Any]	     =		''.join(Infix.split())  # Remove spaces from the input
     print('\n\t', Infix, '(Infix) -> ', infix_2_prefix(Infix), '(Prefix)')