code: import json
  import os
  import unittest
  
  from transformers import BartTokenizer, BartTokenizerFast, BatchEncoding
  from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
  from transformers.testing_utils import require_tokenizers, require_torch
  from transformers.utils import cached_property
  
  from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors
  
  @require_tokenizers
  class 				_lowercase						(    UpperCamelCase_   ,     unittest.TestCase ):
  
  
  
  
  
  
      '''simple docstring'''
      SCREAMING_SNAKE_CASE:							Any        =						BartTokenizer
      SCREAMING_SNAKE_CASE:							List[Any]        =						BartTokenizerFast
      SCREAMING_SNAKE_CASE:							Optional[int]        =						True
      SCREAMING_SNAKE_CASE:							int        =						filter_roberta_detectors
  
  
  
  
      def     _a						(						self   ):
         super().setUp()
         lowerCAmelCase_:       Optional[Any]         =  [
             '''l''',
             '''o''',
             '''w''',
             '''e''',
             '''r''',
             '''s''',
             '''t''',
             '''i''',
             '''d''',
             '''n''',
             '''\u0120''',
             '''\u0120l''',
             '''\u0120n''',
             '''\u0120lo''',
             '''\u0120low''',
             '''er''',
             '''\u0120lowest''',
             '''\u0120newer''',
             '''\u0120wider''',
             '''<unk>''',
         ]
         lowerCAmelCase_:       int         =  dict(zip(__UpperCamelCase					,	range(len(__UpperCamelCase   )   )   )   )
         lowerCAmelCase_:       Optional[int]         =  ['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
         lowerCAmelCase_:       List[Any]         =  {'''unk_token''': '''<unk>'''}
  
         lowerCAmelCase_:       Union[str, Any]         =  os.path.join(self.tmpdirname					,	VOCAB_FILES_NAMES["vocab_file"]   )
         lowerCAmelCase_:       List[Any]         =  os.path.join(self.tmpdirname					,	VOCAB_FILES_NAMES["merges_file"]   )
         with open(self.vocab_file					,	"w"					,	encoding="utf-8"   ) as fp:
            fp.write(json.dumps(__UpperCamelCase   ) + "\n"   )
         with open(self.merges_file					,	"w"					,	encoding="utf-8"   ) as fp:
            fp.write("\n".join(__UpperCamelCase   )   )
  
  
  
  
      def     _a						(						self					,	**lowerCamelCase__   ):
         kwargs.update(self.special_tokens_map   )
         return self.tokenizer_class.from_pretrained(self.tmpdirname					,	**__UpperCamelCase   )
  
  
  
  
      def     _a						(						self					,	**lowerCamelCase__   ):
         kwargs.update(self.special_tokens_map   )
         return self.rust_tokenizer_class.from_pretrained(self.tmpdirname					,	**__UpperCamelCase   )
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__   ):
         return "lower newer", "lower newer"
  
  
  
  
      @cached_property
      def     _a						(						self   ):
         return BartTokenizer.from_pretrained("facebook/bart-large"   )
  
  
  
  
      @cached_property
      def     _a						(						self   ):
         return BartTokenizerFast.from_pretrained("facebook/bart-large"   )
  
  
  
  
      @require_torch
      def     _a						(						self   ):
         lowerCAmelCase_:       List[str]         =  ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
         lowerCAmelCase_:       Union[str, Any]         =  [0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]
  
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            lowerCAmelCase_:       Union[str, Any]         =  tokenizer(__UpperCamelCase					,	max_length=len(__UpperCamelCase   )					,	padding=__UpperCamelCase					,	return_tensors="pt"   )
            self.assertIsInstance(__UpperCamelCase					,	__UpperCamelCase   )
  
            self.assertEqual((2, 9)					,	batch.input_ids.shape   )
            self.assertEqual((2, 9)					,	batch.attention_mask.shape   )
            lowerCAmelCase_:       Optional[Any]         =  batch.input_ids.tolist()[0]
            self.assertListEqual(__UpperCamelCase					,	__UpperCamelCase   )
            # Test that special tokens are reset
  
  
  
  
      @require_torch
      def     _a						(						self   ):
         lowerCAmelCase_:       Optional[Any]         =  ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            lowerCAmelCase_:       Tuple         =  tokenizer(__UpperCamelCase					,	padding=__UpperCamelCase					,	return_tensors="pt"   )
            # check if input_ids are returned and no labels
            self.assertIn("input_ids"					,	__UpperCamelCase   )
            self.assertIn("attention_mask"					,	__UpperCamelCase   )
            self.assertNotIn("labels"					,	__UpperCamelCase   )
            self.assertNotIn("decoder_attention_mask"					,	__UpperCamelCase   )
  
  
  
  
      @require_torch
      def     _a						(						self   ):
         lowerCAmelCase_:       Union[str, Any]         =  [
             '''Summary of the text.''',
             '''Another summary.''',
         ]
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            lowerCAmelCase_:       int         =  tokenizer(text_target=__UpperCamelCase					,	max_length=32					,	padding="max_length"					,	return_tensors="pt"   )
            self.assertEqual(32					,	targets["input_ids"].shape[1]   )
  
  
  
  
      @require_torch
      def     _a						(						self   ):
  
  
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            lowerCAmelCase_:       Any         =  tokenizer(
                ["I am a small frog" * 1_024, "I am a small frog"]					,	padding=__UpperCamelCase					,	truncation=__UpperCamelCase					,	return_tensors="pt"   )
            self.assertIsInstance(__UpperCamelCase					,	__UpperCamelCase   )
            self.assertEqual(batch.input_ids.shape					,	(2, 1_024)   )
  
  
  
  
      @require_torch
      def     _a						(						self   ):
         lowerCAmelCase_:       Tuple         =  ['''A long paragraph for summarization.''']
         lowerCAmelCase_:       Dict         =  [
             '''Summary of the text.''',
         ]
         for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            lowerCAmelCase_:       Tuple         =  tokenizer(__UpperCamelCase					,	return_tensors="pt"   )
            lowerCAmelCase_:       Any         =  tokenizer(text_target=__UpperCamelCase					,	return_tensors="pt"   )
            lowerCAmelCase_:       Tuple         =  inputs['''input_ids''']
            lowerCAmelCase_:       str         =  targets['''input_ids''']
            self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()   )
            self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()   )
            self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()   )
            self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()   )
  
  
  
  
      def     _a						(						self   ):
         pass
  
  
  
  
      def     _a						(						self   ):
  
  
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
            with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''   ):
               lowerCAmelCase_:       str         =  self.rust_tokenizer_class.from_pretrained(__UpperCamelCase					,	**__UpperCamelCase   )
               lowerCAmelCase_:       Optional[Any]         =  self.tokenizer_class.from_pretrained(__UpperCamelCase					,	**__UpperCamelCase   )
               lowerCAmelCase_:       int         =  '''A, <mask> AllenNLP sentence.'''
               lowerCAmelCase_:       Union[str, Any]         =  tokenizer_r.encode_plus(__UpperCamelCase					,	add_special_tokens=__UpperCamelCase					,	return_token_type_ids=__UpperCamelCase   )
               lowerCAmelCase_:       List[str]         =  tokenizer_p.encode_plus(__UpperCamelCase					,	add_special_tokens=__UpperCamelCase					,	return_token_type_ids=__UpperCamelCase   )
  
               # token_type_ids should put 0 everywhere
               self.assertEqual(sum(tokens_r["token_type_ids"]   )					,	sum(tokens_p["token_type_ids"]   )   )
  
               # attention_mask should put 1 everywhere, so sum over length should be 1
               self.assertEqual(
                   sum(tokens_r["attention_mask"]   ) / len(tokens_r["attention_mask"]   )					,	sum(tokens_p["attention_mask"]   ) / len(tokens_p["attention_mask"]   )					,	)
  
               lowerCAmelCase_:       Optional[Any]         =  tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]   )
               lowerCAmelCase_:       List[str]         =  tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"]   )
  
               # Rust correctly handles the space before the mask while python doesnt
               self.assertSequenceEqual(tokens_p["input_ids"]					,	[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]   )
               self.assertSequenceEqual(tokens_r["input_ids"]					,	[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]   )
  
               self.assertSequenceEqual(
                   __UpperCamelCase					,	["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]   )
               self.assertSequenceEqual(
                   __UpperCamelCase					,	["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]   )
style_context: from .balanced_parentheses import balanced_parentheses
  from .stack import Stack
  def 		snake_case__  (		lowercase				):
     return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(lowercase       ,							-1				)
  def 		snake_case__  (		lowercase				):
     if not balanced_parentheses(lowercase				):
        raise ValueError("Mismatched parentheses"				)
     lowerCAmelCase_:       Stack[str]         =  Stack()
     lowerCAmelCase_:       Union[str, Any]         =  []
     for char in expression_str:
        if char.isalpha() or char.isdigit():
           postfix.append(lowercase				)
        elif char == "(":
           stack.push(lowercase				)
        elif char == ")":
           while not stack.is_empty() and stack.peek() != "(":
              postfix.append(stack.pop()				)
           stack.pop()
        else:
           while not stack.is_empty() and precedence(lowercase				) <= precedence(stack.peek()				):
              postfix.append(stack.pop()				)
           stack.push(lowercase				)
     while not stack.is_empty():
        postfix.append(stack.pop()				)
     return " ".join(lowercase				)
  
  
  if __name__ == "__main__":
   from doctest import testmod
  
   testmod()
   a     :			int					    =						"""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))