

import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin






class  UpperCAmelCase__	( A__		,  unittest.TestCase ):






  """simple docstring"""


  a     =      PhobertTokenizer
  a     =      False






  def    lowercase_	(							self		:	str      )	->							List[str]:
       super().setUp()

       # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
       SCREAMING_SNAKE_CASE__					=					['''T@@''', '''i''', '''I''', '''R@@''', '''r''', '''e@@''']
       SCREAMING_SNAKE_CASE__					=					dict(zip(__lowerCamelCase			,     range(len(__lowerCamelCase      )      )      )      )
       SCREAMING_SNAKE_CASE__					=					['''#version: 0.2''', '''l à</w>''']
       SCREAMING_SNAKE_CASE__					=					{'''unk_token''': '''<unk>'''}

       SCREAMING_SNAKE_CASE__					=					os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES['''vocab_file''']      )
       SCREAMING_SNAKE_CASE__					=					os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES['''merges_file''']      )

       with open(self.vocab_file			,     '''w'''			,     encoding='''utf-8'''      ) as fp:
            for token in vocab_tokens:
                 fp.write(f'''{token} {vocab_tokens[token]}\n'''      )
       with open(self.merges_file			,     '''w'''			,     encoding='''utf-8'''      ) as fp:
            fp.write('''\n'''.join(__lowerCamelCase      )      )






  def    lowercase_	(							self		:	Tuple			,     **__lowerCamelCase		:	Any      )	->							int:
       kwargs.update(self.special_tokens_map      )
       return PhobertTokenizer.from_pretrained(self.tmpdirname			,     **__lowerCamelCase      )






  def    lowercase_	(							self		:	Tuple			,     __lowerCamelCase		:	str      )	->							str:
       SCREAMING_SNAKE_CASE__					=					'''Tôi là VinAI Research'''
       SCREAMING_SNAKE_CASE__					=					'''T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'''
       return input_text, output_text







  def    lowercase_	(							self		:	Optional[Any]      )	->							int:
       SCREAMING_SNAKE_CASE__					=					PhobertTokenizer(self.vocab_file			,     self.merges_file			,     **self.special_tokens_map      )
       SCREAMING_SNAKE_CASE__					=					'''Tôi là VinAI Research'''
       SCREAMING_SNAKE_CASE__					=					'''T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
       SCREAMING_SNAKE_CASE__					=					tokenizer.tokenize(__lowerCamelCase      )
       print(__lowerCamelCase      )
       self.assertListEqual(__lowerCamelCase			,     __lowerCamelCase      )

       SCREAMING_SNAKE_CASE__					=					tokens + [tokenizer.unk_token]

       SCREAMING_SNAKE_CASE__					=					[4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase      )			,     __lowerCamelCase      )





def        UpperCAmelCase_     (		_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[]
     for data in source_data:
          for i, el in enumerate(_A       ):
               if len(_A       ) < i + 1:
                    data_lists.append([]       )
               data_lists[i].append(float(_A       )       )
     return data_lists
def        UpperCAmelCase_     (		_A   ,	_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[]
     for dlist, weight in zip(_A   ,	_A       ):
          SCREAMING_SNAKE_CASE__					=					min(_A       )
          SCREAMING_SNAKE_CASE__					=					max(_A       )

          SCREAMING_SNAKE_CASE__					=					[]
          # for weight 0 score is 1 - actual score
          if weight == 0:
               for item in dlist:
                    try:
                         score.append(1 - ((item - mind) / (maxd - mind))       )
                    except ZeroDivisionError:
                         score.append(1       )

          elif weight == 1:
               for item in dlist:
                    try:
                         score.append((item - mind) / (maxd - mind)       )
                    except ZeroDivisionError:
                         score.append(0       )

        # weight not 0 or 1
          else:
               SCREAMING_SNAKE_CASE__					=					F'''Invalid weight of {weight:f} provided'''
               raise ValueError(_A       )

          score_lists.append(_A       )

     return score_lists
def        UpperCAmelCase_     (		_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[0 for i in range(len(score_lists[0]       )       )]

     for slist in score_lists:
          for j, ele in enumerate(_A       ):
               SCREAMING_SNAKE_CASE__					=					final_scores[j] + ele

     return final_scores







def        UpperCAmelCase_     (		_A   ,	_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					get_data(_A       )
     SCREAMING_SNAKE_CASE__					=					calculate_each_score(_A   ,	_A       )
     SCREAMING_SNAKE_CASE__					=					generate_final_scores(_A       )

     # append scores to source data
     for i, ele in enumerate(_A       ):
          source_data[i].append(_A       )

     return source_data


