

import os
import unittest

from transformers import RealmTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.realm.tokenization_realm import RealmTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english







@require_tokenizers
class 		__magic_name__    (							lowerCamelCase__	, unittest.TestCase							):

   '''simple docstring'''




   lowerCamelCase__				:			Dict												=     RealmTokenizer
   lowerCamelCase__				:			Optional[Any]												=     RealmTokenizerFast
   lowerCamelCase__				:			Optional[int]												=     True
   lowerCamelCase__				:			List[str]												=     True
   lowerCamelCase__				:			Optional[int]												=     filter_non_english



   def 				_UpperCAmelCase				(       self )							->					Optional[int]:






     """simple docstring"""






     super().setUp()

     a__						=[
         '''[UNK]''',
         '''[CLS]''',
         '''[SEP]''',
         '''[PAD]''',
         '''[MASK]''',
         '''want''',
         '''##want''',
         '''##ed''',
         '''wa''',
         '''un''',
         '''runn''',
         '''##ing''',
         ''',''',
         '''low''',
         '''lowest''',
     ]
     a__						=os.path.join(self.tmpdirname,					VOCAB_FILES_NAMES['''vocab_file'''] )
     with open(self.vocab_file,					'''w''',					encoding='''utf-8''' ) as vocab_writer:
       vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens] ) )



   def 				_UpperCAmelCase				(       self,					lowercase_ )							->					Any:






     """simple docstring"""






     a__						='''UNwant\u00E9d,running'''
     a__						='''unwanted, running'''
     return input_text, output_text



   def 				_UpperCAmelCase				(       self )							->					Optional[int]:






     """simple docstring"""






     a__						=self.tokenizer_class(self.vocab_file )

     a__						=tokenizer.tokenize('''UNwant\u00E9d,running''' )
     self.assertListEqual(lowercase_,					['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing'''] )
     self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_ ),					[9, 6, 7, 12, 10, 11] )



   def 				_UpperCAmelCase				(       self )							->					int:






     """simple docstring"""






     if not self.test_rust_tokenizer:
       return

     a__						=self.get_tokenizer()
     a__						=self.get_rust_tokenizer()

     a__						='''UNwant\u00E9d,running'''

     a__						=tokenizer.tokenize(lowercase_ )
     a__						=rust_tokenizer.tokenize(lowercase_ )
     self.assertListEqual(lowercase_,					lowercase_ )

     a__						=tokenizer.encode(lowercase_,					add_special_tokens=lowercase_ )
     a__						=rust_tokenizer.encode(lowercase_,					add_special_tokens=lowercase_ )
     self.assertListEqual(lowercase_,					lowercase_ )

     a__						=self.get_rust_tokenizer()
     a__						=tokenizer.encode(lowercase_ )
     a__						=rust_tokenizer.encode(lowercase_ )
     self.assertListEqual(lowercase_,					lowercase_ )

     # With lower casing
     a__						=self.get_tokenizer(do_lower_case=lowercase_ )
     a__						=self.get_rust_tokenizer(do_lower_case=lowercase_ )

     a__						='''UNwant\u00E9d,running'''

     a__						=tokenizer.tokenize(lowercase_ )
     a__						=rust_tokenizer.tokenize(lowercase_ )
     self.assertListEqual(lowercase_,					lowercase_ )

     a__						=tokenizer.encode(lowercase_,					add_special_tokens=lowercase_ )
     a__						=rust_tokenizer.encode(lowercase_,					add_special_tokens=lowercase_ )
     self.assertListEqual(lowercase_,					lowercase_ )

     a__						=self.get_rust_tokenizer()
     a__						=tokenizer.encode(lowercase_ )
     a__						=rust_tokenizer.encode(lowercase_ )
     self.assertListEqual(lowercase_,					lowercase_ )



   def 				_UpperCAmelCase				(       self )							->					str:






     """simple docstring"""






     a__						=BasicTokenizer()

     self.assertListEqual(tokenizer.tokenize('''ah\u535A\u63A8zz''' ),					['''ah''', '''\u535A''', '''\u63A8''', '''zz'''] )



   def 				_UpperCAmelCase				(       self )							->					Optional[int]:






     """simple docstring"""






     a__						=BasicTokenizer(do_lower_case=lowercase_ )

     self.assertListEqual(
         tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  ''' ),					['''hello''', '''!''', '''how''', '''are''', '''you''', '''?'''] )
     self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''' ),					['''hello'''] )



   def 				_UpperCAmelCase				(       self )							->					int:






     """simple docstring"""






     a__						=BasicTokenizer(do_lower_case=lowercase_,					strip_accents=lowercase_ )

     self.assertListEqual(
         tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' ),					['''hällo''', '''!''', '''how''', '''are''', '''you''', '''?'''] )
     self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''' ),					['''h\u00E9llo'''] )



   def 				_UpperCAmelCase				(       self )							->					Any:






     """simple docstring"""






     a__						=BasicTokenizer(do_lower_case=lowercase_,					strip_accents=lowercase_ )

     self.assertListEqual(
         tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' ),					['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?'''] )
     self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''' ),					['''hello'''] )



   def 				_UpperCAmelCase				(       self )							->					Dict:






     """simple docstring"""






     a__						=BasicTokenizer(do_lower_case=lowercase_ )

     self.assertListEqual(
         tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' ),					['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?'''] )
     self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''' ),					['''hello'''] )



   def 				_UpperCAmelCase				(       self )							->					Any:






     """simple docstring"""






     a__						=BasicTokenizer(do_lower_case=lowercase_ )

     self.assertListEqual(
         tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  ''' ),					['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?'''] )



   def 				_UpperCAmelCase				(       self )							->					Any:






     """simple docstring"""






     a__						=BasicTokenizer(do_lower_case=lowercase_,					strip_accents=lowercase_ )

     self.assertListEqual(
         tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' ),					['''HäLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?'''] )



   def 				_UpperCAmelCase				(       self )							->					List[Any]:






     """simple docstring"""






     a__						=BasicTokenizer(do_lower_case=lowercase_,					strip_accents=lowercase_ )

     self.assertListEqual(
         tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' ),					['''HaLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?'''] )



   def 				_UpperCAmelCase				(       self )							->					Tuple:






     """simple docstring"""






     a__						=BasicTokenizer(do_lower_case=lowercase_,					never_split=['''[UNK]'''] )

     self.assertListEqual(
         tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU? [UNK]''' ),					['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''', '''[UNK]'''] )



   def 				_UpperCAmelCase				(       self )							->					List[str]:






     """simple docstring"""






     a__						=['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

     a__						={}
     for i, token in enumerate(lowercase_ ):
       a__						=i
     a__						=WordpieceTokenizer(vocab=lowercase_,					unk_token='''[UNK]''' )

     self.assertListEqual(tokenizer.tokenize('''''' ),					[] )

     self.assertListEqual(tokenizer.tokenize('''unwanted running''' ),					['''un''', '''##want''', '''##ed''', '''runn''', '''##ing'''] )

     self.assertListEqual(tokenizer.tokenize('''unwantedX running''' ),					['''[UNK]''', '''runn''', '''##ing'''] )



   def 				_UpperCAmelCase				(       self )							->					List[str]:






     """simple docstring"""






     self.assertTrue(_is_whitespace(''' ''' ) )
     self.assertTrue(_is_whitespace('''\t''' ) )
     self.assertTrue(_is_whitespace('''\r''' ) )
     self.assertTrue(_is_whitespace('''\n''' ) )
     self.assertTrue(_is_whitespace('''\u00A0''' ) )

     self.assertFalse(_is_whitespace('''A''' ) )
     self.assertFalse(_is_whitespace('''-''' ) )



   def 				_UpperCAmelCase				(       self )							->					Any:






     """simple docstring"""






     self.assertTrue(_is_control('''\u0005''' ) )

     self.assertFalse(_is_control('''A''' ) )
     self.assertFalse(_is_control(''' ''' ) )
     self.assertFalse(_is_control('''\t''' ) )
     self.assertFalse(_is_control('''\r''' ) )



   def 				_UpperCAmelCase				(       self )							->					Dict:






     """simple docstring"""






     self.assertTrue(_is_punctuation('''-''' ) )
     self.assertTrue(_is_punctuation('''$''' ) )
     self.assertTrue(_is_punctuation('''`''' ) )
     self.assertTrue(_is_punctuation('''.''' ) )

     self.assertFalse(_is_punctuation('''A''' ) )
     self.assertFalse(_is_punctuation(''' ''' ) )



   def 				_UpperCAmelCase				(       self )							->					Dict:






     """simple docstring"""






     a__						=self.get_tokenizer()

     # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
     self.assertListEqual([tokenizer.tokenize(lowercase_ ) for t in ['''Test''', '''\xad''', '''test''']],					[['''[UNK]'''], [], ['''[UNK]''']] )

     if self.test_rust_tokenizer:
       a__						=self.get_rust_tokenizer()
       self.assertListEqual(
           [rust_tokenizer.tokenize(lowercase_ ) for t in ['''Test''', '''\xad''', '''test''']],					[['''[UNK]'''], [], ['''[UNK]''']] )



   @slow
   def 				_UpperCAmelCase				(       self )							->					str:






     """simple docstring"""






     a__						=self.tokenizer_class.from_pretrained('''bert-base-uncased''' )

     a__						=tokenizer.encode('''sequence builders''',					add_special_tokens=lowercase_ )
     a__						=tokenizer.encode('''multi-sequence build''',					add_special_tokens=lowercase_ )

     a__						=tokenizer.build_inputs_with_special_tokens(lowercase_ )
     a__						=tokenizer.build_inputs_with_special_tokens(lowercase_,					lowercase_ )

     assert encoded_sentence == [101] + text + [102]
     assert encoded_pair == [101] + text + [102] + text_a + [102]



   def 				_UpperCAmelCase				(       self )							->					Any:






     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
         a__						=self.rust_tokenizer_class.from_pretrained(lowercase_,					**lowercase_ )

         a__						=F"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
         a__						=tokenizer_r.encode_plus(
             lowercase_,					return_attention_mask=lowercase_,					return_token_type_ids=lowercase_,					return_offsets_mapping=lowercase_,					add_special_tokens=lowercase_,					)

         a__						=tokenizer_r.do_lower_case if hasattr(lowercase_,					'''do_lower_case''' ) else False
         a__						=(
             [
                 ((0, 0), tokenizer_r.cls_token),
                 ((0, 1), '''A'''),
                 ((1, 2), ''','''),
                 ((3, 5), '''na'''),
                 ((5, 6), '''##ï'''),
                 ((6, 8), '''##ve'''),
                 ((9, 15), tokenizer_r.mask_token),
                 ((16, 21), '''Allen'''),
                 ((21, 23), '''##NL'''),
                 ((23, 24), '''##P'''),
                 ((25, 33), '''sentence'''),
                 ((33, 34), '''.'''),
                 ((0, 0), tokenizer_r.sep_token),
             ]
             if not do_lower_case
             else [
                 ((0, 0), tokenizer_r.cls_token),
                 ((0, 1), '''a'''),
                 ((1, 2), ''','''),
                 ((3, 8), '''naive'''),
                 ((9, 15), tokenizer_r.mask_token),
                 ((16, 21), '''allen'''),
                 ((21, 23), '''##nl'''),
                 ((23, 24), '''##p'''),
                 ((25, 33), '''sentence'''),
                 ((33, 34), '''.'''),
                 ((0, 0), tokenizer_r.sep_token),
             ]
         )

         self.assertEqual(
             [e[1] for e in expected_results],					tokenizer_r.convert_ids_to_tokens(tokens['''input_ids'''] ) )
         self.assertEqual([e[0] for e in expected_results],					tokens['''offset_mapping'''] )



   @slow
   def 				_UpperCAmelCase				(       self )							->					List[Any]:






     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
         a__						=self.rust_tokenizer_class.from_pretrained(lowercase_,					**lowercase_ )
         a__						=self.tokenizer_class.from_pretrained(lowercase_,					**lowercase_ )
         a__						=[['''Hello world!''', '''Nice to meet you!'''], ['''The cute cat.''', '''The adorable dog.''']]

         a__						=tokenizer_r.batch_encode_candidates(lowercase_,					max_length=10,					return_tensors='''np''' )
         a__						=tokenizer_p.batch_encode_candidates(lowercase_,					max_length=10,					return_tensors='''np''' )

         a__						=(2, 2, 10)

         self.assertEqual(encoded_sentence_r['''input_ids'''].shape,					lowercase_ )
         self.assertEqual(encoded_sentence_r['''attention_mask'''].shape,					lowercase_ )
         self.assertEqual(encoded_sentence_r['''token_type_ids'''].shape,					lowercase_ )

         self.assertEqual(encoded_sentence_p['''input_ids'''].shape,					lowercase_ )
         self.assertEqual(encoded_sentence_p['''attention_mask'''].shape,					lowercase_ )
         self.assertEqual(encoded_sentence_p['''token_type_ids'''].shape,					lowercase_ )



import torch
from transformers import AutoModelForSequenceClassification, AutoTokenizer, Trainer, TrainingArguments

import datasets


lowerCamelCase     =      '''\
@article{eddine2021frugalscore,
  title={FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metrics for Automatic Text Generation},
  author={Eddine, Moussa Kamal and Shang, Guokan and Tixier, Antoine J-P and Vazirgiannis, Michalis},
  journal={arXiv preprint arXiv:2110.08559},
  year={2021}
}
'''

lowerCamelCase     =      '''\
FrugalScore is a reference-based metric for NLG models evaluation. It is based on a distillation approach that allows to learn a fixed, low cost version of any expensive NLG metric, while retaining most of its original performance.
'''


lowerCamelCase     =      '''
Calculates how good are predictions given some references, using certain scores.
Args:
    predictions (list of str): list of predictions to score. Each predictions
        should be a string.
    references (list of str): list of reference for each prediction. Each
        reference should be a string.
    batch_size (int): the batch size for predictions.
    max_length (int): maximum sequence length.
    device (str): either gpu or cpu
Returns:
    scores (list of int): list of scores.
Examples:
    >>> frugalscore = datasets.load_metric("frugalscore")
    >>> results = frugalscore.compute(predictions=[\'hello there\', \'huggingface\'], references=[\'hello world\', \'hugging face\'])
    >>> print([round(s, 3) for s in results["scores"]])
    [0.631, 0.645]
'''







@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION	, _KWARGS_DESCRIPTION							)
class 		__magic_name__    (							datasets.Metric							):

   '''simple docstring'''




   def 				_UpperCAmelCase				(       self )							->					Optional[int]:






     """simple docstring"""






     return datasets.MetricInfo(
         description=_DESCRIPTION,					citation=_CITATION,					inputs_description=_KWARGS_DESCRIPTION,					features=datasets.Features(
             {
                 '''predictions''': datasets.Value('''string''' ),
                 '''references''': datasets.Value('''string''' ),
             } ),					homepage='''https://github.com/moussaKam/FrugalScore''',					)



   def 				_UpperCAmelCase				(       self,					lowercase_ )							->					Dict:






     """simple docstring"""






     if self.config_name == "default":
       a__						='''moussaKam/frugalscore_tiny_bert-base_bert-score'''
     else:
       a__						=self.config_name
     a__						=AutoModelForSequenceClassification.from_pretrained(lowercase_ )
     a__						=AutoTokenizer.from_pretrained(lowercase_ )



   def 				_UpperCAmelCase				(       self,					lowercase_,					lowercase_,					lowercase_=32,					lowercase_=128,					lowercase_=None,					)							->					Union[str, Any]:






     """simple docstring"""






     assert len(lowercase_ ) == len(
         lowercase_ ), "predictions and references should have the same number of sentences."
     if device is not None:
       assert device in ["gpu", "cpu"], "device should be either gpu or cpu."
     else:
       a__						='''gpu''' if torch.cuda.is_available() else '''cpu'''
     a__						=TrainingArguments(
         '''trainer''',					fpaa=(device == '''gpu'''),					per_device_eval_batch_size=lowercase_,					report_to='''all''',					no_cuda=(device == '''cpu'''),					log_level='''warning''',					)
     a__						={'''sentence1''': predictions, '''sentence2''': references}
     a__						=datasets.Dataset.from_dict(lowercase_ )

     def tokenize_function(lowercase_ ):
       return self.tokenizer(
           data['''sentence1'''],					data['''sentence2'''],					max_length=lowercase_,					truncation=lowercase_,					padding=lowercase_ )

     a__						=raw_datasets.map(lowercase_,					batched=lowercase_ )
     tokenized_datasets.remove_columns(['''sentence1''', '''sentence2'''] )
     a__						=Trainer(self.model,					lowercase_,					tokenizer=self.tokenizer )
     a__						=trainer.predict(lowercase_ )
     return {"scores": list(predictions.predictions.squeeze(-1 ) )}
