






'''simple docstring'''
import os
import unittest

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    BertTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english






@require_tokenizers
class        __SCREAMING_SNAKE_CASE (     lowerCamelCase		,			unittest.TestCase			):
 snake_case_												=							BertTokenizer
 snake_case_												=							BertTokenizerFast
 snake_case_												=							True
 snake_case_												=							True
 snake_case_												=							filter_non_english




 def        __magic_name__		( self		:							Optional[int] )		->  List[Any]:
       super().setUp()

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=[
           '''[UNK]''',
           '''[CLS]''',
           '''[SEP]''',
           '''[PAD]''',
           '''[MASK]''',
           '''want''',
           '''##want''',
           '''##ed''',
           '''wa''',
           '''un''',
           '''runn''',
           '''##ing''',
           ''',''',
           '''low''',
           '''lowest''',
       ]
       SCREAMING_SNAKE_CASE__       :			int													=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        __magic_name__		( self		:							int   , __lowercase		:							Optional[int] )		->  Dict:
       SCREAMING_SNAKE_CASE__       :			str													='''UNwant\u00E9d,running'''
       SCREAMING_SNAKE_CASE__       :			List[str]													='''unwanted, running'''
       return input_text, output_text




 def        __magic_name__		( self		:							Optional[Any] )		->  int:
       SCREAMING_SNAKE_CASE__       :			Tuple													=self.tokenizer_class(self.vocab_file )

       SCREAMING_SNAKE_CASE__       :			List[Any]													=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        __magic_name__		( self		:							Tuple )		->  Dict:
       if not self.test_rust_tokenizer:
             return

       SCREAMING_SNAKE_CASE__       :			Dict													=self.get_tokenizer()
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=self.get_rust_tokenizer()

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													='''UNwant\u00E9d,running'''

       SCREAMING_SNAKE_CASE__       :			List[str]													=tokenizer.tokenize(__lowercase )
       SCREAMING_SNAKE_CASE__       :			List[str]													=rust_tokenizer.tokenize(__lowercase )
       self.assertListEqual(__lowercase   , __lowercase )

       SCREAMING_SNAKE_CASE__       :			str													=tokenizer.encode(__lowercase   , add_special_tokens=__lowercase )
       SCREAMING_SNAKE_CASE__       :			str													=rust_tokenizer.encode(__lowercase   , add_special_tokens=__lowercase )
       self.assertListEqual(__lowercase   , __lowercase )

       SCREAMING_SNAKE_CASE__       :			List[str]													=self.get_rust_tokenizer()
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=tokenizer.encode(__lowercase )
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=rust_tokenizer.encode(__lowercase )
       self.assertListEqual(__lowercase   , __lowercase )

       # With lower casing
       SCREAMING_SNAKE_CASE__       :			Any													=self.get_tokenizer(do_lower_case=__lowercase )
       SCREAMING_SNAKE_CASE__       :			str													=self.get_rust_tokenizer(do_lower_case=__lowercase )

       SCREAMING_SNAKE_CASE__       :			Dict													='''UNwant\u00E9d,running'''

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=tokenizer.tokenize(__lowercase )
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=rust_tokenizer.tokenize(__lowercase )
       self.assertListEqual(__lowercase   , __lowercase )

       SCREAMING_SNAKE_CASE__       :			Tuple													=tokenizer.encode(__lowercase   , add_special_tokens=__lowercase )
       SCREAMING_SNAKE_CASE__       :			Tuple													=rust_tokenizer.encode(__lowercase   , add_special_tokens=__lowercase )
       self.assertListEqual(__lowercase   , __lowercase )

       SCREAMING_SNAKE_CASE__       :			int													=self.get_rust_tokenizer()
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=tokenizer.encode(__lowercase )
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=rust_tokenizer.encode(__lowercase )
       self.assertListEqual(__lowercase   , __lowercase )




 def        __magic_name__		( self		:							int )		->  List[str]:
       SCREAMING_SNAKE_CASE__       :			List[Any]													=BasicTokenizer()

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




 def        __magic_name__		( self		:							Optional[int] )		->  List[str]:
       SCREAMING_SNAKE_CASE__       :			Any													=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        __magic_name__		( self		:							List[str] )		->  Optional[int]:
       SCREAMING_SNAKE_CASE__       :			Dict													=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        __magic_name__		( self		:							Optional[Any] )		->  Dict:
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=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        __magic_name__		( self		:							Tuple )		->  Optional[Any]:
       SCREAMING_SNAKE_CASE__       :			Dict													=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        __magic_name__		( self		:							str )		->  List[str]:
       SCREAMING_SNAKE_CASE__       :			List[Any]													=BasicTokenizer(do_lower_case=__lowercase )

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




 def        __magic_name__		( self		:							List[str] )		->  Dict:
       SCREAMING_SNAKE_CASE__       :			str													=BasicTokenizer(do_lower_case=__lowercase   , strip_accents=__lowercase )

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




 def        __magic_name__		( self		:							int )		->  int:
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=BasicTokenizer(do_lower_case=__lowercase   , strip_accents=__lowercase )

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




 def        __magic_name__		( self		:							Union[str, Any] )		->  Dict:
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=BasicTokenizer(do_lower_case=__lowercase   , never_split=['''[UNK]'''] )

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




 def        __magic_name__		( self		:							List[str] )		->  Dict:
       SCREAMING_SNAKE_CASE__       :			Dict													=BasicTokenizer()
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													='''a\n\'ll !!to?\'d of, can\'t.'''
       SCREAMING_SNAKE_CASE__       :			Tuple													=['''a''', '''\'''', '''ll''', '''!''', '''!''', '''to''', '''?''', '''\'''', '''d''', '''of''', ''',''', '''can''', '''\'''', '''t''', '''.''']
       self.assertListEqual(tokenizer.tokenize(__lowercase )   , __lowercase )




 def        __magic_name__		( self		:							List[str] )		->  List[Any]:
       SCREAMING_SNAKE_CASE__       :			int													=['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

       SCREAMING_SNAKE_CASE__       :			int													={}
       for i, token in enumerate(__lowercase ):
             SCREAMING_SNAKE_CASE__       :			List[Any]													=i
       SCREAMING_SNAKE_CASE__       :			str													=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        __magic_name__		( self		:							Tuple )		->  Optional[Any]:
       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        __magic_name__		( self		:							Union[str, Any] )		->  List[str]:
       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        __magic_name__		( self		:							int )		->  List[Any]:
       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        __magic_name__		( self		:							Any )		->  Optional[Any]:
       SCREAMING_SNAKE_CASE__       :			str													=self.get_tokenizer()
       SCREAMING_SNAKE_CASE__       :			int													=self.get_rust_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]''']] )

       self.assertListEqual(
           [rust_tokenizer.tokenize(__lowercase ) for t in ['''Test''', '''\xad''', '''test''']]   , [['''[UNK]'''], [], ['''[UNK]''']] )




 @slow
 def        __magic_name__		( self		:							Optional[int] )		->  Optional[int]:
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=self.tokenizer_class.from_pretrained('''bert-base-uncased''' )

       SCREAMING_SNAKE_CASE__       :			int													=tokenizer.encode('''sequence builders'''   , add_special_tokens=__lowercase )
       SCREAMING_SNAKE_CASE__       :			Any													=tokenizer.encode('''multi-sequence build'''   , add_special_tokens=__lowercase )

       SCREAMING_SNAKE_CASE__       :			int													=tokenizer.build_inputs_with_special_tokens(__lowercase )
       SCREAMING_SNAKE_CASE__       :			Dict													=tokenizer.build_inputs_with_special_tokens(__lowercase   , __lowercase )

       assert encoded_sentence == [1_01] + text + [1_02]
       assert encoded_pair == [1_01] + text + [1_02] + text_a + [1_02]




 def        __magic_name__		( self		:							Any )		->  str:
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})" ):
                   SCREAMING_SNAKE_CASE__       :			List[Any]													=self.rust_tokenizer_class.from_pretrained(__lowercase   , **__lowercase )

                   SCREAMING_SNAKE_CASE__       :			Tuple													=F"A, naïve {tokenizer_r.mask_token} AllenNLP sentence."
                   SCREAMING_SNAKE_CASE__       :			Optional[int]													=tokenizer_r.encode_plus(
                       __lowercase   , return_attention_mask=__lowercase   , return_token_type_ids=__lowercase   , return_offsets_mapping=__lowercase   , add_special_tokens=__lowercase   , )

                   SCREAMING_SNAKE_CASE__       :			List[str]													=tokenizer_r.do_lower_case if hasattr(__lowercase   , '''do_lower_case''' ) else False
                   SCREAMING_SNAKE_CASE__       :			List[Any]													=(
                       [
                           ((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'''] )




 def        __magic_name__		( self		:							List[str] )		->  Union[str, Any]:
       SCREAMING_SNAKE_CASE__       :			int													=['''的''', '''人''', '''有''']
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=''''''.join(__lowercase )
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})" ):
                   SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=True
                   SCREAMING_SNAKE_CASE__       :			Optional[Any]													=self.tokenizer_class.from_pretrained(__lowercase   , **__lowercase )
                   SCREAMING_SNAKE_CASE__       :			Optional[Any]													=self.rust_tokenizer_class.from_pretrained(__lowercase   , **__lowercase )

                   SCREAMING_SNAKE_CASE__       :			List[Any]													=tokenizer_p.encode(__lowercase   , add_special_tokens=__lowercase )
                   SCREAMING_SNAKE_CASE__       :			List[Any]													=tokenizer_r.encode(__lowercase   , add_special_tokens=__lowercase )

                   SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=tokenizer_r.convert_ids_to_tokens(__lowercase )
                   SCREAMING_SNAKE_CASE__       :			Optional[Any]													=tokenizer_p.convert_ids_to_tokens(__lowercase )

                   # it is expected that each Chinese character is not preceded by "##"
                   self.assertListEqual(__lowercase   , __lowercase )
                   self.assertListEqual(__lowercase   , __lowercase )

                   SCREAMING_SNAKE_CASE__       :			List[Any]													=False
                   SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=self.rust_tokenizer_class.from_pretrained(__lowercase   , **__lowercase )
                   SCREAMING_SNAKE_CASE__       :			List[Any]													=self.tokenizer_class.from_pretrained(__lowercase   , **__lowercase )

                   SCREAMING_SNAKE_CASE__       :			int													=tokenizer_r.encode(__lowercase   , add_special_tokens=__lowercase )
                   SCREAMING_SNAKE_CASE__       :			Optional[int]													=tokenizer_p.encode(__lowercase   , add_special_tokens=__lowercase )

                   SCREAMING_SNAKE_CASE__       :			Any													=tokenizer_r.convert_ids_to_tokens(__lowercase )
                   SCREAMING_SNAKE_CASE__       :			List[str]													=tokenizer_p.convert_ids_to_tokens(__lowercase )

                   # it is expected that only the first Chinese character is not preceded by "##".
                   SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=[
                       F"##{token}" if idx != 0 else token for idx, token in enumerate(__lowercase )
                   ]
                   self.assertListEqual(__lowercase   , __lowercase )
                   self.assertListEqual(__lowercase   , __lowercase )







'''simple docstring'''
from scipy.stats import pearsonr

import datasets


a_					=	'\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that each dataset is normally distributed. Like other correlation coefficients, this one varies between -1 and +1 with 0 implying no correlation. Correlations of -1 or +1 imply an exact linear relationship. Positive correlations imply that as x increases, so does y. Negative correlations imply that as x increases, y decreases.\nThe p-value roughly indicates the probability of an uncorrelated system producing datasets that have a Pearson correlation at least as extreme as the one computed from these datasets.\n'


a_					=	'\nArgs:\n    predictions (`list` of `int`): Predicted class labels, as returned by a model.\n    references (`list` of `int`): Ground truth labels.\n    return_pvalue (`boolean`): If `True`, returns the p-value, along with the correlation coefficient. If `False`, returns only the correlation coefficient. Defaults to `False`.\n\nReturns:\n    pearsonr (`float`): Pearson correlation coefficient. Minimum possible value is -1. Maximum possible value is 1. Values of 1 and -1 indicate exact linear positive and negative relationships, respectively. A value of 0 implies no correlation.\n    p-value (`float`): P-value, which roughly indicates the probability of an The p-value roughly indicates the probability of an uncorrelated system producing datasets that have a Pearson correlation at least as extreme as the one computed from these datasets. Minimum possible value is 0. Maximum possible value is 1. Higher values indicate higher probabilities.\n\nExamples:\n\n    Example 1-A simple example using only predictions and references.\n        >>> pearsonr_metric = datasets.load_metric("pearsonr")\n        >>> results = pearsonr_metric.compute(predictions=[10, 9, 2.5, 6, 4], references=[1, 2, 3, 4, 5])\n        >>> print(round(results[\'pearsonr\'], 2))\n        -0.74\n\n    Example 2-The same as Example 1, but that also returns the `p-value`.\n        >>> pearsonr_metric = datasets.load_metric("pearsonr")\n        >>> results = pearsonr_metric.compute(predictions=[10, 9, 2.5, 6, 4], references=[1, 2, 3, 4, 5], return_pvalue=True)\n        >>> print(sorted(list(results.keys())))\n        [\'p-value\', \'pearsonr\']\n        >>> print(round(results[\'pearsonr\'], 2))\n        -0.74\n        >>> print(round(results[\'p-value\'], 2))\n        0.15\n'


a_					=	'\n@article{2020SciPy-NMeth,\nauthor  = {Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E. and\n      Haberland, Matt and Reddy, Tyler and Cournapeau, David and\n      Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and\n      Bright, Jonathan and {van der Walt}, St{\'e}fan J. and\n      Brett, Matthew and Wilson, Joshua and Millman, K. Jarrod and\n      Mayorov, Nikolay and Nelson, Andrew R. J. and Jones, Eric and\n      Kern, Robert and Larson, Eric and Carey, C J and\n      Polat, Ilhan and Feng, Yu and Moore, Eric W. and\n      {VanderPlas}, Jake and Laxalde, Denis and Perktold, Josef and\n      Cimrman, Robert and Henriksen, Ian and Quintero, E. A. and\n      Harris, Charles R. and Archibald, Anne M. and\n      Ribeiro, Antonio H. and Pedregosa, Fabian and\n      {van Mulbregt}, Paul and {SciPy 1.0 Contributors}},\ntitle   = {{{SciPy} 1.0: Fundamental Algorithms for Scientific\n      Computing in Python}},\njournal = {Nature Methods},\nyear    = {2020},\nvolume  = {17},\npages   = {261--272},\nadsurl  = {https://rdcu.be/b08Wh},\ndoi = {10.1038/s41592-019-0686-2},\n}\n'






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




 def        __magic_name__		( self		:							List[Any] )		->  Any:
       return datasets.MetricInfo(
           description=_DESCRIPTION   , citation=_CITATION   , inputs_description=_KWARGS_DESCRIPTION   , features=datasets.Features(
               {
                   '''predictions''': datasets.Value('''float''' ),
                   '''references''': datasets.Value('''float''' ),
               } )   , reference_urls=['''https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.pearsonr.html''']   , )




 def        __magic_name__		( self		:							Optional[int]   , __lowercase		:							List[Any]   , __lowercase		:							List[Any]   , __lowercase		:							str=False )		->  int:
       if return_pvalue:
             SCREAMING_SNAKE_CASE__       :			List[str]													=pearsonr(__lowercase   , __lowercase )
             return {"pearsonr": results[0], "p-value": results[1]}
       else:
             return {"pearsonr": float(pearsonr(__lowercase   , __lowercase )[0] )}