
from scipy.stats import pearsonr

import datasets


lowercase__		:Dict   =    "\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"


lowercase__		:Optional[int]   =    "\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"


lowercase__		:Tuple   =    "\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 				lowercase		(					datasets.Metric		):




							def  A__      (				self):
												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  A__      (				self   ,A__   ,A__   ,A__=False):
												if return_pvalue:
																	lowercase							=						pearsonr(A__   ,A__)
																	return {"pearsonr": results[0], "p-value": results[1]}
												else:
																	return {"pearsonr": float(pearsonr(A__   ,A__)[0])}






import json
import os
import unittest

from transformers.models.roc_bert.tokenization_roc_bert import (
    VOCAB_FILES_NAMES,
    RoCBertBasicTokenizer,
    RoCBertTokenizer,
    RoCBertWordpieceTokenizer,
    _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 				lowercase		(					SCREAMING_SNAKE_CASE__       ,  unittest.TestCase		):
							lowercase_       :       Union[str, Any]       					=RoCBertTokenizer
							lowercase_       :       str       					=None
							lowercase_       :       Optional[Any]       					=False
							lowercase_       :       Any       					=True
							lowercase_       :       int       					=filter_non_english




							def  A__      (				self):
												super().setUp()

												lowercase							=						['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''你''', '''好''', '''是''', '''谁''', '''a''', '''b''', '''c''', '''d''']
												lowercase							=						{}
												lowercase							=						{}
												for i, value in enumerate(A__):
																	lowercase							=						i
																	lowercase							=						i
												lowercase							=						os.path.join(self.tmpdirname   ,VOCAB_FILES_NAMES['''vocab_file'''])
												lowercase							=						os.path.join(self.tmpdirname   ,VOCAB_FILES_NAMES['''word_shape_file'''])
												lowercase							=						os.path.join(self.tmpdirname   ,VOCAB_FILES_NAMES['''word_pronunciation_file'''])
												with open(self.vocab_file   ,'''w'''   ,encoding='''utf-8''') as vocab_writer:
																	vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]))
												with open(self.word_shape_file   ,'''w'''   ,encoding='''utf-8''') as word_shape_writer:
																	json.dump(A__   ,A__   ,ensure_ascii=A__)
												with open(self.word_pronunciation_file   ,'''w'''   ,encoding='''utf-8''') as word_pronunciation_writer:
																	json.dump(A__   ,A__   ,ensure_ascii=A__)




							def  A__      (				self):
												lowercase							=						self.tokenizer_class(self.vocab_file   ,self.word_shape_file   ,self.word_pronunciation_file)

												lowercase							=						tokenizer.tokenize('''你好[SEP]你是谁''')
												self.assertListEqual(A__   ,['''你''', '''好''', '''[SEP]''', '''你''', '''是''', '''谁'''])
												self.assertListEqual(tokenizer.convert_tokens_to_ids(A__)   ,[5, 6, 2, 5, 7, 8])
												self.assertListEqual(tokenizer.convert_tokens_to_shape_ids(A__)   ,[5, 6, 2, 5, 7, 8])
												self.assertListEqual(tokenizer.convert_tokens_to_pronunciation_ids(A__)   ,[5, 6, 2, 5, 7, 8])




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer()

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




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer(do_lower_case=A__)

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




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer(do_lower_case=A__   ,strip_accents=A__)

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




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer(do_lower_case=A__   ,strip_accents=A__)

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




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer(do_lower_case=A__)

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




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer(do_lower_case=A__)

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




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer(do_lower_case=A__   ,strip_accents=A__)

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




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer(do_lower_case=A__   ,strip_accents=A__)

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




							def  A__      (				self):
												lowercase							=						RoCBertBasicTokenizer(do_lower_case=A__   ,never_split=['''[UNK]'''])

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




							def  A__      (				self):
												lowercase							=						['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

												lowercase							=						{}
												for i, token in enumerate(A__):
																	lowercase							=						i
												lowercase							=						RoCBertWordpieceTokenizer(vocab=A__   ,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  A__      (				self):
												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  A__      (				self):
												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  A__      (				self):
												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  A__      (				self):
												lowercase							=						self.get_tokenizer()

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

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




							def  A__      (				self):
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
																						lowercase							=						self.rust_tokenizer_class.from_pretrained(A__   ,**A__)

																						lowercase							=						f'A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'
																						lowercase							=						tokenizer_r.encode_plus(
																						    A__   ,return_attention_mask=A__   ,return_token_type_ids=A__   ,return_offsets_mapping=A__   ,add_special_tokens=A__   ,)

																						lowercase							=						tokenizer_r.do_lower_case if hasattr(A__   ,'''do_lower_case''') else False
																						lowercase							=						(
																						    [
																						        ((0, 0), tokenizer_r.cls_token),
																						        ((0, 1), '''A'''),
																						        ((1, 2), ''','''),
																						        ((3, 5), '''na'''),
																						        ((5, 6), '''##ï'''),
																						        ((6, 8), '''##ve'''),
																						        ((9, 1_5), tokenizer_r.mask_token),
																						        ((1_6, 2_1), '''Allen'''),
																						        ((2_1, 2_3), '''##NL'''),
																						        ((2_3, 2_4), '''##P'''),
																						        ((2_5, 3_3), '''sentence'''),
																						        ((3_3, 3_4), '''.'''),
																						        ((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, 1_5), tokenizer_r.mask_token),
																						        ((1_6, 2_1), '''allen'''),
																						        ((2_1, 2_3), '''##nl'''),
																						        ((2_3, 2_4), '''##p'''),
																						        ((2_5, 3_3), '''sentence'''),
																						        ((3_3, 3_4), '''.'''),
																						        ((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  A__      (				self):
												lowercase							=						['''的''', '''人''', '''有''']
												lowercase							=						''''''.join(A__)
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
																						lowercase							=						True
																						lowercase							=						self.tokenizer_class.from_pretrained(A__   ,**A__)
																						lowercase							=						self.rust_tokenizer_class.from_pretrained(A__   ,**A__)

																						lowercase							=						tokenizer_p.encode(A__   ,add_special_tokens=A__)
																						lowercase							=						tokenizer_r.encode(A__   ,add_special_tokens=A__)

																						lowercase							=						tokenizer_r.convert_ids_to_tokens(A__)
																						lowercase							=						tokenizer_p.convert_ids_to_tokens(A__)

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

																						lowercase							=						False
																						lowercase							=						self.rust_tokenizer_class.from_pretrained(A__   ,**A__)
																						lowercase							=						self.tokenizer_class.from_pretrained(A__   ,**A__)

																						lowercase							=						tokenizer_r.encode(A__   ,add_special_tokens=A__)
																						lowercase							=						tokenizer_p.encode(A__   ,add_special_tokens=A__)

																						lowercase							=						tokenizer_r.convert_ids_to_tokens(A__)
																						lowercase							=						tokenizer_p.convert_ids_to_tokens(A__)

																						# it is expected that only the first Chinese character is not preceded by "##".
																						lowercase							=						[
																						    f'##{token}' if idx != 0 else token for idx, token in enumerate(A__)
																						]
																						self.assertListEqual(A__   ,A__)
																						self.assertListEqual(A__   ,A__)




							@slow
							def  A__      (				self):
												lowercase							=						self.tokenizer_class(self.vocab_file   ,self.word_shape_file   ,self.word_pronunciation_file)

												lowercase							=						tokenizer.encode('''你好'''   ,add_special_tokens=A__)
												lowercase							=						tokenizer.encode('''你是谁'''   ,add_special_tokens=A__)

												lowercase							=						tokenizer.build_inputs_with_special_tokens(A__)
												lowercase							=						tokenizer.build_inputs_with_special_tokens(A__   ,A__)

												assert encoded_sentence == [1] + text + [2]
												assert encoded_pair == [1] + text + [2] + text_a + [2]





							def  A__      (				self):
												lowercase							=						self.get_tokenizers(do_lower_case=A__)
												for tokenizer in tokenizers:
																	with self.subTest(f'{tokenizer.__class__.__name__}'):
																						lowercase							=						'''你好，你是谁'''
																						lowercase							=						tokenizer.tokenize(A__)
																						lowercase							=						tokenizer.convert_tokens_to_ids(A__)
																						lowercase							=						tokenizer.convert_tokens_to_shape_ids(A__)
																						lowercase							=						tokenizer.convert_tokens_to_pronunciation_ids(A__)
																						lowercase							=						tokenizer.prepare_for_model(
																						    A__   ,A__   ,A__   ,add_special_tokens=A__)

																						lowercase							=						tokenizer.encode_plus(A__   ,add_special_tokens=A__)

																						self.assertEqual(A__   ,A__)




