






"""simple docstring"""



from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef

import datasets


__A		:       List[Any]  				=		'''\
@inproceedings{wang2019glue,
  title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
  author={Wang, Alex and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R.},
  note={In the Proceedings of ICLR.},
  year={2019}
}
'''

__A		:       List[str]  				=		'''\
GLUE, the General Language Understanding Evaluation benchmark
(https://gluebenchmark.com/) is a collection of resources for training,
evaluating, and analyzing natural language understanding systems.
'''

__A		:       Any  				=		'''
Compute GLUE evaluation metric associated to each GLUE dataset.
Args:
    predictions: list of predictions to score.
        Each translation should be tokenized into a list of tokens.
    references: list of lists of references for each translation.
        Each reference should be tokenized into a list of tokens.
Returns: depending on the GLUE subset, one or several of:
    "accuracy": Accuracy
    "f1": F1 score
    "pearson": Pearson Correlation
    "spearmanr": Spearman Correlation
    "matthews_correlation": Matthew Correlation
Examples:

    >>> glue_metric = datasets.load_metric(\'glue\', \'sst2\')  # \'sst2\' or any of ["mnli", "mnli_mismatched", "mnli_matched", "qnli", "rte", "wnli", "hans"]
    >>> references = [0, 1]
    >>> predictions = [0, 1]
    >>> results = glue_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'accuracy\': 1.0}

    >>> glue_metric = datasets.load_metric(\'glue\', \'mrpc\')  # \'mrpc\' or \'qqp\'
    >>> references = [0, 1]
    >>> predictions = [0, 1]
    >>> results = glue_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'accuracy\': 1.0, \'f1\': 1.0}

    >>> glue_metric = datasets.load_metric(\'glue\', \'stsb\')
    >>> references = [0., 1., 2., 3., 4., 5.]
    >>> predictions = [0., 1., 2., 3., 4., 5.]
    >>> results = glue_metric.compute(predictions=predictions, references=references)
    >>> print({"pearson": round(results["pearson"], 2), "spearmanr": round(results["spearmanr"], 2)})
    {\'pearson\': 1.0, \'spearmanr\': 1.0}

    >>> glue_metric = datasets.load_metric(\'glue\', \'cola\')
    >>> references = [0, 1]
    >>> predictions = [0, 1]
    >>> results = glue_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'matthews_correlation\': 1.0}
'''



def 						lowercase    (				__snake_case				: int		,					__snake_case				: Optional[Any]	):
		return float((preds == labels).mean()	)



def 						lowercase    (				__snake_case				: Dict		,					__snake_case				: List[str]	):
		lowercase_ : Union[str, Any]							       =   simple_accuracy(__snake_case		,					__snake_case	)
		lowercase_ : Union[str, Any]							       =   float(fa_score(y_true=__snake_case		,					y_pred=__snake_case	)	)
		return {
		    "accuracy": acc,
		    "f1": fa,
		}



def 						lowercase    (				__snake_case				: List[Any]		,					__snake_case				: List[str]	):
		lowercase_ : Any							       =   float(pearsonr(__snake_case		,					__snake_case	)[0]	)
		lowercase_ : Union[str, Any]							       =   float(spearmanr(__snake_case		,					__snake_case	)[0]	)
		return {
		    "pearson": pearson_corr,
		    "spearmanr": spearman_corr,
		}






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




					def   A  (				self     :						Dict   )  ->  List[Any]:
							if self.config_name not in [
							    "sst2",
							    "mnli",
							    "mnli_mismatched",
							    "mnli_matched",
							    "cola",
							    "stsb",
							    "mrpc",
							    "qqp",
							    "qnli",
							    "rte",
							    "wnli",
							    "hans",
							]:
									raise KeyError(
									    '''You should supply a configuration name selected in '''
									    '''["sst2", "mnli", "mnli_mismatched", "mnli_matched", '''
									    '''"cola", "stsb", "mrpc", "qqp", "qnli", "rte", "wnli", "hans"]'''   )
							return datasets.MetricInfo(
							    description=_DESCRIPTION    ,						citation=_CITATION    ,						inputs_description=_KWARGS_DESCRIPTION    ,						features=datasets.Features(
							        {
							            '''predictions''': datasets.Value('''int64''' if self.config_name != '''stsb''' else '''float32'''   ),
							            '''references''': datasets.Value('''int64''' if self.config_name != '''stsb''' else '''float32'''   ),
							        }   )    ,						codebase_urls=[]    ,						reference_urls=[]    ,						format='''numpy'''    ,						)






					def   A  (				self     :						Union[str, Any]    ,						A     :						str    ,						A     :						int   )  ->  int:
							if self.config_name == "cola":
									return {"matthews_correlation": matthews_corrcoef(A    ,						A   )}
							elif self.config_name == "stsb":
									return pearson_and_spearman(A    ,						A   )
							elif self.config_name in ["mrpc", "qqp"]:
									return acc_and_fa(A    ,						A   )
							elif self.config_name in ["sst2", "mnli", "mnli_mismatched", "mnli_matched", "qnli", "rte", "wnli", "hans"]:
									return {"accuracy": simple_accuracy(A    ,						A   )}
							else:
									raise KeyError(
									    '''You should supply a configuration name selected in '''
									    '''["sst2", "mnli", "mnli_mismatched", "mnli_matched", '''
									    '''"cola", "stsb", "mrpc", "qqp", "qnli", "rte", "wnli", "hans"]'''   )





import os
import zipfile

import pytest

from datasets.utils.extract import (
    BzipaExtractor,
    Extractor,
    GzipExtractor,
    LzaExtractor,
    SevenZipExtractor,
    TarExtractor,
    XzExtractor,
    ZipExtractor,
    ZstdExtractor,
)

from .utils import require_lza, require_pyazr, require_zstandard







@pytest.mark.parametrize(
    """compression_format, is_archive"""					,	[
        ("""7z""", True),
        ("""bz2""", False),
        ("""gzip""", False),
        ("""lz4""", False),
        ("""tar""", True),
        ("""xz""", False),
        ("""zip""", True),
        ("""zstd""", False),
    ]					,	)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	) ->    Any:
       lowercase							:     Dict       	=      {
           """7z""": (seven_zip_file, SevenZipExtractor),
           """bz2""": (bza_file, BzipaExtractor),
           """gzip""": (gz_file, GzipExtractor),
           """lz4""": (lza_file, LzaExtractor),
           """tar""": (tar_file, TarExtractor),
           """xz""": (xz_file, XzExtractor),
           """zip""": (zip_file, ZipExtractor),
           """zstd""": (zstd_file, ZstdExtractor),
       }
       lowercase	,			lowercase							:     Optional[Any]       	=      input_paths_and_base_extractors[compression_format]
       if input_path is None:
              lowercase							:     Dict       	=      f"for '{compression_format}' compression_format, "
              if compression_format == "7z":
                     reason += require_pyazr.kwargs["reason"]
              elif compression_format == "lz4":
                     reason += require_lza.kwargs["reason"]
              elif compression_format == "zstd":
                     reason += require_zstandard.kwargs["reason"]
              pytest.skip(SCREAMING_SNAKE_CASE__				)
       assert base_extractor.is_extractable(SCREAMING_SNAKE_CASE__				)
       lowercase							:     Any       	=      tmp_path / ("""extracted""" if is_archive else """extracted.txt""")
       base_extractor.extract(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
       if is_archive:
              assert output_path.is_dir()
              for file_path in output_path.iterdir():
                     assert file_path.name == text_file.name
                     lowercase							:     str       	=      file_path.read_text(encoding="""utf-8"""				)
       else:
              lowercase							:     Optional[Any]       	=      output_path.read_text(encoding="""utf-8"""				)
       lowercase							:     Tuple       	=      text_file.read_text(encoding="""utf-8"""				)
       assert extracted_file_content == expected_file_content







@pytest.mark.parametrize(
    """compression_format, is_archive"""					,	[
        ("""7z""", True),
        ("""bz2""", False),
        ("""gzip""", False),
        ("""lz4""", False),
        ("""tar""", True),
        ("""xz""", False),
        ("""zip""", True),
        ("""zstd""", False),
    ]					,	)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	) ->    Dict:
       lowercase							:     str       	=      {
           """7z""": seven_zip_file,
           """bz2""": bza_file,
           """gzip""": gz_file,
           """lz4""": lza_file,
           """tar""": tar_file,
           """xz""": xz_file,
           """zip""": zip_file,
           """zstd""": zstd_file,
       }
       lowercase							:     Optional[Any]       	=      input_paths[compression_format]
       if input_path is None:
              lowercase							:     int       	=      f"for '{compression_format}' compression_format, "
              if compression_format == "7z":
                     reason += require_pyazr.kwargs["reason"]
              elif compression_format == "lz4":
                     reason += require_lza.kwargs["reason"]
              elif compression_format == "zstd":
                     reason += require_zstandard.kwargs["reason"]
              pytest.skip(SCREAMING_SNAKE_CASE__				)
       lowercase							:     Union[str, Any]       	=      Extractor.infer_extractor_format(SCREAMING_SNAKE_CASE__				)
       assert extractor_format is not None
       lowercase							:     Any       	=      tmp_path / ("""extracted""" if is_archive else """extracted.txt""")
       Extractor.extract(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
       if is_archive:
              assert output_path.is_dir()
              for file_path in output_path.iterdir():
                     assert file_path.name == text_file.name
                     lowercase							:     Dict       	=      file_path.read_text(encoding="""utf-8"""				)
       else:
              lowercase							:     int       	=      output_path.read_text(encoding="""utf-8"""				)
       lowercase							:     Optional[Any]       	=      text_file.read_text(encoding="""utf-8"""				)
       assert extracted_file_content == expected_file_content







@pytest.fixture
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Dict:
       import tarfile

       lowercase							:     Tuple       	=      tmp_path / """data_dot_dot"""
       directory.mkdir()
       lowercase							:     str       	=      directory / """tar_file_with_dot_dot.tar"""
       with tarfile.TarFile(SCREAMING_SNAKE_CASE__					,	"""w"""				) as f:
              f.add(SCREAMING_SNAKE_CASE__					,	arcname=os.path.join(""".."""					,	text_file.name				)				)
       return path







@pytest.fixture
def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    List[str]:
       import tarfile

       lowercase							:     Tuple       	=      tmp_path / """data_sym_link"""
       directory.mkdir()
       lowercase							:     int       	=      directory / """tar_file_with_sym_link.tar"""
       os.symlink(""".."""					,	directory / """subdir"""					,	target_is_directory=SCREAMING_SNAKE_CASE__				)
       with tarfile.TarFile(SCREAMING_SNAKE_CASE__					,	"""w"""				) as f:
              f.add(str(directory / """subdir"""				)					,	arcname="""subdir"""				)  # str required by os.readlink on Windows and Python < 3.8
       return path







@pytest.mark.parametrize(
    """insecure_tar_file, error_log"""					,	[("""tar_file_with_dot_dot""", """illegal path"""), ("""tar_file_with_sym_link""", """Symlink""")]					,	)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Optional[Any]:
       lowercase							:     List[Any]       	=      {
           """tar_file_with_dot_dot""": tar_file_with_dot_dot,
           """tar_file_with_sym_link""": tar_file_with_sym_link,
       }
       lowercase							:     Optional[int]       	=      insecure_tar_files[insecure_tar_file]
       lowercase							:     List[str]       	=      tmp_path / """extracted"""
       TarExtractor.extract(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
       assert caplog.text
       for record in caplog.records:
              assert record.levelname == "ERROR"
              assert error_log in record.msg







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    Optional[int]:
       # We should have less false positives than zipfile.is_zipfile
       # We do that by checking only the magic number
       lowercase							:     Any       	=      tmpdir / """not_a_zip_file"""
       # From: https://github.com/python/cpython/pull/5053
       lowercase							:     str       	=      (
           B"""\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00"""
           B"""\x00\x02\x08\x06\x00\x00\x00\x99\x81\xb6'\x00\x00\x00\x15I"""
           B"""DATx\x01\x01\n\x00\xf5\xff\x00PK\x05\x06\x00PK\x06\x06\x07"""
           B"""\xac\x01N\xc6|a\r\x00\x00\x00\x00IEND\xaeB`\x82"""
       )
       with not_a_zip_file.open("""wb"""				) as f:
              f.write(SCREAMING_SNAKE_CASE__				)
       assert zipfile.is_zipfile(str(SCREAMING_SNAKE_CASE__				)				)  # is a false positive for `zipfile`
       assert not ZipExtractor.is_extractable(SCREAMING_SNAKE_CASE__				)  # but we're right
