


import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile

import pyarrow as pa
import pyarrow.parquet as pq
import pytest

import datasets
import datasets.config



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   )					->		Any:
				_lowercase :							Any   	=	10
				_lowercase :							Dict   	=	datasets.Features(
				    {
				        'tokens': datasets.Sequence(datasets.Value('string'				)				),
				        'labels': datasets.Sequence(datasets.ClassLabel(names=['negative', 'positive']				)				),
				        'answers': datasets.Sequence(
				            {
				                'text': datasets.Value('string'				),
				                'answer_start': datasets.Value('int32'				),
				            }				),
				        'id': datasets.Value('int64'				),
				    }				)
				_lowercase :							Tuple   	=	datasets.Dataset.from_dict(
				    {
				        'tokens': [['foo'] * 5] * n,
				        'labels': [[1] * 5] * n,
				        'answers': [{'answer_start': [97], 'text': ['1976']}] * 10,
				        'id': list(range(lowerCamelCase_				)				),
				    }							,				features=lowerCamelCase_							,				)
				return dataset



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Tuple:
				_lowercase :							List[str]   	=	str(tmp_path_factory.mktemp('data'				) / 'file.arrow'				)
				dataset.map(cache_file_name=lowerCamelCase_				)
				return filename


# FILE_CONTENT + files


SCREAMING_SNAKE_CASE :   Dict							      =				"\\n    Text data.\n    Second line of data."



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Union[str, Any]:
				_lowercase :							Optional[int]   	=	tmp_path_factory.mktemp('data'				) / 'file.txt'
				_lowercase :							int   	=	FILE_CONTENT
				with open(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_				)
				return filename



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		List[Any]:
				import bza

				_lowercase :							int   	=	tmp_path_factory.mktemp('data'				) / 'file.txt.bz2'
				_lowercase :							Tuple   	=	bytes(lowerCamelCase_							,				'utf-8'				)
				with bza.open(lowerCamelCase_							,				'wb'				) as f:
								f.write(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		int:
				import gzip

				_lowercase :							str   	=	str(tmp_path_factory.mktemp('data'				) / 'file.txt.gz'				)
				_lowercase :							str   	=	bytes(lowerCamelCase_							,				'utf-8'				)
				with gzip.open(lowerCamelCase_							,				'wb'				) as f:
								f.write(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Tuple:
				if datasets.config.LZ4_AVAILABLE:
								import lza.frame

								_lowercase :							Optional[int]   	=	tmp_path_factory.mktemp('data'				) / 'file.txt.lz4'
								_lowercase :							int   	=	bytes(lowerCamelCase_							,				'utf-8'				)
								with lza.frame.open(lowerCamelCase_							,				'wb'				) as f:
												f.write(lowerCamelCase_				)
								return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Tuple:
				if datasets.config.PY7ZR_AVAILABLE:
								import pyazr

								_lowercase :							str   	=	tmp_path_factory.mktemp('data'				) / 'file.txt.7z'
								with pyazr.SevenZipFile(lowerCamelCase_							,				'w'				) as archive:
												archive.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
								return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Union[str, Any]:
				import tarfile

				_lowercase :							List[Any]   	=	tmp_path_factory.mktemp('data'				) / 'file.txt.tar'
				with tarfile.TarFile(lowerCamelCase_							,				'w'				) as f:
								f.add(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Optional[int]:
				import lzma

				_lowercase :							Optional[Any]   	=	tmp_path_factory.mktemp('data'				) / 'file.txt.xz'
				_lowercase :							Tuple   	=	bytes(lowerCamelCase_							,				'utf-8'				)
				with lzma.open(lowerCamelCase_							,				'wb'				) as f:
								f.write(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Tuple:
				import zipfile

				_lowercase :							List[str]   	=	tmp_path_factory.mktemp('data'				) / 'file.txt.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Optional[Any]:
				if datasets.config.ZSTANDARD_AVAILABLE:
								import zstandard as zstd

								_lowercase :							str   	=	tmp_path_factory.mktemp('data'				) / 'file.txt.zst'
								_lowercase :							Dict   	=	bytes(lowerCamelCase_							,				'utf-8'				)
								with zstd.open(lowerCamelCase_							,				'wb'				) as f:
												f.write(lowerCamelCase_				)
								return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Tuple:
				_lowercase :							Dict   	=	tmp_path_factory.mktemp('data'				) / 'file.xml'
				_lowercase :							Dict   	=	textwrap.dedent(
				    '\\n    <?xml version="1.0" encoding="UTF-8" ?>\n    <tmx version="1.4">\n      <header segtype="sentence" srclang="ca" />\n      <body>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 1</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 1</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 2</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 2</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 3</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 3</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 4</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 4</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 5</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 5</seg></tuv>\n        </tu>\n      </body>\n    </tmx>'				)
				with open(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_				)
				return filename


SCREAMING_SNAKE_CASE :   List[Any]							      =				[
    {"col_1": "0", "col_2": 0, "col_3": 0.0},
    {"col_1": "1", "col_2": 1, "col_3": 1.0},
    {"col_1": "2", "col_2": 2, "col_3": 2.0},
    {"col_1": "3", "col_2": 3, "col_3": 3.0},
]
SCREAMING_SNAKE_CASE :   str							      =				[
    {"col_1": "4", "col_2": 4, "col_3": 4.0},
    {"col_1": "5", "col_2": 5, "col_3": 5.0},
]
SCREAMING_SNAKE_CASE :   List[Any]							      =				{
    "col_1": ["0", "1", "2", "3"],
    "col_2": [0, 1, 2, 3],
    "col_3": [0.0, 1.0, 2.0, 3.0],
}

SCREAMING_SNAKE_CASE :   str							      =				[
    {"col_3": 0.0, "col_1": "0", "col_2": 0},
    {"col_3": 1.0, "col_1": "1", "col_2": 1},
]

SCREAMING_SNAKE_CASE :   Tuple							      =				[
    {"col_1": "s0", "col_2": 0, "col_3": 0.0},
    {"col_1": "s1", "col_2": 1, "col_3": 1.0},
    {"col_1": "s2", "col_2": 2, "col_3": 2.0},
    {"col_1": "s3", "col_2": 3, "col_3": 3.0},
]



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   )					->		List[str]:
				return DATA_DICT_OF_LISTS



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		List[Any]:
				_lowercase :							int   	=	datasets.Dataset.from_dict(lowerCamelCase_				)
				_lowercase :							Optional[Any]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.arrow'				)
				dataset.map(cache_file_name=lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Any:
				_lowercase :							Union[str, Any]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.sqlite'				)
				with contextlib.closing(sqlitea.connect(lowerCamelCase_				)				) as con:
								_lowercase :							Any   	=	con.cursor()
								cur.execute('CREATE TABLE dataset(col_1 text, col_2 int, col_3 real)'				)
								for item in DATA:
												cur.execute('INSERT INTO dataset(col_1, col_2, col_3) VALUES (?, ?, ?)'							,				tuple(item.values()				)				)
								con.commit()
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Optional[int]:
				_lowercase :							List[str]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.csv'				)
				with open(lowerCamelCase_							,				'w'							,				newline=''				) as f:
								_lowercase :							Union[str, Any]   	=	csv.DictWriter(lowerCamelCase_							,				fieldnames=['col_1', 'col_2', 'col_3']				)
								writer.writeheader()
								for item in DATA:
												writer.writerow(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Optional[Any]:
				_lowercase :							Dict   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset2.csv'				)
				with open(lowerCamelCase_							,				'w'							,				newline=''				) as f:
								_lowercase :							Dict   	=	csv.DictWriter(lowerCamelCase_							,				fieldnames=['col_1', 'col_2', 'col_3']				)
								writer.writeheader()
								for item in DATA:
												writer.writerow(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Union[str, Any]:
				import bza

				_lowercase :							int   	=	tmp_path_factory.mktemp('data'				) / 'dataset.csv.bz2'
				with open(lowerCamelCase_							,				'rb'				) as f:
								_lowercase :							Union[str, Any]   	=	f.read()
				# data = bytes(FILE_CONTENT, "utf-8")
				with bza.open(lowerCamelCase_							,				'wb'				) as f:
								f.write(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		List[str]:
				_lowercase :							Dict   	=	tmp_path_factory.mktemp('data'				) / 'dataset.csv.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		List[Any]:
				_lowercase :							List[str]   	=	tmp_path_factory.mktemp('data'				) / 'dataset.csv.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.basename(csv_path.replace('.csv'							,				'.CSV'				)				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.basename(csva_path.replace('.csv'							,				'.CSV'				)				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		Optional[Any]:
				_lowercase :							List[str]   	=	tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.csv.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.join('main_dir'							,				os.path.basename(lowerCamelCase_				)				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.join('main_dir'							,				os.path.basename(lowerCamelCase_				)				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Union[str, Any]:
				_lowercase :							List[str]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.parquet'				)
				_lowercase :							Tuple   	=	pa.schema(
				    {
				        'col_1': pa.string(),
				        'col_2': pa.intaa(),
				        'col_3': pa.floataa(),
				    }				)
				with open(lowerCamelCase_							,				'wb'				) as f:
								_lowercase :							Tuple   	=	pq.ParquetWriter(lowerCamelCase_							,				schema=lowerCamelCase_				)
								_lowercase :							Tuple   	=	pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(lowerCamelCase_				)				)] for k in DATA[0]}							,				schema=lowerCamelCase_				)
								writer.write_table(lowerCamelCase_				)
								writer.close()
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Dict:
				_lowercase :							Optional[int]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.json'				)
				_lowercase :							Any   	=	{'data': DATA}
				with open(lowerCamelCase_							,				'w'				) as f:
								json.dump(lowerCamelCase_							,				lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Optional[Any]:
				_lowercase :							Optional[Any]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.json'				)
				_lowercase :							List[str]   	=	{'data': DATA_DICT_OF_LISTS}
				with open(lowerCamelCase_							,				'w'				) as f:
								json.dump(lowerCamelCase_							,				lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		str:
				_lowercase :							Tuple   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.jsonl'				)
				with open(lowerCamelCase_							,				'w'				) as f:
								for item in DATA:
												f.write(json.dumps(lowerCamelCase_				) + '\n'				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Any:
				_lowercase :							Dict   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset2.jsonl'				)
				with open(lowerCamelCase_							,				'w'				) as f:
								for item in DATA:
												f.write(json.dumps(lowerCamelCase_				) + '\n'				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		str:
				_lowercase :							Optional[int]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset_312.jsonl'				)
				with open(lowerCamelCase_							,				'w'				) as f:
								for item in DATA_312:
												f.write(json.dumps(lowerCamelCase_				) + '\n'				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		int:
				_lowercase :							int   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset-str.jsonl'				)
				with open(lowerCamelCase_							,				'w'				) as f:
								for item in DATA_STR:
												f.write(json.dumps(lowerCamelCase_				) + '\n'				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Any:
				import gzip

				_lowercase :							Optional[Any]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.txt.gz'				)
				with open(lowerCamelCase_							,				'rb'				) as orig_file:
								with gzip.open(lowerCamelCase_							,				'wb'				) as zipped_file:
												zipped_file.writelines(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Tuple:
				import gzip

				_lowercase :							Tuple   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.gz'				)
				with open(lowerCamelCase_							,				'rb'				) as orig_file:
								with gzip.open(lowerCamelCase_							,				'wb'				) as zipped_file:
												zipped_file.writelines(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		List[str]:
				_lowercase :							Any   	=	tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		Optional[Any]:
				_lowercase :							Optional[int]   	=	tmp_path_factory.mktemp('data'				) / 'dataset_nested.jsonl.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.join('nested'							,				os.path.basename(lowerCamelCase_				)				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		Optional[Any]:
				_lowercase :							Optional[int]   	=	tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.jsonl.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.join('main_dir'							,				os.path.basename(lowerCamelCase_				)				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.join('main_dir'							,				os.path.basename(lowerCamelCase_				)				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		List[Any]:
				_lowercase :							Optional[int]   	=	tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.tar'
				with tarfile.TarFile(lowerCamelCase_							,				'w'				) as f:
								f.add(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
								f.add(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		Union[str, Any]:
				_lowercase :							int   	=	tmp_path_factory.mktemp('data'				) / 'dataset_nested.jsonl.tar'
				with tarfile.TarFile(lowerCamelCase_							,				'w'				) as f:
								f.add(lowerCamelCase_							,				arcname=os.path.join('nested'							,				os.path.basename(lowerCamelCase_				)				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Tuple:
				_lowercase :							Union[str, Any]   	=	['0', '1', '2', '3']
				_lowercase :							List[str]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset.txt'				)
				with open(lowerCamelCase_							,				'w'				) as f:
								for item in data:
												f.write(item + '\n'				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Any:
				_lowercase :							Dict   	=	['0', '1', '2', '3']
				_lowercase :							Optional[Any]   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset2.txt'				)
				with open(lowerCamelCase_							,				'w'				) as f:
								for item in data:
												f.write(item + '\n'				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Tuple:
				_lowercase :							Optional[int]   	=	['0', '1', '2', '3']
				_lowercase :							str   	=	tmp_path_factory.mktemp('data'				) / 'dataset.abc'
				with open(lowerCamelCase_							,				'w'				) as f:
								for item in data:
												f.write(item + '\n'				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		Tuple:
				_lowercase :							List[Any]   	=	tmp_path_factory.mktemp('data'				) / 'dataset.text.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		List[Any]:
				_lowercase :							Dict   	=	tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.text.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.join('main_dir'							,				os.path.basename(lowerCamelCase_				)				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.join('main_dir'							,				os.path.basename(lowerCamelCase_				)				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		Optional[Any]:
				_lowercase :							str   	=	tmp_path_factory.mktemp('data'				) / 'dataset.ext.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.basename('unsupported.ext'				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.basename('unsupported_2.ext'				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		int:
				_lowercase :							Optional[Any]   	=	'\n'.join(['First', 'Second\u2029with Unicode new line', 'Third']				)
				_lowercase :							str   	=	str(tmp_path_factory.mktemp('data'				) / 'dataset_with_unicode_new_lines.txt'				)
				with open(lowerCamelCase_							,				'w'							,				encoding='utf-8'				) as f:
								f.write(lowerCamelCase_				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   )					->		Dict:
				return os.path.join('tests'							,				'features'							,				'data'							,				'test_image_rgb.jpg'				)



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   )					->		str:
				return os.path.join('tests'							,				'features'							,				'data'							,				'test_audio_44100.wav'				)



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Any:
				_lowercase :							Any   	=	tmp_path_factory.mktemp('data'				) / 'dataset.img.zip'
				with zipfile.ZipFile(lowerCamelCase_							,				'w'				) as f:
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				)				)
								f.write(lowerCamelCase_							,				arcname=os.path.basename(lowerCamelCase_				).replace('.jpg'							,				'2.jpg'				)				)
				return path



@pytest.fixture(scope='session'				)
def        UpperCamelCase_(   lowerCamelCase_				)					->		Any:
				_lowercase :							Any   	=	tmp_path_factory.mktemp('data_dir'				)

				(data_dir / "subdir").mkdir()
				with open(data_dir / 'subdir' / 'train.txt'							,				'w'				) as f:
								f.write('foo\n' * 10				)
				with open(data_dir / 'subdir' / 'test.txt'							,				'w'				) as f:
								f.write('bar\n' * 10				)
				# hidden file
				with open(data_dir / 'subdir' / '.test.txt'							,				'w'				) as f:
								f.write('bar\n' * 10				)

				# hidden directory
				(data_dir / ".subdir").mkdir()
				with open(data_dir / '.subdir' / 'train.txt'							,				'w'				) as f:
								f.write('foo\n' * 10				)
				with open(data_dir / '.subdir' / 'test.txt'							,				'w'				) as f:
								f.write('bar\n' * 10				)

				return data_dir






from jiwer import compute_measures

import datasets


SCREAMING_SNAKE_CASE :   Tuple							      =				"\\n@inproceedings{inproceedings,\n    author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n    year = {2004},\n    month = {01},\n    pages = {},\n    title = {From WER and RIL to MER and WIL: improved evaluation measures for connected speech recognition.}\n}\n"

SCREAMING_SNAKE_CASE :   Optional[Any]							      =				"\\nWord error rate (WER) is a common metric of the performance of an automatic speech recognition system.\n\nThe general difficulty of measuring performance lies in the fact that the recognized word sequence can have a different length from the reference word sequence (supposedly the correct one). The WER is derived from the Levenshtein distance, working at the word level instead of the phoneme level. The WER is a valuable tool for comparing different systems as well as for evaluating improvements within one system. This kind of measurement, however, provides no details on the nature of translation errors and further work is therefore required to identify the main source(s) of error and to focus any research effort.\n\nThis problem is solved by first aligning the recognized word sequence with the reference (spoken) word sequence using dynamic string alignment. Examination of this issue is seen through a theory called the power law that states the correlation between perplexity and word error rate.\n\nWord error rate can then be computed as:\n\nWER = (S + D + I) / N = (S + D + I) / (S + D + C)\n\nwhere\n\nS is the number of substitutions,\nD is the number of deletions,\nI is the number of insertions,\nC is the number of correct words,\nN is the number of words in the reference (N=S+D+C).\n\nThis value indicates the average number of errors per reference word. The lower the value, the better the\nperformance of the ASR system with a WER of 0 being a perfect score.\n"

SCREAMING_SNAKE_CASE :   Any							      =				"\nCompute WER score of transcribed segments against references.\n\nArgs:\n    references: List of references for each speech input.\n    predictions: List of transcriptions to score.\n    concatenate_texts (bool, default=False): Whether to concatenate all input texts or compute WER iteratively.\n\nReturns:\n    (float): the word error rate\n\nExamples:\n\n    >>> predictions = [\"this is the prediction\", \"there is an other sample\"]\n    >>> references = [\"this is the reference\", \"there is another one\"]\n    >>> wer = datasets.load_metric(\"wer\")\n    >>> wer_score = wer.compute(predictions=predictions, references=references)\n    >>> print(wer_score)\n    0.5\n"






@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION,				_KWARGS_DESCRIPTION     )
class _lowerCamelCase(		datasets.Metric     ):
       def     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           return datasets.MetricInfo(
               description=_DESCRIPTION,   citation=_CITATION,   inputs_description=_KWARGS_DESCRIPTION,   features=datasets.Features(
                   {
                       'predictions': datasets.Value('string',   id='sequence'),
                       'references': datasets.Value('string',   id='sequence'),
                   }),   codebase_urls=['https://github.com/jitsi/jiwer/'],   reference_urls=[
                   'https://en.wikipedia.org/wiki/Word_error_rate',
               ],   )




       def     UpperCamelCase  (      self,   lowerCamelCase=None,   lowerCamelCase=None,   lowerCamelCase=False) ->     Optional[Any]:




           """simple docstring"""

           if concatenate_texts:
               return compute_measures(lowerCamelCase,   lowerCamelCase)["wer"]
           else:
               _lowercase :							Dict   	=	0
               _lowercase :							Optional[int]   	=	0
               for prediction, reference in zip(lowerCamelCase,   lowerCamelCase):
                   _lowercase :							List[Any]   	=	compute_measures(lowerCamelCase,   lowerCamelCase)
                   incorrect += measures["substitutions"] + measures["deletions"] + measures["insertions"]
                   total += measures["substitutions"] + measures["deletions"] + measures["hits"]
               return incorrect / total


