




"""simple docstring"""



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   _SCREAMING_SNAKE_CASE       (							)						->		str:
    A__	=    10
    A__	=    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"						),
        }						)
    A__	=    datasets.Dataset.from_dict(
        {
            "tokens": [["foo"] * 5] * n,
            "labels": [[1] * 5] * n,
            "answers": [{"answer_start": [97], "text": ["1976"]}] * 10,
            "id": list(range(_UpperCAmelCase						)						),
        }      ,			features=_UpperCAmelCase      ,			)
    return dataset







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_						)						->		List[Any]:
    A__	=    str(tmp_path_factory.mktemp("data"						) / "file.arrow"						)
    dataset.map(cache_file_name=_UpperCAmelCase						)
    return filename


# FILE_CONTENT + files


SCREAMING_SNAKE_CASE    =	'''\
    Text data.
    Second line of data.'''







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Union[str, Any]:
    A__	=    tmp_path_factory.mktemp("data"						) / 'file.txt'
    A__	=    FILE_CONTENT
    with open(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase						)
    return filename







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Tuple:
    import bza

    A__	=    tmp_path_factory.mktemp("data"						) / 'file.txt.bz2'
    A__	=    bytes(_UpperCAmelCase      ,			"utf-8"						)
    with bza.open(_UpperCAmelCase      ,			"wb"						) as f:
        f.write(_UpperCAmelCase						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		str:
    import gzip

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







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		str:
    if datasets.config.LZ4_AVAILABLE:
        import lza.frame

        A__	=    tmp_path_factory.mktemp("data"						) / 'file.txt.lz4'
        A__	=    bytes(_UpperCAmelCase      ,			"utf-8"						)
        with lza.frame.open(_UpperCAmelCase      ,			"wb"						) as f:
            f.write(_UpperCAmelCase						)
        return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_						)						->		Optional[Any]:
    if datasets.config.PY7ZR_AVAILABLE:
        import pyazr

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







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_						)						->		str:
    import tarfile

    A__	=    tmp_path_factory.mktemp("data"						) / 'file.txt.tar'
    with tarfile.TarFile(_UpperCAmelCase      ,			"w"						) as f:
        f.add(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		str:
    import lzma

    A__	=    tmp_path_factory.mktemp("data"						) / 'file.txt.xz'
    A__	=    bytes(_UpperCAmelCase      ,			"utf-8"						)
    with lzma.open(_UpperCAmelCase      ,			"wb"						) as f:
        f.write(_UpperCAmelCase						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_						)						->		Dict:
    import zipfile

    A__	=    tmp_path_factory.mktemp("data"						) / 'file.txt.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Any:
    if datasets.config.ZSTANDARD_AVAILABLE:
        import zstandard as zstd

        A__	=    tmp_path_factory.mktemp("data"						) / 'file.txt.zst'
        A__	=    bytes(_UpperCAmelCase      ,			"utf-8"						)
        with zstd.open(_UpperCAmelCase      ,			"wb"						) as f:
            f.write(_UpperCAmelCase						)
        return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Optional[int]:
    A__	=    tmp_path_factory.mktemp("data"						) / 'file.xml'
    A__	=    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(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase						)
    return filename


SCREAMING_SNAKE_CASE    =	[
    {'''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    =	[
    {'''col_1''': '''4''', '''col_2''': 4, '''col_3''': 4.0},
    {'''col_1''': '''5''', '''col_2''': 5, '''col_3''': 5.0},
]
SCREAMING_SNAKE_CASE    =	{
    '''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    =	[
    {'''col_3''': 0.0, '''col_1''': '''0''', '''col_2''': 0},
    {'''col_3''': 1.0, '''col_1''': '''1''', '''col_2''': 1},
]

SCREAMING_SNAKE_CASE    =	[
    {'''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   _SCREAMING_SNAKE_CASE       (							)						->		List[Any]:
    return DATA_DICT_OF_LISTS







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Any:
    A__	=    datasets.Dataset.from_dict(_UpperCAmelCase						)
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset.arrow"						)
    dataset.map(cache_file_name=_UpperCAmelCase						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Optional[Any]:
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset.sqlite"						)
    with contextlib.closing(sqlitea.connect(_UpperCAmelCase						)						) as con:
        A__	=    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   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Optional[int]:
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset.csv"						)
    with open(_UpperCAmelCase      ,			"w"      ,			newline=""						) as f:
        A__	=    csv.DictWriter(_UpperCAmelCase      ,			fieldnames=["col_1", "col_2", "col_3"]						)
        writer.writeheader()
        for item in DATA:
            writer.writerow(_UpperCAmelCase						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Tuple:
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset2.csv"						)
    with open(_UpperCAmelCase      ,			"w"      ,			newline=""						) as f:
        A__	=    csv.DictWriter(_UpperCAmelCase      ,			fieldnames=["col_1", "col_2", "col_3"]						)
        writer.writeheader()
        for item in DATA:
            writer.writerow(_UpperCAmelCase						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_						)						->		Optional[int]:
    import bza

    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset.csv.bz2'
    with open(_UpperCAmelCase      ,			"rb"						) as f:
        A__	=    f.read()
    # data = bytes(FILE_CONTENT, "utf-8")
    with bza.open(_UpperCAmelCase      ,			"wb"						) as f:
        f.write(_UpperCAmelCase						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_						)						->		Any:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset.csv.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_						)						->		Optional[int]:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset.csv.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(csv_path.replace(".csv"      ,			".CSV"						)						)						)
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(csva_path.replace(".csv"      ,			".CSV"						)						)						)
    return path







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







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







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		str:
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset.json"						)
    A__	=    {'data': DATA}
    with open(_UpperCAmelCase      ,			"w"						) as f:
        json.dump(_UpperCAmelCase      ,			_UpperCAmelCase						)
    return path







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







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Dict:
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset.jsonl"						)
    with open(_UpperCAmelCase      ,			"w"						) as f:
        for item in DATA:
            f.write(json.dumps(_UpperCAmelCase						) + "\n"						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Tuple:
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset2.jsonl"						)
    with open(_UpperCAmelCase      ,			"w"						) as f:
        for item in DATA:
            f.write(json.dumps(_UpperCAmelCase						) + "\n"						)
    return path







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







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		List[str]:
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset-str.jsonl"						)
    with open(_UpperCAmelCase      ,			"w"						) as f:
        for item in DATA_STR:
            f.write(json.dumps(_UpperCAmelCase						) + "\n"						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_						)						->		str:
    import gzip

    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset.txt.gz"						)
    with open(_UpperCAmelCase      ,			"rb"						) as orig_file:
        with gzip.open(_UpperCAmelCase      ,			"wb"						) as zipped_file:
            zipped_file.writelines(_UpperCAmelCase						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_						)						->		Optional[int]:
    import gzip

    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset.jsonl.gz"						)
    with open(_UpperCAmelCase      ,			"rb"						) as orig_file:
        with gzip.open(_UpperCAmelCase      ,			"wb"						) as zipped_file:
            zipped_file.writelines(_UpperCAmelCase						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_						)						->		Union[str, Any]:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset.jsonl.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_      ,			lowercase_						)						->		Tuple:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset_nested.jsonl.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.join("nested"      ,			os.path.basename(_UpperCAmelCase						)						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_						)						->		Union[str, Any]:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset_with_dir.jsonl.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.join("main_dir"      ,			os.path.basename(_UpperCAmelCase						)						)						)
        f.write(_UpperCAmelCase      ,			arcname=os.path.join("main_dir"      ,			os.path.basename(_UpperCAmelCase						)						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_						)						->		int:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset.jsonl.tar'
    with tarfile.TarFile(_UpperCAmelCase      ,			"w"						) as f:
        f.add(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
        f.add(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_      ,			lowercase_						)						->		Dict:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset_nested.jsonl.tar'
    with tarfile.TarFile(_UpperCAmelCase      ,			"w"						) as f:
        f.add(_UpperCAmelCase      ,			arcname=os.path.join("nested"      ,			os.path.basename(_UpperCAmelCase						)						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		int:
    A__	=    ['0', '1', '2', '3']
    A__	=    str(tmp_path_factory.mktemp("data"						) / "dataset.txt"						)
    with open(_UpperCAmelCase      ,			"w"						) as f:
        for item in data:
            f.write(item + "\n"						)
    return path







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







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







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_						)						->		Tuple:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset.text.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_						)						->		Optional[int]:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset_with_dir.text.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.join("main_dir"      ,			os.path.basename(_UpperCAmelCase						)						)						)
        f.write(_UpperCAmelCase      ,			arcname=os.path.join("main_dir"      ,			os.path.basename(_UpperCAmelCase						)						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_						)						->		List[str]:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset.ext.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename("unsupported.ext"						)						)
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename("unsupported_2.ext"						)						)
    return path







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







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							)						->		List[str]:
    return os.path.join("tests"      ,			"features"      ,			"data"      ,			"test_image_rgb.jpg"						)







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							)						->		int:
    return os.path.join("tests"      ,			"features"      ,			"data"      ,			"test_audio_44100.wav"						)







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_						)						->		Dict:
    A__	=    tmp_path_factory.mktemp("data"						) / 'dataset.img.zip'
    with zipfile.ZipFile(_UpperCAmelCase      ,			"w"						) as f:
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						)						)
        f.write(_UpperCAmelCase      ,			arcname=os.path.basename(_UpperCAmelCase						).replace(".jpg"      ,			"2.jpg"						)						)
    return path







@pytest.fixture(scope="session"						)
def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Optional[Any]:
    A__	=    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











"""simple docstring"""



import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding




class      UpperCAmelCase_  (						A_							):
    lowercase__						 =				['''image_processor''', '''tokenizer''']
    lowercase__						 =				'''ViTImageProcessor'''
    lowercase__						 =				('''CLIPTokenizer''', '''CLIPTokenizerFast''')




    def __init__(   self						:	Optional[Any]     ,			snake_case_						:	Union[str, Any]=None     ,			snake_case_						:	Dict=None     ,			**snake_case_						:	Optional[Any]				)				->							List[str]:




     '''simple docstring'''

     A__	=    None
     if "feature_extractor" in kwargs:
      warnings.warn(
          "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
          " instead."     ,			snake_case_     ,			)
      A__	=    kwargs.pop("feature_extractor"				)

     A__	=    image_processor if image_processor is not None else feature_extractor
     if image_processor is None:
      raise ValueError("You need to specify an `image_processor`."				)
     if tokenizer is None:
      raise ValueError("You need to specify a `tokenizer`."				)

     super().__init__(snake_case_     ,			snake_case_				)




    def __call__(   self						:	int     ,			snake_case_						:	Union[str, Any]=None     ,			snake_case_						:	int=None     ,			snake_case_						:	Dict=None     ,			snake_case_						:	int=None     ,			**snake_case_						:	List[str]				)				->							Union[str, Any]:




     '''simple docstring'''

     if text is None and visual_prompt is None and images is None:
      raise ValueError("You have to specify either text, visual prompt or images."				)

     if text is not None and visual_prompt is not None:
      raise ValueError("You have to specify exactly one type of prompt. Either text or visual prompt."				)

     if text is not None:
      A__	=    self.tokenizer(snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)

     if visual_prompt is not None:
      A__	=    self.image_processor(snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)

     if images is not None:
      A__	=    self.image_processor(snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)

     if visual_prompt is not None and images is not None:
      A__	=    {
          "pixel_values": image_features.pixel_values,
          "conditional_pixel_values": prompt_features.pixel_values,
      }
      return encoding
     elif text is not None and images is not None:
      A__	=    image_features.pixel_values
      return encoding
     elif text is not None:
      return encoding
     elif visual_prompt is not None:
      A__	=    {
          "conditional_pixel_values": prompt_features.pixel_values,
      }
      return encoding
     else:
      return BatchEncoding(data=dict(**snake_case_				)     ,			tensor_type=snake_case_				)




    def 							__magic_name__							(   self						:	Tuple     ,			*snake_case_						:	List[str]     ,			**snake_case_						:	Optional[int]				)				->							str:




     '''simple docstring'''

     return self.tokenizer.batch_decode(*snake_case_     ,			**snake_case_				)




    def 							__magic_name__							(   self						:	Optional[Any]     ,			*snake_case_						:	Any     ,			**snake_case_						:	List[Any]				)				->							List[str]:




     '''simple docstring'''

     return self.tokenizer.decode(*snake_case_     ,			**snake_case_				)




    @property
    def 							__magic_name__							(   self						:	int				)				->							Optional[int]:




     '''simple docstring'''

     warnings.warn(
         "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."     ,			snake_case_     ,			)
     return self.image_processor_class




    @property
    def 							__magic_name__							(   self						:	int				)				->							int:




     '''simple docstring'''

     warnings.warn(
         "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."     ,			snake_case_     ,			)
     return self.image_processor





