
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					(    ):
       snake_case       :   int							=      10
       snake_case       :   Any							=      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"    ),
           }    )
       snake_case       :   Optional[int]							=      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     : int				,					__lowerCamelCase     : List[str]    ):
       snake_case       :   List[Any]							=      str(tmp_path_factory.mktemp("data"    ) / "file.arrow"    )
       dataset.map(cache_file_name=__lowerCamelCase    )
       return filename


# FILE_CONTENT + files


__lowerCamelCase							=       """\
    Text data.
    Second line of data."""


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : Any    ):
       snake_case       :   Any							=      tmp_path_factory.mktemp("data"    ) / "file.txt"
       snake_case       :   Union[str, Any]							=      FILE_CONTENT
       with open(__lowerCamelCase				,					"w"    ) as f:
              f.write(__lowerCamelCase    )
       return filename


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : Dict    ):
       import bza

       snake_case       :   Tuple							=      tmp_path_factory.mktemp("data"    ) / "file.txt.bz2"
       snake_case       :   List[Any]							=      bytes(__lowerCamelCase				,					"utf-8"    )
       with bza.open(__lowerCamelCase				,					"wb"    ) as f:
              f.write(__lowerCamelCase    )
       return path


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : Tuple    ):
       import gzip

       snake_case       :   Union[str, Any]							=      str(tmp_path_factory.mktemp("data"    ) / "file.txt.gz"    )
       snake_case       :   Any							=      bytes(__lowerCamelCase				,					"utf-8"    )
       with gzip.open(__lowerCamelCase				,					"wb"    ) as f:
              f.write(__lowerCamelCase    )
       return path


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : Union[str, Any]    ):
       if datasets.config.LZ4_AVAILABLE:
              import lza.frame

              snake_case       :   List[Any]							=      tmp_path_factory.mktemp("data"    ) / "file.txt.lz4"
              snake_case       :   Optional[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     : Union[str, Any]				,					__lowerCamelCase     : List[str]    ):
       if datasets.config.PY7ZR_AVAILABLE:
              import pyazr

              snake_case       :   Dict							=      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     : int				,					__lowerCamelCase     : Union[str, Any]    ):
       import tarfile

       snake_case       :   Optional[int]							=      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     : Any    ):
       import lzma

       snake_case       :   Optional[int]							=      tmp_path_factory.mktemp("data"    ) / "file.txt.xz"
       snake_case       :   int							=      bytes(__lowerCamelCase				,					"utf-8"    )
       with lzma.open(__lowerCamelCase				,					"wb"    ) as f:
              f.write(__lowerCamelCase    )
       return path


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : List[Any]				,					__lowerCamelCase     : Any    ):
       import zipfile

       snake_case       :   List[Any]							=      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     : Union[str, Any]    ):
       if datasets.config.ZSTANDARD_AVAILABLE:
              import zstandard as zstd

              snake_case       :   Optional[int]							=      tmp_path_factory.mktemp("data"    ) / "file.txt.zst"
              snake_case       :   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    ):
       snake_case       :   Optional[Any]							=      tmp_path_factory.mktemp("data"    ) / "file.xml"
       snake_case       :   str							=      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


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

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

__lowerCamelCase							=       [
    {"""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					(    ):
       return DATA_DICT_OF_LISTS


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : Union[str, Any]    ):
       snake_case       :   str							=      datasets.Dataset.from_dict(__lowerCamelCase    )
       snake_case       :   Optional[int]							=      str(tmp_path_factory.mktemp("data"    ) / "dataset.arrow"    )
       dataset.map(cache_file_name=__lowerCamelCase    )
       return path


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : Tuple    ):
       snake_case       :   int							=      str(tmp_path_factory.mktemp("data"    ) / "dataset.sqlite"    )
       with contextlib.closing(sqlitea.connect(__lowerCamelCase    )    ) as con:
              snake_case       :   Optional[int]							=      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     : List[str]    ):
       snake_case       :   Union[str, Any]							=      str(tmp_path_factory.mktemp("data"    ) / "dataset.csv"    )
       with open(__lowerCamelCase				,					"w"				,					newline=""    ) as f:
              snake_case       :   str							=      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     : Dict    ):
       snake_case       :   Any							=      str(tmp_path_factory.mktemp("data"    ) / "dataset2.csv"    )
       with open(__lowerCamelCase				,					"w"				,					newline=""    ) as f:
              snake_case       :   Optional[int]							=      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[int]				,					__lowerCamelCase     : List[str]    ):
       import bza

       snake_case       :   Optional[Any]							=      tmp_path_factory.mktemp("data"    ) / "dataset.csv.bz2"
       with open(__lowerCamelCase				,					"rb"    ) as f:
              snake_case       :   str							=      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     : str				,					__lowerCamelCase     : Tuple				,					__lowerCamelCase     : Dict    ):
       snake_case       :   Union[str, Any]							=      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     : Union[str, Any]				,					__lowerCamelCase     : int				,					__lowerCamelCase     : int    ):
       snake_case       :   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     : Union[str, Any]				,					__lowerCamelCase     : Any				,					__lowerCamelCase     : Any    ):
       snake_case       :   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     : Optional[int]    ):
       snake_case       :   Tuple							=      str(tmp_path_factory.mktemp("data"    ) / "dataset.parquet"    )
       snake_case       :   Tuple							=      pa.schema(
           {
               "col_1": pa.string(),
               "col_2": pa.intaa(),
               "col_3": pa.floataa(),
           }    )
       with open(__lowerCamelCase				,					"wb"    ) as f:
              snake_case       :   Tuple							=      pq.ParquetWriter(__lowerCamelCase				,					schema=__lowerCamelCase    )
              snake_case       :   Dict							=      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     : int    ):
       snake_case       :   List[str]							=      str(tmp_path_factory.mktemp("data"    ) / "dataset.json"    )
       snake_case       :   Union[str, Any]							=      {"data": DATA}
       with open(__lowerCamelCase				,					"w"    ) as f:
              json.dump(__lowerCamelCase				,					__lowerCamelCase    )
       return path


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : Dict    ):
       snake_case       :   Optional[int]							=      str(tmp_path_factory.mktemp("data"    ) / "dataset.json"    )
       snake_case       :   Tuple							=      {"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    ):
       snake_case       :   List[str]							=      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    ):
       snake_case       :   List[str]							=      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     : Any    ):
       snake_case       :   Tuple							=      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     : Any    ):
       snake_case       :   str							=      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     : Dict				,					__lowerCamelCase     : List[str]    ):
       import gzip

       snake_case       :   Tuple							=      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     : Union[str, Any]				,					__lowerCamelCase     : List[str]    ):
       import gzip

       snake_case       :   int							=      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     : Dict				,					__lowerCamelCase     : Union[str, Any]				,					__lowerCamelCase     : Dict    ):
       snake_case       :   Optional[int]							=      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     : Optional[int]				,					__lowerCamelCase     : Tuple				,					__lowerCamelCase     : Dict				,					__lowerCamelCase     : List[Any]    ):
       snake_case       :   Optional[Any]							=      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     : Optional[int]				,					__lowerCamelCase     : Tuple				,					__lowerCamelCase     : int    ):
       snake_case       :   Tuple							=      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     : Union[str, Any]				,					__lowerCamelCase     : Union[str, Any]				,					__lowerCamelCase     : Optional[Any]    ):
       snake_case       :   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     : List[Any]				,					__lowerCamelCase     : Optional[int]				,					__lowerCamelCase     : Optional[Any]				,					__lowerCamelCase     : int    ):
       snake_case       :   str							=      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     : Optional[Any]    ):
       snake_case       :   Dict							=      ["0", "1", "2", "3"]
       snake_case       :   List[Any]							=      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     : int    ):
       snake_case       :   List[Any]							=      ["0", "1", "2", "3"]
       snake_case       :   int							=      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     : Dict    ):
       snake_case       :   Union[str, Any]							=      ["0", "1", "2", "3"]
       snake_case       :   Any							=      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     : Dict				,					__lowerCamelCase     : Dict				,					__lowerCamelCase     : Union[str, Any]    ):
       snake_case       :   Optional[int]							=      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     : Dict				,					__lowerCamelCase     : List[Any]				,					__lowerCamelCase     : Optional[Any]    ):
       snake_case       :   List[Any]							=      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     : List[str]				,					__lowerCamelCase     : Optional[Any]				,					__lowerCamelCase     : Union[str, Any]    ):
       snake_case       :   Any							=      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     : Optional[Any]    ):
       snake_case       :   List[Any]							=      "\n".join(["First", "Second\u2029with Unicode new line", "Third"]    )
       snake_case       :   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					(    ):
       return os.path.join("tests"				,					"features"				,					"data"				,					"test_image_rgb.jpg"    )


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


@pytest.fixture(scope="session"    )
def 			UpperCamelCase					(    __lowerCamelCase     : Tuple				,					__lowerCamelCase     : List[str]    ):
       snake_case       :   str							=      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     : List[str]    ):
       snake_case       :   Optional[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









'''simple docstring'''






import re
import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase    =					['image_processor', 'tokenizer']
    lowercase    =					'AutoImageProcessor'
    lowercase    =					'AutoTokenizer'

    def __init__(   self    :  int    ,						lowerCamelCase    :  List[str]=None    ,						lowerCamelCase    :  Union[str, Any]=None    ,						**lowerCamelCase    :  str		)   ->  Tuple:
      lowerCAmelCase_			:      str			=   None
      if "feature_extractor" in kwargs:
        warnings.warn(
            """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
            """ instead."""    ,						lowerCamelCase    ,						)
        lowerCAmelCase_			:      Tuple			=   kwargs.pop("""feature_extractor"""		)

      lowerCAmelCase_			:      Tuple			=   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__(lowerCamelCase    ,						lowerCamelCase		)
      lowerCAmelCase_			:      Optional[int]			=   self.image_processor
      lowerCAmelCase_			:      Any			=   False

    def __call__(   self    :  List[Any]    ,						*lowerCamelCase    :  str    ,						**lowerCamelCase    :  Tuple		)   ->  Union[str, Any]:
      # For backward compatibility
      if self._in_target_context_manager:
        return self.current_processor(*lowerCamelCase    ,						**lowerCamelCase		)

      lowerCAmelCase_			:      Any			=   kwargs.pop("""images"""    ,						lowerCamelCase		)
      lowerCAmelCase_			:      Dict			=   kwargs.pop("""text"""    ,						lowerCamelCase		)
      if len(lowerCamelCase		) > 0:
        lowerCAmelCase_			:      str			=   args[0]
        lowerCAmelCase_			:      Dict			=   args[1:]

      if images is None and text is None:
        raise ValueError("""You need to specify either an `images` or `text` input to process."""		)

      if images is not None:
        lowerCAmelCase_			:      Any			=   self.image_processor(lowerCamelCase    ,						*lowerCamelCase    ,						**lowerCamelCase		)
      if text is not None:
        lowerCAmelCase_			:      str			=   self.tokenizer(lowerCamelCase    ,						**lowerCamelCase		)

      if text is None:
        return inputs
      elif images is None:
        return encodings
      else:
        lowerCAmelCase_			:      Dict			=   encodings["""input_ids"""]
        return inputs

    def __lowercase   (   self    :  str    ,						*lowerCamelCase    :  Union[str, Any]    ,						**lowerCamelCase    :  Union[str, Any]		)   ->  List[str]:
      return self.tokenizer.batch_decode(*lowerCamelCase    ,						**lowerCamelCase		)

    def __lowercase   (   self    :  List[Any]    ,						*lowerCamelCase    :  Any    ,						**lowerCamelCase    :  Union[str, Any]		)   ->  List[str]:
      return self.tokenizer.decode(*lowerCamelCase    ,						**lowerCamelCase		)

    @contextmanager
    def __lowercase   (   self    :  str		)   ->  Union[str, Any]:
      warnings.warn(
          """`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your """
          """labels by using the argument `text` of the regular `__call__` method (either in the same call as """
          """your images inputs, or in a separate call."""		)
      lowerCAmelCase_			:      List[str]			=   True
      lowerCAmelCase_			:      Optional[Any]			=   self.tokenizer
      yield
      lowerCAmelCase_			:      List[Any]			=   self.image_processor
      lowerCAmelCase_			:      List[str]			=   False

    def __lowercase   (   self    :  Dict    ,						lowerCamelCase    :  List[str]    ,						lowerCamelCase    :  str=False    ,						lowerCamelCase    :  List[Any]=None		)   ->  Optional[int]:
      if added_vocab is None:
        lowerCAmelCase_			:      str			=   self.tokenizer.get_added_vocab()

      lowerCAmelCase_			:      Union[str, Any]			=   {}

      while tokens:
        lowerCAmelCase_			:      Dict			=   re.search(R"""<s_(.*?)>"""    ,						lowerCamelCase    ,						re.IGNORECASE		)
        if start_token is None:
          break
        lowerCAmelCase_			:      Tuple			=   start_token.group(1		)
        lowerCAmelCase_			:      Tuple			=   re.search(RF'</s_{key}>'    ,						lowerCamelCase    ,						re.IGNORECASE		)
        lowerCAmelCase_			:      Tuple			=   start_token.group()
        if end_token is None:
          lowerCAmelCase_			:      str			=   tokens.replace(lowerCamelCase    ,						""""""		)
        else:
          lowerCAmelCase_			:      List[str]			=   end_token.group()
          lowerCAmelCase_			:      Dict			=   re.escape(lowerCamelCase		)
          lowerCAmelCase_			:      int			=   re.escape(lowerCamelCase		)
          lowerCAmelCase_			:      Dict			=   re.search(F'{start_token_escaped}(.*?){end_token_escaped}'    ,						lowerCamelCase    ,						re.IGNORECASE		)
          if content is not None:
            lowerCAmelCase_			:      str			=   content.group(1		).strip()
            if r"<s_" in content and r"</s_" in content:  # non-leaf node
              lowerCAmelCase_			:      str			=   self.tokenajson(lowerCamelCase    ,						is_inner_value=lowerCamelCase    ,						added_vocab=lowerCamelCase		)
              if value:
                if len(lowerCamelCase		) == 1:
                  lowerCAmelCase_			:      List[Any]			=   value[0]
                lowerCAmelCase_			:      Optional[Any]			=   value
            else:  # leaf nodes
              lowerCAmelCase_			:      List[str]			=   []
              for leaf in content.split(R"""<sep/>"""		):
                lowerCAmelCase_			:      Union[str, Any]			=   leaf.strip()
                if leaf in added_vocab and leaf[0] == "<" and leaf[-2:] == "/>":
                  lowerCAmelCase_			:      Any			=   leaf[1:-2]  # for categorical special tokens
                output[key].append(lowerCamelCase		)
              if len(output[key]		) == 1:
                lowerCAmelCase_			:      Optional[Any]			=   output[key][0]

          lowerCAmelCase_			:      List[Any]			=   tokens[tokens.find(lowerCamelCase		) + len(lowerCamelCase		) :].strip()
          if tokens[:6] == r"<sep/>":  # non-leaf nodes
            return [output] + self.tokenajson(tokens[6:]    ,						is_inner_value=lowerCamelCase    ,						added_vocab=lowerCamelCase		)

      if len(lowerCamelCase		):
        return [output] if is_inner_value else output
      else:
        return [] if is_inner_value else {"text_sequence": tokens}

    @property
    def __lowercase   (   self    :  Dict		)   ->  int:
      warnings.warn(
          """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""    ,						lowerCamelCase    ,						)
      return self.image_processor_class





    @property
    def __lowercase   (   self    :  Dict		)   ->  Optional[Any]:
      warnings.warn(
          """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""    ,						lowerCamelCase    ,						)
      return self.image_processor



