'''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  _A		(     )      ->     str:
   _lowercase      :				str      					=       10
   _lowercase      :				Tuple      					=       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      :				str      					=       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  _A		(     snake_case		,							snake_case					)      ->     List[Any]:
   _lowercase      :				Any      					=       str(tmp_path_factory.mktemp("data"					) / "file.arrow"					)
   dataset.map(cache_file_name=_UpperCAmelCase					)
   return filename


# FILE_CONTENT + files


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







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







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

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







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

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







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

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







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

      _lowercase      :				Optional[Any]      					=       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  _A		(     snake_case		,							snake_case					)      ->     str:
   import tarfile

   _lowercase      :				int      					=       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  _A		(     snake_case					)      ->     str:
   import lzma

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







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

   _lowercase      :				int      					=       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  _A		(     snake_case					)      ->     Any:
   if datasets.config.ZSTANDARD_AVAILABLE:
      import zstandard as zstd

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







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


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

_snake_case         =  [
    {'''col_3''': 0.0, '''col_1''': '''0''', '''col_2''': 0},
    {'''col_3''': 1.0, '''col_1''': '''1''', '''col_2''': 1},
]

_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  _A		(     )      ->     List[Any]:
   return DATA_DICT_OF_LISTS







@pytest.fixture(scope="session"					)
def  _A		(     snake_case					)      ->     Any:
   _lowercase      :				Any      					=       datasets.Dataset.from_dict(_UpperCAmelCase					)
   _lowercase      :				Union[str, Any]      					=       str(tmp_path_factory.mktemp("data"					) / "dataset.arrow"					)
   dataset.map(cache_file_name=_UpperCAmelCase					)
   return path







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

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







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







@pytest.fixture(scope="session"					)
def  _A		(     snake_case					)      ->     Dict:
   _lowercase      :				Tuple      					=       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  _A		(     snake_case					)      ->     Tuple:
   _lowercase      :				Union[str, Any]      					=       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  _A		(     snake_case					)      ->     Optional[int]:
   _lowercase      :				int      					=       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  _A		(     snake_case					)      ->     List[str]:
   _lowercase      :				List[str]      					=       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  _A		(     snake_case		,							snake_case					)      ->     str:
   import gzip

   _lowercase      :				List[str]      					=       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  _A		(     snake_case		,							snake_case					)      ->     Optional[int]:
   import gzip

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







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







@pytest.fixture(scope="session"					)
def  _A		(     snake_case		,							snake_case					)      ->     Dict:
   _lowercase      :				List[str]      					=       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  _A		(     snake_case					)      ->     Optional[Any]:
   _lowercase      :				Tuple      					=       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 os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_snake_case         =  logging.get_logger(__name__)

_snake_case         =  {'vocab_file': 'spiece.model'}

_snake_case         =  {
    'vocab_file': {
        'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model',
        'google/bigbird-roberta-large': (
            'https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'
        ),
        'google/bigbird-base-trivia-itc': (
            'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'
        ),
    }
}

_snake_case         =  {
    'google/bigbird-roberta-base': 4_096,
    'google/bigbird-roberta-large': 4_096,
    'google/bigbird-base-trivia-itc': 4_096,
}


class        a__  (							lowerCamelCase_  ):
   _SCREAMING_SNAKE_CASE   :					List[Any]     	=							VOCAB_FILES_NAMES
   _SCREAMING_SNAKE_CASE   :					Any     	=							PRETRAINED_VOCAB_FILES_MAP
   _SCREAMING_SNAKE_CASE   :					Optional[Any]     	=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _SCREAMING_SNAKE_CASE   :					Optional[int]     	=							['input_ids', 'attention_mask']
   _SCREAMING_SNAKE_CASE   :					List[int]     	=							[]


   def __init__(			self      ,    _UpperCamelCase      ,    _UpperCamelCase="<unk>"      ,    _UpperCamelCase="<s>"      ,    _UpperCamelCase="</s>"      ,    _UpperCamelCase="<pad>"      ,    _UpperCamelCase="[SEP]"      ,    _UpperCamelCase="[MASK]"      ,    _UpperCamelCase="[CLS]"      ,    _UpperCamelCase = None      ,    **_UpperCamelCase      ,    ):





      """simple docstring"""





      _lowercase      :				Optional[int]      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else bos_token
      _lowercase      :				Optional[int]      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else eos_token
      _lowercase      :				Optional[Any]      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else unk_token
      _lowercase      :				Union[str, Any]      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else pad_token
      _lowercase      :				Any      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else cls_token
      _lowercase      :				str      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else sep_token

      # Mask token behave like a normal word, i.e. include the space before it
      _lowercase      :				Any      					=       AddedToken(_UpperCamelCase      ,    lstrip=_UpperCamelCase      ,    rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase      ,    _UpperCamelCase  ) else mask_token

      _lowercase      :				Dict      					=       {} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=_UpperCamelCase      ,    eos_token=_UpperCamelCase      ,    unk_token=_UpperCamelCase      ,    pad_token=_UpperCamelCase      ,    sep_token=_UpperCamelCase      ,    mask_token=_UpperCamelCase      ,    cls_token=_UpperCamelCase      ,    sp_model_kwargs=self.sp_model_kwargs      ,    **_UpperCamelCase      ,    )

      _lowercase      :				str      					=       vocab_file

      _lowercase      :				List[Any]      					=       spm.SentencePieceProcessor(**self.sp_model_kwargs  )
      self.sp_model.Load(_UpperCamelCase  )


   @property
   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      return self.sp_model.get_piece_size()


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Dict      					=       {self.convert_ids_to_tokens(_UpperCamelCase  ): i for i in range(self.vocab_size  )}
      vocab.update(self.added_tokens_encoder  )
      return vocab


   def __getstate__(			self  ):





      """simple docstring"""





      _lowercase      :				str      					=       self.__dict__.copy()
      _lowercase      :				Union[str, Any]      					=       None
      return state


   def __setstate__(			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				Dict      					=       d

      # for backward compatibility
      if not hasattr(self      ,    "sp_model_kwargs"  ):
         _lowercase      :				Optional[Any]      					=       {}

      _lowercase      :				Optional[Any]      					=       spm.SentencePieceProcessor(**self.sp_model_kwargs  )
      self.sp_model.Load(self.vocab_file  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      return self.sp_model.encode(_UpperCamelCase      ,    out_type=_UpperCamelCase  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      return self.sp_model.piece_to_id(_UpperCamelCase  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				List[Any]      					=       self.sp_model.IdToPiece(_UpperCamelCase  )
      return token


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				Optional[int]      					=       []
      _lowercase      :				int      					=       ""
      _lowercase      :				Tuple      					=       False
      for token in tokens:
         # make sure that special tokens are not decoded using sentencepiece model
         if token in self.all_special_tokens:
            if not prev_is_special:
               out_string += " "
            out_string += self.sp_model.decode(_UpperCamelCase  ) + token
            _lowercase      :				Union[str, Any]      					=       True
            _lowercase      :				Optional[int]      					=       []
         else:
            current_sub_tokens.append(_UpperCamelCase  )
            _lowercase      :				str      					=       False
      out_string += self.sp_model.decode(_UpperCamelCase  )
      return out_string.strip()


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = False      ,    _UpperCamelCase = None      ,    _UpperCamelCase = True      ,    **_UpperCamelCase      ,    ):





      """simple docstring"""





      _lowercase      :				Any      					=       kwargs.pop("use_source_tokenizer"      ,    _UpperCamelCase  )

      _lowercase      :				Dict      					=       self.convert_ids_to_tokens(_UpperCamelCase      ,    skip_special_tokens=_UpperCamelCase  )

      # To avoid mixing byte-level and unicode for byte-level BPT
      # we need to build string separately for added tokens and byte-level tokens
      # cf. https://github.com/huggingface/transformers/issues/1133
      _lowercase      :				Dict      					=       []
      _lowercase      :				Any      					=       []
      for token in filtered_tokens:
         if skip_special_tokens and token in self.all_special_ids:
            continue
         if token in self.added_tokens_encoder:
            if current_sub_text:
               sub_texts.append(self.convert_tokens_to_string(_UpperCamelCase  )  )
               _lowercase      :				Optional[Any]      					=       []
            sub_texts.append(_UpperCamelCase  )
         else:
            current_sub_text.append(_UpperCamelCase  )
      if current_sub_text:
         sub_texts.append(self.convert_tokens_to_string(_UpperCamelCase  )  )

      # Mimic the behavior of the Rust tokenizer:
      # No space before [MASK] and [SEP]
      if spaces_between_special_tokens:
         _lowercase      :				List[str]      					=       re.sub(R" (\[(MASK|SEP)\])"      ,    R"\1"      ,    " ".join(_UpperCamelCase  )  )
      else:
         _lowercase      :				List[Any]      					=       "".join(_UpperCamelCase  )

      _lowercase      :				Optional[int]      					=       (
          clean_up_tokenization_spaces
          if clean_up_tokenization_spaces is not None
          else self.clean_up_tokenization_spaces
      )
      if clean_up_tokenization_spaces:
         _lowercase      :				Tuple      					=       self.clean_up_tokenization(_UpperCamelCase  )
         return clean_text
      else:
         return text


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None  ):





      """simple docstring"""





      if not os.path.isdir(_UpperCamelCase  ):
         logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
         return
      _lowercase      :				Optional[Any]      					=       os.path.join(
          _UpperCamelCase      ,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )

      if os.path.abspath(self.vocab_file  ) != os.path.abspath(_UpperCamelCase  ) and os.path.isfile(self.vocab_file  ):
         copyfile(self.vocab_file      ,    _UpperCamelCase  )
      elif not os.path.isfile(self.vocab_file  ):
         with open(_UpperCamelCase      ,    "wb"  ) as fi:
            _lowercase      :				List[str]      					=       self.sp_model.serialized_model_proto()
            fi.write(_UpperCamelCase  )

      return (out_vocab_file,)


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None  ):





      """simple docstring"""





      if token_ids_a is None:
         return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      _lowercase      :				str      					=       [self.cls_token_id]
      _lowercase      :				List[str]      					=       [self.sep_token_id]
      return cls + token_ids_a + sep + token_ids_a + sep


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None      ,    _UpperCamelCase = False  ):





      """simple docstring"""





      if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=_UpperCamelCase      ,    token_ids_a=_UpperCamelCase      ,    already_has_special_tokens=_UpperCamelCase  )

      if token_ids_a is None:
         return [1] + ([0] * len(_UpperCamelCase  )) + [1]
      return [1] + ([0] * len(_UpperCamelCase  )) + [1] + ([0] * len(_UpperCamelCase  )) + [1]






   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase = None  ):





      """simple docstring"""





      _lowercase      :				str      					=       [self.sep_token_id]
      _lowercase      :				Union[str, Any]      					=       [self.cls_token_id]
      if token_ids_a is None:
         return len(cls + token_ids_a + sep  ) * [0]
      return len(cls + token_ids_a + sep  ) * [0] + len(token_ids_a + sep  ) * [1]






