

"""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  (  )	->						Any:
   '''simple docstring'''


   __lowercase								=						10
   __lowercase								=						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								=						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  (  UpperCamelCase_     :       Union[str, Any],			UpperCamelCase_     :       Optional[int])	->						Any:
   '''simple docstring'''


   __lowercase								=						str(tmp_path_factory.mktemp("data") / "file.arrow")
   dataset.map(cache_file_name=UpperCamelCase_)
   return filename


# FILE_CONTENT + files


_a       =							'\\n    Text data.\n    Second line of data.'




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       Optional[int])	->						List[Any]:
   '''simple docstring'''


   __lowercase								=						tmp_path_factory.mktemp("data") / "file.txt"
   __lowercase								=						FILE_CONTENT
   with open(UpperCamelCase_,			"w") as f:
      f.write(UpperCamelCase_)
   return filename




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       int)	->						Any:
   '''simple docstring'''


   import bza

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




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       Union[str, Any])	->						Optional[Any]:
   '''simple docstring'''


   import gzip

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




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       Tuple)	->						Union[str, Any]:
   '''simple docstring'''


   if datasets.config.LZ4_AVAILABLE:
      import lza.frame

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




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       str,			UpperCamelCase_     :       Any)	->						Optional[Any]:
   '''simple docstring'''


   if datasets.config.PY7ZR_AVAILABLE:
      import pyazr

      __lowercase								=						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  (  UpperCamelCase_     :       List[str],			UpperCamelCase_     :       Union[str, Any])	->						Optional[Any]:
   '''simple docstring'''


   import tarfile

   __lowercase								=						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  (  UpperCamelCase_     :       Optional[int])	->						int:
   '''simple docstring'''


   import lzma

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




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       Tuple,			UpperCamelCase_     :       Tuple)	->						int:
   '''simple docstring'''


   import zipfile

   __lowercase								=						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  (  UpperCamelCase_     :       str)	->						Union[str, Any]:
   '''simple docstring'''


   if datasets.config.ZSTANDARD_AVAILABLE:
      import zstandard as zstd

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




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       List[Any])	->						Optional[Any]:
   '''simple docstring'''


   __lowercase								=						tmp_path_factory.mktemp("data") / "file.xml"
   __lowercase								=						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


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

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

_a       =							[
    {'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  (  )	->						Any:
   '''simple docstring'''


   return DATA_DICT_OF_LISTS




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       Union[str, Any])	->						Optional[Any]:
   '''simple docstring'''


   __lowercase								=						datasets.Dataset.from_dict(UpperCamelCase_)
   __lowercase								=						str(tmp_path_factory.mktemp("data") / "dataset.arrow")
   dataset.map(cache_file_name=UpperCamelCase_)
   return path




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       Optional[Any])	->						Union[str, Any]:
   '''simple docstring'''


   __lowercase								=						str(tmp_path_factory.mktemp("data") / "dataset.sqlite")
   with contextlib.closing(sqlitea.connect(UpperCamelCase_)) as con:
      __lowercase								=						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  (  UpperCamelCase_     :       Any)	->						int:
   '''simple docstring'''


   __lowercase								=						str(tmp_path_factory.mktemp("data") / "dataset.csv")
   with open(UpperCamelCase_,			"w",			newline="") as f:
      __lowercase								=						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  (  UpperCamelCase_     :       Dict)	->						Dict:
   '''simple docstring'''


   __lowercase								=						str(tmp_path_factory.mktemp("data") / "dataset2.csv")
   with open(UpperCamelCase_,			"w",			newline="") as f:
      __lowercase								=						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  (  UpperCamelCase_     :       Dict,			UpperCamelCase_     :       int)	->						Optional[Any]:
   '''simple docstring'''


   import bza

   __lowercase								=						tmp_path_factory.mktemp("data") / "dataset.csv.bz2"
   with open(UpperCamelCase_,			"rb") as f:
      __lowercase								=						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  (  UpperCamelCase_     :       Dict,			UpperCamelCase_     :       Dict,			UpperCamelCase_     :       List[str])	->						str:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       List[Any],			UpperCamelCase_     :       str,			UpperCamelCase_     :       Optional[Any])	->						Union[str, Any]:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Tuple,			UpperCamelCase_     :       Union[str, Any],			UpperCamelCase_     :       int)	->						int:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       List[str])	->						Union[str, Any]:
   '''simple docstring'''


   __lowercase								=						str(tmp_path_factory.mktemp("data") / "dataset.parquet")
   __lowercase								=						pa.schema(
       {
           "col_1": pa.string(),
           "col_2": pa.intaa(),
           "col_3": pa.floataa(),
       })
   with open(UpperCamelCase_,			"wb") as f:
      __lowercase								=						pq.ParquetWriter(UpperCamelCase_,			schema=UpperCamelCase_)
      __lowercase								=						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  (  UpperCamelCase_     :       str)	->						Tuple:
   '''simple docstring'''


   __lowercase								=						str(tmp_path_factory.mktemp("data") / "dataset.json")
   __lowercase								=						{"data": DATA}
   with open(UpperCamelCase_,			"w") as f:
      json.dump(UpperCamelCase_,			UpperCamelCase_)
   return path




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       Optional[Any])	->						Any:
   '''simple docstring'''


   __lowercase								=						str(tmp_path_factory.mktemp("data") / "dataset.json")
   __lowercase								=						{"data": DATA_DICT_OF_LISTS}
   with open(UpperCamelCase_,			"w") as f:
      json.dump(UpperCamelCase_,			UpperCamelCase_)
   return path




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       str)	->						int:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Optional[int])	->						Tuple:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       str)	->						Any:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Dict)	->						Tuple:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Tuple,			UpperCamelCase_     :       int)	->						Union[str, Any]:
   '''simple docstring'''


   import gzip

   __lowercase								=						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  (  UpperCamelCase_     :       Tuple,			UpperCamelCase_     :       List[str])	->						List[str]:
   '''simple docstring'''


   import gzip

   __lowercase								=						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  (  UpperCamelCase_     :       Dict,			UpperCamelCase_     :       Any,			UpperCamelCase_     :       Union[str, Any])	->						Tuple:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       List[Any],			UpperCamelCase_     :       Dict,			UpperCamelCase_     :       List[Any],			UpperCamelCase_     :       List[str])	->						Union[str, Any]:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Any,			UpperCamelCase_     :       List[Any],			UpperCamelCase_     :       Union[str, Any])	->						Dict:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Optional[int],			UpperCamelCase_     :       List[Any],			UpperCamelCase_     :       Dict)	->						Tuple:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Dict,			UpperCamelCase_     :       str,			UpperCamelCase_     :       Optional[Any],			UpperCamelCase_     :       Optional[int])	->						Optional[Any]:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Any)	->						Dict:
   '''simple docstring'''


   __lowercase								=						["0", "1", "2", "3"]
   __lowercase								=						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  (  UpperCamelCase_     :       str)	->						str:
   '''simple docstring'''


   __lowercase								=						["0", "1", "2", "3"]
   __lowercase								=						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  (  UpperCamelCase_     :       str)	->						Optional[Any]:
   '''simple docstring'''


   __lowercase								=						["0", "1", "2", "3"]
   __lowercase								=						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  (  UpperCamelCase_     :       List[Any],			UpperCamelCase_     :       Optional[Any],			UpperCamelCase_     :       Union[str, Any])	->						str:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       str,			UpperCamelCase_     :       Dict,			UpperCamelCase_     :       int)	->						Tuple:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       int,			UpperCamelCase_     :       str,			UpperCamelCase_     :       Optional[int])	->						Optional[int]:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Dict)	->						Union[str, Any]:
   '''simple docstring'''


   __lowercase								=						"\n".join(["First", "Second\u2029with Unicode new line", "Third"])
   __lowercase								=						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  (  )	->						Any:
   '''simple docstring'''


   return os.path.join("tests",			"features",			"data",			"test_image_rgb.jpg")




@pytest.fixture(scope="session")
def   _A  (  )	->						Union[str, Any]:
   '''simple docstring'''


   return os.path.join("tests",			"features",			"data",			"test_audio_44100.wav")




@pytest.fixture(scope="session")
def   _A  (  UpperCamelCase_     :       Tuple,			UpperCamelCase_     :       List[str])	->						Tuple:
   '''simple docstring'''


   __lowercase								=						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  (  UpperCamelCase_     :       Union[str, Any])	->						Optional[Any]:
   '''simple docstring'''


   __lowercase								=						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"""





from __future__ import annotations

import unittest

from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
   import tensorflow as tf

   from transformers.models.xglm.modeling_tf_xglm import (
       TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
       TFXGLMForCausalLM,
       TFXGLMModel,
   )




@require_tf
class 					_lowerCAmelCase  :







 """simple docstring"""







 __UpperCAmelCase	:					Tuple   		=	XGLMConfig
 __UpperCAmelCase	:					Optional[Any]   		=	{}
 __UpperCAmelCase	:					Union[str, Any]   		=	"gelu"


 def __init__(			self							:			Optional[int],					UpperCAmelCase__							:			List[str],					UpperCAmelCase__							:			Optional[int]=1_4,					UpperCAmelCase__							:			str=7,					UpperCAmelCase__							:			Optional[Any]=True,					UpperCAmelCase__							:			List[Any]=True,					UpperCAmelCase__							:			int=True,					UpperCAmelCase__							:			List[str]=9_9,					UpperCAmelCase__							:			Union[str, Any]=3_2,					UpperCAmelCase__							:			Union[str, Any]=2,					UpperCAmelCase__							:			Union[str, Any]=4,					UpperCAmelCase__							:			Tuple=3_7,					UpperCAmelCase__							:			List[Any]="gelu",					UpperCAmelCase__							:			List[str]=0.1,					UpperCAmelCase__							:			Optional[int]=0.1,					UpperCAmelCase__							:			Tuple=5_1_2,					UpperCAmelCase__							:			Optional[Any]=0.02,					):
    __lowercase								=						parent
    __lowercase								=						batch_size
    __lowercase								=						seq_length
    __lowercase								=						is_training
    __lowercase								=						use_input_mask
    __lowercase								=						use_labels
    __lowercase								=						vocab_size
    __lowercase								=						d_model
    __lowercase								=						num_hidden_layers
    __lowercase								=						num_attention_heads
    __lowercase								=						ffn_dim
    __lowercase								=						activation_function
    __lowercase								=						activation_dropout
    __lowercase								=						attention_dropout
    __lowercase								=						max_position_embeddings
    __lowercase								=						initializer_range
    __lowercase								=						None
    __lowercase								=						0
    __lowercase								=						2
    __lowercase								=						1


 def 					_lowercase (			self							:			Union[str, Any]	):
    return XGLMConfig.from_pretrained("facebook/xglm-564M"	)


 def 					_lowercase (			self							:			Tuple	):
    __lowercase								=						tf.clip_by_value(
        ids_tensor([self.batch_size, self.seq_length],					self.vocab_size	),					clip_value_min=0,					clip_value_max=3	)

    __lowercase								=						None
    if self.use_input_mask:
       __lowercase								=						random_attention_mask([self.batch_size, self.seq_length]	)

    __lowercase								=						self.get_config()

    __lowercase								=						floats_tensor([self.num_hidden_layers, self.num_attention_heads],					2	)

    return (
        config,
        input_ids,
        input_mask,
        head_mask,
    )


 def 					_lowercase (			self							:			List[Any]	):
    return XGLMConfig(
        vocab_size=self.vocab_size,					d_model=self.hidden_size,					num_layers=self.num_hidden_layers,					attention_heads=self.num_attention_heads,					ffn_dim=self.ffn_dim,					activation_function=self.activation_function,					activation_dropout=self.activation_dropout,					attention_dropout=self.attention_dropout,					max_position_embeddings=self.max_position_embeddings,					initializer_range=self.initializer_range,					use_cache=UpperCAmelCase__,					bos_token_id=self.bos_token_id,					eos_token_id=self.eos_token_id,					pad_token_id=self.pad_token_id,					return_dict=UpperCAmelCase__,					)



 def 					_lowercase (			self							:			Dict	):
    __lowercase								=						self.prepare_config_and_inputs()

    (
        (
        __lowercase
    )		,(
        __lowercase
    )		,(
        __lowercase
    )		,(
        __lowercase
    )		,
    )								=						config_and_inputs

    __lowercase								=						{
        "input_ids": input_ids,
        "head_mask": head_mask,
    }

    return config, inputs_dict







@require_tf
class 					_lowerCAmelCase  (	lowercase     ,lowercase     ,unittest.TestCase   ):







 """simple docstring"""







 __UpperCAmelCase	:					Union[str, Any]   		=	(TFXGLMModel, TFXGLMForCausalLM) if is_tf_available() else ()
 __UpperCAmelCase	:					List[str]   		=	(TFXGLMForCausalLM,) if is_tf_available() else ()
 __UpperCAmelCase	:					Any   		=	(
     {"feature-extraction": TFXGLMModel, "text-generation": TFXGLMForCausalLM} if is_tf_available() else {}
 )
 __UpperCAmelCase	:					Optional[Any]   		=	False
 __UpperCAmelCase	:					List[str]   		=	False
 __UpperCAmelCase	:					int   		=	False


 def 					_lowercase (			self							:			Optional[Any]	):
    __lowercase								=						TFXGLMModelTester(self	)
    __lowercase								=						ConfigTester(self,					config_class=UpperCAmelCase__,					n_embd=3_7	)


 def 					_lowercase (			self							:			Any	):
    self.config_tester.run_common_tests()


 @slow
 def 					_lowercase (			self							:			List[str]	):
    for model_name in TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
       __lowercase								=						TFXGLMModel.from_pretrained(UpperCAmelCase__	)
       self.assertIsNotNone(UpperCAmelCase__	)



 @unittest.skip(reason="Currently, model embeddings are going to undergo a major refactor."	)
 def 					_lowercase (			self							:			int	):
    super().test_resize_token_embeddings()







@require_tf
class 					_lowerCAmelCase  (	unittest.TestCase   ):







 """simple docstring"""







 @slow
 def 					_lowercase (			self							:			Dict,					UpperCAmelCase__							:			Optional[int]=True	):
    __lowercase								=						TFXGLMForCausalLM.from_pretrained("facebook/xglm-564M"	)
    __lowercase								=						tf.convert_to_tensor([[2, 2_6_8, 9_8_6_5]],					dtype=tf.intaa	)  # The dog
    # </s> The dog is a very friendly dog. He is very affectionate and loves to play with other
    # fmt: off
    __lowercase								=						[2, 2_6_8, 9_8_6_5, 6_7, 1_1, 1_9_8_8, 5_7_2_5_2, 9_8_6_5, 5, 9_8_4, 6_7, 1_9_8_8, 2_1_3_8_3_8, 1_6_5_8, 5_3, 7_0_4_4_6, 3_3, 6_6_5_7, 2_7_8, 1_5_8_1]
    # fmt: on
    __lowercase								=						model.generate(UpperCAmelCase__,					do_sample=UpperCAmelCase__,					num_beams=1	)
    if verify_outputs:
       self.assertListEqual(output_ids[0].numpy().tolist(),					UpperCAmelCase__	)


 @slow
 def 					_lowercase (			self							:			List[Any]	):
    __lowercase								=						XGLMTokenizer.from_pretrained("facebook/xglm-564M"	)
    __lowercase								=						TFXGLMForCausalLM.from_pretrained("facebook/xglm-564M"	)

    tf.random.set_seed(0	)
    __lowercase								=						tokenizer("Today is a nice day and",					return_tensors="tf"	)
    __lowercase								=						tokenized.input_ids
    # forces the generation to happen on CPU, to avoid GPU-related quirks (and assure same output regardless of the available devices)
    with tf.device(":/CPU:0"	):
       __lowercase								=						model.generate(UpperCAmelCase__,					do_sample=UpperCAmelCase__,					seed=[7, 0]	)
    __lowercase								=						tokenizer.decode(output_ids[0],					skip_special_tokens=UpperCAmelCase__	)

    __lowercase								=						(
        "Today is a nice day and warm evening here over Southern Alberta!! Today when they closed schools due"
    )
    self.assertEqual(UpperCAmelCase__,					UpperCAmelCase__	)



 @slow
 def 					_lowercase (			self							:			Dict	):
    __lowercase								=						TFXGLMForCausalLM.from_pretrained("facebook/xglm-564M"	)
    __lowercase								=						XGLMTokenizer.from_pretrained("facebook/xglm-564M"	)

    __lowercase								=						"left"

    # use different length sentences to test batching
    __lowercase								=						[
        "This is an extremelly long sentence that only exists to test the ability of the model to cope with "
        "left-padding, such as in batched generation. The output for the sequence below should be the same "
        "regardless of whether left padding is applied or not. When",
        "Hello, my dog is a little",
    ]

    __lowercase								=						tokenizer(UpperCAmelCase__,					return_tensors="tf",					padding=UpperCAmelCase__	)
    __lowercase								=						inputs["input_ids"]

    __lowercase								=						model.generate(input_ids=UpperCAmelCase__,					attention_mask=inputs["attention_mask"],					max_new_tokens=1_2	)

    __lowercase								=						tokenizer(sentences[0],					return_tensors="tf"	).input_ids
    __lowercase								=						model.generate(input_ids=UpperCAmelCase__,					max_new_tokens=1_2	)

    __lowercase								=						tokenizer(sentences[1],					return_tensors="tf"	).input_ids
    __lowercase								=						model.generate(input_ids=UpperCAmelCase__,					max_new_tokens=1_2	)

    __lowercase								=						tokenizer.batch_decode(UpperCAmelCase__,					skip_special_tokens=UpperCAmelCase__	)
    __lowercase								=						tokenizer.decode(output_non_padded[0],					skip_special_tokens=UpperCAmelCase__	)
    __lowercase								=						tokenizer.decode(output_padded[0],					skip_special_tokens=UpperCAmelCase__	)

    __lowercase								=						[
        "This is an extremelly long sentence that only exists to test the ability of the model to cope with "
        "left-padding, such as in batched generation. The output for the sequence below should be the same "
        "regardless of whether left padding is applied or not. When left padding is applied, the sequence will be "
        "a single",
        "Hello, my dog is a little bit of a shy one, but he is very friendly",
    ]
    self.assertListEqual(UpperCAmelCase__,					UpperCAmelCase__	)
    self.assertListEqual(UpperCAmelCase__,					[non_padded_sentence, padded_sentence]	)




