
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      lowerCamelCase__       (       ):




			"""simple docstring"""


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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[Any]					,							__lowerCAmelCase						:						List[str]       ):




			"""simple docstring"""


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


# FILE_CONTENT + files


_A     =  "\\n    Text data.\n    Second line of data."






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Dict       ):




			"""simple docstring"""


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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Optional[int]       ):




			"""simple docstring"""


			import bza

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Any       ):




			"""simple docstring"""


			import gzip

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Tuple       ):




			"""simple docstring"""


			if datasets.config.LZ4_AVAILABLE:
						import lza.frame

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Union[str, Any]					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			if datasets.config.PY7ZR_AVAILABLE:
						import pyazr

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						int					,							__lowerCAmelCase						:						Any       ):




			"""simple docstring"""


			import tarfile

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						int       ):




			"""simple docstring"""


			import lzma

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[Any]					,							__lowerCAmelCase						:						int       ):




			"""simple docstring"""


			import zipfile

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Dict       ):




			"""simple docstring"""


			if datasets.config.ZSTANDARD_AVAILABLE:
						import zstandard as zstd

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Tuple       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''file.xml'''
			lowerCAmelCase_      			=			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(a_					,							"w"       ) as f:
						f.write(a_       )
			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      lowerCamelCase__       (       ):




			"""simple docstring"""


			return DATA_DICT_OF_LISTS






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[Any]       ):




			"""simple docstring"""


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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset.sqlite"       )
			with contextlib.closing(sqlitea.connect(a_       )       ) as con:
						lowerCAmelCase_      			=			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      lowerCamelCase__       (       __lowerCAmelCase						:						Optional[int]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset.csv"       )
			with open(a_					,							"w"					,							newline=""       ) as f:
						lowerCAmelCase_      			=			csv.DictWriter(a_					,							fieldnames=["col_1", "col_2", "col_3"]       )
						writer.writeheader()
						for item in DATA:
									writer.writerow(a_       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Tuple       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset2.csv"       )
			with open(a_					,							"w"					,							newline=""       ) as f:
						lowerCAmelCase_      			=			csv.DictWriter(a_					,							fieldnames=["col_1", "col_2", "col_3"]       )
						writer.writeheader()
						for item in DATA:
									writer.writerow(a_       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						str					,							__lowerCAmelCase						:						Optional[int]       ):




			"""simple docstring"""


			import bza

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Dict					,							__lowerCAmelCase						:						List[str]					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset.csv.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.basename(a_       )       )
						f.write(a_					,							arcname=os.path.basename(a_       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Dict					,							__lowerCAmelCase						:						Optional[Any]					,							__lowerCAmelCase						:						List[str]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset.csv.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.basename(csv_path.replace(".csv"					,							".CSV"       )       )       )
						f.write(a_					,							arcname=os.path.basename(csva_path.replace(".csv"					,							".CSV"       )       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Any					,							__lowerCAmelCase						:						str					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset_with_dir.csv.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.join("main_dir"					,							os.path.basename(a_       )       )       )
						f.write(a_					,							arcname=os.path.join("main_dir"					,							os.path.basename(a_       )       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Optional[int]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset.parquet"       )
			lowerCAmelCase_      			=			pa.schema(
			    {
			        "col_1": pa.string(),
			        "col_2": pa.intaa(),
			        "col_3": pa.floataa(),
			    }       )
			with open(a_					,							"wb"       ) as f:
						lowerCAmelCase_      			=			pq.ParquetWriter(a_					,							schema=a_       )
						lowerCAmelCase_      			=			pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(a_       )       )] for k in DATA[0]}					,							schema=a_       )
						writer.write_table(a_       )
						writer.close()
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						str       ):




			"""simple docstring"""


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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						int       ):




			"""simple docstring"""


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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						int       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset.jsonl"       )
			with open(a_					,							"w"       ) as f:
						for item in DATA:
									f.write(json.dumps(a_       ) + "\n"       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[str]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset2.jsonl"       )
			with open(a_					,							"w"       ) as f:
						for item in DATA:
									f.write(json.dumps(a_       ) + "\n"       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Union[str, Any]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset_312.jsonl"       )
			with open(a_					,							"w"       ) as f:
						for item in DATA_312:
									f.write(json.dumps(a_       ) + "\n"       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[Any]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset-str.jsonl"       )
			with open(a_					,							"w"       ) as f:
						for item in DATA_STR:
									f.write(json.dumps(a_       ) + "\n"       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Any					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			import gzip

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[str]					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			import gzip

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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						str					,							__lowerCAmelCase						:						Optional[Any]					,							__lowerCAmelCase						:						Optional[int]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset.jsonl.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.basename(a_       )       )
						f.write(a_					,							arcname=os.path.basename(a_       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Any					,							__lowerCAmelCase						:						List[str]					,							__lowerCAmelCase						:						Tuple					,							__lowerCAmelCase						:						Tuple       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset_nested.jsonl.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.join("nested"					,							os.path.basename(a_       )       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Optional[int]					,							__lowerCAmelCase						:						List[str]					,							__lowerCAmelCase						:						Dict       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset_with_dir.jsonl.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.join("main_dir"					,							os.path.basename(a_       )       )       )
						f.write(a_					,							arcname=os.path.join("main_dir"					,							os.path.basename(a_       )       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[Any]					,							__lowerCAmelCase						:						Any					,							__lowerCAmelCase						:						Optional[Any]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset.jsonl.tar'''
			with tarfile.TarFile(a_					,							"w"       ) as f:
						f.add(a_					,							arcname=os.path.basename(a_       )       )
						f.add(a_					,							arcname=os.path.basename(a_       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Union[str, Any]					,							__lowerCAmelCase						:						List[Any]					,							__lowerCAmelCase						:						Optional[int]					,							__lowerCAmelCase						:						Union[str, Any]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset_nested.jsonl.tar'''
			with tarfile.TarFile(a_					,							"w"       ) as f:
						f.add(a_					,							arcname=os.path.join("nested"					,							os.path.basename(a_       )       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Dict       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			['''0''', '''1''', '''2''', '''3''']
			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset.txt"       )
			with open(a_					,							"w"       ) as f:
						for item in data:
									f.write(item + "\n"       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						int       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			['''0''', '''1''', '''2''', '''3''']
			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset2.txt"       )
			with open(a_					,							"w"       ) as f:
						for item in data:
									f.write(item + "\n"       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[Any]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			['''0''', '''1''', '''2''', '''3''']
			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset.abc'''
			with open(a_					,							"w"       ) as f:
						for item in data:
									f.write(item + "\n"       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Optional[Any]					,							__lowerCAmelCase						:						Optional[int]					,							__lowerCAmelCase						:						Optional[int]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset.text.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.basename(a_       )       )
						f.write(a_					,							arcname=os.path.basename(a_       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[str]					,							__lowerCAmelCase						:						Union[str, Any]					,							__lowerCAmelCase						:						Optional[int]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset_with_dir.text.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.join("main_dir"					,							os.path.basename(a_       )       )       )
						f.write(a_					,							arcname=os.path.join("main_dir"					,							os.path.basename(a_       )       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						int					,							__lowerCAmelCase						:						Optional[int]					,							__lowerCAmelCase						:						Union[str, Any]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset.ext.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.basename("unsupported.ext"       )       )
						f.write(a_					,							arcname=os.path.basename("unsupported_2.ext"       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Dict       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			'''\n'''.join(["First", "Second\u2029with Unicode new line", "Third"]       )
			lowerCAmelCase_      			=			str(tmp_path_factory.mktemp("data"       ) / "dataset_with_unicode_new_lines.txt"       )
			with open(a_					,							"w"					,							encoding="utf-8"       ) as f:
						f.write(a_       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       ):




			"""simple docstring"""


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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       ):




			"""simple docstring"""


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






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						Tuple					,							__lowerCAmelCase						:						Union[str, Any]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			tmp_path_factory.mktemp("data"       ) / '''dataset.img.zip'''
			with zipfile.ZipFile(a_					,							"w"       ) as f:
						f.write(a_					,							arcname=os.path.basename(a_       )       )
						f.write(a_					,							arcname=os.path.basename(a_       ).replace(".jpg"					,							"2.jpg"       )       )
			return path






@pytest.fixture(scope="session"       )
def      lowerCamelCase__       (       __lowerCAmelCase						:						List[Any]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			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





import inspect

import jax
import jax.lax as lax
import jax.numpy as jnp

from ..utils import add_start_docstrings
from ..utils.logging import get_logger


_A     =  get_logger(__name__)


_A     =  R"\n    Args:\n        input_ids (`jnp.ndarray` of shape `(batch_size, sequence_length)`):\n            Indices of input sequence tokens in the vocabulary.\n\n            Indices can be obtained using [`PreTrainedTokenizer`]. See [`PreTrainedTokenizer.encode`] and\n            [`PreTrainedTokenizer.__call__`] for details.\n\n            [What are input IDs?](../glossary#input-ids)\n        scores (`jnp.ndarray` of shape `(batch_size, config.vocab_size)`):\n            Prediction scores of a language modeling head. These can be logits for each vocabulary when not using beam\n            search or log softmax for each vocabulary token when using beam search\n        kwargs (`Dict[str, Any]`, *optional*):\n            Additional logits processor specific kwargs.\n\n    Return:\n        `jnp.ndarray` of shape `(batch_size, config.vocab_size)`: The processed prediction scores.\n\n"





class 			_lowerCAmelCase      :




				@add_start_docstrings(_UpperCamelCase  )
				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							raise NotImplementedError(
							    f"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""  )





class 			_lowerCAmelCase      :




				@add_start_docstrings(_UpperCamelCase  )
				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							raise NotImplementedError(
							    f"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""  )





class 			_lowerCAmelCase      (			__a ):




				@add_start_docstrings(_UpperCamelCase  )
				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       **_UpperCamelCase  )       ->   jnp.ndarray:
							for processor in self:
										lowerCAmelCase_      			=			inspect.signature(processor.__call__  ).parameters
										if len(_UpperCamelCase  ) > 3:
													if not all(arg in kwargs for arg in list(function_args.keys()  )[2:]  ):
																raise ValueError(
																    f"""Make sure that all the required parameters: {list(function_args.keys()  )} for """
																    f"""{processor.__class__} are passed to the logits processor."""  )
													lowerCAmelCase_      			=			processor(_UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       **_UpperCamelCase  )
										else:
													lowerCAmelCase_      			=			processor(_UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )
							return scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase  )       ->   Tuple:
							if not isinstance(_UpperCamelCase       ,       _UpperCamelCase  ) or not (temperature > 0):
										raise ValueError(f"""`temperature` has to be a strictly positive float, but is {temperature}"""  )

							lowerCAmelCase_      			=			temperature




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							lowerCAmelCase_      			=			scores / self.temperature
							return scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase = -float("Inf"  )       ,       _UpperCamelCase = 1  )       ->   Union[str, Any]:
							if not isinstance(_UpperCamelCase       ,       _UpperCamelCase  ) or (top_p < 0 or top_p > 1.0):
										raise ValueError(f"""`top_p` has to be a float > 0 and < 1, but is {top_p}"""  )
							if not isinstance(_UpperCamelCase       ,       _UpperCamelCase  ) or (min_tokens_to_keep < 1):
										raise ValueError(f"""`min_tokens_to_keep` has to be a positive integer, but is {min_tokens_to_keep}"""  )

							lowerCAmelCase_      			=			top_p
							lowerCAmelCase_      			=			filter_value
							lowerCAmelCase_      			=			min_tokens_to_keep




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							lowerCAmelCase_			,						lowerCAmelCase_      			=			lax.top_k(_UpperCamelCase       ,       scores.shape[-1]  )

							lowerCAmelCase_      			=			jnp.full_like(_UpperCamelCase       ,       self.filter_value  )
							lowerCAmelCase_      			=			jax.nn.softmax(_UpperCamelCase       ,       axis=-1  ).cumsum(axis=-1  )
							lowerCAmelCase_      			=			cumulative_probs < self.top_p

							# include the token that is higher than top_p as well
							lowerCAmelCase_      			=			jnp.roll(_UpperCamelCase       ,       1  )
							score_mask |= score_mask.at[:, 0].set(_UpperCamelCase  )

							# min tokens to keep
							lowerCAmelCase_      			=			score_mask.at[:, : self.min_tokens_to_keep].set(_UpperCamelCase  )

							lowerCAmelCase_      			=			jnp.where(_UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			jax.lax.sort_key_val(_UpperCamelCase       ,       _UpperCamelCase  )[-1]

							return next_scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase = -float("Inf"  )       ,       _UpperCamelCase = 1  )       ->   List[Any]:
							if not isinstance(_UpperCamelCase       ,       _UpperCamelCase  ) or top_k <= 0:
										raise ValueError(f"""`top_k` has to be a strictly positive integer, but is {top_k}"""  )

							lowerCAmelCase_      			=			max(_UpperCamelCase       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			filter_value




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							lowerCAmelCase_			,						lowerCAmelCase_      			=			scores.shape
							lowerCAmelCase_      			=			jnp.full(batch_size * vocab_size       ,       self.filter_value  )

							lowerCAmelCase_      			=			min(self.top_k       ,       scores.shape[-1]  )  # Safety check
							lowerCAmelCase_			,						lowerCAmelCase_      			=			lax.top_k(_UpperCamelCase       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			jnp.broadcast_to((jnp.arange(_UpperCamelCase  ) * vocab_size)[:, None]       ,       (batch_size, topk)  ).flatten()
							lowerCAmelCase_      			=			topk_scores.flatten()
							lowerCAmelCase_      			=			topk_indices.flatten() + shift

							lowerCAmelCase_      			=			next_scores_flat.at[topk_indices_flat].set(_UpperCamelCase  )
							lowerCAmelCase_      			=			next_scores_flat.reshape(_UpperCamelCase       ,       _UpperCamelCase  )
							return next_scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase  )       ->   Any:
							lowerCAmelCase_      			=			bos_token_id




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							lowerCAmelCase_      			=			jnp.full(scores.shape       ,       -float("inf"  )  )

							lowerCAmelCase_      			=			1 - jnp.bool_(cur_len - 1  )

							lowerCAmelCase_      			=			jnp.where(_UpperCamelCase       ,       new_scores.at[:, self.bos_token_id].set(0  )       ,       _UpperCamelCase  )

							return scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   List[str]:
							lowerCAmelCase_      			=			max_length
							lowerCAmelCase_      			=			eos_token_id




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							lowerCAmelCase_      			=			jnp.full(scores.shape       ,       -float("inf"  )  )

							lowerCAmelCase_      			=			1 - jnp.bool_(cur_len - self.max_length + 1  )

							lowerCAmelCase_      			=			jnp.where(_UpperCamelCase       ,       new_scores.at[:, self.eos_token_id].set(0  )       ,       _UpperCamelCase  )

							return scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   Optional[int]:
							if not isinstance(_UpperCamelCase       ,       _UpperCamelCase  ) or min_length < 0:
										raise ValueError(f"""`min_length` has to be a positive integer, but is {min_length}"""  )

							if not isinstance(_UpperCamelCase       ,       _UpperCamelCase  ) or eos_token_id < 0:
										raise ValueError(f"""`eos_token_id` has to be a positive integer, but is {eos_token_id}"""  )

							lowerCAmelCase_      			=			min_length
							lowerCAmelCase_      			=			eos_token_id




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							# create boolean flag to decide if min length penalty should be applied
							lowerCAmelCase_      			=			1 - jnp.clip(cur_len - self.min_length       ,       0       ,       1  )

							lowerCAmelCase_      			=			jnp.where(_UpperCamelCase       ,       scores.at[:, self.eos_token_id].set(-float("inf"  )  )       ,       _UpperCamelCase  )

							return scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   int:
							lowerCAmelCase_      			=			list(_UpperCamelCase  )
							lowerCAmelCase_      			=			begin_index




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   int:
							lowerCAmelCase_      			=			1 - jnp.bool_(cur_len - self.begin_index  )

							lowerCAmelCase_      			=			jnp.where(_UpperCamelCase       ,       scores.at[:, self.begin_suppress_tokens].set(-float("inf"  )  )       ,       _UpperCamelCase  )

							return scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase  )       ->   Optional[Any]:
							lowerCAmelCase_      			=			list(_UpperCamelCase  )




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							lowerCAmelCase_      			=			scores.at[..., self.suppress_tokens].set(-float("inf"  )  )

							return scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase  )       ->   List[Any]:
							lowerCAmelCase_      			=			dict(_UpperCamelCase  )
							# Converts the dictionary of format {index: token} containing the tokens to be forced to an array, where the
							# index of the array corresponds to the index of the token to be forced, for XLA compatibility.
							# Indexes without forced tokens will have a negative value.
							lowerCAmelCase_      			=			jnp.ones((max(force_token_map.keys()  ) + 1)       ,       dtype=jnp.intaa  ) * -1
							for index, token in force_token_map.items():
										if token is not None:
													lowerCAmelCase_      			=			force_token_array.at[index].set(_UpperCamelCase  )
							lowerCAmelCase_      			=			jnp.intaa(_UpperCamelCase  )




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   jnp.ndarray:
							def _force_token(_UpperCamelCase  ):
										lowerCAmelCase_      			=			scores.shape[0]
										lowerCAmelCase_      			=			self.force_token_array[generation_idx]

										lowerCAmelCase_      			=			jnp.ones_like(_UpperCamelCase       ,       dtype=scores.dtype  ) * -float("inf"  )
										lowerCAmelCase_      			=			jnp.zeros((batch_size, 1)       ,       dtype=scores.dtype  )
										lowerCAmelCase_      			=			lax.dynamic_update_slice(_UpperCamelCase       ,       _UpperCamelCase       ,       (0, current_token)  )
										return new_scores

							lowerCAmelCase_      			=			lax.cond(
							    cur_len >= self.force_token_array.shape[0]       ,       lambda: scores       ,       lambda: lax.cond(
							        self.force_token_array[cur_len] >= 0       ,       lambda: _force_token(_UpperCamelCase  )       ,       lambda: scores       ,       )       ,       )
							return scores





class 			_lowerCAmelCase      (			__a ):




				def __init__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   Tuple:
							lowerCAmelCase_      			=			generate_config.eos_token_id
							lowerCAmelCase_      			=			generate_config.no_timestamps_token_id
							lowerCAmelCase_      			=			generate_config.no_timestamps_token_id + 1

							lowerCAmelCase_      			=			decoder_input_length + 1

							if generate_config.is_multilingual:
										# room for language token and task token
										self.begin_index += 2
							if hasattr(_UpperCamelCase       ,       "max_initial_timestamp_index"  ):
										lowerCAmelCase_      			=			generate_config.max_initial_timestamp_index
							else:
										lowerCAmelCase_      			=			model_config.vocab_size
							if self.max_initial_timestamp_index is None:
										lowerCAmelCase_      			=			model_config.vocab_size




				def __call__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   Optional[Any]:
							# suppress <|notimestamps|> which is handled by without_timestamps
							lowerCAmelCase_      			=			scores.at[:, self.no_timestamps_token_id].set(-float("inf"  )  )

							def handle_pairs(_UpperCamelCase       ,       _UpperCamelCase  ):
										lowerCAmelCase_      			=			jnp.where((cur_len - self.begin_index) >= 1       ,       _UpperCamelCase       ,       _UpperCamelCase  )
										lowerCAmelCase_      			=			jnp.where(
										    input_ids_k[cur_len - 1] >= self.timestamp_begin       ,       True and last_was_timestamp       ,       _UpperCamelCase       ,       )

										lowerCAmelCase_      			=			jnp.where((cur_len - self.begin_index) < 2       ,       _UpperCamelCase       ,       _UpperCamelCase  )
										lowerCAmelCase_      			=			jnp.where(
										    input_ids_k[cur_len - 2] >= self.timestamp_begin       ,       _UpperCamelCase       ,       _UpperCamelCase       ,       )

										return jnp.where(
										    _UpperCamelCase       ,       jnp.where(
										        penultimate_was_timestamp > 0       ,       scores_k.at[self.timestamp_begin :].set(-float("inf"  )  )       ,       scores_k.at[: self.eos_token_id].set(-float("inf"  )  )       ,       )       ,       _UpperCamelCase       ,       )

							lowerCAmelCase_      			=			jax.vmap(_UpperCamelCase  )(_UpperCamelCase       ,       _UpperCamelCase  )

							lowerCAmelCase_      			=			jnp.where(cur_len == self.begin_index       ,       _UpperCamelCase       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			jnp.where(
							    self.max_initial_timestamp_index is not None       ,       True and apply_max_initial_timestamp       ,       _UpperCamelCase       ,       )

							lowerCAmelCase_      			=			self.timestamp_begin + self.max_initial_timestamp_index

							lowerCAmelCase_      			=			jnp.where(
							    _UpperCamelCase       ,       scores.at[:, last_allowed + 1 :].set(-float("inf"  )  )       ,       _UpperCamelCase       ,       )

							# if sum of probability over timestamps is above any other token, sample timestamp
							lowerCAmelCase_      			=			jax.nn.log_softmax(_UpperCamelCase       ,       axis=-1  )

							def handle_cumulative_probs(_UpperCamelCase       ,       _UpperCamelCase  ):
										lowerCAmelCase_      			=			jax.nn.logsumexp(logprobs_k[self.timestamp_begin :]       ,       axis=-1  )
										lowerCAmelCase_      			=			jnp.max(logprobs_k[: self.timestamp_begin]  )
										return jnp.where(
										    timestamp_logprob > max_text_token_logprob       ,       scores_k.at[: self.timestamp_begin].set(-float("inf"  )  )       ,       _UpperCamelCase       ,       )

							lowerCAmelCase_      			=			jax.vmap(_UpperCamelCase  )(_UpperCamelCase       ,       _UpperCamelCase  )

							return scores



