





'''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 				UpperCAmelCase_     (						):

				"""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(lowerCamelCase__				)				),
				    }		,				features=lowerCamelCase__		,				)
				return dataset







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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


# FILE_CONTENT + files


__lowerCamelCase			:			Dict									=      "\\n    Text data.\n    Second line of data."







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

				"""simple docstring"""






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







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

				"""simple docstring"""






				import bza

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







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

				"""simple docstring"""






				import gzip

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







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

				"""simple docstring"""






				if datasets.config.LZ4_AVAILABLE:
								import lza.frame

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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






				if datasets.config.PY7ZR_AVAILABLE:
								import pyazr

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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






				import tarfile

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







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

				"""simple docstring"""






				import lzma

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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






				import zipfile

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







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

				"""simple docstring"""






				if datasets.config.ZSTANDARD_AVAILABLE:
								import zstandard as zstd

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







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

				"""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(lowerCamelCase__		,				"w"				) as f:
								f.write(lowerCamelCase__				)
				return filename


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

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

__lowerCamelCase			:			List[str]									=      [
    {"col_1": "s0", "col_2": 0, "col_3": 0.0},
    {"col_1": "s1", "col_2": 1, "col_3": 1.0},
    {"col_1": "s2", "col_2": 2, "col_3": 2.0},
    {"col_1": "s3", "col_2": 3, "col_3": 3.0},
]







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

				"""simple docstring"""






				return DATA_DICT_OF_LISTS







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

				"""simple docstring"""






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







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

				"""simple docstring"""






				lowercase    =			str(tmp_path_factory.mktemp("data"				) / "dataset.sqlite"				)
				with contextlib.closing(sqlitea.connect(lowerCamelCase__				)				) 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 				UpperCAmelCase_     (						lowerCAmelCase_				):

				"""simple docstring"""






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







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

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






				import bza

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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







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

				"""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(lowerCamelCase__		,				"wb"				) as f:
								lowercase    =			pq.ParquetWriter(lowerCamelCase__		,				schema=lowerCamelCase__				)
								lowercase    =			pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(lowerCamelCase__				)				)] for k in DATA[0]}		,				schema=lowerCamelCase__				)
								writer.write_table(lowerCamelCase__				)
								writer.close()
				return path







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

				"""simple docstring"""






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







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

				"""simple docstring"""






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







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

				"""simple docstring"""






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







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

				"""simple docstring"""






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







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

				"""simple docstring"""






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







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

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






				import gzip

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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






				import gzip

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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







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

				"""simple docstring"""






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







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

				"""simple docstring"""






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







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

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







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

				"""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(lowerCamelCase__		,				"w"		,				encoding="utf-8"				) as f:
								f.write(lowerCamelCase__				)
				return path







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

				"""simple docstring"""






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







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

				"""simple docstring"""






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







@pytest.fixture(scope="session"				)
def 				UpperCAmelCase_     (						lowerCAmelCase_		,				lowerCAmelCase_				):

				"""simple docstring"""






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







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

				"""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"""


import argparse
import pathlib

import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version

from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaXLForSequenceClassification
from transformers.models.bert.modeling_bert import (
    BertIntermediate,
    BertLayer,
    BertOutput,
    BertSelfAttention,
    BertSelfOutput,
)
from transformers.models.roberta.modeling_roberta import RobertaAttention
from transformers.utils import logging


if version.parse(fairseq.__version__) < version.parse('1.0.0a'):
   raise Exception('requires fairseq >= 1.0.0a')

logging.set_verbosity_info()
__snake_case    					=					logging.get_logger(__name__)

__snake_case    					=					'Hello world! cécé herlolip'


def    _lowerCamelCase   (     lowerCamelCase__	:							str       ,		lowerCamelCase__	:							str       ,		lowerCamelCase__	:							bool  ):
 lowercase__       :       int				=						FairseqRobertaModel.from_pretrained(lowerCamelCase__  )
 roberta.eval()  # disable dropout
 lowercase__       :       Tuple				=						roberta.model.encoder.sentence_encoder
 lowercase__       :       Tuple				=						XLMRobertaConfig(
     vocab_size=roberta_sent_encoder.embed_tokens.num_embeddings       ,		hidden_size=roberta.cfg.model.encoder_embed_dim       ,		num_hidden_layers=roberta.cfg.model.encoder_layers       ,		num_attention_heads=roberta.cfg.model.encoder_attention_heads       ,		intermediate_size=roberta.cfg.model.encoder_ffn_embed_dim       ,		max_position_embeddings=5_14       ,		type_vocab_size=1       ,		layer_norm_eps=1E-5       ,		)
 if classification_head:
  lowercase__       :       Any				=						roberta.model.classification_heads["""mnli"""].out_proj.weight.shape[0]

 print("""Our RoBERTa config:"""       ,		lowerCamelCase__  )

 lowercase__       :       List[Any]				=						XLMRobertaXLForSequenceClassification(lowerCamelCase__  ) if classification_head else XLMRobertaXLForMaskedLM(lowerCamelCase__  )
 model.eval()

 # Now let's copy all the weights.
 # Embeddings
 lowercase__       :       int				=						roberta_sent_encoder.embed_tokens.weight
 lowercase__       :       Union[str, Any]				=						roberta_sent_encoder.embed_positions.weight
 lowercase__       :       int				=						torch.zeros_like(
     model.roberta.embeddings.token_type_embeddings.weight  )  # just zero them out b/c RoBERTa doesn't use them.

 lowercase__       :       int				=						roberta_sent_encoder.layer_norm.weight
 lowercase__       :       List[Any]				=						roberta_sent_encoder.layer_norm.bias

 for i in range(config.num_hidden_layers  ):
  # Encoder: start of layer
  lowercase__       :       BertLayer				=						model.roberta.encoder.layer[i]
  lowercase__       :       TransformerSentenceEncoderLayer				=						roberta_sent_encoder.layers[i]

  lowercase__       :       RobertaAttention				=						layer.attention
  lowercase__       :       str				=						roberta_layer.self_attn_layer_norm.weight
  lowercase__       :       Union[str, Any]				=						roberta_layer.self_attn_layer_norm.bias

  # self attention
  lowercase__       :       BertSelfAttention				=						layer.attention.self
  assert (
      roberta_layer.self_attn.k_proj.weight.data.shape
      == roberta_layer.self_attn.q_proj.weight.data.shape
      == roberta_layer.self_attn.v_proj.weight.data.shape
      == torch.Size((config.hidden_size, config.hidden_size)  )
  )

  lowercase__       :       Optional[Any]				=						roberta_layer.self_attn.q_proj.weight
  lowercase__       :       str				=						roberta_layer.self_attn.q_proj.bias
  lowercase__       :       Optional[int]				=						roberta_layer.self_attn.k_proj.weight
  lowercase__       :       Optional[int]				=						roberta_layer.self_attn.k_proj.bias
  lowercase__       :       int				=						roberta_layer.self_attn.v_proj.weight
  lowercase__       :       Union[str, Any]				=						roberta_layer.self_attn.v_proj.bias

  # self-attention output
  lowercase__       :       BertSelfOutput				=						layer.attention.output
  assert self_output.dense.weight.shape == roberta_layer.self_attn.out_proj.weight.shape
  lowercase__       :       Any				=						roberta_layer.self_attn.out_proj.weight
  lowercase__       :       Optional[int]				=						roberta_layer.self_attn.out_proj.bias

  # this one is final layer norm
  lowercase__       :       Optional[Any]				=						roberta_layer.final_layer_norm.weight
  lowercase__       :       Any				=						roberta_layer.final_layer_norm.bias

  # intermediate
  lowercase__       :       BertIntermediate				=						layer.intermediate
  assert intermediate.dense.weight.shape == roberta_layer.fca.weight.shape
  lowercase__       :       Dict				=						roberta_layer.fca.weight
  lowercase__       :       Any				=						roberta_layer.fca.bias

  # output
  lowercase__       :       BertOutput				=						layer.output
  assert bert_output.dense.weight.shape == roberta_layer.fca.weight.shape
  lowercase__       :       Union[str, Any]				=						roberta_layer.fca.weight
  lowercase__       :       Optional[Any]				=						roberta_layer.fca.bias
  # end of layer

 if classification_head:
  lowercase__       :       Optional[Any]				=						roberta.model.classification_heads["""mnli"""].dense.weight
  lowercase__       :       str				=						roberta.model.classification_heads["""mnli"""].dense.bias
  lowercase__       :       str				=						roberta.model.classification_heads["""mnli"""].out_proj.weight
  lowercase__       :       List[str]				=						roberta.model.classification_heads["""mnli"""].out_proj.bias
 else:
  # LM Head
  lowercase__       :       Tuple				=						roberta.model.encoder.lm_head.dense.weight
  lowercase__       :       int				=						roberta.model.encoder.lm_head.dense.bias
  lowercase__       :       Any				=						roberta.model.encoder.lm_head.layer_norm.weight
  lowercase__       :       Union[str, Any]				=						roberta.model.encoder.lm_head.layer_norm.bias
  lowercase__       :       Dict				=						roberta.model.encoder.lm_head.weight
  lowercase__       :       List[Any]				=						roberta.model.encoder.lm_head.bias

 # Let's check that we get the same results.
 lowercase__       :       torch.Tensor				=						roberta.encode(lowerCamelCase__  ).unsqueeze(0  )  # batch of size 1

 lowercase__       :       Any				=						model(lowerCamelCase__  )[0]
 if classification_head:
  lowercase__       :       Optional[Any]				=						roberta.model.classification_heads["""mnli"""](roberta.extract_features(lowerCamelCase__  )  )
 else:
  lowercase__       :       Tuple				=						roberta.model(lowerCamelCase__  )[0]
 print(our_output.shape       ,		their_output.shape  )
 lowercase__       :       Tuple				=						torch.max(torch.abs(our_output - their_output  )  ).item()
 print(f'''max_absolute_diff = {max_absolute_diff}'''  )  # ~ 1e-7
 lowercase__       :       int				=						torch.allclose(lowerCamelCase__       ,		lowerCamelCase__       ,		atol=1E-3  )
 print("""Do both models output the same tensors?"""       ,		"""🔥""" if success else """💩"""  )
 if not success:
  raise Exception("""Something went wRoNg"""  )

 pathlib.Path(lowerCamelCase__  ).mkdir(parents=lowerCamelCase__       ,		exist_ok=lowerCamelCase__  )
 print(f'''Saving model to {pytorch_dump_folder_path}'''  )
 model.save_pretrained(lowerCamelCase__  )


if __name__ == "__main__":
   __snake_case    					=					argparse.ArgumentParser()
   # Required parameters
   parser.add_argument(
       '--roberta_checkpoint_path', default=None, type=str, required=True, help='Path the official PyTorch dump.'
   )
   parser.add_argument(
       '--pytorch_dump_folder_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
   )
   parser.add_argument(
       '--classification_head', action='store_true', help='Whether to convert a final classification head.'
   )
   __snake_case    					=					parser.parse_args()
   convert_xlm_roberta_xl_checkpoint_to_pytorch(
       args.roberta_checkpoint_path, args.pytorch_dump_folder_path, args.classification_head
   )