

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 					_lowercase     (				)				->	List[str]:




					'''simple docstring'''







					__magic_name__							=    1_0
					__magic_name__							=    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'				),
					    }				)
					__magic_name__							=    datasets.Dataset.from_dict(
					    {
					        'tokens': [['foo'] * 5] * n,
					        'labels': [[1] * 5] * n,
					        'answers': [{'answer_start': [9_7], 'text': ['1976']}] * 1_0,
					        'id': list(range(a_				)				),
					    }					,features=a_					,)
					return dataset




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					str					,a_				:					int				)				->	str:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					Union[str, Any]				)				->	int:




					'''simple docstring'''







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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					List[Any]				)				->	Union[str, Any]:




					'''simple docstring'''







					import bza

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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					Dict				)				->	Any:




					'''simple docstring'''







					import gzip

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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					Optional[Any]				)				->	List[Any]:




					'''simple docstring'''







					if datasets.config.LZ4_AVAILABLE:
										import lza.frame

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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					Optional[Any]					,a_				:					List[Any]				)				->	List[Any]:




					'''simple docstring'''







					if datasets.config.PY7ZR_AVAILABLE:
										import pyazr

										__magic_name__							=    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 					_lowercase     (				a_				:					str					,a_				:					Union[str, Any]				)				->	Optional[Any]:




					'''simple docstring'''







					import tarfile

					__magic_name__							=    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 					_lowercase     (				a_				:					int				)				->	Dict:




					'''simple docstring'''







					import lzma

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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					int					,a_				:					Union[str, Any]				)				->	Optional[int]:




					'''simple docstring'''







					import zipfile

					__magic_name__							=    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 					_lowercase     (				a_				:					Optional[Any]				)				->	Any:




					'''simple docstring'''







					if datasets.config.ZSTANDARD_AVAILABLE:
										import zstandard as zstd

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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					Union[str, Any]				)				->	Optional[int]:




					'''simple docstring'''







					__magic_name__							=    tmp_path_factory.mktemp('data'				) / 'file.xml'
					__magic_name__							=    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 					_lowercase     (				)				->	str:




					'''simple docstring'''







					return DATA_DICT_OF_LISTS




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					List[str]				)				->	List[Any]:




					'''simple docstring'''







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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					List[Any]				)				->	List[Any]:




					'''simple docstring'''







					__magic_name__							=    str(tmp_path_factory.mktemp('data'				) / 'dataset.sqlite'				)
					with contextlib.closing(sqlitea.connect(a_				)				) as con:
										__magic_name__							=    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 					_lowercase     (				a_				:					str				)				->	Dict:




					'''simple docstring'''







					__magic_name__							=    str(tmp_path_factory.mktemp('data'				) / 'dataset.csv'				)
					with open(a_					,'w'					,newline=''				) as f:
										__magic_name__							=    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 					_lowercase     (				a_				:					str				)				->	Tuple:




					'''simple docstring'''







					__magic_name__							=    str(tmp_path_factory.mktemp('data'				) / 'dataset2.csv'				)
					with open(a_					,'w'					,newline=''				) as f:
										__magic_name__							=    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 					_lowercase     (				a_				:					Optional[int]					,a_				:					Optional[Any]				)				->	List[str]:




					'''simple docstring'''







					import bza

					__magic_name__							=    tmp_path_factory.mktemp('data'				) / 'dataset.csv.bz2'
					with open(a_					,'rb'				) as f:
										__magic_name__							=    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 					_lowercase     (				a_				:					Tuple					,a_				:					Dict					,a_				:					Any				)				->	Union[str, Any]:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					Tuple					,a_				:					Optional[int]					,a_				:					Tuple				)				->	List[Any]:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					str					,a_				:					Optional[Any]					,a_				:					List[Any]				)				->	Tuple:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					List[Any]				)				->	Optional[Any]:




					'''simple docstring'''







					__magic_name__							=    str(tmp_path_factory.mktemp('data'				) / 'dataset.parquet'				)
					__magic_name__							=    pa.schema(
					    {
					        'col_1': pa.string(),
					        'col_2': pa.intaa(),
					        'col_3': pa.floataa(),
					    }				)
					with open(a_					,'wb'				) as f:
										__magic_name__							=    pq.ParquetWriter(a_					,schema=a_				)
										__magic_name__							=    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 					_lowercase     (				a_				:					List[str]				)				->	Union[str, Any]:




					'''simple docstring'''







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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					Dict				)				->	List[str]:




					'''simple docstring'''







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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					List[Any]				)				->	Dict:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					Tuple				)				->	int:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					Tuple				)				->	Dict:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					List[Any]				)				->	Any:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					Optional[int]					,a_				:					Optional[int]				)				->	Tuple:




					'''simple docstring'''







					import gzip

					__magic_name__							=    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 					_lowercase     (				a_				:					Dict					,a_				:					Dict				)				->	List[str]:




					'''simple docstring'''







					import gzip

					__magic_name__							=    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 					_lowercase     (				a_				:					Dict					,a_				:					Dict					,a_				:					Any				)				->	int:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					int					,a_				:					int					,a_				:					List[str]					,a_				:					Union[str, Any]				)				->	Tuple:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					Union[str, Any]					,a_				:					str					,a_				:					int				)				->	Optional[Any]:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					int					,a_				:					Dict					,a_				:					Dict				)				->	List[str]:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					str					,a_				:					int					,a_				:					Any					,a_				:					Any				)				->	Optional[Any]:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					Any				)				->	Optional[Any]:




					'''simple docstring'''







					__magic_name__							=    ['0', '1', '2', '3']
					__magic_name__							=    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 					_lowercase     (				a_				:					List[Any]				)				->	Optional[Any]:




					'''simple docstring'''







					__magic_name__							=    ['0', '1', '2', '3']
					__magic_name__							=    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 					_lowercase     (				a_				:					str				)				->	Any:




					'''simple docstring'''







					__magic_name__							=    ['0', '1', '2', '3']
					__magic_name__							=    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 					_lowercase     (				a_				:					Union[str, Any]					,a_				:					int					,a_				:					str				)				->	Any:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					Tuple					,a_				:					str					,a_				:					List[Any]				)				->	Union[str, Any]:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					str					,a_				:					Dict					,a_				:					Union[str, Any]				)				->	List[str]:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					List[str]				)				->	Tuple:




					'''simple docstring'''







					__magic_name__							=    '\n'.join(['First', 'Second\u2029with Unicode new line', 'Third']				)
					__magic_name__							=    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 					_lowercase     (				)				->	Dict:




					'''simple docstring'''







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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				)				->	Optional[Any]:




					'''simple docstring'''







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




@pytest.fixture(scope='session'				)
def 					_lowercase     (				a_				:					List[Any]					,a_				:					List[str]				)				->	Tuple:




					'''simple docstring'''







					__magic_name__							=    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 					_lowercase     (				a_				:					int				)				->	Any:




					'''simple docstring'''







					__magic_name__							=    tmp_path_factory.mktemp('data_dir'				)

					(data_dir / "subdir").mkdir()
					with open(data_dir / 'subdir' / 'train.txt'					,'w'				) as f:
										f.write('foo\n' * 1_0				)
					with open(data_dir / 'subdir' / 'test.txt'					,'w'				) as f:
										f.write('bar\n' * 1_0				)
					# hidden file
					with open(data_dir / 'subdir' / '.test.txt'					,'w'				) as f:
										f.write('bar\n' * 1_0				)

					# hidden directory
					(data_dir / ".subdir").mkdir()
					with open(data_dir / '.subdir' / 'train.txt'					,'w'				) as f:
										f.write('foo\n' * 1_0				)
					with open(data_dir / '.subdir' / 'test.txt'					,'w'				) as f:
										f.write('bar\n' * 1_0				)

					return data_dir







import argparse
from pathlib import Path

from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration




def 					_lowercase     (				a_				:					str					,a_				:					str					,a_				:					str					,a_				:					Path					,a_				:					str = None					,a_				:					str = None					,a_				:					str = None					,)				->	Tuple:




					'''simple docstring'''







					if config_name_or_path is None:
										__magic_name__							=    'facebook/rag-token-base' if model_type == 'rag_token' else 'facebook/rag-sequence-base'

					if generator_tokenizer_name_or_path is None:
										__magic_name__							=    generator_name_or_path

					if question_encoder_tokenizer_name_or_path is None:
										__magic_name__							=    question_encoder_name_or_path

					__magic_name__							=    RagTokenForGeneration if model_type == 'rag_token' else RagSequenceForGeneration

					# Save model.
					__magic_name__							=    RagConfig.from_pretrained(a_				)
					__magic_name__							=    AutoConfig.from_pretrained(a_				)
					__magic_name__							=    AutoConfig.from_pretrained(a_				)

					__magic_name__							=    gen_config
					__magic_name__							=    question_encoder_config

					__magic_name__							=    model_class.from_pretrained_question_encoder_generator(
					    a_					,a_					,config=a_				)
					rag_model.save_pretrained(a_				)

					# Sanity check.
					model_class.from_pretrained(a_				)

					# Save tokenizers.
					__magic_name__							=    AutoTokenizer.from_pretrained(a_				)
					gen_tokenizer.save_pretrained(dest_dir / 'generator_tokenizer/'				)
					__magic_name__							=    AutoTokenizer.from_pretrained(a_				)
					question_encoder_tokenizer.save_pretrained(dest_dir / 'question_encoder_tokenizer/'				)


if __name__ == "__main__":
						A__						=							argparse.ArgumentParser()
						parser.add_argument(
						    "--model_type",
						    choices=["rag_sequence", "rag_token"],
						    required=True,
						    type=str,
						    help="RAG model type: rag_sequence, rag_token",
						)
						parser.add_argument("--dest", type=str, required=True, help="Path to the output checkpoint directory.")
						parser.add_argument("--generator_name_or_path", type=str, required=True, help="Generator model identifier")
						parser.add_argument(
						    "--question_encoder_name_or_path", type=str, required=True, help="Question encoder model identifier"
						)

						parser.add_argument(
						    "--generator_tokenizer_name_or_path",
						    type=str,
						    help="Generator tokenizer identifier, if not specified, resolves to ``generator_name_or_path``",
						)
						parser.add_argument(
						    "--question_encoder_tokenizer_name_or_path",
						    type=str,
						    help="Question encoder tokenizer identifier, if not specified, resolves to ``question_encoder_name_or_path``",
						)
						parser.add_argument(
						    "--config_name_or_path",
						    type=str,
						    help=(
						        "Identifier of the model config to use, if not provided, resolves to a base config for a given"
						        " ``model_type``"
						    ),
						)

						A__						=							parser.parse_args()

						A__						=							Path(args.dest)
						dest_dir.mkdir(exist_ok=True)

						consolidate(
						    args.model_type,
						    args.generator_name_or_path,
						    args.question_encoder_name_or_path,
						    dest_dir,
						    args.config_name_or_path,
						    args.generator_tokenizer_name_or_path,
						    args.question_encoder_tokenizer_name_or_path,
						)




