


"""simple docstring"""




import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__magic_name__						: Optional[int]    =				get_tests_dir('fixtures/test_sentencepiece.model')




@require_sentencepiece
@require_tokenizers
class 			__snake_case   (lowerCamelCase			,		unittest.TestCase  ):
							__a					 =       XLMRobertaTokenizer
							__a					 =       XLMRobertaTokenizerFast
							__a					 =       True
							__a					 =       True




							def   __a   (     self:    List[str]   ):
										super().setUp()

										# We have a SentencePiece fixture for testing
										__lowerCamelCase          =      XLMRobertaTokenizer(A_     ,							keep_accents=A_   )
										tokenizer.save_pretrained(self.tmpdirname   )




							def   __a   (     self:    int   ):
										__lowerCamelCase          =      """<pad>"""
										__lowerCamelCase          =      1

										self.assertEqual(self.get_tokenizer()._convert_token_to_id(A_   )     ,							A_   )
										self.assertEqual(self.get_tokenizer()._convert_id_to_token(A_   )     ,							A_   )




							def   __a   (     self:    Dict   ):
										__lowerCamelCase          =      list(self.get_tokenizer().get_vocab().keys()   )

										self.assertEqual(vocab_keys[0]     ,							"""<s>"""   )
										self.assertEqual(vocab_keys[1]     ,							"""<pad>"""   )
										self.assertEqual(vocab_keys[-1]     ,							"""<mask>"""   )
										self.assertEqual(len(A_   )     ,							10_02   )




							def   __a   (     self:    Optional[Any]   ):
										self.assertEqual(self.get_tokenizer().vocab_size     ,							10_02   )




							def   __a   (     self:    int   ):
										__lowerCamelCase          =      XLMRobertaTokenizer(A_     ,							keep_accents=A_   )

										__lowerCamelCase          =      tokenizer.tokenize("""This is a test"""   )
										self.assertListEqual(A_     ,							["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]   )

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(A_   )     ,							[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]     ,							)

										__lowerCamelCase          =      tokenizer.tokenize("""I was born in 92000, and this is falsé."""   )
										self.assertListEqual(
										    A_     ,							[
										        SPIECE_UNDERLINE + """I""",
										        SPIECE_UNDERLINE + """was""",
										        SPIECE_UNDERLINE + """b""",
										        """or""",
										        """n""",
										        SPIECE_UNDERLINE + """in""",
										        SPIECE_UNDERLINE + """""",
										        """9""",
										        """2""",
										        """0""",
										        """0""",
										        """0""",
										        """,""",
										        SPIECE_UNDERLINE + """and""",
										        SPIECE_UNDERLINE + """this""",
										        SPIECE_UNDERLINE + """is""",
										        SPIECE_UNDERLINE + """f""",
										        """al""",
										        """s""",
										        """é""",
										        """.""",
										    ]     ,							)
										__lowerCamelCase          =      tokenizer.convert_tokens_to_ids(A_   )
										self.assertListEqual(
										    A_     ,							[
										        value + tokenizer.fairseq_offset
										        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
										        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
										    ]     ,							)

										__lowerCamelCase          =      tokenizer.convert_ids_to_tokens(A_   )
										self.assertListEqual(
										    A_     ,							[
										        SPIECE_UNDERLINE + """I""",
										        SPIECE_UNDERLINE + """was""",
										        SPIECE_UNDERLINE + """b""",
										        """or""",
										        """n""",
										        SPIECE_UNDERLINE + """in""",
										        SPIECE_UNDERLINE + """""",
										        """<unk>""",
										        """2""",
										        """0""",
										        """0""",
										        """0""",
										        """,""",
										        SPIECE_UNDERLINE + """and""",
										        SPIECE_UNDERLINE + """this""",
										        SPIECE_UNDERLINE + """is""",
										        SPIECE_UNDERLINE + """f""",
										        """al""",
										        """s""",
										        """<unk>""",
										        """.""",
										    ]     ,							)




							def   __a   (     self:    Dict   ):
										if not self.test_slow_tokenizer:
													# as we don't have a slow version, we can't compare the outputs between slow and fast versions
													return

										__lowerCamelCase          =      (self.rust_tokenizer_class, """hf-internal-testing/tiny-xlm-roberta""", {})
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'   ):
																__lowerCamelCase          =      self.rust_tokenizer_class.from_pretrained(A_     ,							**A_   )
																__lowerCamelCase          =      self.tokenizer_class.from_pretrained(A_     ,							**A_   )

																__lowerCamelCase          =      tempfile.mkdtemp()

																__lowerCamelCase          =      tokenizer_r.save_pretrained(A_   )
																__lowerCamelCase          =      tokenizer_p.save_pretrained(A_   )

																# Checks it save with the same files + the tokenizer.json file for the fast one
																self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files   )   )
																__lowerCamelCase          =      tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f   )
																self.assertSequenceEqual(A_     ,							A_   )

																# Checks everything loads correctly in the same way
																__lowerCamelCase          =      tokenizer_r.from_pretrained(A_   )
																__lowerCamelCase          =      tokenizer_p.from_pretrained(A_   )

																# Check special tokens are set accordingly on Rust and Python
																for key in tokenizer_pp.special_tokens_map:
																			self.assertTrue(hasattr(A_     ,							A_   )   )
																			# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																			# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																shutil.rmtree(A_   )

																# Save tokenizer rust, legacy_format=True
																__lowerCamelCase          =      tempfile.mkdtemp()

																__lowerCamelCase          =      tokenizer_r.save_pretrained(A_     ,							legacy_format=A_   )
																__lowerCamelCase          =      tokenizer_p.save_pretrained(A_   )

																# Checks it save with the same files
																self.assertSequenceEqual(A_     ,							A_   )

																# Checks everything loads correctly in the same way
																__lowerCamelCase          =      tokenizer_r.from_pretrained(A_   )
																__lowerCamelCase          =      tokenizer_p.from_pretrained(A_   )

																# Check special tokens are set accordingly on Rust and Python
																for key in tokenizer_pp.special_tokens_map:
																			self.assertTrue(hasattr(A_     ,							A_   )   )

																shutil.rmtree(A_   )

																# Save tokenizer rust, legacy_format=False
																__lowerCamelCase          =      tempfile.mkdtemp()

																__lowerCamelCase          =      tokenizer_r.save_pretrained(A_     ,							legacy_format=A_   )
																__lowerCamelCase          =      tokenizer_p.save_pretrained(A_   )

																# Checks it saved the tokenizer.json file
																self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files   )   )

																# Checks everything loads correctly in the same way
																__lowerCamelCase          =      tokenizer_r.from_pretrained(A_   )
																__lowerCamelCase          =      tokenizer_p.from_pretrained(A_   )

																# Check special tokens are set accordingly on Rust and Python
																for key in tokenizer_pp.special_tokens_map:
																			self.assertTrue(hasattr(A_     ,							A_   )   )

																shutil.rmtree(A_   )




							@cached_property
							def   __a   (     self:    Union[str, Any]   ):
										return XLMRobertaTokenizer.from_pretrained("""xlm-roberta-base"""   )




							def   __a   (     self:    Union[str, Any]   ):
										with tempfile.NamedTemporaryFile() as f:
													shutil.copyfile(A_     ,							f.name   )
													__lowerCamelCase          =      XLMRobertaTokenizer(f.name     ,							keep_accents=A_   )
													__lowerCamelCase          =      pickle.dumps(A_   )
										pickle.loads(A_   )




							def   __a   (     self:    Union[str, Any]   ):
										if not self.test_rust_tokenizer:
													return

										__lowerCamelCase          =      self.get_tokenizer()
										__lowerCamelCase          =      self.get_rust_tokenizer()

										__lowerCamelCase          =      """I was born in 92000, and this is falsé."""

										__lowerCamelCase          =      tokenizer.tokenize(A_   )
										__lowerCamelCase          =      rust_tokenizer.tokenize(A_   )
										self.assertListEqual(A_     ,							A_   )

										__lowerCamelCase          =      tokenizer.encode(A_     ,							add_special_tokens=A_   )
										__lowerCamelCase          =      rust_tokenizer.encode(A_     ,							add_special_tokens=A_   )
										self.assertListEqual(A_     ,							A_   )

										__lowerCamelCase          =      self.get_rust_tokenizer()
										__lowerCamelCase          =      tokenizer.encode(A_   )
										__lowerCamelCase          =      rust_tokenizer.encode(A_   )
										self.assertListEqual(A_     ,							A_   )




							@slow
							def   __a   (     self:    int   ):
										__lowerCamelCase          =      """Hello World!"""
										__lowerCamelCase          =      [0, 3_53_78, 66_61, 38, 2]
										# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
										# xlmr.eval()
										# xlmr.encode(symbols)

										self.assertListEqual(A_     ,							self.big_tokenizer.encode(A_   )   )




							@slow
							def   __a   (     self:    List[str]   ):
										__lowerCamelCase          =      (
										    """This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"""
										    """ add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"""
										)
										__lowerCamelCase          =      [
										    0,
										    32_93,
										    83,
										    10,
										    45_52,
										    49_89,
										    79_86,
										    6_78,
										    10,
										    59_15,
										    1_11,
										    17_94_59,
										    12_48_50,
										    4,
										    60_44,
										    2_37,
										    12,
										    6,
										    5,
										    6,
										    4,
										    67_80,
										    7_05,
										    15,
										    13_88,
										    44,
										    3_78,
										    1_01_14,
										    7_11,
										    1_52,
										    20,
										    6,
										    5,
										    2_23_76,
										    6_42,
										    12_21,
										    1_51_90,
										    3_41_53,
										    4_50,
										    56_08,
										    9_59,
										    11_19,
										    5_77_02,
										    1_36,
										    1_86,
										    47,
										    10_98,
										    2_93_67,
										    47,
										    # 4426, # What fairseq tokenizes from "<unk>": "_<"
										    # 3678, # What fairseq tokenizes from "<unk>": "unk"
										    # 2740, # What fairseq tokenizes from "<unk>": ">"
										    3,  # What we tokenize from "<unk>": "<unk>"
										    6,  # Residue from the tokenization: an extra sentencepiece underline
										    4,
										    60_44,
										    2_37,
										    62_84,
										    5_09_01,
										    5_28,
										    31,
										    90,
										    34,
										    9_27,
										    2,
										]
										# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
										# xlmr.eval()
										# xlmr.encode(symbols)

										self.assertListEqual(A_     ,							self.big_tokenizer.encode(A_   )   )




							@slow
							def   __a   (     self:    str   ):
										# fmt: off
										__lowerCamelCase          =      {"""input_ids""": [[0, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [0, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
										# fmt: on

										self.tokenizer_integration_test_util(
										    expected_encoding=A_     ,							model_name="""xlm-roberta-base"""     ,							revision="""d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3"""     ,							)








"""simple docstring"""




import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


__magic_name__						: Optional[Any]    =				'http://www.mocksite.com/file1.txt'
__magic_name__						: Tuple    =				'"text": ["foo", "foo"]'
__magic_name__						: str    =				'6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8'




class 			__snake_case   :
							__a					 =       200
							__a					 =       {'''Content-Length''': '''100'''}
							__a					 =       {}




							def   __a   (     self:    List[str]     ,							**A_:    List[Any]   ):
										return [bytes(A_     ,							"""utf-8"""   )]





def       a_ (	*lowercase__ :List[Any],			**lowercase__ :Any     ):
			return MockResponse()





@pytest.mark.parametrize("""urls_type""",			[str, list, dict]     )
def       a_ (	lowercase__ :Optional[int],			lowercase__ :Any,			lowercase__ :Optional[int]     ):
			import requests

			monkeypatch.setattr(lowercase__,			"""request""",			lowercase__     )

			__lowerCamelCase          =      URL
			if issubclass(lowercase__,			lowercase__     ):
						__lowerCamelCase          =      url
			elif issubclass(lowercase__,			lowercase__     ):
						__lowerCamelCase          =      [url]
			elif issubclass(lowercase__,			lowercase__     ):
						__lowerCamelCase          =      {"""train""": url}
			__lowerCamelCase          =      """dummy"""
			__lowerCamelCase          =      """downloads"""
			__lowerCamelCase          =      tmp_path
			__lowerCamelCase          =      DownloadConfig(
			    cache_dir=os.path.join(lowercase__,			lowercase__     ),			use_etag=lowercase__,			)
			__lowerCamelCase          =      DownloadManager(dataset_name=lowercase__,			download_config=lowercase__     )
			__lowerCamelCase          =      dl_manager.download(lowercase__     )
			__lowerCamelCase          =      urls
			for downloaded_paths in [downloaded_paths]:
						if isinstance(lowercase__,			lowercase__     ):
									__lowerCamelCase          =      [downloaded_paths]
									__lowerCamelCase          =      [urls]
						elif isinstance(lowercase__,			lowercase__     ):
									assert "train" in downloaded_paths.keys()
									__lowerCamelCase          =      downloaded_paths.values()
									__lowerCamelCase          =      urls.values()
						assert downloaded_paths
						for downloaded_path, input_url in zip(lowercase__,			lowercase__     ):
									assert downloaded_path == dl_manager.downloaded_paths[input_url]
									__lowerCamelCase          =      Path(lowercase__     )
									__lowerCamelCase          =      downloaded_path.parts
									assert parts[-1] == HASH
									assert parts[-2] == cache_subdir
									assert downloaded_path.exists()
									__lowerCamelCase          =      downloaded_path.read_text()
									assert content == CONTENT
									__lowerCamelCase          =      downloaded_path.with_suffix(""".json"""     )
									assert metadata_downloaded_path.exists()
									__lowerCamelCase          =      json.loads(metadata_downloaded_path.read_text()     )
									assert metadata_content == {"url": URL, "etag": None}





@pytest.mark.parametrize("""paths_type""",			[str, list, dict]     )
def       a_ (	lowercase__ :Dict,			lowercase__ :Optional[Any],			lowercase__ :Dict     ):
			__lowerCamelCase          =      str(lowercase__     )
			if issubclass(lowercase__,			lowercase__     ):
						__lowerCamelCase          =      filename
			elif issubclass(lowercase__,			lowercase__     ):
						__lowerCamelCase          =      [filename]
			elif issubclass(lowercase__,			lowercase__     ):
						__lowerCamelCase          =      {"""train""": filename}
			__lowerCamelCase          =      """dummy"""
			__lowerCamelCase          =      xz_file.parent
			__lowerCamelCase          =      """extracted"""
			__lowerCamelCase          =      DownloadConfig(
			    cache_dir=lowercase__,			use_etag=lowercase__,			)
			__lowerCamelCase          =      DownloadManager(dataset_name=lowercase__,			download_config=lowercase__     )
			__lowerCamelCase          =      dl_manager.extract(lowercase__     )
			__lowerCamelCase          =      paths
			for extracted_paths in [extracted_paths]:
						if isinstance(lowercase__,			lowercase__     ):
									__lowerCamelCase          =      [extracted_paths]
									__lowerCamelCase          =      [paths]
						elif isinstance(lowercase__,			lowercase__     ):
									assert "train" in extracted_paths.keys()
									__lowerCamelCase          =      extracted_paths.values()
									__lowerCamelCase          =      paths.values()
						assert extracted_paths
						for extracted_path, input_path in zip(lowercase__,			lowercase__     ):
									assert extracted_path == dl_manager.extracted_paths[input_path]
									__lowerCamelCase          =      Path(lowercase__     )
									__lowerCamelCase          =      extracted_path.parts
									assert parts[-1] == hash_url_to_filename(lowercase__,			etag=lowercase__     )
									assert parts[-2] == extracted_subdir
									assert extracted_path.exists()
									__lowerCamelCase          =      extracted_path.read_text()
									__lowerCamelCase          =      text_file.read_text()
									assert extracted_file_content == expected_file_content





def       a_ (	lowercase__ :List[str],			lowercase__ :int     ):
			assert path.endswith(""".jsonl"""     )
			for num_items, line in enumerate(lowercase__,			start=1     ):
						__lowerCamelCase          =      json.loads(line.decode("""utf-8"""     )     )
						assert item.keys() == {"col_1", "col_2", "col_3"}
			assert num_items == 4





@pytest.mark.parametrize("""archive_jsonl""",			["""tar_jsonl_path""", """zip_jsonl_path"""]     )
def       a_ (	lowercase__ :Optional[int],			lowercase__ :Union[str, Any]     ):
			__lowerCamelCase          =      request.getfixturevalue(lowercase__     )
			__lowerCamelCase          =      DownloadManager()
			for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(lowercase__     ),			start=1     ):
						_test_jsonl(lowercase__,			lowercase__     )
			assert num_jsonl == 2





@pytest.mark.parametrize("""archive_nested_jsonl""",			["""tar_nested_jsonl_path""", """zip_nested_jsonl_path"""]     )
def       a_ (	lowercase__ :Optional[int],			lowercase__ :List[Any]     ):
			__lowerCamelCase          =      request.getfixturevalue(lowercase__     )
			__lowerCamelCase          =      DownloadManager()
			for num_tar, (path, file) in enumerate(dl_manager.iter_archive(lowercase__     ),			start=1     ):
						for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(lowercase__     ),			start=1     ):
									_test_jsonl(lowercase__,			lowercase__     )
			assert num_tar == 1
			assert num_jsonl == 2





def       a_ (	lowercase__ :Tuple     ):
			__lowerCamelCase          =      DownloadManager()
			for num_file, file in enumerate(dl_manager.iter_files(lowercase__     ),			start=1     ):
						assert os.path.basename(lowercase__     ) == ("test.txt" if num_file == 1 else "train.txt")
			assert num_file == 2




