



"""simple docstring"""

import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class SCREAMING_SNAKE_CASE__					(		__snake_case     ,					unittest.TestCase      ):
						_lowerCAmelCase							=					BarthezTokenizer
						_lowerCAmelCase							=					BarthezTokenizerFast
						_lowerCAmelCase							=					True
						_lowerCAmelCase							=					True



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													super().setUp()

													__a		:		Tuple									=       BarthezTokenizerFast.from_pretrained("""moussaKam/mbarthez"""							)
													tokenizer.save_pretrained(self.tmpdirname							)
													tokenizer.save_pretrained(self.tmpdirname						,     legacy_format=_lowercase							)
													__a		:		List[str]									=       tokenizer



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Tuple									=       """<pad>"""
													__a		:		Any									=       1

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



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Any									=       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(_lowercase							)						,     101122							)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													self.assertEqual(self.get_tokenizer().vocab_size						,     101122							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Dict									=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
													__a		:		str									=       [0, 57, 3018, 70307, 91, 2]

													__a		:		Any									=       self.tokenizer(
													    _lowercase						,     max_length=len(_lowercase							)						,     padding=_lowercase						,     truncation=_lowercase						,     return_tensors="""pt"""							)
													self.assertIsInstance(_lowercase						,     _lowercase							)

													self.assertEqual((2, 6)						,     batch.input_ids.shape							)
													self.assertEqual((2, 6)						,     batch.attention_mask.shape							)
													__a		:		Optional[int]									=       batch.input_ids.tolist()[0]
													self.assertListEqual(_lowercase						,     _lowercase							)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													if not self.test_rust_tokenizer:
																				return

													__a		:		Optional[Any]									=       self.get_tokenizer()
													__a		:		List[str]									=       self.get_rust_tokenizer()

													__a		:		List[str]									=       """I was born in 92000, and this is falsé."""

													__a		:		Optional[Any]									=       tokenizer.tokenize(_lowercase							)
													__a		:		Tuple									=       rust_tokenizer.tokenize(_lowercase							)
													self.assertListEqual(_lowercase						,     _lowercase							)

													__a		:		Any									=       tokenizer.encode(_lowercase						,     add_special_tokens=_lowercase							)
													__a		:		List[Any]									=       rust_tokenizer.encode(_lowercase						,     add_special_tokens=_lowercase							)
													self.assertListEqual(_lowercase						,     _lowercase							)

													__a		:		Dict									=       self.get_rust_tokenizer()
													__a		:		Optional[Any]									=       tokenizer.encode(_lowercase							)
													__a		:		Tuple									=       rust_tokenizer.encode(_lowercase							)
													self.assertListEqual(_lowercase						,     _lowercase							)





						@slow
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		List[Any]									=       {"""input_ids""": [[0, 490, 14328, 4507, 354, 47, 43669, 95, 25, 78117, 20215, 19779, 190, 22, 400, 4, 35343, 80310, 603, 86, 24937, 105, 33438, 94762, 196, 39642, 7, 15, 15933, 173, 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], [0, 10534, 87, 25, 66, 3358, 196, 55289, 8, 82961, 81, 2204, 75203, 7, 15, 763, 12956, 216, 178, 14328, 9595, 1377, 69693, 7, 448, 71021, 196, 18106, 1437, 13974, 108, 9083, 4, 49315, 7, 39, 86, 1326, 2793, 46333, 4, 448, 196, 74588, 7, 49315, 7, 39, 21, 822, 38470, 74, 21, 66723, 62480, 8, 22050, 5, 2]], """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, 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, 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]]}  # noqa: E501
													# fmt: on

													# moussaKam/mbarthez is a french model. So we also use french texts.
													__a		:		Union[str, Any]									=       [
													    """Le transformeur est un modèle d'apprentissage profond introduit en 2017, """
													    """utilisé principalement dans le domaine du traitement automatique des langues (TAL).""",
													    """À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus """
													    """pour gérer des données séquentielles, telles que le langage naturel, pour des tâches """
													    """telles que la traduction et la synthèse de texte.""",
													]

													self.tokenizer_integration_test_util(
													    expected_encoding=_lowercase						,     model_name="""moussaKam/mbarthez"""						,     revision="""c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6"""						,     sequences=_lowercase						,     )






"""simple docstring"""

from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters





def       __magic_name__    (   ):
							__a		:		Dict									=       {
							    """repo_name""": ["""test_repo1""", """test_repo2""", """test_repo3"""],
							    """path""": ["""test_1.py""", """test_2.py""", """unit_test.py"""],
							    """content""": ["""a """ * 2_0, """a """ * 3_0, """b """ * 7],
							}
							__a		:		Optional[Any]									=       Dataset.from_dict(_lowerCamelCase					)
							return dataset







class SCREAMING_SNAKE_CASE__					(		__snake_case      ):



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Optional[int]									=       get_dataset()
													__a		:		List[Any]									=       make_duplicate_clusters(_lowercase						,     0.85							)
													self.assertEqual(len(duplicate_clusters[0]							)						,     2							)





						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Tuple									=       get_dataset()
													__a							,     __a		:		Optional[Any]									=       deduplicate_dataset(_lowercase							)
													self.assertEqual(len(_lowercase							)						,     2							)
													print(_lowercase							)
													self.assertEqual(duplicate_clusters[0][0]["""copies"""]						,     2							)
													self.assertEqual(duplicate_clusters[0][0]["""is_extreme"""]						,     _lowercase							)

