



"""simple docstring"""

import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
			from .tokenization_nllb import NllbTokenizer
else:
			a_			   =					None


a_			   =					logging.get_logger(__name__)


a_			   =					{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

a_			   =					{
    '''vocab_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/tokenizer.json'''
        ),
    },
}

a_			   =					{
    '''facebook/nllb-large-en-ro''': 1024,
    '''facebook/nllb-200-distilled-600M''': 1024,
}

# fmt: off
a_			   =					['''ace_Arab''', '''ace_Latn''', '''acm_Arab''', '''acq_Arab''', '''aeb_Arab''', '''afr_Latn''', '''ajp_Arab''', '''aka_Latn''', '''amh_Ethi''', '''apc_Arab''', '''arb_Arab''', '''ars_Arab''', '''ary_Arab''', '''arz_Arab''', '''asm_Beng''', '''ast_Latn''', '''awa_Deva''', '''ayr_Latn''', '''azb_Arab''', '''azj_Latn''', '''bak_Cyrl''', '''bam_Latn''', '''ban_Latn''', '''bel_Cyrl''', '''bem_Latn''', '''ben_Beng''', '''bho_Deva''', '''bjn_Arab''', '''bjn_Latn''', '''bod_Tibt''', '''bos_Latn''', '''bug_Latn''', '''bul_Cyrl''', '''cat_Latn''', '''ceb_Latn''', '''ces_Latn''', '''cjk_Latn''', '''ckb_Arab''', '''crh_Latn''', '''cym_Latn''', '''dan_Latn''', '''deu_Latn''', '''dik_Latn''', '''dyu_Latn''', '''dzo_Tibt''', '''ell_Grek''', '''eng_Latn''', '''epo_Latn''', '''est_Latn''', '''eus_Latn''', '''ewe_Latn''', '''fao_Latn''', '''pes_Arab''', '''fij_Latn''', '''fin_Latn''', '''fon_Latn''', '''fra_Latn''', '''fur_Latn''', '''fuv_Latn''', '''gla_Latn''', '''gle_Latn''', '''glg_Latn''', '''grn_Latn''', '''guj_Gujr''', '''hat_Latn''', '''hau_Latn''', '''heb_Hebr''', '''hin_Deva''', '''hne_Deva''', '''hrv_Latn''', '''hun_Latn''', '''hye_Armn''', '''ibo_Latn''', '''ilo_Latn''', '''ind_Latn''', '''isl_Latn''', '''ita_Latn''', '''jav_Latn''', '''jpn_Jpan''', '''kab_Latn''', '''kac_Latn''', '''kam_Latn''', '''kan_Knda''', '''kas_Arab''', '''kas_Deva''', '''kat_Geor''', '''knc_Arab''', '''knc_Latn''', '''kaz_Cyrl''', '''kbp_Latn''', '''kea_Latn''', '''khm_Khmr''', '''kik_Latn''', '''kin_Latn''', '''kir_Cyrl''', '''kmb_Latn''', '''kon_Latn''', '''kor_Hang''', '''kmr_Latn''', '''lao_Laoo''', '''lvs_Latn''', '''lij_Latn''', '''lim_Latn''', '''lin_Latn''', '''lit_Latn''', '''lmo_Latn''', '''ltg_Latn''', '''ltz_Latn''', '''lua_Latn''', '''lug_Latn''', '''luo_Latn''', '''lus_Latn''', '''mag_Deva''', '''mai_Deva''', '''mal_Mlym''', '''mar_Deva''', '''min_Latn''', '''mkd_Cyrl''', '''plt_Latn''', '''mlt_Latn''', '''mni_Beng''', '''khk_Cyrl''', '''mos_Latn''', '''mri_Latn''', '''zsm_Latn''', '''mya_Mymr''', '''nld_Latn''', '''nno_Latn''', '''nob_Latn''', '''npi_Deva''', '''nso_Latn''', '''nus_Latn''', '''nya_Latn''', '''oci_Latn''', '''gaz_Latn''', '''ory_Orya''', '''pag_Latn''', '''pan_Guru''', '''pap_Latn''', '''pol_Latn''', '''por_Latn''', '''prs_Arab''', '''pbt_Arab''', '''quy_Latn''', '''ron_Latn''', '''run_Latn''', '''rus_Cyrl''', '''sag_Latn''', '''san_Deva''', '''sat_Beng''', '''scn_Latn''', '''shn_Mymr''', '''sin_Sinh''', '''slk_Latn''', '''slv_Latn''', '''smo_Latn''', '''sna_Latn''', '''snd_Arab''', '''som_Latn''', '''sot_Latn''', '''spa_Latn''', '''als_Latn''', '''srd_Latn''', '''srp_Cyrl''', '''ssw_Latn''', '''sun_Latn''', '''swe_Latn''', '''swh_Latn''', '''szl_Latn''', '''tam_Taml''', '''tat_Cyrl''', '''tel_Telu''', '''tgk_Cyrl''', '''tgl_Latn''', '''tha_Thai''', '''tir_Ethi''', '''taq_Latn''', '''taq_Tfng''', '''tpi_Latn''', '''tsn_Latn''', '''tso_Latn''', '''tuk_Latn''', '''tum_Latn''', '''tur_Latn''', '''twi_Latn''', '''tzm_Tfng''', '''uig_Arab''', '''ukr_Cyrl''', '''umb_Latn''', '''urd_Arab''', '''uzn_Latn''', '''vec_Latn''', '''vie_Latn''', '''war_Latn''', '''wol_Latn''', '''xho_Latn''', '''ydd_Hebr''', '''yor_Latn''', '''yue_Hant''', '''zho_Hans''', '''zho_Hant''', '''zul_Latn''']







class    __lowercase     (					_UpperCAmelCase):







						"""simple docstring"""







						_A		:							Tuple							       =		VOCAB_FILES_NAMES
						_A		:							Optional[Any]							       =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_A		:							Optional[Any]							       =		PRETRAINED_VOCAB_FILES_MAP
						_A		:							Union[str, Any]							       =		["""input_ids""", """attention_mask"""]
						_A		:							Optional[int]							       =		NllbTokenizer

						_A		:							List[int]							       =		[]
						_A		:							List[int]							       =		[]







						def __init__(self   ,		lowercase__=None   ,		lowercase__=None   ,		lowercase__="<s>"   ,		lowercase__="</s>"   ,		lowercase__="</s>"   ,		lowercase__="<s>"   ,		lowercase__="<unk>"   ,		lowercase__="<pad>"   ,		lowercase__="<mask>"   ,		lowercase__=None   ,		lowercase__=None   ,		lowercase__=None   ,		lowercase__=False   ,		**lowercase__   ,		):
											# Mask token behave like a normal word, i.e. include the space before it
											snake_case_					:		int 					=					AddedToken(lowercase__   ,		lstrip=lowercase__   ,		rstrip=lowercase__       ) if isinstance(lowercase__   ,		lowercase__       ) else mask_token
											snake_case_					:		str 					=					legacy_behaviour
											super().__init__(
											    vocab_file=lowercase__   ,		tokenizer_file=lowercase__   ,		bos_token=lowercase__   ,		eos_token=lowercase__   ,		sep_token=lowercase__   ,		cls_token=lowercase__   ,		unk_token=lowercase__   ,		pad_token=lowercase__   ,		mask_token=lowercase__   ,		src_lang=lowercase__   ,		tgt_lang=lowercase__   ,		additional_special_tokens=lowercase__   ,		legacy_behaviour=lowercase__   ,		**lowercase__   ,		)

											snake_case_					:		str 					=					vocab_file
											snake_case_					:		str 					=					False if not self.vocab_file else True

											snake_case_					:		str 					=					FAIRSEQ_LANGUAGE_CODES.copy()

											if additional_special_tokens is not None:
																# Only add those special tokens if they are not already there.
																_additional_special_tokens.extend(
																    [t for t in additional_special_tokens if t not in _additional_special_tokens]       )

											self.add_special_tokens({"""additional_special_tokens""": _additional_special_tokens}       )
											snake_case_					:		List[Any] 					=					{
											    lang_code: self.convert_tokens_to_ids(lowercase__       ) for lang_code in FAIRSEQ_LANGUAGE_CODES
											}

											snake_case_					:		Optional[Any] 					=					src_lang if src_lang is not None else """eng_Latn"""
											snake_case_					:		Dict 					=					self.convert_tokens_to_ids(self._src_lang       )
											snake_case_					:		Tuple 					=					tgt_lang
											self.set_src_lang_special_tokens(self._src_lang       )







						@property
						def 						__UpperCamelCase							(self       ):
											return self._src_lang







						@src_lang.setter
						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											snake_case_					:		Union[str, Any] 					=					new_src_lang
											self.set_src_lang_special_tokens(self._src_lang       )







						def 						__UpperCamelCase							(self   ,		lowercase__   ,		lowercase__ = None       ):
											if token_ids_a is None:
																return self.prefix_tokens + token_ids_a + self.suffix_tokens
											# We don't expect to process pairs, but leave the pair logic for API consistency
											return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens







						def 						__UpperCamelCase							(self   ,		lowercase__   ,		lowercase__ = None       ):
											snake_case_					:		int 					=					[self.sep_token_id]
											snake_case_					:		Dict 					=					[self.cls_token_id]

											if token_ids_a is None:
																return len(cls + token_ids_a + sep       ) * [0]
											return len(cls + token_ids_a + sep + sep + token_ids_a + sep       ) * [0]







						def 						__UpperCamelCase							(self   ,		lowercase__   ,		lowercase__   ,		lowercase__   ,		lowercase__   ,		**lowercase__       ):
											if src_lang is None or tgt_lang is None:
																raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""       )
											snake_case_					:		List[Any] 					=					src_lang
											snake_case_					:		str 					=					self(lowercase__   ,		add_special_tokens=lowercase__   ,		return_tensors=lowercase__   ,		**lowercase__       )
											snake_case_					:		str 					=					self.convert_tokens_to_ids(lowercase__       )
											snake_case_					:		List[str] 					=					tgt_lang_id
											return inputs







						def 						__UpperCamelCase							(self   ,		lowercase__   ,		lowercase__ = "eng_Latn"   ,		lowercase__ = None   ,		lowercase__ = "fra_Latn"   ,		**lowercase__   ,		):
											snake_case_					:		List[Any] 					=					src_lang
											snake_case_					:		int 					=					tgt_lang
											return super().prepare_seqaseq_batch(lowercase__   ,		lowercase__   ,		**lowercase__       )







						def 						__UpperCamelCase							(self       ):
											return self.set_src_lang_special_tokens(self.src_lang       )







						def 						__UpperCamelCase							(self       ):
											return self.set_tgt_lang_special_tokens(self.tgt_lang       )







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											snake_case_					:		int 					=					self.convert_tokens_to_ids(lowercase__       )

											if self.legacy_behaviour:
																snake_case_					:		Dict 					=					[]
																snake_case_					:		Optional[Any] 					=					[self.eos_token_id, self.cur_lang_code]
											else:
																snake_case_					:		Optional[int] 					=					[self.cur_lang_code]
																snake_case_					:		List[str] 					=					[self.eos_token_id]

											snake_case_					:		List[Any] 					=					self.convert_ids_to_tokens(self.prefix_tokens       )
											snake_case_					:		Optional[int] 					=					self.convert_ids_to_tokens(self.suffix_tokens       )

											snake_case_					:		Optional[Any] 					=					processors.TemplateProcessing(
											    single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str   ,		pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str   ,		special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str   ,		self.prefix_tokens + self.suffix_tokens       )       )   ,		)







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											snake_case_					:		str 					=					self.convert_tokens_to_ids(lowercase__       )
											if self.legacy_behaviour:
																snake_case_					:		Tuple 					=					[]
																snake_case_					:		List[Any] 					=					[self.eos_token_id, self.cur_lang_code]
											else:
																snake_case_					:		Any 					=					[self.cur_lang_code]
																snake_case_					:		Union[str, Any] 					=					[self.eos_token_id]

											snake_case_					:		List[Any] 					=					self.convert_ids_to_tokens(self.prefix_tokens       )
											snake_case_					:		Any 					=					self.convert_ids_to_tokens(self.suffix_tokens       )

											snake_case_					:		str 					=					processors.TemplateProcessing(
											    single=prefix_tokens_str + ["""$A"""] + suffix_tokens_str   ,		pair=prefix_tokens_str + ["""$A""", """$B"""] + suffix_tokens_str   ,		special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str   ,		self.prefix_tokens + self.suffix_tokens       )       )   ,		)







						def 						__UpperCamelCase							(self   ,		lowercase__   ,		lowercase__ = None       ):
											if not self.can_save_slow_tokenizer:
																raise ValueError(
																    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
																    """tokenizer."""       )

											if not os.path.isdir(lowercase__       ):
																logger.error(f'Vocabulary path ({save_directory}) should be a directory.'       )
																return
											snake_case_					:		str 					=					os.path.join(
											    lowercase__   ,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )

											if os.path.abspath(self.vocab_file       ) != os.path.abspath(lowercase__       ):
																copyfile(self.vocab_file   ,		lowercase__       )

											return (out_vocab_file,)









"""simple docstring"""

import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
			from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


a_			   =					get_tests_dir('''fixtures/test_sentencepiece.model''')

a_			   =					{'''target_lang''': '''fi''', '''source_lang''': '''en'''}
a_			   =					'''>>zh<<'''
a_			   =					'''Helsinki-NLP/'''

if is_torch_available():
			a_			   =					'''pt'''
elif is_tf_available():
			a_			   =					'''tf'''
else:
			a_			   =					'''jax'''







@require_sentencepiece
class    __lowercase     (					_UpperCAmelCase					,    unittest.TestCase):







						"""simple docstring"""







						_A		:							str							       =		MarianTokenizer
						_A		:							List[str]							       =		False
						_A		:							List[str]							       =		True







						def 						__UpperCamelCase							(self       ):
											super().setUp()
											snake_case_					:		Optional[int] 					=					["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
											snake_case_					:		Any 					=					dict(zip(lowercase__   ,		range(len(lowercase__       )       )       )       )
											snake_case_					:		Any 					=					Path(self.tmpdirname       )
											save_json(lowercase__   ,		save_dir / VOCAB_FILES_NAMES["""vocab"""]       )
											save_json(lowercase__   ,		save_dir / VOCAB_FILES_NAMES["""tokenizer_config_file"""]       )
											if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
																copyfile(lowercase__   ,		save_dir / VOCAB_FILES_NAMES["""source_spm"""]       )
																copyfile(lowercase__   ,		save_dir / VOCAB_FILES_NAMES["""target_spm"""]       )

											snake_case_					:		Optional[Any] 					=					MarianTokenizer.from_pretrained(self.tmpdirname       )
											tokenizer.save_pretrained(self.tmpdirname       )







						def 						__UpperCamelCase							(self   ,		**lowercase__       ):
											return MarianTokenizer.from_pretrained(self.tmpdirname   ,		**lowercase__       )







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											return (
											    "This is a test",
											    "This is a test",
											)







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Union[str, Any] 					=					"""</s>"""
											snake_case_					:		Tuple 					=					0

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







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		List[str] 					=					list(self.get_tokenizer().get_vocab().keys()       )

											self.assertEqual(vocab_keys[0]   ,		"""</s>"""       )
											self.assertEqual(vocab_keys[1]   ,		"""<unk>"""       )
											self.assertEqual(vocab_keys[-1]   ,		"""<pad>"""       )
											self.assertEqual(len(lowercase__       )   ,		9       )







						def 						__UpperCamelCase							(self       ):
											self.assertEqual(self.get_tokenizer().vocab_size   ,		9       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Any 					=					MarianTokenizer.from_pretrained(f'{ORG_NAME}opus-mt-en-de'       )
											snake_case_					:		Tuple 					=					en_de_tokenizer(["""I am a small frog"""]   ,		return_tensors=lowercase__       )
											self.assertIsInstance(lowercase__   ,		lowercase__       )
											snake_case_					:		Dict 					=					[38, 1_21, 14, 6_97, 3_88_48, 0]
											self.assertListEqual(lowercase__   ,		batch.input_ids[0]       )

											snake_case_					:		Tuple 					=					tempfile.mkdtemp()
											en_de_tokenizer.save_pretrained(lowercase__       )
											snake_case_					:		str 					=					[x.name for x in Path(lowercase__       ).glob("""*"""       )]
											self.assertIn("""source.spm"""   ,		lowercase__       )
											MarianTokenizer.from_pretrained(lowercase__       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Union[str, Any] 					=					self.get_tokenizer()

											snake_case_					:		List[str] 					=					tok(
											    ["""I am a small frog""" * 10_00, """I am a small frog"""]   ,		padding=lowercase__   ,		truncation=lowercase__   ,		return_tensors=lowercase__       )
											self.assertIsInstance(lowercase__   ,		lowercase__       )
											self.assertEqual(batch.input_ids.shape   ,		(2, 5_12)       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Tuple 					=					self.get_tokenizer()
											snake_case_					:		Tuple 					=					tok(["""I am a tiny frog""", """I am a small frog"""]   ,		padding=lowercase__   ,		return_tensors=lowercase__       )
											self.assertIsInstance(lowercase__   ,		lowercase__       )
											self.assertEqual(batch_smaller.input_ids.shape   ,		(2, 10)       )







						@slow
						def 						__UpperCamelCase							(self       ):
											# fmt: off
											snake_case_					:		str 					=					{"""input_ids""": [[4_34_95, 4_62, 20, 4_21_64, 13_69, 52, 4_64, 1_32, 17_03, 4_92, 13, 74_91, 3_89_99, 6, 8, 4_64, 1_32, 17_03, 4_92, 13, 46_69, 3_78_67, 13, 75_25, 27, 15_93, 9_88, 13, 3_39_72, 70_29, 6, 20, 82_51, 3_83, 2, 2_70, 58_66, 37_88, 2, 23_53, 82_51, 1_23_38, 2, 1_39_58, 3_87, 2, 36_29, 69_53, 1_88, 29_00, 2, 1_39_58, 80_11, 1_15_01, 23, 84_60, 40_73, 3_40_09, 20, 4_35, 1_14_39, 27, 8, 84_60, 40_73, 60_04, 20, 99_88, 3_75, 27, 33, 2_66, 19_45, 10_76, 13_50, 3_78_67, 32_88, 5, 5_77, 10_76, 43_74, 8, 50_82, 5, 2_64_53, 2_57, 5_56, 4_03, 2, 2_42, 1_32, 3_83, 3_16, 4_92, 8, 1_07_67, 6, 3_16, 3_04, 42_39, 3, 0], [1_48, 1_57_22, 19, 18_39, 12, 13_50, 13, 2_23_27, 50_82, 54_18, 4_75_67, 3_59_38, 59, 3_18, 1_95_52, 1_08, 21_83, 54, 1_49_76, 48_35, 32, 5_47, 11_14, 8, 3_15, 24_17, 5, 92, 1_90_88, 3, 0, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00], [36, 63_95, 1_25_70, 3_91_47, 1_15_97, 6, 2_66, 4, 4_54_05, 72_96, 3, 0, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00]], """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, 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], [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]]}  # noqa: E501
											# fmt: on

											self.tokenizer_integration_test_util(
											    expected_encoding=lowercase__   ,		model_name="""Helsinki-NLP/opus-mt-en-de"""   ,		revision="""1a8c2263da11e68e50938f97e10cd57820bd504c"""   ,		decode_kwargs={"""use_source_tokenizer""": True}   ,		)







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Any 					=					MarianTokenizer.from_pretrained("""hf-internal-testing/test-marian-two-vocabs"""       )

											snake_case_					:		Dict 					=					"""Tämä on testi"""
											snake_case_					:		List[Any] 					=					"""This is a test"""

											snake_case_					:		Optional[int] 					=					[76, 7, 20_47, 2]
											snake_case_					:		List[str] 					=					[69, 12, 11, 9_40, 2]

											snake_case_					:		Any 					=					tokenizer(lowercase__       ).input_ids
											self.assertListEqual(lowercase__   ,		lowercase__       )

											snake_case_					:		str 					=					tokenizer(text_target=lowercase__       ).input_ids
											self.assertListEqual(lowercase__   ,		lowercase__       )

											snake_case_					:		int 					=					tokenizer.decode(lowercase__   ,		skip_special_tokens=lowercase__       )
											self.assertEqual(lowercase__   ,		lowercase__       )




