



import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


snake_case    :						List[str]  =						get_tests_dir('fixtures/test_sentencepiece.model')

if is_torch_available():
  from transformers.models.mbart.modeling_mbart import shift_tokens_right

snake_case    :						str  =						2_5_0_0_0_4
snake_case    :						Union[str, Any]  =						2_5_0_0_2_0




@require_sentencepiece
@require_tokenizers
class 							lowerCAmelCase__  (	UpperCamelCase					,							unittest.TestCase						):
     __A     :    Any           =						MBartaaTokenizer
     __A     :    Dict           =						MBartaaTokenizerFast
     __A     :    Tuple           =						True
     __A     :    Optional[Any]           =						True







     def  _lowercase			(       self      :     Union[str, Any]):
           super().setUp()

           # We have a SentencePiece fixture for testing
           A__	:							Union[str, Any]						    = MBartaaTokenizer(_A			,		src_lang="en_XX"			,		tgt_lang="ro_RO"			,		keep_accents=_A)
           tokenizer.save_pretrained(self.tmpdirname)







     def  _lowercase			(       self      :     Dict):
           A__	:							Union[str, Any]						    = "<s>"
           A__	:							Union[str, Any]						    = 0

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







     def  _lowercase			(       self      :     Optional[int]):
           A__	:							Union[str, 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(_A)			,		1054)







     def  _lowercase			(       self      :     int):
           self.assertEqual(self.get_tokenizer().vocab_size			,		1054)







     def  _lowercase			(       self      :     Optional[int]):
           A__	:							Tuple						    = MBartaaTokenizer(_A			,		src_lang="en_XX"			,		tgt_lang="ro_RO"			,		keep_accents=_A)

           A__	:							List[str]						    = 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 [285, 46, 10, 170, 382]]			,		)

           A__	:							List[str]						    = 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", "."]			,		)
           A__	:							Optional[Any]						    = tokenizer.convert_tokens_to_ids(_A)
           self.assertListEqual(
               _A			,		[
                   value + tokenizer.fairseq_offset
                   for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
               ]			,		)

           A__	:							int						    = 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>", "."]			,		)







     @slow
     def  _lowercase			(       self      :     List[Any]):
           # fmt: off
           A__	:							List[str]						    = {"input_ids": [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 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], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 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="facebook/mbart-large-50"			,		revision="d3913889c59cd5c9e456b269c376325eabad57e2"			,		)







     def  _lowercase			(       self      :     Any):
           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

           A__	:							Optional[Any]						    = (self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart50", {})
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'):
                       A__	:							List[Any]						    = self.rust_tokenizer_class.from_pretrained(_A			,		**_A)
                       A__	:							Tuple						    = self.tokenizer_class.from_pretrained(_A			,		**_A)

                       A__	:							Optional[Any]						    = tempfile.mkdtemp()

                       A__	:							str						    = tokenizer_r.save_pretrained(_A)
                       A__	:							Union[str, Any]						    = 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))
                       A__	:							Dict						    = 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
                       A__	:							Union[str, Any]						    = tokenizer_r.from_pretrained(_A)
                       A__	:							List[str]						    = 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
                       A__	:							List[Any]						    = tempfile.mkdtemp()

                       A__	:							Union[str, Any]						    = tokenizer_r.save_pretrained(_A			,		legacy_format=_A)
                       A__	:							Any						    = tokenizer_p.save_pretrained(_A)

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

                       # Checks everything loads correctly in the same way
                       A__	:							int						    = tokenizer_r.from_pretrained(_A)
                       A__	:							Dict						    = 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
                       A__	:							List[Any]						    = tempfile.mkdtemp()

                       A__	:							str						    = tokenizer_r.save_pretrained(_A			,		legacy_format=_A)
                       A__	:							List[str]						    = 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
                       A__	:							List[Any]						    = tokenizer_r.from_pretrained(_A)
                       A__	:							List[Any]						    = 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)




@require_torch
@require_sentencepiece
@require_tokenizers
class 							lowerCAmelCase__  (	unittest.TestCase						):
     __A     :    List[str]           =						'facebook/mbart-large-50-one-to-many-mmt'
     __A     :    Any           =						[
         ' UN Chief Says There Is No Military Solution in Syria',
         ' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that "there is no military solution" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.',
     ]
     __A     :    List[Any]           =						[
         'Şeful ONU declară că nu există o soluţie militară în Siria',
         'Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'
         ' pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi că noi arme nu vor'
         ' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.',
     ]
     __A     :    int           =						[EN_CODE, 82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2]







     @classmethod
     def  _lowercase			(       cls      :     Optional[int]):
           A__	:							MBartaaTokenizer						    = MBartaaTokenizer.from_pretrained(
               cls.checkpoint_name			,		src_lang="en_XX"			,		tgt_lang="ro_RO")
           A__	:							Tuple						    = 1
           return cls







     def  _lowercase			(       self      :     str):
           self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]			,		25_0001)
           self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]			,		25_0004)
           self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]			,		25_0020)
           self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["mr_IN"]			,		25_0038)







     def  _lowercase			(       self      :     Optional[Any]):
           A__	:							Tuple						    = self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
           self.assertListEqual(self.expected_src_tokens			,		_A)







     def  _lowercase			(       self      :     Optional[Any]):
           self.assertIn(_A			,		self.tokenizer.all_special_ids)
           A__	:							Dict						    = [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
           A__	:							Tuple						    = self.tokenizer.decode(_A			,		skip_special_tokens=_A)
           A__	:							Any						    = self.tokenizer.decode(generated_ids[1:]			,		skip_special_tokens=_A)
           self.assertEqual(_A			,		_A)
           self.assertNotIn(self.tokenizer.eos_token			,		_A)







     def  _lowercase			(       self      :     Optional[int]):
           A__	:							List[str]						    = ["this is gunna be a long sentence " * 20]
           assert isinstance(src_text[0]			,		_A)
           A__	:							str						    = 10
           A__	:							Optional[int]						    = self.tokenizer(_A			,		max_length=_A			,		truncation=_A).input_ids[0]
           self.assertEqual(ids[0]			,		_A)
           self.assertEqual(ids[-1]			,		2)
           self.assertEqual(len(_A)			,		_A)







     def  _lowercase			(       self      :     str):
           self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"])			,		[25_0053, 25_0001])







     def  _lowercase			(       self      :     Union[str, Any]):
           A__	:							Any						    = tempfile.mkdtemp()
           A__	:							Tuple						    = self.tokenizer.fairseq_tokens_to_ids
           self.tokenizer.save_pretrained(_A)
           A__	:							Dict						    = MBartaaTokenizer.from_pretrained(_A)
           self.assertDictEqual(new_tok.fairseq_tokens_to_ids			,		_A)







     @require_torch
     def  _lowercase			(       self      :     Union[str, Any]):
           A__	:							List[Any]						    = self.tokenizer(self.src_text			,		text_target=self.tgt_text			,		padding=_A			,		return_tensors="pt")
           A__	:							Any						    = shift_tokens_right(batch["labels"]			,		self.tokenizer.pad_token_id)

           # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
           assert batch.input_ids[1][0] == EN_CODE
           assert batch.input_ids[1][-1] == 2
           assert batch.labels[1][0] == RO_CODE
           assert batch.labels[1][-1] == 2
           assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]







     @require_torch
     def  _lowercase			(       self      :     Union[str, Any]):
           A__	:							List[Any]						    = self.tokenizer(
               self.src_text			,		text_target=self.tgt_text			,		padding=_A			,		truncation=_A			,		max_length=len(self.expected_src_tokens)			,		return_tensors="pt"			,		)
           A__	:							Optional[int]						    = shift_tokens_right(batch["labels"]			,		self.tokenizer.pad_token_id)

           self.assertIsInstance(_A			,		_A)

           self.assertEqual((2, 14)			,		batch.input_ids.shape)
           self.assertEqual((2, 14)			,		batch.attention_mask.shape)
           A__	:							List[Any]						    = batch.input_ids.tolist()[0]
           self.assertListEqual(self.expected_src_tokens			,		_A)
           self.assertEqual(2			,		batch.decoder_input_ids[0, 0])  # decoder_start_token_id
           # Test that special tokens are reset
           self.assertEqual(self.tokenizer.prefix_tokens			,		[EN_CODE])
           self.assertEqual(self.tokenizer.suffix_tokens			,		[self.tokenizer.eos_token_id])







     def  _lowercase			(       self      :     List[str]):
           A__	:							Optional[int]						    = self.tokenizer(self.src_text			,		padding=_A			,		truncation=_A			,		max_length=3			,		return_tensors="pt")
           A__	:							Optional[Any]						    = self.tokenizer(
               text_target=self.tgt_text			,		padding=_A			,		truncation=_A			,		max_length=10			,		return_tensors="pt")
           A__	:							str						    = targets["input_ids"]
           A__	:							List[str]						    = shift_tokens_right(_A			,		self.tokenizer.pad_token_id)

           self.assertEqual(batch.input_ids.shape[1]			,		3)
           self.assertEqual(batch.decoder_input_ids.shape[1]			,		10)







     @require_torch
     def  _lowercase			(       self      :     int):
           A__	:							Any						    = self.tokenizer._build_translation_inputs(
               "A test"			,		return_tensors="pt"			,		src_lang="en_XX"			,		tgt_lang="ar_AR")

           self.assertEqual(
               nested_simplify(_A)			,		{
                   # en_XX, A, test, EOS
                   "input_ids": [[25_0004, 62, 3034, 2]],
                   "attention_mask": [[1, 1, 1, 1]],
                   # ar_AR
                   "forced_bos_token_id": 25_0001,
               }			,		)




def 	snake_case__       (					__lowercase       )		->		int:







						"""simple docstring"""

						if divisor % 5 == 0 or divisor % 2 == 0:
												return 0
						A__	:							Tuple						    = 1
						A__	:							Union[str, Any]						    = 1
						while repunit:
												A__	:							Union[str, Any]						    = (1_0 * repunit + 1) % divisor
												repunit_index += 1
						return repunit_index
def 	snake_case__       (					__lowercase = 1_0_0_0_0_0_0       )		->		int:







						"""simple docstring"""

						A__	:							Dict						    = limit - 1
						if divisor % 2 == 0:
												divisor += 1
						while least_divisible_repunit(__lowercase       ) <= limit:
												divisor += 2
						return divisor


if __name__ == "__main__":
		print(f"""{solution() = }""")