




'''simple docstring'''





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


__lowerCAmelCase	:       Any     =	get_tests_dir('fixtures/test_sentencepiece.model')

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

__lowerCAmelCase	:       Any     =	25_0004
__lowerCAmelCase	:       Optional[Any]     =	25_0020




@require_sentencepiece
@require_tokenizers
class 					snake_case__							(_UpperCamelCase					, unittest.TestCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							str											=      MBartaaTokenizer
				SCREAMING_SNAKE_CASE_ :							Union[str, Any]											=      MBartaaTokenizerFast
				SCREAMING_SNAKE_CASE_ :							Union[str, Any]											=      True
				SCREAMING_SNAKE_CASE_ :							int											=      True





				def 							__UpperCAmelCase							(   self       :  Dict							)      ->  Union[str, Any]:
							super().setUp()

							# We have a SentencePiece fixture for testing
							a					=    MBartaaTokenizer(__lowerCamelCase      ,   src_lang="en_XX"      ,   tgt_lang="ro_RO"      ,   keep_accents=__lowerCamelCase							)
							tokenizer.save_pretrained(self.tmpdirname							)





				def 							__UpperCAmelCase							(   self       :  int							)      ->  Any:
							a					=    "<s>"
							a					=    0

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





				def 							__UpperCAmelCase							(   self       :  str							)      ->  Union[str, Any]:
							a					=    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(__lowerCamelCase							)      ,   10_54							)





				def 							__UpperCAmelCase							(   self       :  str							)      ->  Dict:
							self.assertEqual(self.get_tokenizer().vocab_size      ,   10_54							)





				def 							__UpperCAmelCase							(   self       :  Tuple							)      ->  List[str]:
							a					=    MBartaaTokenizer(__lowerCamelCase      ,   src_lang="en_XX"      ,   tgt_lang="ro_RO"      ,   keep_accents=__lowerCamelCase							)

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

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

							a					=    tokenizer.tokenize("I was born in 92000, and this is falsé."							)
							self.assertListEqual(
							    __lowerCamelCase      ,   [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					=    tokenizer.convert_tokens_to_ids(__lowerCamelCase							)
							self.assertListEqual(
							    __lowerCamelCase      ,   [
							        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]
							    ]      ,   )

							a					=    tokenizer.convert_ids_to_tokens(__lowerCamelCase							)
							self.assertListEqual(
							    __lowerCamelCase      ,   [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 							__UpperCAmelCase							(   self       :  List[Any]							)      ->  int:
							# fmt: off
							a					=    {"input_ids": [[25_00_04, 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], [25_00_04, 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], [25_00_04, 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=__lowerCamelCase      ,   model_name="facebook/mbart-large-50"      ,   revision="d3913889c59cd5c9e456b269c376325eabad57e2"      ,   )





				def 							__UpperCAmelCase							(   self       :  Optional[Any]							)      ->  Tuple:
							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					=    (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					=    self.rust_tokenizer_class.from_pretrained(__lowerCamelCase      ,   **__lowerCamelCase							)
													a					=    self.tokenizer_class.from_pretrained(__lowerCamelCase      ,   **__lowerCamelCase							)

													a					=    tempfile.mkdtemp()

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

													# 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					=    tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f							)
													self.assertSequenceEqual(__lowerCamelCase      ,   __lowerCamelCase							)

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

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

													shutil.rmtree(__lowerCamelCase							)

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

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

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

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

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

													shutil.rmtree(__lowerCamelCase							)

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

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

													# 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					=    tokenizer_r.from_pretrained(__lowerCamelCase							)
													a					=    tokenizer_p.from_pretrained(__lowerCamelCase							)

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

													shutil.rmtree(__lowerCamelCase							)




@require_torch
@require_sentencepiece
@require_tokenizers
class 					snake_case__							(unittest.TestCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							str											=      """facebook/mbart-large-50-one-to-many-mmt"""
				SCREAMING_SNAKE_CASE_ :							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.""",
				]
				SCREAMING_SNAKE_CASE_ :							Optional[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.""",
				]
				SCREAMING_SNAKE_CASE_ :							Any											=      [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 							__UpperCAmelCase							(   cls       :  Optional[int]							)      ->  str:
							a					=    MBartaaTokenizer.from_pretrained(
							    cls.checkpoint_name      ,   src_lang="en_XX"      ,   tgt_lang="ro_RO"							)
							a					=    1
							return cls





				def 							__UpperCAmelCase							(   self       :  Optional[Any]							)      ->  str:
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]      ,   25_00_01							)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]      ,   25_00_04							)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]      ,   25_00_20							)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["mr_IN"]      ,   25_00_38							)





				def 							__UpperCAmelCase							(   self       :  str							)      ->  Union[str, Any]:
							a					=    self.tokenizer.batch_encode_plus(self.src_text							).input_ids[0]
							self.assertListEqual(self.expected_src_tokens      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Optional[int]							)      ->  Dict:
							self.assertIn(__lowerCamelCase      ,   self.tokenizer.all_special_ids							)
							a					=    [RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
							a					=    self.tokenizer.decode(__lowerCamelCase      ,   skip_special_tokens=__lowerCamelCase							)
							a					=    self.tokenizer.decode(generated_ids[1:]      ,   skip_special_tokens=__lowerCamelCase							)
							self.assertEqual(__lowerCamelCase      ,   __lowerCamelCase							)
							self.assertNotIn(self.tokenizer.eos_token      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Optional[Any]							)      ->  Any:
							a					=    ["this is gunna be a long sentence " * 20]
							assert isinstance(src_text[0]      ,   __lowerCamelCase							)
							a					=    10
							a					=    self.tokenizer(__lowerCamelCase      ,   max_length=__lowerCamelCase      ,   truncation=__lowerCamelCase							).input_ids[0]
							self.assertEqual(ids[0]      ,   __lowerCamelCase							)
							self.assertEqual(ids[-1]      ,   2							)
							self.assertEqual(len(__lowerCamelCase							)      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  str							)      ->  int:
							self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]							)      ,   [25_00_53, 25_00_01]							)





				def 							__UpperCAmelCase							(   self       :  Any							)      ->  Union[str, Any]:
							a					=    tempfile.mkdtemp()
							a					=    self.tokenizer.fairseq_tokens_to_ids
							self.tokenizer.save_pretrained(__lowerCamelCase							)
							a					=    MBartaaTokenizer.from_pretrained(__lowerCamelCase							)
							self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,   __lowerCamelCase							)





				@require_torch
				def 							__UpperCAmelCase							(   self       :  Union[str, Any]							)      ->  Tuple:
							a					=    self.tokenizer(self.src_text      ,   text_target=self.tgt_text      ,   padding=__lowerCamelCase      ,   return_tensors="pt"							)
							a					=    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 							__UpperCAmelCase							(   self       :  Optional[int]							)      ->  Optional[Any]:
							a					=    self.tokenizer(
							    self.src_text      ,   text_target=self.tgt_text      ,   padding=__lowerCamelCase      ,   truncation=__lowerCamelCase      ,   max_length=len(self.expected_src_tokens							)      ,   return_tensors="pt"      ,   )
							a					=    shift_tokens_right(batch["labels"]      ,   self.tokenizer.pad_token_id							)

							self.assertIsInstance(__lowerCamelCase      ,   __lowerCamelCase							)

							self.assertEqual((2, 14)      ,   batch.input_ids.shape							)
							self.assertEqual((2, 14)      ,   batch.attention_mask.shape							)
							a					=    batch.input_ids.tolist()[0]
							self.assertListEqual(self.expected_src_tokens      ,   __lowerCamelCase							)
							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 							__UpperCAmelCase							(   self       :  List[str]							)      ->  str:
							a					=    self.tokenizer(self.src_text      ,   padding=__lowerCamelCase      ,   truncation=__lowerCamelCase      ,   max_length=3      ,   return_tensors="pt"							)
							a					=    self.tokenizer(
							    text_target=self.tgt_text      ,   padding=__lowerCamelCase      ,   truncation=__lowerCamelCase      ,   max_length=10      ,   return_tensors="pt"							)
							a					=    targets["input_ids"]
							a					=    shift_tokens_right(__lowerCamelCase      ,   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 							__UpperCAmelCase							(   self       :  str							)      ->  Optional[Any]:
							a					=    self.tokenizer._build_translation_inputs(
							    "A test"      ,   return_tensors="pt"      ,   src_lang="en_XX"      ,   tgt_lang="ar_AR"							)

							self.assertEqual(
							    nested_simplify(__lowerCamelCase							)      ,   {
							        # en_XX, A, test, EOS
							        "input_ids": [[25_00_04, 62, 30_34, 2]],
							        "attention_mask": [[1, 1, 1, 1]],
							        # ar_AR
							        "forced_bos_token_id": 25_00_01,
							    }      ,   )












def     __magic_name__       (				A	:      str,						A	:      str     ):






			'''simple docstring'''







			def get_matched_characters(A	:      str,						A	:      str     ) -> str:
						a					=    []
						a					=    min(len(_stra     ),						len(_stra     )     ) // 2
						for i, l in enumerate(_stra     ):
									a					=    int(max(0,						i - limit     )     )
									a					=    int(min(i + limit + 1,						len(_stra     )     )     )
									if l in _stra[left:right]:
												matched.append(A     )
												a					=    F"""{_stra[0:_stra.index(A     )]} {_stra[_stra.index(A     ) + 1:]}"""

						return "".join(A     )

			# matching characters
			a					=    get_matched_characters(A,						A     )
			a					=    get_matched_characters(A,						A     )
			a					=    len(A     )

			# transposition
			a					=    (
			    len([(ca, ca) for ca, ca in zip(A,						A     ) if ca != ca]     ) // 2
			)

			if not match_count:
						a					=    0.0
			else:
						a					=    (
						    1
						    / 3
						    * (
						        match_count / len(A     )
						        + match_count / len(A     )
						        + (match_count - transpositions) / match_count
						    )
						)

			# common prefix up to 4 characters
			a					=    0
			for ca, ca in zip(stra[:4],						stra[:4]     ):
						if ca == ca:
									prefix_len += 1
						else:
									break

			return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		print(jaro_winkler('hello', 'world'))






