"""simple docstring"""





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


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


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

lowerCAmelCase_     =	250004
lowerCAmelCase_     =	250020




@require_sentencepiece
@require_tokenizers
class  _snake_case		(    __snake_case   ,       unittest.TestCase ):







				"""simple docstring"""






				a			=						MBartTokenizer
				a			=						MBartTokenizerFast
				a			=						True
				a			=						True





				def 		_lowerCAmelCase		(      self							:							Tuple):



											"""simple docstring"""







											super().setUp()

											# We have a SentencePiece fixture for testing
											_SCREAMING_SNAKE_CASE		:						Dict			  =    MBartTokenizer(_A      ,    keep_accents=_A)
											tokenizer.save_pretrained(self.tmpdirname)





				def 		_lowerCAmelCase		(      self							:							List[str]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    MBartTokenizer(_A      ,    keep_accents=_A)

											_SCREAMING_SNAKE_CASE		:						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 [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]      ,    )

											_SCREAMING_SNAKE_CASE		:						Any			  =    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""",
											        """.""",
											    ]      ,    )
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    tokenizer.convert_tokens_to_ids(_A)
											self.assertListEqual(
											    _A      ,    [
											        value + tokenizer.fairseq_offset
											        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
											        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
											    ]      ,    )

											_SCREAMING_SNAKE_CASE		:						Dict			  =    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 		_lowerCAmelCase		(      self							:							Optional[Any]):



											"""simple docstring"""







											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

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

																									_SCREAMING_SNAKE_CASE		:						List[Any]			  =    tempfile.mkdtemp()

																									_SCREAMING_SNAKE_CASE		:						str			  =    tokenizer_r.save_pretrained(_A)
																									_SCREAMING_SNAKE_CASE		:						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))
																									_SCREAMING_SNAKE_CASE		:						List[Any]			  =    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
																									_SCREAMING_SNAKE_CASE		:						Any			  =    tokenizer_r.from_pretrained(_A)
																									_SCREAMING_SNAKE_CASE		:						Union[str, 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))
																																# 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
																									_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    tempfile.mkdtemp()

																									_SCREAMING_SNAKE_CASE		:						List[Any]			  =    tokenizer_r.save_pretrained(_A      ,    legacy_format=_A)
																									_SCREAMING_SNAKE_CASE		:						List[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
																									_SCREAMING_SNAKE_CASE		:						Tuple			  =    tokenizer_r.from_pretrained(_A)
																									_SCREAMING_SNAKE_CASE		:						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)

																									# Save tokenizer rust, legacy_format=False
																									_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    tempfile.mkdtemp()

																									_SCREAMING_SNAKE_CASE		:						List[Any]			  =    tokenizer_r.save_pretrained(_A      ,    legacy_format=_A)
																									_SCREAMING_SNAKE_CASE		:						Any			  =    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
																									_SCREAMING_SNAKE_CASE		:						Any			  =    tokenizer_r.from_pretrained(_A)
																									_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    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  _snake_case		(    unittest.TestCase ):







				"""simple docstring"""






				a			=						"facebook/mbart-large-en-ro"
				a			=						[
				    " 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			=						[
				    "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			=						[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, EN_CODE]





				@classmethod
				def 		_lowerCAmelCase		(      cls							:							str):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						MBartTokenizer			  =    MBartTokenizer.from_pretrained(
											    cls.checkpoint_name      ,    src_lang="""en_XX"""      ,    tgt_lang="""ro_RO""")
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    1
											return cls





				def 		_lowerCAmelCase		(      self							:							Optional[int]):



											"""simple docstring"""







											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""]      ,    2_5_0_0_0_1)
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""]      ,    2_5_0_0_0_4)
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""]      ,    2_5_0_0_2_0)





				def 		_lowerCAmelCase		(      self							:							Tuple):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Dict			  =    self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
											self.assertListEqual(self.expected_src_tokens      ,    _A)





				def 		_lowerCAmelCase		(      self							:							str):



											"""simple docstring"""







											self.assertIn(_A      ,    self.tokenizer.all_special_ids)
											_SCREAMING_SNAKE_CASE		:						Any			  =    [RO_CODE, 8_8_4, 9_0_1_9, 9_6, 9, 9_1_6, 8_6_7_9_2, 3_6, 1_8_7_4_3, 1_5_5_9_6, 5, 2]
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    self.tokenizer.decode(_A      ,    skip_special_tokens=_A)
											_SCREAMING_SNAKE_CASE		:						Any			  =    self.tokenizer.decode(generated_ids[1:]      ,    skip_special_tokens=_A)
											self.assertEqual(_A      ,    _A)
											self.assertNotIn(self.tokenizer.eos_token      ,    _A)





				def 		_lowerCAmelCase		(      self							:							Optional[Any]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Any			  =    ["""this is gunna be a long sentence """ * 2_0]
											assert isinstance(src_text[0]      ,    _A)
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    1_0
											_SCREAMING_SNAKE_CASE		:						int			  =    self.tokenizer(_A      ,    max_length=_A      ,    truncation=_A).input_ids[0]
											self.assertEqual(ids[-2]      ,    2)
											self.assertEqual(ids[-1]      ,    _A)
											self.assertEqual(len(_A)      ,    _A)





				def 		_lowerCAmelCase		(      self							:							Dict):



											"""simple docstring"""







											self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""])      ,    [2_5_0_0_2_6, 2_5_0_0_0_1])





				def 		_lowerCAmelCase		(      self							:							Union[str, Any]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    tempfile.mkdtemp()
											_SCREAMING_SNAKE_CASE		:						Any			  =    self.tokenizer.fairseq_tokens_to_ids
											self.tokenizer.save_pretrained(_A)
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    MBartTokenizer.from_pretrained(_A)
											self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,    _A)





				@require_torch
				def 		_lowerCAmelCase		(      self							:							List[str]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Dict			  =    self.tokenizer(self.src_text      ,    text_target=self.tgt_text      ,    padding=_A      ,    return_tensors="""pt""")
											_SCREAMING_SNAKE_CASE		:						str			  =    shift_tokens_right(batch["""labels"""]      ,    self.tokenizer.pad_token_id)

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





				@require_torch
				def 		_lowerCAmelCase		(      self							:							Tuple):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Dict			  =    self.tokenizer(
											    self.src_text      ,    text_target=self.tgt_text      ,    padding=_A      ,    truncation=_A      ,    max_length=len(self.expected_src_tokens)      ,    return_tensors="""pt"""      ,    )

											_SCREAMING_SNAKE_CASE		:						Any			  =    shift_tokens_right(batch["""labels"""]      ,    self.tokenizer.pad_token_id)

											self.assertIsInstance(_A      ,    _A)

											self.assertEqual((2, 1_4)      ,    batch.input_ids.shape)
											self.assertEqual((2, 1_4)      ,    batch.attention_mask.shape)
											_SCREAMING_SNAKE_CASE		:						Dict			  =    batch.input_ids.tolist()[0]
											self.assertListEqual(self.expected_src_tokens      ,    _A)
											self.assertEqual(2      ,    batch.decoder_input_ids[0, -1])  # EOS
											# Test that special tokens are reset
											self.assertEqual(self.tokenizer.prefix_tokens      ,    [])
											self.assertEqual(self.tokenizer.suffix_tokens      ,    [self.tokenizer.eos_token_id, EN_CODE])





				def 		_lowerCAmelCase		(      self							:							Optional[Any]):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    self.tokenizer(self.src_text      ,    padding=_A      ,    truncation=_A      ,    max_length=3      ,    return_tensors="""pt""")
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    self.tokenizer(
											    text_target=self.tgt_text      ,    padding=_A      ,    truncation=_A      ,    max_length=1_0      ,    return_tensors="""pt""")
											_SCREAMING_SNAKE_CASE		:						int			  =    targets["""input_ids"""]
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    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]      ,    1_0)





				@require_torch
				def 		_lowerCAmelCase		(      self							:							int):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    self.tokenizer._build_translation_inputs(
											    """A test"""      ,    return_tensors="""pt"""      ,    src_lang="""en_XX"""      ,    tgt_lang="""ar_AR""")

											self.assertEqual(
											    nested_simplify(_A)      ,    {
											        # A, test, EOS, en_XX
											        """input_ids""": [[6_2, 3_0_3_4, 2, 2_5_0_0_0_4]],
											        """attention_mask""": [[1, 1, 1, 1]],
											        # ar_AR
											        """forced_bos_token_id""": 2_5_0_0_0_1,
											    }      ,    )



"""simple docstring"""





def      lowerCamelCase_(__SCREAMING_SNAKE_CASE  )->    int:

							if not isinstance(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE  ):
														raise TypeError("""only integers accepted as input"""  )
							else:
														_SCREAMING_SNAKE_CASE		:						List[Any]			  =    str(abs(__SCREAMING_SNAKE_CASE  )  )
														_SCREAMING_SNAKE_CASE		:						List[str]			  =    [list(__SCREAMING_SNAKE_CASE  ) for char in range(len(__SCREAMING_SNAKE_CASE  )  )]
														for index in range(len(__SCREAMING_SNAKE_CASE  )  ):
																					num_transpositions[index].pop(__SCREAMING_SNAKE_CASE  )
														return max(
														    int("""""".join(list(__SCREAMING_SNAKE_CASE  )  )  ) for transposition in num_transpositions  )


if __name__ == "__main__":
			__import__('''doctest''').testmod()


