





"""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


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

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

a		:				Tuple  			=    250004
a		:				int  			=    250020


@require_sentencepiece
@require_tokenizers
class  __UpperCamelCase       (		a__	, unittest.TestCase		):
							lowerCamelCase     :      List[Any]         =MBartaaTokenizer
							lowerCamelCase     :      List[str]         =MBartaaTokenizerFast
							lowerCamelCase     :      Optional[int]         =True
							lowerCamelCase     :      List[Any]         =True






							def 					__a     (     self   )			->				str:
								super().setUp()

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






							def 					__a     (     self   )			->				int:
								a   :	int			=       "<s>"
								a   :	Tuple			=       0

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






							def 					__a     (     self   )			->				List[str]:
								a   :	Optional[int]			=       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(__UpperCamelCase   )   ,      1054   )






							def 					__a     (     self   )			->				List[Any]:
								self.assertEqual(self.get_tokenizer().vocab_size   ,      1054   )






							def 					__a     (     self   )			->				Optional[int]:
								a   :	str			=       MBartaaTokenizer(__UpperCamelCase   ,      src_lang="en_XX"   ,      tgt_lang="ro_RO"   ,      keep_accents=__UpperCamelCase   )

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

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(__UpperCamelCase   )   ,      [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,      )

								a   :	List[Any]			=       tokenizer.tokenize("I was born in 92000, and this is falsé."   )
								self.assertListEqual(
								    __UpperCamelCase   ,      [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   :	int			=       tokenizer.convert_tokens_to_ids(__UpperCamelCase   )
								self.assertListEqual(
								    __UpperCamelCase   ,      [
								        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(__UpperCamelCase   )
								self.assertListEqual(
								    __UpperCamelCase   ,      [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 					__a     (     self   )			->				List[str]:
								# fmt: off
								a   :	Tuple			=       {"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=__UpperCamelCase   ,      model_name="facebook/mbart-large-50"   ,      revision="d3913889c59cd5c9e456b269c376325eabad57e2"   ,      )






							def 					__a     (     self   )			->				Optional[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   :	List[str]			=       (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   :	Dict			=       self.rust_tokenizer_class.from_pretrained(__UpperCamelCase   ,      **__UpperCamelCase   )
										a   :	str			=       self.tokenizer_class.from_pretrained(__UpperCamelCase   ,      **__UpperCamelCase   )

										a   :	str			=       tempfile.mkdtemp()

										a   :	str			=       tokenizer_r.save_pretrained(__UpperCamelCase   )
										a   :	Optional[Any]			=       tokenizer_p.save_pretrained(__UpperCamelCase   )

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

										# Checks everything loads correctly in the same way
										a   :	Union[str, Any]			=       tokenizer_r.from_pretrained(__UpperCamelCase   )
										a   :	Optional[Any]			=       tokenizer_p.from_pretrained(__UpperCamelCase   )

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

										shutil.rmtree(__UpperCamelCase   )

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

										a   :	Tuple			=       tokenizer_r.save_pretrained(__UpperCamelCase   ,      legacy_format=__UpperCamelCase   )
										a   :	Optional[int]			=       tokenizer_p.save_pretrained(__UpperCamelCase   )

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

										# Checks everything loads correctly in the same way
										a   :	Optional[int]			=       tokenizer_r.from_pretrained(__UpperCamelCase   )
										a   :	Optional[Any]			=       tokenizer_p.from_pretrained(__UpperCamelCase   )

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

										shutil.rmtree(__UpperCamelCase   )

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

										a   :	Optional[Any]			=       tokenizer_r.save_pretrained(__UpperCamelCase   ,      legacy_format=__UpperCamelCase   )
										a   :	Optional[Any]			=       tokenizer_p.save_pretrained(__UpperCamelCase   )

										# 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   :	Tuple			=       tokenizer_r.from_pretrained(__UpperCamelCase   )
										a   :	Optional[Any]			=       tokenizer_p.from_pretrained(__UpperCamelCase   )

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

										shutil.rmtree(__UpperCamelCase   )


@require_torch
@require_sentencepiece
@require_tokenizers
class  __UpperCamelCase       (		unittest.TestCase		):
							lowerCamelCase     :      int         ="""facebook/mbart-large-50-one-to-many-mmt"""
							lowerCamelCase     :      Tuple         =[
							    """ 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.""",
							]
							lowerCamelCase     :      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.""",
							]
							lowerCamelCase     :      Optional[int]         =[EN_CODE, 8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2]






							@classmethod
							def 					__a     (     cls   )			->				int:
								a   :	List[Any]			=       MBartaaTokenizer.from_pretrained(
								    cls.checkpoint_name   ,      src_lang="en_XX"   ,      tgt_lang="ro_RO"   )
								a   :	Optional[int]			=       1
								return cls






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






							def 					__a     (     self   )			->				Optional[int]:
								self.assertIn(__UpperCamelCase   ,      self.tokenizer.all_special_ids   )
								a   :	Optional[Any]			=       [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
								a   :	List[str]			=       self.tokenizer.decode(__UpperCamelCase   ,      skip_special_tokens=__UpperCamelCase   )
								a   :	Any			=       self.tokenizer.decode(generated_ids[1:]   ,      skip_special_tokens=__UpperCamelCase   )
								self.assertEqual(__UpperCamelCase   ,      __UpperCamelCase   )
								self.assertNotIn(self.tokenizer.eos_token   ,      __UpperCamelCase   )






							def 					__a     (     self   )			->				Tuple:
								a   :	List[Any]			=       ["this is gunna be a long sentence " * 20]
								assert isinstance(src_text[0]   ,      __UpperCamelCase   )
								a   :	Union[str, Any]			=       10
								a   :	int			=       self.tokenizer(__UpperCamelCase   ,      max_length=__UpperCamelCase   ,      truncation=__UpperCamelCase   ).input_ids[0]
								self.assertEqual(ids[0]   ,      __UpperCamelCase   )
								self.assertEqual(ids[-1]   ,      2   )
								self.assertEqual(len(__UpperCamelCase   )   ,      __UpperCamelCase   )






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






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






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

								self.assertIsInstance(__UpperCamelCase   ,      __UpperCamelCase   )

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

								self.assertEqual(
								    nested_simplify(__UpperCamelCase   )   ,      {
								        # 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,
								    }   ,      )









"""simple docstring"""




from ..utils import DummyObject, requires_backends


class  __UpperCamelCase       (		metaclass=a__		):
							lowerCamelCase     :      Optional[Any]         =["""transformers""", """torch""", """note_seq"""]






							def __init__(     self   ,      *lowerCAmelCase__   ,      **lowerCAmelCase__   )			->				Union[str, Any]:
								requires_backends(self   ,      ["transformers", "torch", "note_seq"]   )






							@classmethod
							def 					__a     (     cls   ,      *lowerCAmelCase__   ,      **lowerCAmelCase__   )			->				Any:
								requires_backends(cls   ,      ["transformers", "torch", "note_seq"]   )






							@classmethod
							def 					__a     (     cls   ,      *lowerCAmelCase__   ,      **lowerCAmelCase__   )			->				int:
								requires_backends(cls   ,      ["transformers", "torch", "note_seq"]   )


