





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

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
     from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
     _UpperCamelCase				=       get_tests_dir('''fixtures/test_sentencepiece.model''')


if is_torch_available():
     from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

_UpperCamelCase				=       12_8022
_UpperCamelCase				=       12_8028




@require_sentencepiece
class  _lowerCamelCase       (			__SCREAMING_SNAKE_CASE       ,      unittest.TestCase			):



      """simple docstring"""






      UpperCAmelCase_  :					int      			=MaMaaaTokenizer
      UpperCAmelCase_  :					int      			=False
      UpperCAmelCase_  :					Union[str, Any]      			=False
      UpperCAmelCase_  :					str      			=True







      def   UpperCAmelCase						(       self      )				->      Tuple:






        '''simple docstring'''






        super().setUp()

        __snake_case      : List[Any]						=				["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
        __snake_case      : Optional[Any]						=				dict(zip(UpperCAmelCase_ ,  range(len(UpperCAmelCase_      )      )      )      )
        __snake_case      : int						=				Path(self.tmpdirname      )
        save_json(UpperCAmelCase_ ,  save_dir / VOCAB_FILES_NAMES["vocab_file"]      )
        if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
          copyfile(UpperCAmelCase_ ,  save_dir / VOCAB_FILES_NAMES["spm_file"]      )

        __snake_case      : List[Any]						=				MaMaaaTokenizer.from_pretrained(self.tmpdirname      )
        tokenizer.save_pretrained(self.tmpdirname      )







      def   UpperCAmelCase						(       self ,  **UpperCAmelCase      )				->      str:






        '''simple docstring'''






        return MaMaaaTokenizer.from_pretrained(self.tmpdirname ,  **UpperCAmelCase_      )







      def   UpperCAmelCase						(       self ,  UpperCAmelCase      )				->      Optional[Any]:






        '''simple docstring'''






        return (
            "This is a test",
            "This is a test",
        )







      def   UpperCAmelCase						(       self      )				->      Dict:






        '''simple docstring'''






        __snake_case      : Dict						=				"</s>"
        __snake_case      : int						=				0

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







      def   UpperCAmelCase						(       self      )				->      Optional[Any]:






        '''simple docstring'''






        __snake_case      : Any						=				self.get_tokenizer()
        __snake_case      : Dict						=				list(tokenizer.get_vocab().keys()      )

        self.assertEqual(vocab_keys[0] ,  "</s>"      )
        self.assertEqual(vocab_keys[1] ,  "<unk>"      )
        self.assertEqual(vocab_keys[-1] ,  "<s>"      )
        self.assertEqual(len(UpperCAmelCase_      ) ,  tokenizer.vocab_size + len(tokenizer.get_added_vocab()      )      )







      @unittest.skip("Skip this test while all models are still to be uploaded."      )
      def   UpperCAmelCase						(       self      )				->      List[str]:






        '''simple docstring'''






        pass







      def   UpperCAmelCase						(       self      )				->      Dict:






        '''simple docstring'''






        __snake_case      : Optional[Any]						=				self.get_tokenizer()

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

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(UpperCAmelCase_      ) ,  [2, 3, 4, 5, 6] ,  )

        __snake_case      : List[Any]						=				tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]      )
        self.assertListEqual(UpperCAmelCase_ ,  ["▁This", "▁is", "▁a", "▁t", "est"]      )

        __snake_case      : int						=				tokenizer.convert_tokens_to_string(UpperCAmelCase_      )
        self.assertEqual(UpperCAmelCase_ ,  "This is a test"      )







      @slow
      def   UpperCAmelCase						(       self      )				->      Union[str, Any]:






        '''simple docstring'''






        __snake_case      : Optional[Any]						=				{"input_ids": [[128022, 110108, 397, 11, 38272, 2247, 124811, 285, 18105, 1586, 207, 7, 39534, 4428, 397, 1019, 18105, 1586, 207, 7, 41337, 16786, 241, 7, 20214, 17, 125690, 10398, 7, 44378, 58069, 68342, 7798, 7343, 11, 299, 33310, 4, 158, 37350, 94077, 4569, 299, 33310, 90, 4, 52840, 290, 4, 31270, 112, 299, 682, 4, 52840, 39953, 14079, 193, 52519, 90894, 17894, 120697, 11, 40445, 551, 17, 1019, 52519, 90894, 17756, 963, 11, 40445, 480, 17, 9792, 1120, 5173, 1393, 6240, 16786, 241, 120996, 28, 1245, 1393, 118240, 11123, 1019, 93612, 2691, 10618, 98058, 120409, 1928, 279, 4, 40683, 367, 178, 207, 1019, 103, 103121, 506, 65296, 5, 2], [128022, 21217, 367, 117, 125450, 128, 719, 7, 7308, 40, 93612, 12669, 1116, 16704, 71, 17785, 3699, 15592, 35, 144, 9584, 241, 11943, 713, 950, 799, 2247, 88427, 150, 149, 118813, 120706, 1019, 106906, 81518, 28, 1224, 22799, 397, 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], [128022, 1658, 123311, 5155, 5578, 4722, 279, 14947, 2366, 1120, 1197, 14, 1348, 9232, 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, 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, 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], [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, 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/m2m100_418M" ,  revision="c168bae485c864188cf9aa0e4108b0b6934dc91e" ,  )




@require_torch
@require_sentencepiece
@require_tokenizers
class  _lowerCamelCase       (			unittest.TestCase			):



      """simple docstring"""






      UpperCAmelCase_  :					Optional[int]      			="facebook/m2m100_418M"
      UpperCAmelCase_  :					List[Any]      			=[
          "In my opinion, there are two levels of response from the French government.",
          "NSA Affair Emphasizes Complete Lack of Debate on Intelligence",
      ]
      UpperCAmelCase_  :					List[str]      			=[
          "Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.",
          "L'affaire NSA souligne l'absence totale de débat sur le renseignement",
      ]

      # fmt: off
      UpperCAmelCase_  :					str      			=[EN_CODE, 593, 1_949, 115_781, 4, 71_586, 4_234, 60_633, 126_233, 432, 123_808, 15_592, 1_197, 117_132, 120_618, 5, 2]







      @classmethod
      def   UpperCAmelCase						(       cls      )				->      Dict:






        '''simple docstring'''






        __snake_case      : MaMaaaTokenizer						=				MaMaaaTokenizer.from_pretrained(
            cls.checkpoint_name ,  src_lang="en" ,  tgt_lang="fr"      )
        __snake_case      : List[Any]						=				1
        return cls







      def   UpperCAmelCase						(       self      )				->      Any:






        '''simple docstring'''






        self.assertEqual(self.tokenizer.get_lang_id("ar"      ) ,  128006      )
        self.assertEqual(self.tokenizer.get_lang_id("en"      ) ,  128022      )
        self.assertEqual(self.tokenizer.get_lang_id("ro"      ) ,  128076      )
        self.assertEqual(self.tokenizer.get_lang_id("mr"      ) ,  128063      )







      def   UpperCAmelCase						(       self      )				->      List[Any]:






        '''simple docstring'''






        __snake_case      : List[str]						=				self.tokenizer.get_vocab()
        self.assertEqual(len(UpperCAmelCase_      ) ,  self.tokenizer.vocab_size      )
        self.assertEqual(vocab["<unk>"] ,  3      )
        self.assertIn(self.tokenizer.get_lang_token("en"      ) ,  UpperCAmelCase_      )







      def   UpperCAmelCase						(       self      )				->      Dict:






        '''simple docstring'''






        __snake_case      : str						=				"en"
        __snake_case      : int						=				self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
        self.assertListEqual(self.expected_src_tokens ,  UpperCAmelCase_      )







      def   UpperCAmelCase						(       self      )				->      Dict:






        '''simple docstring'''






        self.assertIn(UpperCAmelCase_ ,  self.tokenizer.all_special_ids      )
        # fmt: off
        __snake_case      : Dict						=				[FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 14028, 136, 3286, 9706, 6, 90797, 6, 144012, 162, 88128, 30061, 5, 2]
        # fmt: on
        __snake_case      : int						=				self.tokenizer.decode(UpperCAmelCase_ ,  skip_special_tokens=UpperCAmelCase_      )
        __snake_case      : Dict						=				self.tokenizer.decode(generated_ids[1:] ,  skip_special_tokens=UpperCAmelCase_      )
        self.assertEqual(UpperCAmelCase_ ,  UpperCAmelCase_      )
        self.assertNotIn(self.tokenizer.eos_token ,  UpperCAmelCase_      )







      def   UpperCAmelCase						(       self      )				->      Optional[Any]:






        '''simple docstring'''






        __snake_case      : int						=				tempfile.mkdtemp()
        __snake_case      : Any						=				self.tokenizer.lang_token_to_id
        self.tokenizer.save_pretrained(UpperCAmelCase_      )
        __snake_case      : Tuple						=				MaMaaaTokenizer.from_pretrained(UpperCAmelCase_      )
        self.assertDictEqual(new_tok.lang_token_to_id ,  UpperCAmelCase_      )







      @require_torch
      def   UpperCAmelCase						(       self      )				->      Union[str, Any]:






        '''simple docstring'''






        __snake_case      : Union[str, Any]						=				"en"
        __snake_case      : Any						=				"fr"

        __snake_case      : Optional[Any]						=				self.tokenizer(self.src_text ,  text_target=self.tgt_text ,  padding=UpperCAmelCase_ ,  return_tensors="pt"      )

        __snake_case      : List[str]						=				shift_tokens_right(
            batch["labels"] ,  self.tokenizer.pad_token_id ,  self.tokenizer.eos_token_id      )

        for k in batch:
          __snake_case      : Any						=				batch[k].tolist()
        # batch = {k: v.tolist() for k,v in batch.items()}
        # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
        # batch.decoder_inputs_ids[0][0] ==
        assert batch.input_ids[1][0] == EN_CODE
        assert batch.input_ids[1][-1] == 2
        assert batch.labels[1][0] == FR_CODE
        assert batch.labels[1][-1] == 2
        assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]







      @require_torch
      def   UpperCAmelCase						(       self      )				->      Optional[int]:






        '''simple docstring'''






        __snake_case      : Tuple						=				"mr"
        self.assertListEqual(self.tokenizer.prefix_tokens ,  [self.tokenizer.get_lang_id("mr"      )]      )
        self.assertListEqual(self.tokenizer.suffix_tokens ,  [self.tokenizer.eos_token_id]      )

        __snake_case      : List[Any]						=				"zh"
        self.assertListEqual(self.tokenizer.prefix_tokens ,  [self.tokenizer.get_lang_id("zh"      )]      )
        self.assertListEqual(self.tokenizer.suffix_tokens ,  [self.tokenizer.eos_token_id]      )







      @require_torch
      def   UpperCAmelCase						(       self      )				->      List[str]:






        '''simple docstring'''






        __snake_case      : Any						=				"mr"
        self.tokenizer._switch_to_target_mode()
        self.assertListEqual(self.tokenizer.prefix_tokens ,  [self.tokenizer.get_lang_id("mr"      )]      )
        self.assertListEqual(self.tokenizer.suffix_tokens ,  [self.tokenizer.eos_token_id]      )
        self.tokenizer._switch_to_input_mode()
        self.assertListEqual(self.tokenizer.prefix_tokens ,  [self.tokenizer.get_lang_id(self.tokenizer.src_lang      )]      )

        __snake_case      : Tuple						=				"zh"
        self.tokenizer._switch_to_target_mode()
        self.assertListEqual(self.tokenizer.prefix_tokens ,  [self.tokenizer.get_lang_id("zh"      )]      )
        self.assertListEqual(self.tokenizer.suffix_tokens ,  [self.tokenizer.eos_token_id]      )
        self.tokenizer._switch_to_input_mode()
        self.assertListEqual(self.tokenizer.prefix_tokens ,  [self.tokenizer.get_lang_id(self.tokenizer.src_lang      )]      )







      @require_torch
      def   UpperCAmelCase						(       self      )				->      Union[str, Any]:






        '''simple docstring'''






        __snake_case      : List[str]						=				self.tokenizer._build_translation_inputs("A test" ,  return_tensors="pt" ,  src_lang="en" ,  tgt_lang="ar"      )

        self.assertEqual(
            nested_simplify(UpperCAmelCase_      ) ,  {
                # en_XX, A, test, EOS
                "input_ids": [[128022, 58, 4183, 2]],
                "attention_mask": [[1, 1, 1, 1]],
                # ar_AR
                "forced_bos_token_id": 128006,
            } ,  )








import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


__A									=				get_tests_dir("fixtures/test_sentencepiece_bpe.model")



class    _SCREAMING_SNAKE_CASE						(	__SCREAMING_SNAKE_CASE    ,							unittest.TestCase    ):







 '''simple docstring'''
 lowercase_		=			BartphoTokenizer
 lowercase_		=			False
 lowercase_		=			True

 def 							SCREAMING_SNAKE_CASE_					(self				:   List[Any])       ->Tuple:



   '''simple docstring'''



   super().setUp()

   lowerCamelCase__:      int			  =["▁This", "▁is", "▁a", "▁t", "est"]
   lowerCamelCase__:      Tuple			  =dict(zip(UpperCAmelCase_       , range(len(UpperCAmelCase_))))
   lowerCamelCase__:      List[Any]			  ={"unk_token": "<unk>"}

   lowerCamelCase__:      Dict			  =os.path.join(self.tmpdirname       , VOCAB_FILES_NAMES["monolingual_vocab_file"])
   with open(self.monolingual_vocab_file       , "w"       , encoding="utf-8") as fp:
     for token in vocab_tokens:
       fp.write(F"""{token} {vocab_tokens[token]}\n""")

   lowerCamelCase__:      Dict			  =BartphoTokenizer(UpperCAmelCase_       , self.monolingual_vocab_file       , **self.special_tokens_map)
   tokenizer.save_pretrained(self.tmpdirname)

 def 							SCREAMING_SNAKE_CASE_					(self				:   Optional[int]       , **UpperCAmelCase_				:   Optional[Any])       ->str:



   '''simple docstring'''



   kwargs.update(self.special_tokens_map)
   return BartphoTokenizer.from_pretrained(self.tmpdirname       , **UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_					(self				:   Union[str, Any]       , UpperCAmelCase_				:   Optional[Any])       ->List[Any]:



   '''simple docstring'''



   lowerCamelCase__:      Optional[int]			  ="This is a là test"
   lowerCamelCase__:      Optional[Any]			  ="This is a<unk><unk> test"
   return input_text, output_text







 def 							SCREAMING_SNAKE_CASE_					(self				:   List[Any])       ->Optional[Any]:



   '''simple docstring'''



   lowerCamelCase__:      str			  =BartphoTokenizer(UpperCAmelCase_       , self.monolingual_vocab_file       , **self.special_tokens_map)
   lowerCamelCase__:      List[Any]			  ="This is a là test"
   lowerCamelCase__:      Optional[int]			  ="▁This ▁is ▁a ▁l à ▁t est".split()
   lowerCamelCase__:      Optional[int]			  =tokenizer.tokenize(UpperCAmelCase_)
   self.assertListEqual(UpperCAmelCase_       , UpperCAmelCase_)

   lowerCamelCase__:      Tuple			  =tokens + [tokenizer.unk_token]
   lowerCamelCase__:      List[Any]			  =[4, 5, 6, 3, 3, 7, 8, 3]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase_)       , UpperCAmelCase_)

