





'''simple docstring'''




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():
  lowercase__    :      Optional[Any]						=    get_tests_dir('''fixtures/test_sentencepiece.model''')


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

lowercase__    :      List[Any]						=    12_80_22
lowercase__    :      int						=    12_80_28


@require_sentencepiece
class  SCREAMING_SNAKE_CASE    (_a					,		unittest.TestCase							):
     lowerCAmelCase					=       MaMaaaTokenizer
     lowerCAmelCase					=       False
     lowerCAmelCase					=       False
     lowerCAmelCase					=       True


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          super().setUp()

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

          __A						: int      =       MaMaaaTokenizer.from_pretrained(self.tmpdirname)
          tokenizer.save_pretrained(self.tmpdirname)


     def 							SCREAMING_SNAKE_CASE  (						self						,	**_UpperCAmelCase):

          '''simple docstring'''






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


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase):

          '''simple docstring'''






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


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: List[Any]      =       """</s>"""
          __A						: Any      =       0

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


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: List[str]      =       self.get_tokenizer()
          __A						: Optional[Any]      =       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(snake_case_)						,	tokenizer.vocab_size + len(tokenizer.get_added_vocab()))


     @unittest.skip('Skip this test while all models are still to be uploaded.')
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          pass


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Dict      =       self.get_tokenizer()

          __A						: List[str]      =       tokenizer.tokenize('This is a test')
          self.assertListEqual(snake_case_						,	['▁This', '▁is', '▁a', '▁t', 'est'])

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

          __A						: str      =       tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6])
          self.assertListEqual(snake_case_						,	['▁This', '▁is', '▁a', '▁t', 'est'])

          __A						: Dict      =       tokenizer.convert_tokens_to_string(snake_case_)
          self.assertEqual(snake_case_						,	'This is a test')


     @slow
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: str      =       {"""input_ids""": [[12_8022, 11_0108, 397, 11, 3_8272, 2247, 12_4811, 285, 1_8105, 1586, 207, 7, 3_9534, 4428, 397, 1019, 1_8105, 1586, 207, 7, 4_1337, 1_6786, 241, 7, 2_0214, 17, 12_5690, 1_0398, 7, 4_4378, 5_8069, 6_8342, 7798, 7343, 11, 299, 3_3310, 4, 158, 3_7350, 9_4077, 4569, 299, 3_3310, 90, 4, 5_2840, 290, 4, 3_1270, 112, 299, 682, 4, 5_2840, 3_9953, 1_4079, 193, 5_2519, 9_0894, 1_7894, 12_0697, 11, 4_0445, 551, 17, 1019, 5_2519, 9_0894, 1_7756, 963, 11, 4_0445, 480, 17, 9792, 1120, 5173, 1393, 6240, 1_6786, 241, 12_0996, 28, 1245, 1393, 11_8240, 1_1123, 1019, 9_3612, 2691, 1_0618, 9_8058, 12_0409, 1928, 279, 4, 4_0683, 367, 178, 207, 1019, 103, 10_3121, 506, 6_5296, 5, 2], [12_8022, 2_1217, 367, 117, 12_5450, 128, 719, 7, 7308, 40, 9_3612, 1_2669, 1116, 1_6704, 71, 1_7785, 3699, 1_5592, 35, 144, 9584, 241, 1_1943, 713, 950, 799, 2247, 8_8427, 150, 149, 11_8813, 12_0706, 1019, 10_6906, 8_1518, 28, 1224, 2_2799, 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], [12_8022, 1658, 12_3311, 5155, 5578, 4722, 279, 1_4947, 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=snake_case_						,	model_name='facebook/m2m100_418M'						,	revision='c168bae485c864188cf9aa0e4108b0b6934dc91e'						,	)




@require_torch
@require_sentencepiece
@require_tokenizers
class  SCREAMING_SNAKE_CASE    (unittest.TestCase							):
     lowerCAmelCase					=       '''facebook/m2m100_418M'''
     lowerCAmelCase					=       [
         '''In my opinion, there are two levels of response from the French government.''',
         '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
     ]
     lowerCAmelCase					=       [
         '''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
     lowerCAmelCase					=       [EN_CODE, 593, 1949, 11_5781, 4, 7_1586, 4234, 6_0633, 12_6233, 432, 12_3808, 1_5592, 1197, 11_7132, 12_0618, 5, 2]


     @classmethod
     def 							SCREAMING_SNAKE_CASE  (						cls):

          '''simple docstring'''






          __A						: MaMaaaTokenizer      =       MaMaaaTokenizer.from_pretrained(
              cls.checkpoint_name						,	src_lang='en'						,	tgt_lang='fr')
          __A						: int      =       1
          return cls


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          self.assertEqual(self.tokenizer.get_lang_id('ar')						,	12_8006)
          self.assertEqual(self.tokenizer.get_lang_id('en')						,	12_8022)
          self.assertEqual(self.tokenizer.get_lang_id('ro')						,	12_8076)
          self.assertEqual(self.tokenizer.get_lang_id('mr')						,	12_8063)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Dict      =       self.tokenizer.get_vocab()
          self.assertEqual(len(snake_case_)						,	self.tokenizer.vocab_size)
          self.assertEqual(vocab['<unk>']						,	3)
          self.assertIn(self.tokenizer.get_lang_token('en')						,	snake_case_)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Optional[Any]      =       """en"""
          __A						: List[str]      =       self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
          self.assertListEqual(self.expected_src_tokens						,	snake_case_)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          self.assertIn(snake_case_						,	self.tokenizer.all_special_ids)
          # fmt: off
          __A						: Optional[int]      =       [FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 1_4028, 136, 3286, 9706, 6, 9_0797, 6, 14_4012, 162, 8_8128, 3_0061, 5, 2]
          # fmt: on
          __A						: Optional[Any]      =       self.tokenizer.decode(snake_case_						,	skip_special_tokens=snake_case_)
          __A						: Tuple      =       self.tokenizer.decode(generated_ids[1:]						,	skip_special_tokens=snake_case_)
          self.assertEqual(snake_case_						,	snake_case_)
          self.assertNotIn(self.tokenizer.eos_token						,	snake_case_)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: int      =       tempfile.mkdtemp()
          __A						: Any      =       self.tokenizer.lang_token_to_id
          self.tokenizer.save_pretrained(snake_case_)
          __A						: str      =       MaMaaaTokenizer.from_pretrained(snake_case_)
          self.assertDictEqual(new_tok.lang_token_to_id						,	snake_case_)


     @require_torch
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Optional[Any]      =       """en"""
          __A						: Optional[Any]      =       """fr"""

          __A						: str      =       self.tokenizer(self.src_text						,	text_target=self.tgt_text						,	padding=snake_case_						,	return_tensors='pt')

          __A						: Optional[Any]      =       shift_tokens_right(
              batch['labels']						,	self.tokenizer.pad_token_id						,	self.tokenizer.eos_token_id)

          for k in batch:
               __A						: Union[str, 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 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Optional[Any]      =       """mr"""
          self.assertListEqual(self.tokenizer.prefix_tokens						,	[self.tokenizer.get_lang_id('mr')])
          self.assertListEqual(self.tokenizer.suffix_tokens						,	[self.tokenizer.eos_token_id])

          __A						: str      =       """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 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Union[str, 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)])

          __A						: Union[str, Any]      =       """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 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: List[Any]      =       self.tokenizer._build_translation_inputs('A test'						,	return_tensors='pt'						,	src_lang='en'						,	tgt_lang='ar')

          self.assertEqual(
              nested_simplify(snake_case_)						,	{
                  # en_XX, A, test, EOS
                  'input_ids': [[12_8022, 58, 4183, 2]],
                  'attention_mask': [[1, 1, 1, 1]],
                  # ar_AR
                  'forced_bos_token_id': 12_8006,
              }						,	)




'''simple docstring'''





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


__a          =		logging.get_logger(__name__)

__a          =		{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

__a          =		{
    "vocab_file": {
        "junnyu/roformer_chinese_small": "https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt",
        "junnyu/roformer_chinese_base": "https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt",
        "junnyu/roformer_chinese_char_small": (
            "https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_chinese_char_base": (
            "https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_small_discriminator": (
            "https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_small_generator": (
            "https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt"
        ),
    }
}

__a          =		{
    "junnyu/roformer_chinese_small": 1536,
    "junnyu/roformer_chinese_base": 1536,
    "junnyu/roformer_chinese_char_small": 512,
    "junnyu/roformer_chinese_char_base": 512,
    "junnyu/roformer_small_discriminator": 128,
    "junnyu/roformer_small_generator": 128,
}


__a          =		{
    "junnyu/roformer_chinese_small": {"do_lower_case": True},
    "junnyu/roformer_chinese_base": {"do_lower_case": True},
    "junnyu/roformer_chinese_char_small": {"do_lower_case": True},
    "junnyu/roformer_chinese_char_base": {"do_lower_case": True},
    "junnyu/roformer_small_discriminator": {"do_lower_case": True},
    "junnyu/roformer_small_generator": {"do_lower_case": True},
}







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		VOCAB_FILES_NAMES
    lowercase					=		PRETRAINED_VOCAB_FILES_MAP
    lowercase					=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase					=		PRETRAINED_INIT_CONFIGURATION
    lowercase					=		RoFormerTokenizer




    def __init__(    self					:     List[Any] ,     snake_case_					:     List[str]=None ,     snake_case_					:     Dict=None ,     snake_case_					:     Any=True ,     snake_case_					:     str="[UNK]" ,     snake_case_					:     List[str]="[SEP]" ,     snake_case_					:     Optional[Any]="[PAD]" ,     snake_case_					:     Union[str, Any]="[CLS]" ,     snake_case_					:     Union[str, Any]="[MASK]" ,     snake_case_					:     List[Any]=True ,     snake_case_					:     Optional[Any]=None ,     **snake_case_					:     Tuple ,     ):
          super().__init__(
              snake_case_ ,     tokenizer_file=snake_case_ ,     do_lower_case=snake_case_ ,     unk_token=snake_case_ ,     sep_token=snake_case_ ,     pad_token=snake_case_ ,     cls_token=snake_case_ ,     mask_token=snake_case_ ,     tokenize_chinese_chars=snake_case_ ,     strip_accents=snake_case_ ,     **snake_case_ ,     )

          snake_case__  :    str    						=      json.loads(self.backend_tokenizer.normalizer.__getstate__()						)
          if (
              pre_tok_state.get("""lowercase""" ,     snake_case_						) != do_lower_case
              or pre_tok_state.get("""strip_accents""" ,     snake_case_						) != strip_accents
          ):
                snake_case__  :    str    						=      getattr(snake_case_ ,     pre_tok_state.pop("""type"""						)						)
                snake_case__  :    Optional[int]    						=      do_lower_case
                snake_case__  :    Union[str, Any]    						=      strip_accents
                snake_case__  :    Union[str, Any]    						=      pre_tok_class(**snake_case_						)

          snake_case__  :    str    						=      do_lower_case




    def __getstate__(    self					:     int						):
          snake_case__  :    List[Any]    						=      self.__dict__.copy()
          snake_case__  :    str    						=      BertPreTokenizer()
          return state




    def __setstate__(    self					:     Dict ,     snake_case_					:     Dict						):
          snake_case__  :    List[Any]    						=      d
          snake_case__  :    Union[str, Any]    						=      self.__dict__["""_tokenizer"""].get_vocab()
          snake_case__  :    List[Any]    						=      PreTokenizer.custom(JiebaPreTokenizer(snake_case_						)						)




    def lowerCamelCase       (    self					:     str ,     snake_case_					:     Optional[Any] ,     snake_case_					:     List[str]=None						):
          snake_case__  :    str    						=      [self.cls_token_id] + token_ids_a + [self.sep_token_id]

          if token_ids_a:
                output += token_ids_a + [self.sep_token_id]

          return output




    def lowerCamelCase       (    self					:     str ,     snake_case_					:     List[int] ,     snake_case_					:     Optional[List[int]] = None						):
          snake_case__  :    int    						=      [self.sep_token_id]
          snake_case__  :    str    						=      [self.cls_token_id]
          if token_ids_a is None:
                return len(cls + token_ids_a + sep						) * [0]
          return len(cls + token_ids_a + sep						) * [0] + len(token_ids_a + sep						) * [1]




    def lowerCamelCase       (    self					:     Dict ,     snake_case_					:     str ,     snake_case_					:     Optional[str] = None						):
          snake_case__  :    Union[str, Any]    						=      self._tokenizer.model.save(snake_case_ ,     name=snake_case_						)
          return tuple(snake_case_						)




    def lowerCamelCase       (    self					:     Dict ,     snake_case_					:     List[str] ,     snake_case_					:     Tuple=None ,     snake_case_					:     List[str]=None ,     snake_case_					:     Union[str, Any]=False ,     **snake_case_					:     Tuple ,     ):
          snake_case__  :    Optional[Any]    						=      BertPreTokenizer()
          return super().save_pretrained(snake_case_ ,     snake_case_ ,     snake_case_ ,     snake_case_ ,     **snake_case_						)
