






'''simple docstring'''



__UpperCamelCase      :       Optional[Any]      			=      [
    """DownloadConfig""",
    """DownloadManager""",
    """DownloadMode""",
    """StreamingDownloadManager""",
]

from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager







'''simple docstring'''



import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__UpperCamelCase      :       Tuple      			=      get_tests_dir("""fixtures/test_sentencepiece.model""")
@require_sentencepiece
@require_tokenizers
class 							__SCREAMING_SNAKE_CASE       (							_lowerCAmelCase      ,      unittest.TestCase     ):
      __a  					=XLMRobertaTokenizer
      __a  					=XLMRobertaTokenizerFast
      __a  					=True
      __a  					=True




      def  __UpperCamelCase							(  self      )							->Tuple:



         '''simple docstring'''
         super().setUp()

         # We have a SentencePiece fixture for testing
         __a				     =    XLMRobertaTokenizer(lowerCamelCase ,   keep_accents=lowerCamelCase      )
         tokenizer.save_pretrained(self.tmpdirname      )




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



         '''simple docstring'''
         __a				     =    '<pad>'
         __a				     =    1

         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      )							->int:



         '''simple docstring'''
         __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      ) ,   1002      )




      def  __UpperCamelCase							(  self      )							->Tuple:



         '''simple docstring'''
         self.assertEqual(self.get_tokenizer().vocab_size ,   1002      )




      def  __UpperCamelCase							(  self      )							->int:



         '''simple docstring'''
         __a				     =    XLMRobertaTokenizer(lowerCamelCase ,   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 [285, 46, 10, 170, 382]] ,   )

         __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, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                 #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
             ] ,   )

         __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>',
                 '.',
             ] ,   )




      def  __UpperCamelCase							(  self      )							->Dict:



         '''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

         __a				     =    (self.rust_tokenizer_class, 'hf-internal-testing/tiny-xlm-roberta', {})
         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      )




      @cached_property
      def  __UpperCamelCase							(  self      )							->List[str]:



         '''simple docstring'''
         return XLMRobertaTokenizer.from_pretrained('xlm-roberta-base'      )




      def  __UpperCamelCase							(  self      )							->Union[str, Any]:



         '''simple docstring'''
         with tempfile.NamedTemporaryFile() as f:
            shutil.copyfile(lowerCamelCase ,   f.name      )
            __a				     =    XLMRobertaTokenizer(f.name ,   keep_accents=lowerCamelCase      )
            __a				     =    pickle.dumps(lowerCamelCase      )
         pickle.loads(lowerCamelCase      )




      def  __UpperCamelCase							(  self      )							->Tuple:



         '''simple docstring'''
         if not self.test_rust_tokenizer:
            return

         __a				     =    self.get_tokenizer()
         __a				     =    self.get_rust_tokenizer()

         __a				     =    'I was born in 92000, and this is falsé.'

         __a				     =    tokenizer.tokenize(lowerCamelCase      )
         __a				     =    rust_tokenizer.tokenize(lowerCamelCase      )
         self.assertListEqual(lowerCamelCase ,   lowerCamelCase      )

         __a				     =    tokenizer.encode(lowerCamelCase ,   add_special_tokens=lowerCamelCase      )
         __a				     =    rust_tokenizer.encode(lowerCamelCase ,   add_special_tokens=lowerCamelCase      )
         self.assertListEqual(lowerCamelCase ,   lowerCamelCase      )

         __a				     =    self.get_rust_tokenizer()
         __a				     =    tokenizer.encode(lowerCamelCase      )
         __a				     =    rust_tokenizer.encode(lowerCamelCase      )
         self.assertListEqual(lowerCamelCase ,   lowerCamelCase      )




      @slow
      def  __UpperCamelCase							(  self      )							->Optional[Any]:



         '''simple docstring'''
         __a				     =    'Hello World!'
         __a				     =    [0, 3_5378, 6661, 38, 2]
         # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
         # xlmr.eval()
         # xlmr.encode(symbols)

         self.assertListEqual(lowerCamelCase ,   self.big_tokenizer.encode(lowerCamelCase      )      )




      @slow
      def  __UpperCamelCase							(  self      )							->Optional[int]:



         '''simple docstring'''
         __a				     =    (
             'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
             ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
         )
         __a				     =    [
             0,
             3293,
             83,
             10,
             4552,
             4989,
             7986,
             678,
             10,
             5915,
             111,
             17_9459,
             12_4850,
             4,
             6044,
             237,
             12,
             6,
             5,
             6,
             4,
             6780,
             705,
             15,
             1388,
             44,
             378,
             1_0114,
             711,
             152,
             20,
             6,
             5,
             2_2376,
             642,
             1221,
             1_5190,
             3_4153,
             450,
             5608,
             959,
             1119,
             5_7702,
             136,
             186,
             47,
             1098,
             2_9367,
             47,
             # 4426, # What fairseq tokenizes from "<unk>": "_<"
             # 3678, # What fairseq tokenizes from "<unk>": "unk"
             # 2740, # What fairseq tokenizes from "<unk>": ">"
             3,  # What we tokenize from "<unk>": "<unk>"
             6,  # Residue from the tokenization: an extra sentencepiece underline
             4,
             6044,
             237,
             6284,
             5_0901,
             528,
             31,
             90,
             34,
             927,
             2,
         ]
         # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
         # xlmr.eval()
         # xlmr.encode(symbols)

         self.assertListEqual(lowerCamelCase ,   self.big_tokenizer.encode(lowerCamelCase      )      )






      @slow
      def  __UpperCamelCase							(  self      )							->Tuple:



         '''simple docstring'''
         # fmt: off
         __a				     =    {'input_ids': [[0, 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], [0, 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], [0, 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=lowerCamelCase ,   model_name='xlm-roberta-base' ,   revision='d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3' ,   )