


'''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


__snake_case    						=get_tests_dir("""fixtures/test_sentencepiece.model""")

@require_sentencepiece
@require_tokenizers
class 		UpperCAmelCase_      (  __lowercase       ,	unittest.TestCase		):
     lowerCamelCase				:	Union[str, Any]		=     XLMRobertaTokenizer
     lowerCamelCase				:	Dict		=     XLMRobertaTokenizerFast
     lowerCamelCase				:	str		=     True
     lowerCamelCase				:	Optional[int]		=     True





     def 							__UpperCAmelCase      ( self       :      Dict    )				->  str:
        super().setUp()

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





     def 							__UpperCAmelCase      ( self       :      List[Any]    )				->  Union[str, Any]:
        lowerCAmelCase     =			'<pad>'
        lowerCAmelCase     =			1

        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]    )				->  Union[str, Any]:
        lowerCAmelCase     =			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__    )    ,      1_0_0_2    )





     def 							__UpperCAmelCase      ( self       :      Union[str, Any]    )				->  Tuple:
        self.assertEqual(self.get_tokenizer().vocab_size    ,      1_0_0_2    )





     def 							__UpperCAmelCase      ( self       :      Optional[int]    )				->  List[str]:
        lowerCAmelCase     =			XLMRobertaTokenizer(UpperCAmelCase__    ,      keep_accents=UpperCAmelCase__    )

        lowerCAmelCase     =			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 [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]    ,      )

        lowerCAmelCase     =			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',
                '.',
            ]    ,      )
        lowerCAmelCase     =			tokenizer.convert_tokens_to_ids(UpperCAmelCase__    )
        self.assertListEqual(
            UpperCAmelCase__    ,      [
                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 ^
            ]    ,      )

        lowerCAmelCase     =			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>',
                '.',
            ]    ,      )





     def 							__UpperCAmelCase      ( self       :      List[Any]    )				->  str:
        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

        lowerCAmelCase     =			(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})'''    ):
              lowerCAmelCase     =			self.rust_tokenizer_class.from_pretrained(UpperCAmelCase__    ,      **UpperCAmelCase__    )
              lowerCAmelCase     =			self.tokenizer_class.from_pretrained(UpperCAmelCase__    ,      **UpperCAmelCase__    )

              lowerCAmelCase     =			tempfile.mkdtemp()

              lowerCAmelCase     =			tokenizer_r.save_pretrained(UpperCAmelCase__    )
              lowerCAmelCase     =			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    )    )
              lowerCAmelCase     =			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
              lowerCAmelCase     =			tokenizer_r.from_pretrained(UpperCAmelCase__    )
              lowerCAmelCase     =			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
              lowerCAmelCase     =			tempfile.mkdtemp()

              lowerCAmelCase     =			tokenizer_r.save_pretrained(UpperCAmelCase__    ,      legacy_format=UpperCAmelCase__    )
              lowerCAmelCase     =			tokenizer_p.save_pretrained(UpperCAmelCase__    )

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

              # Checks everything loads correctly in the same way
              lowerCAmelCase     =			tokenizer_r.from_pretrained(UpperCAmelCase__    )
              lowerCAmelCase     =			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
              lowerCAmelCase     =			tempfile.mkdtemp()

              lowerCAmelCase     =			tokenizer_r.save_pretrained(UpperCAmelCase__    ,      legacy_format=UpperCAmelCase__    )
              lowerCAmelCase     =			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
              lowerCAmelCase     =			tokenizer_r.from_pretrained(UpperCAmelCase__    )
              lowerCAmelCase     =			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__    )





     @cached_property
     def 							__UpperCAmelCase      ( self       :      Union[str, Any]    )				->  Dict:
        return XLMRobertaTokenizer.from_pretrained('xlm-roberta-base'    )





     def 							__UpperCAmelCase      ( self       :      int    )				->  Union[str, Any]:
        with tempfile.NamedTemporaryFile() as f:
           shutil.copyfile(UpperCAmelCase__    ,      f.name    )
           lowerCAmelCase     =			XLMRobertaTokenizer(f.name    ,      keep_accents=UpperCAmelCase__    )
           lowerCAmelCase     =			pickle.dumps(UpperCAmelCase__    )
        pickle.loads(UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      Optional[int]    )				->  Dict:
        if not self.test_rust_tokenizer:
           return

        lowerCAmelCase     =			self.get_tokenizer()
        lowerCAmelCase     =			self.get_rust_tokenizer()

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

        lowerCAmelCase     =			tokenizer.tokenize(UpperCAmelCase__    )
        lowerCAmelCase     =			rust_tokenizer.tokenize(UpperCAmelCase__    )
        self.assertListEqual(UpperCAmelCase__    ,      UpperCAmelCase__    )

        lowerCAmelCase     =			tokenizer.encode(UpperCAmelCase__    ,      add_special_tokens=UpperCAmelCase__    )
        lowerCAmelCase     =			rust_tokenizer.encode(UpperCAmelCase__    ,      add_special_tokens=UpperCAmelCase__    )
        self.assertListEqual(UpperCAmelCase__    ,      UpperCAmelCase__    )

        lowerCAmelCase     =			self.get_rust_tokenizer()
        lowerCAmelCase     =			tokenizer.encode(UpperCAmelCase__    )
        lowerCAmelCase     =			rust_tokenizer.encode(UpperCAmelCase__    )
        self.assertListEqual(UpperCAmelCase__    ,      UpperCAmelCase__    )





     @slow
     def 							__UpperCAmelCase      ( self       :      Optional[Any]    )				->  Any:
        lowerCAmelCase     =			'Hello World!'
        lowerCAmelCase     =			[0, 3_5_3_7_8, 6_6_6_1, 3_8, 2]
        # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
        # xlmr.eval()
        # xlmr.encode(symbols)

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





     @slow
     def 							__UpperCAmelCase      ( self       :      Tuple    )				->  Optional[int]:
        lowerCAmelCase     =			(
            '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'
        )
        lowerCAmelCase     =			[
            0,
            3_2_9_3,
            8_3,
            1_0,
            4_5_5_2,
            4_9_8_9,
            7_9_8_6,
            6_7_8,
            1_0,
            5_9_1_5,
            1_1_1,
            1_7_9_4_5_9,
            1_2_4_8_5_0,
            4,
            6_0_4_4,
            2_3_7,
            1_2,
            6,
            5,
            6,
            4,
            6_7_8_0,
            7_0_5,
            1_5,
            1_3_8_8,
            4_4,
            3_7_8,
            1_0_1_1_4,
            7_1_1,
            1_5_2,
            2_0,
            6,
            5,
            2_2_3_7_6,
            6_4_2,
            1_2_2_1,
            1_5_1_9_0,
            3_4_1_5_3,
            4_5_0,
            5_6_0_8,
            9_5_9,
            1_1_1_9,
            5_7_7_0_2,
            1_3_6,
            1_8_6,
            4_7,
            1_0_9_8,
            2_9_3_6_7,
            4_7,
            # 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,
            6_0_4_4,
            2_3_7,
            6_2_8_4,
            5_0_9_0_1,
            5_2_8,
            3_1,
            9_0,
            3_4,
            9_2_7,
            2,
        ]
        # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
        # xlmr.eval()
        # xlmr.encode(symbols)

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





     @slow
     def 							__UpperCAmelCase      ( self       :      str    )				->  Tuple:
        # fmt: off
        lowerCAmelCase     =			{'input_ids': [[0, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 5_4_2_8, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 1_2_3_9_9, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 2_7_8_9, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 8_0_5, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [0, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 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, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 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='xlm-roberta-base'    ,      revision='d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'    ,      )









'''simple docstring'''




import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


__snake_case    						=logging.get_logger(__name__)

class 		UpperCAmelCase_      (  __lowercase		):





     def __init__( self       :      Dict    ,      *UpperCAmelCase__       :      Dict    ,      **UpperCAmelCase__       :      List[str]    )				->  None:
        warnings.warn(
            'The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
            ' use FlavaImageProcessor instead.'    ,      UpperCAmelCase__    ,      )
        super().__init__(*UpperCAmelCase__    ,      **UpperCAmelCase__    )





