



'''simple docstring'''

import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a							   =				'▁'

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






@require_sentencepiece
class 						a_		(     __UpperCamelCase    ,   unittest.TestCase    ):
							UpperCAmelCase			:		List[str]        =				BertGenerationTokenizer
							UpperCAmelCase			:		int        =				False
							UpperCAmelCase			:		Optional[Any]        =				True


							def    UpperCamelCase     (				self   :						List[str]			)			->					Union[str, Any]:
										super().setUp()

										snake_case:    Any      							=BertGenerationTokenizer(a_      ,						keep_accents=a_			)
										tokenizer.save_pretrained(self.tmpdirname			)


							def    UpperCamelCase     (				self   :						Optional[int]			)			->					Tuple:
										snake_case:    Optional[int]      							='<s>'
										snake_case:    Optional[Any]      							=1

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


							def    UpperCamelCase     (				self   :						Any			)			->					Dict:
										snake_case:    Any      							=list(self.get_tokenizer().get_vocab().keys()			)

										self.assertEqual(vocab_keys[0]      ,						'<unk>'			)
										self.assertEqual(vocab_keys[1]      ,						'<s>'			)
										self.assertEqual(vocab_keys[-1]      ,						'<pad>'			)
										self.assertEqual(len(a_			)      ,						1_0_0_2			)


							def    UpperCamelCase     (				self   :						Optional[int]			)			->					Dict:
										self.assertEqual(self.get_tokenizer().vocab_size      ,						1_0_0_0			)


							def    UpperCamelCase     (				self   :						Optional[int]			)			->					Union[str, Any]:
										snake_case:    Optional[Any]      							=BertGenerationTokenizer(a_      ,						keep_accents=a_			)

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

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(a_			)      ,						[2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]      ,						)

										snake_case:    Dict      							=tokenizer.tokenize('I was born in 92000, and this is falsé.'			)
										self.assertListEqual(
										    a_      ,						[
										        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',
										        '.',
										    ]      ,						)
										snake_case:    List[str]      							=tokenizer.convert_tokens_to_ids(a_			)
										self.assertListEqual(
										    a_      ,						[8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]      ,						)

										snake_case:    Optional[Any]      							=tokenizer.convert_ids_to_tokens(a_			)
										self.assertListEqual(
										    a_      ,						[
										        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>',
										        '.',
										    ]      ,						)


							@cached_property
							def    UpperCamelCase     (				self   :						Dict			)			->					Dict:
										return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'			)


							@slow
							def    UpperCamelCase     (				self   :						Any			)			->					Optional[int]:
										snake_case:    Tuple      							='Hello World!'
										snake_case:    Union[str, Any]      							=[1_8_5_3_6, 2_2_6_0, 1_0_1]

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


							@slow
							def    UpperCamelCase     (				self   :						List[Any]			)			->					Optional[Any]:
										snake_case:    Optional[Any]      							=(
										    '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'
										)
										snake_case:    List[Any]      							=[
										    8_7_1,
										    4_1_9,
										    3_5_8,
										    9_4_6,
										    9_9_1,
										    2_5_2_1,
										    4_5_2,
										    3_5_8,
										    1_3_5_7,
										    3_8_7,
										    7_7_5_1,
										    3_5_3_6,
										    1_1_2,
										    9_8_5,
										    4_5_6,
										    1_2_6,
										    8_6_5,
										    9_3_8,
										    5_4_0_0,
										    5_7_3_4,
										    4_5_8,
										    1_3_6_8,
										    4_6_7,
										    7_8_6,
										    2_4_6_2,
										    5_2_4_6,
										    1_1_5_9,
										    6_3_3,
										    8_6_5,
										    4_5_1_9,
										    4_5_7,
										    5_8_2,
										    8_5_2,
										    2_5_5_7,
										    4_2_7,
										    9_1_6,
										    5_0_8,
										    4_0_5,
										    3_4_3_2_4,
										    4_9_7,
										    3_9_1,
										    4_0_8,
										    1_1_3_4_2,
										    1_2_4_4,
										    3_8_5,
										    1_0_0,
										    9_3_8,
										    9_8_5,
										    4_5_6,
										    5_7_4,
										    3_6_2,
										    1_2_5_9_7,
										    3_2_0_0,
										    3_1_2_9,
										    1_1_7_2,
										]

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


							@require_torch
							@slow
							def    UpperCamelCase     (				self   :						Any			)			->					Tuple:
										import torch

										from transformers import BertGenerationConfig, BertGenerationEncoder

										# Build sequence
										snake_case:    List[Any]      							=list(self.big_tokenizer.get_vocab().keys()			)[:1_0]
										snake_case:    int      							=' '.join(a_			)
										snake_case:    Optional[Any]      							=self.big_tokenizer.encode_plus(a_      ,						return_tensors='pt'      ,						return_token_type_ids=a_			)
										snake_case:    int      							=self.big_tokenizer.batch_encode_plus(
										    [sequence + ' ' + sequence]      ,						return_tensors='pt'      ,						return_token_type_ids=a_			)

										snake_case:    Optional[int]      							=BertGenerationConfig()
										snake_case:    Tuple      							=BertGenerationEncoder(a_			)

										assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

										with torch.no_grad():
													model(**a_			)
													model(**a_			)




							@slow
							def    UpperCamelCase     (				self   :						Dict			)			->					Tuple:
										# fmt: off
										snake_case:    Dict      							={'input_ids': [[3_9_2_8_6, 4_5_8, 3_6_3_3_5, 2_0_0_1, 4_5_6, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 7_7_4_6, 1_7_4_1, 1_1_1_5_7, 3_9_1, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 3_9_6_7, 3_5_4_1_2, 1_1_3, 4_9_3_6, 1_0_9, 3_8_7_0, 2_3_7_7, 1_1_3, 3_0_0_8_4, 4_5_7_2_0, 4_5_8, 1_3_4, 1_7_4_9_6, 1_1_2, 5_0_3, 1_1_6_7_2, 1_1_3, 1_1_8, 1_1_2, 5_6_6_5, 1_3_3_4_7, 3_8_6_8_7, 1_1_2, 1_4_9_6, 3_1_3_8_9, 1_1_2, 3_2_6_8, 4_7_2_6_4, 1_3_4, 9_6_2, 1_1_2, 1_6_3_7_7, 8_0_3_5, 2_3_1_3_0, 4_3_0, 1_2_1_6_9, 1_5_5_1_8, 2_8_5_9_2, 4_5_8, 1_4_6, 4_1_6_9_7, 1_0_9, 3_9_1, 1_2_1_6_9, 1_5_5_1_8, 1_6_6_8_9, 4_5_8, 1_4_6, 4_1_3_5_8, 1_0_9, 4_5_2, 7_2_6, 4_0_3_4, 1_1_1, 7_6_3, 3_5_4_1_2, 5_0_8_2, 3_8_8, 1_9_0_3, 1_1_1, 9_0_5_1, 3_9_1, 2_8_7_0, 4_8_9_1_8, 1_9_0_0, 1_1_2_3, 5_5_0, 9_9_8, 1_1_2, 9_5_8_6, 1_5_9_8_5, 4_5_5, 3_9_1, 4_1_0, 2_2_9_5_5, 3_7_6_3_6, 1_1_4], [4_4_8, 1_7_4_9_6, 4_1_9, 3_6_6_3, 3_8_5, 7_6_3, 1_1_3, 2_7_5_3_3, 2_8_7_0, 3_2_8_3, 1_3_0_4_3, 1_6_3_9, 2_4_7_1_3, 5_2_3, 6_5_6, 2_4_0_1_3, 1_8_5_5_0, 2_5_2_1, 5_1_7, 2_7_0_1_4, 2_1_2_4_4, 4_2_0, 1_2_1_2, 1_4_6_5, 3_9_1, 9_2_7, 4_8_3_3, 3_8_8, 5_7_8, 1_1_7_8_6, 1_1_4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [4_8_4, 2_1_6_9, 7_6_8_7, 2_1_9_3_2, 1_8_1_4_6, 7_2_6, 3_6_3, 1_7_0_3_2, 3_3_9_1, 1_1_4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=a_      ,						model_name='google/bert_for_seq_generation_L-24_bbc_encoder'      ,						revision='c817d1fd1be2ffa69431227a1fe320544943d4db'      ,						)






import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


__magic_name__  							=	logging.get_logger(__name__)

__magic_name__  							=	{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__magic_name__  							=	{
    '''vocab_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/vocab.json''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/vocab.json''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/vocab.json''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/merges.txt''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/merges.txt''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/merges.txt''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/tokenizer.json''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/tokenizer.json''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json''',
        '''roberta-base-openai-detector''': (
            '''https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json'''
        ),
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json'''
        ),
    },
}

__magic_name__  							=	{
    '''roberta-base''': 512,
    '''roberta-large''': 512,
    '''roberta-large-mnli''': 512,
    '''distilroberta-base''': 512,
    '''roberta-base-openai-detector''': 512,
    '''roberta-large-openai-detector''': 512,
}




class        _SCREAMING_SNAKE_CASE	(   __UpperCamelCase			):
      _A    :		Dict     						=  VOCAB_FILES_NAMES
      _A    :		List[str]     						=  PRETRAINED_VOCAB_FILES_MAP
      _A    :		Any     						=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _A    :		str     						=  ['input_ids', 'attention_mask']
      _A    :		Dict     						=  RobertaTokenizer
      def __init__(      self		,						lowerCamelCase=None		,						lowerCamelCase=None		,						lowerCamelCase=None		,						lowerCamelCase="replace"		,						lowerCamelCase="<s>"		,						lowerCamelCase="</s>"		,						lowerCamelCase="</s>"		,						lowerCamelCase="<s>"		,						lowerCamelCase="<unk>"		,						lowerCamelCase="<pad>"		,						lowerCamelCase="<mask>"		,						lowerCamelCase=False		,						lowerCamelCase=True		,						**lowerCamelCase		,						):
          super().__init__(
              lowerCamelCase		,						lowerCamelCase		,						tokenizer_file=lowerCamelCase		,						errors=lowerCamelCase		,						bos_token=lowerCamelCase		,						eos_token=lowerCamelCase		,						sep_token=lowerCamelCase		,						cls_token=lowerCamelCase		,						unk_token=lowerCamelCase		,						pad_token=lowerCamelCase		,						mask_token=lowerCamelCase		,						add_prefix_space=lowerCamelCase		,						trim_offsets=lowerCamelCase		,						**lowerCamelCase		,						)

          snake_case__    =					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
          if pre_tok_state.get("add_prefix_space"		,						lowerCamelCase			) != add_prefix_space:
              snake_case__    =					getattr(lowerCamelCase		,						pre_tok_state.pop("type"			)			)
              snake_case__    =					add_prefix_space
              snake_case__    =					pre_tok_class(**lowerCamelCase			)

          snake_case__    =					add_prefix_space

          snake_case__    =					"post_processor"
          snake_case__    =					getattr(self.backend_tokenizer		,						lowerCamelCase		,						lowerCamelCase			)
          if tokenizer_component_instance:
              snake_case__    =					json.loads(tokenizer_component_instance.__getstate__()			)

              # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
              if "sep" in state:
                  snake_case__    =					tuple(state["sep"]			)
              if "cls" in state:
                  snake_case__    =					tuple(state["cls"]			)

              snake_case__    =					False

              if state.get("add_prefix_space"		,						lowerCamelCase			) != add_prefix_space:
                  snake_case__    =					add_prefix_space
                  snake_case__    =					True

              if state.get("trim_offsets"		,						lowerCamelCase			) != trim_offsets:
                  snake_case__    =					trim_offsets
                  snake_case__    =					True

              if changes_to_apply:
                  snake_case__    =					getattr(lowerCamelCase		,						state.pop("type"			)			)
                  snake_case__    =					component_class(**lowerCamelCase			)
                  setattr(self.backend_tokenizer		,						lowerCamelCase		,						lowerCamelCase			)
      @property
      def A_      (      self			):
          if self._mask_token is None:
              if self.verbose:
                  logger.error("Using mask_token, but it is not set yet."			)
              return None
          return str(self._mask_token			)
      @mask_token.setter
      def A_      (      self		,						lowerCamelCase			):
          snake_case__    =					AddedToken(lowerCamelCase		,						lstrip=lowerCamelCase		,						rstrip=lowerCamelCase			) if isinstance(lowerCamelCase		,						lowerCamelCase			) else value
          snake_case__    =					value
      def A_      (      self		,						*lowerCamelCase		,						**lowerCamelCase			):
          snake_case__    =					kwargs.get("is_split_into_words"		,						lowerCamelCase			)
          assert self.add_prefix_space or not is_split_into_words, (
              F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
              "to use it with pretokenized inputs."
          )

          return super()._batch_encode_plus(*lowerCamelCase		,						**lowerCamelCase			)
      def A_      (      self		,						*lowerCamelCase		,						**lowerCamelCase			):
          snake_case__    =					kwargs.get("is_split_into_words"		,						lowerCamelCase			)

          assert self.add_prefix_space or not is_split_into_words, (
              F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
              "to use it with pretokenized inputs."
          )

          return super()._encode_plus(*lowerCamelCase		,						**lowerCamelCase			)
      def A_      (      self		,						lowerCamelCase		,						lowerCamelCase = None			):
          snake_case__    =					self._tokenizer.model.save(lowerCamelCase		,						name=lowerCamelCase			)
          return tuple(lowerCamelCase			)
      def A_      (      self		,						lowerCamelCase		,						lowerCamelCase=None			):
          snake_case__    =					[self.bos_token_id] + token_ids_a + [self.eos_token_id]
          if token_ids_a is None:
              return output

          return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]



      def A_      (      self		,						lowerCamelCase		,						lowerCamelCase = None			):
          snake_case__    =					[self.sep_token_id]
          snake_case__    =					[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 + sep + token_ids_a + sep			) * [0]



