
import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 						_a   (						snake_case_ ,      unittest.TestCase       ):

       """simple docstring"""





       snake_case				=RobertaTokenizer
       snake_case				=RobertaTokenizerFast
       snake_case				=True
       snake_case				={'''cls_token''': '''<s>'''}
       def     SCREAMING_SNAKE_CASE  (					self	):
        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        _UpperCAmelCase 				=[
            'l',
            'o',
            'w',
            'e',
            'r',
            's',
            't',
            'i',
            'd',
            'n',
            '\u0120',
            '\u0120l',
            '\u0120n',
            '\u0120lo',
            '\u0120low',
            'er',
            '\u0120lowest',
            '\u0120newer',
            '\u0120wider',
            '<unk>',
        ]
        _UpperCAmelCase 				=dict(zip(__lowercase       ,					range(len(__lowercase	)	)	)	)
        _UpperCAmelCase 				=['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
        _UpperCAmelCase 				={'unk_token': '<unk>'}

        _UpperCAmelCase 				=os.path.join(self.tmpdirname       ,					VOCAB_FILES_NAMES["vocab_file"]	)
        _UpperCAmelCase 				=os.path.join(self.tmpdirname       ,					VOCAB_FILES_NAMES["merges_file"]	)
        with open(self.vocab_file       ,					"w"       ,					encoding="utf-8"	) as fp:
         fp.write(json.dumps(__lowercase	) + "\n"	)
        with open(self.merges_file       ,					"w"       ,					encoding="utf-8"	) as fp:
         fp.write("\n".join(__lowercase	)	)
       def     SCREAMING_SNAKE_CASE  (					self       ,					**_snake_case	):
        kwargs.update(self.special_tokens_map	)
        return self.tokenizer_class.from_pretrained(self.tmpdirname       ,					**__lowercase	)
       def     SCREAMING_SNAKE_CASE  (					self       ,					**_snake_case	):
        kwargs.update(self.special_tokens_map	)
        return RobertaTokenizerFast.from_pretrained(self.tmpdirname       ,					**__lowercase	)
       def     SCREAMING_SNAKE_CASE  (					self       ,					_snake_case	):
        _UpperCAmelCase 				='lower newer'
        _UpperCAmelCase 				='lower newer'
        return input_text, output_text
       def     SCREAMING_SNAKE_CASE  (					self	):
        _UpperCAmelCase 				=self.tokenizer_class(self.vocab_file       ,					self.merges_file       ,					**self.special_tokens_map	)
        _UpperCAmelCase 				='lower newer'
        _UpperCAmelCase 				=['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
        _UpperCAmelCase 				=tokenizer.tokenize(__lowercase	)  # , add_prefix_space=True)
        self.assertListEqual(__lowercase       ,					__lowercase	)

        _UpperCAmelCase 				=tokens + [tokenizer.unk_token]
        _UpperCAmelCase 				=[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowercase	)       ,					__lowercase	)
       def     SCREAMING_SNAKE_CASE  (					self	):
        _UpperCAmelCase 				=self.get_tokenizer()

        self.assertListEqual(tokenizer.encode("Hello world!"       ,					add_special_tokens=__lowercase	)       ,					[0, 3_1414, 232, 328, 2]	)
        self.assertListEqual(
            tokenizer.encode("Hello world! cécé herlolip 418"       ,					add_special_tokens=__lowercase	)       ,					[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]       ,					)
       @slow
       def     SCREAMING_SNAKE_CASE  (					self	):
        _UpperCAmelCase 				=self.tokenizer_class.from_pretrained("roberta-base"	)

        _UpperCAmelCase 				=tokenizer.encode("sequence builders"       ,					add_special_tokens=__lowercase	)
        _UpperCAmelCase 				=tokenizer.encode("multi-sequence build"       ,					add_special_tokens=__lowercase	)

        _UpperCAmelCase 				=tokenizer.encode(
            "sequence builders"       ,					add_special_tokens=__lowercase       ,					add_prefix_space=__lowercase	)
        _UpperCAmelCase 				=tokenizer.encode(
            "sequence builders"       ,					"multi-sequence build"       ,					add_special_tokens=__lowercase       ,					add_prefix_space=__lowercase	)

        _UpperCAmelCase 				=tokenizer.build_inputs_with_special_tokens(__lowercase	)
        _UpperCAmelCase 				=tokenizer.build_inputs_with_special_tokens(__lowercase       ,					__lowercase	)

        assert encoded_sentence == encoded_text_from_decode
        assert encoded_pair == encoded_pair_from_decode
       def     SCREAMING_SNAKE_CASE  (					self	):
        _UpperCAmelCase 				=self.get_tokenizer()

        _UpperCAmelCase 				='Encode this sequence.'
        _UpperCAmelCase 				=tokenizer.byte_encoder[' '.encode("utf-8"	)[0]]

        # Testing encoder arguments
        _UpperCAmelCase 				=tokenizer.encode(__lowercase       ,					add_special_tokens=__lowercase       ,					add_prefix_space=__lowercase	)
        _UpperCAmelCase 				=tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
        self.assertNotEqual(__lowercase       ,					__lowercase	)

        _UpperCAmelCase 				=tokenizer.encode(__lowercase       ,					add_special_tokens=__lowercase       ,					add_prefix_space=__lowercase	)
        _UpperCAmelCase 				=tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
        self.assertEqual(__lowercase       ,					__lowercase	)

        tokenizer.add_special_tokens({"bos_token": "<s>"}	)
        _UpperCAmelCase 				=tokenizer.encode(__lowercase       ,					add_special_tokens=__lowercase	)
        _UpperCAmelCase 				=tokenizer.convert_ids_to_tokens(encoded[1]	)[0]
        self.assertNotEqual(__lowercase       ,					__lowercase	)

        # Testing spaces after special tokens
        _UpperCAmelCase 				='<mask>'
        tokenizer.add_special_tokens(
            {"mask_token": AddedToken(__lowercase       ,					lstrip=__lowercase       ,					rstrip=__lowercase	)}	)  # mask token has a left space
        _UpperCAmelCase 				=tokenizer.convert_tokens_to_ids(__lowercase	)

        _UpperCAmelCase 				='Encode <mask> sequence'
        _UpperCAmelCase 				='Encode <mask>sequence'

        _UpperCAmelCase 				=tokenizer.encode(__lowercase	)
        _UpperCAmelCase 				=encoded.index(__lowercase	)
        _UpperCAmelCase 				=tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
        self.assertEqual(__lowercase       ,					__lowercase	)

        _UpperCAmelCase 				=tokenizer.encode(__lowercase	)
        _UpperCAmelCase 				=encoded.index(__lowercase	)
        _UpperCAmelCase 				=tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
        self.assertNotEqual(__lowercase       ,					__lowercase	)
       def     SCREAMING_SNAKE_CASE  (					self	):
        pass
       def     SCREAMING_SNAKE_CASE  (					self	):







        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"	):
          _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(__lowercase       ,					**__lowercase	)
          _UpperCAmelCase 				=self.tokenizer_class.from_pretrained(__lowercase       ,					**__lowercase	)
          _UpperCAmelCase 				='A, <mask> AllenNLP sentence.'
          _UpperCAmelCase 				=tokenizer_r.encode_plus(__lowercase       ,					add_special_tokens=__lowercase       ,					return_token_type_ids=__lowercase	)
          _UpperCAmelCase 				=tokenizer_p.encode_plus(__lowercase       ,					add_special_tokens=__lowercase       ,					return_token_type_ids=__lowercase	)

          # token_type_ids should put 0 everywhere
          self.assertEqual(sum(tokens_r["token_type_ids"]	)       ,					sum(tokens_p["token_type_ids"]	)	)

          # attention_mask should put 1 everywhere, so sum over length should be 1
          self.assertEqual(
              sum(tokens_r["attention_mask"]	) / len(tokens_r["attention_mask"]	)       ,					sum(tokens_p["attention_mask"]	) / len(tokens_p["attention_mask"]	)       ,					)

          _UpperCAmelCase 				=tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]	)
          _UpperCAmelCase 				=tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"]	)

          # Rust correctly handles the space before the mask while python doesnt
          self.assertSequenceEqual(tokens_p["input_ids"]       ,					[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]	)
          self.assertSequenceEqual(tokens_r["input_ids"]       ,					[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]	)

          self.assertSequenceEqual(
              __lowercase       ,					["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]	)
          self.assertSequenceEqual(
              __lowercase       ,					["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]	)
       def     SCREAMING_SNAKE_CASE  (					self	):







        for trim_offsets, add_prefix_space in itertools.product([True, False]       ,					repeat=2	):
         _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(
             self.tmpdirname       ,					use_fast=__lowercase       ,					add_prefix_space=__lowercase       ,					trim_offsets=__lowercase	)

         _UpperCAmelCase 				=json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()	)
         _UpperCAmelCase 				=json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()	)

         self.assertEqual(pre_tokenizer_state["add_prefix_space"]       ,					__lowercase	)

         self.assertEqual(post_processor_state["add_prefix_space"]       ,					__lowercase	)
         self.assertEqual(post_processor_state["trim_offsets"]       ,					__lowercase	)

       def     SCREAMING_SNAKE_CASE  (					self	):







        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"	):
          _UpperCAmelCase 				='hello'  # `hello` is a token in the vocabulary of `pretrained_name`
          _UpperCAmelCase 				=F"{text_of_1_token} {text_of_1_token}"

          _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(
              __lowercase       ,					use_fast=__lowercase       ,					add_prefix_space=__lowercase       ,					trim_offsets=__lowercase	)
          _UpperCAmelCase 				=tokenizer_r(__lowercase       ,					return_offsets_mapping=__lowercase       ,					add_special_tokens=__lowercase	)
          self.assertEqual(encoding.offset_mapping[0]       ,					(0, len(__lowercase	))	)
          self.assertEqual(
              encoding.offset_mapping[1]       ,					(len(__lowercase	) + 1, len(__lowercase	) + 1 + len(__lowercase	))       ,					)

          _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(
              __lowercase       ,					use_fast=__lowercase       ,					add_prefix_space=__lowercase       ,					trim_offsets=__lowercase	)
          _UpperCAmelCase 				=tokenizer_r(__lowercase       ,					return_offsets_mapping=__lowercase       ,					add_special_tokens=__lowercase	)
          self.assertEqual(encoding.offset_mapping[0]       ,					(0, len(__lowercase	))	)
          self.assertEqual(
              encoding.offset_mapping[1]       ,					(len(__lowercase	) + 1, len(__lowercase	) + 1 + len(__lowercase	))       ,					)

          _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(
              __lowercase       ,					use_fast=__lowercase       ,					add_prefix_space=__lowercase       ,					trim_offsets=__lowercase	)
          _UpperCAmelCase 				=tokenizer_r(__lowercase       ,					return_offsets_mapping=__lowercase       ,					add_special_tokens=__lowercase	)
          self.assertEqual(encoding.offset_mapping[0]       ,					(0, len(__lowercase	))	)
          self.assertEqual(
              encoding.offset_mapping[1]       ,					(len(__lowercase	), len(__lowercase	) + 1 + len(__lowercase	))       ,					)

          _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(
              __lowercase       ,					use_fast=__lowercase       ,					add_prefix_space=__lowercase       ,					trim_offsets=__lowercase	)
          _UpperCAmelCase 				=tokenizer_r(__lowercase       ,					return_offsets_mapping=__lowercase       ,					add_special_tokens=__lowercase	)
          self.assertEqual(encoding.offset_mapping[0]       ,					(0, len(__lowercase	))	)
          self.assertEqual(
              encoding.offset_mapping[1]       ,					(len(__lowercase	), len(__lowercase	) + 1 + len(__lowercase	))       ,					)

          _UpperCAmelCase 				=F" {text}"

          # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
          #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
          # )
          # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
          # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
          # self.assertEqual(
          #     encoding.offset_mapping[1],
          #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
          # )

          _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(
              __lowercase       ,					use_fast=__lowercase       ,					add_prefix_space=__lowercase       ,					trim_offsets=__lowercase	)
          _UpperCAmelCase 				=tokenizer_r(__lowercase       ,					return_offsets_mapping=__lowercase       ,					add_special_tokens=__lowercase	)
          self.assertEqual(encoding.offset_mapping[0]       ,					(1, 1 + len(__lowercase	))	)
          self.assertEqual(
              encoding.offset_mapping[1]       ,					(1 + len(__lowercase	) + 1, 1 + len(__lowercase	) + 1 + len(__lowercase	))       ,					)

          _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(
              __lowercase       ,					use_fast=__lowercase       ,					add_prefix_space=__lowercase       ,					trim_offsets=__lowercase	)
          _UpperCAmelCase 				=tokenizer_r(__lowercase       ,					return_offsets_mapping=__lowercase       ,					add_special_tokens=__lowercase	)
          self.assertEqual(encoding.offset_mapping[0]       ,					(0, 1 + len(__lowercase	))	)
          self.assertEqual(
              encoding.offset_mapping[1]       ,					(1 + len(__lowercase	), 1 + len(__lowercase	) + 1 + len(__lowercase	))       ,					)

          _UpperCAmelCase 				=self.rust_tokenizer_class.from_pretrained(
              __lowercase       ,					use_fast=__lowercase       ,					add_prefix_space=__lowercase       ,					trim_offsets=__lowercase	)
          _UpperCAmelCase 				=tokenizer_r(__lowercase       ,					return_offsets_mapping=__lowercase       ,					add_special_tokens=__lowercase	)
          self.assertEqual(encoding.offset_mapping[0]       ,					(0, 1 + len(__lowercase	))	)
          self.assertEqual(
              encoding.offset_mapping[1]       ,					(1 + len(__lowercase	), 1 + len(__lowercase	) + 1 + len(__lowercase	))       ,					)









'''simple docstring'''
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer


UpperCAmelCase_			:  int										=   logging.get_logger(__name__)

UpperCAmelCase_			:  int										=   {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

UpperCAmelCase_			:  List[str]										=   {
    'vocab_file': {
        'google/realm-cc-news-pretrained-embedder': (
            'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/vocab.txt'
        ),
        'google/realm-cc-news-pretrained-encoder': (
            'https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/vocab.txt'
        ),
        'google/realm-cc-news-pretrained-scorer': (
            'https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/vocab.txt'
        ),
        'google/realm-cc-news-pretrained-openqa': (
            'https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/vocab.txt'
        ),
        'google/realm-orqa-nq-openqa': 'https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/vocab.txt',
        'google/realm-orqa-nq-reader': 'https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/vocab.txt',
        'google/realm-orqa-wq-openqa': 'https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/vocab.txt',
        'google/realm-orqa-wq-reader': 'https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/vocab.txt',
    },
    'tokenizer_file': {
        'google/realm-cc-news-pretrained-embedder': (
            'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/tokenizer.jsont'
        ),
        'google/realm-cc-news-pretrained-encoder': (
            'https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/tokenizer.json'
        ),
        'google/realm-cc-news-pretrained-scorer': (
            'https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/tokenizer.json'
        ),
        'google/realm-cc-news-pretrained-openqa': (
            'https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/tokenizer.json'
        ),
        'google/realm-orqa-nq-openqa': (
            'https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/tokenizer.json'
        ),
        'google/realm-orqa-nq-reader': (
            'https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/tokenizer.json'
        ),
        'google/realm-orqa-wq-openqa': (
            'https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/tokenizer.json'
        ),
        'google/realm-orqa-wq-reader': (
            'https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/tokenizer.json'
        ),
    },
}

UpperCAmelCase_			:  str										=   {
    'google/realm-cc-news-pretrained-embedder': 5_1_2,
    'google/realm-cc-news-pretrained-encoder': 5_1_2,
    'google/realm-cc-news-pretrained-scorer': 5_1_2,
    'google/realm-cc-news-pretrained-openqa': 5_1_2,
    'google/realm-orqa-nq-openqa': 5_1_2,
    'google/realm-orqa-nq-reader': 5_1_2,
    'google/realm-orqa-wq-openqa': 5_1_2,
    'google/realm-orqa-wq-reader': 5_1_2,
}

UpperCAmelCase_			:  str										=   {
    'google/realm-cc-news-pretrained-embedder': {'do_lower_case': True},
    'google/realm-cc-news-pretrained-encoder': {'do_lower_case': True},
    'google/realm-cc-news-pretrained-scorer': {'do_lower_case': True},
    'google/realm-cc-news-pretrained-openqa': {'do_lower_case': True},
    'google/realm-orqa-nq-openqa': {'do_lower_case': True},
    'google/realm-orqa-nq-reader': {'do_lower_case': True},
    'google/realm-orqa-wq-openqa': {'do_lower_case': True},
    'google/realm-orqa-wq-reader': {'do_lower_case': True},
}

class     _lowerCamelCase       (     snake_case_					):




 '''simple docstring'''
 __lowercase					:		Union[str, Any]     				=    VOCAB_FILES_NAMES
 __lowercase					:		int     				=    PRETRAINED_VOCAB_FILES_MAP
 __lowercase					:		Union[str, Any]     				=    PRETRAINED_INIT_CONFIGURATION
 __lowercase					:		Union[str, Any]     				=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowercase					:		List[str]     				=    RealmTokenizer


 def __init__(   self   ,   __lowercase=None   ,   __lowercase=None   ,   __lowercase=True   ,   __lowercase="[UNK]"   ,   __lowercase="[SEP]"   ,   __lowercase="[PAD]"   ,   __lowercase="[CLS]"   ,   __lowercase="[MASK]"   ,   __lowercase=True   ,   __lowercase=None   ,   **__lowercase   ,   ):

  """simple docstring"""







  super().__init__(
      __lowercase   ,   tokenizer_file=__lowercase   ,   do_lower_case=__lowercase   ,   unk_token=__lowercase   ,   sep_token=__lowercase   ,   pad_token=__lowercase   ,   cls_token=__lowercase   ,   mask_token=__lowercase   ,   tokenize_chinese_chars=__lowercase   ,   strip_accents=__lowercase   ,   **__lowercase   ,   )

  __A	:		Optional[int]	  =      json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
  if (
      normalizer_state.get('lowercase'   ,   __lowercase    ) != do_lower_case
      or normalizer_state.get('strip_accents'   ,   __lowercase    ) != strip_accents
      or normalizer_state.get('handle_chinese_chars'   ,   __lowercase    ) != tokenize_chinese_chars
  ):
   __A	:		Tuple	  =      getattr(__lowercase   ,   normalizer_state.pop('type'    )    )
   __A	:		Optional[int]	  =      do_lower_case
   __A	:		List[str]	  =      strip_accents
   __A	:		Dict	  =      tokenize_chinese_chars
   __A	:		List[Any]	  =      normalizer_class(**__lowercase    )

  __A	:		int	  =      do_lower_case


 def 			snake_case__ (   self   ,   __lowercase   ,   **__lowercase    ):

  """simple docstring"""







  __A	:		Dict	  =      PaddingStrategy.MAX_LENGTH

  __A	:		Optional[int]	  =      text
  __A	:		Union[str, Any]	  =      kwargs.pop('text_pair'   ,   __lowercase    )
  __A	:		List[str]	  =      kwargs.pop('return_tensors'   ,   __lowercase    )

  __A	:		int	  =      {
      'input_ids': [],
      'attention_mask': [],
      'token_type_ids': [],
  }

  for idx, candidate_text in enumerate(__lowercase    ):
   if batch_text_pair is not None:
    __A	:		Tuple	  =      batch_text_pair[idx]
   else:
    __A	:		Union[str, Any]	  =      None

   __A	:		Optional[int]	  =      super().__call__(__lowercase   ,   __lowercase   ,   return_tensors=__lowercase   ,   **__lowercase    )

   __A	:		str	  =      encoded_candidates.get('input_ids'    )
   __A	:		Union[str, Any]	  =      encoded_candidates.get('attention_mask'    )
   __A	:		Optional[int]	  =      encoded_candidates.get('token_type_ids'    )

   if encoded_input_ids is not None:
    output_data["input_ids"].append(__lowercase    )
   if encoded_attention_mask is not None:
    output_data["attention_mask"].append(__lowercase    )
   if encoded_token_type_ids is not None:
    output_data["token_type_ids"].append(__lowercase    )

  __A	:		List[str]	  =      {key: item for key, item in output_data.items() if len(__lowercase    ) != 0}

  return BatchEncoding(__lowercase   ,   tensor_type=__lowercase    )


 def 			snake_case__ (   self   ,   __lowercase   ,   __lowercase=None    ):

  """simple docstring"""







  __A	:		Union[str, Any]	  =      [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 			snake_case__ (   self   ,   __lowercase   ,   __lowercase = None    ):

  """simple docstring"""







  __A	:		Union[str, Any]	  =      [self.sep_token_id]
  __A	:		Tuple	  =      [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 			snake_case__ (   self   ,   __lowercase   ,   __lowercase = None    ):

  """simple docstring"""







  __A	:		int	  =      self._tokenizer.model.save(__lowercase   ,   name=__lowercase    )
  return tuple(__lowercase    )






