





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       __SCREAMING_SNAKE_CASE   (				__lowercase						,   unittest.TestCase):
						_SCREAMING_SNAKE_CASE		:    Any						=   RobertaTokenizer
						_SCREAMING_SNAKE_CASE		:    Any						=   RobertaTokenizerFast
						_SCREAMING_SNAKE_CASE		:    Optional[int]						=   True
						_SCREAMING_SNAKE_CASE		:    Tuple						=   {'''cls_token''': '''<s>'''}






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												super().setUp()

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

												lowerCAmelCase__        =  os.path.join(self.tmpdirname       ,  VOCAB_FILES_NAMES['vocab_file']				)
												lowerCAmelCase__        =  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(_UpperCamelCase				) + '\n'				)
												with open(self.merges_file       ,  'w'       ,  encoding='utf-8'				) as fp:
																		fp.write('\n'.join(_UpperCamelCase				)				)






						def  UpperCamelCase__ (		self       ,  **_UpperCamelCase				):






												"""simple docstring"""
												kwargs.update(self.special_tokens_map				)
												return self.tokenizer_class.from_pretrained(self.tmpdirname       ,  **_UpperCamelCase				)






						def  UpperCamelCase__ (		self       ,  **_UpperCamelCase				):






												"""simple docstring"""
												kwargs.update(self.special_tokens_map				)
												return RobertaTokenizerFast.from_pretrained(self.tmpdirname       ,  **_UpperCamelCase				)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  'lower newer'
												lowerCAmelCase__        =  'lower newer'
												return input_text, output_text






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.tokenizer_class(self.vocab_file       ,  self.merges_file       ,  **self.special_tokens_map				)
												lowerCAmelCase__        =  'lower newer'
												lowerCAmelCase__        =  ['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
												lowerCAmelCase__        =  tokenizer.tokenize(_UpperCamelCase				)  # , add_prefix_space=True)
												self.assertListEqual(_UpperCamelCase       ,  _UpperCamelCase				)

												lowerCAmelCase__        =  tokens + [tokenizer.unk_token]
												lowerCAmelCase__        =  [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase				)       ,  _UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.get_tokenizer()

												self.assertListEqual(tokenizer.encode('Hello world!'       ,  add_special_tokens=_UpperCamelCase				)       ,  [0, 3_14_14, 2_32, 3_28, 2]				)
												self.assertListEqual(
												    tokenizer.encode('Hello world! cécé herlolip 418'       ,  add_special_tokens=_UpperCamelCase				)       ,  [0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]       ,  )






						@slow
						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.tokenizer_class.from_pretrained('roberta-base'				)

												lowerCAmelCase__        =  tokenizer.encode('sequence builders'       ,  add_special_tokens=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.encode('multi-sequence build'       ,  add_special_tokens=_UpperCamelCase				)

												lowerCAmelCase__        =  tokenizer.encode(
												    'sequence builders'       ,  add_special_tokens=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.encode(
												    'sequence builders'       ,  'multi-sequence build'       ,  add_special_tokens=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase				)

												lowerCAmelCase__        =  tokenizer.build_inputs_with_special_tokens(_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.build_inputs_with_special_tokens(_UpperCamelCase       ,  _UpperCamelCase				)

												assert encoded_sentence == encoded_text_from_decode
												assert encoded_pair == encoded_pair_from_decode






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.get_tokenizer()

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

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

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

												tokenizer.add_special_tokens({'bos_token': '<s>'}				)
												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.convert_ids_to_tokens(encoded[1]				)[0]
												self.assertNotEqual(_UpperCamelCase       ,  _UpperCamelCase				)

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

												lowerCAmelCase__        =  'Encode <mask> sequence'
												lowerCAmelCase__        =  'Encode <mask>sequence'

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

												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase				)
												lowerCAmelCase__        =  encoded.index(_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
												self.assertNotEqual(_UpperCamelCase       ,  _UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												pass






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												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__        =  'A, <mask> AllenNLP sentence.'
																								lowerCAmelCase__        =  tokenizer_r.encode_plus(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase       ,  return_token_type_ids=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_p.encode_plus(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase       ,  return_token_type_ids=_UpperCamelCase				)

																								# 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']				)       ,  )

																								lowerCAmelCase__        =  tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']				)
																								lowerCAmelCase__        =  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, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]				)
																								self.assertSequenceEqual(tokens_r['input_ids']       ,  [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]				)

																								self.assertSequenceEqual(
																								    _UpperCamelCase       ,  ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']				)
																								self.assertSequenceEqual(
																								    _UpperCamelCase       ,  ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												for trim_offsets, add_prefix_space in itertools.product([True, False]       ,  repeat=2				):
																		lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																		    self.tmpdirname       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)

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

																		self.assertEqual(pre_tokenizer_state['add_prefix_space']       ,  _UpperCamelCase				)

																		self.assertEqual(post_processor_state['add_prefix_space']       ,  _UpperCamelCase				)
																		self.assertEqual(post_processor_state['trim_offsets']       ,  _UpperCamelCase				)







						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
												# `trim_offsets`
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"				):
																								lowerCAmelCase__        =  'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
																								lowerCAmelCase__        =  F"{text_of_1_token} {text_of_1_token}"

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

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

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

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

																								lowerCAmelCase__        =  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)),
																								# )

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

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

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













import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


__snake_case      :      Any             =       logging.get_logger(__name__)


__snake_case      :      Union[str, Any]             =       {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all LED models at https://huggingface.co/models?filter=LED
__snake_case      :      Optional[Any]             =       {
    """vocab_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json""",
    },
}

__snake_case      :      List[str]             =       {
    """allenai/led-base-16384""": 1_63_84,
}







@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def 		_UpperCamelCase				(      )					->				int:

						"""simple docstring"""



						lowerCAmelCase__        =  (
						    list(range(ord('!'						)      ,    ord('~'						) + 1						)						) + list(range(ord('¡'						)      ,    ord('¬'						) + 1						)						) + list(range(ord('®'						)      ,    ord('ÿ'						) + 1						)						)
						)
						lowerCAmelCase__        =  bs[:]
						lowerCAmelCase__        =  0
						for b in range(2**8						):
												if b not in bs:
																		bs.append(UpperCamelCase_						)
																		cs.append(2**8 + n						)
																		n += 1
						lowerCAmelCase__        =  [chr(UpperCamelCase_						) for n in cs]
						return dict(zip(UpperCamelCase_      ,    UpperCamelCase_						)						)







def 		_UpperCamelCase				(      UpperCamelCase_    :   Optional[Any]						)					->				Dict:

						"""simple docstring"""



						lowerCAmelCase__        =  set()
						lowerCAmelCase__        =  word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)						)
												lowerCAmelCase__        =  char
						return pairs


class       __SCREAMING_SNAKE_CASE   (				__lowercase):
						_SCREAMING_SNAKE_CASE		:    Optional[int]						=   VOCAB_FILES_NAMES
						_SCREAMING_SNAKE_CASE		:    Optional[int]						=   PRETRAINED_VOCAB_FILES_MAP
						_SCREAMING_SNAKE_CASE		:    Optional[Any]						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_SCREAMING_SNAKE_CASE		:    Any						=   ['''input_ids''', '''attention_mask''']






						def __init__(		self       ,  _UpperCamelCase       ,  _UpperCamelCase       ,  _UpperCamelCase="replace"       ,  _UpperCamelCase="<s>"       ,  _UpperCamelCase="</s>"       ,  _UpperCamelCase="</s>"       ,  _UpperCamelCase="<s>"       ,  _UpperCamelCase="<unk>"       ,  _UpperCamelCase="<pad>"       ,  _UpperCamelCase="<mask>"       ,  _UpperCamelCase=False       ,  **_UpperCamelCase       ,  ):






												"""simple docstring"""
												lowerCAmelCase__        =  AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				) if isinstance(_UpperCamelCase       ,  _UpperCamelCase				) else bos_token
												lowerCAmelCase__        =  AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				) if isinstance(_UpperCamelCase       ,  _UpperCamelCase				) else eos_token
												lowerCAmelCase__        =  AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				) if isinstance(_UpperCamelCase       ,  _UpperCamelCase				) else sep_token
												lowerCAmelCase__        =  AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				) if isinstance(_UpperCamelCase       ,  _UpperCamelCase				) else cls_token
												lowerCAmelCase__        =  AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				) if isinstance(_UpperCamelCase       ,  _UpperCamelCase				) else unk_token
												lowerCAmelCase__        =  AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				) if isinstance(_UpperCamelCase       ,  _UpperCamelCase				) else pad_token

												# Mask token behave like a normal word, i.e. include the space before it
												lowerCAmelCase__        =  AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				) if isinstance(_UpperCamelCase       ,  _UpperCamelCase				) else mask_token

												super().__init__(
												    errors=_UpperCamelCase       ,  bos_token=_UpperCamelCase       ,  eos_token=_UpperCamelCase       ,  unk_token=_UpperCamelCase       ,  sep_token=_UpperCamelCase       ,  cls_token=_UpperCamelCase       ,  pad_token=_UpperCamelCase       ,  mask_token=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  **_UpperCamelCase       ,  )

												with open(_UpperCamelCase       ,  encoding='utf-8'				) as vocab_handle:
																		lowerCAmelCase__        =  json.load(_UpperCamelCase				)
												lowerCAmelCase__        =  {v: k for k, v in self.encoder.items()}
												lowerCAmelCase__        =  errors  # how to handle errors in decoding
												lowerCAmelCase__        =  bytes_to_unicode()
												lowerCAmelCase__        =  {v: k for k, v in self.byte_encoder.items()}
												with open(_UpperCamelCase       ,  encoding='utf-8'				) as merges_handle:
																		lowerCAmelCase__        =  merges_handle.read().split('\n'				)[1:-1]
												lowerCAmelCase__        =  [tuple(merge.split()				) for merge in bpe_merges]
												lowerCAmelCase__        =  dict(zip(_UpperCamelCase       ,  range(len(_UpperCamelCase				)				)				)				)
												lowerCAmelCase__        =  {}
												lowerCAmelCase__        =  add_prefix_space

												# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
												lowerCAmelCase__        =  re.compile(r'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'				)






						@property
						# Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												return len(self.encoder				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												return dict(self.encoder       ,  **self.added_tokens_encoder				)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												if token in self.cache:
																		return self.cache[token]
												lowerCAmelCase__        =  tuple(_UpperCamelCase				)
												lowerCAmelCase__        =  get_pairs(_UpperCamelCase				)

												if not pairs:
																		return token

												while True:
																		lowerCAmelCase__        =  min(_UpperCamelCase       ,  key=lambda _UpperCamelCase				: self.bpe_ranks.get(_UpperCamelCase       ,  float('inf'				)				)				)
																		if bigram not in self.bpe_ranks:
																								break
																		lowerCAmelCase__  ,    lowerCAmelCase__        =  bigram
																		lowerCAmelCase__        =  []
																		lowerCAmelCase__        =  0
																		while i < len(_UpperCamelCase				):
																								try:
																														lowerCAmelCase__        =  word.index(_UpperCamelCase       ,  _UpperCamelCase				)
																								except ValueError:
																														new_word.extend(word[i:]				)
																														break
																								else:
																														new_word.extend(word[i:j]				)
																														lowerCAmelCase__        =  j

																								if word[i] == first and i < len(_UpperCamelCase				) - 1 and word[i + 1] == second:
																														new_word.append(first + second				)
																														i += 2
																								else:
																														new_word.append(word[i]				)
																														i += 1
																		lowerCAmelCase__        =  tuple(_UpperCamelCase				)
																		lowerCAmelCase__        =  new_word
																		if len(_UpperCamelCase				) == 1:
																								break
																		else:
																								lowerCAmelCase__        =  get_pairs(_UpperCamelCase				)
												lowerCAmelCase__        =  ' '.join(_UpperCamelCase				)
												lowerCAmelCase__        =  word
												return word






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  []
												for token in re.findall(self.pat       ,  _UpperCamelCase				):
																		lowerCAmelCase__        =  ''.join(
																		    self.byte_encoder[b] for b in token.encode('utf-8'				)				)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
																		bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_UpperCamelCase				).split(' '				)				)
												return bpe_tokens






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												return self.encoder.get(_UpperCamelCase       ,  self.encoder.get(self.unk_token				)				)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												return self.decoder.get(_UpperCamelCase				)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  ''.join(_UpperCamelCase				)
												lowerCAmelCase__        =  bytearray([self.byte_decoder[c] for c in text]				).decode('utf-8'       ,  errors=self.errors				)
												return text






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = None				):






												"""simple docstring"""
												if not os.path.isdir(_UpperCamelCase				):
																		logger.error(F"Vocabulary path ({save_directory}) should be a directory"				)
																		return
												lowerCAmelCase__        =  os.path.join(
												    _UpperCamelCase       ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)
												lowerCAmelCase__        =  os.path.join(
												    _UpperCamelCase       ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']				)

												with open(_UpperCamelCase       ,  'w'       ,  encoding='utf-8'				) as f:
																		f.write(json.dumps(self.encoder       ,  indent=2       ,  sort_keys=_UpperCamelCase       ,  ensure_ascii=_UpperCamelCase				) + '\n'				)

												lowerCAmelCase__        =  0
												with open(_UpperCamelCase       ,  'w'       ,  encoding='utf-8'				) as writer:
																		writer.write('#version: 0.2\n'				)
																		for bpe_tokens, token_index in sorted(self.bpe_ranks.items()       ,  key=lambda _UpperCamelCase				: kv[1]				):
																								if index != token_index:
																														logger.warning(
																														    F"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
																														    ' Please check that the tokenizer is not corrupted!'				)
																														lowerCAmelCase__        =  token_index
																								writer.write(' '.join(_UpperCamelCase				) + '\n'				)
																								index += 1

												return vocab_file, merge_file






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = None				):






												"""simple docstring"""
												if token_ids_a is None:
																		return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
												lowerCAmelCase__        =  [self.cls_token_id]
												lowerCAmelCase__        =  [self.sep_token_id]
												return cls + token_ids_a + sep + sep + token_ids_a + sep






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = None       ,  _UpperCamelCase = False				):






												"""simple docstring"""
												if already_has_special_tokens:
																		return super().get_special_tokens_mask(
																		    token_ids_a=_UpperCamelCase       ,  token_ids_a=_UpperCamelCase       ,  already_has_special_tokens=_UpperCamelCase				)

												if token_ids_a is None:
																		return [1] + ([0] * len(_UpperCamelCase				)) + [1]
												return [1] + ([0] * len(_UpperCamelCase				)) + [1, 1] + ([0] * len(_UpperCamelCase				)) + [1]






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = None				):






												"""simple docstring"""
												lowerCAmelCase__        =  [self.sep_token_id]
												lowerCAmelCase__        =  [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]






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase=False       ,  **_UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  kwargs.pop('add_prefix_space'       ,  self.add_prefix_space				)
												if (is_split_into_words or add_prefix_space) and (len(_UpperCamelCase				) > 0 and not text[0].isspace()):
																		lowerCAmelCase__        =  ' ' + text
												return (text, kwargs)







						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase = None       ,  _UpperCamelCase = PaddingStrategy.DO_NOT_PAD       ,  _UpperCamelCase = None       ,  _UpperCamelCase = None       ,  ):






												"""simple docstring"""
												lowerCAmelCase__        =  super()._pad(
												    encoded_inputs=_UpperCamelCase       ,  max_length=_UpperCamelCase       ,  padding_strategy=_UpperCamelCase       ,  pad_to_multiple_of=_UpperCamelCase       ,  return_attention_mask=_UpperCamelCase       ,  )

												# Load from model defaults
												if return_attention_mask is None:
																		lowerCAmelCase__        =  'attention_mask' in self.model_input_names

												if return_attention_mask and "global_attention_mask" in encoded_inputs:
																		lowerCAmelCase__        =  encoded_inputs[self.model_input_names[0]]
																		# `global_attention_mask` need to have the same length as other (sequential) inputs.
																		lowerCAmelCase__        =  len(encoded_inputs['global_attention_mask']				) != len(_UpperCamelCase				)

																		if needs_to_be_padded:
																								lowerCAmelCase__        =  len(_UpperCamelCase				) - len(encoded_inputs['global_attention_mask']				)

																								if self.padding_side == "right":
																														# Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
																														lowerCAmelCase__        =  (
																														    encoded_inputs['global_attention_mask'] + [-1] * difference
																														)
																								elif self.padding_side == "left":
																														lowerCAmelCase__        =  [-1] * difference + encoded_inputs[
																														    'global_attention_mask'
																														]
																								else:
																														raise ValueError('Invalid padding strategy:' + str(self.padding_side				)				)

												return encoded_inputs





