



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       :	int            =get_tests_dir('fixtures/test_sentencepiece.model')



@require_sentencepiece
@require_tokenizers
class  lowerCamelCase__    (							lowerCamelCase__   ,       unittest.TestCase):




		'''simple docstring'''



		snake_case_			=XLMRobertaTokenizer
		snake_case_			=XLMRobertaTokenizerFast
		snake_case_			=True
		snake_case_			=True



		def 	lowerCAmelCase__   (self				)  ->    Any:

						"""simple docstring"""






						super().setUp()

						# We have a SentencePiece fixture for testing
						lowerCAmelCase__  :       str				=  XLMRobertaTokenizer(__lowerCamelCase	,keep_accents=__lowerCamelCase				)
						tokenizer.save_pretrained(self.tmpdirname				)



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

						"""simple docstring"""






						lowerCAmelCase__  :       List[str]				=  '''<pad>'''
						lowerCAmelCase__  :       Union[str, Any]				=  1

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



		def 	lowerCAmelCase__   (self				)  ->    Any:

						"""simple docstring"""






						lowerCAmelCase__  :       List[Any]				=  list(self.get_tokenizer().get_vocab().keys()				)

						self.assertEqual(vocab_keys[0]	,'''<s>'''				)
						self.assertEqual(vocab_keys[1]	,'''<pad>'''				)
						self.assertEqual(vocab_keys[-1]	,'''<mask>'''				)
						self.assertEqual(len(__lowerCamelCase				)	,10_02				)



		def 	lowerCAmelCase__   (self				)  ->    Any:

						"""simple docstring"""






						self.assertEqual(self.get_tokenizer().vocab_size	,10_02				)



		def 	lowerCAmelCase__   (self				)  ->    int:

						"""simple docstring"""






						lowerCAmelCase__  :       str				=  XLMRobertaTokenizer(__lowerCamelCase	,keep_accents=__lowerCamelCase				)

						lowerCAmelCase__  :       Dict				=  tokenizer.tokenize('''This is a test'''				)
						self.assertListEqual(__lowerCamelCase	,['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']				)

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(__lowerCamelCase				)	,[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]	,)

						lowerCAmelCase__  :       Optional[Any]				=  tokenizer.tokenize('''I was born in 92000, and this is falsé.'''				)
						self.assertListEqual(
						    __lowerCamelCase	,[
						        SPIECE_UNDERLINE + '''I''',
						        SPIECE_UNDERLINE + '''was''',
						        SPIECE_UNDERLINE + '''b''',
						        '''or''',
						        '''n''',
						        SPIECE_UNDERLINE + '''in''',
						        SPIECE_UNDERLINE + '''''',
						        '''9''',
						        '''2''',
						        '''0''',
						        '''0''',
						        '''0''',
						        ''',''',
						        SPIECE_UNDERLINE + '''and''',
						        SPIECE_UNDERLINE + '''this''',
						        SPIECE_UNDERLINE + '''is''',
						        SPIECE_UNDERLINE + '''f''',
						        '''al''',
						        '''s''',
						        '''é''',
						        '''.''',
						    ]	,)
						lowerCAmelCase__  :       Any				=  tokenizer.convert_tokens_to_ids(__lowerCamelCase				)
						self.assertListEqual(
						    __lowerCamelCase	,[
						        value + tokenizer.fairseq_offset
						        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
						        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
						    ]	,)

						lowerCAmelCase__  :       Union[str, Any]				=  tokenizer.convert_ids_to_tokens(__lowerCamelCase				)
						self.assertListEqual(
						    __lowerCamelCase	,[
						        SPIECE_UNDERLINE + '''I''',
						        SPIECE_UNDERLINE + '''was''',
						        SPIECE_UNDERLINE + '''b''',
						        '''or''',
						        '''n''',
						        SPIECE_UNDERLINE + '''in''',
						        SPIECE_UNDERLINE + '''''',
						        '''<unk>''',
						        '''2''',
						        '''0''',
						        '''0''',
						        '''0''',
						        ''',''',
						        SPIECE_UNDERLINE + '''and''',
						        SPIECE_UNDERLINE + '''this''',
						        SPIECE_UNDERLINE + '''is''',
						        SPIECE_UNDERLINE + '''f''',
						        '''al''',
						        '''s''',
						        '''<unk>''',
						        '''.''',
						    ]	,)



		def 	lowerCAmelCase__   (self				)  ->    Any:

						"""simple docstring"""






						if not self.test_slow_tokenizer:
										# as we don't have a slow version, we can't compare the outputs between slow and fast versions
										return

						lowerCAmelCase__  :       List[str]				=  (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__  :       List[str]				=  self.rust_tokenizer_class.from_pretrained(__lowerCamelCase	,**__lowerCamelCase				)
														lowerCAmelCase__  :       Union[str, Any]				=  self.tokenizer_class.from_pretrained(__lowerCamelCase	,**__lowerCamelCase				)

														lowerCAmelCase__  :       Union[str, Any]				=  tempfile.mkdtemp()

														lowerCAmelCase__  :       Any				=  tokenizer_r.save_pretrained(__lowerCamelCase				)
														lowerCAmelCase__  :       List[Any]				=  tokenizer_p.save_pretrained(__lowerCamelCase				)

														# Checks it save with the same files + the tokenizer.json file for the fast one
														self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files				)				)
														lowerCAmelCase__  :       Any				=  tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f				)
														self.assertSequenceEqual(__lowerCamelCase	,__lowerCamelCase				)

														# Checks everything loads correctly in the same way
														lowerCAmelCase__  :       int				=  tokenizer_r.from_pretrained(__lowerCamelCase				)
														lowerCAmelCase__  :       List[Any]				=  tokenizer_p.from_pretrained(__lowerCamelCase				)

														# Check special tokens are set accordingly on Rust and Python
														for key in tokenizer_pp.special_tokens_map:
																		self.assertTrue(hasattr(__lowerCamelCase	,__lowerCamelCase				)				)
																		# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																		# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

														shutil.rmtree(__lowerCamelCase				)

														# Save tokenizer rust, legacy_format=True
														lowerCAmelCase__  :       Any				=  tempfile.mkdtemp()

														lowerCAmelCase__  :       str				=  tokenizer_r.save_pretrained(__lowerCamelCase	,legacy_format=__lowerCamelCase				)
														lowerCAmelCase__  :       Any				=  tokenizer_p.save_pretrained(__lowerCamelCase				)

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

														# Checks everything loads correctly in the same way
														lowerCAmelCase__  :       List[Any]				=  tokenizer_r.from_pretrained(__lowerCamelCase				)
														lowerCAmelCase__  :       Optional[int]				=  tokenizer_p.from_pretrained(__lowerCamelCase				)

														# Check special tokens are set accordingly on Rust and Python
														for key in tokenizer_pp.special_tokens_map:
																		self.assertTrue(hasattr(__lowerCamelCase	,__lowerCamelCase				)				)

														shutil.rmtree(__lowerCamelCase				)

														# Save tokenizer rust, legacy_format=False
														lowerCAmelCase__  :       str				=  tempfile.mkdtemp()

														lowerCAmelCase__  :       Dict				=  tokenizer_r.save_pretrained(__lowerCamelCase	,legacy_format=__lowerCamelCase				)
														lowerCAmelCase__  :       List[str]				=  tokenizer_p.save_pretrained(__lowerCamelCase				)

														# Checks it saved the tokenizer.json file
														self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files				)				)

														# Checks everything loads correctly in the same way
														lowerCAmelCase__  :       Tuple				=  tokenizer_r.from_pretrained(__lowerCamelCase				)
														lowerCAmelCase__  :       Tuple				=  tokenizer_p.from_pretrained(__lowerCamelCase				)

														# Check special tokens are set accordingly on Rust and Python
														for key in tokenizer_pp.special_tokens_map:
																		self.assertTrue(hasattr(__lowerCamelCase	,__lowerCamelCase				)				)

														shutil.rmtree(__lowerCamelCase				)



		@cached_property
		def 	lowerCAmelCase__   (self				)  ->    Dict:

						"""simple docstring"""






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



		def 	lowerCAmelCase__   (self				)  ->    Dict:

						"""simple docstring"""






						with tempfile.NamedTemporaryFile() as f:
										shutil.copyfile(__lowerCamelCase	,f.name				)
										lowerCAmelCase__  :       Optional[int]				=  XLMRobertaTokenizer(f.name	,keep_accents=__lowerCamelCase				)
										lowerCAmelCase__  :       Union[str, Any]				=  pickle.dumps(__lowerCamelCase				)
						pickle.loads(__lowerCamelCase				)



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

						"""simple docstring"""






						if not self.test_rust_tokenizer:
										return

						lowerCAmelCase__  :       Optional[Any]				=  self.get_tokenizer()
						lowerCAmelCase__  :       List[str]				=  self.get_rust_tokenizer()

						lowerCAmelCase__  :       Tuple				=  '''I was born in 92000, and this is falsé.'''

						lowerCAmelCase__  :       Tuple				=  tokenizer.tokenize(__lowerCamelCase				)
						lowerCAmelCase__  :       List[Any]				=  rust_tokenizer.tokenize(__lowerCamelCase				)
						self.assertListEqual(__lowerCamelCase	,__lowerCamelCase				)

						lowerCAmelCase__  :       str				=  tokenizer.encode(__lowerCamelCase	,add_special_tokens=__lowerCamelCase				)
						lowerCAmelCase__  :       Union[str, Any]				=  rust_tokenizer.encode(__lowerCamelCase	,add_special_tokens=__lowerCamelCase				)
						self.assertListEqual(__lowerCamelCase	,__lowerCamelCase				)

						lowerCAmelCase__  :       Tuple				=  self.get_rust_tokenizer()
						lowerCAmelCase__  :       Union[str, Any]				=  tokenizer.encode(__lowerCamelCase				)
						lowerCAmelCase__  :       Any				=  rust_tokenizer.encode(__lowerCamelCase				)
						self.assertListEqual(__lowerCamelCase	,__lowerCamelCase				)



		@slow
		def 	lowerCAmelCase__   (self				)  ->    str:

						"""simple docstring"""






						lowerCAmelCase__  :       List[Any]				=  '''Hello World!'''
						lowerCAmelCase__  :       Optional[int]				=  [0, 3_53_78, 66_61, 38, 2]
						# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
						# xlmr.eval()
						# xlmr.encode(symbols)

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



		@slow
		def 	lowerCAmelCase__   (self				)  ->    int:

						"""simple docstring"""






						lowerCAmelCase__  :       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'''
						)
						lowerCAmelCase__  :       Optional[Any]				=  [
						    0,
						    32_93,
						    83,
						    10,
						    45_52,
						    49_89,
						    79_86,
						    6_78,
						    10,
						    59_15,
						    1_11,
						    17_94_59,
						    12_48_50,
						    4,
						    60_44,
						    2_37,
						    12,
						    6,
						    5,
						    6,
						    4,
						    67_80,
						    7_05,
						    15,
						    13_88,
						    44,
						    3_78,
						    1_01_14,
						    7_11,
						    1_52,
						    20,
						    6,
						    5,
						    2_23_76,
						    6_42,
						    12_21,
						    1_51_90,
						    3_41_53,
						    4_50,
						    56_08,
						    9_59,
						    11_19,
						    5_77_02,
						    1_36,
						    1_86,
						    47,
						    10_98,
						    2_93_67,
						    47,
						    # 4426, # What fairseq tokenizes from "<unk>": "_<"
						    # 3678, # What fairseq tokenizes from "<unk>": "unk"
						    # 2740, # What fairseq tokenizes from "<unk>": ">"
						    3,  # What we tokenize from "<unk>": "<unk>"
						    6,  # Residue from the tokenization: an extra sentencepiece underline
						    4,
						    60_44,
						    2_37,
						    62_84,
						    5_09_01,
						    5_28,
						    31,
						    90,
						    34,
						    9_27,
						    2,
						]
						# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
						# xlmr.eval()
						# xlmr.encode(symbols)

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



		@slow
		def 	lowerCAmelCase__   (self				)  ->    List[Any]:

						"""simple docstring"""






						lowerCAmelCase__  :       Tuple				=  {'''input_ids''': [[0, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [0, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 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_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=__lowerCamelCase	,model_name='''xlm-roberta-base'''	,revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''	,)






import json
import os
from typing import Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__snake_case       :	int            =logging.get_logger(__name__)

__snake_case       :	List[Any]            ={
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
}

__snake_case       :	Any            ={
    'vocab_file': {'ctrl': 'https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-vocab.json'},
    'merges_file': {'ctrl': 'https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-merges.txt'},
}

__snake_case       :	Optional[int]            ={
    'ctrl': 2_5_6,
}

__snake_case       :	Optional[int]            ={
    'Pregnancy': 1_6_8_6_2_9,
    'Christianity': 7_6_7_5,
    'Explain': 1_0_6_4_2_3,
    'Fitness': 6_3_4_4_0,
    'Saving': 6_3_1_6_3,
    'Ask': 2_7_1_7_1,
    'Ass': 9_5_9_8_5,
    'Joke': 1_6_3_5_0_9,
    'Questions': 4_5_6_2_2,
    'Thoughts': 4_9_6_0_5,
    'Retail': 5_2_3_4_2,
    'Feminism': 1_6_4_3_3_8,
    'Writing': 1_1_9_9_2,
    'Atheism': 1_9_2_2_6_3,
    'Netflix': 4_8_6_1_6,
    'Computing': 3_9_6_3_9,
    'Opinion': 4_3_2_1_3,
    'Alone': 4_4_9_6_7,
    'Funny': 5_8_9_1_7,
    'Gaming': 4_0_3_5_8,
    'Human': 4_0_8_8,
    'India': 1_3_3_1,
    'Joker': 7_7_1_3_8,
    'Diet': 3_6_2_0_6,
    'Legal': 1_1_8_5_9,
    'Norman': 4_9_3_9,
    'Tip': 7_2_6_8_9,
    'Weight': 5_2_3_4_3,
    'Movies': 4_6_2_7_3,
    'Running': 2_3_4_2_5,
    'Science': 2_0_9_0,
    'Horror': 3_7_7_9_3,
    'Confession': 6_0_5_7_2,
    'Finance': 1_2_2_5_0,
    'Politics': 1_6_3_6_0,
    'Scary': 1_9_1_9_8_5,
    'Support': 1_2_6_5_4,
    'Technologies': 3_2_5_1_6,
    'Teenage': 6_6_1_6_0,
    'Event': 3_2_7_6_9,
    'Learned': 6_7_4_6_0,
    'Notion': 1_8_2_7_7_0,
    'Wikipedia': 3_7_5_8_3,
    'Books': 6_6_6_5,
    'Extract': 7_6_0_5_0,
    'Confessions': 1_0_2_7_0_1,
    'Conspiracy': 7_5_9_3_2,
    'Links': 6_3_6_7_4,
    'Narcissus': 1_5_0_4_2_5,
    'Relationship': 5_4_7_6_6,
    'Relationships': 1_3_4_7_9_6,
    'Reviews': 4_1_6_7_1,
    'News': 4_2_5_6,
    'Translation': 2_6_8_2_0,
    'multilingual': 1_2_8_4_0_6,
}






def 			lowerCAmelCase__	(					lowerCamelCase_	:	Optional[Any]):





				'''simple docstring'''

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

				lowerCAmelCase__  :       Dict				=  set(lowerCamelCase_)
				return pairs



class  lowerCamelCase__    (							lowerCamelCase__):




		'''simple docstring'''



		snake_case_			=VOCAB_FILES_NAMES
		snake_case_			=PRETRAINED_VOCAB_FILES_MAP
		snake_case_			=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		snake_case_			=CONTROL_CODES



		def __init__(self	,__lowerCamelCase	,__lowerCamelCase	,__lowerCamelCase="<unk>"	,**__lowerCamelCase				)  ->    Union[str, Any]:

						"""simple docstring"""






						super().__init__(unk_token=__lowerCamelCase	,**__lowerCamelCase				)

						with open(__lowerCamelCase	,encoding='''utf-8'''				) as vocab_handle:
										lowerCAmelCase__  :       List[str]				=  json.load(__lowerCamelCase				)
						lowerCAmelCase__  :       int				=  {v: k for k, v in self.encoder.items()}
						with open(__lowerCamelCase	,encoding='''utf-8'''				) as merges_handle:
										lowerCAmelCase__  :       str				=  merges_handle.read().split('''\n'''				)[1:-1]
						lowerCAmelCase__  :       Optional[Any]				=  [tuple(merge.split()				) for merge in merges]
						lowerCAmelCase__  :       int				=  dict(zip(__lowerCamelCase	,range(len(__lowerCamelCase				)				)				)				)
						lowerCAmelCase__  :       Union[str, Any]				=  {}



		@property
		def 	lowerCAmelCase__   (self				)  ->    Optional[Any]:

						"""simple docstring"""






						return len(self.encoder				)



		def 	lowerCAmelCase__   (self				)  ->    int:

						"""simple docstring"""






						return dict(self.encoder	,**self.added_tokens_encoder				)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    int:

						"""simple docstring"""






						if token in self.cache:
										return self.cache[token]
						lowerCAmelCase__  :       Union[str, Any]				=  tuple(__lowerCamelCase				)
						lowerCAmelCase__  :       Tuple				=  tuple(list(word[:-1]				) + [word[-1] + '''</w>''']				)
						lowerCAmelCase__  :       Union[str, Any]				=  get_pairs(__lowerCamelCase				)

						if not pairs:
										return token

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

														if word[i] == first and i < len(__lowerCamelCase				) - 1 and word[i + 1] == second:
																		new_word.append(first + second				)
																		i += 2
														else:
																		new_word.append(word[i]				)
																		i += 1
										lowerCAmelCase__  :       Optional[Any]				=  tuple(__lowerCamelCase				)
										lowerCAmelCase__  :       Any				=  new_word
										if len(__lowerCamelCase				) == 1:
														break
										else:
														lowerCAmelCase__  :       Optional[Any]				=  get_pairs(__lowerCamelCase				)
						lowerCAmelCase__  :       List[Any]				=  '''@@ '''.join(__lowerCamelCase				)
						lowerCAmelCase__  :       Optional[int]				=  word[:-4]
						lowerCAmelCase__  :       List[Any]				=  word
						return word



		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    List[Any]:

						"""simple docstring"""






						lowerCAmelCase__  :       List[Any]				=  []

						lowerCAmelCase__  :       int				=  re.findall(R'''\S+\n?'''	,__lowerCamelCase				)

						for token in words:
										split_tokens.extend(list(self.bpe(__lowerCamelCase				).split(''' '''				)				)				)
						return split_tokens



		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    List[str]:

						"""simple docstring"""






						return self.encoder.get(__lowerCamelCase	,self.encoder.get(self.unk_token				)				)



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

						"""simple docstring"""






						return self.decoder.get(__lowerCamelCase	,self.unk_token				)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    Optional[int]:

						"""simple docstring"""






						lowerCAmelCase__  :       Dict				=  ''' '''.join(__lowerCamelCase				).replace('''@@ '''	,''''''				).strip()
						return out_string



		def 	lowerCAmelCase__   (self	,__lowerCamelCase	,__lowerCamelCase = None				)  ->    Tuple[str]:

						"""simple docstring"""






						if not os.path.isdir(__lowerCamelCase				):
										logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
										return
						lowerCAmelCase__  :       Optional[int]				=  os.path.join(
						    __lowerCamelCase	,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)
						lowerCAmelCase__  :       List[Any]				=  os.path.join(
						    __lowerCamelCase	,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']				)

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

						lowerCAmelCase__  :       Optional[Any]				=  0
						with open(__lowerCamelCase	,'''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 __lowerCamelCase				: 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__  :       Optional[int]				=  token_index
														writer.write(''' '''.join(__lowerCamelCase				) + '''\n'''				)
														index += 1

						return vocab_file, merge_file

		# def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
		#     filtered_tokens = ' '.join(self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens))
		#     tokens_generated_so_far = re.sub('(@@ )', '', string=filtered_tokens)
		#     tokens_generated_so_far = re.sub('(@@ ?$)', '', string=tokens_generated_so_far)
		#     return ''.join(tokens_generated_so_far)

