

'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin
class 					_snake_case		(__SCREAMING_SNAKE_CASE			,			unittest.TestCase):
			__A  :	List[Any]        =CanineTokenizer
			__A  :	Any        =False






			def 		UpperCamelCase__							(  self     ):
				super().setUp()
				UpperCAmelCase_     :      Dict						=  CanineTokenizer()
				tokenizer.save_pretrained(self.tmpdirname     )






			@cached_property
			def 		UpperCamelCase__							(  self     ):
				return CanineTokenizer.from_pretrained("google/canine-s"     )






			def 		UpperCamelCase__							(  self			,**_snake_case     ):
				UpperCAmelCase_     :      Optional[int]						=  self.tokenizer_class.from_pretrained(self.tmpdirname			,**_snake_case     )
				UpperCAmelCase_     :      int						=  10_24
				return tokenizer






			@require_torch
			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Dict						=  self.canine_tokenizer
				UpperCAmelCase_     :      str						=  ["Life is like a box of chocolates.", "You never know what you're gonna get."]
				# fmt: off
				UpperCAmelCase_     :      Any						=  [5_73_44, 76, 1_05, 1_02, 1_01, 32, 1_05, 1_15, 32, 1_08, 1_05, 1_07, 1_01, 32, 97, 32, 98, 1_11, 1_20, 32, 1_11, 1_02, 32, 99, 1_04, 1_11, 99, 1_11, 1_08, 97, 1_16, 1_01, 1_15, 46, 5_73_45, 0, 0, 0, 0]
				# fmt: on
				UpperCAmelCase_     :      List[Any]						=  tokenizer(_snake_case			,padding=_snake_case			,return_tensors="pt"     )
				self.assertIsInstance(_snake_case			,_snake_case     )

				UpperCAmelCase_     :      str						=  list(batch.input_ids.numpy()[0]     )

				self.assertListEqual(_snake_case			,_snake_case     )

				self.assertEqual((2, 39)			,batch.input_ids.shape     )
				self.assertEqual((2, 39)			,batch.attention_mask.shape     )






			@require_torch
			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Tuple						=  self.canine_tokenizer
				UpperCAmelCase_     :      List[Any]						=  ["Once there was a man.", "He wrote a test in HuggingFace Tranformers."]
				UpperCAmelCase_     :      Tuple						=  tokenizer(_snake_case			,padding=_snake_case			,return_tensors="pt"     )
				# check if input_ids, attention_mask and token_type_ids are returned
				self.assertIn("input_ids"			,_snake_case     )
				self.assertIn("attention_mask"			,_snake_case     )
				self.assertIn("token_type_ids"			,_snake_case     )






			@require_torch
			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Optional[int]						=  self.canine_tokenizer
				UpperCAmelCase_     :      Tuple						=  [
				    "What's the weater?",
				    "It's about 25 degrees.",
				]
				UpperCAmelCase_     :      Union[str, Any]						=  tokenizer(
				    text_target=_snake_case			,max_length=32			,padding="max_length"			,truncation=_snake_case			,return_tensors="pt"     )
				self.assertEqual(32			,targets["input_ids"].shape[1]     )






			def 		UpperCamelCase__							(  self     ):
				# safety check on max_len default value so we are sure the test works
				UpperCAmelCase_     :      List[Any]						=  self.get_tokenizers()
				for tokenizer in tokenizers:
					with self.subTest(f'''{tokenizer.__class__.__name__}'''     ):
						self.assertNotEqual(tokenizer.model_max_length			,42     )

        # Now let's start the test
				UpperCAmelCase_     :      Optional[int]						=  self.get_tokenizers()
				for tokenizer in tokenizers:
					with self.subTest(f'''{tokenizer.__class__.__name__}'''     ):
						# Isolate this from the other tests because we save additional tokens/etc
						UpperCAmelCase_     :      List[str]						=  tempfile.mkdtemp()

						UpperCAmelCase_     :      Dict						=  " He is very happy, UNwant\u00E9d,running"
						UpperCAmelCase_     :      int						=  tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )
						tokenizer.save_pretrained(_snake_case     )

						UpperCAmelCase_     :      Optional[int]						=  tokenizer.__class__.from_pretrained(_snake_case     )
						UpperCAmelCase_     :      Optional[Any]						=  after_tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )
						self.assertListEqual(_snake_case			,_snake_case     )

						shutil.rmtree(_snake_case     )

				UpperCAmelCase_     :      Optional[Any]						=  self.get_tokenizers(model_max_length=42     )
				for tokenizer in tokenizers:
					with self.subTest(f'''{tokenizer.__class__.__name__}'''     ):
						# Isolate this from the other tests because we save additional tokens/etc
						UpperCAmelCase_     :      Any						=  tempfile.mkdtemp()

						UpperCAmelCase_     :      List[str]						=  " He is very happy, UNwant\u00E9d,running"

						UpperCAmelCase_     :      Union[str, Any]						=  tokenizer.additional_special_tokens

						# We can add a new special token for Canine as follows:
						UpperCAmelCase_     :      Any						=  chr(0xE_007     )
						additional_special_tokens.append(_snake_case     )
						tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}     )
						UpperCAmelCase_     :      int						=  tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )
						tokenizer.save_pretrained(_snake_case     )

						UpperCAmelCase_     :      Optional[Any]						=  tokenizer.__class__.from_pretrained(_snake_case     )
						UpperCAmelCase_     :      List[Any]						=  after_tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )
						self.assertListEqual(_snake_case			,_snake_case     )
						self.assertIn(_snake_case			,after_tokenizer.additional_special_tokens     )
						self.assertEqual(after_tokenizer.model_max_length			,42     )

						UpperCAmelCase_     :      List[str]						=  tokenizer.__class__.from_pretrained(_snake_case			,model_max_length=43     )
						self.assertEqual(tokenizer.model_max_length			,43     )

						shutil.rmtree(_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Dict						=  self.get_tokenizers(do_lower_case=_snake_case     )
				for tokenizer in tokenizers:
					with self.subTest(f'''{tokenizer.__class__.__name__}'''     ):
						UpperCAmelCase_					,					UpperCAmelCase_     :      Any						=  self.get_clean_sequence(_snake_case     )

						# a special token for Canine can be defined as follows:
						UpperCAmelCase_     :      int						=  0xE_005
						UpperCAmelCase_     :      int						=  chr(_snake_case     )

						tokenizer.add_special_tokens({"cls_token": special_token}     )
						UpperCAmelCase_     :      int						=  tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )
						self.assertEqual(len(_snake_case     )			,1     )

						UpperCAmelCase_     :      Optional[Any]						=  tokenizer.decode(ids + encoded_special_token			,clean_up_tokenization_spaces=_snake_case     )
						UpperCAmelCase_     :      List[Any]						=  tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )

						UpperCAmelCase_     :      str						=  tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )
						UpperCAmelCase_     :      Optional[int]						=  tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )
						self.assertEqual(_snake_case			,input_encoded + special_token_id     )

						UpperCAmelCase_     :      Optional[Any]						=  tokenizer.decode(_snake_case			,skip_special_tokens=_snake_case     )
						self.assertTrue(special_token not in decoded     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      int						=  self.get_tokenizers(do_lower_case=_snake_case     )
				for tokenizer in tokenizers:
					with self.subTest(f'''{tokenizer.__class__.__name__}'''     ):
						UpperCAmelCase_     :      str						=  chr(0xE_005     )
						UpperCAmelCase_     :      List[str]						=  chr(0xE_006     )

						# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
						tokenizer.add_tokens([SPECIAL_TOKEN_1]			,special_tokens=_snake_case     )
						# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
						# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
						tokenizer.add_special_tokens({"additional_special_tokens": [SPECIAL_TOKEN_2]}     )

						UpperCAmelCase_     :      Optional[int]						=  tokenizer.tokenize(_snake_case     )
						UpperCAmelCase_     :      Any						=  tokenizer.tokenize(_snake_case     )

						self.assertEqual(len(_snake_case     )			,1     )
						self.assertEqual(len(_snake_case     )			,1     )
						self.assertEqual(token_a[0]			,_snake_case     )
						self.assertEqual(token_a[0]			,_snake_case     )






			@require_tokenizers
			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Optional[int]						=  self.get_tokenizers(do_lower_case=_snake_case     )
				for tokenizer in tokenizers:
					with self.subTest(f'''{tokenizer.__class__.__name__}'''     ):
						# a special token for Canine can be defined as follows:
						UpperCAmelCase_     :      Union[str, Any]						=  0xE_006
						UpperCAmelCase_     :      Any						=  chr(_snake_case     )

						UpperCAmelCase_     :      Tuple						=  AddedToken(_snake_case			,lstrip=_snake_case     )
						tokenizer.add_special_tokens({"additional_special_tokens": [new_token]}     )

						with tempfile.TemporaryDirectory() as tmp_dir_name:
							tokenizer.save_pretrained(_snake_case     )
							tokenizer.from_pretrained(_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      List[str]						=  []
				if self.test_slow_tokenizer:
					tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())     )

				if self.test_rust_tokenizer:
					tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())     )

				for tokenizer_class, tokenizer_utils in tokenizer_list:
					with tempfile.TemporaryDirectory() as tmp_dir:
						tokenizer_utils.save_pretrained(_snake_case     )

						with open(os.path.join(_snake_case			,"special_tokens_map.json"     )			,encoding="utf-8"     ) as json_file:
							UpperCAmelCase_     :      Any						=  json.load(_snake_case     )

						with open(os.path.join(_snake_case			,"tokenizer_config.json"     )			,encoding="utf-8"     ) as json_file:
							UpperCAmelCase_     :      Dict						=  json.load(_snake_case     )

						# a special token for Canine can be defined as follows:
						UpperCAmelCase_     :      Tuple						=  0xE_006
						UpperCAmelCase_     :      str						=  chr(_snake_case     )

						UpperCAmelCase_     :      Any						=  [new_token_a]
						UpperCAmelCase_     :      Any						=  [new_token_a]

						with open(os.path.join(_snake_case			,"special_tokens_map.json"     )			,"w"			,encoding="utf-8"     ) as outfile:
							json.dump(_snake_case			,_snake_case     )
						with open(os.path.join(_snake_case			,"tokenizer_config.json"     )			,"w"			,encoding="utf-8"     ) as outfile:
							json.dump(_snake_case			,_snake_case     )

						# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
						# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
						# "special_tokens_map.json" files
						UpperCAmelCase_     :      List[Any]						=  tokenizer_class.from_pretrained(_snake_case			,extra_ids=0     )
						self.assertIn(_snake_case			,tokenizer_without_change_in_init.additional_special_tokens     )
						# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
						self.assertEqual(
						    [new_token_a]			,tokenizer_without_change_in_init.convert_ids_to_tokens(
						        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]     )     )			,)

						UpperCAmelCase_     :      List[str]						=  0xE_007
						UpperCAmelCase_     :      Any						=  chr(_snake_case     )
						# Now we test that we can change the value of additional_special_tokens in the from_pretrained
						UpperCAmelCase_     :      List[Any]						=  [AddedToken(_snake_case			,lstrip=_snake_case     )]
						UpperCAmelCase_     :      List[Any]						=  tokenizer_class.from_pretrained(
						    _snake_case			,additional_special_tokens=_snake_case			,extra_ids=0     )

						self.assertIn(_snake_case			,tokenizer.additional_special_tokens     )
						# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
						self.assertEqual(
						    [new_token_a]			,tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]     )     )     )






			@require_tokenizers
			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      int						=  self.get_tokenizers(do_lower_case=_snake_case     )
				for tokenizer in tokenizers:
					with self.subTest(f'''{tokenizer.__class__.__name__}'''     ):
						UpperCAmelCase_     :      Tuple						=  "hello world"
						if self.space_between_special_tokens:
							UpperCAmelCase_     :      str						=  "[CLS] hello world [SEP]"
						else:
							UpperCAmelCase_     :      List[str]						=  input
						UpperCAmelCase_     :      str						=  tokenizer.encode(_snake_case			,add_special_tokens=_snake_case     )
						UpperCAmelCase_     :      List[Any]						=  tokenizer.decode(_snake_case			,spaces_between_special_tokens=self.space_between_special_tokens     )
						self.assertIn(_snake_case			,[output, output.lower()]     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Dict						=  self.get_tokenizers()
				for tokenizer in tokenizers:
					with self.subTest(f'''{tokenizer.__class__.__name__}'''     ):
						UpperCAmelCase_     :      Optional[int]						=  [
						    "bos_token",
						    "eos_token",
						    "unk_token",
						    "sep_token",
						    "pad_token",
						    "cls_token",
						    "mask_token",
						]

				UpperCAmelCase_     :      Tuple						=  "a"
				UpperCAmelCase_     :      int						=  ord(_snake_case     )

				for attr in attributes_list:
					setattr(_snake_case			,attr + "_id"			,_snake_case     )
					self.assertEqual(getattr(_snake_case			,_snake_case     )			,_snake_case     )
					self.assertEqual(getattr(_snake_case			,attr + "_id"     )			,_snake_case     )

					setattr(_snake_case			,attr + "_id"			,_snake_case     )
					self.assertEqual(getattr(_snake_case			,_snake_case     )			,_snake_case     )
					self.assertEqual(getattr(_snake_case			,attr + "_id"     )			,_snake_case     )

				setattr(_snake_case			,"additional_special_tokens_ids"			,[]     )
				self.assertListEqual(getattr(_snake_case			,"additional_special_tokens"     )			,[]     )
				self.assertListEqual(getattr(_snake_case			,"additional_special_tokens_ids"     )			,[]     )

				UpperCAmelCase_     :      Optional[int]						=  0xE_006
				UpperCAmelCase_     :      List[Any]						=  chr(_snake_case     )
				setattr(_snake_case			,"additional_special_tokens_ids"			,[additional_special_token_id]     )
				self.assertListEqual(getattr(_snake_case			,"additional_special_tokens"     )			,[additional_special_token]     )
				self.assertListEqual(getattr(_snake_case			,"additional_special_tokens_ids"     )			,[additional_special_token_id]     )






			def 		UpperCamelCase__							(  self     ):
				pass






			def 		UpperCamelCase__							(  self     ):
				pass






			def 		UpperCamelCase__							(  self     ):
				pass






			def 		UpperCamelCase__							(  self     ):
				pass






			def 		UpperCamelCase__							(  self     ):
				pass






			def 		UpperCamelCase__							(  self     ):
				pass






			def 		UpperCamelCase__							(  self     ):
				pass






			def 		UpperCamelCase__							(  self     ):
				pass









"""simple docstring"""







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  ( SCREAMING_SNAKE_CASE__     ,	unittest.TestCase):
			__magic_name__     					=     RobertaTokenizer
			__magic_name__     					=     RobertaTokenizerFast
			__magic_name__     					=     True
			__magic_name__     					=     {"""cls_token""": """<s>"""}



			def 				__lowercase					(			self							:				Any		)							->					int:
									super().setUp()

									# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
									snake_case   :			int						    = [
									    "l",
									    "o",
									    "w",
									    "e",
									    "r",
									    "s",
									    "t",
									    "i",
									    "d",
									    "n",
									    "\u0120",
									    "\u0120l",
									    "\u0120n",
									    "\u0120lo",
									    "\u0120low",
									    "er",
									    "\u0120lowest",
									    "\u0120newer",
									    "\u0120wider",
									    "<unk>",
									]
									snake_case   :			Optional[int]						    = dict(zip(_lowercase   ,	range(len(_lowercase		)		)		)		)
									snake_case   :			int						    = ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
									snake_case   :			Union[str, Any]						    = {"unk_token": "<unk>"}

									snake_case   :			Optional[Any]						    = os.path.join(self.tmpdirname   ,	VOCAB_FILES_NAMES["vocab_file"]		)
									snake_case   :			str						    = 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 				__lowercase					(			self							:				Optional[Any]   ,	**_lowercase							:				Union[str, Any]		)							->					Dict:
									kwargs.update(self.special_tokens_map		)
									return self.tokenizer_class.from_pretrained(self.tmpdirname   ,	**_lowercase		)



			def 				__lowercase					(			self							:				List[str]   ,	**_lowercase							:				Union[str, Any]		)							->					str:
									kwargs.update(self.special_tokens_map		)
									return RobertaTokenizerFast.from_pretrained(self.tmpdirname   ,	**_lowercase		)



			def 				__lowercase					(			self							:				Union[str, Any]   ,	_lowercase							:				str		)							->					Optional[Any]:
									snake_case   :			Any						    = "lower newer"
									snake_case   :			Union[str, Any]						    = "lower newer"
									return input_text, output_text



			def 				__lowercase					(			self							:				Optional[int]		)							->					Any:
									snake_case   :			Any						    = self.tokenizer_class(self.vocab_file   ,	self.merges_file   ,	**self.special_tokens_map		)
									snake_case   :			Dict						    = "lower newer"
									snake_case   :			Dict						    = ["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
									snake_case   :			Any						    = tokenizer.tokenize(_lowercase		)  # , add_prefix_space=True)
									self.assertListEqual(_lowercase   ,	_lowercase		)

									snake_case   :			List[str]						    = tokens + [tokenizer.unk_token]
									snake_case   :			List[Any]						    = [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase		)   ,	_lowercase		)



			def 				__lowercase					(			self							:				int		)							->					str:
									snake_case   :			List[str]						    = self.get_tokenizer()

									self.assertListEqual(tokenizer.encode("Hello world!"   ,	add_special_tokens=_lowercase		)   ,	[0, 31414, 232, 328, 2]		)
									self.assertListEqual(
									    tokenizer.encode("Hello world! cécé herlolip 418"   ,	add_special_tokens=_lowercase		)   ,	[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]   ,	)



			@slow
			def 				__lowercase					(			self							:				Dict		)							->					Optional[int]:
									snake_case   :			Tuple						    = self.tokenizer_class.from_pretrained("roberta-base"		)

									snake_case   :			Tuple						    = tokenizer.encode("sequence builders"   ,	add_special_tokens=_lowercase		)
									snake_case   :			Optional[int]						    = tokenizer.encode("multi-sequence build"   ,	add_special_tokens=_lowercase		)

									snake_case   :			Optional[Any]						    = tokenizer.encode(
									    "sequence builders"   ,	add_special_tokens=_lowercase   ,	add_prefix_space=_lowercase		)
									snake_case   :			Optional[int]						    = tokenizer.encode(
									    "sequence builders"   ,	"multi-sequence build"   ,	add_special_tokens=_lowercase   ,	add_prefix_space=_lowercase		)

									snake_case   :			Optional[Any]						    = tokenizer.build_inputs_with_special_tokens(_lowercase		)
									snake_case   :			Any						    = tokenizer.build_inputs_with_special_tokens(_lowercase   ,	_lowercase		)

									assert encoded_sentence == encoded_text_from_decode
									assert encoded_pair == encoded_pair_from_decode



			def 				__lowercase					(			self							:				int		)							->					Any:
									snake_case   :			Any						    = self.get_tokenizer()

									snake_case   :			Optional[Any]						    = "Encode this sequence."
									snake_case   :			List[Any]						    = tokenizer.byte_encoder[" ".encode("utf-8"		)[0]]

									# Testing encoder arguments
									snake_case   :			Any						    = tokenizer.encode(_lowercase   ,	add_special_tokens=_lowercase   ,	add_prefix_space=_lowercase		)
									snake_case   :			Any						    = tokenizer.convert_ids_to_tokens(encoded[0]		)[0]
									self.assertNotEqual(_lowercase   ,	_lowercase		)

									snake_case   :			Dict						    = tokenizer.encode(_lowercase   ,	add_special_tokens=_lowercase   ,	add_prefix_space=_lowercase		)
									snake_case   :			Any						    = tokenizer.convert_ids_to_tokens(encoded[0]		)[0]
									self.assertEqual(_lowercase   ,	_lowercase		)

									tokenizer.add_special_tokens({"bos_token": "<s>"}		)
									snake_case   :			Union[str, Any]						    = tokenizer.encode(_lowercase   ,	add_special_tokens=_lowercase		)
									snake_case   :			List[str]						    = tokenizer.convert_ids_to_tokens(encoded[1]		)[0]
									self.assertNotEqual(_lowercase   ,	_lowercase		)

									# Testing spaces after special tokens
									snake_case   :			Optional[int]						    = "<mask>"
									tokenizer.add_special_tokens(
									    {"mask_token": AddedToken(_lowercase   ,	lstrip=_lowercase   ,	rstrip=_lowercase		)}		)  # mask token has a left space
									snake_case   :			Optional[int]						    = tokenizer.convert_tokens_to_ids(_lowercase		)

									snake_case   :			Tuple						    = "Encode <mask> sequence"
									snake_case   :			Union[str, Any]						    = "Encode <mask>sequence"

									snake_case   :			Union[str, Any]						    = tokenizer.encode(_lowercase		)
									snake_case   :			Optional[int]						    = encoded.index(_lowercase		)
									snake_case   :			int						    = tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]		)[0]
									self.assertEqual(_lowercase   ,	_lowercase		)

									snake_case   :			int						    = tokenizer.encode(_lowercase		)
									snake_case   :			Optional[int]						    = encoded.index(_lowercase		)
									snake_case   :			List[Any]						    = tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]		)[0]
									self.assertNotEqual(_lowercase   ,	_lowercase		)



			def 				__lowercase					(			self							:				Dict		)							->					Union[str, Any]:
									pass



			def 				__lowercase					(			self							:				List[str]		)							->					str:
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
																					snake_case   :			List[Any]						    = self.rust_tokenizer_class.from_pretrained(_lowercase   ,	**_lowercase		)
																					snake_case   :			Optional[int]						    = self.tokenizer_class.from_pretrained(_lowercase   ,	**_lowercase		)
																					snake_case   :			Optional[int]						    = "A, <mask> AllenNLP sentence."
																					snake_case   :			Tuple						    = tokenizer_r.encode_plus(_lowercase   ,	add_special_tokens=_lowercase   ,	return_token_type_ids=_lowercase		)
																					snake_case   :			Optional[Any]						    = 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"]		)   ,	)

																					snake_case   :			List[str]						    = tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]		)
																					snake_case   :			List[Any]						    = 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, 50264, 3823, 487, 21992, 3645, 4, 2]		)
																					self.assertSequenceEqual(tokens_r["input_ids"]   ,	[0, 250, 6, 50264, 3823, 487, 21992, 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 				__lowercase					(			self							:				Tuple		)							->					List[Any]:
									for trim_offsets, add_prefix_space in itertools.product([True, False]   ,	repeat=2		):
															snake_case   :			List[Any]						    = self.rust_tokenizer_class.from_pretrained(
															    self.tmpdirname   ,	use_fast=_lowercase   ,	add_prefix_space=_lowercase   ,	trim_offsets=_lowercase		)

															snake_case   :			Optional[int]						    = json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()		)
															snake_case   :			Union[str, Any]						    = 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 				__lowercase					(			self							:				int		)							->					List[str]:
									# 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})'''		):
																					snake_case   :			List[Any]						    = "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
																					snake_case   :			List[str]						    = F'''{text_of_1_token} {text_of_1_token}'''

																					snake_case   :			Optional[Any]						    = self.rust_tokenizer_class.from_pretrained(
																					    _lowercase   ,	use_fast=_lowercase   ,	add_prefix_space=_lowercase   ,	trim_offsets=_lowercase		)
																					snake_case   :			Union[str, Any]						    = 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		))   ,	)

																					snake_case   :			List[Any]						    = self.rust_tokenizer_class.from_pretrained(
																					    _lowercase   ,	use_fast=_lowercase   ,	add_prefix_space=_lowercase   ,	trim_offsets=_lowercase		)
																					snake_case   :			Tuple						    = 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		))   ,	)

																					snake_case   :			Dict						    = self.rust_tokenizer_class.from_pretrained(
																					    _lowercase   ,	use_fast=_lowercase   ,	add_prefix_space=_lowercase   ,	trim_offsets=_lowercase		)
																					snake_case   :			int						    = 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		))   ,	)

																					snake_case   :			Optional[int]						    = self.rust_tokenizer_class.from_pretrained(
																					    _lowercase   ,	use_fast=_lowercase   ,	add_prefix_space=_lowercase   ,	trim_offsets=_lowercase		)
																					snake_case   :			Optional[int]						    = 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		))   ,	)

																					snake_case   :			Dict						    = 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)),
																					# )

																					snake_case   :			List[str]						    = self.rust_tokenizer_class.from_pretrained(
																					    _lowercase   ,	use_fast=_lowercase   ,	add_prefix_space=_lowercase   ,	trim_offsets=_lowercase		)
																					snake_case   :			List[str]						    = 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		))   ,	)

																					snake_case   :			Union[str, Any]						    = self.rust_tokenizer_class.from_pretrained(
																					    _lowercase   ,	use_fast=_lowercase   ,	add_prefix_space=_lowercase   ,	trim_offsets=_lowercase		)
																					snake_case   :			Optional[int]						    = 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		))   ,	)

																					snake_case   :			Optional[Any]						    = self.rust_tokenizer_class.from_pretrained(
																					    _lowercase   ,	use_fast=_lowercase   ,	add_prefix_space=_lowercase   ,	trim_offsets=_lowercase		)
																					snake_case   :			Union[str, Any]						    = 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		))   ,	)



