"""simple docstring"""


from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


a							=logging.get_logger(__name__)






class        __UpperCAmelCase						(     __lowerCAmelCase     ):
				A__				:       Dict  							=	['''input_ids''', '''attention_mask''']

				def __init__(				self     ,			_lowerCamelCase="[PAD]"     ,			_lowerCamelCase="[BOS]"     ,			_lowerCamelCase="[EOS]"     ,			_lowerCamelCase="[MASK]"     ,			_lowerCamelCase="[CLS]"     ,			_lowerCamelCase="[SEP]"     ,			_lowerCamelCase=2048     ,			**_lowerCamelCase     ,			):
										lowerCamelCase__ =AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase				) if isinstance(_lowerCamelCase     ,			_lowerCamelCase				) else pad_token
										lowerCamelCase__ =AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase				) if isinstance(_lowerCamelCase     ,			_lowerCamelCase				) else bos_token
										lowerCamelCase__ =AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase				) if isinstance(_lowerCamelCase     ,			_lowerCamelCase				) else eos_token
										lowerCamelCase__ =AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase				) if isinstance(_lowerCamelCase     ,			_lowerCamelCase				) else mask_token
										lowerCamelCase__ =AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase				) if isinstance(_lowerCamelCase     ,			_lowerCamelCase				) else cls_token
										lowerCamelCase__ =AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase				) if isinstance(_lowerCamelCase     ,			_lowerCamelCase				) else sep_token

										super().__init__(
										    pad_token=_lowerCamelCase     ,			bos_token=_lowerCamelCase     ,			eos_token=_lowerCamelCase     ,			mask_token=_lowerCamelCase     ,			cls_token=_lowerCamelCase     ,			sep_token=_lowerCamelCase     ,			model_max_length=_lowerCamelCase     ,			**_lowerCamelCase     ,			)

										lowerCamelCase__ =2**8  # utf is 8 bits

										# define special tokens dict
										lowerCamelCase__ ={
										    self.pad_token: 0,
										    self.bos_token: 1,
										    self.eos_token: 2,
										    self.mask_token: 3,
										    self.cls_token: 4,
										    self.sep_token: 5,
										}
										lowerCamelCase__ =len(self.special_tokens_encoder				)
										lowerCamelCase__ ={v: k for k, v in self.special_tokens_encoder.items()}

				def 		_a     (				self				):
										lowerCamelCase__ =self.special_tokens_encoder.copy()
										vocab.update(self.added_tokens_encoder				)
										for i in range(self._utf_vocab_size				):
																lowerCamelCase__ =chr(_lowerCamelCase				)
																lowerCamelCase__ =i + len(self.special_tokens_encoder				)
										return vocab

				@property
				def 		_a     (				self				):
										return self._utf_vocab_size + self._num_special_tokens

				def 		_a     (				self     ,			_lowerCamelCase     ,			_lowerCamelCase = None     ,			_lowerCamelCase = False				):
										if already_has_special_tokens:
																return super().get_special_tokens_mask(
																    token_ids_a=_lowerCamelCase     ,			token_ids_a=_lowerCamelCase     ,			already_has_special_tokens=_lowerCamelCase				)

										# normal case: some special tokens
										if token_ids_a is None:
																return [1] + [0] * len(_lowerCamelCase				) + [1]
										return [1] + ([0] * len(_lowerCamelCase				)) + [1] + ([0] * len(_lowerCamelCase				)) + [1]

				def 		_a     (				self     ,			_lowerCamelCase     ,			_lowerCamelCase = None				):
										if token_ids_a is None:
																return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										else:
																return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]

				def 		_a     (				self     ,			_lowerCamelCase				):
										lowerCamelCase__ =[chr(_lowerCamelCase				) for i in text.encode("utf-8"				)]
										return tokens

				def 		_a     (				self     ,			_lowerCamelCase				):
										if token in self.special_tokens_encoder:
																lowerCamelCase__ =self.special_tokens_encoder[token]
										elif token in self.added_tokens_encoder:
																lowerCamelCase__ =self.added_tokens_encoder[token]
										elif len(_lowerCamelCase				) != 1:
																lowerCamelCase__ =self.unk_token_id
										else:
																lowerCamelCase__ =ord(_lowerCamelCase				) + self._num_special_tokens
										return token_id

				def 		_a     (				self     ,			_lowerCamelCase				):
										if index in self.special_tokens_decoder:
																lowerCamelCase__ =self.special_tokens_decoder[index]
										elif index in self.added_tokens_decoder:
																lowerCamelCase__ =self.added_tokens_decoder[index]
										else:
																lowerCamelCase__ =chr(index - self._num_special_tokens				)
										return token

				def 		_a     (				self     ,			_lowerCamelCase				):
										lowerCamelCase__ =b""
										for token in tokens:
																if token in self.special_tokens_decoder:
																						lowerCamelCase__ =self.special_tokens_decoder[token].encode("utf-8"				)
																elif token in self.added_tokens_decoder:
																						lowerCamelCase__ =self.special_tokens_decoder[token].encode("utf-8"				)
																elif token in self.special_tokens_encoder:
																						lowerCamelCase__ =token.encode("utf-8"				)
																elif token in self.added_tokens_encoder:
																						lowerCamelCase__ =token.encode("utf-8"				)
																else:
																						lowerCamelCase__ =bytes([ord(_lowerCamelCase				)]				)
																bstring += tok_string
										lowerCamelCase__ =bstring.decode("utf-8"     ,			errors="replace"				)
										return string






				def 		_a     (				self     ,			_lowerCamelCase     ,			_lowerCamelCase = None				):
										return ()



"""simple docstring"""


from collections import Counter
import datasets
import transformers
from transformers.convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS

from transformers.utils import logging

logging.set_verbosity_info()

a							={
    name: (getattr(transformers, name), getattr(transformers, name + 'Fast')) for name in SLOW_TO_FAST_CONVERTERS
}

a							=datasets.load_dataset('xnli', split='test+validation')

a							=0
a							=0
a							=0
a							=0





def       lowerCamelCase_			( __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    )							-> Optional[int]:




						'''simple docstring'''



						if spm_diff == list(reversed(__lowerCAmelCase    )    ):
												# AAA -> AA+A vs A+AA case.
												return True
						elif len(__lowerCAmelCase    ) == len(__lowerCAmelCase    ) and fast.decode(__lowerCAmelCase    ) == fast.decode(__lowerCAmelCase    ):
												# Second order OK
												# Barrich -> Barr + ich vs Bar + rich
												return True
						lowerCamelCase__ =slow.encode(slow.decode(__lowerCAmelCase    )    )
						lowerCamelCase__ =fast.encode(fast.decode(__lowerCAmelCase    )    )
						if spm_reencoded != spm_diff and spm_reencoded == tok_reencoded:
												# Type 3 error.
												# Snehagatha ->
												#       Sne, h, aga, th, a
												#       Sne, ha, gat, ha
												# Encoding the wrong with sp does not even recover what spm gave us
												# It fits tokenizer however...
												return True
						return False





def       lowerCamelCase_			( __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    )							-> List[str]:




						'''simple docstring'''



						lowerCamelCase__ =fast.encode_plus(__lowerCAmelCase    )[0]
						lowerCamelCase__ =enc.offsets
						lowerCamelCase__ ,				lowerCamelCase__ =offsets[idx], offsets[idx - 1]
						if curr is not None and line[curr[0] : curr[1]] == "\u200f":
												return True
						if prev is not None and line[prev[0] : prev[1]] == "\u200f":
												return True





def       lowerCamelCase_			( __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    )							-> Tuple:




						'''simple docstring'''



						for i, (spm_id, tok_id) in enumerate(zip(__lowerCAmelCase       ,   __lowerCAmelCase    )    ):
												if spm_id != tok_id:
																		break
						lowerCamelCase__ =i
						for i, (spm_id, tok_id) in enumerate(zip(reversed(__lowerCAmelCase    )       ,   reversed(__lowerCAmelCase    )    )    ):
												if spm_id != tok_id:
																		break
						lowerCamelCase__ =len(__lowerCAmelCase    ) - i

						lowerCamelCase__ =spm_ids[first:last]
						lowerCamelCase__ =tok_ids[first:last]

						if check_diff(__lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    ):
												return True

						if check_LTR_mark(__lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    ):
												return True

						if last - first > 5:
												# We might have twice a single problem, attempt to subdivide the disjointed tokens into smaller problems
												lowerCamelCase__ =Counter(spm_ids[first:last]    )
												lowerCamelCase__ =Counter(tok_ids[first:last]    )

												lowerCamelCase__ ={spm_ for (spm_, si) in spms.items() if toks.get(spm_       ,   0    ) == si}
												lowerCamelCase__ =3
												for i in range(last - first - min_width    ):
																		if all(spm_ids[first + i + j] in removable_tokens for j in range(__lowerCAmelCase    )    ):
																								lowerCamelCase__ =[
																								    k
																								    for k in range(last - first - min_width    )
																								    if tok_ids[first + k : first + k + min_width] == spm_ids[first + i : first + i + min_width]
																								]
																								for j in possible_matches:
																														if check_diff(spm_ids[first : first + i]       ,   tok_ids[first : first + j]       ,   __lowerCAmelCase       ,   __lowerCAmelCase    ) and check_details(
																														    __lowerCAmelCase       ,   spm_ids[first + i : last]       ,   tok_ids[first + j : last]       ,   __lowerCAmelCase       ,   __lowerCAmelCase       ,   ):
																																				return True

						print(F'''Spm: {[fast.decode([spm_ids[i]]    ) for i in range(__lowerCAmelCase       ,   __lowerCAmelCase    )]}'''    )
						try:
												print(F'''Tok: {[fast.decode([tok_ids[i]]    ) for i in range(__lowerCAmelCase       ,   __lowerCAmelCase    )]}'''    )
						except Exception:
												pass

						lowerCamelCase__ =fast.decode(spm_ids[:first]    )
						lowerCamelCase__ =fast.decode(spm_ids[last:]    )
						lowerCamelCase__ =fast.decode(spm_ids[first:last]    )
						print()
						print(__lowerCAmelCase    )
						return False





def       lowerCamelCase_			( __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    )							-> Optional[int]:




						'''simple docstring'''



						global perfect
						global imperfect
						global wrong
						global total

						lowerCamelCase__ =slow.encode(__lowerCAmelCase    )
						lowerCamelCase__ =fast.encode(__lowerCAmelCase    )

						lowerCamelCase__ =False
						total += 1

						if slow_ids != fast_ids:
												if check_details(__lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    ):
																		lowerCamelCase__ =True
																		imperfect += 1
												else:
																		wrong += 1
						else:
												perfect += 1

						if total % 1_0000 == 0:
												print(F'''({perfect} / {imperfect} / {wrong} ----- {perfect + imperfect + wrong})'''    )

						if skip_assert:
												return

						assert (
						    slow_ids == fast_ids
						), F'''line {text} : \n\n{slow_ids}\n{fast_ids}\n\n{slow.tokenize(__lowerCAmelCase    )}\n{fast.tokenize(__lowerCAmelCase    )}'''





def       lowerCamelCase_			( __lowerCAmelCase       ,   __lowerCAmelCase    )							-> List[str]:




						'''simple docstring'''



						global batch_total
						for i in range(len(__lowerCAmelCase    )    ):
												# premise, all languages
												for text in dataset[i]["premise"].values():
																		test_string(__lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    )

												# hypothesis, all languages
												for text in dataset[i]["hypothesis"]["translation"]:
																		test_string(__lowerCAmelCase       ,   __lowerCAmelCase       ,   __lowerCAmelCase    )


if __name__ == "__main__":
	for name, (slow_class, fast_class) in TOKENIZER_CLASSES.items():
		a							=list(slow_class.max_model_input_sizes.keys())
		for checkpoint in checkpoint_names:
			a							=0
			a							=0
			a							=0
			a							=0

			print(F'''========================== Checking {name}: {checkpoint} ==========================''')
			a							=slow_class.from_pretrained(checkpoint, force_download=True)
			a							=fast_class.from_pretrained(checkpoint, force_download=True)
			test_tokenizer(slow, fast)
			print(F'''Accuracy {perfect * 100 / total:.2f}''')


