




"""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 							lowercase   (snake_case__				:	Any ,    snake_case__				:	List[Any] ,    snake_case__				:	Dict ,    snake_case__				:	List[Any]	)       ->					int:


				'''simple docstring'''






				if spm_diff == list(reversed(snake_case__	)	):
								# AAA -> AA+A vs A+AA case.
								return True
				elif len(snake_case__	) == len(snake_case__	) and fast.decode(snake_case__	) == fast.decode(snake_case__	):
								# Second order OK
								# Barrich -> Barr + ich vs Bar + rich
								return True
				lowerCAmelCase		=			slow.encode(slow.decode(snake_case__	)	)
				lowerCAmelCase		=			fast.encode(fast.decode(snake_case__	)	)
				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 							lowercase   (snake_case__				:	Tuple ,    snake_case__				:	List[str] ,    snake_case__				:	Tuple	)       ->					int:


				'''simple docstring'''






				lowerCAmelCase		=			fast.encode_plus(snake_case__	)[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 							lowercase   (snake_case__				:	int ,    snake_case__				:	Optional[Any] ,    snake_case__				:	Dict ,    snake_case__				:	Optional[Any] ,    snake_case__				:	List[str]	)       ->					Optional[Any]:


				'''simple docstring'''






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

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

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

				if check_LTR_mark(snake_case__ ,    snake_case__ ,    snake_case__	):
								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(snake_case__	)	):
																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] ,    snake_case__ ,    snake_case__	) and check_details(
																				    snake_case__ ,    spm_ids[first + i : last] ,    tok_ids[first + j : last] ,    snake_case__ ,    snake_case__ ,    ):
																								return True

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

				lowerCAmelCase		=			fast.decode(spm_ids[:first]	)
				lowerCAmelCase		=			fast.decode(spm_ids[last:]	)
				lowerCAmelCase		=			fast.decode(spm_ids[first:last]	)
				print()
				print(snake_case__	)
				return False





def 							lowercase   (snake_case__				:	Union[str, Any] ,    snake_case__				:	Union[str, Any] ,    snake_case__				:	Optional[Any]	)       ->					Tuple:


				'''simple docstring'''






				global perfect
				global imperfect
				global wrong
				global total

				lowerCAmelCase		=			slow.encode(snake_case__	)
				lowerCAmelCase		=			fast.encode(snake_case__	)

				lowerCAmelCase		=			False
				total += 1

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

				if total % 10_000 == 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(snake_case__	)}\n{fast.tokenize(snake_case__	)}'''





def 							lowercase   (snake_case__				:	Tuple ,    snake_case__				:	Optional[Any]	)       ->					Any:


				'''simple docstring'''






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

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


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 * 1_0_0 / total:.2f}""")











"""simple docstring"""







import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


a								=							logging.get_logger(__name__)

a								=							{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

a								=							{
    'vocab_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
    },
    'tokenizer_file': {
        'allenai/longformer-base-4096': (
            'https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json'
        ),
    },
}

a								=							{
    'allenai/longformer-base-4096': 4_0_9_6,
    'allenai/longformer-large-4096': 4_0_9_6,
    'allenai/longformer-large-4096-finetuned-triviaqa': 4_0_9_6,
    'allenai/longformer-base-4096-extra.pos.embd.only': 4_0_9_6,
    'allenai/longformer-large-4096-extra.pos.embd.only': 4_0_9_6,
}






class  SCREAMING_SNAKE_CASE__   (   _a   ):
						_a        =  VOCAB_FILES_NAMES
						_a        =  PRETRAINED_VOCAB_FILES_MAP
						_a        =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_a        =  ['input_ids', 'attention_mask']
						_a        =  LongformerTokenizer


						def __init__(							self			:     Optional[Any]  ,  lowerCAmelCase			:     Tuple=None  ,  lowerCAmelCase			:     Any=None  ,  lowerCAmelCase			:     List[Any]=None  ,  lowerCAmelCase			:     Optional[Any]="replace"  ,  lowerCAmelCase			:     Union[str, Any]="<s>"  ,  lowerCAmelCase			:     int="</s>"  ,  lowerCAmelCase			:     Any="</s>"  ,  lowerCAmelCase			:     Union[str, Any]="<s>"  ,  lowerCAmelCase			:     List[str]="<unk>"  ,  lowerCAmelCase			:     Optional[Any]="<pad>"  ,  lowerCAmelCase			:     List[str]="<mask>"  ,  lowerCAmelCase			:     Tuple=False  ,  lowerCAmelCase			:     List[str]=True  ,  **lowerCAmelCase			:     Optional[int]  ,  ):
										super().__init__(
										    lowerCAmelCase  ,  lowerCAmelCase  ,  tokenizer_file=lowerCAmelCase  ,  errors=lowerCAmelCase  ,  bos_token=lowerCAmelCase  ,  eos_token=lowerCAmelCase  ,  sep_token=lowerCAmelCase  ,  cls_token=lowerCAmelCase  ,  unk_token=lowerCAmelCase  ,  pad_token=lowerCAmelCase  ,  mask_token=lowerCAmelCase  ,  add_prefix_space=lowerCAmelCase  ,  trim_offsets=lowerCAmelCase  ,  **lowerCAmelCase  ,  )

										lowerCAmelCase		=			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
										if pre_tok_state.get("""add_prefix_space"""  ,  lowerCAmelCase   ) != add_prefix_space:
														lowerCAmelCase		=			getattr(lowerCAmelCase  ,  pre_tok_state.pop("""type"""   )   )
														lowerCAmelCase		=			add_prefix_space
														lowerCAmelCase		=			pre_tok_class(**lowerCAmelCase   )

										lowerCAmelCase		=			add_prefix_space

										lowerCAmelCase		=			"""post_processor"""
										lowerCAmelCase		=			getattr(self.backend_tokenizer  ,  lowerCAmelCase  ,  lowerCAmelCase   )
										if tokenizer_component_instance:
														lowerCAmelCase		=			json.loads(tokenizer_component_instance.__getstate__()   )

														# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
														if "sep" in state:
																		lowerCAmelCase		=			tuple(state["""sep"""]   )
														if "cls" in state:
																		lowerCAmelCase		=			tuple(state["""cls"""]   )

														lowerCAmelCase		=			False

														if state.get("""add_prefix_space"""  ,  lowerCAmelCase   ) != add_prefix_space:
																		lowerCAmelCase		=			add_prefix_space
																		lowerCAmelCase		=			True

														if state.get("""trim_offsets"""  ,  lowerCAmelCase   ) != trim_offsets:
																		lowerCAmelCase		=			trim_offsets
																		lowerCAmelCase		=			True

														if changes_to_apply:
																		lowerCAmelCase		=			getattr(lowerCAmelCase  ,  state.pop("""type"""   )   )
																		lowerCAmelCase		=			component_class(**lowerCAmelCase   )
																		setattr(self.backend_tokenizer  ,  lowerCAmelCase  ,  lowerCAmelCase   )


						@property
						def 					__lowercase	(							self			:     List[Any]   ):
										if self._mask_token is None:
														if self.verbose:
																		logger.error("""Using mask_token, but it is not set yet."""   )
														return None
										return str(self._mask_token   )


						@mask_token.setter
						def 					__lowercase	(							self			:     List[Any]  ,  lowerCAmelCase			:     Dict   ):
										lowerCAmelCase		=			AddedToken(lowerCAmelCase  ,  lstrip=lowerCAmelCase  ,  rstrip=lowerCAmelCase   ) if isinstance(lowerCAmelCase  ,  lowerCAmelCase   ) else value
										lowerCAmelCase		=			value


						def 					__lowercase	(							self			:     Tuple  ,  *lowerCAmelCase			:     Optional[int]  ,  **lowerCAmelCase			:     Optional[Any]   ):
										lowerCAmelCase		=			kwargs.get("""is_split_into_words"""  ,  lowerCAmelCase   )
										assert self.add_prefix_space or not is_split_into_words, (
										    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
										    "to use it with pretokenized inputs."
										)

										return super()._batch_encode_plus(*lowerCAmelCase  ,  **lowerCAmelCase   )


						def 					__lowercase	(							self			:     str  ,  *lowerCAmelCase			:     str  ,  **lowerCAmelCase			:     str   ):
										lowerCAmelCase		=			kwargs.get("""is_split_into_words"""  ,  lowerCAmelCase   )

										assert self.add_prefix_space or not is_split_into_words, (
										    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
										    "to use it with pretokenized inputs."
										)

										return super()._encode_plus(*lowerCAmelCase  ,  **lowerCAmelCase   )


						def 					__lowercase	(							self			:     Optional[int]  ,  lowerCAmelCase			:     str  ,  lowerCAmelCase			:     Optional[str] = None   ):
										lowerCAmelCase		=			self._tokenizer.model.save(lowerCAmelCase  ,  name=lowerCAmelCase   )
										return tuple(lowerCAmelCase   )


						def 					__lowercase	(							self			:     Optional[Any]  ,  lowerCAmelCase			:     List[str]  ,  lowerCAmelCase			:     Optional[int]=None   ):
										lowerCAmelCase		=			[self.bos_token_id] + token_ids_a + [self.eos_token_id]
										if token_ids_a is None:
														return output

										return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




						def 					__lowercase	(							self			:     Optional[int]  ,  lowerCAmelCase			:     List[int]  ,  lowerCAmelCase			:     Optional[List[int]] = None   ):
										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]





