






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()

snake_case_   :	Union[str, Any]							      ={
    name: (getattr(transformers, name), getattr(transformers, name + '''Fast''')) for name in SLOW_TO_FAST_CONVERTERS
}

snake_case_   :	Tuple							      =datasets.load_dataset('''xnli''', split='''test+validation''')

snake_case_   :	Any							      =0
snake_case_   :	List[str]							      =0
snake_case_   :	Any							      =0
snake_case_   :	Optional[Any]							      =0



def      UpperCAmelCase						( lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__	):


		'''simple docstring'''

		if spm_diff == list(reversed(__lowercase	)	):
				# AAA -> AA+A vs A+AA case.
				return True
		elif len(__lowercase	) == len(__lowercase	) and fast.decode(__lowercase	) == fast.decode(__lowercase	):
				# Second order OK
				# Barrich -> Barr + ich vs Bar + rich
				return True
		__A    =							slow.encode(slow.decode(__lowercase	)	)
		__A    =							fast.encode(fast.decode(__lowercase	)	)
		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      UpperCAmelCase						( lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__	):


		'''simple docstring'''

		__A    =							fast.encode_plus(__lowercase	)[0]
		__A    =							enc.offsets
		__A    =							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      UpperCAmelCase						( lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__	):


		'''simple docstring'''

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

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

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

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

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

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

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

		__A    =							fast.decode(spm_ids[:first]	)
		__A    =							fast.decode(spm_ids[last:]	)
		__A    =							fast.decode(spm_ids[first:last]	)
		print()
		print(__lowercase	)
		return False



def      UpperCAmelCase						( lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__	):


		'''simple docstring'''

		global perfect
		global imperfect
		global wrong
		global total

		__A    =							slow.encode(__lowercase	)
		__A    =							fast.encode(__lowercase	)

		__A    =							False
		total += 1

		if slow_ids != fast_ids:
				if check_details(__lowercase					,     __lowercase					,     __lowercase					,     __lowercase					,     __lowercase	):
						__A    =							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(__lowercase	)}\n{fast.tokenize(__lowercase	)}"""



def      UpperCAmelCase						( lowerCAmelCase__					,     lowerCAmelCase__	):


		'''simple docstring'''

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

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


if __name__ == "__main__":
					for name, (slow_class, fast_class) in TOKENIZER_CLASSES.items():
										snake_case_   :	Dict							      =list(slow_class.max_model_input_sizes.keys())
										for checkpoint in checkpoint_names:
															snake_case_   :	Any							      =0
															snake_case_   :	Any							      =0
															snake_case_   :	List[str]							      =0
															snake_case_   :	int							      =0

															print(f"""========================== Checking {name}: {checkpoint} ==========================""")
															snake_case_   :	List[str]							      =slow_class.from_pretrained(checkpoint, force_download=True)
															snake_case_   :	int							      =fast_class.from_pretrained(checkpoint, force_download=True)
															test_tokenizer(slow, fast)
															print(f"""Accuracy {perfect * 100 / total:.2f}""")







'''simple docstring'''


from __future__ import annotations

from collections.abc import Callable
from typing import Generic, TypeVar

UpperCamelCase			     =					TypeVar('''T''')
UpperCamelCase			     =					TypeVar('''U''')






class 						lowerCAmelCase_	(       Generic[T, U]							):







  '''simple docstring'''

  def __init__( self				:							Tuple					,  SCREAMING_SNAKE_CASE_				:							T | None					,  SCREAMING_SNAKE_CASE_				:							U | None	)			->		Any:







       '''simple docstring'''



       A:		Union[str, Any]          =		key
       A:		Union[str, Any]          =		val
       A:		int          =		0
       A:		DoubleLinkedListNode[T, U] | None          =		None
       A:		DoubleLinkedListNode[T, U] | None          =		None




  def __repr__( self				:							Any	)			->		str:







       '''simple docstring'''



       return "Node: key: {}, val: {}, freq: {}, has next: {}, has prev: {}".format(
           self.key					,  self.val					,  self.freq					,  self.next is not None					,  self.prev is not None	)






class 						lowerCAmelCase_	(       Generic[T, U]							):







  '''simple docstring'''

  def __init__( self				:							int	)			->		None:







       '''simple docstring'''



       A:		DoubleLinkedListNode[T, U]          =		DoubleLinkedListNode(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_	)
       A:		DoubleLinkedListNode[T, U]          =		DoubleLinkedListNode(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_	)
       A     ,    A:		Any          =		self.rear, self.head



  def __repr__( self				:							Optional[int]	)			->		str:







       '''simple docstring'''



       A:		int          =		['''DoubleLinkedList''']
       A:		Dict          =		self.head
       while node.next is not None:
            rep.append(str(SCREAMING_SNAKE_CASE_	)	)
            A:		int          =		node.next
       rep.append(str(self.rear	)	)
       return ",\n    ".join(SCREAMING_SNAKE_CASE_	)



  def 					_snake_case     ( self				:							Any					,  SCREAMING_SNAKE_CASE_				:							DoubleLinkedListNode[T, U]	)			->		None:







       '''simple docstring'''



       A:		Union[str, Any]          =		self.rear.prev

       # All nodes other than self.head are guaranteed to have non-None previous
       assert previous is not None

       A:		Optional[int]          =		node
       A:		int          =		previous
       A:		Dict          =		node
       A:		int          =		self.rear
       node.freq += 1
       self._position_node(SCREAMING_SNAKE_CASE_	)



  def 					_snake_case     ( self				:							int					,  SCREAMING_SNAKE_CASE_				:							DoubleLinkedListNode[T, U]	)			->		None:







       '''simple docstring'''



       while node.prev is not None and node.prev.freq > node.freq:
            # swap node with previous node
            A:		Any          =		node.prev

            A:		Optional[Any]          =		previous_node.prev
            A:		int          =		node.prev
            A:		int          =		previous_node
            A:		Optional[int]          =		node




  def 					_snake_case     ( self				:							Dict					,  SCREAMING_SNAKE_CASE_				:							DoubleLinkedListNode[T, U]	)			->		DoubleLinkedListNode[T, U] | None:







       '''simple docstring'''



       if node.prev is None or node.next is None:
            return None

       A:		List[Any]          =		node.next
       A:		Dict          =		node.prev
       A:		str          =		None
       A:		Union[str, Any]          =		None
       return node






class 						lowerCAmelCase_	(       Generic[T, U]							):







  '''simple docstring'''

  UpperCamelCase_			:      dict[Callable[[T], U], LFUCache[T, U]]										=				{}



  def __init__( self				:							List[str]					,  SCREAMING_SNAKE_CASE_				:							int	)			->		int:







       '''simple docstring'''



       A:		DoubleLinkedList[T, U]          =		DoubleLinkedList()
       A:		Any          =		capacity
       A:		List[Any]          =		0
       A:		Dict          =		0
       A:		Dict          =		0
       A:		dict[T, DoubleLinkedListNode[T, U]]          =		{}



  def __repr__( self				:							Optional[int]	)			->		str:







       '''simple docstring'''



       return (
           f"""CacheInfo(hits={self.hits}, misses={self.miss}, """
           f"""capacity={self.capacity}, current_size={self.num_keys})"""
       )



  def __contains__( self				:							str					,  SCREAMING_SNAKE_CASE_				:							T	)			->		bool:







       '''simple docstring'''



       return key in self.cache



  def 					_snake_case     ( self				:							Dict					,  SCREAMING_SNAKE_CASE_				:							T	)			->		U | None:







       '''simple docstring'''



       if key in self.cache:
            self.hits += 1
            A:		DoubleLinkedListNode[T, U]          =		self.cache[key]
            A:		List[str]          =		self.list.remove(self.cache[key]	)
            assert node == value_node

            # node is guaranteed not None because it is in self.cache
            assert node is not None
            self.list.add(SCREAMING_SNAKE_CASE_	)
            return node.val
       self.miss += 1
       return None



  def 					_snake_case     ( self				:							List[str]					,  SCREAMING_SNAKE_CASE_				:							T					,  SCREAMING_SNAKE_CASE_				:							U	)			->		None:







       '''simple docstring'''



       if key not in self.cache:
            if self.num_keys >= self.capacity:
                 # delete first node when over capacity
                 A:		List[Any]          =		self.list.head.next

                 # guaranteed to have a non-None first node when num_keys > 0
                 # explain to type checker via assertions
                 assert first_node is not None
                 assert first_node.key is not None
                 assert self.list.remove(SCREAMING_SNAKE_CASE_	) is not None
                 # first_node guaranteed to be in list

                 del self.cache[first_node.key]
                 self.num_keys -= 1
            A:		Tuple          =		DoubleLinkedListNode(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_	)
            self.list.add(self.cache[key]	)
            self.num_keys += 1

       else:
            A:		Optional[Any]          =		self.list.remove(self.cache[key]	)
            assert node is not None  # node guaranteed to be in list
            A:		List[str]          =		value
            self.list.add(SCREAMING_SNAKE_CASE_	)




  @classmethod
  def 					_snake_case     ( cls				:							type[LFUCache[T, U]]					,  SCREAMING_SNAKE_CASE_				:							int = 1_28	)			->		Callable[[Callable[[T], U]], Callable[..., U]]:







       '''simple docstring'''



       def cache_decorator_inner(SCREAMING_SNAKE_CASE_				:							Callable[[T], U]	) -> Callable[..., U]:
            def cache_decorator_wrapper(*SCREAMING_SNAKE_CASE_				:							T	) -> U:
                 if func not in cls.decorator_function_to_instance_map:
                      A:		Tuple          =		LFUCache(SCREAMING_SNAKE_CASE_	)

                 A:		List[Any]          =		cls.decorator_function_to_instance_map[func].get(args[0]	)
                 if result is None:
                      A:		List[str]          =		func(*SCREAMING_SNAKE_CASE_	)
                      cls.decorator_function_to_instance_map[func].put(args[0]					,  SCREAMING_SNAKE_CASE_	)
                 return result

            def cache_info() -> LFUCache[T, U]:
                 return cls.decorator_function_to_instance_map[func]

            setattr(SCREAMING_SNAKE_CASE_					,  '''cache_info'''					,  SCREAMING_SNAKE_CASE_	)  # noqa: B010

            return cache_decorator_wrapper

       return cache_decorator_inner


if __name__ == "__main__":
     import doctest

     doctest.testmod()






