


"""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()

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

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

lowercase_							 =       0
lowercase_							 =       0
lowercase_							 =       0
lowercase_							 =       0
def     UpperCAmelCase    (					_lowercase   :      Optional[Any] ,      _lowercase   :      Tuple ,      _lowercase   :      List[str] ,      _lowercase   :      Tuple  )	->   Dict:


	"""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     UpperCAmelCase    (					_lowercase   :      Optional[int] ,      _lowercase   :      List[Any] ,      _lowercase   :      Optional[int]  )	->   Union[str, Any]:


	"""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     UpperCAmelCase    (					_lowercase   :      Dict ,      _lowercase   :      Dict ,      _lowercase   :      List[Any] ,      _lowercase   :      Optional[int] ,      _lowercase   :      Optional[int]  )	->   List[str]:


	"""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     UpperCAmelCase    (					_lowercase   :      Tuple ,      _lowercase   :      List[Any] ,      _lowercase   :      Union[str, Any]  )	->   str:


	"""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_0_0_0_0 == 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     UpperCAmelCase    (					_lowercase   :      Dict ,      _lowercase   :      Union[str, Any]  )	->   int:


	"""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():
						lowercase_							 =       list(slow_class.max_model_input_sizes.keys())
						for checkpoint in checkpoint_names:
									lowercase_							 =       0
									lowercase_							 =       0
									lowercase_							 =       0
									lowercase_							 =       0

									print(f"""========================== Checking {name}: {checkpoint} ==========================""")
									lowercase_							 =       slow_class.from_pretrained(checkpoint, force_download=True)
									lowercase_							 =       fast_class.from_pretrained(checkpoint, force_download=True)
									test_tokenizer(slow, fast)
									print(f"""Accuracy {perfect * 1_00 / total:.2f}""")



"""simple docstring"""



def     UpperCAmelCase    (					_lowercase   :      list[int]  )	->   int:


	"""simple docstring"""




	lowerCAmelCase_			       = len(_lowercase  )
	if n in (0, 1):
		return 0
	return sum(query * (n - i - 1) for i, query in enumerate(sorted(_lowercase  )  )  )


if __name__ == "__main__":
		import doctest

		doctest.testmod()