





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

lowercase__     :  Any    					=			datasets.load_dataset('xnli', split='test+validation')

lowercase__     :  Optional[Any]    					=			0
lowercase__     :  Optional[Any]    					=			0
lowercase__     :  Optional[int]    					=			0
lowercase__     :  Optional[int]    					=			0





def 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_	):
    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
    UpperCamelCase__      =			slow.encode(slow.decode(lowerCAmelCase_	)	)
    UpperCamelCase__      =			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 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_	):
    UpperCamelCase__      =			fast.encode_plus(lowerCAmelCase_	)[0]
    UpperCamelCase__      =			enc.offsets
    UpperCamelCase__    ,  UpperCamelCase__      =			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 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_	):
    # Encoding can be the same with same result AAA -> A + AA vs AA + A
    # We can check that we use at least exactly the same number of tokens.
    for i, (spm_id, tok_id) in enumerate(zip(lowerCAmelCase_					,  lowerCAmelCase_	)	):
        if spm_id != tok_id:
            break
    UpperCamelCase__      =			i
    for i, (spm_id, tok_id) in enumerate(zip(reversed(lowerCAmelCase_	)					,  reversed(lowerCAmelCase_	)	)	):
        if spm_id != tok_id:
            break
    UpperCamelCase__      =			len(lowerCAmelCase_	) - i

    UpperCamelCase__      =			spm_ids[first:last]
    UpperCamelCase__      =			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
        UpperCamelCase__      =			Counter(spm_ids[first:last]	)
        UpperCamelCase__      =			Counter(tok_ids[first:last]	)

        UpperCamelCase__      =			{spm_ for (spm_, si) in spms.items() if toks.get(spm_					,  0	) == si}
        UpperCamelCase__      =			3
        for i in range(last - first - min_width	):
            if all(spm_ids[first + i + j] in removable_tokens for j in range(lowerCAmelCase_	)	):
                UpperCamelCase__      =			[
                    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

    UpperCamelCase__      =			fast.decode(spm_ids[:first]	)
    UpperCamelCase__      =			fast.decode(spm_ids[last:]	)
    UpperCamelCase__      =			fast.decode(spm_ids[first:last]	)
    print()
    print(lowerCAmelCase_	)
    return False





def 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_	):
    global perfect
    global imperfect
    global wrong
    global total

    UpperCamelCase__      =			slow.encode(lowerCAmelCase_	)
    UpperCamelCase__      =			fast.encode(lowerCAmelCase_	)

    UpperCamelCase__      =			False
    total += 1

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

    if total % 1_00_00 == 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 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_	):
    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__     :  Tuple    					=			list(slow_class.max_model_input_sizes.keys())
            for checkpoint in checkpoint_names:
                  lowercase__     :  List[Any]    					=			0
                  lowercase__     :  Optional[Any]    					=			0
                  lowercase__     :  List[Any]    					=			0
                  lowercase__     :  Any    					=			0

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









'''simple docstring'''







def 						snake_case__ (lowerCAmelCase_	):
    for i, _ in enumerate(lowerCAmelCase_	):
        if (i % 2 == 1) == (nums[i - 1] > nums[i]):
            UpperCamelCase__    ,  UpperCamelCase__      =			nums[i], nums[i - 1]

    return nums


if __name__ == "__main__":
      print('Enter the array elements:')
      lowercase__     :  Optional[int]    					=			list(map(int, input().split()))
      print('The unsorted array is:')
      print(array)
      print('Array after Wiggle sort:')
      print(wiggle_sort(array))




