




'''simple docstring'''




from __future__ import annotations

from queue import Queue




def   snake_case__			(       lowerCamelCase__ :      Optional[Any]	,						lowerCamelCase__ :      List[str]	)      ->      Dict:
					a ^= b
					b ^= a
					a ^= b
					return a, b




def   snake_case__			(       lowerCamelCase__ :      Union[str, Any]	,						lowerCamelCase__ :      Optional[Any]	)      ->      int:
					A_       :   List[str]       =							1
					while (1 << j) < max_node:
										for i in range(1	,						max_node + 1	):
															A_       :   Dict       =							parent[j - 1][parent[j - 1][i]]
										j += 1
					return parent




def   snake_case__			(       lowerCamelCase__ :      Optional[Any]	,						lowerCamelCase__ :      int	,						lowerCamelCase__ :      Optional[int]	,						lowerCamelCase__ :      str	)      ->      Dict:






					if level[u] < level[v]:
										A_       ,A_       :   Dict       =							swap(_snake_case	,						_snake_case	)
					# making depth of u same as depth of v
					for i in range(1_8	,						-1	,						-1	):
										if level[u] - (1 << i) >= level[v]:
															A_       :   Any       =							parent[i][u]
    # at the same depth if u==v that mean lca is found
					if u == v:
										return u
					# moving both nodes upwards till lca in found
					for i in range(1_8	,						-1	,						-1	):
										if parent[i][u] not in [0, parent[i][v]]:
															A_       ,A_       :   str       =							parent[i][u], parent[i][v]
    # returning longest common ancestor of u,v
					return parent[0][u]




def   snake_case__			(       lowerCamelCase__ :      Optional[int]	,						lowerCamelCase__ :      List[str]	,						lowerCamelCase__ :      Dict	,						lowerCamelCase__ :      Optional[int]	,						lowerCamelCase__ :      Optional[int] = 1	,						)      ->      Any:
					A_       :   List[Any]       =							0
					A_       :   List[str]       =							Queue(maxsize=_snake_case	)
					q.put(_snake_case	)
					while q.qsize() != 0:
										A_       :   Dict       =							q.get()
										for v in graph[u]:
															if level[v] == -1:
																				A_       :   str       =							level[u] + 1
																				q.put(_snake_case	)
																				A_       :   Optional[int]       =							u
					return level, parent




def   snake_case__			(       )      ->      Optional[int]:
					A_       :   Union[str, Any]       =							1_3
					# initializing with 0
					A_       :   List[Any]       =							[[0 for _ in range(max_node + 1_0	)] for _ in range(2_0	)]
					# initializing with -1 which means every node is unvisited
					A_       :   List[str]       =							[-1 for _ in range(max_node + 1_0	)]
					A_       :   List[Any]       =							{
					    1: [2, 3, 4],
					    2: [5],
					    3: [6, 7],
					    4: [8],
					    5: [9, 1_0],
					    6: [1_1],
					    7: [],
					    8: [1_2, 1_3],
					    9: [],
					    1_0: [],
					    1_1: [],
					    1_2: [],
					    1_3: [],
					}
					A_       ,A_       :   str       =							breadth_first_search(_snake_case	,						_snake_case	,						_snake_case	,						_snake_case	,						1	)
					A_       :   Optional[int]       =							create_sparse(_snake_case	,						_snake_case	)
					print('''LCA of node 1 and 3 is: '''	,						lowest_common_ancestor(1	,						3	,						_snake_case	,						_snake_case	)	)
					print('''LCA of node 5 and 6 is: '''	,						lowest_common_ancestor(5	,						6	,						_snake_case	,						_snake_case	)	)
					print('''LCA of node 7 and 11 is: '''	,						lowest_common_ancestor(7	,						1_1	,						_snake_case	,						_snake_case	)	)
					print('''LCA of node 6 and 7 is: '''	,						lowest_common_ancestor(6	,						7	,						_snake_case	,						_snake_case	)	)
					print('''LCA of node 4 and 12 is: '''	,						lowest_common_ancestor(4	,						1_2	,						_snake_case	,						_snake_case	)	)
					print('''LCA of node 8 and 8 is: '''	,						lowest_common_ancestor(8	,						8	,						_snake_case	,						_snake_case	)	)


if __name__ == "__main__":
							main()











"""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()

_UpperCamelCase     			=  {
    name: (getattr(transformers, name), getattr(transformers, name + """Fast""")) for name in SLOW_TO_FAST_CONVERTERS
}

_UpperCamelCase     			=  datasets.load_dataset("""xnli""", split="""test+validation""")

_UpperCamelCase     			=  0
_UpperCamelCase     			=  0
_UpperCamelCase     			=  0
_UpperCamelCase     			=  0

def _a (		_snake_case      ,       _snake_case      ,       _snake_case      ,       _snake_case							):







      """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
      UpperCAmelCase							=       slow.encode(slow.decode(_snake_case							)							)
      UpperCAmelCase							=       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 _a (		_snake_case      ,       _snake_case      ,       _snake_case							):







      """simple docstring"""






      UpperCAmelCase							=       fast.encode_plus(_snake_case							)[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 _a (		_snake_case      ,       _snake_case      ,       _snake_case      ,       _snake_case      ,       _snake_case							):







      """simple docstring"""






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

      UpperCAmelCase							=       spm_ids[first:last]
      UpperCAmelCase							=       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
            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(_snake_case							)							):
                        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]      ,       _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

      UpperCAmelCase							=       fast.decode(spm_ids[:first]							)
      UpperCAmelCase							=       fast.decode(spm_ids[last:]							)
      UpperCAmelCase							=       fast.decode(spm_ids[first:last]							)
      print()
      print(_snake_case							)
      return False

def _a (		_snake_case      ,       _snake_case      ,       _snake_case							):







      """simple docstring"""






      global perfect
      global imperfect
      global wrong
      global total

      UpperCAmelCase							=       slow.encode(_snake_case							)
      UpperCAmelCase							=       fast.encode(_snake_case							)

      UpperCAmelCase							=       False
      total += 1

      if slow_ids != fast_ids:
            if check_details(_snake_case      ,       _snake_case      ,       _snake_case      ,       _snake_case      ,       _snake_case							):
                  UpperCAmelCase							=       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(_snake_case							)}\n{fast.tokenize(_snake_case							)}'''

def _a (		_snake_case      ,       _snake_case							):







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

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



