'''simple docstring'''
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer


lowercase__  :      List[Any]        =					logging.get_logger(__name__)

lowercase__  :      Optional[int]        =					{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

lowercase__  :      Union[str, Any]        =					{
    "vocab_file": {"mobilebert-uncased": "https://huggingface.co/google/mobilebert-uncased/resolve/main/vocab.txt"},
    "tokenizer_file": {
        "mobilebert-uncased": "https://huggingface.co/google/mobilebert-uncased/resolve/main/tokenizer.json"
    },
}

lowercase__  :      Tuple        =					{"mobilebert-uncased": 512}


lowercase__  :      Union[str, Any]        =					{}







class lowerCamelCase							(	lowerCamelCase					):




  '''simple docstring'''



  lowerCAmelCase__										=	VOCAB_FILES_NAMES
  lowerCAmelCase__										=	PRETRAINED_VOCAB_FILES_MAP
  lowerCAmelCase__										=	PRETRAINED_INIT_CONFIGURATION
  lowerCAmelCase__										=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowerCAmelCase__										=	MobileBertTokenizer






  def __init__(      self			:       Dict  ,							UpperCAmelCase__			:       Optional[int]=None  ,							UpperCAmelCase__			:       Dict=None  ,							UpperCAmelCase__			:       str=True  ,							UpperCAmelCase__			:       int="[UNK]"  ,							UpperCAmelCase__			:       List[Any]="[SEP]"  ,							UpperCAmelCase__			:       Any="[PAD]"  ,							UpperCAmelCase__			:       Optional[int]="[CLS]"  ,							UpperCAmelCase__			:       Dict="[MASK]"  ,							UpperCAmelCase__			:       Any=True  ,							UpperCAmelCase__			:       List[str]=None  ,							**UpperCAmelCase__			:       Optional[int]  ,							)				->Any:
        super().__init__(
            UpperCAmelCase__  ,							tokenizer_file=UpperCAmelCase__  ,							do_lower_case=UpperCAmelCase__  ,							unk_token=UpperCAmelCase__  ,							sep_token=UpperCAmelCase__  ,							pad_token=UpperCAmelCase__  ,							cls_token=UpperCAmelCase__  ,							mask_token=UpperCAmelCase__  ,							tokenize_chinese_chars=UpperCAmelCase__  ,							strip_accents=UpperCAmelCase__  ,							**UpperCAmelCase__  ,							)

        UpperCAmelCase_            =  json.loads(self.backend_tokenizer.normalizer.__getstate__()  )
        if (
            normalizer_state.get('''lowercase'''  ,							UpperCAmelCase__  ) != do_lower_case
            or normalizer_state.get('''strip_accents'''  ,							UpperCAmelCase__  ) != strip_accents
            or normalizer_state.get('''handle_chinese_chars'''  ,							UpperCAmelCase__  ) != tokenize_chinese_chars
        ):
              UpperCAmelCase_            =  getattr(UpperCAmelCase__  ,							normalizer_state.pop('''type'''  )  )
              UpperCAmelCase_            =  do_lower_case
              UpperCAmelCase_            =  strip_accents
              UpperCAmelCase_            =  tokenize_chinese_chars
              UpperCAmelCase_            =  normalizer_class(**UpperCAmelCase__  )

        UpperCAmelCase_            =  do_lower_case






  def  lowerCAmelCase__ (      self			:       Dict  ,							UpperCAmelCase__			:       Union[str, Any]  ,							UpperCAmelCase__			:       str=None  )				->Optional[Any]:
        UpperCAmelCase_            =  [self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
              output += token_ids_a + [self.sep_token_id]

        return output






  def  lowerCAmelCase__ (      self			:       Tuple  ,							UpperCAmelCase__			:       List[int]  ,							UpperCAmelCase__			:       Optional[List[int]] = None  )				->List[int]:
        UpperCAmelCase_            =  [self.sep_token_id]
        UpperCAmelCase_            =  [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  ) * [0] + len(token_ids_a + sep  ) * [1]






  def  lowerCAmelCase__ (      self			:       Tuple  ,							UpperCAmelCase__			:       str  ,							UpperCAmelCase__			:       Optional[str] = None  )				->Tuple[str]:
        UpperCAmelCase_            =  self._tokenizer.model.save(UpperCAmelCase__  ,							name=UpperCAmelCase__  )
        return tuple(UpperCAmelCase__  )




'''simple docstring'''
from heapq import heappop, heappush

import numpy as np



def  __lowerCamelCase       (      _UpperCamelCase  :  np.ndarray							,    _UpperCamelCase  :  tuple[int, int]							,    _UpperCamelCase  :  tuple[int, int]							,    _UpperCamelCase  :  bool							,    ):


      '''simple docstring'''


      UpperCAmelCase_      ,		UpperCAmelCase_            =  grid.shape
      UpperCAmelCase_            =  [-1, 1, 0, 0]
      UpperCAmelCase_            =  [0, 0, -1, 1]
      if allow_diagonal:
            dx += [-1, -1, 1, 1]
            dy += [-1, 1, -1, 1]

      UpperCAmelCase_      ,		UpperCAmelCase_            =  [(0, source)], set()
      UpperCAmelCase_            =  np.full((rows, cols)							,    np.inf					)
      UpperCAmelCase_            =  0
      UpperCAmelCase_            =  np.empty((rows, cols)							,    dtype=_UpperCamelCase					)
      UpperCAmelCase_            =  None

      while queue:
            ((UpperCAmelCase_)      ,		(UpperCAmelCase_))            =  heappop(_UpperCamelCase					)
            if (x, y) in visited:
                  continue
            visited.add((x, y)					)

            if (x, y) == destination:
                  UpperCAmelCase_            =  []
                  while (x, y) != source:
                        path.append((x, y)					)
                        UpperCAmelCase_      ,		UpperCAmelCase_            =  predecessors[x, y]
                  path.append(_UpperCamelCase					)  # add the source manually
                  path.reverse()
                  return matrix[destination], path

            for i in range(len(_UpperCamelCase					)					):
                  UpperCAmelCase_      ,		UpperCAmelCase_            =  x + dx[i], y + dy[i]
                  if 0 <= nx < rows and 0 <= ny < cols:
                        UpperCAmelCase_            =  grid[nx][ny]
                        if next_node == 1 and matrix[nx, ny] > dist + 1:
                              heappush(_UpperCamelCase							,    (dist + 1, (nx, ny))					)
                              UpperCAmelCase_            =  dist + 1
                              UpperCAmelCase_            =  (x, y)

      return np.inf, []


if __name__ == "__main__":
      import doctest

      doctest.testmod()





