


"""simple docstring"""


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_snake_case          =							logging.get_logger(__name__)

_snake_case          =							{"vocab_file": "sentencepiece.bpe.model"}

_snake_case          =							{
    "vocab_file": {
        "moussaKam/mbarthez": "https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model",
        "moussaKam/barthez": "https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model",
        "moussaKam/barthez-orangesum-title": (
            "https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"
        ),
    },
}

_snake_case          =							{
    "moussaKam/mbarthez": 1024,
    "moussaKam/barthez": 1024,
    "moussaKam/barthez-orangesum-title": 1024,
}

_snake_case          =							"▁"



class   _a      (      SCREAMING_SNAKE_CASE_ ):
    a_    :				List[str]             =    VOCAB_FILES_NAMES
    a_    :				str             =    PRETRAINED_VOCAB_FILES_MAP
    a_    :				Tuple             =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a_    :				Union[str, Any]             =    ['input_ids', 'attention_mask']
    def __init__( self							:					List[Any]							,					SCREAMING_SNAKE_CASE__							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					Tuple="<s>"							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]="</s>"							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]="</s>"							,					SCREAMING_SNAKE_CASE__							:					int="<s>"							,					SCREAMING_SNAKE_CASE__							:					str="<unk>"							,					SCREAMING_SNAKE_CASE__							:					int="<pad>"							,					SCREAMING_SNAKE_CASE__							:					List[str]="<mask>"							,					SCREAMING_SNAKE_CASE__							:					Optional[Dict[str, Any]] = None							,					**SCREAMING_SNAKE_CASE__							:					Optional[Any]							,					):
          # Mask token behave like a normal word, i.e. include the space before it
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else mask_token

          lowerCamelCase__           =		{} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              bos_token=SCREAMING_SNAKE_CASE__							,					eos_token=SCREAMING_SNAKE_CASE__							,					unk_token=SCREAMING_SNAKE_CASE__							,					sep_token=SCREAMING_SNAKE_CASE__							,					cls_token=SCREAMING_SNAKE_CASE__							,					pad_token=SCREAMING_SNAKE_CASE__							,					mask_token=SCREAMING_SNAKE_CASE__							,					sp_model_kwargs=self.sp_model_kwargs							,					**SCREAMING_SNAKE_CASE__							,					)

          lowerCamelCase__           =		vocab_file
          lowerCamelCase__           =		spm.SentencePieceProcessor(**self.sp_model_kwargs				)
          self.sp_model.Load(str(SCREAMING_SNAKE_CASE__				)				)

          lowerCamelCase__           =		{'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

          lowerCamelCase__           =		len(self.sp_model				) - 1
          lowerCamelCase__           =		{v: k for k, v in self.fairseq_tokens_to_ids.items()}
    def      _UpperCamelCase       ( self							:					Optional[Any]							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None				):

          if token_ids_a is None:
                return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          lowerCamelCase__           =		[self.cls_token_id]
          lowerCamelCase__           =		[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep
    def      _UpperCamelCase       ( self							:					Optional[int]							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None							,					SCREAMING_SNAKE_CASE__							:					bool = False				):
          if already_has_special_tokens:
                return super().get_special_tokens_mask(
                    token_ids_a=SCREAMING_SNAKE_CASE__							,					token_ids_a=SCREAMING_SNAKE_CASE__							,					already_has_special_tokens=SCREAMING_SNAKE_CASE__				)

          if token_ids_a is None:
                return [1] + ([0] * len(SCREAMING_SNAKE_CASE__				)) + [1]
          return [1] + ([0] * len(SCREAMING_SNAKE_CASE__				)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE__				)) + [1]
    def      _UpperCamelCase       ( self							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None				):
          lowerCamelCase__           =		[self.sep_token_id]
          lowerCamelCase__           =		[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 + sep + token_ids_a + sep				) * [0]
    @property
    def      _UpperCamelCase       ( self							:					List[str]				):
          return len(self.sp_model				)
    def      _UpperCamelCase       ( self							:					Dict				):
          lowerCamelCase__           =		{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__				): i for i in range(self.vocab_size				)}
          vocab.update(self.added_tokens_encoder				)
          return vocab
    def      _UpperCamelCase       ( self							:					Dict							,					SCREAMING_SNAKE_CASE__							:					str				):
          return self.sp_model.encode(SCREAMING_SNAKE_CASE__							,					out_type=SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					List[str]				):
          if token in self.fairseq_tokens_to_ids:
                return self.fairseq_tokens_to_ids[token]
          lowerCamelCase__           =		self.sp_model.PieceToId(SCREAMING_SNAKE_CASE__				)

          return spm_id if spm_id else self.unk_token_id
    def      _UpperCamelCase       ( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					List[Any]				):
          if index in self.fairseq_ids_to_tokens:
                return self.fairseq_ids_to_tokens[index]
          return self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					Dict							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]				):
          lowerCamelCase__           =		[]
          lowerCamelCase__           =		''
          lowerCamelCase__           =		False
          for token in tokens:
                # make sure that special tokens are not decoded using sentencepiece model
                if token in self.all_special_tokens:
                      if not prev_is_special:
                            out_string += " "
                      out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__				) + token
                      lowerCamelCase__           =		True
                      lowerCamelCase__           =		[]
                else:
                      current_sub_tokens.append(SCREAMING_SNAKE_CASE__				)
                      lowerCamelCase__           =		False
          out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__				)
          return out_string.strip()
    def __getstate__( self							:					str				):
          lowerCamelCase__           =		self.__dict__.copy()
          lowerCamelCase__           =		None
          return state
    def __setstate__( self							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					Tuple				):
          lowerCamelCase__           =		d

          # for backward compatibility
          if not hasattr(self							,					'sp_model_kwargs'				):
                lowerCamelCase__           =		{}

          lowerCamelCase__           =		spm.SentencePieceProcessor(**self.sp_model_kwargs				)
          self.sp_model.Load(self.vocab_file				)


    def      _UpperCamelCase       ( self							:					Any							,					SCREAMING_SNAKE_CASE__							:					str							,					SCREAMING_SNAKE_CASE__							:					Optional[str] = None				):
          if not os.path.isdir(SCREAMING_SNAKE_CASE__				):
                logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
                return
          lowerCamelCase__           =		os.path.join(
              SCREAMING_SNAKE_CASE__							,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

          if os.path.abspath(self.vocab_file				) != os.path.abspath(SCREAMING_SNAKE_CASE__				) and os.path.isfile(self.vocab_file				):
                copyfile(self.vocab_file							,					SCREAMING_SNAKE_CASE__				)
          elif not os.path.isfile(self.vocab_file				):
                with open(SCREAMING_SNAKE_CASE__							,					'wb'				) as fi:
                      lowerCamelCase__           =		self.sp_model.serialized_model_proto()
                      fi.write(SCREAMING_SNAKE_CASE__				)

          return (out_vocab_file,)







"""simple docstring"""


from __future__ import annotations

_snake_case          =							[
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]



def   snake_case						(				_a:     list[list[int]]		,   _a:     list[int]		,   _a:     list[int]		,   _a:     int		,   _a:     list[list[int]]		,   )->		tuple[list[list[int]], list[list[int]]]:
      '''simple docstring'''


      lowerCamelCase__           =		[
          [0 for col in range(len(grid[0]							)							)] for row in range(len(_a							)							)
      ]  # the reference grid
      lowerCamelCase__           =		1
      lowerCamelCase__           =		[
          [0 for col in range(len(grid[0]							)							)] for row in range(len(_a							)							)
      ]  # the action grid

      lowerCamelCase__           =		init[0]
      lowerCamelCase__           =		init[1]
      lowerCamelCase__           =		0
      lowerCamelCase__           =		g + heuristic[x][y]  # cost from starting cell to destination cell
      lowerCamelCase__           =		[[f, g, x, y]]

      lowerCamelCase__           =		False  # flag that is set when search is complete
      lowerCamelCase__           =		False  # flag set if we can't find expand

      while not found and not resign:
            if len(_a							) == 0:
                  raise ValueError('Algorithm is unable to find solution'							)
            else:  # to choose the least costliest action so as to move closer to the goal
                  cell.sort()
                  cell.reverse()
                  lowerCamelCase__           =		cell.pop()
                  lowerCamelCase__           =		next_cell[2]
                  lowerCamelCase__           =		next_cell[3]
                  lowerCamelCase__           =		next_cell[1]

                  if x == goal[0] and y == goal[1]:
                        lowerCamelCase__           =		True
                  else:
                        for i in range(len(_a							)							):  # to try out different valid actions
                              lowerCamelCase__           =		x + DIRECTIONS[i][0]
                              lowerCamelCase__           =		y + DIRECTIONS[i][1]
                              if xa >= 0 and xa < len(_a							) and ya >= 0 and ya < len(grid[0]							):
                                    if closed[xa][ya] == 0 and grid[xa][ya] == 0:
                                          lowerCamelCase__           =		g + cost
                                          lowerCamelCase__           =		ga + heuristic[xa][ya]
                                          cell.append([fa, ga, xa, ya]							)
                                          lowerCamelCase__           =		1
                                          lowerCamelCase__           =		i
      lowerCamelCase__           =		[]
      lowerCamelCase__           =		goal[0]
      lowerCamelCase__           =		goal[1]
      invpath.append([x, y]							)  # we get the reverse path from here
      while x != init[0] or y != init[1]:
            lowerCamelCase__           =		x - DIRECTIONS[action[x][y]][0]
            lowerCamelCase__           =		y - DIRECTIONS[action[x][y]][1]
            lowerCamelCase__           =		xa
            lowerCamelCase__           =		ya
            invpath.append([x, y]							)

      lowerCamelCase__           =		[]
      for i in range(len(_a							)							):
            path.append(invpath[len(_a							) - 1 - i]							)
      return path, action


if __name__ == "__main__":
   _snake_case          =							[
       [0, 1, 0, 0, 0, 0],
       [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
       [0, 1, 0, 0, 0, 0],
       [0, 1, 0, 0, 1, 0],
       [0, 0, 0, 0, 1, 0],
   ]

   _snake_case          =							[0, 0]
   # all coordinates are given in format [y,x]
   _snake_case          =							[len(grid) - 1, len(grid[0]) - 1]
   _snake_case          =							1

   # the cost map which pushes the path closer to the goal
   _snake_case          =							[[0 for row in range(len(grid[0]))] for col in range(len(grid))]
   for i in range(len(grid)):
      for j in range(len(grid[0])):
         _snake_case          =							abs(i - goal[0]) + abs(j - goal[1])
         if grid[i][j] == 1:
            # added extra penalty in the heuristic map
            _snake_case          =							99

   _snake_case      ,					_snake_case          =							search(grid, init, goal, cost, heuristic)

   print("ACTION MAP")
   for i in range(len(action)):
      print(action[i])

   for i in range(len(path)):
      print(path[i])



