




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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase								=					logging.get_logger(__name__)

UpperCamelCase								=					'▁'

UpperCamelCase								=					{'vocab_file': 'sentencepiece.bpe.model'}

UpperCamelCase								=					{
    'vocab_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model',
    }
}

UpperCamelCase								=					{
    'facebook/xglm-564M': 2048,
}





class 			__lowerCamelCase	(   UpperCamelCase__   ):




    """simple docstring"""

    snake_case__ =				VOCAB_FILES_NAMES
    snake_case__ =				PRETRAINED_VOCAB_FILES_MAP
    snake_case__ =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    snake_case__ =				["input_ids", "attention_mask"]


    def __init__(	self					:					Tuple       ,     SCREAMING_SNAKE_CASE__					:					List[Any]       ,     SCREAMING_SNAKE_CASE__					:					int="<s>"       ,     SCREAMING_SNAKE_CASE__					:					List[Any]="</s>"       ,     SCREAMING_SNAKE_CASE__					:					List[str]="</s>"       ,     SCREAMING_SNAKE_CASE__					:					List[Any]="<s>"       ,     SCREAMING_SNAKE_CASE__					:					List[str]="<unk>"       ,     SCREAMING_SNAKE_CASE__					:					List[Any]="<pad>"       ,     SCREAMING_SNAKE_CASE__					:					Optional[Dict[str, Any]] = None       ,     **SCREAMING_SNAKE_CASE__					:					int       ,     )				->	None:
         lowerCAmelCase__          =			{} if sp_model_kwargs is None else sp_model_kwargs

         # Compatibility with the original tokenizer
         lowerCAmelCase__          =			7
         lowerCAmelCase__          =			[f'<madeupword{i}>' for i in range(self.num_madeup_words       )]

         lowerCAmelCase__          =			kwargs.get("additional_special_tokens"       ,     []       )
         kwargs["additional_special_tokens"] += [
             word for word in madeup_words if word not in kwargs["additional_special_tokens"]
         ]

         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__       ,     sp_model_kwargs=self.sp_model_kwargs       ,     **SCREAMING_SNAKE_CASE__       ,     )

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

         # Original fairseq vocab and spm vocab must be "aligned":
         # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
         # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
         # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
         # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

         # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
         lowerCAmelCase__          =			1

         # Mimic fairseq token-to-id alignment for the first 4 token
         lowerCAmelCase__          =			{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

         lowerCAmelCase__          =			len(self.sp_model       )
         lowerCAmelCase__          =			{f'<madeupword{i}>': sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words       )}
         self.fairseq_tokens_to_ids.update(SCREAMING_SNAKE_CASE__       )

         lowerCAmelCase__          =			{v: k for k, v in self.fairseq_tokens_to_ids.items()}


    def __getstate__(	self					:					Any       )				->	int:
         lowerCAmelCase__          =			self.__dict__.copy()
         lowerCAmelCase__          =			None
         lowerCAmelCase__          =			self.sp_model.serialized_model_proto()
         return state


    def __setstate__(	self					:					List[str]       ,     SCREAMING_SNAKE_CASE__					:					Any       )				->	Any:
         lowerCAmelCase__          =			d

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

         lowerCAmelCase__          =			spm.SentencePieceProcessor(**self.sp_model_kwargs       )
         self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )


    def        a				(	self					:					Dict       ,     SCREAMING_SNAKE_CASE__					:					List[int]       ,     SCREAMING_SNAKE_CASE__					:					Optional[List[int]] = None       )				->	List[int]:

         if token_ids_a is None:
              return [self.sep_token_id] + token_ids_a
         lowerCAmelCase__          =			[self.sep_token_id]
         return sep + token_ids_a + sep + sep + token_ids_a


    def        a				(	self					:					List[Any]       ,     SCREAMING_SNAKE_CASE__					:					List[int]       ,     SCREAMING_SNAKE_CASE__					:					Optional[List[int]] = None       ,     SCREAMING_SNAKE_CASE__					:					bool = False       )				->	List[int]:

         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__       ))
         return [1] + ([0] * len(SCREAMING_SNAKE_CASE__       )) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE__       ))


    def        a				(	self					:					Optional[Any]       ,     SCREAMING_SNAKE_CASE__					:					List[int]       ,     SCREAMING_SNAKE_CASE__					:					Optional[List[int]] = None       )				->	List[int]:
         lowerCAmelCase__          =			[self.sep_token_id]

         if token_ids_a is None:
              return len(sep + token_ids_a       ) * [0]
         return len(sep + token_ids_a + sep + sep + token_ids_a       ) * [0]


    @property
    def        a				(	self					:					int       )				->	Any:
         return len(self.sp_model       ) + self.fairseq_offset + self.num_madeup_words


    def        a				(	self					:					str       )				->	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        a				(	self					:					List[Any]       ,     SCREAMING_SNAKE_CASE__					:					str       )				->	List[str]:
         return self.sp_model.encode(SCREAMING_SNAKE_CASE__       ,     out_type=SCREAMING_SNAKE_CASE__       )


    def        a				(	self					:					Dict       ,     SCREAMING_SNAKE_CASE__					:					int       )				->	Union[str, Any]:
         if token in self.fairseq_tokens_to_ids:
              return self.fairseq_tokens_to_ids[token]
         lowerCAmelCase__          =			self.sp_model.PieceToId(SCREAMING_SNAKE_CASE__       )

         # Need to return unknown token if the SP model returned 0
         return spm_id + self.fairseq_offset if spm_id else self.unk_token_id


    def        a				(	self					:					Tuple       ,     SCREAMING_SNAKE_CASE__					:					Tuple       )				->	Any:
         if index in self.fairseq_ids_to_tokens:
              return self.fairseq_ids_to_tokens[index]
         return self.sp_model.IdToPiece(index - self.fairseq_offset       )


    def        a				(	self					:					Optional[Any]       ,     SCREAMING_SNAKE_CASE__					:					Optional[int]       )				->	Dict:
         lowerCAmelCase__          =			"".join(SCREAMING_SNAKE_CASE__       ).replace(SCREAMING_SNAKE_CASE__       ,     " "       ).strip()
         return out_string


    def        a				(	self					:					Union[str, Any]       ,     SCREAMING_SNAKE_CASE__					:					str       ,     SCREAMING_SNAKE_CASE__					:					Optional[str] = None       )				->	Tuple[str]:
         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,)






from __future__ import annotations

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



def 							_A       (						lowerCAmelCase_					: list[list[int]]       ,    lowerCAmelCase_					: list[int]       ,    lowerCAmelCase_					: list[int]       ,    lowerCAmelCase_					: int       ,    lowerCAmelCase_					: list[list[int]]       ,    ):
     """simple docstring"""

     lowerCAmelCase__          =			[
         [0 for col in range(len(grid[0]      )      )] for row in range(len(lowerCAmelCase_      )      )
     ]  # the reference grid
     lowerCAmelCase__          =			1
     lowerCAmelCase__          =			[
         [0 for col in range(len(grid[0]      )      )] for row in range(len(lowerCAmelCase_      )      )
     ]  # 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(lowerCAmelCase_      ) == 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(lowerCAmelCase_      )      ):  # to try out different valid actions
                         lowerCAmelCase__          =			x + DIRECTIONS[i][0]
                         lowerCAmelCase__          =			y + DIRECTIONS[i][1]
                         if xa >= 0 and xa < len(lowerCAmelCase_      ) 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(lowerCAmelCase_      )      ):
          path.append(invpath[len(lowerCAmelCase_      ) - 1 - i]      )
     return path, action


if __name__ == "__main__":
     UpperCamelCase								=					[
         [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],
     ]

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

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

     UpperCamelCase						,  UpperCamelCase								=					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])
