'''simple docstring'''




import os
import unicodedata
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


__SCREAMING_SNAKE_CASE       :     Union[str, Any]     =  logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE       :     Tuple     =  {"""vocab_file""": """spiece.model"""}

__SCREAMING_SNAKE_CASE       :     int     =  {
    """vocab_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/spiece.model""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/spiece.model""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/spiece.model""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/spiece.model""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model""",
    }
}

__SCREAMING_SNAKE_CASE       :     int     =  {
    """albert-base-v1""": 512,
    """albert-large-v1""": 512,
    """albert-xlarge-v1""": 512,
    """albert-xxlarge-v1""": 512,
    """albert-base-v2""": 512,
    """albert-large-v2""": 512,
    """albert-xlarge-v2""": 512,
    """albert-xxlarge-v2""": 512,
}

__SCREAMING_SNAKE_CASE       :     Tuple     =  """▁"""

class 	lowerCamelCase_	(snake_case__    ):
      '''simple docstring'''

      __UpperCamelCase:  Tuple						=						VOCAB_FILES_NAMES
      __UpperCamelCase:  List[Any]						=						PRETRAINED_VOCAB_FILES_MAP
      __UpperCamelCase:  int						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




      def __init__(       self						:				Dict						,					A						:				Optional[int]						,					A						:				Any=True						,					A						:				List[Any]=True						,					A						:				Optional[Any]=False						,					A						:				Any="[CLS]"						,					A						:				List[str]="[SEP]"						,					A						:				str="<unk>"						,					A						:				Any="[SEP]"						,					A						:				int="<pad>"						,					A						:				Union[str, Any]="[CLS]"						,					A						:				List[str]="[MASK]"						,					A						:				Optional[Dict[str, Any]] = None						,					**A						:				int						,					):
             # Mask token behave like a normal word, i.e. include the space before it and
             # is included in the raw text, there should be a match in a non-normalized sentence.
             _UpperCAmelCase     :  Any							      =    (
                 AddedToken(A						,					lstrip=A						,					rstrip=A						,					normalized=A       )
                 if isinstance(A						,					A       )
                 else mask_token
             )

             _UpperCAmelCase     :  Any							      =    {} if sp_model_kwargs is None else sp_model_kwargs

             super().__init__(
                 do_lower_case=A						,					remove_space=A						,					keep_accents=A						,					bos_token=A						,					eos_token=A						,					unk_token=A						,					sep_token=A						,					pad_token=A						,					cls_token=A						,					mask_token=A						,					sp_model_kwargs=self.sp_model_kwargs						,					**A						,					)

             _UpperCAmelCase     :  List[Any]							      =    do_lower_case
             _UpperCAmelCase     :  str							      =    remove_space
             _UpperCAmelCase     :  Optional[Any]							      =    keep_accents
             _UpperCAmelCase     :  Optional[int]							      =    vocab_file

             _UpperCAmelCase     :  Optional[int]							      =    spm.SentencePieceProcessor(**self.sp_model_kwargs       )
             self.sp_model.Load(A       )




      @property
      def      _A	(       self						:				str       ):
             return len(self.sp_model       )




      def      _A	(       self						:				Any       ):
             _UpperCAmelCase     :  Any							      =    {self.convert_ids_to_tokens(A       ): i for i in range(self.vocab_size       )}
             vocab.update(self.added_tokens_encoder       )
             return vocab




      def __getstate__(       self						:				Optional[int]       ):
             _UpperCAmelCase     :  int							      =    self.__dict__.copy()
             _UpperCAmelCase     :  List[str]							      =    None
             return state




      def __setstate__(       self						:				List[str]						,					A						:				int       ):
             _UpperCAmelCase     :  Dict							      =    d

             # for backward compatibility
             if not hasattr(self						,					"sp_model_kwargs"       ):
                    _UpperCAmelCase     :  Optional[int]							      =    {}

             _UpperCAmelCase     :  str							      =    spm.SentencePieceProcessor(**self.sp_model_kwargs       )
             self.sp_model.Load(self.vocab_file       )




      def      _A	(       self						:				List[Any]						,					A						:				Optional[int]       ):
             if self.remove_space:
                    _UpperCAmelCase     :  int							      =    " ".join(inputs.strip().split()       )
             else:
                    _UpperCAmelCase     :  Tuple							      =    inputs
             _UpperCAmelCase     :  Optional[Any]							      =    outputs.replace("``"						,					"\""       ).replace("''"						,					"\""       )

             if not self.keep_accents:
                    _UpperCAmelCase     :  Union[str, Any]							      =    unicodedata.normalize("NFKD"						,					A       )
                    _UpperCAmelCase     :  List[Any]							      =    "".join([c for c in outputs if not unicodedata.combining(A       )]       )
             if self.do_lower_case:
                    _UpperCAmelCase     :  int							      =    outputs.lower()

             return outputs




      def      _A	(       self						:				str						,					A						:				str       ):
             _UpperCAmelCase     :  Union[str, Any]							      =    self.preprocess_text(A       )
             _UpperCAmelCase     :  Optional[int]							      =    self.sp_model.encode(A						,					out_type=A       )
             _UpperCAmelCase     :  int							      =    []
             for piece in pieces:
                    if len(A       ) > 1 and piece[-1] == str(","       ) and piece[-2].isdigit():
                           _UpperCAmelCase     :  Dict							      =    self.sp_model.EncodeAsPieces(piece[:-1].replace(A						,					""       )       )
                           if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                                  if len(cur_pieces[0]       ) == 1:
                                         _UpperCAmelCase     :  Optional[Any]							      =    cur_pieces[1:]
                                  else:
                                         _UpperCAmelCase     :  Dict							      =    cur_pieces[0][1:]
                           cur_pieces.append(piece[-1]       )
                           new_pieces.extend(A       )
                    else:
                           new_pieces.append(A       )

             return new_pieces




      def      _A	(       self						:				Union[str, Any]						,					A						:				Optional[Any]       ):
             return self.sp_model.PieceToId(A       )




      def      _A	(       self						:				int						,					A						:				Optional[Any]       ):
             return self.sp_model.IdToPiece(A       )




      def      _A	(       self						:				int						,					A						:				Tuple       ):
             _UpperCAmelCase     :  List[str]							      =    []
             _UpperCAmelCase     :  List[Any]							      =    ""
             _UpperCAmelCase     :  Tuple							      =    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(A       ) + token
                           _UpperCAmelCase     :  Optional[int]							      =    True
                           _UpperCAmelCase     :  List[str]							      =    []
                    else:
                           current_sub_tokens.append(A       )
                           _UpperCAmelCase     :  List[Any]							      =    False
             out_string += self.sp_model.decode(A       )
             return out_string.strip()




      def      _A	(       self						:				List[Any]						,					A						:				List[int]						,					A						:				Optional[List[int]] = None       ):
             _UpperCAmelCase     :  List[str]							      =    [self.sep_token_id]
             _UpperCAmelCase     :  Tuple							      =    [self.cls_token_id]
             if token_ids_a is None:
                    return cls + token_ids_a + sep
             return cls + token_ids_a + sep + token_ids_a + sep




      def      _A	(       self						:				Tuple						,					A						:				List[int]						,					A						:				Optional[List[int]] = None						,					A						:				bool = False       ):

             if already_has_special_tokens:
                    return super().get_special_tokens_mask(
                        token_ids_a=A						,					token_ids_a=A						,					already_has_special_tokens=A       )

             if token_ids_a is not None:
                    return [1] + ([0] * len(A       )) + [1] + ([0] * len(A       )) + [1]
             return [1] + ([0] * len(A       )) + [1]




      def      _A	(       self						:				int						,					A						:				List[int]						,					A						:				Optional[List[int]] = None       ):
             _UpperCAmelCase     :  Tuple							      =    [self.sep_token_id]
             _UpperCAmelCase     :  List[str]							      =    [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      _A	(       self						:				Union[str, Any]						,					A						:				str						,					A						:				Optional[str] = None       ):
             if not os.path.isdir(A       ):
                    logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
                    return
             _UpperCAmelCase     :  Union[str, Any]							      =    os.path.join(
                 A						,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]       )

             if os.path.abspath(self.vocab_file       ) != os.path.abspath(A       ) and os.path.isfile(self.vocab_file       ):
                    copyfile(self.vocab_file						,					A       )
             elif not os.path.isfile(self.vocab_file       ):
                    with open(A						,					"wb"       ) as fi:
                           _UpperCAmelCase     :  int							      =    self.sp_model.serialized_model_proto()
                           fi.write(A       )

             return (out_vocab_file,)







from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
snake_case_ : str    		=       0

snake_case_ : Union[str, Any]    		=       [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

snake_case_ : str    		=       [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

snake_case_ : List[Any]    		=       tuple[int, int]







class __snake_case			:







   def __init__(      self		:						Any					,						_snake_case		:						int					,						_snake_case		:						int					,						_snake_case		:						int					,						_snake_case		:						int					,						_snake_case		:						int					,						_snake_case		:						Node | None					,						):

        """simple docstring"""


        UpperCAmelCase_          =							pos_x
        UpperCAmelCase_          =							pos_y
        UpperCAmelCase_          =							(pos_y, pos_x)
        UpperCAmelCase_          =							goal_x
        UpperCAmelCase_          =							goal_y
        UpperCAmelCase_          =							g_cost
        UpperCAmelCase_          =							parent
        UpperCAmelCase_          =							self.calculate_heuristic()
        UpperCAmelCase_          =							self.g_cost + self.h_cost







   def lowerCamelCase						(      self		:						List[str]):

        """simple docstring"""


        UpperCAmelCase_          =							self.pos_x - self.goal_x
        UpperCAmelCase_          =							self.pos_y - self.goal_y
        if HEURISTIC == 1:
             return abs(_snake_case) + abs(_snake_case)
        else:
             return sqrt(dy**2 + dx**2)







   def __lt__(      self		:						Union[str, Any]					,						_snake_case		:						Node):

        """simple docstring"""


        return self.f_cost < other.f_cost







class __snake_case			:







   def __init__(      self		:						str					,						_snake_case		:						TPosition					,						_snake_case		:						TPosition):

        """simple docstring"""


        UpperCAmelCase_          =							Node(start[1]					,						start[0]					,						goal[1]					,						goal[0]					,						0					,						_snake_case)
        UpperCAmelCase_          =							Node(goal[1]					,						goal[0]					,						goal[1]					,						goal[0]					,						99999					,						_snake_case)

        UpperCAmelCase_          =							[self.start]
        UpperCAmelCase_          =							[]

        UpperCAmelCase_          =							False







   def lowerCamelCase						(      self		:						Optional[int]):

        """simple docstring"""


        while self.open_nodes:
             # Open Nodes are sorted using __lt__
             self.open_nodes.sort()
             UpperCAmelCase_          =							self.open_nodes.pop(0)

             if current_node.pos == self.target.pos:
                  return self.retrace_path(_snake_case)

             self.closed_nodes.append(_snake_case)
             UpperCAmelCase_          =							self.get_successors(_snake_case)

             for child_node in successors:
                  if child_node in self.closed_nodes:
                       continue

                  if child_node not in self.open_nodes:
                       self.open_nodes.append(_snake_case)
                  else:
                       # retrieve the best current path
                       UpperCAmelCase_          =							self.open_nodes.pop(self.open_nodes.index(_snake_case))

                       if child_node.g_cost < better_node.g_cost:
                            self.open_nodes.append(_snake_case)
                       else:
                            self.open_nodes.append(_snake_case)

        return [self.start.pos]







   def lowerCamelCase						(      self		:						Tuple					,						_snake_case		:						Node):

        """simple docstring"""


        UpperCAmelCase_          =							[]
        for action in delta:
             UpperCAmelCase_          =							parent.pos_x + action[1]
             UpperCAmelCase_          =							parent.pos_y + action[0]
             if not (0 <= pos_x <= len(grid[0]) - 1 and 0 <= pos_y <= len(_snake_case) - 1):
                  continue

             if grid[pos_y][pos_x] != 0:
                  continue

             successors.append(
                 Node(
                     _snake_case					,						_snake_case					,						self.target.pos_y					,						self.target.pos_x					,						parent.g_cost + 1					,						_snake_case					,						))
        return successors







   def lowerCamelCase						(      self		:						Any					,						_snake_case		:						Node | None):

        """simple docstring"""


        UpperCAmelCase_          =							node
        UpperCAmelCase_          =							[]
        while current_node is not None:
             path.append((current_node.pos_y, current_node.pos_x))
             UpperCAmelCase_          =							current_node.parent
        path.reverse()
        return path







class __snake_case			:







   def __init__(      self		:						Any					,						_snake_case		:						TPosition					,						_snake_case		:						TPosition):

        """simple docstring"""


        UpperCAmelCase_          =							AStar(_snake_case					,						_snake_case)
        UpperCAmelCase_          =							AStar(_snake_case					,						_snake_case)
        UpperCAmelCase_          =							False







   def lowerCamelCase						(      self		:						List[Any]):

        """simple docstring"""


        while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
             self.fwd_astar.open_nodes.sort()
             self.bwd_astar.open_nodes.sort()
             UpperCAmelCase_          =							self.fwd_astar.open_nodes.pop(0)
             UpperCAmelCase_          =							self.bwd_astar.open_nodes.pop(0)

             if current_bwd_node.pos == current_fwd_node.pos:
                  return self.retrace_bidirectional_path(
                      _snake_case					,						_snake_case)

             self.fwd_astar.closed_nodes.append(_snake_case)
             self.bwd_astar.closed_nodes.append(_snake_case)

             UpperCAmelCase_          =							current_bwd_node
             UpperCAmelCase_          =							current_fwd_node

             UpperCAmelCase_          =							{
                 self.fwd_astar: self.fwd_astar.get_successors(_snake_case),
                 self.bwd_astar: self.bwd_astar.get_successors(_snake_case),
             }

             for astar in [self.fwd_astar, self.bwd_astar]:
                  for child_node in successors[astar]:
                       if child_node in astar.closed_nodes:
                            continue

                       if child_node not in astar.open_nodes:
                            astar.open_nodes.append(_snake_case)
                       else:
                            # retrieve the best current path
                            UpperCAmelCase_          =							astar.open_nodes.pop(
                                astar.open_nodes.index(_snake_case))

                            if child_node.g_cost < better_node.g_cost:
                                 astar.open_nodes.append(_snake_case)
                            else:
                                 astar.open_nodes.append(_snake_case)

        return [self.fwd_astar.start.pos]







   def lowerCamelCase						(      self		:						int					,						_snake_case		:						Node					,						_snake_case		:						Node):

        """simple docstring"""


        UpperCAmelCase_          =							self.fwd_astar.retrace_path(_snake_case)
        UpperCAmelCase_          =							self.bwd_astar.retrace_path(_snake_case)
        bwd_path.pop()
        bwd_path.reverse()
        UpperCAmelCase_          =							fwd_path + bwd_path
        return path


if __name__ == "__main__":
    # all coordinates are given in format [y,x]
    snake_case_ : Any    		=       (0, 0)
    snake_case_ : Union[str, Any]    		=       (len(grid) - 1, len(grid[0]) - 1)
    for elem in grid:
        print(elem)

    snake_case_ : str    		=       time.time()
    snake_case_ : List[str]    		=       AStar(init, goal)
    snake_case_ : Optional[int]    		=       a_star.search()
    snake_case_ : Optional[Any]    		=       time.time() - start_time
    print(f"AStar execution time = {end_time:f} seconds")

    snake_case_ : int    		=       time.time()
    snake_case_ : Dict    		=       BidirectionalAStar(init, goal)
    snake_case_ : str    		=       time.time() - bd_start_time
    print(f"BidirectionalAStar execution time = {bd_end_time:f} seconds")






