





from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
_UpperCAmelCase							:			Tuple        =							0

_UpperCAmelCase							:			List[str]        =							[
    [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],
]

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

_UpperCAmelCase							:			Any        =							tuple[int, int]

class   lowerCAmelCase				:
 def __init__( self    : Dict     ,	UpperCAmelCase    : int     ,	UpperCAmelCase    : int     ,	UpperCAmelCase    : int     ,	UpperCAmelCase    : int     ,	UpperCAmelCase    : int     ,	UpperCAmelCase    : Node | None     ,	)     ->      None:
     lowerCamelCase__       : Any   					=						pos_x
     lowerCamelCase__       : Dict   					=						pos_y
     lowerCamelCase__       : int   					=						(pos_y, pos_x)
     lowerCamelCase__       : List[Any]   					=						goal_x
     lowerCamelCase__       : List[str]   					=						goal_y
     lowerCamelCase__       : Any   					=						g_cost
     lowerCamelCase__       : Union[str, Any]   					=						parent
     lowerCamelCase__       : Optional[int]   					=						self.calculate_heuristic()
     lowerCamelCase__       : Optional[Any]   					=						self.g_cost + self.h_cost
 def 	A_      ( self    : Optional[Any]      )     ->      float:
     lowerCamelCase__       : Optional[int]   					=						self.pos_x - self.goal_x
     lowerCamelCase__       : Union[str, Any]   					=						self.pos_y - self.goal_y
     if HEURISTIC == 1:
         return abs(UpperCAmelCase      ) + abs(UpperCAmelCase      )
     else:
         return sqrt(dy**2 + dx**2      )







 def __lt__( self    : Dict     ,	UpperCAmelCase    : Node      )     ->      bool:
     return self.f_cost < other.f_cost


class   lowerCAmelCase				:
 def __init__( self    : Optional[Any]     ,	UpperCAmelCase    : TPosition     ,	UpperCAmelCase    : TPosition      )     ->      Tuple:
     lowerCamelCase__       : int   					=						Node(start[1]     ,	start[0]     ,	goal[1]     ,	goal[0]     ,	0     ,	UpperCAmelCase      )
     lowerCamelCase__       : List[str]   					=						Node(goal[1]     ,	goal[0]     ,	goal[1]     ,	goal[0]     ,	99999     ,	UpperCAmelCase      )

     lowerCamelCase__       : Any   					=						[self.start]
     lowerCamelCase__       : list[Node]   					=						[]

     lowerCamelCase__       : Dict   					=						False
 def 	A_      ( self    : Tuple      )     ->      list[TPosition]:
     while self.open_nodes:
         # Open Nodes are sorted using __lt__
         self.open_nodes.sort()
         lowerCamelCase__       : Optional[int]   					=						self.open_nodes.pop(0      )

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

         self.closed_nodes.append(UpperCAmelCase      )
         lowerCamelCase__       : int   					=						self.get_successors(UpperCAmelCase      )

         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(UpperCAmelCase      )
             else:
                 # retrieve the best current path
                 lowerCamelCase__       : Optional[Any]   					=						self.open_nodes.pop(self.open_nodes.index(UpperCAmelCase      )      )

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

     return [self.start.pos]
 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : Node      )     ->      list[Node]:
     lowerCamelCase__       : List[Any]   					=						[]
     for action in delta:
         lowerCamelCase__       : Union[str, Any]   					=						parent.pos_x + action[1]
         lowerCamelCase__       : List[Any]   					=						parent.pos_y + action[0]
         if not (0 <= pos_x <= len(grid[0]      ) - 1 and 0 <= pos_y <= len(UpperCAmelCase      ) - 1):
             continue

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

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







 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : Node | None      )     ->      list[TPosition]:
     lowerCamelCase__       : Dict   					=						node
     lowerCamelCase__       : Union[str, Any]   					=						[]
     while current_node is not None:
         path.append((current_node.pos_y, current_node.pos_x)      )
         lowerCamelCase__       : Optional[int]   					=						current_node.parent
     path.reverse()
     return path


class   lowerCAmelCase				:
 def __init__( self    : str     ,	UpperCAmelCase    : TPosition     ,	UpperCAmelCase    : TPosition      )     ->      None:
     lowerCamelCase__       : Optional[Any]   					=						AStar(UpperCAmelCase     ,	UpperCAmelCase      )
     lowerCamelCase__       : List[Any]   					=						AStar(UpperCAmelCase     ,	UpperCAmelCase      )
     lowerCamelCase__       : Optional[int]   					=						False
 def 	A_      ( self    : Optional[Any]      )     ->      list[TPosition]:
     while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
         self.fwd_astar.open_nodes.sort()
         self.bwd_astar.open_nodes.sort()
         lowerCamelCase__       : List[str]   					=						self.fwd_astar.open_nodes.pop(0      )
         lowerCamelCase__       : List[str]   					=						self.bwd_astar.open_nodes.pop(0      )

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

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

         lowerCamelCase__       : int   					=						current_bwd_node
         lowerCamelCase__       : Optional[int]   					=						current_fwd_node

         lowerCamelCase__       : Optional[int]   					=						{
             self.fwd_astar: self.fwd_astar.get_successors(UpperCAmelCase      ),
             self.bwd_astar: self.bwd_astar.get_successors(UpperCAmelCase      ),
         }

         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(UpperCAmelCase      )
                 else:
                     # retrieve the best current path
                     lowerCamelCase__       : List[str]   					=						astar.open_nodes.pop(
                         astar.open_nodes.index(UpperCAmelCase      )      )

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

     return [self.fwd_astar.start.pos]







 def 	A_      ( self    : Tuple     ,	UpperCAmelCase    : Node     ,	UpperCAmelCase    : Node      )     ->      list[TPosition]:
     lowerCamelCase__       : List[Any]   					=						self.fwd_astar.retrace_path(UpperCAmelCase      )
     lowerCamelCase__       : Dict   					=						self.bwd_astar.retrace_path(UpperCAmelCase      )
     bwd_path.pop()
     bwd_path.reverse()
     lowerCamelCase__       : str   					=						fwd_path + bwd_path
     return path


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

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

    _UpperCAmelCase							:			str        =							time.time()
    _UpperCAmelCase							:			List[str]        =							BidirectionalAStar(init, goal)
    _UpperCAmelCase							:			List[Any]        =							time.time() - bd_start_time
    print(F"""BidirectionalAStar execution time = {bd_end_time:f} seconds""")












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							:			List[str]        =							logging.get_logger(__name__)

_UpperCAmelCase							:			List[str]        =							{"""vocab_file""": """spiece.model"""}

_UpperCAmelCase							:			Tuple        =							{
    """vocab_file""": {
        """bert_for_seq_generation""": (
            """https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model"""
        ),
    }
}

_UpperCAmelCase							:			List[str]        =							{"""bert_for_seq_generation""": 5_12}

class   lowerCAmelCase				(   __UpperCamelCase     ):
 UpperCAmelCase__						=						VOCAB_FILES_NAMES
 UpperCAmelCase__						=						PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase__						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCAmelCase__						=						[]
 UpperCAmelCase__						=						["""input_ids""", """attention_mask"""]
 def __init__( self    : Union[str, Any]     ,	UpperCAmelCase    : List[Any]     ,	UpperCAmelCase    : int="<s>"     ,	UpperCAmelCase    : Any="</s>"     ,	UpperCAmelCase    : List[Any]="<unk>"     ,	UpperCAmelCase    : Any="<pad>"     ,	UpperCAmelCase    : Dict="<::::>"     ,	UpperCAmelCase    : Optional[Dict[str, Any]] = None     ,	**UpperCAmelCase    : Any     ,	)     ->      None:
     lowerCamelCase__       : str   					=						{} if sp_model_kwargs is None else sp_model_kwargs

     # Add extra_ids to the special token list
     super().__init__(
         bos_token=UpperCAmelCase     ,	eos_token=UpperCAmelCase     ,	unk_token=UpperCAmelCase     ,	pad_token=UpperCAmelCase     ,	sep_token=UpperCAmelCase     ,	sp_model_kwargs=self.sp_model_kwargs     ,	**UpperCAmelCase     ,	)

     lowerCamelCase__       : List[str]   					=						vocab_file

     lowerCamelCase__       : List[str]   					=						spm.SentencePieceProcessor(**self.sp_model_kwargs      )
     self.sp_model.Load(UpperCAmelCase      )
 @property
 def 	A_      ( self    : List[str]      )     ->      Optional[int]:
     return self.sp_model.get_piece_size()
 def 	A_      ( self    : Tuple      )     ->      Any:
     lowerCamelCase__       : Tuple   					=						{self.convert_ids_to_tokens(UpperCAmelCase      ): i for i in range(self.vocab_size      )}
     vocab.update(self.added_tokens_encoder      )
     return vocab
 def __getstate__( self    : Union[str, Any]      )     ->      Optional[Any]:
     lowerCamelCase__       : List[str]   					=						self.__dict__.copy()
     lowerCamelCase__       : List[Any]   					=						None
     return state
 def __setstate__( self    : Dict     ,	UpperCAmelCase    : Optional[int]      )     ->      List[Any]:
     lowerCamelCase__       : Optional[int]   					=						d

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

     lowerCamelCase__       : Optional[int]   					=						spm.SentencePieceProcessor(**self.sp_model_kwargs      )
     self.sp_model.Load(self.vocab_file      )
 def 	A_      ( self    : Dict     ,	UpperCAmelCase    : str      )     ->      List[str]:
     return self.sp_model.encode(UpperCAmelCase     ,	out_type=UpperCAmelCase      )
 def 	A_      ( self    : str     ,	UpperCAmelCase    : Tuple      )     ->      Union[str, Any]:
     return self.sp_model.piece_to_id(UpperCAmelCase      )
 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : Tuple      )     ->      Dict:
     lowerCamelCase__       : str   					=						self.sp_model.IdToPiece(UpperCAmelCase      )
     return token
 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : int      )     ->      Union[str, Any]:
     lowerCamelCase__       : str   					=						[]
     lowerCamelCase__       : List[str]   					=						''
     for token in tokens:
         # make sure that special tokens are not decoded using sentencepiece model
         if token in self.all_special_tokens:
             out_string += self.sp_model.decode(UpperCAmelCase      ) + token
             lowerCamelCase__       : Tuple   					=						[]
         else:
             current_sub_tokens.append(UpperCAmelCase      )
     out_string += self.sp_model.decode(UpperCAmelCase      )
     return out_string.strip()







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

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

     return (out_vocab_file,)





