


'''simple docstring'''






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


lowercase							=logging.get_logger(__name__)

lowercase							='▁'

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

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

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






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										=VOCAB_FILES_NAMES
       UpperCAmelCase										=PRETRAINED_VOCAB_FILES_MAP
       UpperCAmelCase										=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCAmelCase										=["input_ids", "attention_mask"]






       def __init__(      self  ,							snake_case  ,							snake_case="<s>"  ,							snake_case="</s>"  ,							snake_case="</s>"  ,							snake_case="<s>"  ,							snake_case="<unk>"  ,							snake_case="<pad>"  ,							snake_case = None  ,							**snake_case  ,							)						->  None:




          '''simple docstring'''
          _UpperCAmelCase       :       Optional[int]							   ={} if sp_model_kwargs is None else sp_model_kwargs

          # Compatibility with the original tokenizer
          _UpperCAmelCase       :       List[Any]							   =7
          _UpperCAmelCase       :       Optional[int]							   =[f"<madeupword{i}>" for i in range(self.num_madeup_words)]

          _UpperCAmelCase       :       Optional[Any]							   =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=snake_case  ,							eos_token=snake_case  ,							unk_token=snake_case  ,							sep_token=snake_case  ,							cls_token=snake_case  ,							pad_token=snake_case  ,							sp_model_kwargs=self.sp_model_kwargs  ,							**snake_case  ,							)

          _UpperCAmelCase       :       str							   =spm.SentencePieceProcessor(**self.sp_model_kwargs)
          self.sp_model.Load(str(snake_case))
          _UpperCAmelCase       :       Dict							   =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
          _UpperCAmelCase       :       Dict							   =1

          # Mimic fairseq token-to-id alignment for the first 4 token
          _UpperCAmelCase       :       Union[str, Any]							   ={'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

          _UpperCAmelCase       :       Dict							   =len(self.sp_model)
          _UpperCAmelCase       :       int							   ={f"<madeupword{i}>": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words)}
          self.fairseq_tokens_to_ids.update(snake_case)

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






       def __getstate__(      self)						->  Optional[int]:




          '''simple docstring'''
          _UpperCAmelCase       :       Optional[Any]							   =self.__dict__.copy()
          _UpperCAmelCase       :       Optional[Any]							   =None
          _UpperCAmelCase       :       List[str]							   =self.sp_model.serialized_model_proto()
          return state






       def __setstate__(      self  ,							snake_case)						->  Any:




          '''simple docstring'''
          _UpperCAmelCase       :       Optional[Any]							   =d

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

          _UpperCAmelCase       :       Optional[Any]							   =spm.SentencePieceProcessor(**self.sp_model_kwargs)
          self.sp_model.LoadFromSerializedProto(self.sp_model_proto)






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  List[int]:




          '''simple docstring'''

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






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None  ,							snake_case = False)						->  List[int]:




          '''simple docstring'''

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

          if token_ids_a is None:
             return [1] + ([0] * len(snake_case))
          return [1] + ([0] * len(snake_case)) + [1, 1] + ([0] * len(snake_case))






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  List[int]:




          '''simple docstring'''
          _UpperCAmelCase       :       List[Any]							   =[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       lowerCAmelCase		(      self)						->  int:




          '''simple docstring'''
          return len(self.sp_model) + self.fairseq_offset + self.num_madeup_words






       def       lowerCAmelCase		(      self)						->  Tuple:




          '''simple docstring'''
          _UpperCAmelCase       :       Dict							   ={self.convert_ids_to_tokens(snake_case): i for i in range(self.vocab_size)}
          vocab.update(self.added_tokens_encoder)
          return vocab






       def       lowerCAmelCase		(      self  ,							snake_case)						->  List[str]:




          '''simple docstring'''
          return self.sp_model.encode(snake_case  ,							out_type=snake_case)






       def       lowerCAmelCase		(      self  ,							snake_case)						->  Union[str, Any]:




          '''simple docstring'''
          if token in self.fairseq_tokens_to_ids:
             return self.fairseq_tokens_to_ids[token]
          _UpperCAmelCase       :       int							   =self.sp_model.PieceToId(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       lowerCAmelCase		(      self  ,							snake_case)						->  str:




          '''simple docstring'''
          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       lowerCAmelCase		(      self  ,							snake_case)						->  Any:




          '''simple docstring'''
          _UpperCAmelCase       :       Dict							   =''.join(snake_case).replace(snake_case  ,							' ').strip()
          return out_string






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  Tuple[str]:




          '''simple docstring'''
          if not os.path.isdir(snake_case):
             logger.error(f"Vocabulary path ({save_directory}) should be a directory")
             return
          _UpperCAmelCase       :       Optional[int]							   =os.path.join(
              snake_case  ,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

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

          return (out_vocab_file,)



'''simple docstring'''






import numpy as np






class  __magic_name__							:






       def __init__(      self)						->  Optional[Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       List[str]							   =(0, 0)
          _UpperCAmelCase       :       Any							   =None
          _UpperCAmelCase       :       List[str]							   =0
          _UpperCAmelCase       :       Dict							   =0
          _UpperCAmelCase       :       Dict							   =0






       def __eq__(      self  ,							snake_case)						->  Dict:




          '''simple docstring'''
          return self.position == cell.position






       def       lowerCAmelCase		(      self)						->  Optional[int]:




          '''simple docstring'''
          print(self.position)






class  __magic_name__							:






       def __init__(      self  ,							snake_case=(5, 5))						->  Optional[int]:




          '''simple docstring'''
          _UpperCAmelCase       :       List[str]							   =np.zeros(snake_case)
          _UpperCAmelCase       :       Optional[Any]							   =world_size[0]
          _UpperCAmelCase       :       Any							   =world_size[1]






       def       lowerCAmelCase		(      self)						->  Tuple:




          '''simple docstring'''
          print(self.w)






       def       lowerCAmelCase		(      self  ,							snake_case)						->  Any:




          '''simple docstring'''
          _UpperCAmelCase       :       str							   =[
              (-1, -1),
              (-1, 0),
              (-1, 1),
              (0, -1),
              (0, 1),
              (1, -1),
              (1, 0),
              (1, 1),
          ]
          _UpperCAmelCase       :       int							   =cell.position[0]
          _UpperCAmelCase       :       Optional[Any]							   =cell.position[1]
          _UpperCAmelCase       :       Dict							   =[]
          for n in neughbour_cord:
             _UpperCAmelCase       :       List[str]							   =current_x + n[0]
             _UpperCAmelCase       :       int							   =current_y + n[1]
             if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
                _UpperCAmelCase       :       List[Any]							   =Cell()
                _UpperCAmelCase       :       Dict							   =(x, y)
                _UpperCAmelCase       :       Any							   =cell
                neighbours.append(snake_case)
          return neighbours






def lowerCamelCase__      (						__lowerCamelCase	:							List[str]	,   __lowerCamelCase	:							str	,   __lowerCamelCase	:							int							):







   '''simple docstring'''




   _UpperCAmelCase       :       List[Any]							   =[]
   _UpperCAmelCase       :       Union[str, Any]							   =[]
   _open.append(__lowerCamelCase							)

   while _open:
      _UpperCAmelCase       :       List[str]							   =np.argmin([n.f for n in _open]							)
      _UpperCAmelCase       :       Optional[int]							   =_open[min_f]
      _closed.append(_open.pop(__lowerCamelCase							)							)
      if current == goal:
         break
      for n in world.get_neigbours(__lowerCamelCase							):
         for c in _closed:
            if c == n:
               continue
         _UpperCAmelCase       :       Tuple							   =current.g + 1
         _UpperCAmelCase   ,	_UpperCAmelCase       :       Any							   =n.position
         _UpperCAmelCase   ,	_UpperCAmelCase       :       List[str]							   =goal.position
         _UpperCAmelCase       :       Optional[int]							   =(ya - ya) ** 2 + (xa - xa) ** 2
         _UpperCAmelCase       :       Optional[Any]							   =n.h + n.g

         for c in _open:
            if c == n and c.f < n.f:
               continue
         _open.append(__lowerCamelCase							)
   _UpperCAmelCase       :       str							   =[]
   while current.parent is not None:
      path.append(current.position							)
      _UpperCAmelCase       :       Any							   =current.parent
   path.append(current.position							)
   return path[::-1]


if __name__ == "__main__":
 lowercase							=Gridworld()
 # Start position and goal
 lowercase							=Cell()
 lowercase							=(0, 0)
 lowercase							=Cell()
 lowercase							=(4, 4)
 print(F"""path from {start.position} to {goal.position}""")
 lowercase							=astar(world, start, goal)
 #   Just for visual reasons.
 for i in s:
  lowercase							=1
 print(world.w)

