



'''simple docstring'''



import numpy as np





class _UpperCamelCase		:





				'''simple docstring'''





				def __init__(							self  :  Dict):







											'''simple docstring'''

											__lowercase       	=(0, 0)
											__lowercase       	=None
											__lowercase       	=0
											__lowercase       	=0
											__lowercase       	=0

				def __eq__(							self  :  List[str]  ,       _lowerCAmelCase  :  Optional[Any]):







											'''simple docstring'''

											return self.position == cell.position

				def 				__lowerCamelCase     (							self  :  Dict):







											'''simple docstring'''

											print(self.position)





class _UpperCamelCase		:





				'''simple docstring'''





				def __init__(							self  :  Any  ,       _lowerCAmelCase  :  List[str]=(5, 5)):







											'''simple docstring'''

											__lowercase       	=np.zeros(_lowerCAmelCase)
											__lowercase       	=world_size[0]
											__lowercase       	=world_size[1]

				def 				__lowerCamelCase     (							self  :  Optional[int]):







											'''simple docstring'''

											print(self.w)

				def 				__lowerCamelCase     (							self  :  int  ,       _lowerCAmelCase  :  List[str]):







											'''simple docstring'''

											__lowercase       	=[
											    (-1, -1),
											    (-1, 0),
											    (-1, 1),
											    (0, -1),
											    (0, 1),
											    (1, -1),
											    (1, 0),
											    (1, 1),
											]
											__lowercase       	=cell.position[0]
											__lowercase       	=cell.position[1]
											__lowercase       	=[]
											for n in neughbour_cord:
																		__lowercase       	=current_x + n[0]
																		__lowercase       	=current_y + n[1]
																		if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																									__lowercase       	=Cell()
																									__lowercase       	=(x, y)
																									__lowercase       	=cell
																									neighbours.append(_lowerCAmelCase)
											return neighbours






def   _A       (   _lowerCAmelCase  ,   _lowerCAmelCase  ,   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=[]
							__lowercase       	=[]
							_open.append(_lowerCAmelCase					)

							while _open:
														__lowercase       	=np.argmin([n.f for n in _open]					)
														__lowercase       	=_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
																					__lowercase       	=current.g + 1
																					__lowercase	,				__lowercase       	=n.position
																					__lowercase	,				__lowercase       	=goal.position
																					__lowercase       	=(ya - ya) ** 2 + (xa - xa) ** 2
																					__lowercase       	=n.h + n.g

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


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








'''simple docstring'''



import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


lowerCamelCase	 =       logging.get_logger(__name__)


lowerCamelCase	 =       {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

# See all BART models at https://huggingface.co/models?filter=bart
lowerCamelCase	 =       {
    """vocab_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/vocab.json""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/vocab.json""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/merges.txt""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/merges.txt""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json""",
    },
}

lowerCamelCase	 =       {
    """facebook/bart-base""": 1024,
    """facebook/bart-large""": 1024,
    """facebook/bart-large-mnli""": 1024,
    """facebook/bart-large-cnn""": 1024,
    """facebook/bart-large-xsum""": 1024,
    """yjernite/bart_eli5""": 1024,
}





class _UpperCamelCase		(     A		):





				'''simple docstring'''





				lowerCAmelCase__					    =    VOCAB_FILES_NAMES
				lowerCAmelCase__					    =    PRETRAINED_VOCAB_FILES_MAP
				lowerCAmelCase__					    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCAmelCase__					    =    ["""input_ids""", """attention_mask"""]
				lowerCAmelCase__					    =    BartTokenizer

				def __init__(							self  :  Optional[int]  ,       _lowerCAmelCase  :  Any=None  ,       _lowerCAmelCase  :  Tuple=None  ,       _lowerCAmelCase  :  Optional[int]=None  ,       _lowerCAmelCase  :  str="replace"  ,       _lowerCAmelCase  :  List[Any]="<s>"  ,       _lowerCAmelCase  :  int="</s>"  ,       _lowerCAmelCase  :  Dict="</s>"  ,       _lowerCAmelCase  :  Optional[int]="<s>"  ,       _lowerCAmelCase  :  str="<unk>"  ,       _lowerCAmelCase  :  List[str]="<pad>"  ,       _lowerCAmelCase  :  Dict="<mask>"  ,       _lowerCAmelCase  :  Tuple=False  ,       _lowerCAmelCase  :  str=True  ,       **_lowerCAmelCase  :  Tuple  ,       ):







											'''simple docstring'''

											super().__init__(
											    _lowerCAmelCase  ,       _lowerCAmelCase  ,       tokenizer_file=_lowerCAmelCase  ,       errors=_lowerCAmelCase  ,       bos_token=_lowerCAmelCase  ,       eos_token=_lowerCAmelCase  ,       sep_token=_lowerCAmelCase  ,       cls_token=_lowerCAmelCase  ,       unk_token=_lowerCAmelCase  ,       pad_token=_lowerCAmelCase  ,       mask_token=_lowerCAmelCase  ,       add_prefix_space=_lowerCAmelCase  ,       trim_offsets=_lowerCAmelCase  ,       **_lowerCAmelCase  ,       )

											__lowercase       	=json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
											if pre_tok_state.get('add_prefix_space'  ,       _lowerCAmelCase) != add_prefix_space:
																		__lowercase       	=getattr(_lowerCAmelCase  ,       pre_tok_state.pop('type'))
																		__lowercase       	=add_prefix_space
																		__lowercase       	=pre_tok_class(**_lowerCAmelCase)

											__lowercase       	=add_prefix_space

											# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
											__lowercase       	='post_processor'
											__lowercase       	=getattr(self.backend_tokenizer  ,       _lowerCAmelCase  ,       _lowerCAmelCase)
											if tokenizer_component_instance:
																		__lowercase       	=json.loads(tokenizer_component_instance.__getstate__())

																		# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
																		if "sep" in state:
																									__lowercase       	=tuple(state['sep'])
																		if "cls" in state:
																									__lowercase       	=tuple(state['cls'])

																		__lowercase       	=False

																		if state.get('add_prefix_space'  ,       _lowerCAmelCase) != add_prefix_space:
																									__lowercase       	=add_prefix_space
																									__lowercase       	=True

																		if state.get('trim_offsets'  ,       _lowerCAmelCase) != trim_offsets:
																									__lowercase       	=trim_offsets
																									__lowercase       	=True

																		if changes_to_apply:
																									__lowercase       	=getattr(_lowerCAmelCase  ,       state.pop('type'))
																									__lowercase       	=component_class(**_lowerCAmelCase)
																									setattr(self.backend_tokenizer  ,       _lowerCAmelCase  ,       _lowerCAmelCase)

				@property
				def 				__lowerCamelCase     (							self  :  List[str]):







											'''simple docstring'''

											if self._mask_token is None:
																		if self.verbose:
																									logger.error('Using mask_token, but it is not set yet.')
																		return None
											return str(self._mask_token)

				@mask_token.setter
				def 				__lowerCamelCase     (							self  :  Union[str, Any]  ,       _lowerCAmelCase  :  Optional[int]):







											'''simple docstring'''

											__lowercase       	=AddedToken(_lowerCAmelCase  ,       lstrip=_lowerCAmelCase  ,       rstrip=_lowerCAmelCase) if isinstance(_lowerCAmelCase  ,       _lowerCAmelCase) else value
											__lowercase       	=value

				def 				__lowerCamelCase     (							self  :  List[Any]  ,       *_lowerCAmelCase  :  int  ,       **_lowerCAmelCase  :  str):







											'''simple docstring'''

											__lowercase       	=kwargs.get('is_split_into_words'  ,       _lowerCAmelCase)

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.')

											return super()._batch_encode_plus(*_lowerCAmelCase  ,       **_lowerCAmelCase)

				def 				__lowerCamelCase     (							self  :  List[Any]  ,       *_lowerCAmelCase  :  List[str]  ,       **_lowerCAmelCase  :  Tuple):







											'''simple docstring'''

											__lowercase       	=kwargs.get('is_split_into_words'  ,       _lowerCAmelCase)

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.')

											return super()._encode_plus(*_lowerCAmelCase  ,       **_lowerCAmelCase)

				def 				__lowerCamelCase     (							self  :  int  ,       _lowerCAmelCase  :  str  ,       _lowerCAmelCase  :  Optional[str] = None):







											'''simple docstring'''

											__lowercase       	=self._tokenizer.model.save(_lowerCAmelCase  ,       name=_lowerCAmelCase)
											return tuple(_lowerCAmelCase)

				def 				__lowerCamelCase     (							self  :  str  ,       _lowerCAmelCase  :  Union[str, Any]  ,       _lowerCAmelCase  :  List[str]=None):







											'''simple docstring'''

											__lowercase       	=[self.bos_token_id] + token_ids_a + [self.eos_token_id]
											if token_ids_a is None:
																		return output

											return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]

				def 				__lowerCamelCase     (							self  :  List[str]  ,       _lowerCAmelCase  :  List[int]  ,       _lowerCAmelCase  :  Optional[List[int]] = None):







											'''simple docstring'''

											__lowercase       	=[self.sep_token_id]
											__lowercase       	=[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]



