



'''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
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin





class _UpperCamelCase		(     A      ,       unittest.TestCase		):





				'''simple docstring'''





				lowerCAmelCase__					    =    BlenderbotSmallTokenizer
				lowerCAmelCase__					    =    False

				def 				__lowerCamelCase     (							self  :  str):







											'''simple docstring'''

											super().setUp()

											__lowercase       	=['__start__', 'adapt', 'act', 'ap@@', 'te', '__end__', '__unk__']
											__lowercase       	=dict(zip(_lowerCAmelCase  ,       range(len(_lowerCAmelCase))))

											__lowercase       	=['#version: 0.2', 'a p', 't e</w>', 'ap t</w>', 'a d', 'ad apt</w>', 'a c', 'ac t</w>', '']
											__lowercase       	={'unk_token': '__unk__', 'bos_token': '__start__', 'eos_token': '__end__'}

											__lowercase       	=os.path.join(self.tmpdirname  ,       VOCAB_FILES_NAMES['vocab_file'])
											__lowercase       	=os.path.join(self.tmpdirname  ,       VOCAB_FILES_NAMES['merges_file'])
											with open(self.vocab_file  ,       'w'  ,       encoding='utf-8') as fp:
																		fp.write(json.dumps(_lowerCAmelCase) + '\n')
											with open(self.merges_file  ,       'w'  ,       encoding='utf-8') as fp:
																		fp.write('\n'.join(_lowerCAmelCase))

				def 				__lowerCamelCase     (							self  :  int  ,       **_lowerCAmelCase  :  Tuple):







											'''simple docstring'''

											kwargs.update(self.special_tokens_map)
											return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname  ,       **_lowerCAmelCase)

				def 				__lowerCamelCase     (							self  :  Tuple  ,       _lowerCAmelCase  :  Any):







											'''simple docstring'''

											__lowercase       	='adapt act apte'
											__lowercase       	='adapt act apte'
											return input_text, output_text

				def 				__lowerCamelCase     (							self  :  Union[str, Any]):







											'''simple docstring'''

											__lowercase       	=BlenderbotSmallTokenizer(self.vocab_file  ,       self.merges_file  ,       **self.special_tokens_map)
											__lowercase       	='adapt act apte'
											__lowercase       	=['adapt', 'act', 'ap@@', 'te']
											__lowercase       	=tokenizer.tokenize(_lowerCAmelCase)
											self.assertListEqual(_lowerCAmelCase  ,       _lowerCAmelCase)

											__lowercase       	=[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

											__lowercase       	=[0, 1, 2, 3, 4, 5]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase)  ,       _lowerCAmelCase)

				def 				__lowerCamelCase     (							self  :  Union[str, Any]):







											'''simple docstring'''

											__lowercase       	=BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M')
											assert tok('sam').input_ids == [1_3_8_4]
											__lowercase       	='I am a small frog.'
											__lowercase       	=tok([src_text]  ,       padding=_lowerCAmelCase  ,       truncation=_lowerCAmelCase)['input_ids']
											__lowercase       	=tok.batch_decode(_lowerCAmelCase  ,       skip_special_tokens=_lowerCAmelCase  ,       clean_up_tokenization_spaces=_lowerCAmelCase)[0]
											assert src_text != decoded  # I wish it did!
											assert decoded == "i am a small frog ."

				def 				__lowerCamelCase     (							self  :  str):







											'''simple docstring'''

											__lowercase       	=BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M')
											__lowercase       	='I am a small frog .'
											__lowercase       	='.'
											__lowercase       	=tok(_lowerCAmelCase)['input_ids']
											__lowercase       	=tok(_lowerCAmelCase)['input_ids']

											assert encoded[-1] == encoded_dot[0]



