



"""simple docstring"""






from heapq import heappop, heappush

import numpy as np


def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case					,__snake_case					,)						->   tuple[float | int, list[tuple[int, int]]]:
			__lowerCAmelCase						,	__lowerCAmelCase      :  Optional[int]												=       grid.shape
			__lowerCAmelCase      :  List[str]												=       [-1, 1, 0, 0]
			__lowerCAmelCase      :  Tuple												=       [0, 0, -1, 1]
			if allow_diagonal:
						dx += [-1, -1, 1, 1]
						dy += [-1, 1, -1, 1]

			__lowerCAmelCase						,	__lowerCAmelCase      :  List[Any]												=       [(0, source)], set()
			__lowerCAmelCase      :  int												=       np.full((rows, cols)					,np.inf	)
			__lowerCAmelCase      :  Optional[int]												=       0
			__lowerCAmelCase      :  Optional[Any]												=       np.empty((rows, cols)					,dtype=__snake_case	)
			__lowerCAmelCase      :  Union[str, Any]												=       None

			while queue:
						((__lowerCAmelCase)						,	(__lowerCAmelCase))      :  Optional[Any]												=       heappop(__snake_case	)
						if (x, y) in visited:
									continue
						visited.add((x, y)	)

						if (x, y) == destination:
									__lowerCAmelCase      :  Tuple												=       []
									while (x, y) != source:
												path.append((x, y)	)
												__lowerCAmelCase						,	__lowerCAmelCase      :  Tuple												=       predecessors[x, y]
									path.append(__snake_case	)  # add the source manually
									path.reverse()
									return matrix[destination], path

						for i in range(len(__snake_case	)	):
									__lowerCAmelCase						,	__lowerCAmelCase      :  Optional[Any]												=       x + dx[i], y + dy[i]
									if 0 <= nx < rows and 0 <= ny < cols:
												__lowerCAmelCase      :  Optional[int]												=       grid[nx][ny]
												if next_node == 1 and matrix[nx, ny] > dist + 1:
															heappush(__snake_case					,(dist + 1, (nx, ny))	)
															__lowerCAmelCase      :  str												=       dist + 1
															__lowerCAmelCase      :  Union[str, Any]												=       (x, y)

			return np.inf, []


if __name__ == "__main__":
	import doctest

	doctest.testmod()




"""simple docstring"""






import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 			A__   (  __SCREAMING_SNAKE_CASE  ,		unittest.TestCase							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE          =	FunnelTokenizer
	SCREAMING_SNAKE_CASE          =	FunnelTokenizerFast
	SCREAMING_SNAKE_CASE          =	True
	SCREAMING_SNAKE_CASE          =	True

	def 							_SCREAMING_SNAKE_CASE   (     self:		Tuple)				->       Optional[int]:

				"""simple docstring"""

				super().setUp()

				__lowerCAmelCase      :  str												=       [
				    "<unk>",
				    "<cls>",
				    "<sep>",
				    "want",
				    "##want",
				    "##ed",
				    "wa",
				    "un",
				    "runn",
				    "##ing",
				    ",",
				    "low",
				    "lowest",
				]
				__lowerCAmelCase      :  int												=       os.path.join(self.tmpdirname       ,			VOCAB_FILES_NAMES["vocab_file"])
				with open(self.vocab_file       ,			"w"       ,			encoding="utf-8") as vocab_writer:
							vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))

	def 							_SCREAMING_SNAKE_CASE   (     self:		Optional[Any]       ,			**_SCREAMING_SNAKE_CASE:		Union[str, Any])				->       int:

				"""simple docstring"""

				return FunnelTokenizer.from_pretrained(self.tmpdirname       ,			**_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE   (     self:		Any       ,			**_SCREAMING_SNAKE_CASE:		Any)				->       str:

				"""simple docstring"""

				return FunnelTokenizerFast.from_pretrained(self.tmpdirname       ,			**_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE   (     self:		Tuple       ,			_SCREAMING_SNAKE_CASE:		str)				->       Any:

				"""simple docstring"""

				__lowerCAmelCase      :  Union[str, Any]												=       "UNwant\u00E9d,running"
				__lowerCAmelCase      :  str												=       "unwanted, running"
				return input_text, output_text

	def 							_SCREAMING_SNAKE_CASE   (     self:		Optional[int])				->       List[str]:

				"""simple docstring"""

				__lowerCAmelCase      :  Any												=       self.tokenizer_class(self.vocab_file)

				__lowerCAmelCase      :  Any												=       tokenizer.tokenize("UNwant\u00E9d,running")
				self.assertListEqual(_SCREAMING_SNAKE_CASE       ,			["un", "##want", "##ed", ",", "runn", "##ing"])
				self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE)       ,			[7, 4, 5, 10, 8, 9])







	def 							_SCREAMING_SNAKE_CASE   (     self:		List[str])				->       List[str]:

				"""simple docstring"""

				__lowerCAmelCase      :  Optional[Any]												=       self.get_tokenizers(do_lower_case=_SCREAMING_SNAKE_CASE)
				for tokenizer in tokenizers:
							__lowerCAmelCase      :  List[str]												=       tokenizer("UNwant\u00E9d,running")
							__lowerCAmelCase      :  Optional[int]												=       len(inputs["input_ids"]) - 1
							self.assertListEqual(inputs["token_type_ids"]       ,			[2] + [0] * sentence_len)

							__lowerCAmelCase      :  List[str]												=       tokenizer("UNwant\u00E9d,running"       ,			"UNwant\u00E9d,running")
							self.assertListEqual(inputs["token_type_ids"]       ,			[2] + [0] * sentence_len + [1] * sentence_len)