





"""simple docstring"""




import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class        __UpperCamelCase				(						a__		,       unittest.TestCase						):
							lowerCamelCase   :					Dict      					=None
							lowerCamelCase   :					Dict      					=BloomTokenizerFast
							lowerCamelCase   :					int      					=BloomTokenizerFast
							lowerCamelCase   :					List[Any]      					=True
							lowerCamelCase   :					Optional[int]      					=False
							lowerCamelCase   :					Dict      					="""tokenizer_file"""
							lowerCamelCase   :					Union[str, Any]      					={"""bos_token""": """<s>""", """eos_token""": """</s>""", """unk_token""": """<unk>""", """pad_token""": """<pad>"""}






							def     __a   (   self      )	-> str:
								super().setUp()
								a      :		Dict	=				BloomTokenizerFast.from_pretrained("bigscience/tokenizer"      )
								tokenizer.save_pretrained(self.tmpdirname      )






							def     __a   (   self      ,					**lowerCAmelCase__      )	-> List[str]:
								kwargs.update(self.special_tokens_map      )
								return BloomTokenizerFast.from_pretrained(self.tmpdirname      ,					**lowerCAmelCase__      )






							def     __a   (   self      )	-> Any:
								a      :		Union[str, Any]	=				self.get_rust_tokenizer()

								a      :		Dict	=				["The quick brown fox</s>", "jumps over the lazy dog</s>"]
								a      :		Optional[int]	=				[[2175, 2_3714, 7_3173, 14_4252, 2], [77, 13_2619, 3478, 368, 10_9586, 3_5433, 2]]

								a      :		Optional[Any]	=				tokenizer.batch_encode_plus(lowerCAmelCase__      )["input_ids"]
								self.assertListEqual(lowerCAmelCase__      ,					lowerCAmelCase__      )

								a      :		List[str]	=				tokenizer.batch_decode(lowerCAmelCase__      )
								self.assertListEqual(lowerCAmelCase__      ,					lowerCAmelCase__      )






							def     __a   (   self      ,					lowerCAmelCase__=6      )	-> Optional[int]:
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""      ):
										a      :		Dict	=				self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__      ,					**lowerCAmelCase__      )
										# tokenizer_r.pad_token = None # Hotfixing padding = None
										# Simple input
										a      :		Optional[Any]	=				"This is a simple input"
										a      :		str	=				["This is a simple input 1", "This is a simple input 2"]
										a      :		int	=				("This is a simple input", "This is a pair")
										a      :		List[str]	=				[
										    ("This is a simple input 1", "This is a simple input 2"),
										    ("This is a simple pair 1", "This is a simple pair 2"),
										]

										# Simple input tests
										try:
											tokenizer_r.encode(lowerCAmelCase__      ,					max_length=lowerCAmelCase__      )
											tokenizer_r.encode_plus(lowerCAmelCase__      ,					max_length=lowerCAmelCase__      )

											tokenizer_r.batch_encode_plus(lowerCAmelCase__      ,					max_length=lowerCAmelCase__      )
											tokenizer_r.encode(lowerCAmelCase__      ,					max_length=lowerCAmelCase__      )
											tokenizer_r.batch_encode_plus(lowerCAmelCase__      ,					max_length=lowerCAmelCase__      )
										except ValueError:
											self.fail("Bloom Tokenizer should be able to deal with padding"      )

										a      :		Tuple	=				None  # Hotfixing padding = None
										self.assertRaises(lowerCAmelCase__      ,					tokenizer_r.encode      ,					lowerCAmelCase__      ,					max_length=lowerCAmelCase__      ,					padding="max_length"      )

										# Simple input
										self.assertRaises(lowerCAmelCase__      ,					tokenizer_r.encode_plus      ,					lowerCAmelCase__      ,					max_length=lowerCAmelCase__      ,					padding="max_length"      )

										# Simple input
										self.assertRaises(
										    lowerCAmelCase__      ,					tokenizer_r.batch_encode_plus      ,					lowerCAmelCase__      ,					max_length=lowerCAmelCase__      ,					padding="max_length"      ,					)

										# Pair input
										self.assertRaises(lowerCAmelCase__      ,					tokenizer_r.encode      ,					lowerCAmelCase__      ,					max_length=lowerCAmelCase__      ,					padding="max_length"      )

										# Pair input
										self.assertRaises(lowerCAmelCase__      ,					tokenizer_r.encode_plus      ,					lowerCAmelCase__      ,					max_length=lowerCAmelCase__      ,					padding="max_length"      )

										# Pair input
										self.assertRaises(
										    lowerCAmelCase__      ,					tokenizer_r.batch_encode_plus      ,					lowerCAmelCase__      ,					max_length=lowerCAmelCase__      ,					padding="max_length"      ,					)






							def     __a   (   self      )	-> Optional[int]:
								a      :		Optional[int]	=				self.get_rust_tokenizer()
								a      :		Tuple	=				load_dataset("xnli"      ,					"all_languages"      ,					split="test"      ,					streaming=lowerCAmelCase__      )

								a      :		List[Any]	=				next(iter(lowerCAmelCase__      )      )["premise"]  # pick up one data
								a      :		Union[str, Any]	=				list(sample_data.values()      )

								a      :		Tuple	=				list(map(tokenizer.encode      ,					lowerCAmelCase__      )      )
								a      :		Union[str, Any]	=				[tokenizer.decode(lowerCAmelCase__      ,					clean_up_tokenization_spaces=lowerCAmelCase__      ) for x in output_tokens]
								self.assertListEqual(lowerCAmelCase__      ,					lowerCAmelCase__      )






							def     __a   (   self      )	-> Union[str, Any]:
								# The test has to be overriden because BLOOM uses ALiBi positional embeddings that does not have
								# any sequence length constraints. This test of the parent class will fail since it relies on the
								# maximum sequence length of the positoonal embeddings.
								self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map      )      ,					1      )
								self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()      )[0]      )      ,					1      )









"""simple docstring"""




import heapq as hq
import math
from collections.abc import Iterator


class        __UpperCamelCase				:






							def __init__(   self      ,					lowerCAmelCase__      )	-> Optional[int]:
								a      :		List[str]	=				str(id_      )
								a      :		Optional[Any]	=				None
								a      :		Tuple	=				None
								a      :		str	=				[]
								a      :		Any	=				{}  # {vertex:distance}






							def __lt__(   self      ,					lowerCAmelCase__      )	-> Any:
								return self.key < other.key






							def __repr__(   self      )	-> Optional[Any]:
								return self.id






							def     __a   (   self      ,					lowerCAmelCase__      )	-> Any:
								self.neighbors.append(lowerCAmelCase__      )






							def     __a   (   self      ,					lowerCAmelCase__      ,					lowerCAmelCase__      )	-> Tuple:
								a      :		Optional[Any]	=				weight






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    int    ,       _lowercase						:    int    ,       _lowercase						:    int    ,       _lowercase						:    Union[str, Any]					) ->str:






	'''simple docstring'''






	graph[a - 1].add_neighbor(graph[b - 1]					)
	graph[b - 1].add_neighbor(graph[a - 1]					)
	# add the edges:
	graph[a - 1].add_edge(graph[b - 1]    ,       _lowercase					)
	graph[b - 1].add_edge(graph[a - 1]    ,       _lowercase					)






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    list    ,       _lowercase						:    Vertex					) ->list:






	'''simple docstring'''






	a      :		int	=				[]
	for u in graph:
		a      :		List[str]	=				math.inf
		a      :		int	=				None
	a      :		str	=				0
	a      :		Union[str, Any]	=				graph[:]
	while q:
		a      :		List[Any]	=				min(_lowercase					)
		q.remove(_lowercase					)
		for v in u.neighbors:
			if (v in q) and (u.edges[v.id] < v.key):
				a      :		List[Any]	=				u
				a      :		Optional[int]	=				u.edges[v.id]
	for i in range(1    ,       len(_lowercase					)					):
		a.append((int(graph[i].id					) + 1, int(graph[i].pi.id					) + 1)					)
	return a






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    list    ,       _lowercase						:    Vertex					) ->Iterator[tuple]:






	'''simple docstring'''






	for u in graph:
		a      :		str	=				math.inf
		a      :		Dict	=				None
	a      :		Dict	=				0

	a      :		List[Any]	=				list(_lowercase					)
	hq.heapify(_lowercase					)

	while h:
		a      :		Dict	=				hq.heappop(_lowercase					)
		for v in u.neighbors:
			if (v in h) and (u.edges[v.id] < v.key):
				a      :		Dict	=				u
				a      :		Optional[Any]	=				u.edges[v.id]
				hq.heapify(_lowercase					)

	for i in range(1    ,       len(_lowercase					)					):
		yield (int(graph[i].id					) + 1, int(graph[i].pi.id					) + 1)






def       _SCREAMING_SNAKE_CASE		(	) ->None:






	'''simple docstring'''








if __name__ == "__main__":
		import doctest

		doctest.testmod()


