



"""simple docstring"""





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



class    _lowerCAmelCase    :





		"""simple docstring"""






		def __init__(					self							,    _lowercase   ) ->						Tuple:







								'''simple docstring'''

								snake_case_   : Any						=			str(id_   )
								snake_case_   : Optional[int]						=			None
								snake_case_   : Dict						=			None
								snake_case_   : Tuple						=			[]
								snake_case_   : int						=			{}  # {vertex:distance}





		def __lt__(					self							,    _lowercase   ) ->						str:







								'''simple docstring'''

								return self.key < other.key





		def __repr__(					self   ) ->						int:







								'''simple docstring'''

								return self.id





		def    UpperCAmelCase__							(					self							,    _lowercase   ) ->						Union[str, Any]:







								'''simple docstring'''

								self.neighbors.append(_lowercase   )





		def    UpperCAmelCase__							(					self							,    _lowercase							,    _lowercase   ) ->						str:







								'''simple docstring'''

								snake_case_   : Dict						=			weight




def 	__lowerCAmelCase						(		__UpperCamelCase      :			Union[str, Any]					, __UpperCamelCase      :			Union[str, Any]					, __UpperCamelCase      :			Tuple					, __UpperCamelCase      :			Union[str, Any]    ):


						'''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]					, __UpperCamelCase    )
						graph[b - 1].add_edge(graph[a - 1]					, __UpperCamelCase    )
def 	__lowerCAmelCase						(		__UpperCamelCase      :			list					, __UpperCamelCase      :			Vertex    ):


						'''simple docstring'''






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


						'''simple docstring'''






						for u in graph:
												snake_case_   : Optional[Any]						=			math.inf
												snake_case_   : str						=			None
						snake_case_   : Optional[int]						=			0

						snake_case_   : int						=			list(__UpperCamelCase    )
						hq.heapify(__UpperCamelCase    )

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

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


						'''simple docstring'''








if __name__ == "__main__":
					import doctest

					doctest.testmod()






"""simple docstring"""





import unittest

import numpy as np

from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
					import jax.numpy as jnp

					from transformers.models.roformer.modeling_flax_roformer import (
					    FlaxRoFormerForMaskedLM,
					    FlaxRoFormerForMultipleChoice,
					    FlaxRoFormerForQuestionAnswering,
					    FlaxRoFormerForSequenceClassification,
					    FlaxRoFormerForTokenClassification,
					    FlaxRoFormerModel,
					)



class    _lowerCAmelCase    (				unittest.TestCase		):





		"""simple docstring"""






		def __init__(					self							,    _lowercase							,    _lowercase=1_3							,    _lowercase=7							,    _lowercase=True							,    _lowercase=True							,    _lowercase=True							,    _lowercase=True							,    _lowercase=9_9							,    _lowercase=3_2							,    _lowercase=5							,    _lowercase=4							,    _lowercase=3_7							,    _lowercase="gelu"							,    _lowercase=0.1							,    _lowercase=0.1							,    _lowercase=5_1_2							,    _lowercase=1_6							,    _lowercase=2							,    _lowercase=0.02							,    _lowercase=4							,    ) ->						List[str]:







								'''simple docstring'''

								snake_case_   : Tuple						=			parent
								snake_case_   : List[str]						=			batch_size
								snake_case_   : int						=			seq_length
								snake_case_   : List[Any]						=			is_training
								snake_case_   : Optional[int]						=			use_attention_mask
								snake_case_   : Optional[Any]						=			use_token_type_ids
								snake_case_   : Union[str, Any]						=			use_labels
								snake_case_   : str						=			vocab_size
								snake_case_   : List[str]						=			hidden_size
								snake_case_   : List[str]						=			num_hidden_layers
								snake_case_   : int						=			num_attention_heads
								snake_case_   : Dict						=			intermediate_size
								snake_case_   : Union[str, Any]						=			hidden_act
								snake_case_   : List[str]						=			hidden_dropout_prob
								snake_case_   : Any						=			attention_probs_dropout_prob
								snake_case_   : List[str]						=			max_position_embeddings
								snake_case_   : Union[str, Any]						=			type_vocab_size
								snake_case_   : str						=			type_sequence_label_size
								snake_case_   : Dict						=			initializer_range
								snake_case_   : str						=			num_choices





		def    UpperCAmelCase__							(					self   ) ->						List[Any]:







								'''simple docstring'''

								snake_case_   : List[Any]						=			ids_tensor([self.batch_size, self.seq_length]							,    self.vocab_size   )

								snake_case_   : Tuple						=			None
								if self.use_attention_mask:
														snake_case_   : Union[str, Any]						=			random_attention_mask([self.batch_size, self.seq_length]   )

								snake_case_   : Optional[int]						=			None
								if self.use_token_type_ids:
														snake_case_   : str						=			ids_tensor([self.batch_size, self.seq_length]							,    self.type_vocab_size   )

								snake_case_   : Union[str, Any]						=			RoFormerConfig(
								    vocab_size=self.vocab_size							,    hidden_size=self.hidden_size							,    num_hidden_layers=self.num_hidden_layers							,    num_attention_heads=self.num_attention_heads							,    intermediate_size=self.intermediate_size							,    hidden_act=self.hidden_act							,    hidden_dropout_prob=self.hidden_dropout_prob							,    attention_probs_dropout_prob=self.attention_probs_dropout_prob							,    max_position_embeddings=self.max_position_embeddings							,    type_vocab_size=self.type_vocab_size							,    is_decoder=_lowercase							,    initializer_range=self.initializer_range							,    )

								return config, input_ids, token_type_ids, attention_mask





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







								'''simple docstring'''

								snake_case_   : str						=			self.prepare_config_and_inputs()
								snake_case_			,		snake_case_			,		snake_case_			,		snake_case_   : List[Any]						=			config_and_inputs
								snake_case_   : Tuple						=			{"""input_ids""": input_ids, """token_type_ids""": token_type_ids, """attention_mask""": attention_mask}
								return config, inputs_dict




@require_flax
class    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__  ,				unittest.TestCase		):





		"""simple docstring"""






		_lowerCamelCase			  =       True

		_lowerCamelCase			  =       (
		    (
		        FlaxRoFormerModel,
		        FlaxRoFormerForMaskedLM,
		        FlaxRoFormerForSequenceClassification,
		        FlaxRoFormerForTokenClassification,
		        FlaxRoFormerForMultipleChoice,
		        FlaxRoFormerForQuestionAnswering,
		    )
		    if is_flax_available()
		    else ()
		)





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







								'''simple docstring'''

								snake_case_   : Dict						=			FlaxRoFormerModelTester(self   )





		@slow
		def    UpperCAmelCase__							(					self   ) ->						Union[str, Any]:







								'''simple docstring'''

								for model_class_name in self.all_model_classes:
														snake_case_   : Tuple						=			model_class_name.from_pretrained("""junnyu/roformer_chinese_small"""							,    from_pt=_lowercase   )
														snake_case_   : List[str]						=			model(np.ones((1, 1)   )   )
														self.assertIsNotNone(_lowercase   )




@require_flax
class    _lowerCAmelCase    (				unittest.TestCase		):





		"""simple docstring"""






		@slow
		def    UpperCAmelCase__							(					self   ) ->						Tuple:







								'''simple docstring'''

								snake_case_   : Dict						=			FlaxRoFormerForMaskedLM.from_pretrained("""junnyu/roformer_chinese_base"""   )
								snake_case_   : Tuple						=			jnp.array([[0, 1, 2, 3, 4, 5]]   )
								snake_case_   : Dict						=			model(_lowercase   )[0]

								snake_case_   : Optional[int]						=			5_0_0_0_0

								snake_case_   : Union[str, Any]						=			(1, 6, vocab_size)
								self.assertEqual(output.shape							,    _lowercase   )

								snake_case_   : Dict						=			jnp.array(
								    [[[-0.1205, -1.0265, 0.2922], [-1.5134, 0.1974, 0.1519], [-5.0135, -3.9003, -0.8404]]]   )

								self.assertTrue(jnp.allclose(output[:, :3, :3]							,    _lowercase							,    atol=1E-4   )   )

