

from collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst

def 							__SCREAMING_SNAKE_CASE							(				)   ->       Dict:
				_UpperCAmelCase       :		Any 		=    9, 14  # noqa: F841
				_UpperCAmelCase       :		str 		=    [
				    [0, 1, 4],
				    [0, 7, 8],
				    [1, 2, 8],
				    [7, 8, 7],
				    [7, 6, 1],
				    [2, 8, 2],
				    [8, 6, 6],
				    [2, 3, 7],
				    [2, 5, 4],
				    [6, 5, 2],
				    [3, 5, 14],
				    [3, 4, 9],
				    [5, 4, 10],
				    [1, 7, 11],
				]

				_UpperCAmelCase       :		List[Any] 		=    defaultdict(__lowercase )
				for nodea, nodea, cost in edges:
								adjancency[nodea].append([nodea, cost] )
								adjancency[nodea].append([nodea, cost] )

				_UpperCAmelCase       :		Tuple 		=    mst(__lowercase )

				_UpperCAmelCase       :		Tuple 		=    [
				    [7, 6, 1],
				    [2, 8, 2],
				    [6, 5, 2],
				    [0, 1, 4],
				    [2, 5, 4],
				    [2, 3, 7],
				    [0, 7, 8],
				    [3, 4, 9],
				]

				for answer in expected:
								_UpperCAmelCase       :		List[Any] 		=    tuple(answer[:2] )
								_UpperCAmelCase       :		Union[str, Any] 		=    tuple(edge[::-1] )
								assert edge in result or reverse in result





from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_        =      {
    # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}

class 				a  (	UpperCAmelCase				):
						_lowercase    						=			"megatron-bert"


						def __init__(       self						,					A_=29056						,					A_=1024						,					A_=24						,					A_=16						,					A_=4096						,					A_="gelu"						,					A_=0.1						,					A_=0.1						,					A_=512						,					A_=2						,					A_=0.02						,					A_=1e-12						,					A_=0						,					A_="absolute"						,					A_=True						,					**A_						,					):







										'''simple docstring'''


										super().__init__(pad_token_id=A_						,					**A_	)

										_UpperCAmelCase       :		Optional[Any] 		=    vocab_size
										_UpperCAmelCase       :		List[str] 		=    hidden_size
										_UpperCAmelCase       :		List[str] 		=    num_hidden_layers
										_UpperCAmelCase       :		Optional[Any] 		=    num_attention_heads
										_UpperCAmelCase       :		Any 		=    hidden_act
										_UpperCAmelCase       :		Optional[Any] 		=    intermediate_size
										_UpperCAmelCase       :		int 		=    hidden_dropout_prob
										_UpperCAmelCase       :		Optional[Any] 		=    attention_probs_dropout_prob
										_UpperCAmelCase       :		Any 		=    max_position_embeddings
										_UpperCAmelCase       :		str 		=    type_vocab_size
										_UpperCAmelCase       :		Optional[int] 		=    initializer_range
										_UpperCAmelCase       :		Dict 		=    layer_norm_eps
										_UpperCAmelCase       :		Tuple 		=    position_embedding_type
										_UpperCAmelCase       :		Tuple 		=    use_cache


