



"""simple docstring"""
from graphs.minimum_spanning_tree_kruskal import kruskal
def    A_  (			):







						'''simple docstring'''


						snake_case_ :int						=			9
						snake_case_ :Tuple						=			[
						    [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],
						]

						snake_case_ :Union[str, Any]						=			kruskal(_lowercase,					_lowercase	)

						snake_case_ :Optional[int]						=			[
						    [7, 6, 1],
						    [2, 8, 2],
						    [6, 5, 2],
						    [0, 1, 4],
						    [2, 5, 4],
						    [2, 3, 7],
						    [0, 7, 8],
						    [3, 4, 9],
						]

						assert sorted(_lowercase	) == sorted(_lowercase	)



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCAmelCase					:			Tuple  				=			{
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase					:			Optional[int]  				=			["LlamaTokenizer"]

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase					:			Optional[int]  				=			["LlamaTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase					:			List[Any]  				=			[
						    "LlamaForCausalLM",
						    "LlamaModel",
						    "LlamaPreTrainedModel",
						    "LlamaForSequenceClassification",
						]


if TYPE_CHECKING:
						from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_llama import LlamaTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_llama_fast import LlamaTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
						import sys

						_lowerCAmelCase					:			int  				=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






