


'''simple docstring'''



from collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst






def   lowerCamelCase							():
					__a    ,				__a			:       Union[str, Any]					    =  9, 14  # noqa: F841
					__a			:       Optional[Any]					    =  [
					    [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],
					]

					__a			:       Dict					    =  defaultdict(_SCREAMING_SNAKE_CASE   )
					for nodea, nodea, cost in edges:
										adjancency[nodea].append([nodea, cost]   )
										adjancency[nodea].append([nodea, cost]   )

					__a			:       Union[str, Any]					    =  mst(_SCREAMING_SNAKE_CASE   )

					__a			:       List[Any]					    =  [
					    [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:
										__a			:       Optional[Any]					    =  tuple(answer[:2]   )
										__a			:       Any					    =  tuple(edge[::-1]   )
										assert edge in result or reverse in result







'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowercase	:						Union[str, Any]       =	{
    'configuration_blenderbot': [
        'BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlenderbotConfig',
        'BlenderbotOnnxConfig',
    ],
    'tokenization_blenderbot': ['BlenderbotTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						List[Any]       =	['BlenderbotTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						List[Any]       =	[
	    'BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'BlenderbotForCausalLM',
	    'BlenderbotForConditionalGeneration',
	    'BlenderbotModel',
	    'BlenderbotPreTrainedModel',
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						Union[str, Any]       =	[
	    'TFBlenderbotForConditionalGeneration',
	    'TFBlenderbotModel',
	    'TFBlenderbotPreTrainedModel',
	]


try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						Dict       =	[
	    'FlaxBlenderbotForConditionalGeneration',
	    'FlaxBlenderbotModel',
	    'FlaxBlenderbotPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_blenderbot import (
	    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    BlenderbotConfig,
	    BlenderbotOnnxConfig,
	)
	from .tokenization_blenderbot import BlenderbotTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_blenderbot import (
		    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    BlenderbotForCausalLM,
		    BlenderbotForConditionalGeneration,
		    BlenderbotModel,
		    BlenderbotPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_blenderbot import (
		    TFBlenderbotForConditionalGeneration,
		    TFBlenderbotModel,
		    TFBlenderbotPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_blenderbot import (
		    FlaxBlenderbotForConditionalGeneration,
		    FlaxBlenderbotModel,
		    FlaxBlenderbotPreTrainedModel,
		)

else:
	import sys

	__lowercase	:						str       =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



