






"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available


UpperCAmelCase_     :				str         =				{
    "configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_     :				Tuple         =				[
      "LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST",
      "LongT5EncoderModel",
      "LongT5ForConditionalGeneration",
      "LongT5Model",
      "LongT5PreTrainedModel",
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_     :				Dict         =				[
      "FlaxLongT5ForConditionalGeneration",
      "FlaxLongT5Model",
      "FlaxLongT5PreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_longta import LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP, LongTaConfig, LongTaOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_longta import (
        LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST,
        LongTaEncoderModel,
        LongTaForConditionalGeneration,
        LongTaModel,
        LongTaPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_longta import (
        FlaxLongTaForConditionalGeneration,
        FlaxLongTaModel,
        FlaxLongTaPreTrainedModel,
    )


else:
  import sys

  UpperCAmelCase_     :				Union[str, Any]         =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










"""simple docstring"""






from collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst



def       _A    ()				-> Union[str, Any]:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_		,    SCREAMING_SNAKE_CASE_   :						Tuple							=	9, 14  # noqa: F841
    SCREAMING_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],
    ]

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

    SCREAMING_SNAKE_CASE_   :						Any							=	mst(__a							)

    SCREAMING_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],
    ]

    for answer in expected:
        SCREAMING_SNAKE_CASE_   :						Dict							=	tuple(answer[:2]							)
        SCREAMING_SNAKE_CASE_   :						Optional[int]							=	tuple(edge[::-1]							)
        assert edge in result or reverse in result


