






from __future__ import annotations

from typing import Generic, TypeVar

SCREAMING_SNAKE_CASE__		:							Any 				=				TypeVar("""T""")







class 				UpperCAmelCase_  (		Generic[T]		):




     def __init__(				self	,						_lowerCAmelCase		):
          UpperCAmelCase__      :  Union[str, Any]				      =			data
          UpperCAmelCase__      :  Tuple				      =			self
          UpperCAmelCase__      :  Optional[int]				      =			0







class 				UpperCAmelCase_  (		Generic[T]		):




     def __init__(				self		):
          # map from node name to the node object
          UpperCAmelCase__      :  dict[T, DisjointSetTreeNode[T]]				      =			{}




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase		):
          # create a new set with x as its member
          UpperCAmelCase__      :  Any				      =			DisjointSetTreeNode(_lowerCAmelCase		)




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase		):
          # find the set x belongs to (with path-compression)
          UpperCAmelCase__      :  Dict				      =			self.map[data]
          if elem_ref != elem_ref.parent:
               UpperCAmelCase__      :  str				      =			self.find_set(elem_ref.parent.data		)
          return elem_ref.parent




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase	,						_lowerCAmelCase		):
          # helper function for union operation
          if nodea.rank > nodea.rank:
               UpperCAmelCase__      :  Optional[int]				      =			nodea
          else:
               UpperCAmelCase__      :  Optional[Any]				      =			nodea
               if nodea.rank == nodea.rank:
                    nodea.rank += 1




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase	,						_lowerCAmelCase		):
          # merge 2 disjoint sets
          self.link(self.find_set(_lowerCAmelCase		)	,						self.find_set(_lowerCAmelCase		)		)







class 				UpperCAmelCase_  (		Generic[T]		):




     def __init__(				self		):
          # connections: map from the node to the neighbouring nodes (with weights)
          UpperCAmelCase__      :  dict[T, dict[T, int]]				      =			{}




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase		):
          # add a node ONLY if its not present in the graph
          if node not in self.connections:
               UpperCAmelCase__      :  Union[str, Any]				      =			{}




     def   __UpperCAmelCase  (				self	,						_lowerCAmelCase	,						_lowerCAmelCase	,						_lowerCAmelCase		):
          # add an edge with the given weight
          self.add_node(_lowerCAmelCase		)
          self.add_node(_lowerCAmelCase		)
          UpperCAmelCase__      :  List[Any]				      =			weight
          UpperCAmelCase__      :  int				      =			weight




     def   __UpperCAmelCase  (				self		):
          UpperCAmelCase__      :  Union[str, Any]				      =			[]
          UpperCAmelCase__      :  Any				      =			set()
          for start in self.connections:
               for end in self.connections[start]:
                    if (start, end) not in seen:
                         seen.add((end, start)		)
                         edges.append((start, end, self.connections[start][end])		)
          edges.sort(key=lambda _lowerCAmelCase		: x[2]		)

          # creating the disjoint set
          UpperCAmelCase__      :  Optional[Any]				      =			DisjointSetTree[T]()
          for node in self.connections:
               disjoint_set.make_set(_lowerCAmelCase		)

          # MST generation
          UpperCAmelCase__      :  int				      =			0
          UpperCAmelCase__      :  Optional[Any]				      =			0
          UpperCAmelCase__      :  str				      =			GraphUndirectedWeighted[T]()
          while num_edges < len(self.connections		) - 1:
               UpperCAmelCase__      ,		UpperCAmelCase__      ,		UpperCAmelCase__      :  Optional[Any]				      =			edges[index]
               index += 1
               UpperCAmelCase__      :  Optional[int]				      =			disjoint_set.find_set(_lowerCAmelCase		)
               UpperCAmelCase__      :  str				      =			disjoint_set.find_set(_lowerCAmelCase		)
               if parent_u != parent_v:
                    num_edges += 1
                    graph.add_edge(_lowerCAmelCase	,						_lowerCAmelCase	,						_lowerCAmelCase		)
                    disjoint_set.union(_lowerCAmelCase	,						_lowerCAmelCase		)
          return graph










'''simple docstring'''





import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict


@pytest.mark.parametrize(
    '''split_dict''',   [
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train''',   num_bytes=1_337,   num_examples=42,   dataset_name='''my_dataset'''						)}						),
        SplitDict({'''train''': SplitInfo(name='''train''',   num_bytes=1_337,   num_examples=42						)}						),
        SplitDict({'''train''': SplitInfo()}						),
    ],   )
def        a__     (					UpperCamelCase_						:      SplitDict						):
   UpperCAmelCase__	:List[Any]      =      split_dict._to_yaml_list()
   assert len(UpperCamelCase_						) == len(UpperCamelCase_						)
   UpperCAmelCase__	:Tuple      =      SplitDict._from_yaml_list(UpperCamelCase_						)
   for split_name, split_info in split_dict.items():
      # dataset_name field is deprecated, and is therefore not part of the YAML dump
      UpperCAmelCase__	:Union[str, Any]      =      None
      # the split name of split_dict takes over the name of the split info object
      UpperCAmelCase__	:Union[str, Any]      =      split_name
   assert split_dict == reloaded


@pytest.mark.parametrize(
    '''split_info''',   [SplitInfo(), SplitInfo(dataset_name=UpperCamelCase_						), SplitInfo(dataset_name='''my_dataset'''						)]						)
def        a__     (					UpperCamelCase_						:      List[Any]						):
   # For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
   # field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
   UpperCAmelCase__	:List[Any]      =      asdict(SplitDict({'''train''': split_info}						)						)
   assert "dataset_name" in split_dict_asdict["train"]
   assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name



