code: def _get_optim_cut(valid_cut_edges, local_measurement=False):
      """Picks out the best cut from a dict of valid candidate cuts."""
  
      if local_measurement:
          min_max_node_degree = min(
              max_node_degree for _, max_node_degree in valid_cut_edges
          )
          optim_cuts = {
              k: cut_edges
              for (
                  k,
                  max_node_degree,
              ), cut_edges in valid_cut_edges.items()
              if (max_node_degree == min_max_node_degree)
          }
      else:
          min_cuts = min(
              len(cut_edges) for cut_edges in valid_cut_edges.values()
          )
          optim_cuts = {
              k: cut_edges
              for (k, _), cut_edges in valid_cut_edges.items()
              if (len(cut_edges) == min_cuts)
          }
  
      return optim_cuts[min(optim_cuts)]
  
imports: import uuid
  from typing import Any, Callable, Sequence, Tuple
  import warnings
  import numpy
  from networkx import MultiDiGraph, has_path, weakly_connected_components
  import pennylane
  from pennylane.measurements import MeasurementProcess
  from pennylane.ops.meta import WireCut
  from pennylane.queuing import WrappedObj
  from pennylane.operation import Operation
  from .kahypar import kahypar_cut
  from .cutstrategy import CutStrategy
label_desc: Use image node_id 14 for calling a global function with example usage: _get_optim_cut(valid_cut_edges, local_measurement) and returns: optim_cuts