code: def convert_dependency_to_set(
      dependency: Dict[Any, Set[Any]]
  ) -> List[Set[Any]]:
      """
      Convert the dependency dict to sets of dependent nodes.
  
      Parameters
      ----------
      dependency : Dict
          The individual dependency mapping for the target graph.
  
      Returns
      -------
      List
          A list of dependencies for the target graph.
      """
      visited = set()
      d_sets = []
      for key, value in dependency.items():
          if key not in visited:
              tmp = set([key]) | value
              visited.update(tmp)
              if len(tmp) > 1:
                  d_sets.append(tmp)
      return d_sets
  
file_path: nni/nni/compression/speedup/dependency.py
imports: import logging
  import operator
  from copy import deepcopy
  from typing import Any, Dict, List, Set
  from uuid import uuid4
  import numpy
  import torch
  import torch.fx
  from torch.fx.passes.shape_prop import TensorMetadata
  from nni.compression.base.config import trans_legacy_config_list, select_modules_by_config
label_desc: Use image node_id 6 for calling a global function with example usage: convert_dependency_to_set(dependency) and returns: d_sets