code: def _dfs(node, paths):
      """use depth first search to find all path activation combination"""
      if node == paths:
          return [[0], [1]]
      child = _dfs(node + 1, paths)
      return [[0] + _ for _ in child] + [[1] + _ for _ in child]
  
imports: from __future__ import annotations
  import datetime
  import warnings
  from typing import Optional
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from monai.networks.blocks.dints_block import ActiConvNormBlock, FactorizedIncreaseBlock, FactorizedReduceBlock, P3DActiConvNormBlock
  from monai.networks.layers.factories import Conv
  from monai.networks.layers.utils import get_act_layer, get_norm_layer
  from monai.utils import optional_import
label_desc: Use image node_id 1 for calling a global function with example usage: _dfs(node, paths) and returns: unknown, list