code: def to_bm(num_points, use_symeig_workaround):
      device = torch.device("cuda:0")
      points_padded, _normals = TestPCLNormals.init_spherical_pcl(
          num_points=num_points, device=device, use_pointclouds=False
      )
      torch.cuda.synchronize()
  
      def run():
          estimate_pointcloud_normals(
              points_padded, use_symeig_workaround=use_symeig_workaround
          )
          torch.cuda.synchronize()
  
      return run
  
imports: import itertools
  import torch
  from fvcore.common.benchmark import benchmark
  from pytorch3d.ops import estimate_pointcloud_normals
  from tests.test_points_normals import TestPCLNormals
label_desc: Use image node_id 1 for calling a global function with example usage: to_bm(num_points, use_symeig_workaround) and returns: run