code: def test_from_trimesh():
      import trimesh
  
      vertices = [[0, 0, 0], [1, 0, 0], [0, 1, 0]]
      faces = [[0, 1, 2]]
      mesh = trimesh.Trimesh(
          vertices=vertices, faces=faces, process=False
      )
  
      data = from_trimesh(mesh)
  
      assert data.pos.tolist() == vertices
      assert data.face.t().contiguous().tolist() == faces
  
imports: import pytest
  import scipy.sparse
  import torch
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.testing import get_random_edge_index, withPackage
  from torch_geometric.utils import from_cugraph, from_dgl, from_networkit, from_networkx, from_scipy_sparse_matrix, from_trimesh, sort_edge_index, subgraph, to_cugraph, to_dgl, to_networkit, to_networkx, to_scipy_sparse_matrix, to_trimesh
label_desc: Use image node_id 23 for calling a global function with example usage: test_from_trimesh() without return types