class_docstr: Class for Deep Marching Tetrahedra (DMTet).
  
  Attributes:
      device (torch.device): Device to place the tensors.
      triangle_table (Tensor): Lookup table for the triangles.
      num_triangles_table (Tensor): Table for the number of triangles.
      base_tet_edges (Tensor): The base edges for the tetrahedrons.
docstr: Create the lookup table for triangles.
  
  Returns:
      Tensor: The triangle lookup table.
docstr_tok: ["Create","the","lookup","table","for","triangles",".","Returns",":","Tensor",":","The","triangle","lookup","table","."]
code: def _create_triangle_table(self) -> torch.Tensor:
      """Create the lookup table for triangles.
  
      Returns:
          Tensor: The triangle lookup table.
      """
      return torch.tensor(
          [
              [-1, -1, -1, -1, -1, -1],
              [1, 0, 2, -1, -1, -1],
              [4, 0, 3, -1, -1, -1],
              [1, 4, 2, 1, 3, 4],
              [3, 1, 5, -1, -1, -1],
              [2, 3, 0, 2, 5, 3],
              [1, 4, 0, 1, 5, 4],
              [4, 2, 5, -1, -1, -1],
              [4, 5, 2, -1, -1, -1],
              [4, 1, 0, 4, 5, 1],
              [3, 2, 0, 3, 5, 2],
              [1, 3, 5, -1, -1, -1],
              [4, 1, 2, 4, 3, 1],
              [3, 0, 4, -1, -1, -1],
              [2, 0, 1, -1, -1, -1],
              [-1, -1, -1, -1, -1, -1],
          ],
          dtype=torch.long,
          device=self.device,
      )
  
imports: import torch
label_desc: Use image node_id 2 for calling the DeepMarchingTetrahedra obj's underlying member method code with example usage: obj._create_triangle_table() and returns: torch