], dtype=torch.int).unsqueeze(0)
     writer = SummaryWriter()
     writer.add_mesh('my_mesh', vertices=vertices_tensor, colors=colors_tensor, faces=faces_tensor)

     writer.close()

add_hparams(hparam_dict, metric_dict, hparam_domain_discrete=None, run_name=None)
  Add a set of hyperparameters to be compared in TensorBoard.

  Parameters:
     * **hparam_dict** (*dict*) -- Each key-value pair in the
       dictionary is the name of the hyper parameter and it's
       corresponding value. The type of the value can be one of
       *bool*, *string*, *float*, *int*, or *None*.

     * **metric_dict** (*dict*) -- Each key-value pair in the
       dictionary is the name of the metric and it's corresponding
       value. Note that the key used here should be unique in the
       tensorboard record. Otherwise the value you added by
       "add_scalar" will be displayed in hparam plugin. In most
       cases, this is unwanted.
