import tensorflow as tf

    lazy_model = DynamicsModel(dim_state, dim_action, normalizers, FLAGS.model.hidden_sizes)
    warmup_model = DynamicsModel(dim_state, dim_action, normalizers, FLAGS.model.hidden_sizes)
    sync_warmup_model = tf.group(*[tf.assign(w_v, p_v) for w_v, p_v in zip(warmup_model.parameters(), model.parameters())])
    shadow_models = [DynamicsModel(dim_state, dim_action, normalizers, FLAGS.model.hidden_sizes) for n in range(FLAGS.warmup.n_shadow_models)]
    sync_model_from_lazymodel = tf.group(*[tf.assign(w_v, p_v) for w_v, p_v in zip(model.parameters(), lazy_model.parameters())])
    sync_model_to_lazymodel = tf.group(*[tf.assign(w_v, p_v) for w_v, p_v in zip(lazy_model.parameters(), model.parameters())])

    virt_env = VirtualEnv(model, make_env(FLAGS.env.id, task_config=task), FLAGS.plan.n_envs, opt_model=FLAGS.slbo.opt_model)
