code: def test_torch_to_np():
      """Test whether tuples of tensors can be converted to np arrays."""
      tup = (torch.zeros(1), torch.zeros(1))
      np_out_1, np_out_2 = torch_to_np(tup)
      assert isinstance(np_out_1, np.ndarray)
      assert isinstance(np_out_2, np.ndarray)
  
imports: import collections
  import numpy
  import pytest
  import torch
  from torch import tensor
  import torch.nn.functional
  from garage.envs import GymEnv, normalize
  from garage.experiment.deterministic import set_seed
  from garage.torch import as_torch_dict, compute_advantages, flatten_to_single_vector, global_device, pad_to_last, product_of_gaussians, set_gpu_mode, state_dict_to, torch_to_np
  import garage.torch._functions
  from garage.torch.policies import DeterministicMLPPolicy
  from tests.fixtures import TfGraphTestCase
label_desc: Use image node_id 3 for calling a global function with example usage: test_torch_to_np() without return types