code: def test_numpy_index_multi(self, device):
      for dim_sz in [2, 8, 16, 32]:
          i = np.zeros((dim_sz, dim_sz, dim_sz), dtype=np.int32)
          i[: dim_sz // 2, :, :] = 1
          x = torch.randn(dim_sz, dim_sz, dim_sz)
          self.assertTrue(x[i == 1].numel() == np.sum(i))
  
imports: import torch
  import numpy
  from itertools import product
  from torch.testing._internal.common_utils import skipIfTorchDynamo, TestCase, run_tests
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, dtypes, skipMeta
  from torch.testing._internal.common_dtype import all_types_and_complex_and
label_desc: Use image node_id 11 for calling the TestNumPyInterop obj's underlying member method code with example usage: obj.test_numpy_index_multi(device) without return types