code: def test_mixed_indexing():
      t = ones((100, 200, 300, 400))
  
      with pytest.raises(IndexError):
          _ = t[ones((100, 200), dtype=float)]  # noqa: F841
  
      t2 = t[ones(100) < 2, ..., 20::101, 2]
      assert len(t2.shape) == 3
      assert np.isnan(t2.shape[0])
  
      t3 = ones((2, 3, 4, 5))
      t4 = t3[1]
      assert (
          t4.flags["C_CONTIGUOUS"]
          == np.ones((2, 3, 4, 5))[1].flags["C_CONTIGUOUS"]
      )
      assert (
          t4.flags["F_CONTIGUOUS"]
          == np.ones((2, 3, 4, 5))[1].flags["F_CONTIGUOUS"]
      )
  
imports: import numpy
  import pytest
  from ....config import option_context
  from ....core import tile
  from ...base.broadcast_to import TensorBroadcastTo
  from ...datasource import ones, tensor, array, empty
  from ...datasource.ones import TensorOnes
  from ...merge.concatenate import TensorConcatenate
  from ..None import choose, unravel_index, nonzero, compress, fill_diagonal
  from ..setitem import TensorIndexSetValue
label_desc: Use image node_id 4 for calling a global function with example usage: test_mixed_indexing() without return types