code: def test_sparse_coo_tensor_numpy_roundtrip(dtype_str, arrow_type):
      dtype = np.dtype(dtype_str)
      data = np.array([[1, 2, 3, 4, 5, 6]]).T.astype(dtype)
      coords = np.array(
          [
              [0, 0, 2, 3, 1, 3],
              [0, 2, 0, 4, 5, 5],
          ]
      ).T
      shape = (4, 6)
      dim_names = ("x", "y")
  
      sparse_tensor = pa.SparseCOOTensor.from_numpy(
          data, coords, shape, dim_names
      )
      repr(sparse_tensor)
      result_data, result_coords = sparse_tensor.to_numpy()
      assert sparse_tensor.type == arrow_type
      assert np.array_equal(data, result_data)
      assert np.array_equal(coords, result_coords)
      assert sparse_tensor.dim_names == dim_names
  
imports: import pytest
  import sys
  import weakref
  import numpy
  import pyarrow
label_desc: Use image node_id 10 for calling a global function with example usage: test_sparse_coo_tensor_numpy_roundtrip(dtype_str, arrow_type) without return types