code: def test_sparse_csf_tensor_numpy_roundtrip(dtype_str, arrow_type):
      dtype = np.dtype(dtype_str)
      data = np.array([[8, 2, 5, 3, 4, 6]]).T.astype(dtype)
      indptr = [np.array([0, 2, 3, 4, 6])]
      indices = [np.array([0, 1, 2, 3]), np.array([0, 2, 5, 0, 4, 5])]
      axis_order = (0, 1)
      shape = (4, 6)
      dim_names = ("x", "y")
  
      sparse_tensor = pa.SparseCSFTensor.from_numpy(
          data, indptr, indices, shape, axis_order, dim_names
      )
      repr(sparse_tensor)
      (
          result_data,
          result_indptr,
          result_indices,
      ) = sparse_tensor.to_numpy()
      assert sparse_tensor.type == arrow_type
      assert np.array_equal(data, result_data)
      assert np.array_equal(indptr[0], result_indptr[0])
      assert np.array_equal(indices[0], result_indices[0])
      assert np.array_equal(indices[1], result_indices[1])
      assert sparse_tensor.dim_names == dim_names
  
imports: import pytest
  import sys
  import weakref
  import numpy
  import pyarrow
label_desc: Use image node_id 12 for calling a global function with example usage: test_sparse_csf_tensor_numpy_roundtrip(dtype_str, arrow_type) without return types