code: def testTranspose(self):
      if not self._gpu_available:
          return
  
      for conjugate in False, True:
          sparsify = lambda m: m * (m > 0)
          dense_shape = [5, 7, 13]
          a_mats = sparsify(
              (
                  np.random.randn(*dense_shape)
                  + 1.0j * np.random.randn(*dense_shape)
              )
          ).astype(np.complex64)
          expected = np.transpose(a_mats, (0, 2, 1))
          if conjugate:
              expected = np.conj(expected)
          a_sm = sparse_csr_matrix_ops.CSRSparseMatrix(a_mats)
          if conjugate:
              a_sm_t = a_sm.hermitian_transpose()
          else:
              a_sm_t = a_sm.transpose()
          self.assertIsInstance(
              a_sm_t, sparse_csr_matrix_ops.CSRSparseMatrix
          )
          a_sm_t_dense = a_sm_t.to_dense()
          a_sm_t_dense = self.evaluate(a_sm_t_dense)
          self.assertAllClose(expected, a_sm_t_dense)
  
imports: import itertools
  import numpy
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.linalg.sparse import sparse_csr_matrix_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 6 for calling the CSRSparseMatrixTest obj's underlying member method code with example usage: obj.testTranspose() without return types