code: def testConstructorFromDenseTensorWithIndices(self):
      if not self._gpu_available:
          return
  
      dense_shape = [5, 7, 13]
      a_mats = np.random.randn(*dense_shape).astype(np.float32)
      indices = np.array([[0, 0, 0], [1, 0, 0]], dtype=np.int64)
  
      a_sm = sparse_csr_matrix_ops.CSRSparseMatrix(
          a_mats, indices=indices
      )
      self.assertEqual(a_sm.shape, a_mats.shape)
  
      a_sm_st = a_sm.to_sparse_tensor()
      a_sm_st = self.evaluate(a_sm_st)
  
      # Count number of nonzero entries for each batch using bincount.
      self.assertAllEqual(indices, a_sm_st.indices)
      self.assertAllEqual(dense_shape, a_sm.shape)
      self.assertAllEqual(dense_shape, a_sm_st.dense_shape)
      self.assertAllClose(
          [a_mats[tuple(x)] for x in indices], a_sm_st.values
      )
  
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 4 for calling the CSRSparseMatrixTest obj's underlying member method code with example usage: obj.testConstructorFromDenseTensorWithIndices() without return types