code: def testFromTensorSlicesMixedRagged(self):
      components = (
          np.tile(np.array([[1], [2], [3]]), 20),
          np.tile(np.array([[12], [13], [14]]), 22),
          np.array([37.0, 38.0, 39.0]),
          sparse_tensor.SparseTensorValue(
              indices=np.array([[0, 0], [1, 0], [2, 0]]),
              values=np.array([0, 0, 0]),
              dense_shape=np.array([3, 1]),
          ),
          sparse_tensor.SparseTensorValue(
              indices=np.array([[0, 0], [1, 1], [2, 2]]),
              values=np.array([1, 2, 3]),
              dense_shape=np.array([3, 3]),
          ),
          ragged_factory_ops.constant_value([[[0]], [[1]], [[2]]]),
      )
  
      dataset = dataset_ops.Dataset.from_tensor_slices(components)
      get_next = self.getNext(dataset)
  
      expected = [
          (
              sparse_tensor.SparseTensorValue(
                  indices=np.array([[0]]),
                  values=np.array([0]),
                  dense_shape=np.array([1]),
              ),
              sparse_tensor.SparseTensorValue(
                  indices=np.array([[0]]),
                  values=np.array([1]),
                  dense_shape=np.array([3]),
              ),
              ragged_factory_ops.constant_value([[0]]),
          ),
          (
              sparse_tensor.SparseTensorValue(
                  indices=np.array([[0]]),
                  values=np.array([0]),
                  dense_shape=np.array([1]),
              ),
              sparse_tensor.SparseTensorValue(
                  indices=np.array([[1]]),
                  values=np.array([2]),
                  dense_shape=np.array([3]),
              ),
              ragged_factory_ops.constant_value([[1]]),
          ),
          (
              sparse_tensor.SparseTensorValue(
                  indices=np.array([[0]]),
                  values=np.array([0]),
                  dense_shape=np.array([1]),
              ),
              sparse_tensor.SparseTensorValue(
                  indices=np.array([[2]]),
                  values=np.array([3]),
                  dense_shape=np.array([3]),
              ),
              ragged_factory_ops.constant_value([[2]]),
          ),
      ]
      for i in range(3):
          results = self.evaluate(get_next())
          for component, result_component in zip(
              (list(zip(*components[:3]))[i] + expected[i]), results
          ):
              self.assertValuesEqual(component, result_component)
      with self.assertRaises(errors.OutOfRangeError):
          self.evaluate(get_next())
  
imports: import collections
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import random_access
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 10 for calling the FromTensorSlicesTest obj's underlying member method code with example usage: obj.testFromTensorSlicesMixedRagged() without return types