code: def _build_sparse_tensor_slice_dataset(self, slices):
      # pylint: disable=g-complex-comprehension
      indices = np.array(
          [
              [i, j]
              for i in range(len(slices))
              for j in range(len(slices[i]))
          ],
          dtype=np.int64,
      )
      values = np.array(
          [val for s in slices for val in s], dtype=np.float64
      )
      # pylint: enable=g-complex-comprehension
      dense_shape = np.array(
          [len(slices), max(len(s) for s in slices) + 1], dtype=np.int64
      )
      sparse_components = sparse_tensor.SparseTensor(
          indices, values, dense_shape
      )
      return dataset_ops.Dataset.from_sparse_tensor_slices(
          sparse_components
      )
  
imports: from absl.testing import parameterized
  import numpy
  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.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.ops import array_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the FromSparseTensorSlicesCheckpointTest obj's underlying member method code with example usage: obj._build_sparse_tensor_slice_dataset(slices) and returns: dataset_ops