docstr: Test a dataset based on invalid `tf.sparse.SparseTensor`.
docstr_tok: ["Test","a","dataset","based","on","invalid","`","tf.sparse.SparseTensor","`","."]
code: def testEmptySparseTensorSlicesInvalid(self):
      """Test a dataset based on invalid `tf.sparse.SparseTensor`."""
      st = array_ops.sparse_placeholder(dtypes.float64)
      iterator = dataset_ops.make_initializable_iterator(
          dataset_ops.Dataset.from_sparse_tensor_slices(st)
      )
      init_op = iterator.initializer
  
      with self.cached_session() as sess:
          # Test with an empty sparse tensor but with non empty values.
          empty_indices = np.empty((0, 4), dtype=np.int64)
          non_empty_values = [1, 2, 3, 4]
          empty_dense_shape = [0, 4, 37, 9]
          sparse_feed = sparse_tensor.SparseTensorValue(
              empty_indices, non_empty_values, empty_dense_shape
          )
          # Here, we expect the test to fail when running the feed.
          with self.assertRaises(errors.InvalidArgumentError):
              sess.run(init_op, feed_dict={st: sparse_feed})
  
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 4 for calling the FromSparseTensorSlicesTest obj's underlying member method code with example usage: obj.testEmptySparseTensorSlicesInvalid() without return types