code: def testSerializedContainingSparseAndSparseFeatureAndDenseWithNoDefault(
      self,
  ):
      original = [
          example(
              features=features(
                  {
                      "c": float_feature([3, 4]),
                      "val": bytes_feature([b"a", b"b"]),
                      "idx": int64_feature([0, 3]),
                  }
              )
          ),
          example(
              features=features(
                  {
                      "c": float_feature([1, 2]),
                      "val": bytes_feature([b"c"]),
                      "idx": int64_feature([7]),
                  }
              )
          ),
      ]
  
      a_default = np.array([[1, 2, 3]], dtype=np.int64)
      b_default = np.random.rand(3, 3).astype(bytes)
  
      expected_st_a = empty_sparse(np.int64)
  
      expected_outputs = [
          {
              "st_a": expected_st_a,
              "sp": (
                  np.array([[0], [3]], dtype=np.int64),
                  np.array(["a", "b"], dtype=bytes),
                  np.array([13], dtype=np.int64),
              ),
              "a": a_default,
              "b": b_default,
              "c": np.array([3, 4], dtype=np.float32),
          },
          {
              "st_a": expected_st_a,
              "sp": (
                  np.array([[7]], dtype=np.int64),
                  np.array(["c"], dtype=bytes),
                  np.array([13], dtype=np.int64),
              ),
              "a": a_default,
              "b": b_default,
              "c": np.array([1, 2], dtype=np.float32),
          },
      ]
  
      for proto, expected_output in zip(original, expected_outputs):
          self._test(
              {
                  "serialized": ops.convert_to_tensor(
                      proto.SerializeToString()
                  ),
                  "features": {
                      "st_a": parsing_ops.VarLenFeature(dtypes.int64),
                      "sp": parsing_ops.SparseFeature(
                          "idx", "val", dtypes.string, 13
                      ),
                      "a": parsing_ops.FixedLenFeature(
                          (1, 3), dtypes.int64, default_value=a_default
                      ),
                      "b": parsing_ops.FixedLenFeature(
                          (3, 3), dtypes.string, default_value=b_default
                      ),
                      # Feature "c" must be provided, since it has no default_value.
                      "c": parsing_ops.FixedLenFeature(
                          (2,), dtypes.float32
                      ),
                  },
              },
              expected_output,
          )
  
imports: import itertools
  import numpy
  from tensorflow.core.example import example_pb2
  from tensorflow.core.example import feature_pb2
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import parsing_ops
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 14 for calling the ParseExampleTest obj's underlying member method code with example usage: obj.testSerializedContainingSparseAndSparseFeatureAndDenseWithNoDefault() without return types