ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Get attr
  AttrValue read_attr;
  GetAttr("test_attr_name", &read_attr);
  ASSERT_EQ(attr.DebugString(), read_attr.DebugString());

  // Retrieve the same attr after save/restore
  Reincarnate();
  AttrValue read_attr2;
  GetAttr("test_attr_name", &read_attr2);
  ASSERT_EQ(attr.DebugString(), read_attr2.DebugString());
}

        // Test setAttr
        tag.setAttr("data-role", "button");
        assertTrue(tag.toString().contains("attrName=data-role"));
        assertTrue(tag.toString().contains("attrValue=button"));

        // Test overwriting values
        tag.setId("new-id");
        tag.setCss("new-class");
        tag.setAttr("role", "link");

_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers")
setattr(_current_module, "losses", _losses)
setattr(_current_module, "metrics", _metrics)
setattr(_current_module, "optimizers", _optimizers)
setattr(_current_module, "initializers", _initializers)


# Do an eager load for Keras' code so that any function/method that needs to

     * Sets a custom attribute name-value pair that this pruned tag should match.
     *
     * @param name the attribute name to match
     * @param value the attribute value to match
     */
    public void setAttr(final String name, final String value) {
        attrName = name;
        attrValue = value;
    }

    @Override
    public String toString() {

  import tensorflow_io_gcs_filesystem as _tensorflow_io_gcs_filesystem

# Lazy-load Keras v1.
_tf_uses_legacy_keras = (
    _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"))
setattr(_current_module, "keras", _KerasLazyLoader(globals(), mode="v1"))
_module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__

        which would previously raise an error. This will correspond to an
        attribute name with an embedded '.' symbol (e.g. 'a.b'), which can only
        be accessed indirectly (e.g. through getattr and setattr). To set this
        up the user will first need to explicitly add the variable to the hparam
        object (e.g. "hparams.add_hparam(name='a.b', value=0.0)").
    *   Benchmark for tf.scan in graph and eager modes.