<pre>
func (p *Point) Length() float64 {
	return math.Sqrt(p.x * p.x + p.y * p.y)
}

func (p *Point) Scale(factor float64) {
	p.x *= factor
	p.y *= factor
}
</pre>

<p>
bind the methods <code>Length</code> and <code>Scale</code>,
with receiver type <code>*Point</code>,
to the base type <code>Point</code>.
</p>

<p>

  auto init_func_op =
      sub_symbol_table.lookup<mlir::func::FuncOp>(target_node_name);
  init_func_op->removeAttr("tf.entry_function");

  mlir::OpBuilder builder(module_->getBodyRegion());

  // Bind asset inputs to asset ops.
  DCHECK_EQ(init_func_op.getNumArguments(), assets.size());
  for (const auto& iter : llvm::enumerate(assets)) {
    auto asset_op = iter.value().op;
    init_func_op.setArgAttr(

	ListenAndServePodResources()
	Run(<-chan kubetypes.PodUpdate)
	RunOnce(<-chan kubetypes.PodUpdate) ([]RunPodResult, error)
}

// Dependencies is a bin for things we might consider "injected dependencies" -- objects constructed
// at runtime that are necessary for running the Kubelet. This is a temporary solution for grouping

ick","createFxNow","genFx","includeWidth","createTween","animation","Animation","tweeners","properties","stopped","prefilters","currentTime","startTime","tweens","opts","specialEasing","originalProperties","originalOptions","gotoEnd","propFilter","bind","complete","timer","anim","*","tweener","oldfire","propTween","restoreDisplay","isBox","dataShow","unqueued","overflow","overflowX","overflowY","prefilter","speed","speeds","fadeTo","to","animate","optall","doAnimation","finish","stopQueue","time...

					CreationTimestamp: metav1.Time{Time: time.Now().Add(1.9e9)},
				},
				Data: map[string]string{
					"foo": "bar",
				},
				BinaryData: map[string][]byte{
					"bin": []byte("binary data"),
				},
			},
			// Columns: Name, (Num) Data, Age
			expected: []metav1.TableRow{{Cells: []interface{}{"configmap3", int64(2), "0s"}}},
		},
	}

	for i, test := range tests {