*
   * {@snippet :
   * Map<String, Integer> map = ImmutableMap.of("a", 4, "b", 9);
   * Function<Integer, Double> sqrt = (Integer in) -> Math.sqrt((int) in);
   * Map<String, Double> transformed = Maps.transformValues(map, sqrt);
   * System.out.println(transformed);
   * }
   *
   * ... prints {@code {a=2.0, b=3.0}}.
   *

   *
   * {@snippet :
   * Map<String, Integer> map = ImmutableMap.of("a", 4, "b", 9);
   * Function<Integer, Double> sqrt = (Integer in) -> Math.sqrt((int) in);
   * Map<String, Double> transformed = Maps.transformValues(map, sqrt);
   * System.out.println(transformed);
   * }
   *
   * ... prints {@code {a=2.0, b=3.0}}.
   *

        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],
        keepdims=True) # Author code uses std + 1e-5 return
        super().convolution_op(inputs, (kernel - mean) / tf.sqrt(var + 1e-10))`

the non-blank method and field names must be distinct.
</p>

<p>
Given defined type <code>Point</code> the declarations
</p>

<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>,