* {@snippet :
   * ListMultimap<String, Integer> multimap =
   *      ImmutableListMultimap.of("a", 4, "a", 16, "b", 9);
   * Function<Integer, Double> sqrt = (Integer in) -> Math.sqrt((int) in);
   * ListMultimap<String, Double> transformed = Multimaps.transformValues(map,
   *     sqrt);
   * System.out.println(transformed);
   * }
   *
   * ... prints {@code {a=[2.0, 4.0], b=[3.0]}}.
   *

pkg math, func Erfcinv(float64) float64
pkg math, func Erfinv(float64) float64
pkg math, func Round(float64) float64
pkg math, func RoundToEven(float64) float64
pkg math/big, const MaxBase = 62
pkg math/big, method (*Float) Sqrt(*Float) *Float
pkg math/big, method (*Int) CmpAbs(*Int) int
pkg math/rand, func Shuffle(int, func(int, int))
pkg math/rand, method (*Rand) Shuffle(int, func(int, int))

	XVMODV		X3, X2, X1	// 418ce374
	XVMODBU		X3, X2, X1	// 410ce674
	XVMODHU		X3, X2, X1	// 418ce674
	XVMODWU		X3, X2, X1	// 410ce774
	XVMODVU		X3, X2, X1	// 418ce774

	// [X]VF{SQRT/RECIP/RSQRT}{F/D} instructions
	VFSQRTF		V1, V2		// 22e49c72
	VFSQRTD		V1, V2		// 22e89c72
	VFRECIPF	V1, V2		// 22f49c72
	VFRECIPD	V1, V2		// 22f89c72
	VFRSQRTF	V1, V2		// 22049d72
	VFRSQRTD	V1, V2		// 22089d72

    assertEquals(ImmutableSet.of(1, 2, 3), bimap.inverse().keySet());
    assertEquals(ImmutableSet.of(1, 2, 3), sync.inverse().keySet());
  }

  private static final Function<Integer, Double> SQRT_FUNCTION = in -> Math.sqrt(in);

  public void testTransformValues() {
    Map<String, Integer> map = ImmutableMap.of("a", 4, "b", 9);
    Map<String, Double> transformed = transformValues(map, SQRT_FUNCTION);

    assertEquals(ImmutableSet.of(1, 2, 3), bimap.inverse().keySet());
    assertEquals(ImmutableSet.of(1, 2, 3), sync.inverse().keySet());
  }

  private static final Function<Integer, Double> SQRT_FUNCTION = in -> Math.sqrt(in);

  public void testTransformValues() {
    Map<String, Integer> map = ImmutableMap.of("a", 4, "b", 9);
    Map<String, Double> transformed = transformValues(map, SQRT_FUNCTION);

        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))`

	DIVF.NE	F0, F2        // 002a821e
	DIVD	F3, F5        // 035b85ee
	NEGF	F0, F1        // 401ab1ee
	NEGD	F4, F5        // 445bb1ee
	ABSF	F0, F1        // c01ab0ee
	ABSD	F4, F5        // c45bb0ee
	SQRTF	F0, F1        // c01ab1ee
	SQRTD	F4, F5        // c45bb1ee
	MOVFD	F0, F1        // c01ab7ee
	MOVDF	F4, F5        // c45bb7ee

	LDREX	(R8), R9      // 9f9f98e1
	LDREXB	(R11), R12    // 9fcfdbe1
	LDREXD	(R11), R12    // 9fcfbbe1

  @Param InputOrder inputOrder;

  enum InputOrder {
    SORTED {
      @Override
      void arrange(List<Integer> list) {
        sort(list);
      }
    },
    ALMOST_SORTED {
      @Override
      void arrange(List<Integer> list) {
        sort(list);
        if (list.size() > 1) {
          int i = (list.size() - 1) / 2;
          Collections.swap(list, i, i + 1);
        }
      }
    },

		if len(user.Pets) != len(expect.Pets) {
			t.Fatalf("pets should equal, expect: %v, got %v", len(expect.Pets), len(user.Pets))
		}

		sort.Slice(user.Pets, func(i, j int) bool {
			return user.Pets[i].ID > user.Pets[j].ID
		})

		sort.Slice(expect.Pets, func(i, j int) bool {
			return expect.Pets[i].ID > expect.Pets[j].ID
		})

		for idx, pet := range user.Pets {

        "legend": {
          "calcs": [],
          "displayMode": "list",
          "placement": "bottom",
          "showLegend": true
        },
        "tooltip": {
          "mode": "multi",
          "sort": "none"
        }
      },
      "pluginVersion": "10.4.0",
      "targets": [
        {
          "datasource": {
            "type": "prometheus",
            "uid": "${DS_PROMETHEUS}"
          },