* {@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))

    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);

	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);

        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

				data-bs-toggle="collapse"> <c:if test="${empty sort}">
						<la:message key="labels.searchoptions_score" />
					</c:if> <c:if test="${sort=='score.desc'}">
						<la:message key="labels.searchoptions_score" />
					</c:if> <c:if test="${sort=='filename.asc'}">
						<la:message key="labels.search_result_sort_filename_asc" />
					</c:if> <c:if test="${sort=='filename.desc'}">

				data-bs-toggle="collapse"> <c:if test="${empty sort}">
						<la:message key="labels.searchoptions_score" />
					</c:if> <c:if test="${sort=='score.desc'}">
						<la:message key="labels.searchoptions_score" />
					</c:if> <c:if test="${sort=='filename.asc'}">
						<la:message key="labels.search_result_sort_filename_asc" />
					</c:if> <c:if test="${sort=='filename.desc'}">

        }
        return null;
    }

    /**
     * Gets the sort prefix used for identifying sort parameters in search queries.
     *
     * @return the sortPrefix
     */
    public String getSortPrefix() {
        return sortPrefix;
    }

    /**
     * Sets the sort prefix used for identifying sort parameters in search queries.
     *
     * @param sortPrefix the sortPrefix to set