in early_s in Estimator
    *   Canned Estimators will now use keras optimizers by default. An error
        will be raised if tf.train.Optimizers are used, and you will have to
        switch to tf.keras.optimizers or tf.compat.v1 canned Estimators.
    *   A checkpoint converter for canned Estimators has been provided to
        transition canned Estimators that are warm started from

     */
    Integer getQueryHighlightBoundaryMaxScanAsInteger();

    /**
     * Get the value for the key 'query.highlight.boundary.scanner'. <br>
     * The value is, e.g. chars <br>
     * comment: Scanner type for query highlight boundaries.
     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */

1F950..1F95E  ; valid                  ;      ; NV8    # 9.0  CROISSANT..PANCAKES
1F95F..1F96B  ; valid                  ;      ; NV8    # 10.0 DUMPLING..CANNED FOOD
1F96C..1F970  ; valid                  ;      ; NV8    # 11.0 LEAFY GREEN..SMILING FACE WITH SMILING EYES AND THREE HEARTS
1F971         ; valid                  ;      ; NV8    # 12.0 YAWNING FACE

got %v, want %v", result, expected) } }) default: t.Fatalf("unknown key %q on line %d", k, lineNum) } } if err := scanner.Err(); err != nil { t.Fatal(err) } } func TestTotient(t *testing.T) { f, err := os.Open("testdata/gcd_lcm_tests.txt") if err != nil { t.Fatal(err) } var GCD, A, B, LCM string var lineNum int scanner := bufio.NewScanner(f) for scanner.Scan() { lineNum++ line := scanner.Text() if len(line) == 0 || line[0] == '#' { continue } k, v, _ := strings.Cut(line, " = ") switch k { case "GCD":...

- `maxThreshold` of `ImageLocality` plugin is now scaled by the number of images in the pod, which helps to distinguish the node priorities for pod with several images. ([#91138](https://github.com/kubernetes/kubernetes/pull/91138), [@chendave](https://github.com/chendave)) [SIG Scheduling]