context = browser.new_context(viewport={"width": 960, "height": 1080})
    page = context.new_page()
    page.goto("http://localhost:8000/docs")
    page.get_by_role("button", name="Item-Input").click()
    page.get_by_role("button", name="Item-Output").click()
    page.set_viewport_size({"width": 960, "height": 820})
    page.screenshot(

struct TFE_Executor {
  explicit TFE_Executor(bool async, bool enable_streaming_enqueue,
                        int in_flight_nodes_limit)
      : owned_executor(new tensorflow::EagerExecutor(
            async, enable_streaming_enqueue, in_flight_nodes_limit)) {}

  explicit TFE_Executor(tensorflow::EagerExecutor* executor)
      : owned_executor(nullptr), unowned_executor(executor) {}

    browser = playwright.chromium.launch(headless=False)
    context = browser.new_context(viewport={"width": 960, "height": 1080})
    page = context.new_page()
    page.goto("http://localhost:8000/docs")
    page.get_by_role("button", name="Item", exact=True).click()
    page.set_viewport_size({"width": 960, "height": 700})
    page.screenshot(
        path="docs/en/docs/img/tutorial/separate-openapi-schemas/image05.png"
    )

    final int weight;

    WeightedWeakValueReference(
        ReferenceQueue<V> queue, V referent, ReferenceEntry<K, V> entry, int weight) {
      super(queue, referent, entry);
      this.weight = weight;
    }

    @Override
    public int getWeight() {
      return weight;
    }

    @Override
    public ValueReference<K, V> copyFor(

  flex-wrap: wrap;
  margin-bottom: 2rem;
}

.user-list-center {
  justify-content: space-evenly;
}

.user {
  margin: 1em;
  min-width: 7em;
}

.user .avatar-wrapper {
  width: 80px;
  height: 80px;
  margin: 10px auto;
  overflow: hidden;
  border-radius: 50%;
  position: relative;
}

.user .avatar-wrapper img {
  position: absolute;
  top: 50%;
  left: 50%;

 * prevention and <i>no</i> expectation of bit dispersion. This leaves them perfectly suitable for
 * use in hash tables, because extra collisions cause only a slight performance hit, while poor bit
 * dispersion is easily corrected using a secondary hash function (which all reasonable hash table
 * implementations in Java use). For the many uses of hash functions beyond data structures,

end }} {{- range $key, $val := $nodeSelector }} - key: {{ $key }} operator: In values: - {{ $val | quote }} {{- end }} {{- end }} {{- end }} {{- define "nodeAffinityPreferre" }} {{- range $key, $val := .global.arch }} {{- if gt ($val | int) 0 }} - weight: {{ $val | int }} preference: matchExpressions: - key: kubernetes.io/arch operator: In values: - {{ $key | quote }} {{- end }} {{- end }} {{- end }} {{- define "podAntiAffinity" }} {{- if or .podAntiAffinityLabel .podAntiAffinityTermL}} podAntiAffinity:...

    assertThat(keySet).containsExactly(0, 1, 2, 3, 4, 5, 6, 7, 8, 9);

    // add an at-the-maximum-weight entry
    getAll(cache, asList(45));
    CacheTesting.drainRecencyQueues(cache);
    assertThat(keySet).containsExactly(0, 45);

    // add an over-the-maximum-weight entry
    getAll(cache, asList(46));
    CacheTesting.drainRecencyQueues(cache);
    assertThat(keySet).contains(0);
  }

 */
@GwtCompatible
@FunctionalInterface
@ElementTypesAreNonnullByDefault
public interface Weigher<K, V> {

  /**
   * Returns the weight of a cache entry. There is no unit for entry weights; rather they are simply
   * relative to each other.
   *
   * @return the weight of the entry; must be non-negative
   */
  int weigh(K key, V value);

 );\n\n  const rects = {\n    top: {\n      width: boundaries.width,\n      height: refRect.top - boundaries.top,\n    },\n    right: {\n      width: boundaries.right - refRect.right,\n      height: boundaries.height,\n    },\n    bottom: {\n      width: boundaries.width,\n      height: boundaries.bottom - refRect.bottom,\n    },\n    left: {\n      width: refRect.left - boundaries.left,\n      height: boundaries.height,\n    },\n  };\n\n  const sortedAreas = Object.keys(rects)\n    .map(key => ({\n...