* good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *
 * <p>This implementation consumes significantly less memory than {@code java.util.LinkedHashSet} or
 * even {@code java.util.HashSet}, and places considerably less load on the garbage collector. Like

void TF_OutputListSetNumOutputs(TF_OutputList* o, int num_outputs,
                                TF_Status* s) {
  unwrap(o)->expected_num_outputs = num_outputs;
  unwrap(o)->outputs.clear();
  unwrap(o)->outputs.resize(num_outputs);
}
int TF_OutputListNumOutputs(TF_OutputList* o) {
  return unwrap(o)->outputs.size();
}
TF_AbstractTensor* TF_OutputListGet(TF_OutputList* o, int i) {
  return wrap(unwrap(o)->outputs[i]);
}

:(!/^([a-zA-Z:]*\/\/)/.test(e)&&!r||e.replace(RegExp.$1,"").split("/")[0]===a.location.host)&&("//"===e.substring(0,2)&&(e=a.location.protocol+e),d.push({href:e,media:f})))}w()};x(),c.update=x,c.getEmValue=t,a.addEventListener?a.addEventListener("resize",b,!1):a.attachEvent&&a.attachEvent("onresize",b)}}(this);...

 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>As compared with {@link java.util.LinkedHashMap}, this structure places significantly reduced
 * load on the garbage collector by only using a constant number of internal objects.
 *

   * (UNSET).
   */
  @VisibleForTesting transient long[] entries;

  /** The load factor. */
  private transient float loadFactor;

  /** When we have this many elements, resize the hashtable. */
  private transient int threshold;

  /** Constructs a new empty instance of {@code ObjectCountHashMap}. */
  ObjectCountHashMap() {
    init(DEFAULT_SIZE, DEFAULT_LOAD_FACTOR);
  }

PSED)) {\n      this.expand()\n    } else {\n      this.collapse()\n    }\n  }\n\n  autoCollapse(resize = false) {\n    if (!this._options.autoCollapseSize) {\n      return\n    }\n\n    const $bodySelector = $(SELECTOR_BODY)\n\n    if ($(window).width() <= this._options.autoCollapseSize) {\n      if (!$bodySelector.hasClass(CLASS_NAME_OPEN)) {\n        this.collapse()\n      }\n    } else if (resize === true) {\n      if ($bodySelector.hasClass(CLASS_NAME_OPEN)) {\n        $bodySelector.removeC...

update the popper position\n * @method\n * @memberof Popper.Utils\n * @private\n */\nexport default function setupEventListeners(\n  reference,\n  options,\n  state,\n  updateBound\n) {\n  // Resize event listener on window\n  state.updateBound = updateBound;\n  getWindow(reference).addEventListener('resize', state.updateBound, { passive: true });\n\n  // Scroll event listener on scroll parents\n  const scrollElement = getScrollParent(reference);\n  attachToScrollParents(\n    scrollElement,\n  ...

p:!0,keyboard:!0,focus:!0,show:!0},ae={backdrop:"(boolean|string)",keyboard:"boolean",focus:"boolean",show:"boolean"},le={HIDE:"hide"+oe,HIDE_PREVENTED:"hidePrevented"+oe,HIDDEN:"hidden"+oe,SHOW:"show"+oe,SHOWN:"shown"+oe,FOCUSIN:"focusin"+oe,RESIZE:"resize"+oe,CLICK_DISMISS:"click.dismiss"+oe,KEYDOWN_DISMISS:"keydown.dismiss"+oe,MOUSEUP_DISMISS:"mouseup.dismiss"+oe,MOUSEDOWN_DISMISS:"mousedown.dismiss"+oe,CLICK_DATA_API:"click"+oe+".data-api"},ce="modal-dialog-scrollable",he="modal-scrollbar-me...

r||M(n(p.parentNode),t,o,i),i.push(p)}function F(e,t,o,i){o.updateBound=i,A(e).addEventListener('resize',o.updateBound,{passive:!0});var r=n(e);return M(r,'scroll',o.updateBound,o.scrollParents),o.scrollElement=r,o.eventsEnabled=!0,o}function I(){this.state.eventsEnabled||(this.state=F(this.reference,this.options,this.state,this.scheduleUpdate))}function R(e,t){return A(e).removeEventListener('resize',t.updateBound),t.scrollParents.forEach(function(e){e.removeEventListener('scroll',t.updateBound...

  }

  TFE_Execute(op_.get(), unwrapped_results.data(), &real_num_outputs, status);
  if (TF_GetCode(status) != TF_OK) {
    cancellation_manager_->StartCancel();
    return;
  }
  unwrapped_results.resize(real_num_outputs);
  outputs->reserve(real_num_outputs);
  for (TFE_TensorHandle* unwrapped_result : unwrapped_results) {
    outputs->emplace_back(unwrapped_result);
  }
}