* 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

                                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]);
}

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.
 *

    if (newEntryIndex == Integer.MAX_VALUE) {
      throw new IllegalStateException("Cannot contain more than Integer.MAX_VALUE elements!");
    }
    int newSize = newEntryIndex + 1;
    resizeMeMaybe(newSize);
    insertEntry(newEntryIndex, key, value, hash);
    this.size = newSize;
    if (newEntryIndex >= threshold) {
      resizeTable(2 * table.length);
    }
    modCount++;
    return 0;
  }

  /**

else if (unit === 'vh' || unit === 'vw') {\n    // if is a vh or vw, we calculate the size based on the viewport\n    let size;\n    if (unit === 'vh') {\n      size = Math.max(\n        document.documentElement.clientHeight,\n        window.innerHeight || 0\n      );\n    } else {\n      size = Math.max(\n        document.documentElement.clientWidth,\n        window.innerWidth || 0\n      );\n    }\n    return size / 100 * value;\n  } else {\n    // if is an explicit pixel unit, we get rid of the unit...

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...

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...

  for (int device_index = 0; device_index < underlying_devices_.size();
       ++device_index) {
    DeviceThread* device_thread = device_threads_[device_index].get();
    std::vector<TFE_TensorHandle*> device_inputs;
    device_inputs.reserve(inputs.size());
    for (int input_index = 0; input_index < inputs.size(); ++input_index) {
      // Parallel tensors are divided between operations by device.