this._element.classList.add(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW)\n\n      this._element.style[dimension] = ''\n\n      EventHandler.trigger(this._element, EVENT_SHOWN)\n    }\n\n    const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1)\n    const scrollSize = `scroll${capitalizedDimension}`\n\n    this._queueCallback(complete, this._element, true)\n    this._element.style[dimension] = `${this._element[scrollSize]}px`\n  }\n\n  hide() {\n    if (this._isTransitioning || !this._isShown())...

   * example is when a server has just booted, and it is mostly busy with getting itself up to
   * speed).
   *
   * To deal with such scenarios, we add an extra dimension, that of "past underutilization",
   * modeled by "storedPermits" variable. This variable is zero when there is no underutilization,
   * and it can grow up to maxStoredPermits, for sufficiently large underutilization. So, the

  // Fetch the shape and validate it is 2 by -1.
  num_dims = TF_GraphGetTensorNumDims(graph, feed_out_0, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(2, num_dims);

  // Resize the dimension vector appropriately.
  int64_t returned_dims[2];
  TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(dims[0], returned_dims[0]);

        control flow.
    *   Add `RaggedTensor.numpy()`.
    *   Update `RaggedTensor.__getitem__` to preserve uniform dimensions & allow
        indexing into uniform dimensions.
    *   Update `tf.expand_dims` to always insert the new dimension as a
        non-ragged dimension.
    *   Update `tf.embedding_lookup` to use `partition_strategy` and `max_norm`
        when `ids` is ragged.

unbound persistent volumes as Metrics. This PR adds four kinds of Volume Metrics for kube-controller-manager: bound PVC numbers, unbound PVC numbers, bound PV numbers and unbound PV numbers. The PVC metrics use namespace as dimension and the PV metrics use StorageClassName as its dimension. With these metrics we can better monitor the use of volumes in the cluster. ([#57872](https://github.com/kubernetes/kubernetes/pull/57872), [@mlmhl](https://github.com/mlmhl))

* Add windows config to Kubelet...

refixes","emptyStyle","vendorProps","finalPropName","final","cssProps","capName","vendorPropName","rdisplayswap","cssShow","visibility","cssNormalTransform","letterSpacing","fontWeight","setPositiveNumber","subtract","max","boxModelAdjustment","dimension","box","isBorderBox","styles","computedVal","extra","delta","marginDelta","ceil","getWidthOrHeight","valueIsBorderBox","offsetProp","getClientRects","Tween","easing","cssHooks","opacity","animationIterationCount","aspectRatio","borderImageSlice"...

- The `apiserver_request_total` metric is promoted to stable status and no longer has a content-type dimensions, so any alerts/charts which presume the existence of this will fail. This is however, unlikely to be the case since it was effectively an unbounded dimension in the first place. ([#99788](https://github.com/kubernetes/kubernetes/pull/99788), [@logicalhan](https://github.com/logicalhan))

refixes","emptyStyle","vendorProps","finalPropName","final","cssProps","capName","vendorPropName","rdisplayswap","cssShow","visibility","cssNormalTransform","letterSpacing","fontWeight","setPositiveNumber","subtract","max","boxModelAdjustment","dimension","box","isBorderBox","styles","computedVal","extra","delta","marginDelta","ceil","getWidthOrHeight","valueIsBorderBox","offsetProp","getClientRects","Tween","easing","cssHooks","opacity","animationIterationCount","aspectRatio","borderImageSlice"...

\",\"data\":{\"label\":\"Query Count\",\"id\":\"1\"},\"valueAxis\":\"ValueAxis-1\",\"drawLinesBetweenPoints\":true,\"showCircles\":true}],\"addTooltip\":true,\"addLegend\":true,\"legendPosition\":\"right\",\"times\":[],\"addTimeMarker\":false,\"dimensions\":{\"x\":{\"accessor\":0,\"format\":{\"id\":\"date\",\"params\":{\"pattern\":\"HH:mm\"}},\"params\":{\"date\":true,\"interval\":\"PT10M\",\"format\":\"HH:mm\",\"bounds\":{\"min\":\"2019-07-28T10:40:08.271Z\",\"max\":\"2019-07-30T10:40:08.271Z\"...

void Range(vector<int32_t>* data, int32_t start, int32_t end,
           int32_t step = 1) {
  for (int32_t i = start; i < end; i += step) {
    (*data)[i] = i;
  }
}

// Fills out_dims with the dimensions of the given tensor.
void GetDims(const TF_Tensor* t, int64_t* out_dims) {
  int num_dims = TF_NumDims(t);
  for (int i = 0; i < num_dims; i++) {
    out_dims[i] = TF_Dim(t, i);
  }
}