And in she went.

  Once more she found herself in the long hall, and close to the
little glass table.  `Now, I'll manage better this time,'
she said to herself, and began by taking the little golden key,
and unlocking the door that led into the garden.  Then she went
to work nibbling at the mushroom (she had kept a piece of it
in her pocket) till she was about a foot high:  then she walked down

And in she went.

  Once more she found herself in the long hall, and close to the
little glass table.  `Now, I'll manage better this time,'
she said to herself, and began by taking the little golden key,
and unlocking the door that led into the garden.  Then she went
to work nibbling at the mushroom (she had kept a piece of it
in her pocket) till she was about a foot high:  then she walked down

  - Fix priority expander falling back to a random choice even though there is a higher priority option to choose
  - Clone `kubernetes/kubernetes` in `update-vendor.sh` shallowly, instead of fetching all revisions
  - Speed up binpacking by reducing the number of PreFilter calls (call once per pod instead of #pods*#nodes times)
  - Speed up finding unneeded nodes by 5x+ in very large clusters by reducing the number of PreFilter calls

the function completes.
(See also the section on <a href="#Handling_panics">handling panics</a>.)
</p>

<pre>
lock(l)
defer unlock(l)  // unlocking happens before surrounding function returns

// prints 3 2 1 0 before surrounding function returns
for i := 0; i &lt;= 3; i++ {
	defer fmt.Print(i)
}

// f returns 42
func f() (result int) {

  - Fix priority expander falling back to a random choice even though there is a higher priority option to choose
  - Clone `kubernetes/kubernetes` in `update-vendor.sh` shallowly, instead of fetching all revisions
  - Speed up binpacking by reducing the number of PreFilter calls (call once per pod instead of #pods*#nodes times)
  - Speed up finding unneeded nodes by 5x+ in very large clusters by reducing the number of PreFilter calls

        [example](https://github.com/tensorflow/models/blob/master/official/modeling/grad_utils.py)
        usage.
    *   Experimental support of
        [all reduce gradient packing](https://www.tensorflow.org/api_docs/python/tf/distribute/experimental/CollectiveHints)
        to allow overlapping gradient aggregation with backward path
        computation.