- Previously, when trying to allocate devices through DRA for a node timed out, scheduling would proceed with another node if any had the necessary resources. This potentially hid that a node was ignored. Worse, if scheduling was slow overall, the pod was incorrectly moved to "unschedulable" and only retried after a periodic sweep. Now timeouts are errors that are always visible as pod scheduling...

Thus <code>0(FP)</code> is the first argument to the function,
<code>8(FP)</code> is the second (on a 64-bit machine), and so on.
However, when referring to a function argument this way, it is necessary to place a name
at the beginning, as in <code>first_arg+0(FP)</code> and <code>second_arg+8(FP)</code>.
(The meaning of the offset—offset from the frame pointer—distinct

      keys[size] = key;
      values[size] = value;
      size++;
      return this;
    }

    /**
     * Adds the given {@code entry} to the map, making it immutable if necessary. Duplicate keys,
     * according to the comparator (which might be the keys' natural order), are not allowed, and
     * will cause {@link #build} to fail.
     *
     * @since 11.0
     */

`tensorflow` pip package has a new, optional installation method for Linux that installs necessary Nvidia CUDA libraries through pip. As long as the Nvidia driver is already installed on the system, you may now run `pip install tensorflow[and-cuda]` to install TensorFlow's Nvidia CUDA library dependencies in the Python environment. Aside from the Nvidia driver, no other pre-existing Nvidia CUDA packages are necessary.

*   Enable JIT-compiled i64-indexed kernels on GPU for large tensors with...

// using a delete-marker and MetaSys entries. It's used to track tiered content of a
// deleted/overwritten version. This version is visible _only_to the scanner routine, for subsequent deletion.
// This kind of tracking is necessary since a version's tiered content is deleted asynchronously.

// Backend directory tree structure:
// disk1/
// └── bucket
//     └── object
//         ├── a192c1d5-9bd5-41fd-9a90-ab10e165398d

    val framesThatFillWindow =
      roundUp(Settings.DEFAULT_INITIAL_WINDOW_SIZE, peer.maxOutboundDataLength())

    // Write the mocking script. This accepts more data frames than necessary!
    peer.sendFrame().settings(Settings())
    peer.acceptFrame() // SETTINGS ACK
    peer.acceptFrame() // SYN_STREAM on stream 1
    for (i in 0 until framesThatFillWindow) {

	// bucket.Methods(http.MethodPut).Path("/{object:.+}").HeadersRegexp("X-Amz-Copy-Source", ".*?(\\/|%2F).*?").HandlerFunc(api.CopyObjectPartHandler).Queries("partNumber", "{partNumber:[0-9]+}", "uploadId", "{uploadId:.*}")
	// Its necessary to set the "X-Amz-Copy-Source" header for the request to be accepted by the handler.
	nilReq.Header.Set("X-Amz-Copy-Source", url.QueryEscape(SlashSeparator+nilBucket+SlashSeparator+nilObject))

* Implementers of the cloud provider interface will note the addition of a context to this interface. Trivial code modification will be necessary for a cloud provider to continue to compile. ([#59287](https://github.com/kubernetes/kubernetes/pull/59287), [@cheftako](https://github.com/cheftako))

 * for each class that is used in a list</li>
 * </ul>
 * Code is written like it could be generated, with default behaviour to be overridden when necessary.
 * This is particularly the case for <code>Object get<i>Classname</i>Key( <i>Classname</i> <i>classname</i> )</code>
 * method, which by default return the object itself and is expected to be overridden to calculate better suited key

  * After your master is upgraded to 1.6, you will need to update your PodSpecs to set the `tolerations` field of the PodSpec and remove the `scheduler.alpha.kubernetes.io/tolerations` annotation on the Pod. (It's not strictly necessary to remove the annotation, as it will have no effect once you upgrade to 1.6.) Between the time the master is upgraded to 1.6 and when you do this, tolerations attached to Pods that are created will have no effect. Pods that are already running will...