```
Client #1596980209979 left the chat
```

/// tip

The app above is a minimal and simple example to demonstrate how to handle and broadcast messages to several WebSocket connections.

But keep in mind that, as everything is handled in memory, in a single list, it will only work while the process is running, and will only work with a single process.

    return nullptr;
  }
  tensorflow::TensorHandle* handle =
      tensorflow::TensorHandleFromInterface(unwrapped_handle);

  if (handle->Type() != tensorflow::TensorHandle::LOCAL) {
    status->status = tensorflow::errors::InvalidArgument(
        "TFE_TensorHandleDevicePointer may not be called on a ",
        handle->TypeString(), " tensor handle.");
    return nullptr;

* Cluster Autoscaler 1.0.0 ([#53005](https://github.com/kubernetes/kubernetes/pull/53005), [@mwielgus](https://github.com/mwielgus))
* Remove the --docker-exec-handler flag. Only native exec handler is supported. ([#52287](https://github.com/kubernetes/kubernetes/pull/52287), [@yujuhong](https://github.com/yujuhong))

#### CRD Watcher

    }
    return makeHash();
  }

  /**
   * Computes a hash code based on the data that have been provided to this hasher. This is called
   * after all chunks are handled with {@link #process} and any leftover bytes that did not make a
   * complete chunk are handled with {@link #processRemaining}.
   */
  protected abstract HashCode makeHash();

  // Process pent-up data in chunks
  private void munchIfFull() {

    tensorflow::ImmediateExecutionTensorHandle* unwrapped_handle =
        tensorflow::unwrap(handles[i]);
    if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) {
      // One of the inputs we're trying to pack is on a custom device. We'll let
      // the first custom device we see handle all of the packing.
      auto* custom_device_handle =

  virtual ImmediateExecutionContext* GetContext() const = 0;

  // Following two methods are used to support custom device.
  // Return true if the inputs contain custom device tensor handle. It means
  // that the argument need to be handled by a custom device.
  virtual bool HasCustomDeviceInput() const = 0;

  virtual const tensorflow::OpDef* OpDef() const = 0;

// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package handlers

import (
	"context"
	"net"
	"net/http"
	"net/http/httputil"
	"net/url"
	"strings"
	"sync"
	"time"
)

const defaultFlushInterval = time.Duration(100) * time.Millisecond

// Create a packed TensorHandle with the given list of TensorHandles.
// If `handles` are on the same device, assign the same device to the packed
// handle; if `handles` are on different deivces, assign a CompositeDevice to
// it.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_CreatePackedTensorHandle(
    TFE_Context* ctx, TFE_TensorHandle** handles, int* num_handles,
    TF_Status* status);

This process can take some time, especially when coordination is required with maintainers of other projects.
Every effort will be made to handle the bug in as timely a manner as possible, however it's important that we