protected C computeNext() {
        while (merged.hasNext()) {
          C next = merged.next();
          boolean duplicate = lastValue != null && comparator.compare(next, lastValue) == 0;

          // Keep looping till we find a non-duplicate value.
          if (!duplicate) {
            lastValue = next;
            return lastValue;
          }
        }

        lastValue = null; // clear reference to unused data

                                                TF_Status* status);

// This function will block till the operation that produces `h` has
// completed. This is only valid on local TFE_TensorHandles. The pointer
// returned will be on the device in which the TFE_TensorHandle resides (so e.g.
// for a GPU tensor this will return a pointer to GPU memory). The pointer is

	// Object operations.

	// GetObjectNInfo returns a GetObjectReader that satisfies the
	// ReadCloser interface. The Close method runs any cleanup
	// functions, so it must always be called after reading till EOF
	//
	// IMPORTANTLY, when implementations return err != nil, this
	// function MUST NOT return a non-nil ReadCloser.

  }
  ~GraphOperation() override {}

 private:
  friend class GraphContext;  // For access to op_.
  TF_Graph* g_;
  std::unique_ptr<TF_OperationDescription> op_;
  // Hold `op_type` and `op_name` till both are available since we need both
  // to build a graph operation.
  string op_type_;
  const char* op_name_ = nullptr;
  // TODO(srbs): Use this.
  string device_name_;
};

    retry docker exec "${CLUSTER_NAME}"-control-plane bash -c "sysctl -w kernel.core_pattern=/var/lib/istio/data/core.proxy && ulimit -c unlimited"
  }

  # Now deploy the specified number of KinD clusters and
  # wait till they are provisioned successfully.
  declare -a DEPLOY_KIND_JOBS
  for i in "${!CLUSTER_NAMES[@]}"; do
    deploy_kind "${i}" & DEPLOY_KIND_JOBS+=("${!}")
  done

  for pid in "${DEPLOY_KIND_JOBS[@]}"; do

  buf->Unref();
  return tensorflow::wrap(tensorflow::TensorHandle::CreateLocalHandle(
      std::move(t), device, device, context));
}

// This function will block till the operation that produces `h` has
// completed. This is only valid on local TFE_TensorHandles. Returns the size in
// bytes of the memory pointed to by the device pointer returned above.

// ARN
func (s *replicationResyncer) resyncBucket(ctx context.Context, objectAPI ObjectLayer, heal bool, opts resyncOpts) {
	select {
	case <-s.workerCh: // block till a worker is available
	case <-ctx.Done():
		return
	}

	resyncStatus := ResyncFailed
	defer func() {
		s.markStatus(resyncStatus, opts, objectAPI)

			expectedRespStatus: http.StatusRequestedRangeNotSatisfiable,
		},
		// Test case - 5.
		// Test case with byte range exceeding the object size.
		// Expected to read till end of the object.
		{
			bucketName: bucketName,
			objectName: objectName,
			byteRange:  "bytes=10-1000000000000000",
			accessKey:  credentials.AccessKey,
			secretKey:  credentials.SecretKey,

	data := "1234567890"
	// seed the random number generator once.
	rand.Seed(3)
	// generate a random number between 13 and 200.
	randInt := getRandomRange(13, 200, -1)
	// write into buffer till length of the buffer is greater than the generated random number.
	for i := 0; i <= randInt; i += 10 {
		buffer.WriteString(data)
	}
	// String content which is used for put object range test.

    update your imports accordingly, the old files will be removed in Release
    2.11.
*   `tf.keras.optimizers.experimental.Optimizer` will graduate in Release 2.11,
    which means `tf.keras.optimizers.Optimizer` will be an alias of
    `tf.keras.optimizers.experimental.Optimizer`. The current
    `tf.keras.optimizers.Optimizer` will continue to be supported as
    `tf.keras.optimizers.legacy.Optimizer`,