* than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to
     * ensure that completed write operations performed by other threads are noticed. For most
     * purposes, the "count" field, tracking the number of elements, serves as that volatile

  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.
size_t TFE_TensorHandleDeviceMemorySize(TFE_TensorHandle* h,

func (p *xlStorageDiskIDCheck) monitorDiskWritable(ctx context.Context) {
	var (
		// We check every 15 seconds if the disk is writable and we can read back.
		checkEvery = 15 * time.Second

		// If the disk has completed an operation successfully within last 5 seconds, don't check it.
		skipIfSuccessBefore = 5 * time.Second
	)

	// if disk max timeout is smaller than checkEvery window
	// reduce checks by a second.

     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to
     * ensure that completed write operations performed by other threads are noticed. For most
     * purposes, the "count" field, tracking the number of elements, serves as that volatile

     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to
     * ensure that completed write operations performed by other threads are noticed. For most
     * purposes, the "count" field, tracking the number of elements, serves as that volatile

    assertThat(actual).isEqualTo(expected)
  }

  /**
   * Returns true when all work currently in progress by the watchdog have completed. This method
   * creates more work for the watchdog and waits for that work to be executed. When it is, we know
   * work that preceded this call is complete.
   */
  private fun awaitWatchdogIdle() {
    val latch = CountDownLatch(1)
    val watchdogJob: AsyncTimeout =

	}

	var buf bytes.Buffer
	r, err := obj.GetObjectNInfo(context.Background(), bucketName, testObject, nil, nil, ObjectOptions{})
	if err != nil {
		t.Fatalf("Test %s: reading completed file failed: <ERROR> %v", instanceType, err)
	}
	if _, err = io.Copy(&buf, r); err != nil {
		r.Close()
		t.Fatalf("Test %s: Failed to fetch the copied object: <ERROR> %s", instanceType, err)
	}
	r.Close()

	// limit (8KB), we stop growing the source string once the limit
	// is reached and keep reusing the same source string - that
	// should therefore be always resident in the L1 cache - until we
	// have completed the construction of the result.
	// This yields significant speedups (up to +100%) in cases where
	// the result length is large (roughly, over L2 cache size).
	const chunkLimit = 8 * 1024
	chunkMax := n

// This operation lists in-progress multipart uploads. An in-progress
// multipart upload is a multipart upload that has been initiated,
// using the Initiate Multipart Upload request, but has not yet been
// completed or aborted. This operation returns at most 1,000 multipart
// uploads in the response.
func (api objectAPIHandlers) ListMultipartUploadsHandler(w http.ResponseWriter, r *http.Request) {

    // the connection flow-control window so new requests can proceed.
    call1.cancel()
    assertThat(
      response1.body.source().discard(1, TimeUnit.SECONDS),
      "Call should not have completed successfully.",
    ).isFalse()
    val call2 = client.newCall(Request(server.url("/")))
    val response2 = call2.execute()
    assertThat(response2.body.string()).isEqualTo("abc")
  }