* decide not to by returning -1L.
 *
 * Task Queues
 * -----------
 *
 * Tasks are bound to the [TaskQueue] they are scheduled in. Each queue is sequential and the tasks
 * within it never execute concurrently. It is an error to use a task in multiple queues.
 */
abstract class Task(
  val name: String,
  val cancelable: Boolean = true,
) {
  // Guarded by the TaskRunner.
  internal var queue: TaskQueue? = null

 *
 * <p><b>Warning:</b> The caller is responsible for not attempting to read past the end of the
 * array. If any method encounters the end of the array prematurely, it throws {@link
 * IllegalStateException} to signify <i>programmer error</i>. This behavior is a technical violation
 * of the supertype's contract, which specifies a checked exception.
 *
 * @author Kevin Bourrillion
 * @since 1.0
 */
@J2ktIncompatible
@GwtIncompatible

                HttpResponse response = httpClient.execute(request);
                if(response.getStatusLine().getStatusCode() != HttpStatus.SC_OK) {
                    Logger.warn("Error response:" + response.getStatusLine().getStatusCode());
                    EntityUtils.consume(response.getEntity());
                    continue;
                }

  }

  @Test
  fun protocolErrorBeforeCloseSendsFailure() {
    server.sink.write("0a00".decodeHex()).emit() // Invalid non-final ping frame.
    client.processNextFrame() // Detects error, send close, close connection.
    taskFaker.runTasks()
    client.webSocket!!.finishReader()
    assertThat(client.closed).isTrue()
    client.listener.assertFailure(
      ProtocolException::class.java,

            doc.put("title", setting.get("title"));
            doc.put("role", "Rguest");
            doc.put("boost", setting.get("boost"));
            //            doc.put("click_count", 100);  // Validation Error
            requestBody.put("doc", doc);

            checkPostMethod(requestBody, getItemEndpointSuffix()).then().body("response.status", equalTo(0));
            refresh();
        }

        checkUpdate();

                        return false;
                    }
                } catch (RuntimeException e) {
                    problems.add(new ModelProblemCollectorRequest(Severity.ERROR, Version.BASE)
                            .setMessage("Failed to determine activation for profile " + profile.getId() + ": "
                                    + e.getMessage())

 */
@Deprecated(since = "4.0.0")
public interface SettingsProblem {

    /**
     * The different severity levels for a problem, in decreasing order.
     */
    enum Severity {
        FATAL, //
        ERROR, //
        WARNING //
    }

    /**
     * Gets the hint about the source of the problem. While the syntax of this hint is unspecified and depends on the

       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the $LD_LIBRARY_PATH environment variable.
       * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).
     * If error still persists then, apparently your CPU model does not support AVX instruction sets.
       * Refer [hardware requirements](https://www.tensorflow.org/install/pip#hardware-requirements).
   

	for scanner.Scan() {
		f := strings.Fields(scanner.Text())
		if len(f) < 3 {
			continue
		}
		syms[f[2]] = f[0]
	}
	if err := scanner.Err(); err != nil {
		t.Fatalf("error reading symbols: %v", err)
	}
	return syms
}

func runAddr2Line(t *testing.T, dbgExePath, addr string) (funcname, path, lineno string) {
	cmd := testenv.Command(t, testenv.Executable(t), dbgExePath)

    replaceWith = ReplaceWith(expression = "tlsVersions"),
    level = DeprecationLevel.ERROR,
  )
  fun tlsVersions(): List<TlsVersion>? = tlsVersions

  @JvmName("-deprecated_supportsTlsExtensions")
  @Deprecated(
    message = "moved to val",
    replaceWith = ReplaceWith(expression = "supportsTlsExtensions"),
    level = DeprecationLevel.ERROR,
  )
  fun supportsTlsExtensions(): Boolean = supportsTlsExtensions