// Step 1 is not cancelled because it was done.
    assertWithMessage("step1.statusFuture().isCancelled()")
        .that(step1.statusFuture().isCancelled())
        .isFalse();
    // But its closeable is closed.
    assertClosed(closeable1);

    // Step 2 is cancelled because it wasn't complete.
    assertWithMessage("step2.statusFuture().isCancelled()")
        .that(step2.statusFuture().isCancelled())
        .isTrue();

    // Step 1 is not cancelled because it was done.
    assertWithMessage("step1.statusFuture().isCancelled()")
        .that(step1.statusFuture().isCancelled())
        .isFalse();
    // But its closeable is closed.
    assertClosed(closeable1);

    // Step 2 is cancelled because it wasn't complete.
    assertWithMessage("step2.statusFuture().isCancelled()")
        .that(step2.statusFuture().isCancelled())
        .isTrue();

                  "text": "N/A"
                }
              },
              "type": "special"
            }
          ],
          "thresholds": {
            "mode": "percentage",
            "steps": [
              {
                "color": "green",
                "value": null
              }
            ]
          },
          "unit": "dtdurations"
        },
        "overrides": []
      },

// Conditional for step 2
C_2 = cond(args_2)

new_while_body (new_args) {  // starts at i==2
   // Finish step i-2
   B_im2 = backward(args_im2, N_im2, F_im2, T_im2)

   // Advance step i-1
   T_im1 = core_tpu(args_im1, N_im1, F_im1)

   // Finish the update of args_2
   args_i = args_2b = update_args(args_2a, T_im1)

   // Start step i
   N_i = non_tpu(args_i)
   F_i = forward(args_i, N_i)

  let description = [{
writer: Handle of `SummaryWriter`.
step: The step to write the summary for.
tensor: A scalar string of the serialized tf.GraphDef proto.
  }];

  let arguments = (ins
    Arg<TF_ResourceTensor, "", [TF_SummaryWrite]>:$writer,
    TF_Int64Tensor:$step,
    TF_StrTensor:$tensor
  );

  let results = (outs);
}

 public:
  explicit AndRecurrencePredicate(int64_t id, Predicate* start, Predicate* step,
                                  std::vector<string> frame)
      : Predicate(id), operands_({start, step}), frame_(std::move(frame)) {}

  Predicate* start() const { return operands_[0]; }
  Predicate* step() const { return operands_[1]; }
  absl::Span<const string> frame() const { return frame_; }

        Doc(
            """
            'Whitelist' validation step. The parameter field will be the single one
            allowed by the alias or set of aliases defined.
            """
        ),
    ] = None,
    serialization_alias: Annotated[
        Union[str, None],
        Doc(
            """
            'Blacklist' validation step. The vanilla parameter field will be the

		}
	}

	// Step 7: For containers in podContainerChanges.ContainersToUpdate[CPU,Memory] list, invoke UpdateContainerResources
	if isInPlacePodVerticalScalingAllowed(pod) {
		if len(podContainerChanges.ContainersToUpdate) > 0 || podContainerChanges.UpdatePodResources {
			m.doPodResizeAction(pod, podStatus, podContainerChanges, result)
		}
	}

				}
			default:
				t.Fatalf("[%s] Unexpected container: %+v", step, c)
			}
		}
		if status.Conditions[0].Type != v1.PodReady {
			t.Fatalf("[%s] Unexpected condition: %+v", step, status.Conditions[0])
		} else if ready := (status.Conditions[0].Status == v1.ConditionTrue); ready != podReady {

			restartCount = count
		}
	}
	return restartCount, nil
}

// startContainer starts a container and returns a message indicates why it is failed on error.
// It starts the container through the following steps:
// * pull the image
// * create the container
// * start the container
// * run the post start lifecycle hooks (if applicable)