// 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": []
      },

The steps below show how to use this notification target in `namespace` format. The other format is very similar and is omitted for brevity.

### Step 1: Ensure Elasticsearch minimum requirements are met

// 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)

        output.count('Single step transform received dependencies files [] for processing slf4j-api-1.7.24.jar') == 1
        output.count('Single step transform received dependencies files [] for processing slf4j-api-1.7.25.jar') == 1
        output.count('Single step transform received dependencies files [slf4j-api-1.7.24.jar] for processing lib.jar') == 1

// A scriptedReader is an io.Reader that executes its steps sequentially.
type scriptedReader []func(p []byte) (n int, err error)

func (sr *scriptedReader) Read(p []byte) (n int, err error) {
	if len(*sr) == 0 {
		panic("too many Read calls on scripted Reader. No steps remain.")
	}
	step := (*sr)[0]
	*sr = (*sr)[1:]
	return step(p)
}

func newScriptedReader(steps ...func(p []byte) (n int, err error)) io.Reader {

  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