auto it = block.rbegin();
  YieldOp yield = dyn_cast<YieldOp>(*it++);

  if (it == block.rend()) return std::nullopt;

  // Operation which is expected to consume all the call results.
  Operation* call_consumer = yield;

  // Allow a single ToBoolOp between the call and the yield (valid only
  // when the yield has a single operand)
  if (allow_to_bool && yield.getNumOperands() == 1 && isa<ToBoolOp>(*it)) {

  func.return
}

// -----

// Check that a tf_executor.yield parent is a tf_executor.island.
func.func @parent_is_island() {
  "tf.some_op"() ({
    tf_executor.yield
// expected-error@-1 {{'tf_executor.yield' op expects parent op 'tf_executor.island'}}
  }) : () -> ()
  func.return
}

// -----

// Check that an island yield matches the island results.

        %4 = "tf.B"(%2) : (tensor<?xi32>) -> tensor<?xi32>
        tf_device.return %4 : tensor<?xi32>
      }) {device = "/device:test_device:0"} : () -> tensor<?xi32>

      // CHECK: tf_executor.yield %[[LAUNCH_OUTPUT]]
      tf_executor.yield %3 : tensor<?xi32>
    }
    tf_executor.fetch %1#0 : tensor<?xi32>
  }
  func.return %0 : tensor<?xi32>
}

// CHECK: func private @[[LAUNCH]]

### Lifespan-Funktion

Das Erste, was auffällt, ist, dass wir eine asynchrone Funktion mit `yield` definieren. Das ist sehr ähnlich zu Abhängigkeiten mit `yield`.

```Python hl_lines="14-19"
{!../../../docs_src/events/tutorial003.py!}
```

Der erste Teil der Funktion, vor dem `yield`, wird ausgeführt **bevor** die Anwendung startet.

Und der Teil nach `yield` wird ausgeführt, **nachdem** die Anwendung beendet ist.

### Asynchroner Kontextmanager

	}
	m2 := (*T).PM
	for range m2 /* ERROR "cannot range over m2 (variable of type func(*T)): func must be func(yield func(...) bool): argument is not func" */ {
	}
	for range f1 /* ERROR "cannot range over f1 (value of type func()): func must be func(yield func(...) bool): wrong argument count" */ {
	}

A primeira coisa a notar, é que estamos definindo uma função assíncrona com `yield`. Isso é muito semelhante à Dependências com `yield`.

```Python hl_lines="14-19"
{!../../../docs_src/events/tutorial003.py!}
```

A primeira parte da função, antes do `yield`, será  executada **antes** da aplicação inicializar.

E a parte posterior do `yield` irá executar **após** a aplicação ser encerrada.

### Gerenciador de Contexto Assíncrono

```Python hl_lines="14-19"
{!../../../docs_src/events/tutorial003.py!}
```

The first part of the function, before the `yield`, will be executed **before** the application starts.

And the part after the `yield` will be executed **after** the application has finished.

### Async Context Manager

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// Use of public API is ok.

package main

import (
	"iter"
	"unique"
)

func seq(yield func(int) bool) {
	yield(123)
}

var s = "hello"

func main() {
	h := unique.Make(s)
	next, stop := iter.Pull(seq)
	defer stop()
	println(h.Value())
	println(next())
	println(next())

  OpBuilder builder(&island.GetBody(), island.GetBody().begin());
  tf_executor::YieldOp yield = island.GetYield();
  if (yield.getNumOperands() == 0) {
    builder.create<TF::NoOp>(island.getLoc(), TypeRange{}, ValueRange{});
  } else if (yield.getNumOperands() == 1) {
    Value operand = yield.getOperand(0);
    auto identity = builder.create<TF::IdentityOp>(island.getLoc(),

    %1 = "tf.WhileRegion"(%0) ({
       // Condition region
       // CHECK: ^bb
       // CHECK: "tf.Yield"
       ^bb0(%carg0: tensor<i32>):
          %c0 = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
          %c1 = "tf.GreaterEqual"(%carg0, %0) {T = i32, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i1>
          "tf.Yield"(%c1) : (tensor<i1>) -> ()
      }, {
       // Body region
       // CHECK: ^bb0