}

  static final ImmutableSet<Double> INTEGRAL_DOUBLE_CANDIDATES;
  static final ImmutableSet<Double> FRACTIONAL_DOUBLE_CANDIDATES;
  static final Iterable<Double> INFINITIES =
      Doubles.asList(Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY);
  static final Iterable<Double> FINITE_DOUBLE_CANDIDATES;
  static final Iterable<Double> POSITIVE_FINITE_DOUBLE_CANDIDATES;

 * you would expect.
 *
 * <p>If required to do a weighted average between an infinity and a finite value, or between an
 * infinite value and itself, the infinite value is returned. If required to do a weighted average
 * between {@link Double#NEGATIVE_INFINITY NEGATIVE_INFINITY} and {@link Double#POSITIVE_INFINITY

*   `tf.debugging`
    *   Add `tf.debugging.enable_check_numerics()` and
        `tf.debugging.disable_check_numerics()` to help debugging the root
        causes of issues involving infinities and `NaN`s.
*   `tf.distribute`
    *   Custom training loop support on TPUs and TPU pods is available through
        `strategy.experimental_distribute_dataset`,

    PAST(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO),
    FUTURE(Timeout.SMALL, Timeout.MAX),
    SMALL(Timeout.SMALL),
    FINITE(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO, Timeout.SMALL),
    INFINITE(Timeout.LARGE, Timeout.MAX);

    final ImmutableList<Timeout> timeouts;

    TimeoutsToUse(Timeout... timeouts) {
      this.timeouts = ImmutableList.copyOf(timeouts);
    }
  }

    PAST(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO),
    FUTURE(Timeout.SMALL, Timeout.MAX),
    SMALL(Timeout.SMALL),
    FINITE(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO, Timeout.SMALL),
    INFINITE(Timeout.LARGE, Timeout.MAX);

    final ImmutableList<Timeout> timeouts;

    TimeoutsToUse(Timeout... timeouts) {
      this.timeouts = ImmutableList.copyOf(timeouts);
    }
  }

    cancelled = await _run_asgi_and_cancel(app, "/stream-raw", timeout=3.0)
    # The key assertion: we reached this line at all (didn't hang).
    # cancelled will be True because the infinite generator was interrupted.
    assert cancelled


async def test_jsonl_stream_cancellation() -> None:
    """JSONL streaming endpoint should be cancellable within a reasonable time."""

.status-lozenge.status-ready {
    background-color: #dfe1e6;
    color: #42526e;
}

.status-lozenge.status-thinking {
    background-color: #deebff;
    color: #0052cc;
    animation: lozenge-pulse 2s ease-in-out infinite;
}

.status-lozenge.status-error {
    background-color: #ffebe6;
    color: #de350b;
}

.status-lozenge.status-success {
    background-color: #e3fcef;
    color: #00875a;
}

    Client->>Client: Process Item 2
    App->>Client: Send Item 3
    Client->>Client: Process Item 3
    Note over App: Keeps producing...
    Note over Client: Keeps consuming...
```

It could even be an infinite stream, where you keep sending data.

## JSON Lines { #json-lines }

In these cases, it's common to send "**JSON Lines**", which is a format where you send one JSON object per line.

Integrations and "plug-ins" can be built using the **Dependency Injection** system. But in fact, there is actually **no need to create "plug-ins"**, as by using dependencies it's possible to declare an infinite number of integrations and interactions that become available to your *path operation functions*.

Como este pequeño ejemplo no necesita ninguna sentencia `await`, añadimos un `await anyio.sleep(0)` para darle al loop de eventos la oportunidad de manejar la cancelación.

Esto sería aún más importante con streams grandes o infinitos.

///

/// tip | Consejo