}
	return args, tokens
}

// invokeMacro pushes onto the input Stack a Slice that holds the macro definition with the actual
// parameters substituted for the formals.
// Invoking a macro does not touch the PC/line history.
func (in *Input) invokeMacro(macro *Macro) {
	// If the macro has no arguments, just substitute the text.
	if macro.args == nil {
		in.Push(NewSlice(in.Base(), in.Line(), macro.tokens))
		return
	}

# to build TensorFlow. Look at ci/official/envs to find which types of jobs
# push to the cache.  For macOS, use --config=tf_public_macos_cache
build:tf_public_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/january2024" --remote_upload_local_results=false
# Cache pushes are limited to TF's CI system.

  public void testSplitterIterableIsLazy_pattern() {
    if (!CommonPattern.isPcreLike()) {
      return;
    }
    assertSplitterIterableIsLazy(Splitter.onPattern(","));
  }

  /**
   * This test really pushes the boundaries of what we support. In general the splitter's behaviour
   * is not well defined if the char sequence it's splitting is mutated during iteration.
   */

		return false
	}
	return !h.endTime.IsZero()
}

// stops the heal sequence - safe to call multiple times.
func (h *healSequence) stop() {
	h.cancelCtx()
}

// pushHealResultItem - pushes a heal result item for consumption in
// the heal-status API. It blocks if there are
// maxUnconsumedHealResultItems. When it blocks, the heal sequence
// routine is effectively paused - this happens when the server has

	w.imported[name] = pkg
	return pkg, nil
}

// pushScope enters a new scope (walking a package, type, node, etc)
// and returns a function that will leave the scope (with sanity checking
// for mismatched pushes & pops)
func (w *Walker) pushScope(name string) (popFunc func()) {
	w.scope = append(w.scope, name)
	return func() {
		if len(w.scope) == 0 {
			log.Fatalf("attempt to leave scope %q with empty scope list", name)

        id: date
      -
        name: Build containers, and push to GCR only if the 'build and push to gcr.io for staging' label is applied
        id: docker_build
        uses: docker/build-push-action@4f58ea79222b3b9dc2c8bbdd6debcef730109a75 # v6.9.0
        with:
          push: ${{ contains(github.event.pull_request.labels.*.name, 'build and push to gcr.io for staging') }}
          context: ./tensorflow/tools/tf_sig_build_dockerfiles

Pero aún quieres poder filtrar y convertir los datos que retornas con un `response_model`.

Para esos casos, puedes usar un parámetro `Response`.

## Usar un parámetro `Response`

Puedes declarar un parámetro de tipo `Response` en tu *función de la operación de path* (como puedes hacer para cookies y headers).

Y luego puedes establecer el `status_code` en ese objeto de respuesta *temporal*.

```Python hl_lines="1  9  12"

# Parámetros de Cookie

Puedes definir parámetros de Cookie de la misma manera que defines parámetros de `Query` y `Path`.

## Importar `Cookie`

Primero importa `Cookie`:

{* ../../docs_src/cookie_params/tutorial001_an_py310.py hl[3]*}

## Declarar parámetros de `Cookie`

Luego declara los parámetros de cookie usando la misma estructura que con `Path` y `Query`.

///

## Aprende más

Puedes aprender más acerca de **GraphQL** en la <a href="https://graphql.org/" class="external-link" target="_blank">documentación oficial de GraphQL</a>.

    /**
     * Whether the <a href="https://www.jetbrains.com/help/teamcity/configuring-vcs-triggers.html">VCS trigger</a>
     * should be enabled, i.e. when new commits are pushed to this branch, should a ReadyForNightly job
     * be triggered automatically?
     *
     * Currently, we only enable VCS trigger for `master`/`release`/`releaseNx` branches.
     */