org/apache/maven/plugin/Mojo$1.class package org.apache.maven.plugin; synchronized class Mojo$1 { } org/apache/maven/plugin/Mojo.class package org.apache.maven.plugin; public abstract interface Mojo { public static final String ROLE; public abstract void execute() throws MojoExecutionExcepti, MojoFailureException; public abstract void setLog(logging.Log); public abstract logging.Log getLog(); static void <clinit>(); } org/apache/maven/plugin/MojoExecutionExcepti.class package org.apache.maven.plugin; public...

     * a no-op. We could log, but if that's what we really want, we should modify
     * AbstractFuture.executeListener to do so, since that method would have the ability to continue
     * to execute other listeners.
     *
     * What about RuntimeException? If there is a bug in set()/setValue() that produces one, it will
     * propagate, too, but only as far as AbstractFuture.executeListener, which will catch and log

2. Running the CI scripts locally, as explained below
3. **Google employees only**: Google employees can use an internal-only tool
called "MLCI" that makes testing more convenient: it can execute any full CI job
against a pending change. Search for "MLCI" internally to find it.

You may invoke a CI script of your choice by following these instructions:

```bash
cd tensorflow-git-dir

<a href="https://github.com/containous/traefik/releases" class="external-link" target="_blank">Faça o download do Traefik</a>, ele é um único binário, você pode extrair o arquivo compactado e executá-lo diretamente do terminal.

Então, crie um arquivo `traefik.toml` com:

```TOML hl_lines="3"
[entryPoints]
  [entryPoints.http]
    address = ":9999"

[providers]
  [providers.file]

     * canceled, even if this plan is canceled.
     */
    fun retry(): Plan?
  }

  /**
   * What to do once a plan has executed.
   *
   * If [nextPlan] is not-null, another attempt should be made by following it. If [throwable] is
   * non-null, it should be reported to the user should all further attempts fail.
   *

import org.apache.maven.lifecycle.internal.ExecutionPlanItem;
import org.apache.maven.model.Plugin;
import org.apache.maven.plugin.MojoExecution;
import org.apache.maven.plugin.descriptor.MojoDescriptor;

// TODO lifecycles being executed
// TODO what runs in each phase
// TODO plugins that need downloading
// TODO project dependencies that need downloading

```

This results in the following execution order:

* **Request**: MiddlewareB → MiddlewareA → route

* **Response**: route → MiddlewareA → MiddlewareB

This stacking behavior ensures that middlewares are executed in a predictable and controllable order.

## Other middlewares { #other-middlewares }

    /**
     * Constructs a new suggest job.
     */
    public SuggestJob() {
        // do nothing
    }

    @Override
    public String execute() {
        final StringBuilder resultBuf = new StringBuilder();

        if (sessionId == null) { // create session id
            sessionId = RandomStringUtils.randomAlphabetic(15);
        }

     *
     * @return this job instance for method chaining
     */
    public GenerateThumbnailJob cleanup() {
        cleanup = true;
        return this;
    }

    @Override
    public String execute() {
        final StringBuilder resultBuf = new StringBuilder();

        if (sessionId == null) { // create session id
            sessionId = RandomStringUtils.randomAlphabetic(15);
        }

            runner.clean();
        }
    }

    @Before
    public void before() throws Exception {
        try {
            runner.admin().indices().prepareDelete("DefaultContentsParserTest*", "fess_suggest*").execute().actionGet();
        } catch (Exception e) {
            // ignore
        }
        runner.refresh();
        suggester = Suggester.builder().build(runner.client(), "DefaultContentsParserTest");