various sources must be consolidated and injected using the container.

  Currently, mojo configuration is done externally to the container, in the
  DefaultPluginManager in the maven-core API. In order to get from here to
  there, we need to do several things to add capability to the default
  configuration of plexus. This document will detail those changes.

Container Enhancements

* ExpressionEvaluator

In einem solchen Szenario möchten Sie wahrscheinlich **einen einzelnen (Uvicorn-)Prozess pro Container** haben, da Sie die Replikation bereits auf Cluster-Ebene durchführen würden.

In diesem Fall möchten Sie also **nicht** mehrere Worker im Container haben, z. B. mit der `--workers` Befehlszeilenoption. Sie möchten nur einen **einzelnen Uvicorn-Prozess** pro Container haben (wahrscheinlich aber mehrere Container).

```sh
docker ps -a
```

`-a` flag makes sure you get all the containers (Created, Running, Exited). Then identify the `Container ID` from the output.

### Starting and Stopping Containers

To start a stopped container, you can use the [`docker start`](https://docs.docker.com/engine/reference/commandline/start/) command.

```sh
docker start <container_id>
```

        try {
            container.setLookupRealm(null);
            container.setLoggerManager(createLoggerManager());
            container.getLoggerManager().setThresholds(toPlexusLoggingLevel(context.loggerLevel));
            Thread.currentThread().setContextClassLoader(container.getContainerRealm());

            settingsCleaner = invoker.settings(context, false, container.lookup(SettingsBuilder.class));

    static boolean testShouldNotHaveDuplicates() {
        return true;
    }

    @Nested
    class DiTest1 {

        PlexusContainer container;

        @BeforeEach
        void setup() throws Exception {
            container = new DefaultPlexusContainer(
                    new DefaultContainerConfiguration(),
                    new AbstractModule() {
                        @Override

When the **container** is started and running (started from a **container image**) it could create or change files, environment variables, etc. Those changes will exist only in that container, but would not persist in the underlying container image (would not be saved to disk).

A container image is comparable to the **program** file and contents, e.g. `python` and some file `main.py`.

@Named
@Singleton
public class DefaultLookup implements Lookup {

    private final PlexusContainer container;

    @Inject
    public DefaultLookup(PlexusContainer container) {
        this.container = container;
    }

    @Override
    public <T> T lookup(Class<T> type) {
        try {
            return container.lookup(type);
        } catch (ComponentLookupException e) {
            throw new LookupException(e);

    docker push "$TFCI_DOCKER_IMAGE"
  fi
fi

# Keep the existing "tf" container if it's already present.
# The container is not cleaned up automatically! Remove it with:
# docker rm tf
if ! docker container inspect tf >/dev/null 2>&1 ; then
  # Pass all existing TFCI_ variables into the Docker container
  env_file=$(mktemp)
  env | grep ^TFCI_ > "$env_file"

  if [[ $(uname -s) == MSYS_NT* ]]; then

                                                "profile dependencyManagement"))
                                .filter(container -> container.element != null)));

        return dependencyContainers
                .map(container -> fixDuplicateDependenciesInSection(container.element, context, container.sectionName))
                .reduce(false, Boolean::logicalOr);
    }

    private static class DependencyContainer {

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML