/**
   * <a
   * href="https://developer.apple.com/library/archive/documentation/NetworkingInternet/Conceptual/iPhoneOTAConfiguration/profile-service/profile-service.html">Apple
   * over-the-air mobile configuration profiles</a>.
   *
   * @since 18.0
   */
  public static final MediaType APPLE_MOBILE_CONFIG =
      createConstant(APPLICATION_TYPE, "x-apple-aspen-config");

  /**

- Dockershim security: pod sandbox now always run with `no-new-privileges` and `runtime/default` seccomp profile
  dockershim seccomp: custom profiles can now have smaller seccomp profiles when set at pod level ([#90948](https://github.com/kubernetes/kubernetes/pull/90948), [@pjbgf](https://github.com/pjbgf)) [SIG Node]

 *       <li>Removes dependency {@code <version>} when it points to a project artifact</li>
 *       <li>Removes dependency {@code <groupId>} when it points to a project artifact</li>
 *       <li>Applies to main dependencies, profile dependencies, and plugin dependencies</li>
 *     </ul>
 *   </li>
 *   <li><strong>Subprojects List Removal</strong>: Removes redundant {@code <subprojects>} lists that match direct child directories</li>
 * </ul>
 *

Vous écrivez du python standard avec des annotations de types:

```Python
from datetime import date

from pydantic import BaseModel

# Déclare une variable comme étant une str
# et profitez de l'aide de votre IDE dans cette fonction
def main(user_id: str):
    return user_id


# Un modèle Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

              <include>org.apache.maven.model</include>
              <include>org.apache.maven.monitor</include>
              <include>org.apache.maven.plugin</include>
              <include>org.apache.maven.profiles</include>
              <include>org.apache.maven.project</include>
              <include>org.apache.maven.reporting</include>
              <include>org.apache.maven.repository</include>

                    .get());
            options.addOption(Option.builder()
                    .longOpt(YJP)
                    .desc("Launch the JVM with Yourkit profiler (script option).")
                    .get());

            // Deprecated
            options.addOption(Option.builder(ALTERNATE_GLOBAL_SETTINGS)
                    .longOpt("global-settings")

            "//tensorflow/core/common_runtime/eager:execute",
            "//tensorflow/core/common_runtime/eager:placement_utils",
            "//tensorflow/core/common_runtime/eager:tensor_handle",
            "//tensorflow/core/profiler/lib:traceme",
            "@com_google_absl//absl/algorithm:container",
            "@com_google_absl//absl/types:span",
            "@com_google_absl//absl/types:variant",
        ],
    }) + [

    public static final String LABELS_PROFILE_TITLE = "{labels.profile.title}";

    /** The key of the message: Update */
    public static final String LABELS_PROFILE_UPDATE = "{labels.profile.update}";

    /** The key of the message: Back */
    public static final String LABELS_PROFILE_BACK = "{labels.profile.back}";

    /** The key of the message: Current Password */

    analyzing input pipeline performance with TF Profiler.

*   [`tf.distribute.TPUStrategy`](https://www.tensorflow.org/api_docs/python/tf/distribute/TPUStrategy)
    is now a stable API and no longer considered experimental for TensorFlow.
    (earlier `tf.distribute.experimental.TPUStrategy`).

*   [TF Profiler](https://www.tensorflow.org/guide/profiler) introduces two new
    tools: a memory profiler to visualize your model’s memory usage over time

  existingClientSecretName: ""
  existingClientIdKey: ""
  existingClientSecretKey: ""
  claimName: "policy"
  scopes: "openid,profile,email"
  redirectUri: "https://console-endpoint-url/oauth_callback"
  # Can leave empty
  claimPrefix: ""
  comment: ""
  displayName: ""

networkPolicy:
  enabled: false