labels.profile_button = 설정
labels.profile.title = 설정
labels.profile.update = 업데이트
labels.profile.back = 이전
labels.profile.placeholder_old_password = 현재 비밀번호
labels.profile.placeholder_new_password = 새 암호
labels.profile.placeholder_confirm_new_password = 새 암호 확인
labels.top.search = 검색
labels.index_title = Fess
labels.index_form_search_btn = 검색
labels.index_osdd_title = 검색
labels.index_form_option_btn = 옵션

labels.profile.title=Profil
labels.profile.update=Aktualisieren
labels.profile.back=Zurück
labels.profile.placeholder_old_password=Aktuelles Passwort
labels.profile.placeholder_new_password=Neues Passwort
labels.profile.placeholder_confirm_new_password=Neues Passwort (bestätigen)
labels.top.search=Suche
labels.index_title=Fess
labels.index_form_search_btn=Suche
labels.index_osdd_title=Suche
labels.index_form_option_btn=Optionen

		}

		if len(results) != 2 {
			t.Errorf("Incorrect users length, expects: 2, got %v", len(results))
		}

		for idx := range results {
			results[idx].Name = results[idx].Name + "_new"
		}

		if err := tx.Save(results).Error; err != nil {
			t.Fatalf("failed to save users, got error %v", err)
		}

		return nil
	}); result.Error != nil || result.RowsAffected != 6 {

  }

  // We may need to allocate zero inputs for trainable dtypes we don't have JVPs
  // for. Make sure they get cleaned up.
  std::vector<Gradient*> new_zeros;
  auto delete_new_zeros = gtl::MakeCleanup([&new_zeros, this] {
    for (Gradient* tensor : new_zeros) {
      this->vspace_.DeleteGradient(tensor);
    }
  });
  std::vector<Gradient*> in_grads;
  in_grads.reserve(input_tensors.size());

Harshavardhana <******@****.***> 1713892552 -0700

        ConcurrentHashMap<Object, Supplier<?>> cache;
        RepositoryCache repositoryCache = session != null ? session.getCache() : null;
        if (repositoryCache == null) {
            return new DefaultModelCache(new ConcurrentHashMap<>());
        } else {
            if (anew) {
                cache = new ConcurrentHashMap<>();

  // +optional
  optional bool readOnlyRootFilesystem = 6;

  // AllowPrivilegeEscalation controls whether a process can gain more
  // privileges than its parent process. This bool directly controls if
  // the no_new_privs flag will be set on the container process.
  // AllowPrivilegeEscalation is true always when the container is:
  // 1) run as Privileged
  // 2) has CAP_SYS_ADMIN

*   `tf.lite`
    *   Enabled the new MLIR-based quantization backend by default
        *   The new backend is used for 8 bits full integer post-training
            quantization
        *   The new backend removes the redundant rescales and fixes some bugs
            (shared weight/bias, extremely small scales, etc)
        *   Set `experimental_new_quantizer` in tf.lite.TFLiteConverter to False

    testRotate(new short[] {1, 2}, -3, new short[] {2, 1});
    testRotate(new short[] {1, 2}, -1, new short[] {2, 1});
    testRotate(new short[] {1, 2}, -2, new short[] {1, 2});
    testRotate(new short[] {1, 2}, 0, new short[] {1, 2});
    testRotate(new short[] {1, 2}, 1, new short[] {2, 1});
    testRotate(new short[] {1, 2}, 2, new short[] {1, 2});
    testRotate(new short[] {1, 2}, 3, new short[] {2, 1});

    URL url1 = new URL("file:/a");
    URL url2 = new URL("file:/b");
    URLClassLoader grandParent = new URLClassLoader(new URL[] {url1}, null);
    URLClassLoader parent = new URLClassLoader(new URL[] {url2}, grandParent);
    assertThat(ClassPath.getClassPathEntries(new ClassLoader(parent) {}))
        .containsExactly(new File("/a"), grandParent, new File("/b"), parent);
  }