}
                this.firstResponse = false;
            }
            else {
                if ( targ.getMechanism() != null && !targ.getMechanism().equals(this.selectedMech) ) {
                    throw new SmbException("Server switched mechanism");
                }
            }
            inputToken = targ.getMechanismToken();
        }
        else {
            throw new SmbException("Invalid token");

									value = stmt.DB.NowFunc().UnixNano()
								} else if field.AutoUpdateTime == schema.UnixMillisecond {
									value = stmt.DB.NowFunc().UnixMilli()
								} else if field.AutoUpdateTime == schema.UnixSecond {
									value = stmt.DB.NowFunc().Unix()
								} else {
									value = stmt.DB.NowFunc()
								}
								isZero = false
							}

							if (ok || !isZero) && field.Updatable {

	user.Age = 1
	if err := DB.Save(user).Error; err != nil {
		t.Errorf("errors happened when update: %v", err)
	} else if user.Age != 1 {
		t.Errorf("Age should equals to 1, but got %v", user.Age)
	} else if user.Active != false {
		t.Errorf("Active should equals to false, but got %v", user.Active)
	}
	checkUpdatedAtChanged("Save", user.UpdatedAt)
	checkOtherData("Save")

	var result4 User

  }

  ctx.device_id = device_id;
  if (device_type == "CPU") {
    ctx.device_type = DLDeviceType::kDLCPU;
  } else if (device_type == "GPU") {
#if TENSORFLOW_USE_ROCM
    ctx.device_type = DLDeviceType::kDLROCM;
#else
    ctx.device_type = DLDeviceType::kDLCUDA;
#endif
  } else {
    status->status = tensorflow::errors::InvalidArgument(
        "Unsupported Device Type for dlpack");
  }

                    } else if (badWord == null) {
                        badWord = new BadWord();
                        badWord.setSuggestWord(targetWord);
                        badWord.setCreatedBy(Constants.SYSTEM_USER);
                        badWord.setCreatedTime(now);
                        badWordBhv.insert(badWord);
                    } else {

        return n;
      default:
        if (n < factorials.length) {
          return factorials[n] / (factorials[k] * factorials[n - k]);
        } else if (k >= biggestBinomials.length || n > biggestBinomials[k]) {
          return Long.MAX_VALUE;
        } else if (k < biggestSimpleBinomials.length && n <= biggestSimpleBinomials[k]) {
          // guaranteed not to overflow
          long result = n--;

}

func resetCompressEncryption() {
	// Reset...
	globalCompressConfigMu.Lock()
	globalCompressConfig.Enabled = false
	globalCompressConfig.AllowEncrypted = false
	globalCompressConfigMu.Unlock()
	globalAutoEncryption = false
	GlobalKMS = nil
}

func execExtended(t *testing.T, fn func(t *testing.T, init func(), bucketOptions MakeBucketOptions)) {
	// Exec with default settings...
	resetCompressEncryption()

    static LogStream log = LogStream.getInstance();
    static final boolean strictView = Config.getBoolean("jcifs.smb1.smb.client.dfs.strictView", false);
    static final long TTL = Config.getLong("jcifs.smb1.smb.client.dfs.ttl", 300);
    static final boolean DISABLED = Config.getBoolean("jcifs.smb1.smb.client.dfs.disabled", false);

    protected static CacheEntry FALSE_ENTRY = new Dfs.CacheEntry(0L);

        else:
            return deepcopy(field.default), []
    v_, errors_ = field.validate(value, values, loc=loc)
    if isinstance(errors_, ErrorWrapper):
        return None, [errors_]
    elif isinstance(errors_, list):
        new_errors = _regenerate_error_with_loc(errors=errors_, loc_prefix=())
        return None, new_errors
    else:
        return v_, []

* Einfache Python-Integration mit **Jupyter-Kerneln** für Remote- oder In-Docker-Entwicklung mit Erweiterungen wie Atom Hydrogen...