tx.Statement.Unscoped = db.Statement.Unscoped
				if err := preload(tx, rel, append(preloads[name], associationsConds...), preloadMap[name]); err != nil {
					return err
				}
			}
		} else {
			return fmt.Errorf("%s: %w for schema %s", name, gorm.ErrUnsupportedRelation, db.Statement.Schema.Name)
		}
	}
	return nil
}

func preloadDB(db *gorm.DB, reflectValue reflect.Value, dest interface{}) *gorm.DB {

     *
     * @return total bytes
     */
    public long getBytesTransferred() {
        return bytesTransferred.get();
    }

    /**
     * Get total number of operation errors
     *
     * @return error count
     */
    public long getOperationErrors() {
        return operationErrors.get();
    }

    /**
     * Get total number of connections created
     *

        // Verify result contains error message
        assertNotNull(result);
        assertTrue(result.contains("Illegal state in search log processing"));
        assertTrue(result.endsWith("\n"));
    }

    @Test
    public void test_execute_multipleErrors() {
        // Test with multiple calls to execute() with errors
        SearchLogHelper mockSearchLogHelper = new SearchLogHelper() {

        Exception level3 = new RuntimeException("Level 3 error");
        Exception level2 = new IllegalStateException("Level 2 error", level3);
        Exception level1 = new IOException("Level 1 error", level2);
        SsoLoginException exception = new SsoLoginException("Top level SSO error", level1);

        assertEquals("Top level SSO error", exception.getMessage());

        // Verify the exception chain

   * data, and vertical if there is variance in the {@code y} data but not the {@code x} data.
   *
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}

			cReverse.Local = hosts[y]
			cReverse.Remote = hosts[x]
			if c.shouldConnect() == cReverse.shouldConnect() {
				t.Errorf("shouldConnect(%q, %q) != shouldConnect(%q, %q)", hosts[x], hosts[y], hosts[y], hosts[x])
			}
			if c.shouldConnect() {
				should++
			}
		}
		if should < 10 {
			t.Errorf("host %q only connects to %d hosts", hosts[x], should)
		}
		t.Logf("host %q should connect to %d hosts", hosts[x], should)
	}

func (ps *PubSub[T, M]) Subscribe(mask M, subCh chan T, doneCh <-chan struct{}, filter func(entry T) bool) error {
	totalSubs := atomic.AddInt32(&ps.numSubscribers, 1)
	if ps.maxSubscribers > 0 && totalSubs > ps.maxSubscribers {
		atomic.AddInt32(&ps.numSubscribers, -1)
		return fmt.Errorf("the limit of `%d` subscribers is reached", ps.maxSubscribers)
	}
	ps.Lock()
	defer ps.Unlock()

// Checksum types must match.
func (c *Checksum) AddPart(other Checksum, size int64) error {
	if !other.Type.CanMerge() {
		return fmt.Errorf("checksum type cannot be merged")
	}
	if size == 0 {
		return nil
	}
	if !c.Type.Is(other.Type.Base()) {
		return fmt.Errorf("checksum type does not match got %s and %s", c.Type.String(), other.Type.String())
	}
	// If never set, just add first checksum.

   * data, and vertical if there is variance in the {@code y} data but not the {@code x} data.
   *
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}

					WriteThroughput: r.WriteThroughput,
					Error: func() string {
						if r.Error != nil {
							return r.Error.Error()
						}
						return ""
					}(),
				}
				results = append(results, result)
			}
			for _, inp := range ignoredPaths {
				results = append(results, madmin.DrivePerf{
					Path:  inp,
					Error: errFaultyDisk.Error(),
				})
			}
			return results
		}(),