}
			case float64:
				field.ReflectValueOf(ctx, value).SetFloat(data)
			case float32:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case int64:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case int:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case int8:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case int16:

    *   Layers now default to `float32`, and automatically cast their inputs to
        the layer's dtype. If you had a model that used `float64`, it will
        probably silently use `float32` in TensorFlow2, and a warning will be
        issued that starts with Layer "layer-name" is casting an input tensor
        from dtype float64 to the layer's dtype of float32. To fix, either set
        the default dtype to float64 with

		}
	case obj.TYPE_FCONST:
		switch sz {
		case 4:
			nameAddr.Sym.WriteFloat32(p.ctxt, nameAddr.Offset, float32(valueAddr.Val.(float64)))
		case 8:
			nameAddr.Sym.WriteFloat64(p.ctxt, nameAddr.Offset, valueAddr.Val.(float64))
		default:
			p.errorf("bad float size for DATA argument: %d", sz)
		}
	case obj.TYPE_SCONST:
		nameAddr.Sym.WriteString(p.ctxt, nameAddr.Offset, int(sz), valueAddr.Val.(string))

	type MigrateNullableColumn struct {
		ID    uint
		Bonus float64 `gorm:"not null"`
		Stock float64
	}

	DB.Migrator().DropTable(&MigrateNullableColumn{})

	DB.AutoMigrate(&MigrateNullableColumn{})

	type MigrateNullableColumn2 struct {
		ID    uint
		Bonus float64
		Stock float64 `gorm:"not null"`
	}

		return globalVeeamForceSC
	}
	return s
}

type ordered interface {
	~int | ~int8 | ~int16 | ~int32 | ~int64 | ~uint | ~uint8 | ~uint16 | ~uint32 | ~uint64 | ~uintptr | ~float32 | ~float64 | string
}

// mapKeysSorted returns the map keys as a sorted slice.
func mapKeysSorted[Map ~map[K]V, K ordered, V any](m Map) []K {
	res := make([]K, 0, len(m))
	for k := range m {

    return Float.compare(a, b);
  }

  /**
   * Returns {@code true} if {@code value} represents a real number. This is equivalent to, but not
   * necessarily implemented as, {@code !(Float.isInfinite(value) || Float.isNaN(value))}.
   *
   * <p>Prefer {@link Float#isFinite(float)} instead.
   *
   * @since 10.0
   */
  @InlineMe(replacement = "Float.isFinite(value)")
  public static boolean isFinite(float value) {

    testRotate(new float[] {}, 0, new float[] {});
    testRotate(new float[] {}, 1, new float[] {});

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

    testRotate(new float[] {}, 0, new float[] {});
    testRotate(new float[] {}, 1, new float[] {});

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

    @Override
    protected List<Float> create(Float[] elements) {
      return asList(elements);
    }
  }

  public static final class FloatsAsListHeadSubListGenerator extends TestFloatListGenerator {
    @Override
    protected List<Float> create(Float[] elements) {
      Float[] suffix = {Float.MIN_VALUE, Float.MAX_VALUE};
      Float[] all = concat(elements, suffix);

    @Override
    protected List<Float> create(Float[] elements) {
      return asList(elements);
    }
  }

  public static final class FloatsAsListHeadSubListGenerator extends TestFloatListGenerator {
    @Override
    protected List<Float> create(Float[] elements) {
      Float[] suffix = {Float.MIN_VALUE, Float.MAX_VALUE};
      Float[] all = concat(elements, suffix);