t.Errorf("should find product, but got error %v", err)
	}

	if productWithItem.Item.AfterFindCallTimes != 0 {
		t.Fatalf("AfterFind should not be called times:%d", productWithItem.Item.AfterFindCallTimes)
	}
}

type Product5 struct {
	gorm.Model
	Name string
}

var beforeUpdateCall int

func (p *Product5) BeforeUpdate(*gorm.DB) error {

local storage (JBOD/JBOF) mapped as persistent local volumes. This architecture enables multi-tenant MinIO, allowing isolation of data between customers.

MinIO also supports multi-cluster, multi-site federation similar to AWS regions and tiers. Using MinIO Information Lifecycle Management (ILM), you can configure data to be tiered between NVMe based hot storage, and HDD based warm storage. All data is encrypted with per-object key. Access Control and Identity Management between the tenants...

     * Test transformer reusability
     */
    public void test_transformerReusability() {
        TestTransformer transformer = new TestTransformer("reusableTransformer");

        // Use transformer multiple times
        for (int i = 0; i < 10; i++) {
            ResponseData responseData = new ResponseData();
            responseData.setUrl("http://example.com/page" + i);

     }
    ```

    You may also skip the retry when you’ve hit an application-defined attempt limit:

    ```kotlin
    if (response.responseCount >= 3) {
      return null // If we've failed 3 times, give up.
    }
    ```

    This above code relies on this `responseCount` extension val:

    ```kotlin
    val Response.responseCount: Int

      MockResponse(
        code = 401,
        headers = headersOf("WWW-Authenticate", "Basic realm=\"protected area\""),
        body = "Please authenticate.",
      )
    // Fail auth three times...
    server.enqueue(pleaseAuthenticate)
    server.enqueue(pleaseAuthenticate)
    server.enqueue(pleaseAuthenticate)
    // ...then succeed the fourth time.
    server.enqueue(

   * nodes. This is an O(n) operation in the common case (and O(n^2) in the worst), but we are saved
   * by two things.
   *
   * <ul>
   *   <li>This is only called when a waiting thread times out or is interrupted. Both of which
   *       should be rare.
   *   <li>The waiters list should be very short.
   * </ul>
   */
  private void removeWaiter(Waiter node) {

        totalKeyRotations.incrementAndGet();
        lastKeyRotationTime.set(System.currentTimeMillis());
    }

    /**
     * Get the current key rotation count
     *
     * @return number of times keys have been rotated
     */
    public int getKeyRotationCount() {
        return rotationCount;
    }

    /**
     * Set the key rotation bytes limit
     *

   * {@code Set}.
   *
   * <p>The function is applied lazily, invoked when needed. This is necessary for the returned
   * multimap to be a view, but it means that the function will be applied many times for bulk
   * operations like {@link Multimap#containsValue} and {@code Multimap.toString()}. For this to
   * perform well, {@code function} should be fast. To avoid lazy evaluation when the returned

   * {@code Set}.
   *
   * <p>The function is applied lazily, invoked when needed. This is necessary for the returned
   * multimap to be a view, but it means that the function will be applied many times for bulk
   * operations like {@link Multimap#containsValue} and {@code Multimap.toString()}. For this to
   * perform well, {@code function} should be fast. To avoid lazy evaluation when the returned

      int same = 0x0; // bitset for output bits with same values
      int diff = 0x0; // bitset for output bits with different values
      int count = 0;
      // originally was 2 * Math.log(...), making it try more times to avoid flakiness issues
      int maxCount = (int) (4 * Math.log(2 * keyBits * hashBits) + 1);
      while (same != 0xffffffff || diff != 0xffffffff) {
        int key1 = rand.nextInt();
        // flip input bit for key2