ASSERT_EQ(expected[i], data[i]) << "Different data at index " << i;
    }
  }

  std::vector<TF_Output> ToOutput(const std::vector<TF_Operation*> ops) {
    std::vector<TF_Output> out;
    for (auto op : ops) {
      out.push_back({op, 0});
    }
    return out;
  }

  void Define(int num_opers, const std::vector<TF_Operation*>& opers,

        testRule.setMatchResult(false);

        // Serialize
        ByteArrayOutputStream baos = new ByteArrayOutputStream();
        ObjectOutputStream oos = new ObjectOutputStream(baos);
        oos.writeObject(testRule);
        oos.close();

        // Deserialize
        ByteArrayInputStream bais = new ByteArrayInputStream(baos.toByteArray());
        ObjectInputStream ois = new ObjectInputStream(bais);

  @SuppressWarnings("unchecked") // how to explain?
  @Override
  public <S extends T> Ordering<S> reverse() {
    return (Ordering<S>) forwardOrder;
  }

  // Override the min/max methods to "hoist" delegation outside loops

  @Override
  public <E extends T> E min(@ParametricNullness E a, @ParametricNullness E b) {
    return forwardOrder.max(a, b);
  }

  @Override
  public <E extends T> E min(

  @SuppressWarnings("unchecked") // how to explain?
  @Override
  public <S extends T> Ordering<S> reverse() {
    return (Ordering<S>) forwardOrder;
  }

  // Override the min/max methods to "hoist" delegation outside loops

  @Override
  public <E extends T> E min(@ParametricNullness E a, @ParametricNullness E b) {
    return forwardOrder.max(a, b);
  }

  @Override
  public <E extends T> E min(

existing object replication are not marked as `PENDING` prior to replication.

	return dst, nil
}

const (
	// Lock maintenance interval.
	lockMaintenanceInterval = 1 * time.Minute

	// Lock validity duration
	lockValidityDuration = 1 * time.Minute
)

// lockMaintenance loops over all locks and discards locks
// that have not been refreshed for some time.
func lockMaintenance(ctx context.Context) {
	if !globalIsDistErasure {
		return
	}

---
name: TensorFlow Lite Op Request
about: Use this template for reporting Lite ops you are using or missing
labels: 'comp:lite'

---

**System information**
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installed from (source or binary):
- TensorFlow version (or github SHA if from source):


**Provide the text output from tflite_convert**

```
# Copy and paste here
```

        for (CrawlerStatus original : statuses) {
            // Serialize
            ByteArrayOutputStream baos = new ByteArrayOutputStream();
            ObjectOutputStream oos = new ObjectOutputStream(baos);
            oos.writeObject(original);
            oos.close();

            // Deserialize
            ByteArrayInputStream bais = new ByteArrayInputStream(baos.toByteArray());

    ByteArrayOutputStream bytes = new ByteArrayOutputStream();
    ObjectOutputStream oos = new ObjectOutputStream(bytes);
    oos.writeObject(map);
    oos.flush();

    int mapSize = bytes.size();
    oos.writeObject(keySet);
    oos.writeObject(values);
    oos.close();

    int finalSize = bytes.size();

    assertThat(finalSize - mapSize).isLessThan(100);
  }

		adminRouter.Methods(http.MethodPut).Path(adminVersion+"/set-user-status").HandlerFunc(adminMiddleware(adminAPI.SetUserStatus)).Queries("accessKey", "{accessKey:.*}").Queries("status", "{status:.*}")

		// Service accounts ops
		adminRouter.Methods(http.MethodPut).Path(adminVersion + "/add-service-account").HandlerFunc(adminMiddleware(adminAPI.AddServiceAccount))