if !reflect.DeepEqual(lc.Keys(), []string{"key1"}) {
		t.Fatalf("value differs from expected")
	}

	if lc.Resize(0) != 0 {
		t.Fatalf("evicted count differs from expected")
	}
	if lc.Resize(2) != 0 {
		t.Fatalf("evicted count differs from expected")
	}
	lc.Add("key2", "val2")
	if lc.Resize(1) != 1 {
		t.Fatalf("evicted count differs from expected")
	}
}

func TestLRUEdgeCases(t *testing.T) {

  outputs_.clear();
  for (TF_Operation* o : outputs) {
    outputs_.emplace_back(TF_Output{o, 0});
  }
  output_values_.resize(outputs_.size());
}

void CSession::SetOutputs(const std::vector<TF_Output>& outputs) {
  ResetOutputValues();
  outputs_ = outputs;
  output_values_.resize(outputs_.size());
}

void CSession::SetTargets(std::initializer_list<TF_Operation*> targets) {
  targets_.clear();

      newDelegate.addAll(delegate);
      this.table = newDelegate;
      return;
    }
    int size = this.size;
    if (size < requireEntries().length) {
      resizeEntries(size);
    }
    int minimumTableSize = CompactHashing.tableSize(size);
    int mask = hashTableMask();
    if (minimumTableSize < mask) { // smaller table size will always be less than current mask

    }
    int size = this.size;
    if (size < requireEntries().length) {
      resizeEntries(size);
    }
    int minimumTableSize = CompactHashing.tableSize(size);
    int mask = hashTableMask();
    if (minimumTableSize < mask) { // smaller table size will always be less than current mask
      resizeTable(mask, minimumTableSize, UNSET, UNSET);
    }
  }

  @Override
  public void clear() {

	return c.evictList.Length()
}

// Resize changes the cache size. Size of 0 means unlimited.
func (c *LRU[K, V]) Resize(size int) (evicted int) {
	c.mu.Lock()
	defer c.mu.Unlock()
	if size <= 0 {
		c.size = 0
		return 0
	}
	diff := c.evictList.Length() - size
	if diff < 0 {
		diff = 0
	}
	for i := 0; i < diff; i++ {
		c.removeOldest()
	}
	c.size = size
	return diff
}

 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>As compared with {@link java.util.LinkedHashMap}, this structure places significantly reduced
 * load on the garbage collector by only using a constant number of internal objects.
 *

    int size = this.size;
    if (size < requireEntries().length) {
      resizeEntries(size);
    }
    int minimumTableSize = CompactHashing.tableSize(size);
    int mask = hashTableMask();
    if (minimumTableSize < mask) { // smaller table size will always be less than current mask
      resizeTable(mask, minimumTableSize, UNSET, UNSET);
    }
  }

  @Override
  public void clear() {
    if (needsAllocArrays()) {

 * good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *
 * <p>This implementation consumes significantly less memory than {@code java.util.LinkedHashSet} or
 * even {@code java.util.HashSet}, and places considerably less load on the garbage collector. Like

 * good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *
 * <p>This implementation consumes significantly less memory than {@code java.util.LinkedHashSet} or
 * even {@code java.util.HashSet}, and places considerably less load on the garbage collector. Like

    if (newEntryIndex == Integer.MAX_VALUE) {
      throw new IllegalStateException("Cannot contain more than Integer.MAX_VALUE elements!");
    }
    int newSize = newEntryIndex + 1;
    resizeMeMaybe(newSize);
    insertEntry(newEntryIndex, key, value, hash);
    this.size = newSize;
    if (newEntryIndex >= threshold) {
      resizeTable(2 * table.length);
    }
    modCount++;
    return 0;
  }

  /**