}

    /**
     * Returns the number of POMs processed.
     */
    public int processedCount() {
        return processedPoms.size();
    }

    /**
     * Returns the number of POMs modified.
     */
    public int modifiedCount() {
        return modifiedPoms.size();
    }

    /**
     * Returns the number of POMs that had errors.
     */
    public int errorCount() {

// modification of the graph can increase the number of inputs of
// an operation.
TF_CAPI_EXPORT extern void TF_OperationAllInputs(TF_Operation* oper,
                                                 TF_Output* inputs,
                                                 int max_inputs);

// Get the number of current consumers of a specific output of an
// operation.  Note that this number can change when new operations

   * hexadecimal number in lower case.
   *
   * <p>Note that if the output is considered to be a single hexadecimal number, whether this string
   * is big-endian or little-endian depends on the byte order of {@link #asBytes}. This may be
   * surprising for implementations of {@code HashCode} that represent the number in big-endian

  private final ByteBuffer buffer;

  /** Number of bytes to be filled before process() invocation(s). */
  private final int bufferSize;

  /** Number of bytes processed per process() invocation. */
  private final int chunkSize;

  /**
   * Constructor for use by subclasses. This hasher instance will process chunks of the specified
   * size.
   *

      ArrayList<V> arrayList = (ArrayList<V>) collection;
      arrayList.trimToSize();
    }
  }

  /**
   * @serialData expectedValuesPerKey, number of distinct keys, and then for each distinct key: the
   *     key, number of values for that key, and the key's values
   */
  @GwtIncompatible
  @J2ktIncompatible
    private void writeObject(ObjectOutputStream stream) throws IOException {

        src[srcIndex + 8] = 0x00;
        src[srcIndex + 9] = 0x00;
        // RData length
        src[srcIndex + 10] = 0x00;
        src[srcIndex + 11] = 0x1F; // 31 bytes: 1 + 18 + 6 + 6
        // Number of names (1)
        src[srcIndex + 12] = 0x01;
        // Name entry (18 bytes)
        String name = "TEST            ";
        System.arraycopy(name.getBytes("US-ASCII"), 0, src, srcIndex + 13, 16);

			if setSize%s == 0 {
				ss = append(ss, s)
			}
		}
		return ss
	}

	setCounts := possibleSetCounts(commonSize)
	if len(setCounts) == 0 {
		msg := fmt.Sprintf("Incorrect number of endpoints provided %s, number of drives %d is not divisible by any supported erasure set sizes %d", args, commonSize, setSizes)
		return nil, config.ErrInvalidNumberOfErasureEndpoints(nil).Msg(msg)
	}

	var setSize uint64

        if (o == null) {
            return null;
        } else if (o instanceof Double) {
            return (Double) o;
        } else if (o instanceof Number) {
            return Double.valueOf(((Number) o).doubleValue());
        } else if (o instanceof String) {
            return toDouble((String) o);
        } else if (o instanceof java.util.Date) {
            if (pattern != null) {

with 4 drives we get a total of 256 possible sets. So algorithm automatically chooses 64 sets, which is *16* 64 = 1024* drives in total.

- *If total number of nodes are of odd number then GCD algorithm provides affinity towards odd number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution,...

labels.givenName=Given Name
labels.user_surname=Surname
labels.surame=Surname
labels.user_mail=Mail
labels.mail=Mail
labels.user_employeeNumber=Employee Number
labels.employeeNumber=Employee Number
labels.user_telephoneNumber=Telephone Number
labels.telephoneNumber=Telephone Number
labels.user_homePhone=Home Phone
labels.homePhone=Home Phone
labels.user_homePostalAddress=Home Postal Address
labels.homePostalAddress=Home Postal Address