EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

    // Compare that the graphs match.
    GraphDef expected_gdef;
    GraphDef gdef;
    EXPECT_TRUE(GetGraphDef(expected_graph_, &expected_gdef));
    EXPECT_TRUE(GetGraphDef(graph_, &gdef));
    TF_EXPECT_GRAPH_EQ(expected_gdef, gdef);

    // Compare that the output of the gradients of both graphs match.

      if (obj instanceof ContainsPatternPredicate) {
        ContainsPatternPredicate that = (ContainsPatternPredicate) obj;

        // Pattern uses Object (identity) equality, so we have to reach
        // inside to compare individual fields.
        return Objects.equals(pattern.pattern(), that.pattern.pattern())
            && pattern.flags() == that.pattern.flags();
      }
      return false;
    }

    @Override

}

func (r *rleBuffer) ReadAt(p []byte, off int64) (n int, err error) {
	if len(p) == 0 {
		return
	}
	skipParts, _ := slices.BinarySearchFunc(r.buf, off, func(rb repeatedByte, off int64) int {
		return cmp.Compare(rb.off+rb.n, off)
	})
	parts := r.buf[skipParts:]
	if len(parts) > 0 {
		skipBytes := off - parts[0].off
		for _, part := range parts {
			repeat := int(min(part.n-skipBytes, int64(len(p)-n)))

*   When you contribute a new feature to TensorFlow, the maintenance burden is
    (by default) transferred to the TensorFlow team. This means that the benefit
    of the contribution must be compared against the cost of maintaining the
    feature.
*   Full new features (e.g., a new op implementing a cutting-edge algorithm)
    typically will live in

            // Sort by version number
            archives.sort((a, b) -> {
                int versionA = extractVersion(a);
                int versionB = extractVersion(b);
                return Integer.compare(versionB, versionA); // Descending order
            });

            // Keep only the specified number of versions
            for (int i = keepVersions; i < archives.size(); i++) {

// included to match [bufio.Writer]'s WriteRune. The buffer is grown as needed;
// if it becomes too large, WriteRune will panic with [ErrTooLarge].
func (b *Buffer) WriteRune(r rune) (n int, err error) {
	// Compare as uint32 to correctly handle negative runes.
	if uint32(r) < utf8.RuneSelf {
		b.WriteByte(byte(r))
		return 1, nil
	}
	b.lastRead = opInvalid
	m, ok := b.tryGrowByReslice(utf8.UTFMax)
	if !ok {

      Ordering<K> keyOrdering =
          new Ordering<K>() {
            @Override
            public int compare(K left, K right) {
              // requireNonNull is safe because we are passing keys in the map.
              return valueComparator.compare(
                  requireNonNull(map.get(left)), requireNonNull(map.get(right)));
            }
          };

     * {@code " x "} (space, letter x, space), followed by the count.
     */
    @Override
    String toString();
  }

  // Comparison and hashing

  /**
   * Compares the specified object with this multiset for equality. Returns {@code true} if the
   * given object is also a multiset and contains equal elements with equal counts, regardless of
   * order.
   */
  @Override

    builder.put("bb", 3);
    builder.put("d", 2);
    builder.put("a", 5);
    builder.orderKeysBy(
        new Ordering<String>() {
          @Override
          public int compare(String left, String right) {
            return left.length() - right.length();
          }
        });
    builder.put("cc", 4);
    builder.put("a", 2);
    builder.put("bb", 6);

      if (obj instanceof ContainsPatternPredicate) {
        ContainsPatternPredicate that = (ContainsPatternPredicate) obj;

        // Pattern uses Object (identity) equality, so we have to reach
        // inside to compare individual fields.
        return Objects.equals(pattern.pattern(), that.pattern.pattern())
            && pattern.flags() == that.pattern.flags();
      }
      return false;
    }

    @Override