### Bug Fixes and Other Changes

*   Add TensorFlow Quantizer to TensorFlow pip package.

*   `tf.sparse.segment_sum` `tf.sparse.segment_mean` `tf.sparse.segment_sqrt_n` `SparseSegmentSum/Mean/SqrtN[WithNumSegments]`

    *   Added `sparse_gradient` option (default=false) that makes the gradient of these functions/ops sparse (`IndexedSlices`) instead of dense (`Tensor`), using new `SparseSegmentSum/Mean/SqrtNGradV2` ops.

import com.google.errorprone.annotations.Immutable;
import java.util.LinkedHashMap;
import java.util.Map;
import java.util.Map.Entry;

/** A {@code RegularImmutableTable} optimized for sparse data. */
@GwtCompatible
@Immutable(containerOf = {"R", "C", "V"})
final class SparseImmutableTable<R, C, V> extends RegularImmutableTable<R, C, V> {
  static final ImmutableTable<Object, Object, Object> EMPTY =

  /**
   * Closed addressing tends to perform well even with high load factors. Being conservative here
   * ensures that the table is still likely to be relatively sparse (hence it misses fast) while
   * saving space.
   */
  @VisibleForTesting static final double MAX_LOAD_FACTOR = 1.2;

  /**
   * Maximum allowed false positive probability of detecting a hash flooding attack given random
   * input.
   */

import java.util.Objects;
import java.util.Set;
import org.jspecify.annotations.Nullable;

/**
 * A collection that associates an ordered pair of keys, called a row key and a column key, with a
 * single value. A table may be sparse, with only a small fraction of row key / column key pairs
 * possessing a corresponding value.
 *
 * <p>The mappings corresponding to a given row key may be viewed as a {@link Map} whose keys are

 * iterator remains valid.
 *
 * <p>This class requires less memory than the {@link HashBasedTable} and {@link TreeBasedTable}
 * implementations, except when the table is sparse.
 *
 * <p>Null row keys or column keys are not permitted.
 *
 * <p>This class provides methods involving the underlying array structure, where the array indices

     * @return the parsed Query object
     * @throws QueryParseException if the query cannot be parsed
     */
    public Query parse(final String query) {
        return filterChain.parse(query);
    }

    /**
     * Creates a new Lucene query parser with the current configuration.
     * The parser is configured with the default field, analyzer, wildcard settings,
     * and default operator.
     *

     */
    public SitemapSet parse(final InputStream in) {
        return parse(in, true);
    }

    /**
     * Parses a sitemap from the given input stream.
     * @param in the input stream to parse
     * @param recursive whether to recursively parse compressed files
     * @return the parsed sitemap set
     */
    protected SitemapSet parse(final InputStream in, final boolean recursive) {

    }

    @Test
    @DisplayName("parse sets mechanismToken and flags parsed")
    void parseSetsMechanismToken() throws IOException {
        TestSpnegoToken t = new TestSpnegoToken();
        byte[] raw = new byte[] { 5, 6 };
        t.parse(raw);
        assertTrue(t.isParsed(), "parse should mark parsed");
        assertArrayEquals(raw, t.getMechanismToken(), "parse should set mechanismToken");
    }

    @Test

     */
    public static void parse(final SAXParser parser, final InputSource inputSource, final DefaultHandler handler) {
        assertArgumentNotNull("parser", parser);
        assertArgumentNotNull("inputSource", inputSource);
        assertArgumentNotNull("handler", handler);

        try {
            parser.parse(inputSource, handler);
        } catch (final SAXException e) {

            final SAXParser parser = factory.newSAXParser();
            parser.setProperty(XMLConstants.ACCESS_EXTERNAL_DTD, StringUtil.EMPTY);
            parser.setProperty(XMLConstants.ACCESS_EXTERNAL_SCHEMA, StringUtil.EMPTY);
            parser.parse(is, this);
        } catch (final Exception e) {
            throw new GsaConfigException("Failed to parse XML file.", e);
        }
    }

    /**