<?xml version="1.0" encoding="UTF-8"?>
<properties>
  <parsers>
    <parser class="org.apache.tika.parser.DefaultParser">
      <parser-exclude class="org.apache.tika.parser.ocr.TesseractOCRParser"/>
    </parser>
  </parsers>

import org.codelibs.fess.mylasta.action.FessUserBean;
import org.codelibs.fess.mylasta.direction.FessConfig;
import org.codelibs.fess.query.QueryFieldConfig;
import org.codelibs.fess.query.parser.QueryParser;
import org.codelibs.fess.score.QueryRescorer;
import org.codelibs.fess.util.ComponentUtil;
import org.dbflute.optional.OptionalThing;
import org.lastaflute.core.message.UserMessages;

### 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.

        .addEqualityGroup(parse(""), parse(""))
        .addEqualityGroup(parse("concurrencyLevel=7"), parse("concurrencyLevel=7"))
        .addEqualityGroup(parse("concurrencyLevel=15"), parse("concurrencyLevel=15"))
        .addEqualityGroup(parse("initialCapacity=7"), parse("initialCapacity=7"))
        .addEqualityGroup(parse("initialCapacity=15"), parse("initialCapacity=15"))
        .addEqualityGroup(parse("maximumSize=7"), parse("maximumSize=7"))

            MediaType.parse("text/plain; charset=UTF-8"),
            MediaType.parse("text/plain ; charset=utf-8"),
            MediaType.parse("text/plain; charset =UTF-8"),
            MediaType.parse("text/plain; charset= UTF-8"),
            MediaType.parse("text/plain; charset  =  UTF-8"),
            MediaType.parse("text/plain; charset=\tUTF-8"))

        parameters = "";
        parameterMap = ParameterUtil.parse(parameters);
        assertEquals(0, parameterMap.size());

        parameters = "domain";
        parameterMap = ParameterUtil.parse(parameters);
        assertEquals(1, parameterMap.size());
        assertEquals("", parameterMap.get("domain"));

        parameters = "domain=";
        parameterMap = ParameterUtil.parse(parameters);
        assertEquals(1, parameterMap.size());

for f in files.strip().splitlines():
  # Just ignore any failures, they're probably not important
  try:
    r = JUnitXml.fromfile(f)
  except Exception as e:  # pylint: disable=broad-except
    print("Ignoring this XML parse failure in {}: ".format(f), str(e))

  source_file = re.search(
      r"/(bazel_pip|tensorflow)/.*", f.decode("utf-8")
  ).group(0)
  for testsuite in r:
    testsuite._elem.set("source_file", source_file)

                    </table>
                </section>
            </chapter>
        ''')

        def extraAttribute = new ExtraAttributeDoc(parse('<td>Extra column</td>'), parse('<td>some value</td>'))
        ClassDoc classDoc = classDoc('Class', content: content)

		return true
	}
	return false
}

// MCR is not defined by the obj/arm; instead we define it privately here.
// It is encoded as an MRC with a bit inside the instruction word,
// passed to arch.ARMMRCOffset.
const aMCR = arm.ALAST + 1

// IsARMMRC reports whether the op (as defined by an arm.A* constant) is
// MRC or MCR.
func IsARMMRC(op obj.As) bool {
	switch op {

- All value additions or removals are user-facing and must come with a release note.