<param name="jar.groupId" value="jakarta/annotation" />
			<param name="jar.artifactId" value="jakarta.annotation-api" />
			<param name="jar.version" value="2.1.1" />
			<param name="file.version" value="2.1.1" />
		</antcall>
		<!-- kopf -->
		<get dest="${target.dir}/kopf.zip">
			<url url="https://github.com/codelibs/elasticsearch-kopf/archive/${kopf.branch}.zip" />
		</get>

        map sigbuild-r2.10 2.10-python3.9
        map sigbuild-r2.10-python3.8 2.10-python3.8
        map sigbuild-r2.10-python3.9 2.10-python3.9
        map sigbuild-r2.10-python3.10 2.10-python3.10
        # TF 2.11
        map sigbuild-r2.11 2.11-python3.9
        map sigbuild-r2.11-python3.8 2.11-python3.8
        map sigbuild-r2.11-python3.9 2.11-python3.9
        map sigbuild-r2.11-python3.10 2.11-python3.10

  } ]
}, {
  "scenario" : "org.gradle.performance.regression.corefeature.VerboseTestOutputPerformanceTest.cleanTest test with verbose test output",
  "durations" : [ {
    "testProject" : "withVerboseJUnit",
    "linux" : 211
  }, {
    "testProject" : "withVerboseTestNG",
    "linux" : 200
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.inception.BuildSrcApiChangePerformanceTest.buildSrc abi change",
  "durations" : [ {

namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==2.1.1 \
    --hash=sha256:046356b19d7ad1890c751b99acad5e82dc4a02232013bd9a9a712fddf8eb60f5 \
    --hash=sha256:0b8cc2715a84b7c3b161f9ebbd942740aaed913584cae9cdc7f8ad5ad41943d0 \

        .addEqualityGroup(ImmutableSet.of(), ImmutableSet.of())
        .addEqualityGroup(ImmutableSet.of(1), ImmutableSet.of(1), ImmutableSet.of(1, 1))
        .addEqualityGroup(ImmutableSet.of(1, 2, 1), ImmutableSet.of(2, 1, 1))
        .testEquals();
  }

  @GwtIncompatible("internals")
  public void testControlsArraySize() {
    ImmutableSet.Builder<String> builder = new ImmutableSet.Builder<String>();

namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==2.1.1 \
    --hash=sha256:046356b19d7ad1890c751b99acad5e82dc4a02232013bd9a9a712fddf8eb60f5 \
    --hash=sha256:0b8cc2715a84b7c3b161f9ebbd942740aaed913584cae9cdc7f8ad5ad41943d0 \

        .addEqualityGroup(ImmutableMultiset.of(1), ImmutableMultiset.of(1))
        .addEqualityGroup(ImmutableMultiset.of(1, 1), ImmutableMultiset.of(1, 1))
        .addEqualityGroup(ImmutableMultiset.of(1, 2, 1), ImmutableMultiset.of(2, 1, 1))
        .testEquals();
  }

  public void testIterationOrderThroughBuilderRemovals() {
    ImmutableMultiset.Builder<String> builder = ImmutableMultiset.builder();
    builder.addCopies("a", 2);

        .addEqualityGroup(ImmutableMultiset.of(1), ImmutableMultiset.of(1))
        .addEqualityGroup(ImmutableMultiset.of(1, 1), ImmutableMultiset.of(1, 1))
        .addEqualityGroup(ImmutableMultiset.of(1, 2, 1), ImmutableMultiset.of(2, 1, 1))
        .testEquals();
  }

  public void testIterationOrderThroughBuilderRemovals() {
    ImmutableMultiset.Builder<String> builder = ImmutableMultiset.builder();
    builder.addCopies("a", 2);

namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==2.1.1 \
    --hash=sha256:046356b19d7ad1890c751b99acad5e82dc4a02232013bd9a9a712fddf8eb60f5 \
    --hash=sha256:0b8cc2715a84b7c3b161f9ebbd942740aaed913584cae9cdc7f8ad5ad41943d0 \

    write_action_env_to_bazelrc('HIP_PLATFORM', environ_cp.get('HIP_PLATFORM'))

  if is_windows():
    print('\nWARNING: Cannot build with CUDA support on Windows.\n'
          'Starting in TF 2.11, CUDA build is not supported for Windows. '
          'For using TensorFlow GPU on Windows, you will need to build/install '
          'TensorFlow in WSL2.\n')
    environ_cp['TF_NEED_CUDA'] = '0'
  else: