}

                PluginExecution execution = new PluginExecution();
                execution.setId(getExecutionId(plugin, gs.goal));
                execution.setPhase(phase);
                execution.setPriority(i - mojos.size());
                execution.getGoals().add(gs.goal);

                execution.setLocation("", location);
                execution.setLocation("id", location);

        String[] c = coords.split(":");
        return Plugin.newBuilder()
                .groupId(c[0])
                .artifactId(c[1])
                .version(c[2])
                .executions(Collections.singletonList(PluginExecution.newBuilder()
                        .id("default-" + c[3])
                        .phase(phase)
                        .goals(Collections.singletonList(c[3]))

        echo Finished downloading %WRAPPER_JAR%
    )
)
@REM End of extension

@REM Provide a "standardized" way to retrieve the CLI args that will
@REM work with both Windows and non-Windows executions.
set MAVEN_CMD_LINE_ARGS=%*

%MAVEN_JAVA_EXE% %JVM_CONFIG_MAVEN_PROPS% %MAVEN_OPTS% %MAVEN_DEBUG_OPTS% -classpath %WRAPPER_JAR% "-Dmaven.multiModuleProjectDirectory=%MAVEN_PROJECTBASEDIR%" %WRAPPER_LAUNCHER% %MAVEN_CONFIG% %*

        for (Element pluginElement : pluginElements) {
            Element executionsElement = pluginElement.child(EXECUTIONS).orElse(null);
            if (executionsElement != null) {
                var executionElements = executionsElement
                        .children(MavenPomElements.Elements.EXECUTION)
                        .toList();
                for (Element executionElement : executionElements) {

    MAVEN_PROJECTBASEDIR=`cygpath --path --windows "$MAVEN_PROJECTBASEDIR"`
fi

# Provide a "standardized" way to retrieve the CLI args that will
# work with both Windows and non-Windows executions.
MAVEN_CMD_LINE_ARGS="$MAVEN_CONFIG $@"
export MAVEN_CMD_LINE_ARGS

WRAPPER_LAUNCHER=org.apache.maven.wrapper.MavenWrapperMain

exec "$JAVACMD" \
  $MAVEN_OPTS \

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

#   which mounts your TensorFlow directory into the container.
#
#   Important: because the container is persistent, you cannot change TFCI
#   variables in between script executions. To forcibly remove the
#   container and start fresh, run "docker rm -f tf". Removing the container
#   destroys some temporary bazel data and causes longer builds.
#

        String result1 = purgeDocJob.execute();

        // Reset the flag
        deleteByQueryCalled = false;

        String result2 = purgeDocJob.execute();

        // Assert both executions were successful
        assertEquals("", result1);
        assertEquals("", result2);
        assertTrue(deleteByQueryCalled);
    }

    @Test
    public void test_execute_withEmptyIndexName() {

// Causes the calling thread to block till all ops dispatched in this executor
// have been executed. Note that "execution" here refers to kernel execution /
// scheduling of copies, etc. Similar to sync execution, it doesn't guarantee
// that lower level device queues (like GPU streams) have been flushed.
//
// This call may not block for execution of ops enqueued concurrently with this
// call.

         *
         * @return true if the thread is actively executing
         */
        public boolean isRunning() {
            return running;
        }

        /**
         * Waits for the crawling thread to terminate.
         * This method blocks until the thread completes its execution.
         * Interrupted exceptions are caught and logged at debug level.
         */