/**
   * Returns a linear transformation giving the best fit to the data according to <a
   * href="http://mathworld.wolfram.com/LeastSquaresFitting.html">Ordinary Least Squares linear
   * regression</a> of {@code y} as a function of {@code x}. The count must be greater than one, and
   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code

 * limitations under the License.
 */

package com.google.common.collect;

import static java.util.Arrays.asList;

import com.google.common.base.Function;
import com.google.common.collect.Multiset.Entry;
import com.google.common.collect.testing.SetTestSuiteBuilder;
import com.google.common.collect.testing.TestStringSetGenerator;

 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.util;

import java.util.function.Consumer;

import org.codelibs.fess.Constants;

public class JobProcess {
    protected Process process;

    protected InputStreamThread inputStreamThread;

    public JobProcess(final Process process) {

import "runtime"

// IsRootDisk returns if diskPath belongs to root-disk, i.e the disk mounted at "/"
func IsRootDisk(diskPath string, rootDisk string) (bool, error) {
	if runtime.GOOS == "windows" {
		// On windows this function is not implemented.
		return false, nil
	}
	return SameDisk(diskPath, rootDisk)

			mod = result.module;
			inst = result.instance;
			document.getElementById("runButton").disabled = false;
		}).catch((err) => {
			console.error(err);
		});

		async function run() {
			console.clear();
			await go.run(inst);
			inst = await WebAssembly.instantiate(mod, go.importObject); // reset instance
		}
	</script>

	<button onClick="run();" id="runButton" disabled>Run</button>

==============================================================================*/
#include "tensorflow/c/eager/graph_function.h"

#include <utility>

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),

import java.util.Map;
import java.util.Set;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.function.Consumer;
import java.util.function.Function;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
import java.util.stream.Collectors;

import org.apache.catalina.connector.ClientAbortException;

  /**
   * Returns a linear transformation giving the best fit to the data according to <a
   * href="http://mathworld.wolfram.com/LeastSquaresFitting.html">Ordinary Least Squares linear
   * regression</a> of {@code y} as a function of {@code x}. The count must be greater than one, and
   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code

UPDATE_BRANCH=${UPDATE_BRANCH:-"master"}

SCRIPTPATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
ROOTDIR=$(dirname "${SCRIPTPATH}")
cd "${ROOTDIR}"

# Get the sha of top commit
# $1 = repo
function getSha() {
  git ls-remote "https://github.com/istio/${1}.git" "refs/heads/${UPDATE_BRANCH}" | cut -f 1
}

make update-common

export GO111MODULE=on
go get -u "istio.io/api@${UPDATE_BRANCH}"

var commitRE = /^(?:\d+:)?([0-9a-f]{6,40})$/; // e.g "8486:ab29d2698a47" or "ab29d2698a47"
var gerritChangeIdRE = /^I[0-9a-f]{4,40}$/; // e.g. Id69c00d908d18151486007ec03da5495b34b05f5
var pkgRE = /^[a-z0-9_\/]+$/;

function urlForInput(t) {
    if (!t) {
        return null;
    }

    if (numericRE.test(t)) {
        if (t < 150000) {
            // We could use the golang.org/cl/ handler here, but