assertFalse(set.isEmpty(), "No Artifacts");
        Iterator iter = set.iterator();
        assertTrue(set.size() == 4, "Set size should be 4, is " + set.size());

        while (iter.hasNext()) {
            Artifact artifact = (Artifact) iter.next();
            System.out.println("Artifact: " + artifact.getDependencyConflictId() + " " + artifact.getVersion()

    for (Class<? super T> itf : allInterfaceClasses) {
      Iterator<Class<?>> iterator = interfaceClasses.iterator();
      boolean addToSet = true;
      while (iterator.hasNext()) {
        Class<?> current = iterator.next();
        if (current == itf || itf.isAssignableFrom(current)) {
          // Skip any super interface of the ones that are already included.
          addToSet = false;

        tempFile.deleteOnExit();
        markForDeletion(tempFile);

        return tempFile;
    }

    public void cleanUp() throws IOException {
        for (Iterator it = filesToDelete.iterator(); it.hasNext(); ) {
            File file = (File) it.next();

            if (file.exists()) {
                if (file.isDirectory()) {
                    FileUtils.deleteDirectory(file);
                } else {

   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

  public void testClear() {
    collection.clear();
    assertTrue("After clear(), a collection should be empty.", collection.isEmpty());
    assertEquals(0, collection.size());
    assertFalse(collection.iterator().hasNext());
  }

  @CollectionFeature.Require(absent = SUPPORTS_REMOVE)
  @CollectionSize.Require(absent = ZERO)
  public void testClear_unsupported() {

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

import java.math.BigDecimal;
import java.util.HashSet;
import java.util.Set;

import org.apache.lucene.index.Term;
import org.apache.lucene.search.PrefixQuery;
import org.apache.lucene.search.TermQuery;
import org.codelibs.fess.Constants;

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.lang.reflect.Method;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Enumeration;
import java.util.HashSet;
import java.util.LinkedHashSet;
import java.util.List;
import java.util.Set;
import java.util.logging.Logger;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestSuite;

        return setupNodeParent;
    }

    private void addSkip(ArrayNode skipParent) {
        Iterator<JsonNode> skipParentIt = skipParent.elements();
        boolean found = false;
        while (skipParentIt.hasNext()) {
            JsonNode arrayEntry = skipParentIt.next();
            if (arrayEntry.isObject()) {
                ObjectNode skipCandidate = (ObjectNode) arrayEntry;
                if (skipCandidate.get("skip") != null) {

    Predicate<? super Entry<K, V>> entryPredicate = multimap.entryPredicate();
    for (Iterator<Entry<K, V>> unfilteredItr = multimap.unfiltered().entries().iterator();
        unfilteredItr.hasNext(); ) {
      Entry<K, V> entry = unfilteredItr.next();
      if (entryPredicate.apply(entry) && Objects.equals(entry.getValue(), o)) {
        unfilteredItr.remove();
        return true;
      }
    }

import static org.junit.jupiter.api.Assertions.assertTrue;

import java.nio.ByteBuffer;
import java.security.SecureRandom;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;