// Round down to the nearest power of 2.
    expectedEntries = max(expectedEntries, 2);
    int tableSize = Integer.highestOneBit(expectedEntries);
    // Check to make sure that we will not exceed the maximum load factor.
    if (expectedEntries > (int) (loadFactor * tableSize)) {
      tableSize <<= 1;
      return (tableSize > 0) ? tableSize : MAX_TABLE_SIZE;
    }
    return tableSize;
  }

        File pom0 = new File(localRepo, "p0/pom.xml");

        File pom0Basedir = pom0.getParentFile();

        File pom1 = new File(pom0Basedir, "p1/pom.xml");

        // load everything...
        MavenProject project0 = getProjectWithDependencies(pom0);
        MavenProject project1 = getProjectWithDependencies(pom1);

        assertEquals(pom0Basedir, project1.getParent().getBasedir());

	req.Header.Set(xhttp.MinIOPeerCall, "true")

	resp, err := httpClient.Do(req)
	if err != nil {
		return err
	}
	xhttp.DrainBody(resp.Body)

	return nil
}

// connect to list of endpoints and load all Erasure disk formats, validate the formats are correct
// and are in quorum, if no formats are found attempt to initialize all of them for the first
// time. additionally make sure to close all the disks used in this attempt.

    </default>
  </defaults>

  <classes>
    <class rootElement="true" xml.tagName="extensions" xsd.compositor="sequence">
      <name>CoreExtensions</name>
      <description>Extensions to load.</description>
      <version>1.0.0+</version>
      <fields>
        <field>
          <name>extensions</name>
          <description>A set of build extensions to use from this project.</description>

   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   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.

    }
  }

  @SuppressWarnings("GoodTime") // timestamps as numeric primitives
  private V load(K key) throws ExecutionException {
    long startTime = ticker.read();
    V calculatedValue;
    try {
      calculatedValue = loader.load(key);
      put(key, calculatedValue);
    } catch (RuntimeException e) {
      statsCounter.recordLoadException(ticker.read() - startTime);

redirected to the OpenID Provider in the beginning. For some setups, extra configuration may be required for this step to work correctly.

For a simple setup where the user/client app accesses MinIO directly (i.e. with no intervening proxies/load-balancers), and each MinIO server (if there are more than one) has a unique domain name, this redirection should work automatically with no further configuration. For example, if the MinIO service is being accessed by the browser at the URL `https...

    /**
     * <p>
     * PluginId =&gt; ExtensionRealmCache.CacheRecord map MavenProject context value key. The map is used to ensure the
     * same class realm is used to load build extensions and load mojos for extensions=true plugins.
     * </p>
     * <strong>Note:</strong> This is part of internal implementation and may be changed or removed without notice
     *
     * @since 3.3.0
     */

            .concurrencyLevel(segments)
            .maximumSize(maximumSize)
            .build(
                new CacheLoader<Integer, Integer>() {
                  @Override
                  public Integer load(Integer from) {
                    return (int) misses.incrementAndGet();
                  }
                });

    // To start, fill up the cache.

        try (InputStream is = DefaultRuntimeInformation.class.getResourceAsStream("/" + resource)) {
            if (is != null) {
                props.load(is);
            } else {
                logger.warn("Could not locate " + resource + " on classpath, Maven runtime information not available");
            }
        } catch (IOException e) {