var mountPointCache sync.Map

// IsLikelyMountPoint determines if a directory is a mountpoint.
func IsLikelyMountPoint(path string) bool {
	path = filepath.Dir(path)
	if v, ok := mountPointCache.Load(path); ok {
		return v.(bool)
	}
	wpath, _ := windows.UTF16PtrFromString(path)
	wvolume := make([]uint16, len(path)+1)

	if err := windows.GetVolumePathName(wpath, &wvolume[0], uint32(len(wvolume))); err != nil {

		return globalLockServer
	}
	return newlockRESTClient(endpoint)
}

// Returns a lock rest client.
func newlockRESTClient(ep Endpoint) *lockRESTClient {
	return &lockRESTClient{globalLockGrid.Load().Connection(ep.GridHost())}

                return doc
            } catch (ClassDocGenerationException e) {
                throw e
            } catch (Exception e) {
                throw new ClassDocGenerationException("Could not load the class documentation for class '$className'.", e)
            }
        } finally {
            currentlyBuilding.removeLast()
        }
    }

    private File getFileForClass(String className) {

        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());

    // 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;
  }

        Properties systemProperties = new Properties();

        // ----------------------------------------------------------------------
        // Load environment and system properties
        // ----------------------------------------------------------------------

        EnvironmentUtils.addEnvVars(systemProperties);

  private GraphConstants() {}

  static final int EXPECTED_DEGREE = 2;

  static final int DEFAULT_NODE_COUNT = 10;
  static final int DEFAULT_EDGE_COUNT = DEFAULT_NODE_COUNT * EXPECTED_DEGREE;

  // Load factor and capacity for "inner" (i.e. per node/edge element) hash sets or maps
  static final float INNER_LOAD_FACTOR = 1.0f;
  static final int INNER_CAPACITY = 2; // ceiling(EXPECTED_DEGREE / INNER_LOAD_FACTOR)

    </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.

    @PostConstruct
    public void init() {
        if (logger.isDebugEnabled()) {
            logger.debug("Initialize {}", this.getClass().getSimpleName());
        }
        load();
    }

    @Override
    public int load() {
        final List<LabelType> labelTypeList = ComponentUtil.getComponent(LabelTypeService.class).getLabelTypeList();
        buildLabelTypeItems(labelTypeList);