*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.

    private File projectDirectory;

    @Override
    public List<String> getActiveProfileIds() {
        return activeProfileIds;
    }

    /**
     * Sets the identifiers of those profiles that should be activated by explicit demand.
     *
     * @param activeProfileIds The identifiers of those profiles to activate, may be {@code null}.
     * @return This context, never {@code null}.

        this.result = result;
    }

    /**
     * Gets the interim result of the model building up to the point where it failed.
     *
     * @return The interim model building result or {@code null} if not available.
     */
    public ModelBuildingResult getResult() {
        return result;
    }

    /**
     * Gets the model that could not be built properly.
     *

        this.columnNumber = columnNumber;
    }

    /**
     * Gets the one-based index of the line containing the error.
     *
     * @return The one-based index of the line containing the error or a non-positive value if unknown.
     */
    public int getLineNumber() {
        return lineNumber;
    }

    /**
     * Gets the one-based index of the column containing the error.
     *

      this.taskRunner = okHttpClient.taskRunner
    }

    /**
     * Sets the dispatcher used to set policy and execute asynchronous requests. Must not be null.
     */
    fun dispatcher(dispatcher: Dispatcher) =
      apply {
        this.dispatcher = dispatcher
      }

    /**
     * Sets the connection pool used to recycle HTTP and HTTPS connections.
     *

 *
 * @since 3.0-alpha
 */
public interface ProjectDependencyGraph {

    /**
     * Gets all collected projects.
     *
     * @return All collected projects.
     *
     * @since 3.5.0
     */
    List<MavenProject> getAllProjects();

    /**
     * Gets all projects in their intended build order, i.e. after topologically sorting the projects according to their
     * interdependencies.

   * Collections#reverseOrder(Comparator)}.
   *
   * <p><b>Java 8+ users:</b> Use {@code thisComparator.reversed()} instead.
   */
  // type parameter <S> lets us avoid the extra <String> in statements like:
  // Ordering<String> o = Ordering.<String>natural().reverse();
  @GwtCompatible(serializable = true)
  public <S extends T> Ordering<S> reverse() {

     *
     * @return A <code>byte[]</code> containing the challenge.
     */
    public byte[] getChallenge() {
        return challenge;
    }

    /**
     * Sets the challenge for this message.
     *
     * @param challenge The challenge from the domain controller/server.
     */
    public void setChallenge(byte[] challenge) {
        this.challenge = challenge;
    }

// consistently for a given object name.
func TestHashedLayer(t *testing.T) {
	// Test distribution with 16 sets.
	var objs [16]*erasureObjects
	for i := range objs {
		objs[i] = &erasureObjects{}
	}

	sets := &erasureSets{sets: objs[:], distributionAlgo: "CRCMOD"}

	testCases := []struct {
		objectName  string
		expectedObj *erasureObjects
	}{

    }

    public Source getSource() {
        return source;
    }

    /**
     * Gets the model being wrapped.
     *
     * @return The model or {@code null} if not set.
     */
    public Model getModel() {
        return model;
    }

    /**
     * Gets the effective group identifier of the model.
     *