<repository>
			<id>snapshots.central.sonatype.com</id>
			<url>https://central.sonatype.com/repository/maven-snapshots</url>
			<releases>
				<enabled>false</enabled>
			</releases>
			<snapshots>
				<enabled>true</enabled>
			</snapshots>
		</repository>
	</repositories>

                                </div>
                            </div>
                            <div class="card-body">
                                <div>
                                    <la:info id="msg" message="true">
                                        <div class="alert alert-info">${msg}</div>
                                    </la:info>
                                    <la:errors property="_global"/>

                            </div>
                            <div class="card-body">
                                <div>
                                    <la:info id="msg" message="true">
                                        <div class="alert alert-info">${msg}</div>
                                    </la:info>
                                    <la:errors property="_global"/>

  }

  /**
   * Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of
   * lower magnitude.
   */
  static BigInteger randomBigInteger(int numBits) {
    while (true) {
      if (RANDOM_SOURCE.nextBoolean()) {
        return randomNonNegativeBigInteger(numBits);
      }
      BigInteger neg = randomNonNegativeBigInteger(numBits).negate();
      if (neg.signum() != 0) {

    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.

    Random gen = new Random(42); // Fixed seed so test results are deterministic.

    for (int trial = 0; trial < NUM_TRIALS; ++trial) {
      MutableGraph<Integer> graph = graphBuilder.allowsSelfLoops(true).build();

      assertThat(graph.nodes()).isEmpty();
      assertThat(graph.edges()).isEmpty();
      AbstractGraphTest.validateGraph(graph);

      while (graph.nodes().size() < NUM_NODES) {

        try {
          UPDATE_BB.invokeExact(cs, bb);
        } catch (Throwable e) {
          // `update` has no `throws` clause.
          sneakyThrow(e);
        }
        return true;
      } else {
        return false;
      }
    }

    private static @Nullable MethodHandle updateByteBuffer() {
      try {
        Class<?> clazz = Class.forName("java.util.zip.Checksum");

    }

    @Override
    protected int readParameterWordsWireFormat(final byte[] buffer, int bufferIndex) {
        final int start = bufferIndex;
        this.isLoggedInAsGuest = ((buffer[bufferIndex] & 0x01) == 0x01) == true;
        bufferIndex += 2;
        if (this.isExtendedSecurity()) {
            final int blobLength = SMBUtil.readInt2(buffer, bufferIndex);
            bufferIndex += 2;
            this.blob = new byte[blobLength];

    @Override
    public int size() {
        return 20; // Fixed size: 2 + 2 + 4 + 12 (transform structure)
    }

    /**
     * Check if RDMA is supported based on this context
     *
     * @return true if RDMA Transform V1 is supported
     */
    public boolean isRdmaSupported() {
        return transformCount > 0 && rdmaTransformId == 0x0001;
    }

    /**
     * Get the transform count
     *

   
      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.