for RNN cells in TF v2. User can use it to implement RNN cells with
        custom behavior.
    *   Keras training and validation curves are shown on the same plot when
        using the TensorBoard callback.
    *   Switched Keras `fit/evaluate/predict` execution to use only a single
        unified path by default unless eager execution has been explicitly

 */
@SuppressSignatureCheck
class YubikeyClientAuth {
  fun run() {
    // The typical PKCS11 slot, may vary with different hardware.
    val slot = 0

    val config = "--name=OpenSC\nlibrary=/Library/OpenSC/lib/opensc-pkcs11.so\nslot=$slot\n"

    // May fail with ProviderException with root cause like
    // sun.security.pkcs11.wrapper.PKCS11Exception: CKR_SLOT_ID_INVALID

    void cacheCapacityAndRetrievalOrder() {
        BufferCacheImpl impl = new BufferCacheImpl(2, 3);
        byte[] a = new byte[1];
        byte[] c = new byte[2];
        byte[] d = new byte[4];

        impl.releaseBuffer(a); // goes to slot 0
        impl.releaseBuffer(c); // goes to slot 1
        impl.releaseBuffer(d); // dropped (cache full)

  }

  @Flaky
  @RetryingTest(5)
  fun missingClientAuthFailsForNeeds() {
    // Fails with 11.0.1 https://github.com/square/okhttp/issues/4598
    // StreamReset stream was reset: PROT...
    val client = buildClient(null, clientIntermediateCa.certificate)
    val socketFactory = buildServerSslSocketFactory()
    server.useHttps(socketFactory)
    server.requireClientAuth()

    assertThrows(IndexOutOfBoundsException.class, () -> sink.putBytes(new byte[8], 0, -1));
  }

  /**
   * This test creates a long random sequence of inputs, then a lot of differently configured sinks
   * process it; all should produce the same answer, the only difference should be the number of
   * process()/processRemaining() invocations, due to alignment.
   */

In many cases you might already know the answer for those questions. 🤓

If you are helping a lot of people with their questions, you will become an official [FastAPI Expert](fastapi-people.md#fastapi-experts){.internal-link target=_blank}. 🎉

So, to balance that out, imagine the following short story:

> You have to clean a big, dirty house.

*Yep, that's the whole story*.

---

There's no waiting 🕙 anywhere, just a lot of work to be done, on multiple places of the house.

  ls -t *.whl | tail -n +2 | xargs mv -t $TFCI_OUTPUT_DIR/extra_wheels
fi

# Repair wheels with auditwheel and delete the old one.
if [[ "$TFCI_WHL_AUDIT_ENABLE" == "1" ]]; then
  python3 -m auditwheel repair --plat "$TFCI_WHL_AUDIT_PLAT" --wheel-dir . *.whl
  # if the wheel is already named correctly, auditwheel won't rename it. so we
  # list all .whl files by their modification time (ls -t) and delete anything

You can use this template to get started, as it includes a lot of the initial set up, security, database and some API endpoints already done for you.

In a typical modern infrastructure deployment, application, database, key-store, etc. already live in containers and are managed by orchestration platforms. MinIO brings robust, scalable, AWS S3 compatible object storage to the lot.