*   Add `tf.contrib.bayesflow.metropolis_hastings`.
*   Add `log_rate` parameter to `tf.contrib.distributions.Poisson`.
*   Extend `tf.contrib.distributions.bijector` API to handle some non-injective
    transforms.
*   Java:
    *   Generics (e.g., `Tensor<Integer>`) for improved type-safety (courtesy
        @andrewcmyers).
    *   Support for multi-dimensional string tensors.

  * Add an AEAD encrypting transformer for storing secrets encrypted at rest ([#41939](https://github.com/kubernetes/kubernetes/pull/41939), [@smarterclayton](https://github.com/smarterclayton))

specifically for use in, a User Product, and the conveying occurs as
part of a transaction in which the right of possession and use of the
User Product is transferred to the recipient in perpetuity or for a
fixed term (regardless of how the transaction is characterized), the
Corresponding Source conveyed under this section must be accompanied

### Feature

- Parallelize calls to conversion webhooks when watching from etcd to prevent watchcache from lagging and helps clusters with slow conversion webhooks or transformers. 

) << 24) } else if nk > 6 && i%nk == 4 { t = subw(t) } c.enc[i] = c.enc[i-nk] ^ t } // Derive decryption key from encryption key. // Reverse the 4-word round key sets from enc to produce dec. // All sets but the first and last get the MixColumn transform applied. n := c.roundKeysSize() for i := 0; i < n; i += 4 { ei := n - i - 4 for j := 0; j < 4; j++ { x := c.enc[ei+j] if i > 0 && i+4 < n { x = td0[sbox0[x>>24]] ^ td1[sbox0[x>>16&0xff]] ^ td2[sbox0[x>>8&0xff]] ^ td3[sbox0[x&0xff]] } c.dec[i+j] =...