[`tf.distribute.Strategy`](https://www.tensorflow.org/beta/guide/distribute_strategy)
    API to distribute training with minimal code changes, yielding great
    out-of-the-box performance. It supports distributed training with Keras
    model.fit, as well as with custom training loops. Multi-GPU support is
    available, along with experimental support for multi worker and Cloud TPUs.
    Check out the

te3[uint8(s0)] t2 = xk[k+2] ^ te0[uint8(s2>>24)] ^ te1[uint8(s3>>16)] ^ te2[uint8(s0>>8)] ^ te3[uint8(s1)] t3 = xk[k+3] ^ te0[uint8(s3>>24)] ^ te1[uint8(s0>>16)] ^ te2[uint8(s1>>8)] ^ te3[uint8(s2)] k += 4 s0, s1, s2, s3 = t0, t1, t2, t3 } // Last round uses s-box directly and XORs to produce output. s0 = uint32(sbox0[t0>>24])<<24 | uint32(sbox0[t1>>16&0xff])<<16 | uint32(sbox0[t2>>8&0xff])<<8 | uint32(sbox0[t3&0xff]) s1 = uint32(sbox0[t1>>24])<<24 | uint32(sbox0[t2>>16&0xff])<<16 | uint32(sbox0[t3>>8&0xff])<<8...