tTable, aes.EncryptionKeySchedul(&g.cipher)) } func seal(out []byte, g *GCM, nonce, plaintext, data []byte) { if !supportsAESGCM { sealGeneric(out, g, nonce, plaintext, data) return } var counter, tagMask [gcmBlockSize]byte if len(nonce) == gcmStandardNonceSize { // Init counter to nonce||1 copy(counter[:], nonce) counter[gcmBlockSize-1] = 1 } else { // Otherwise counter = GHASH(nonce) gcmAesData(&g.productTable, nonce, &counter) gcmAesFinish(&g.productTable, &tagMask, &counter, uint64(len(nonce)),...

tTable, aes.EncryptionKeySchedul(&g.cipher)) } func seal(out []byte, g *GCM, nonce, plaintext, data []byte) { if !supportsAESGCM { sealGeneric(out, g, nonce, plaintext, data) return } var counter, tagMask [gcmBlockSize]byte if len(nonce) == gcmStandardNonceSize { // Init counter to nonce||1 copy(counter[:], nonce) counter[gcmBlockSize-1] = 1 } else { // Otherwise counter = GHASH(nonce) gcmAesData(&g.productTable, nonce, &counter) gcmAesFinish(&g.productTable, &tagMask, &counter, uint64(len(nonce)),...

## Breaking Changes

*   Prebuilt binaries are now (as of TensorFlow 1.10) built against NCCL 2.2 and
    no longer include NCCL in the binary install. TensorFlow usage with multiple
    GPUs and NCCL requires upgrade to
    [NCCL 2.2](https://developer.nvidia.com/nccl). See updated install guides:
    [TensorFlow GPU support](https://www.tensorflow.org/install/gpu) and