[`tf.keras.layers.MultiHeadAttention`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MultiHeadAttention).
        *   Implicit masks for `query`, `key` and `value` inputs will
            automatically be used to compute a correct attention mask for the
            layer. These padding masks will be combined with any
            `attention_mask` passed in directly when calling the layer. This can
            be used with

func gcmCounterCryptGener(b *aes.Block, out, src []byte, counter *[gcmBlockSize]byte) { var mask [gcmBlockSize]byte for len(src) >= gcmBlockSize { aes.EncryptBlockInternal(b, mask[:], counter[:]) gcmInc32(counter) subtle.XORBytes(out, src, mask[:]) out = out[gcmBlockSize:] src = src[gcmBlockSize:] } if len(src) > 0 { aes.EncryptBlockInternal(b, mask[:], counter[:]) gcmInc32(counter) subtle.XORBytes(out, src, mask[:]) } } // gcmInc32 treats the final four bytes of counterBlock as a big-endian value //...