* Add an option `disable_eager_executer_streaming_enqueue` to `tensorflow.ConfigProto.Experimental` to control the eager runtime's behavior around parallel remote function invocations; when set to `True`, the eager runtime will be allowed to execute multiple function invocations in parallel.

* `tf.constant_initializer`

panic("crypto/cipher: incorrect nonce length given to GCM") } if fips140.Enabled { if !g.prefixReady { // The first invocation sets the fixed prefix. g.prefixReady = true g.prefix = byteorder.BEUint32(nonce[:4]) } if g.prefix != byteorder.BEUint32(nonce[:4]) { panic("crypto/cipher: GCM nonce prefix changed") } counter := byteorder.BEUint64(nonce[len(nonce)-8:]) if !g.startReady { // The first invocation sets the starting counter, if not fixed. g.startReady = true g.start = counter } counter -= g.start // Ensure...

range n.limbs { limbs = append(limbs, fmt.Sprintf("%016X", n.limbs[len(n.limbs)-1-i])) } return "{" + strings.Join(limbs, " ") + "}" } // Generate generates an even nat. It's used by testing/quick to produce random // *nat values for quick.Check invocations. func (*Nat) Generate(r *rand.Rand, size int) reflect.Value { limbs := make([]uint, size) for i := 0; i < size; i++ { limbs[i] = uint(r.Uint64()) & ((1 << _W) - 2) } return reflect.ValueOf(&Nat{limbs}) } func testModAddCommutativ(a *Nat, b *Nat)...