for {
		for _i0 := 0; _i0 <= 1; _i0, v_0, v_1 = _i0+1, v_1, v_0 {
			if v_0.Op != OpConst16 {
				continue
			}
			c := auxIntToInt16(v_0.AuxInt)
			if v_1.Op != OpConst16 {
				continue
			}
			d := auxIntToInt16(v_1.AuxInt)
			v.reset(OpConst16)
			v.AuxInt = int16ToAuxInt(c + d)
			return true
		}
		break
	}
	// match: (Add16 <t> (Mul16 x y) (Mul16 x z))
	// result: (Mul16 x (Add16 <t> y z))

	// result: (MOVLconst [c+d])
	for {
		c := auxIntToInt32(v.AuxInt)
		if v_0.Op != OpAMD64MOVLconst {
			break
		}
		d := auxIntToInt32(v_0.AuxInt)
		v.reset(OpAMD64MOVLconst)
		v.AuxInt = int32ToAuxInt(c + d)
		return true
	}
	// match: (ADDLconst [c] (ADDLconst [d] x))
	// result: (ADDLconst [c+d] x)
	for {
		c := auxIntToInt32(v.AuxInt)
		if v_0.Op != OpAMD64ADDLconst {
			break
		}

		x := v_0.Args[0]
		v.reset(OpARM64ADDconst)
		v.AuxInt = int64ToAuxInt(c + d)
		v.AddArg(x)
		return true
	}
	// match: (ADDconst [c] (SUBconst [d] x))
	// result: (ADDconst [c-d] x)
	for {
		c := auxIntToInt64(v.AuxInt)
		if v_0.Op != OpARM64SUBconst {
			break
		}
		d := auxIntToInt64(v_0.AuxInt)
		x := v_0.Args[0]
		v.reset(OpARM64ADDconst)

pkg math (freebsd-riscv64), const MaxInt = 9223372036854775807 #53466
pkg math (freebsd-riscv64), const MaxUint = 18446744073709551615 #53466
pkg math (freebsd-riscv64), const MinInt = -9223372036854775808 #53466
pkg math (freebsd-riscv64-cgo), const MaxInt = 9223372036854775807 #53466
pkg math (freebsd-riscv64-cgo), const MaxUint = 18446744073709551615 #53466
pkg math (freebsd-riscv64-cgo), const MinInt = -9223372036854775808 #53466

		{"MaxFloat32", Const, 0},
		{"MaxFloat64", Const, 0},
		{"MaxInt", Const, 17},
		{"MaxInt16", Const, 0},
		{"MaxInt32", Const, 0},
		{"MaxInt64", Const, 0},
		{"MaxInt8", Const, 0},
		{"MaxUint", Const, 17},
		{"MaxUint16", Const, 0},
		{"MaxUint32", Const, 0},
		{"MaxUint64", Const, 0},
		{"MaxUint8", Const, 0},
		{"Min", Func, 0},
		{"MinInt", Const, 17},
		{"MinInt16", Const, 0},

            "type": "string"
          },

 different computation approaches and orders.
    *   To verify if oneDNN optimizations are on, look for a message with *"oneDNN custom operations are on"* in the log. If the exact phrase is not there, it means they are off.

* Making the `tf.function` type system fully available:

    * `tf.types.experimental.TraceType` now allows custom tf.function inputs to declare Tensor decomposition and type casting support.

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