tot := t.list[len(t.list)-1].time.Sub(pt.time)
		for i := 1; i < len(t.list); i++ {
			qt := &t.list[i] // current timestamp
			dt := qt.time.Sub(pt.time)

			var label string
			var events []*event
			if pt.start {
				// previous phase started
				label = pt.label
				events = t.events[i-1]
				if qt.start {
					// start implicitly ended previous phase; nothing to do
				} else {

// squashed to a requantize op if the scales are different.
def : Pat<(TFL_QuantizeOp (TFL_DequantizeOp $in), $qt), (replaceWithValue $in)>;

// If the tfl.dequantize op wasn't fused, we shouldn't quantize the floating
// point constant.
def : Pat<(TFL_DequantizeOp
             (TFL_QuantizeOp (Arith_ConstantOp F32ElementsAttr:$cst), $qt)),
          (TFL_ConstOp $cst)>;

// Transpose conv supports hybrid computation with quantized weights.

	qt := qs.QStats
	m.Set(replicationAverageQueuedBytes, float64(qt.Avg.Bytes))
	m.Set(replicationAverageQueuedCount, float64(qt.Avg.Count))
	m.Set(replicationMaxQueuedBytes, float64(qt.Max.Bytes))
	m.Set(replicationMaxQueuedCount, float64(qt.Max.Count))
	m.Set(replicationLastMinuteQueuedBytes, float64(qt.Curr.Bytes))
	m.Set(replicationLastMinuteQueuedCount, float64(qt.Curr.Count))

	qa := qs.ActiveWorkers

      (ins), [{}], [{return false;}]>,
  ];
}

// Specify this trait if the op has a fixed output value range.
class FixedResultScale<QuantizedType qt> : NativeOpTrait<!strconcat(
  "quant::FixedResult", qt.name, "Scale<", qt.asTraitArgsStr, ">::Impl")>;

// Specify this trait if the bias-th input of the op is a bias input, which
// needs a scale based on the scales of op1 and op2.

// TODO(b/185915462): Compare the scale of input and output. This can also be
// squashed to a requantize op if the scales are different.

include "tensorflow/compiler/mlir/lite/ir/tfl_ops.td"

// Both Quantize and Dequantize ops have side effects, so we have to define
// patterns to remove dead ones after the quantization rewrite.
def : Pat<(TFL_QuantizeOp:$op $in, $qt), (replaceWithValue $in), [(HasNoUseOf:$op)]>;

package work

import (
	"os"
	"strings"
	"testing"
)

var goodCompilerFlags = [][]string{
	{"-DFOO"},
	{"-Dfoo=bar"},
	{"-Ufoo"},
	{"-Ufoo1"},
	{"-F/Qt"},
	{"-F", "/Qt"},
	{"-I/"},
	{"-I/etc/passwd"},
	{"-I."},
	{"-O"},
	{"-O2"},
	{"-Osmall"},
	{"-W"},
	{"-Wall"},
	{"-Wp,-Dfoo=bar"},
	{"-Wp,-Ufoo"},
	{"-Wp,-Dfoo1"},
	{"-Wp,-Ufoo1"},
	{"-flto"},

00000000  16 03 03 00 5d 02 00 00  59 03 03 1c ad ae e9 64  |....]...Y......d|
00000010  35 80 c6 04 f5 69 05 bb  5c 38 78 d3 99 2f ad e6  |5....i..\8x../..|
00000020  56 20 d4 79 89 1a 51 54  14 ac 6d 20 06 6d 1a bd  |V .y..QT..m .m..|
00000030  04 cf 4f 42 3d aa 31 3b  fb dc c1 85 42 c3 6d 12  |..OB=.1;....B.m.|
00000040  27 98 be 4b 88 93 45 0e  78 ba d8 13 c0 2f 00 00  |'..K..E.x..../..|

// reconstructBlock dequantizes, performs the inverse DCT and stores the block
// to the image.
func (d *decoder) reconstructBlock(b *block, bx, by, compIndex int) error {
	qt := &d.quant[d.comp[compIndex].tq]
	for zig := 0; zig < blockSize; zig++ {
		b[unzig[zig]] *= qt[zig]
	}
	idct(b)
	dst, stride := []byte(nil), 0
	if d.nComp == 1 {
		dst, stride = d.img1.Pix[8*(by*d.img1.Stride+bx):], d.img1.Stride
	} else {

00000090  01 16 03 03 00 40 ac 30  bb 83 2f e2 a1 98 a3 c5  |.....@.0../.....|
000000a0  9c e3 55 36 70 a0 10 fc  53 7e 2d ae f1 02 d7 04  |..U6p...S~-.....|
000000b0  1f 4e 5d ed 33 29 99 04  54 8e 51 74 d5 2a 73 21  |.N].3)..T.Qt.*s!|
000000c0  4f bf 8b 0c 04 b2 f2 d4  3e a7 f6 ee 8b fb 3a 0b  |O.......>.....:.|
000000d0  86 27 7c a7 bb 32                                 |.'|..2|
>>> Flow 4 (server to client)