TF_ASSERT_OK(CreateMlirModule("empty_func.mlir"));

  TF_EXPECT_OK(ExportFromTensorflowDialectToExecutor(*mlir_module_));

  EXPECT_EQ(compilation_status.Delta(kExportSuccess), 1);
  EXPECT_EQ(compilation_status.Delta(kExportFailed), 0);
}

TEST_F(TensorflowDialectToExecutorTest, ErrorsWhenCannotConvert) {
  CellReader<int64_t> compilation_status(kExportStreamzName);

		Tk := measureKaratsuba(th)

		// improvement over Tb
		delta := (Tb - Tk) * 100 / Tb

		fmt.Printf("th = %3d  Tk = %10s  %4d%%", th, Tk, delta)

		// determine break-even point
		if Tk < Tb && th1 < 0 {
			th1 = th
			fmt.Print("  break-even point")
		}

		// determine diminishing return
		if 0 < delta && delta < deltaOld && th2 < 0 {
			th2 = th
			fmt.Print("  diminishing return")
		}

// See the WaitGroup example.
func (wg *WaitGroup) Add(delta int) {
	if race.Enabled {
		if delta < 0 {
			// Synchronize decrements with Wait.
			race.ReleaseMerge(unsafe.Pointer(wg))
		}
		race.Disable()
		defer race.Enable()
	}
	state := wg.state.Add(uint64(delta) << 32)
	v := int32(state >> 32)
	w := uint32(state)
	if race.Enabled && delta > 0 && v == int32(delta) {
		// The first increment must be synchronized with Wait.

func (x *Int32) CompareAndSwap(old, new int32) (swapped bool) {
	return CompareAndSwapInt32(&x.v, old, new)
}

// Add atomically adds delta to x and returns the new value.
func (x *Int32) Add(delta int32) (new int32) { return AddInt32(&x.v, delta) }

// And atomically performs a bitwise AND operation on x using the bitmask
// provided as mask and returns the old value.

  ASSERT_THAT(result, IsOkOrFiltered());
  EXPECT_EQ(mlir_bridge_legalize_count.Delta("tf.Acos"), 0);
  EXPECT_THAT(result,
              IncrementedOrFiltered(counts.Delta(kMlirCombinedMlirSuccess), 1));
  EXPECT_THAT(result,
              IncrementedOrFiltered(counts.Delta(kMlirCombinedOldSuccess), 1));
}

TEST(LegalizeWithCombinedBridge,

  })";
  CreateModule(kMlirModuleStr);
  CellReader<int64_t> reader(kMetricsName);

  auto result = Run();

  EXPECT_TRUE(result.succeeded());
  EXPECT_EQ(reader.Delta("tf.ConcatV2"), 1);
  EXPECT_EQ(reader.Delta("func.return"), 1);
  EXPECT_EQ(reader.Delta("func.func"), 0);
}

TEST_F(LegalizeTfTypesTest, RecordsStreamzNoQuantOps) {
  static constexpr char kMlirModuleStr[] = R"(

	// histogram.
	mudDegree = 1024
)

type edge struct {
	// At x, the function increases by y.
	x, delta float64
	// Additionally at x is a Dirac delta function with area dirac.
	dirac float64
}

// add adds a uniform function over [l, r] scaled so the total weight
// of the uniform is area. If l==r, this adds a Dirac delta function.
func (d *mud) add(l, r, area float64) {
	if area == 0 {
		return
	}

	if r < l {

        then:
        clock.currentTime == START_MILLIS + 15
    }

    def "provides current time based on nanoTime delta"() {
        when:
        setNanos(delta)

        then:
        clock.currentTime == START_MILLIS + Math.max(0, delta)

        where:
        delta << [0, 100, -100]
    }

    def "resyncs with system wall clock"() {
        when:
        setNanos(10)

        then:

  CellReader<int64_t> static_error(kNonStaticOpStreamz);
  CreateModule(kNonStaticFailure);

  auto result = Run();

  EXPECT_TRUE(result.failed());
  EXPECT_EQ(legal_error.Delta("mhlo.dynamic_iota"), 0);
  EXPECT_EQ(static_error.Delta("mhlo.dynamic_iota"), 1);
}

TEST_F(VerifyTfxlaLegalizationTest, SkipsSpecificNonStaticInputs) {
  // Using a string constant here instead of testdata to make this compatible

}

func (v *Float) appendJSON(b []byte) []byte {
	return strconv.AppendFloat(b, math.Float64frombits(v.f.Load()), 'g', -1, 64)
}

// Add adds delta to v.
func (v *Float) Add(delta float64) {
	for {
		cur := v.f.Load()
		curVal := math.Float64frombits(cur)
		nxtVal := curVal + delta
		nxt := math.Float64bits(nxtVal)
		if v.f.CompareAndSwap(cur, nxt) {
			return
		}
	}
}

// Set sets v to value.