}
func TestSpec(t *testing.T) { testDirFiles(t, "../../../../internal/types/testdata/spec", 20, false) } // TODO(gri) narrow column tolerance
func TestExamples(t *testing.T) {
	testDirFiles(t, "../../../../internal/types/testdata/examples", 125, false)
} // TODO(gri) narrow column tolerance
func TestFixedbugs(t *testing.T) {

	cert := &x509.Certificate{
		NotAfter: time.Now().Add(validity),
	}

	e := newExpirationInfo("x", cert, false)

	if math.Abs(float64(validity-e.ResidualTime())) > float64(5*time.Second) { // using 5s of tolerance because the function is not deterministic (it uses time.Now()) and we want to avoid flakes
		t.Errorf("expected IsInRenewalWindow equal to %v, saw %v", validity, e.ResidualTime())
	}

// CHECK-NEXT:  } ]
// CHECK-NEXT:  signature_defs: [ ]
// CHECK-NEXT:}

func.func @main(%arg0: tensor<4xf32>, %arg1: tensor<4x!quant.uniform<u8:f32, 0.1>>) -> tensor<4xf32> {
  "tfl.NumericVerify"(%arg1, %arg0) {tolerance = 0.1 : f32} : (tensor<4x!quant.uniform<u8:f32, 0.1>>, tensor<4xf32>) -> (tensor<4xf32>)
  func.return %arg0 : tensor<4xf32>

// renewed the leader lease. Thus the implementation is tolerant to arbitrary
// clock skew, but is not tolerant to arbitrary clock skew rate.
//
// However the level of tolerance to skew rate can be configured by setting
// RenewDeadline and LeaseDuration appropriately. The tolerance expressed as a
// maximum tolerated ratio of time passed on the fastest node to time passed on
// the slowest node can be approximately achieved with a configuration that sets

	// backwards and not scale down below any recommendation it made during that period.
	HorizontalPodAutoscalerDownscaleStabilizationWindow metav1.Duration
	// horizontalPodAutoscalerTolerance is the tolerance for when
	// resource usage suggests upscaling/downscaling
	HorizontalPodAutoscalerTolerance float64
	// HorizontalPodAutoscalerCPUInitializationPeriod is the period after pod start when CPU samples
	// might be skipped.

/** Asserts that double actual == expected within the specified tolerance.
 *  If actual is within granularity of expected, the assertion passes.
 *  Reports failure with no other action.
 */
#define CU_ASSERT_DOUBLE_EQUAL(actual, expected, granularity) \

	fs.Float64Var(&o.HorizontalPodAutoscalerTolerance, "horizontal-pod-autoscaler-tolerance", o.HorizontalPodAutoscalerTolerance, "The minimum change (from 1.0) in the desired-to-actual metrics ratio for the horizontal pod autoscaler to consider scaling.")

// DEBUG: %[[f_split:.*]]:2 = "tfl.split"
// DEBUG: %[[q_split:.*]]:2 = "tfl.split"
// DEBUG: "tfl.NumericVerify"(%[[q_split]]#1, %[[f_split]]#1) <{log_if_failed = true, tolerance = 5.000000e+00 : f32}>
// DEBUG: "tfl.NumericVerify"(%[[q_split]]#0, %[[f_split]]#0) <{log_if_failed = true, tolerance = 5.000000e+00 : f32}>
}

// DEBUG-LABEL: NotQuantizePow
func.func @NotQuantizePow(%arg0: tensor<4x!quant.uniform<u8:f32, 1.0>>,

			t.Errorf("%s, bounds differ: %v and %v", tc.filename, m0.Bounds(), m1.Bounds())
			continue
		}
		// Compare the average delta to the tolerance level.
		avgDelta := averageDelta(m0, m1)
		if avgDelta > tc.tolerance {
			t.Errorf("%s: average delta is too high. expected: %d, got %d", tc.filename, tc.tolerance, avgDelta)
			continue
		}
	}
}

func TestSubImage(t *testing.T) {
	m0, err := readImg("../testdata/video-001.gif")

			r0, g0, b0, a0, r1, g1, b1, a1)
	}
	return nil
}

// TestYCbCrRoundtrip tests that a subset of RGB space can be converted to YCbCr
// and back to within 2/256 tolerance.
func TestYCbCrRoundtrip(t *testing.T) {
	for r := 0; r < 256; r += 7 {
		for g := 0; g < 256; g += 5 {
			for b := 0; b < 256; b += 3 {
				r0, g0, b0 := uint8(r), uint8(g), uint8(b)