%in = arith.constant dense<0.0> : tensor<8xf32>
  %min = arith.constant dense<0.0> : tensor<f32>
  %max = arith.constant dense<255.0> : tensor<f32>
  %rst = "tf.FakeQuantWithMinMaxVars"(%in, %min, %max) {num_bits = 5, narrow_range = false} : (tensor<8xf32>, tensor<f32>, tensor<f32>) -> tensor<8xf32>
  func.return %rst : tensor<8xf32>

// CHECK: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<8xf32>

  %in = arith.constant dense<0.0> : tensor<8xf32>
  %min = arith.constant dense<0.0> : tensor<f32>
  %max = arith.constant dense<15.0> : tensor<f32>
  %rst = "tf.FakeQuantWithMinMaxVars"(%in, %min, %max) {num_bits = 3, narrow_range = false} : (tensor<8xf32>, tensor<f32>, tensor<f32>) -> tensor<8xf32>
  func.return %rst : tensor<8xf32>

// CHECK: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<8xf32>

func ExampleCompare() {
	vs := []constant.Value{
		constant.MakeString("Z"),
		constant.MakeString("bacon"),
		constant.MakeString("go"),
		constant.MakeString("Frame"),
		constant.MakeString("defer"),
		constant.MakeFromLiteral(`"a"`, token.STRING, 0),
	}

	slices.SortFunc(vs, func(a, b constant.Value) int {
		if constant.Compare(a, token.LSS, b) {
			return -1
		}
		if constant.Compare(a, token.GTR, b) {
			return +1

  %0 = arith.constant dense<8> : tensor<i32>
  %1 = arith.constant dense<1> : tensor<i32>

  %2 = arith.constant dense< 4> : tensor<4xi32>
  %3 = arith.constant dense<-2> : tensor<4xi32>

  // CHECK-DAG: %[[CST:.*]] = arith.constant dense<9> : tensor<i32>
  // CHECK-DAG: %[[CST_0:.*]]  = arith.constant dense<6> : tensor<4xi32>
  // CHECK-DAG: %[[CST_1:.*]]  = arith.constant dense<5> : tensor<4xi32>

// special cases
const (
	_n0 = nil /* ERROR "not constant" */
	_n1 = [ /* ERROR "not constant" */ ]int{}
)

// iotas must not be usable in expressions outside constant declarations
type _ [iota /* ERROR "iota outside constant decl" */ ]byte
var _ = iota /* ERROR "iota outside constant decl" */
func _() {
	_ = iota /* ERROR "iota outside constant decl" */
	const _ = iota

		return constant.MakeFloat64(f)
	}
	return nil
}

func fitsFloat64(x constant.Value) bool {
	f, _ := constant.Float64Val(x)
	return !math.IsInf(f, 0)
}

func roundFloat64(x constant.Value) constant.Value {
	f, _ := constant.Float64Val(x)
	if !math.IsInf(f, 0) {
		return constant.MakeFloat64(f)
	}
	return nil
}

// representable checks that a constant operand is representable in the given

    layerStats = dense<[-1.28e-5, 1.27e-5]> : tensor<2xf32>
  } : (tensor<1x5x5x2xf32>) -> tensor<1x5x5x2xf32>
  %w = arith.constant dense<[[[[-1.0, 1.0]]], [[[1.0, 2.0]]], [[[-2.0, 1.0]]]]> : tensor<3x1x1x2xf32>
  %b = arith.constant dense<0.0> : tensor<3xf32>
  %b2 = arith.constant dense<[1.0e-2, 2.1473647e1, -2.1473647e2]> : tensor<3xf32>
  %conv = "tfl.conv_2d"(%0, %w, %b) {

			// Growth to an O(MiB) heap, then constant heap size, alloc/scan rates.
			name:          "Steady",
			gcPercent:     100,
			memoryLimit:   math.MaxInt64,
			globalsBytes:  32 << 10,
			nCores:        8,
			allocRate:     constant(33.0),
			scanRate:      constant(1024.0),
			growthRate:    constant(2.0).sum(ramp(-1.0, 12)),
			scannableFrac: constant(1.0),
			stackBytes:    constant(8192),
			length:        50,

func.func @foldDiv() -> tensor<2xf32> {
  %0 = stablehlo.constant dense<[2.0, 3.0]> : tensor<2xf32>
  %1 = stablehlo.constant dense<[4.0, 6.0]> : tensor<2xf32>
  %2 = stablehlo.divide %0, %1 : tensor<2xf32>
  return %2 : tensor<2xf32>
}

// CHECK-LABEL: foldDiv
// CHECK: stablehlo.constant dense<5.000000e-01> : tensor<2xf32>

// -----

func.func @foldDivLHSSplat() -> tensor<2xf32> {
  %0 = stablehlo.constant dense<2.0> : tensor<2xf32>

    %1 = stablehlo.constant dense<1.000000e+03> : tensor<1x1x1x1xf32>  // Input inverse scale.
    %2 = stablehlo.constant dense<-128> : tensor<1x1x1x1xi8>  // Input zero point.
    %3 = stablehlo.constant dense<1> : tensor<3x3x4x4xi8>  // Quantized filter tensor.
    %4 = stablehlo.constant dense<3.000000e+03> : tensor<1x1x1x4xf32>
    %5 = stablehlo.constant dense<4.000000e+03> : tensor<1x1x1x1xf32>  // Output inverse scale.