for _, name := range types {
		if !strings.Contains(sgot, name) {
			t.Fatalf("could not find %s in 'info typrs astruct' output", name)
		}
	}
}

const constsSource = `
package main

const aConstant int = 42
const largeConstant uint64 = ^uint64(0)
const minusOne int64 = -1

func main() {
	println("hello world")
}
`

func TestGdbConst(t *testing.T) {
	checkGdbEnvironment(t)

func.func @testConcatOffsetWithZeros() -> (tensor<3xi32>, tensor<3xi32>, tensor<3xi32>, tensor<3xi32>) {
  %concat_dim = arith.constant dense<1> : tensor<i32>
  %shape0 = arith.constant dense<0> : tensor<3xi32>
  %shape1 = arith.constant dense<[0, 3, 0]> : tensor<3xi32>
  %shape2 = arith.constant dense<[0, 5, 0]> : tensor<3xi32>
  %shape3 = arith.constant dense<0> : tensor<3xi32>

  // CHECK-DAG: [[OFFSET_0:%.*]] = "tf.Const{{.*}} dense<0> : tensor<3xi32>

module {
  func.func @main() -> tensor<1xi64> {
  %0 = "tfl.custom"() {custom_code = "stablehlo.constant", custom_option = #tfl<const_bytes : "0x76616C75650001020109010101062C022401">} : () -> tensor<1xi64>
  func.return %0 : tensor<1xi64>
  }
}

// CHECK:  module {
// CHECK-NEXT:    func @main() -> tensor<1xi64> {
// CHECK-NEXT:    %[[c0:.+]] = stablehlo.constant dense<2> : tensor<1xi64>
// CHECK-NEXT:    return %[[c0]] : tensor<1xi64>
// CHECK-NEXT:    }

calvin <******@****.***> 1706611761 +0800

  %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>

		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) {