SYS_GETEUID                 = 5105
	SYS_GETEGID                 = 5106
	SYS_SETPGID                 = 5107
	SYS_GETPPID                 = 5108
	SYS_GETPGRP                 = 5109
	SYS_SETSID                  = 5110
	SYS_SETREUID                = 5111
	SYS_SETREGID                = 5112
	SYS_GETGROUPS               = 5113
	SYS_SETGROUPS               = 5114
	SYS_SETRESUID               = 5115
	SYS_GETRESUID               = 5116

	SYS_STAT                         = 4106
	SYS_LSTAT                        = 4107
	SYS_FSTAT                        = 4108
	SYS_UNUSED109                    = 4109
	SYS_IOPL                         = 4110
	SYS_VHANGUP                      = 4111
	SYS_IDLE                         = 4112
	SYS_VM86                         = 4113
	SYS_WAIT4                        = 4114
	SYS_SWAPOFF                      = 4115

// CHECK-NEXT:      %4 = "tfl.pseudo_const"() <{value = dense<[-1, -1, 0, -1]> : tensor<4xi32>}> : () -> tensor<4xi32>
// CHECK-NEXT:      %5 = "tfl.pseudo_const"() <{value = dense<[-1, -1, -1, 0]> : tensor<4xi32>}> : () -> tensor<4xi32>
// CHECK-NEXT:      %6 = "tfl.pseudo_const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>

	SYS_STAT                         = 4106
	SYS_LSTAT                        = 4107
	SYS_FSTAT                        = 4108
	SYS_UNUSED109                    = 4109
	SYS_IOPL                         = 4110
	SYS_VHANGUP                      = 4111
	SYS_IDLE                         = 4112
	SYS_VM86                         = 4113
	SYS_WAIT4                        = 4114
	SYS_SWAPOFF                      = 4115

00000010  31 f3 b1 d8 c7 c9 26 6d  74 0a c0 c0 c0 39 ad b5  |1.....&mt....9..|
00000020  1b b1 dc d3 15 9f a4 96  27 dd 65 85 ad 83 2f 97  |........'.e.../.|
00000030  42 6f 8a 9b 58 fc f8 1b  54 89 cd 9c 11 10 b9 1d  |Bo..X...T.......|
00000040  c3 e1 8e 89 20 a5 2d 0b  31 b5 e0 16 54 ce 93 9b  |.... .-.1...T...|
00000050  de cc b1 af 48 48 33 96  4d a6 00 78 7b 60 3f 7c  |....HH3.M..x{`?||

func.func @prepareStatisticsNudge(%arg0: tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
  %0 = "quantfork.stats"(%arg0) {
    layerStats = dense<[0.1, 1.0]> : tensor<2xf32>
  } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
  %1 = "quantfork.stats"(%0) {
    layerStats = dense<[0.1, 1.0]> : tensor<2xf32>,
    axisStats = dense<[
      [-1.0, 1.0],
      [-8.0, -1.0],
      [-0.5, 0.5]
    ]> : tensor<3x2xf32>, axis = 2 : i64

	}

	var y32 float32
	switch y32 {
	case 1.1:
	case 11/10: // integer division!
	case 11. /* ERROR "duplicate case" */ /10:
	case 2, 3.0, 4.1:
	case 5.2, 1.10 /* ERROR "duplicate case" */ :
	}

	var y64 float64
	switch y64 {
	case 1.1:
	case 11/10: // integer division!
	case 11. /* ERROR "duplicate case" */ /10:
	case 2, 3.0, 4.1:

                    }
                }
            }
        }

        where:
        v1    | v2    | usePluginsDSL
        '1.0' | '1.0' | false
        '1.1' | '1.0' | false

        '1.0' | '1.0' | true
        '1.1' | '1.0' | true
    }

    private String usesTypedAttributesPlugin(String version, boolean usePluginsDSL) {
        String pluginsBlock = usePluginsDSL ? """
            plugins {

	typeGroups := []string{
		"NaN: 1.1: 2.1: 3.1:", // float64
		"false: true:",        // bool
		"1: 2: 3:",            // int
		"a: b: c:",            // string
		"[0 1]: [1 0]:",       // [2]int
		"{0 1}: {1 0}:",       // struct{ x int; y int }
	}
	for _, g := range typeGroups {
		if !strings.Contains(got, g) {
			t.Errorf("sorted map should contain %q", g)
		}
	}

00000050  2e 00 2b 00 02 03 04 00  33 00 24 00 1d 00 20 10  |..+.....3.$... .|
00000060  0e 84 6c ef b3 7e f7 93  33 67 0e d0 5e e4 c6 a8  |..l..~..3g..^...|
00000070  5f c5 ac e7 85 06 86 a4  21 10 aa 56 18 3a 39 14  |_.......!..V.:9.|
00000080  03 03 00 01 01 17 03 03  00 17 a8 c3 84 a3 a2 42  |...............B|
00000090  ba c8 40 ef f8 53 02 58  d7 39 3f b2 34 2f 4e 71  |..@..S.X.9?.4/Nq|