subTest(t, debugger+"-dbg", "hist", dbgFlags, moreargs...)
	subTest(t, debugger+"-dbg", "scopes", dbgFlags, moreargs...)
	subTest(t, debugger+"-dbg", "i22558", dbgFlags, moreargs...)

	subTest(t, debugger+"-dbg-race", "i22600", dbgFlags, append(moreargs, "-race")...)

	optSubTest(t, debugger+"-opt", "hist", optFlags, 1000, moreargs...)
	optSubTest(t, debugger+"-opt", "scopes", optFlags, 1000, moreargs...)

        model.getProjectProfile("a").getTaskProfile("a:foo").completed(Stub(TaskState)).setStart(time(12, 25, 0)).setFinish(time(12, 26, 30))
        model.getProjectProfile("a").getTaskProfile("a:bar").completed(Stub(TaskState)).setStart(time(12, 26, 30)).setFinish(time(12, 27, 0))

        model.getProjectProfile("b").configurationOperation.start = time(12, 20, 10)

# CHECK: %[[parse_example:.*]]:8, %[[parse_example_control:.*]] = tf_executor.island wraps "tf.ParseExampleV2"(%arg0,
# CHECK: resultSegmentSizes = array<i32: 2, 2, 2, 2, 0, 0>
# CHECK: tf_executor.fetch %[[parse_example]]#0, %[[parse_example]]#7 : tensor<*xi64>, tensor<*xf32>

node {
  name: "input0"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_STRING

%outputs, %outputs_0) {Tdense = ["tfdtype$DT_FLOAT", "tfdtype$DT_FLOAT"], dense_shapes = [#tf_type.shape<>, #tf_type.shape<>], device = "", num_sparse = 2 : i64, ragged_split_types = [], ragged_value_types = [], resultSegmentSizes = array<i32: 2, 2, 2, 2, 0, 0>, sparse_types = ["tfdtype$DT_STRING", "tfdtype$DT_INT64"]} : (tensor<32x!tf_type.string>, tensor<0x!tf_type.string>, tensor<2x!tf_type.string>, tensor<2x!tf_type.string>, tensor<0x!tf_type.string>, tensor<0xf32>, tensor<0xf32>) -> (tensor<?x2xi64>,...

00000100  45 02 20 32 21 14 38 06  d8 72 2e 00 30 64 1a e2  |E. 2!.8..r..0d..|
00000110  e8 6d 4e 5a e1 d9 42 1e  82 4b 96 25 89 d5 26 13  |.mNZ..B..K.%..&.|
00000120  d3 9c fa 02 21 00 8f 12  28 64 51 4f 44 d5 8c 18  |....!...(dQOD...|
00000130  62 23 b2 43 93 33 05 f3  43 55 a1 d9 ee cd c5 71  |b#.C.3..CU.....q|
00000140  35 91 dd 49 d1 0b 00 76  00 ee 4b bd b7 75 ce 60  |5..I...v..K..u.`|

            assert r.id == 1
            assert r.className == 'class-1'
        }
        0 * action._
    }

    def "merge methods in duplicate classes"() {
        final long startTimeSooner = 122000
        final long startTimeLater = 123000
        def action = Mock(Action)
        def class1 = Stub(TestClassResult) {
            getClassName() >> 'class-1'

	// t.Round(   1ns) = 12:15:30.918273645
	// t.Round(   1µs) = 12:15:30.918274
	// t.Round(   1ms) = 12:15:30.918
	// t.Round(    1s) = 12:15:31
	// t.Round(    2s) = 12:15:30
	// t.Round(  1m0s) = 12:16:00
	// t.Round( 10m0s) = 12:20:00
	// t.Round(1h0m0s) = 12:00:00
}

func ExampleTime_Truncate() {
	t, _ := time.Parse("2006 Jan 02 15:04:05", "2012 Dec 07 12:15:30.918273645")
	trunc := []time.Duration{
		time.Nanosecond,

		"testing.tRunner;runtime/pprof.TestGenericsHashKeyInPprofBuilder;runtime/pprof.genericAllocFunc[go.shape.uint32] [1 256 0 0]",
		"testing.tRunner;runtime/pprof.TestGenericsHashKeyInPprofBuilder;runtime/pprof.genericAllocFunc[go.shape.uint64] [1 32 0 0]",

	C_UAUTO8K     // 0 to 8190, 0 mod 2  + C_PSAUTO
	C_UAUTO16K_16 // 0 to 16380, 0 mod 16
	C_UAUTO16K_8  // 0 to 16380, 0 mod 8
	C_UAUTO16K    // 0 to 16380, 0 mod 4 + C_PSAUTO
	C_UAUTO32K_16 // 0 to 32760, 0 mod 16 + C_PSAUTO
	C_UAUTO32K    // 0 to 32760, 0 mod 8 + C_PSAUTO
	C_UAUTO64K    // 0 to 65520, 0 mod 16 + C_PSAUTO
	C_LAUTOPOOL   // any other constant up to 64 bits (needs pool literal)
	C_LAUTO       // any other constant up to 64 bits

    {
      Tdense = [f32, f32], dense_shapes = [#tf_type.shape<>, #tf_type.shape<>],
      device = "/device:CPU:0", num_sparse = 2 : i64, ragged_split_types = [], ragged_value_types = [],
      resultSegmentSizes = array<i32: 2, 2, 2, 2, 0, 0>,
      sparse_types = [!tf_type.string, !tf_type.string]
    } : (tensor<32x!tf_type.string>, tensor<0x!tf_type.string>, tensor<2x!tf_type.string>, tensor<2x!tf_type.string>, tensor<0x!tf_type.string>, tensor<0xf32>, tensor<0xf32>)