-- trace --
Trace Go1.22
EventBatch gen=1 m=0 time=0 size=15
GoStatus dt=1 g=1 m=0 gstatus=3
ProcStatus dt=1 p=1 pstatus=2
ProcStart dt=1 p=1 p_seq=1
GoSyscallEndBlocked dt=1
EventBatch gen=1 m=1 time=0 size=9
ProcStatus dt=1 p=0 pstatus=4
ProcSteal dt=1 p=0 p_seq=1 m=0
EventBatch gen=1 m=18446744073709551615 time=0 size=5
Frequency freq=15625000
EventBatch gen=1 m=18446744073709551615 time=0 size=1
Stacks

  SmallVector<int32_t> offsets;
  if (begin_values.size() == end_values.size()) {
    for (size_t i = 0; i < begin_values.size(); ++i) {
      offsets.push_back(end_values[i] - begin_values[i]);
    }
  }

  return mlir::DenseElementsAttr::get(
      RankedTensorType::get({static_cast<int>(offsets.size())},
                            mlir::IntegerType::get(begin.getContext(), 32)),

            }
            with(it.find { it.details.buildPath == ":include" }) {
                details.rootProject.children.size() == 1
            }
            with(it.find { it.details.buildPath == ":include:inner-include" }) {
                details.rootProject.children.size() == 1
            }
        }

        when:
        configurationCacheRun(task)

        then:

  %2 = "tf.MatMul"(%arg0, %1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:CPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32>
  // CHECK-NEXT: [[r1:%.*]] = tfrt_fallback_async.executeop {{.*}} "tf.BiasAdd"([[r0]], [[result]])

  int32_t num_strings = offset_.size() - 1;
  // Total bytes include:
  //   * size of content (data_.size)
  //   * offset of each tensor (sizeof(int32_t) * num_strings)
  //   * length of whole buffer (int32_t)
  //   * num of strings (int32_t).
  int32_t bytes = data_.size()                            // size of content
                  + sizeof(int32_t) * (num_strings + 2);  // size of header

SUCCESS
-- trace --
Trace Go1.22
EventBatch gen=1 m=0 time=0 size=15
ProcStatus dt=1 p=0 pstatus=1
GoStatus dt=1 g=1 m=0 gstatus=2
GoSyscallBegin dt=1 p_seq=1 stack=0
GoSyscallEndBlocked dt=1
EventBatch gen=1 m=1 time=0 size=14
ProcStatus dt=1 p=2 pstatus=1
GoStatus dt=1 g=2 m=1 gstatus=2
ProcSteal dt=1 p=0 p_seq=2 m=0
EventBatch gen=1 m=18446744073709551615 time=0 size=5
Frequency freq=15625000

        revisedLines = revisedLines.subList(offsetHead, revisedLines.size() - offsetTail);

        original = new int[originalLines.size() + 1];
        revised = new int[revisedLines.size() + 1];
        lcs = new int[originalLines.size() + 1][revisedLines.size() + 1];

        for (int i = 0; i < originalLines.size(); i++) {

func cgoCheckUsingType(typ *_type, src unsafe.Pointer, off, size uintptr) {
	if !typ.Pointers() {
		return
	}

	// Anything past typ.PtrBytes is not a pointer.
	if typ.PtrBytes <= off {
		return
	}
	if ptrdataSize := typ.PtrBytes - off; size > ptrdataSize {
		size = ptrdataSize
	}

	if typ.Kind_&abi.KindGCProg == 0 {
		cgoCheckBits(src, typ.GCData, off, size)
		return
	}
	switch typ.Kind_ & abi.KindMask {

      shape.push_back(static_cast<int64_t>(op->window_strides.size()));
      attributes.emplace_back(builder.getNamedAttr(
          "window_strides",
          BuildVhloTensorV1Attr(shape, op->window_strides, builder)));
    } else {
      std::vector<int64_t> data(op->input_spatial_dimensions.size(), 1);
      std::vector<int64_t> shape;
      shape.push_back(static_cast<int64_t>(data.size()));
      attributes.emplace_back(builder.getNamedAttr(

		32769,
	}
	t.Run("sendfile-to-unix", func(t *testing.T) {
		for _, size := range sizes {
			t.Run(strconv.Itoa(size), func(t *testing.T) {
				testSendFile(t, "unix", int64(size))
			})
		}
	})
	t.Run("sendfile-to-tcp", func(t *testing.T) {
		for _, size := range sizes {
			t.Run(strconv.Itoa(size), func(t *testing.T) {
				testSendFile(t, "tcp", int64(size))
			})
		}
	})
}