diff --git a/torch/csrc/autograd/init.cpp b/torch/csrc/autograd/init.cpp
index 28c1a43..70d8f7b 100644
--- a/torch/csrc/autograd/init.cpp
+++ b/torch/csrc/autograd/init.cpp
@@ -301,12 +301,7 @@ PyObject* THPAutograd_initExtension(PyObject* _unused, PyObject* unused) {
       .def("privateuse1_elapsed_us", &KinetoEvent::privateuse1ElapsedUs)
       .def(
           "is_user_annotation",
-          [](const KinetoEvent& e) {
-            return e.activityType() ==
-                (uint8_t)libkineto::ActivityType::USER_ANNOTATION ||
-                e.activityType() ==
-                (uint8_t)libkineto::ActivityType::GPU_USER_ANNOTATION;
-          })
+          [](const KinetoEvent& e) { return e.isUserAnnotation(); })
       .def("nbytes", [](const KinetoEvent& e) { return e.nBytes(); })
       // whether the event is hidden
       .def(
diff --git a/torch/csrc/autograd/profiler_kineto.cpp b/torch/csrc/autograd/profiler_kineto.cpp
index dd4598669827e..85de1c3af923f 100644
--- a/torch/csrc/autograd/profiler_kineto.cpp
+++ b/torch/csrc/autograd/profiler_kineto.cpp
@@ -1081,6 +1081,13 @@ int64_t KinetoEvent::privateuse1ElapsedUs() const {
   return -1;
 }
 
+bool KinetoEvent::isUserAnnotation() const {
+  constexpr uint8_t kUserAnnotation = 1;
+  constexpr uint8_t kGpuUserAnnotation = 2;
+  const auto type = activityType();
+  return type == kUserAnnotation || type == kGpuUserAnnotation;
+}
+
 void KinetoEvent::getPerfEventCounters(std::vector<uint64_t>& in) const {
   return result_->visit(c10::overloaded(
       [&in](const ExtraFields<EventType::TorchOp>& e) -> void {
diff --git a/torch/csrc/autograd/profiler_kineto.h b/torch/csrc/autograd/profiler_kineto.h
index 777b8a5851ed5..c3135c61245d4 100644
--- a/torch/csrc/autograd/profiler_kineto.h
+++ b/torch/csrc/autograd/profiler_kineto.h
@@ -67,6 +67,7 @@ struct TORCH_API KinetoEvent {
   bool isPythonFunction() const;
   int64_t cudaElapsedUs() const;
   int64_t privateuse1ElapsedUs() const;
+  bool isUserAnnotation() const;
   void getPerfEventCounters(torch::profiler::perf_counters_t& /*in*/) const;
   extra_meta_t extraMeta() const;
   std::string metadataJson() const;
diff --git a/torch/csrc/profiler/collection.cpp b/torch/csrc/profiler/collection.cpp
index eb29cb7382127..8ee3a9e7707a8 100644
--- a/torch/csrc/profiler/collection.cpp
+++ b/torch/csrc/profiler/collection.cpp
@@ -572,11 +572,13 @@ std::string toString(const ExtraFields<EventType::PyCall>& e) {
       e.callsite_.funcname_.str());
 }
 
+#ifdef USE_KINETO
 auto scopeToType(at::RecordScope scope) {
   return scope == at::RecordScope::USER_SCOPE
       ? libkineto::ActivityType::USER_ANNOTATION
       : libkineto::ActivityType::CPU_OP;
 }
+#endif
 
 int64_t torchOpEndNS(
     const ExtraFields<EventType::TorchOp>& e,
@@ -625,6 +627,7 @@ std::string Result::overload_name() const {
       [](const auto& e) -> std::string { return ""; }));
 }
 
+#ifdef USE_KINETO
 libkineto::ActivityType Result::kinetoType() const {
   return visit(c10::overloaded(
       ATTRIBUTE(TorchOp, scopeToType(e.scope_)),
@@ -637,6 +640,11 @@ libkineto::ActivityType Result::kinetoType() const {
       ATTRIBUTE(PythonGC, libkineto::ActivityType::PYTHON_FUNCTION),
       ATTRIBUTE(Kineto, e.activity_type_)));
 }
+#else
+libkineto::ActivityType Result::kinetoType() const {
+  return libkineto::ActivityType::NONE;
+}
+#endif
 
 uint64_t Result::correlationID() const {
   return visit(c10::overloaded(
diff --git a/torch/csrc/profiler/kineto_shim.cpp b/torch/csrc/profiler/kineto_shim.cpp
index fa232e1a01016..0ddf62997a07e 100644
--- a/torch/csrc/profiler/kineto_shim.cpp
+++ b/torch/csrc/profiler/kineto_shim.cpp
@@ -138,6 +138,7 @@ TraceWrapper::TraceWrapper(const int64_t start_time, const std::string& name)
 }
 #endif // USE_KINETO
 
+#ifdef USE_KINETO
 activity_t* TraceWrapper::addCPUActivity(
     const std::string& name,
     const libkineto::ActivityType type,
@@ -145,7 +146,6 @@ activity_t* TraceWrapper::addCPUActivity(
     const uint64_t correlation_id,
     const int64_t start_time,
     const int64_t end_time) {
-#ifdef USE_KINETO
   TORCH_CHECK((bool)(*this), "Cannot add event to non-existent trace.");
   cpu_trace_->emplace_activity(cpu_trace_->span, type, name);
   auto& act = libkineto::CpuTraceBuffer::toRef(cpu_trace_->activities.back());
@@ -157,10 +157,18 @@ activity_t* TraceWrapper::addCPUActivity(
     act.endTime = end_time;
   }
   return cpu_trace_->activities.back().get();
+}
 #else
+activity_t* TraceWrapper::addCPUActivity(
+    const std::string& name,
+    const libkineto::ActivityType type,
+    const DeviceAndResource device_and_resource,
+    const uint64_t correlation_id,
+    const int64_t start_time,
+    const int64_t end_time) {
   return nullptr;
-#endif // USE_KINETO
 }
+#endif // USE_KINETO
 
 void TraceWrapper::transferCpuTrace(int64_t end_time) {
 #ifdef USE_KINETO
@@ -473,6 +481,7 @@ void logInvariantViolation(
 
 namespace autograd::profiler {
 c10::DeviceType deviceTypeFromActivity(libkineto::ActivityType activity_type) {
+#ifdef USE_KINETO
   // PrivateUse1 kineto backend reuse some ActivityTypes,
   // If PrivateUse1 backend is enabled, this should return
   // c10::DeviceType::PrivateUse1.
@@ -524,6 +533,9 @@ c10::DeviceType deviceTypeFromActivity(libkineto::ActivityType activity_type) {
       return c10::DeviceType::CPU;
     }
   }
+#else
+  return c10::DeviceType::CPU;
+#endif // USE_KINETO
 }
 
 void addMetadataJson(const std::string& key, const std::string& value) {
diff --git a/torch/csrc/profiler/kineto_shim.h b/torch/csrc/profiler/kineto_shim.h
index 4f9bdc6770507..ddc00c03fa9cc 100644
--- a/torch/csrc/profiler/kineto_shim.h
+++ b/torch/csrc/profiler/kineto_shim.h
@@ -12,7 +12,21 @@
 #undef USE_KINETO
 #endif
 
+#ifdef USE_KINETO
 #include <ActivityType.h>
+#else
+namespace libkineto {
+enum class ActivityType : uint8_t {
+  CPU_OP = 0,
+  USER_ANNOTATION,
+  GPU_USER_ANNOTATION,
+  NONE = CPU_OP,
+};
+inline const char* toString(ActivityType) {
+  return "CPU_OP";
+}
+} // namespace libkineto
+#endif
 
 #include <torch/csrc/Export.h>
 #include <torch/csrc/profiler/api.h>