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Even when building without Kineto, the <ActivityType.h> header is still
imported and the ActivityType type is used. This patch was copied from
https://github.com/pytorch/pytorch/pull/111048.
diff --git a/torch/csrc/profiler/kineto_shim.h b/torch/csrc/profiler/kineto_shim.h
index e92cbf00..68985ab7 100644
--- a/torch/csrc/profiler/kineto_shim.h
+++ b/torch/csrc/profiler/kineto_shim.h
@@ -12,7 +12,51 @@
#undef USE_KINETO
#endif
+#ifdef USE_KINETO
#include <ActivityType.h>
+#else
+namespace libkineto {
+// copied from header
+/*
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ * All rights reserved.
+ *
+ * This source code is licensed under the BSD-style license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+// Note : All activity types are not enabled by default. Please add them
+// at correct position in the enum
+enum class ActivityType {
+ // Activity types enabled by default
+ CPU_OP = 0, // cpu side ops
+ USER_ANNOTATION,
+ GPU_USER_ANNOTATION,
+ GPU_MEMCPY,
+ GPU_MEMSET,
+ CONCURRENT_KERNEL, // on-device kernels
+ EXTERNAL_CORRELATION,
+ CUDA_RUNTIME, // host side cuda runtime events
+ CUDA_DRIVER, // host side cuda driver events
+ CPU_INSTANT_EVENT, // host side point-like events
+ PYTHON_FUNCTION,
+ OVERHEAD, // CUPTI induced overhead events sampled from its overhead API.
+
+ // Optional Activity types
+ CUDA_SYNC, // synchronization events between runtime and kernels
+ GLOW_RUNTIME, // host side glow runtime events
+ MTIA_RUNTIME, // host side MTIA runtime events
+ CUDA_PROFILER_RANGE, // CUPTI Profiler range for performance metrics
+ MTIA_CCP_EVENTS, // MTIA ondevice CCP events
+ HPU_OP, // HPU host side runtime event
+ XPU_RUNTIME, // host side xpu runtime events
+
+ ENUM_COUNT, // This is to add buffer and not used for any profiling logic. Add your new type before it.
+ OPTIONAL_ACTIVITY_TYPE_START = CUDA_SYNC,
+};
+}
+
+#endif
#include <torch/csrc/Export.h>
#include <torch/csrc/profiler/api.h>
|