Even when building without Kineto, the header is still imported and the ActivityType type is used. This patch was copied from https://github.com/pytorch/pytorch/pull/111048 and adapted. diff --git a/torch/csrc/profiler/kineto_shim.h b/torch/csrc/profiler/kineto_shim.h index 7a3b788..7f49d18 100644 --- a/torch/csrc/profiler/kineto_shim.h +++ b/torch/csrc/profiler/kineto_shim.h @@ -12,7 +12,55 @@ #undef USE_KINETO #endif +#ifdef USE_KINETO #include +#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 + MTIA_WORKLOADD, + + PRIVATEUSE1_RUNTIME, + PRIVATEUSE1_DRIVER, + + 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 #include