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https://github.com/pytorch/pytorch.git
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c25e33789e
Summary: Resubmit #20698 which got messed up. Idea is that when PyTorch is used in a custom build environment (e.g. Facebook), it's useful to track usage of various APIs centrally. This PR introduces a simple very lightweight mechanism to do so - only first invocation of a trigger point would be logged. This is significantly more lightweight than #18235 and thus we can allow to put logging in e.g. TensorImpl. Also adds an initial list of trigger points. Trigger points are added in such a way that no static initialization triggers them, i.e. just linking with libtorch.so will not cause any logging. Further suggestions of what to log are welcomed. Pull Request resolved: https://github.com/pytorch/pytorch/pull/20745 Differential Revision: D15429196 Pulled By: dzhulgakov fbshipit-source-id: a5e41a709a65b7ebccc6b95f93854e583cf20aca
83 lines
2.5 KiB
CMake
83 lines
2.5 KiB
CMake
caffe2_binary_target("convert_caffe_image_db.cc")
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caffe2_binary_target("convert_db.cc")
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caffe2_binary_target("make_cifar_db.cc")
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caffe2_binary_target("make_mnist_db.cc")
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if (NOT ANDROID)
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caffe2_binary_target("parallel_info.cc")
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target_include_directories(parallel_info PUBLIC
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${CMAKE_BINARY_DIR}/aten/src) # provides "ATen/TypeExtendedInterface.h" to ATen.h
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endif()
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caffe2_binary_target("predictor_verifier.cc")
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caffe2_binary_target("print_registered_core_operators.cc")
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caffe2_binary_target("run_plan.cc")
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caffe2_binary_target("speed_benchmark.cc")
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caffe2_binary_target("split_db.cc")
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caffe2_binary_target("db_throughput.cc")
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if (BUILD_TEST AND NOT ANDROID)
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# Core overhead benchmark
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caffe2_binary_target("core_overhead_benchmark.cc")
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target_link_libraries(core_overhead_benchmark benchmark)
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endif()
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if (USE_CUDA)
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caffe2_binary_target("inspect_gpu.cc")
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target_link_libraries(inspect_gpu ${CUDA_LIBRARIES})
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caffe2_binary_target("print_core_object_sizes_gpu.cc")
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if (BUILD_TEST)
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# Core overhead benchmark
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caffe2_binary_target("core_overhead_benchmark_gpu.cc")
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target_link_libraries(core_overhead_benchmark_gpu benchmark ${CUDA_curand_LIBRARY})
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endif()
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endif()
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if (USE_ROCM)
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caffe2_hip_binary_target("hip/inspect_gpu.cc")
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caffe2_hip_binary_target("hip/print_core_object_sizes_gpu.cc")
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if (BUILD_TEST)
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# Core overhead benchmark
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caffe2_hip_binary_target("hip/core_overhead_benchmark_gpu.cc")
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target_link_libraries(core_overhead_benchmark_gpu benchmark)
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endif()
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endif()
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if (USE_ZMQ)
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caffe2_binary_target("zmq_feeder.cc")
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target_link_libraries(zmq_feeder ${ZMQ_LIBRARIES})
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endif()
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if(USE_MPI)
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caffe2_binary_target("run_plan_mpi.cc")
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target_link_libraries(run_plan_mpi ${MPI_CXX_LIBRARIES})
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endif()
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if (USE_OPENCV AND USE_LEVELDB)
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caffe2_binary_target("convert_encoded_to_raw_leveldb.cc")
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target_link_libraries(
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convert_encoded_to_raw_leveldb
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${OpenCV_LIBS} ${LevelDB_LIBRARIES} ${Snappy_LIBRARIES})
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endif()
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if (USE_OPENCV)
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caffe2_binary_target("make_image_db.cc")
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target_link_libraries(make_image_db ${OpenCV_LIBS})
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caffe2_binary_target("convert_image_to_tensor.cc")
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target_link_libraries(convert_image_to_tensor ${OpenCV_LIBS})
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endif()
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if (USE_OBSERVERS)
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caffe2_binary_target(caffe2_benchmark "caffe2_benchmark.cc" "benchmark_helper.cc")
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endif()
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if (USE_OBSERVERS AND USE_OPENCV)
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caffe2_binary_target("convert_and_benchmark.cc")
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target_link_libraries(convert_and_benchmark ${OpenCV_LIBS})
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endif()
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# ---[ tutorials
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caffe2_binary_target("tutorial_blob.cc")
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