mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
Remove binaries using caffe2 functionality (#125885)
This PR removed some binaries using deleted or to be deleted Caffe2 functions. Pull Request resolved: https://github.com/pytorch/pytorch/pull/125885 Approved by: https://github.com/r-barnes, https://github.com/Chillee
This commit is contained in:
cyy
PyTorch MergeBot
@ -37,24 +37,12 @@ endif()
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if(USE_CUDA)
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if(USE_CUDA)
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caffe2_binary_target("inspect_gpu.cc")
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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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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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endif()
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if(USE_ROCM)
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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/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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endif()
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if(USE_MPI)
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if(USE_MPI)
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@ -1,222 +0,0 @@
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/**
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* Copyright (c) 2016-present, Facebook, Inc.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "benchmark/benchmark.h"
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#include "caffe2/core/context.h"
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#include "caffe2/core/context_gpu.h"
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#include "caffe2/core/operator.h"
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#define CAFFE2_SKIP_IF_NO_GPU \
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if (!caffe2::NumCudaDevices()) { \
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state.SkipWithError("No CUDA available, skipping benchmark."); \
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return; \
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}
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using namespace caffe2;
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static void BM_CUDAContextCreation(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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volatile CUDAContext context_so_we_do_initialization_work;
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while (state.KeepRunning()) {
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volatile CUDAContext context;
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}
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}
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BENCHMARK(BM_CUDAContextCreation);
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static void BM_CUDAContextStreamAccess(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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CUDAContext context;
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while (state.KeepRunning()) {
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volatile cudaStream_t stream = context.cuda_stream();
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}
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}
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BENCHMARK(BM_CUDAContextStreamAccess);
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static void BM_cudaGetDevice(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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int id;
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while (state.KeepRunning()) {
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CUDA_ENFORCE(cudaGetDevice(&id));
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}
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}
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BENCHMARK(BM_cudaGetDevice);
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static void BM_cudaSetDevice(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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int total = NumCudaDevices();
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int i = 0;
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while (state.KeepRunning()) {
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CUDA_ENFORCE(cudaSetDevice((i++) % total));
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}
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}
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BENCHMARK(BM_cudaSetDevice);
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static void BM_cudaSetAndGetDevice(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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int total = NumCudaDevices();
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int i = 0;
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int id;
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while (state.KeepRunning()) {
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CUDA_ENFORCE(cudaSetDevice((i++) % total));
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CUDA_ENFORCE(cudaGetDevice(&id));
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}
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}
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BENCHMARK(BM_cudaSetAndGetDevice);
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static void BM_cudaSetSameDevice(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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while (state.KeepRunning()) {
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CUDA_ENFORCE(cudaSetDevice(0));
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}
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}
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BENCHMARK(BM_cudaSetSameDevice);
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static void BM_cudaStreamCreateSyncDelete(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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cudaStream_t stream;
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while (state.KeepRunning()) {
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CUDA_ENFORCE(cudaStreamCreate(&stream));
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CUDA_ENFORCE(cudaStreamSynchronize(stream));
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CUDA_ENFORCE(cudaStreamDestroy(stream));
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}
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}
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BENCHMARK(BM_cudaStreamCreateSyncDelete);
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static void BM_cudaStreamSynchronize(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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cudaStream_t stream;
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CUDA_ENFORCE(cudaStreamCreate(&stream));
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while (state.KeepRunning()) {
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CUDA_ENFORCE(cudaStreamSynchronize(stream));
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}
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}
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BENCHMARK(BM_cudaStreamSynchronize);
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static void BM_cudaEventRecord(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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cudaStream_t stream;
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cudaEvent_t event;
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CUDA_ENFORCE(cudaStreamCreate(&stream));
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CUDA_ENFORCE(cudaEventCreateWithFlags(
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&event, cudaEventDefault | cudaEventDisableTiming));
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while (state.KeepRunning()) {
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CUDA_ENFORCE(cudaEventRecord(event, stream));
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}
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}
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BENCHMARK(BM_cudaEventRecord);
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static void BM_cudaStreamWaitEventThenStreamSynchronize(
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benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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cudaStream_t stream;
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cudaEvent_t event;
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CUDA_ENFORCE(cudaStreamCreate(&stream));
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CUDA_ENFORCE(cudaEventCreateWithFlags(
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&event, cudaEventDefault | cudaEventDisableTiming));
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CUDA_ENFORCE(cudaEventRecord(event, stream));
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CUDA_ENFORCE(cudaStreamWaitEvent(stream, event, 0));
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CUDA_ENFORCE(cudaStreamSynchronize(stream));
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while (state.KeepRunning()) {
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CUDA_ENFORCE(cudaStreamWaitEvent(stream, event, 0));
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CUDA_ENFORCE(cudaStreamSynchronize(stream));
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}
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}
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BENCHMARK(BM_cudaStreamWaitEventThenStreamSynchronize);
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static void BM_CudaPointerAffinity(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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Tensor tensor(vector<int64_t>{1, 2, 3, 4}, CUDA);
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float* ptr = tensor.mutable_data<float>();
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while (state.KeepRunning()) {
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volatile int id = GetGPUIDForPointer(ptr);
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}
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}
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BENCHMARK(BM_CudaPointerAffinity);
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namespace {
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template <class Context>
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class DummyEmptyOp : public Operator<Context> {
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public:
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DummyEmptyOp(const OperatorDef& def, Workspace* ws)
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: Operator<Context>(def, ws) {}
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bool RunOnDevice() final { return true; }
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};
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REGISTER_CPU_OPERATOR(DummyEmpty, DummyEmptyOp<CPUContext>);
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REGISTER_CUDA_OPERATOR(DummyEmpty, DummyEmptyOp<CUDAContext>);
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OPERATOR_SCHEMA(DummyEmpty);
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} // namespace
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static void BM_OperatorCreationCPU(benchmark::State& state) {
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std::unique_ptr<OperatorBase> op;
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OperatorDef def;
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Workspace ws;
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def.set_type("DummyEmpty");
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def.mutable_device_option()->set_device_type(PROTO_CPU);
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while (state.KeepRunning()) {
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op = CreateOperator(def, &ws);
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}
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}
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BENCHMARK(BM_OperatorCreationCPU);
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static void BM_OperatorCreationCUDA(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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std::unique_ptr<OperatorBase> op;
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OperatorDef def;
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Workspace ws;
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def.set_type("DummyEmpty");
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def.mutable_device_option()->set_device_type(PROTO_CUDA);
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while (state.KeepRunning()) {
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op = CreateOperator(def, &ws);
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}
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}
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BENCHMARK(BM_OperatorCreationCUDA);
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static void BM_RawAllocDeallocCPU(benchmark::State& state) {
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while (state.KeepRunning()) {
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// Allocating only 1 byte in order to measure the overhead.
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auto data_ptr = GetCPUAllocator()->allocate(1);
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// Deallocated when it's out of scope
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}
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}
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BENCHMARK(BM_RawAllocDeallocCPU);
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static void BM_TensorAllocDeallocCPU(benchmark::State& state) {
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Tensor tensor(CPU);
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// small allocation
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tensor.Resize(32, 32);
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while (state.KeepRunning()) {
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CHECK(tensor.mutable_data<float>());
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tensor.FreeMemory();
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}
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}
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BENCHMARK(BM_TensorAllocDeallocCPU);
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static void BM_TensorAllocDeallocCUDA(benchmark::State& state) {
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CAFFE2_SKIP_IF_NO_GPU;
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Tensor tensor(CUDA);
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// small allocation
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tensor.Resize(32, 32);
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while (state.KeepRunning()) {
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CHECK(tensor.mutable_data<float>());
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tensor.FreeMemory();
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}
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}
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BENCHMARK(BM_TensorAllocDeallocCUDA);
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BENCHMARK_MAIN();
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@ -1,40 +0,0 @@
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/**
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* Copyright (c) 2016-present, Facebook, Inc.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <iostream>
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#include "caffe2/core/operator.h"
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#include "caffe2/core/context.h"
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#include "caffe2/core/context_gpu.h"
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#include "caffe2/proto/caffe2_pb.h"
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#define PRINT_SIZE(cls) \
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std::cout << "Size of " #cls ": " << sizeof(cls) << " bytes." \
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<< std::endl;
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int main(int /* unused */, char** /* unused */) {
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PRINT_SIZE(caffe2::Blob);
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PRINT_SIZE(caffe2::Tensor);
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PRINT_SIZE(caffe2::CPUContext);
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PRINT_SIZE(caffe2::CUDAContext);
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PRINT_SIZE(caffe2::OperatorBase);
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PRINT_SIZE(caffe2::OperatorDef);
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PRINT_SIZE(caffe2::Operator<caffe2::CPUContext>);
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PRINT_SIZE(caffe2::Operator<caffe2::CUDAContext>);
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PRINT_SIZE(caffe2::TypeMeta);
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PRINT_SIZE(caffe2::Workspace);
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return 0;
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}
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@ -1,49 +0,0 @@
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/**
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* Copyright (c) 2016-present, Facebook, Inc.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <sstream>
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#include <string>
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#include "caffe2/core/blob_serialization.h"
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#include "caffe2/core/db.h"
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#include "caffe2/core/init.h"
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#include "caffe2/core/logging.h"
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#include "caffe2/proto/caffe2_pb.h"
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#include "caffe2/utils/proto_utils.h"
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C10_DEFINE_string(f_in, "", "The input data file name.");
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C10_DEFINE_string(f_out, "", "The output data file name.");
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int main(int argc, char** argv) {
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caffe2::GlobalInit(&argc, &argv);
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std::ifstream f_in(FLAGS_f_in);
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std::ofstream f_out(FLAGS_f_out);
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std::string line;
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caffe2::TensorProtos tensor_protos;
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while (std::getline(f_in, line)) {
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caffe2::TensorProto* data = tensor_protos.add_protos();
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data->set_data_type(caffe2::TensorProto::STRING);
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data->add_dims(1);
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data->add_string_data(line);
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data->set_name("text");
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}
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f_in.close();
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std::string output_str;
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tensor_protos.SerializeToString(&output_str);
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f_out << output_str;
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f_out.close();
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return 0;
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}
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