tensor-tang
6 years ago
parent
d538513fce
commit
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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// #include <cstring> // for memcpy
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// #include <random>
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#include <iostream>
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#include <string>
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#include <vector>
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#include "gflags/gflags.h"
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#include "glog/logging.h"
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#include "paddle/fluid/operators/jit/kernels.h"
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#include "paddle/fluid/platform/place.h"
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#include "paddle/fluid/platform/port.h"
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DEFINE_int32(burning, 10, "Burning times.");
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DEFINE_int32(repeat, 3000, "Repeat times.");
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DEFINE_int32(max_size, 1000, "The Max size would be tested.");
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inline double GetCurrentUS() {
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struct timeval time;
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gettimeofday(&time, NULL);
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return 1e+6 * time.tv_sec + time.tv_usec;
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}
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template <typename T>
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void RandomVec(const int n, T* a, const T lower = static_cast<T>(-20.f),
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const T upper = static_cast<T>(20.f)) {
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static unsigned int seed = 100;
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std::mt19937 rng(seed++);
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std::uniform_real_distribution<double> uniform_dist(0, 1);
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for (int i = 0; i < n; ++i) {
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a[i] = static_cast<T>(uniform_dist(rng) * (upper - lower) + lower);
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}
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}
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std::vector<int> TestSizes() {
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std::vector<int> s;
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for (int i = 1; i <= FLAGS_max_size; ++i) {
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s.push_back(i);
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}
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return s;
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}
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// return this function avg time
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template <typename T, typename Func>
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double BenchTartgetFunc(const Func tgt, const std::vector<T>& x,
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const std::vector<T>& y, std::vector<T>& z) { // NOLINT
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const T* x_data = x.data();
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const T* y_data = y.data();
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const int d = z.size();
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T* z_data = z.data();
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for (int i = 0; i < FLAGS_burning; ++i) {
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tgt(x_data, y_data, z_data, d);
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}
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auto start = GetCurrentUS();
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for (int i = 0; i < FLAGS_repeat; ++i) {
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tgt(x_data, y_data, z_data, d);
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}
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auto end = GetCurrentUS();
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return (end - start) / FLAGS_repeat;
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}
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// Benchmark all jit kernels including jitcode, mkl and refer.
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// To use this tool, run command: ./benchmark [options...]
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// Options:
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// --burning: the burning time before count
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// --repeat: the repeat times
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// --max_size: the max size would be tested
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int main(int argc, char* argv[]) {
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gflags::ParseCommandLineFlags(&argc, &argv, true);
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google::InitGoogleLogging(argv[0]);
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using T = float;
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using PlaceType = paddle::platform::CPUPlace;
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namespace jit = paddle::operators::jit;
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const auto KT = jit::vmul;
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LOG(INFO) << "Burning " << FLAGS_burning << " times, Repeat " << FLAGS_repeat
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<< " times.";
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for (int d : TestSizes()) {
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// for (kernels type) { // TODO(TJ): more jit::KernelType
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std::vector<std::pair<std::string, double>> infos;
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std::vector<T> x(d), y(d), z(d);
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RandomVec<T>(d, x.data());
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RandomVec<T>(d, y.data());
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// refer
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auto refer = jit::GetRefer<KT, T, jit::VMulTuples<T>::func_type,
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jit::VMulTuples<T>::attr_type>();
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if (refer) {
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auto res =
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BenchTartgetFunc<T, jit::VMulTuples<T>::func_type>(refer, x, y, z);
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infos.push_back(std::make_pair("Refer", res));
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}
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// test jitcode
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auto jitcode = jit::GetJitCode<KT, T, jit::VMulTuples<T>::func_type,
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jit::VMulTuples<T>::attr_type, PlaceType>(d);
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if (jitcode) {
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auto res =
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BenchTartgetFunc<T, jit::VMulTuples<T>::func_type>(jitcode, x, y, z);
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infos.push_back(std::make_pair("JitCode", res));
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}
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// test all impls in more
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jit::KernelKey kkey(KT, PlaceType());
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auto& pool = jit::KernelPool().Instance().AllKernels();
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auto iter = pool.find(kkey);
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if (iter != pool.end()) {
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auto& impls = iter->second;
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for (auto& impl : impls) {
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auto i =
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dynamic_cast<const jit::KernelImpl<T, jit::VMulTuples<T>::func_type,
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jit::VMulTuples<T>::attr_type>*>(
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impl.get());
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if (i && i->UseMe(d)) {
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auto more = i->GetFunc();
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auto res =
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BenchTartgetFunc<T, jit::VMulTuples<T>::func_type>(more, x, y, z);
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infos.push_back(std::make_pair("More", res));
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}
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}
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}
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// Test result from Get function
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auto tgt = jit::Get<KT, T, jit::VMulTuples<T>::func_type,
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jit::VMulTuples<T>::attr_type, PlaceType>(d);
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if (!tgt) {
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LOG(ERROR) << "Target can not be empty!";
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}
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auto res = BenchTartgetFunc<T, jit::VMulTuples<T>::func_type>(tgt, x, y, z);
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infos.push_back(std::make_pair("Target", res));
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// print
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std::ostringstream loginfos;
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loginfos << "Kernel Type: " << KT << ", size " << d << ": ";
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for (auto pair : infos) {
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loginfos << pair.first << " takes " << pair.second << " us; ";
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}
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LOG(INFO) << loginfos.str();
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// }
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}
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}
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