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#define EIGEN_USE_THREADS
#include "base/sysinfo.h"
#include "strings/strcat.h"
#include "third_party/eigen3/tensor_benchmarks.h"
#include "thread/threadpool.h"
#ifdef __ANDROID__
#define CREATE_THREAD_POOL(threads) \
Eigen::ThreadPoolDevice device(threads);
#else
#define CREATE_THREAD_POOL(threads) \
ThreadPool tp(threads); \
tp.StartWorkers(); \
Eigen::ThreadPoolDevice device(&tp, threads);
#endif
// Simple functions
#define BM_FuncCPU(FUNC, THREADS) \
static void BM_##FUNC##_##THREADS##T(int iters, int N) { \
StopBenchmarkTiming(); \
CREATE_THREAD_POOL(THREADS); \
BenchmarkSuite<Eigen::ThreadPoolDevice> suite(device, N); \
suite.FUNC(iters); \
SetBenchmarkLabel(StrCat("using ", THREADS, " threads")); \
} \
BENCHMARK_RANGE(BM_##FUNC##_##THREADS##T, 10, 5000);
BM_FuncCPU(memcpy, 4);
BM_FuncCPU(memcpy, 8);
BM_FuncCPU(memcpy, 12);
BM_FuncCPU(random, 4);
BM_FuncCPU(random, 8);
BM_FuncCPU(random, 12);
BM_FuncCPU(slicing, 4);
BM_FuncCPU(slicing, 8);
BM_FuncCPU(slicing, 12);
BM_FuncCPU(shuffling, 4);
BM_FuncCPU(shuffling, 8);
BM_FuncCPU(shuffling, 12);
BM_FuncCPU(padding, 4);
BM_FuncCPU(padding, 8);
BM_FuncCPU(padding, 12);
BM_FuncCPU(striding, 4);
BM_FuncCPU(striding, 8);
BM_FuncCPU(striding, 12);
BM_FuncCPU(broadcasting, 4);
BM_FuncCPU(broadcasting, 8);
BM_FuncCPU(broadcasting, 12);
BM_FuncCPU(coeffWiseOp, 4);
BM_FuncCPU(coeffWiseOp, 8);
BM_FuncCPU(coeffWiseOp, 12);
BM_FuncCPU(algebraicFunc, 4);
BM_FuncCPU(algebraicFunc, 8);
BM_FuncCPU(algebraicFunc, 12);
BM_FuncCPU(transcendentalFunc, 4);
BM_FuncCPU(transcendentalFunc, 8);
BM_FuncCPU(transcendentalFunc, 12);
BM_FuncCPU(reduction, 4);
BM_FuncCPU(reduction, 8);
BM_FuncCPU(reduction, 12);
// Contractions
#define BM_FuncWithInputDimsCPU(FUNC, D1, D2, D3, THREADS) \
static void BM_##FUNC##_##D1##x##D2##x##D3##_##THREADS##T(int iters, int N) {\
StopBenchmarkTiming(); \
if (THREADS == 1) { \
Eigen::DefaultDevice device; \
BenchmarkSuite<Eigen::DefaultDevice> suite(device, D1, D2, D3); \
suite.FUNC(iters); \
} else { \
CREATE_THREAD_POOL(THREADS); \
BenchmarkSuite<Eigen::ThreadPoolDevice> suite(device, D1, D2, D3); \
suite.FUNC(iters); \
} \
SetBenchmarkLabel(StrCat("using ", THREADS, " threads")); \
} \
BENCHMARK_RANGE(BM_##FUNC##_##D1##x##D2##x##D3##_##THREADS##T, 10, 5000);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 1);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 4);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 8);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 12);
BM_FuncWithInputDimsCPU(contraction, N, N, N, 16);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 1);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 4);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 8);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 12);
BM_FuncWithInputDimsCPU(contraction, 64, N, N, 16);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 1);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 4);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 8);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 12);
BM_FuncWithInputDimsCPU(contraction, N, 64, N, 16);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 1);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 4);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 8);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 12);
BM_FuncWithInputDimsCPU(contraction, 1, N, N, 16);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 1);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 4);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 8);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 12);
BM_FuncWithInputDimsCPU(contraction, N, N, 1, 16);
// Convolutions
#define BM_FuncWithKernelDimsCPU(FUNC, DIM1, DIM2, THREADS) \
static void BM_##FUNC##_##DIM1##x##DIM2##_##THREADS##T(int iters, int N) { \
StopBenchmarkTiming(); \
CREATE_THREAD_POOL(THREADS); \
BenchmarkSuite<Eigen::ThreadPoolDevice> suite(device, N); \
suite.FUNC(iters, DIM1, DIM2); \
SetBenchmarkLabel(StrCat("using ", THREADS, " threads")); \
} \
BENCHMARK_RANGE(BM_##FUNC##_##DIM1##x##DIM2##_##THREADS##T, 128, 5000);
BM_FuncWithKernelDimsCPU(convolution, 7, 1, 4);
BM_FuncWithKernelDimsCPU(convolution, 7, 1, 8);
BM_FuncWithKernelDimsCPU(convolution, 7, 1, 12);
BM_FuncWithKernelDimsCPU(convolution, 1, 7, 4);
BM_FuncWithKernelDimsCPU(convolution, 1, 7, 8);
BM_FuncWithKernelDimsCPU(convolution, 1, 7, 12);
BM_FuncWithKernelDimsCPU(convolution, 7, 4, 4);
BM_FuncWithKernelDimsCPU(convolution, 7, 4, 8);
BM_FuncWithKernelDimsCPU(convolution, 7, 4, 12);
BM_FuncWithKernelDimsCPU(convolution, 4, 7, 4);
BM_FuncWithKernelDimsCPU(convolution, 4, 7, 8);
BM_FuncWithKernelDimsCPU(convolution, 4, 7, 12);
BM_FuncWithKernelDimsCPU(convolution, 7, 64, 4);
BM_FuncWithKernelDimsCPU(convolution, 7, 64, 8);
BM_FuncWithKernelDimsCPU(convolution, 7, 64, 12);
BM_FuncWithKernelDimsCPU(convolution, 64, 7, 4);
BM_FuncWithKernelDimsCPU(convolution, 64, 7, 8);
BM_FuncWithKernelDimsCPU(convolution, 64, 7, 12);
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