forked from jiuyuan/InfiniTensor
85 lines
3.1 KiB
C++
85 lines
3.1 KiB
C++
#include "core/graph.h"
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#include "core/kernel.h"
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#include "core/perf_engine.h"
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#include "intelcpu/mkl_runtime.h"
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#include "operators/conv.h"
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#include "test.h"
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namespace infini {
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void testConvTransposedMkl(
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const std::function<void(void *, size_t, DataType)> &generator,
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vector<float> ansVec) {
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const auto &[N, C, H, W, F, R, S] = tuple{1, 1, 2, 2, 1, 4, 4};
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const int stride = 1, padding = 0, dilation = 1;
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Runtime runtime = MklRuntimeObj::getInstance();
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Graph gMkl = make_ref<GraphObj>(runtime);
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// Set input data on CPU in a CPU Graph
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Tensor i0 = gMkl->addTensor({N, F, H, H}, DataType::Float32);
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Tensor w0 = gMkl->addTensor({F, C, R, S}, DataType::Float32);
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auto conv = gMkl->addOp<ConvTransposed2dObj>(
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i0, w0, nullptr, padding, padding, stride, stride, dilation, dilation);
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gMkl->dataMalloc();
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i0->setData(generator);
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w0->setData(generator);
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runtime->run(gMkl);
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EXPECT_TRUE(conv->getOutput()->equalData(ansVec));
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}
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TEST(mkl_ConvTransposed, run) {
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testConvTransposedMkl(IncrementalGenerator(),
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vector<float>{0., 0., 1., 2., 3., 0., 6.,
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12., 18., 16., 8., 30., 36., 42.,
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32., 16., 54., 60., 66., 48., 24.,
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62., 67., 72., 45.});
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}
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TEST(mkl_ConvTransposed, run1) {
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Runtime runtime = MklRuntimeObj::getInstance();
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Graph gMkl = make_ref<GraphObj>(runtime);
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// Set input data on CPU in a CPU Graph
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Tensor i0 = gMkl->addTensor({1, 2, 3, 3}, DataType::Float32);
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Tensor w0 = gMkl->addTensor({2, 2, 3, 3}, DataType::Float32);
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auto conv = gMkl->addOp<ConvTransposed2dObj>(i0, w0, nullptr, 0, 0);
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gMkl->dataMalloc();
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i0->setData(IncrementalGenerator());
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w0->setData(IncrementalGenerator());
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runtime->run(gMkl);
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EXPECT_TRUE(conv->getOutput()->equalData(vector<float>{
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162, 351, 569, 413, 224, 405, 876, 1417, 1024, 553,
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747, 1611, 2598, 1869, 1005, 639, 1368, 2191, 1564, 835,
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396, 843, 1343, 953, 506, 243, 531, 866, 629, 341,
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621, 1344, 2173, 1564, 841, 1152, 2475, 3975, 2841, 1518,
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963, 2052, 3271, 2320, 1231, 585, 1239, 1964, 1385, 731}));
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}
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TEST(mkl_ConvTransposed, tune) {
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Runtime runtime = MklRuntimeObj::getInstance();
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Graph gMkl = make_ref<GraphObj>(runtime);
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Tensor i0 = gMkl->addTensor({1, 448, 2, 2}, DataType::Float32);
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Tensor w0 = gMkl->addTensor({448, 256, 4, 4}, DataType::Float32);
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auto conv = gMkl->addOp<ConvTransposed2dObj>(i0, w0, nullptr);
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gMkl->dataMalloc();
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i0->setData(IncrementalGenerator());
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w0->setData(IncrementalGenerator());
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bool tune = true;
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runtime->run(gMkl, tune);
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// check record
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auto kernelAttrs = KernelAttrs{
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Device::INTELCPU, conv->getOpType().underlying(), DataType::Float32};
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auto perfKey = PerfEngine::Key{kernelAttrs, conv->getOpPerfKey()};
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std::optional<PerfRecord> perfData =
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PerfEngine::getInstance().getPerfData(perfKey);
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ASSERT_TRUE(perfData.has_value());
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}
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} // namespace infini
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