forked from jiuyuan/InfiniTensor
59 lines
1.9 KiB
C++
59 lines
1.9 KiB
C++
#include "bang/bang_runtime.h"
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#include "core/graph.h"
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#include "core/kernel.h"
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#include "core/runtime.h"
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#include "operators/matmul.h"
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#include "test.h"
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namespace infini {
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template <class T>
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void testMatmul(const std::function<void(void *, size_t, DataType)> &generatorA,
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const std::function<void(void *, size_t, DataType)> &generatorB,
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bool transA, bool transB, const Shape &shapeA,
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const Shape &shapeB) {
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// Runtime
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Runtime cpuRuntime = NativeCpuRuntimeObj::getInstance();
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auto bangRuntime = make_ref<BangRuntimeObj>();
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// Build input data on CPU
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Tensor inputCpu1 =
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make_ref<TensorObj>(shapeA, DataType::Float32, cpuRuntime);
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Tensor inputCpu2 =
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make_ref<TensorObj>(shapeB, DataType::Float32, cpuRuntime);
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// MLU
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Graph bangGraph = make_ref<GraphObj>(bangRuntime);
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auto inputMlu1 = bangGraph->cloneTensor(inputCpu1);
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auto inputMlu2 = bangGraph->cloneTensor(inputCpu2);
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auto mluOp = bangGraph->addOp<T>(inputMlu1, inputMlu2, nullptr);
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bangGraph->dataMalloc();
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inputMlu1->setData(generatorA);
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inputMlu2->setData(generatorB);
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bangRuntime->run(bangGraph);
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auto outputMlu = mluOp->getOutput();
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auto outputMlu2Cpu = outputMlu->clone(cpuRuntime);
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// CPU
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Graph cpuGraph = make_ref<GraphObj>(cpuRuntime);
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auto cpuOp = cpuGraph->addOp<T>(inputCpu1, inputCpu2, nullptr);
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cpuGraph->addTensor(inputCpu1);
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cpuGraph->addTensor(inputCpu2);
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cpuGraph->dataMalloc();
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inputCpu1->setData(generatorA);
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inputCpu2->setData(generatorB);
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cpuRuntime->run(cpuGraph);
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auto outputCpu = cpuOp->getOutput();
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outputCpu->print();
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outputMlu2Cpu->print();
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// Check
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EXPECT_TRUE(outputCpu->equalData(outputMlu2Cpu));
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}
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TEST(cnnl_Matmul, run) {
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testMatmul<MatmulObj>(IncrementalGenerator(), IncrementalGenerator(), false,
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false, Shape{1, 2, 3}, Shape{1, 3, 4});
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}
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} // namespace infini
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