forked from jiuyuan/InfiniTensor
66 lines
2.0 KiB
C++
66 lines
2.0 KiB
C++
#include "bang/bang_runtime.h"
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#include "core/blob.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/element_wise.h"
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#include "utils/validation.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 testBangcKernel(
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const std::function<void(void *, size_t, DataType)> &generator,
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const Shape &shape) {
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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>(shape, DataType::Float32, cpuRuntime);
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Tensor inputCpu2 =
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make_ref<TensorObj>(shape, DataType::Float32, cpuRuntime);
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// inputCpu1->printData();
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// inputCpu2->printData();
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// GPU
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Graph bangGraph = make_ref<GraphObj>(bangRuntime);
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auto inputGpu1 = bangGraph->cloneTensor(inputCpu1);
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auto inputGpu2 = bangGraph->cloneTensor(inputCpu2);
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auto gpuOp = bangGraph->addOp<T>(inputGpu1, inputGpu2, nullptr);
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bangGraph->dataMalloc();
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inputGpu1->setData(generator);
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inputGpu2->setData(generator);
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bangRuntime->run(bangGraph);
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auto outputGpu = gpuOp->getOutput();
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auto outputGpu2Cpu = outputGpu->clone(cpuRuntime);
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// outputGpu2Cpu->printData();
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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(generator);
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inputCpu2->setData(generator);
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cpuRuntime->run(cpuGraph);
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auto outputCpu = cpuOp->getOutput();
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// outputCpu->printData();
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// Check
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float *const cpuRes =
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(float *)(outputCpu->template getRawDataPtr<float *>());
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float *const mluRes =
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(float *)(outputGpu2Cpu->template getRawDataPtr<float *>());
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EXPECT_LE(computeDifference2(cpuRes, mluRes, outputCpu->size()), 0.003);
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}
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TEST(BangcKernel_Div, run) {
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testBangcKernel<DivObj>(IncrementalGenerator(), Shape{1, 2, 2, 3});
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}
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} // namespace infini
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