forked from jiuyuan/InfiniTensor
48 lines
1.5 KiB
C++
48 lines
1.5 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/element_wise.h"
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#include "operators/unary.h"
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#include "test.h"
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namespace infini {
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void testNet(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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inputCpu1->dataMalloc();
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inputCpu1->setData(generator);
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Tensor inputCpu2 =
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make_ref<TensorObj>(shape, DataType::Float32, cpuRuntime);
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inputCpu2->dataMalloc();
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inputCpu2->setData(generator);
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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<AddObj>(inputGpu1, inputGpu2, nullptr);
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auto outputGpu = gpuOp->getOutput();
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auto gpuOp2 = bangGraph->addOp<SigmoidObj>(outputGpu, nullptr);
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bangGraph->dataMalloc();
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bangRuntime->run(bangGraph);
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auto outputGpu2 = gpuOp2->getOutput();
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auto outputGpu2Cpu2 = outputGpu2->clone(cpuRuntime);
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// Check
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inputCpu2->printData();
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outputGpu2Cpu2->printData();
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EXPECT_TRUE(1);
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}
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TEST(cnnl_Net, run) { testNet(IncrementalGenerator(), Shape{1, 2, 2, 3}); }
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} // namespace infini
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