InfiniTensor/test/kernels/kunlun/test_kunlun_pooling.cc

52 lines
1.6 KiB
C++

#include "core/graph.h"
#include "core/kernel.h"
#include "core/runtime.h"
#include "kunlun/kunlun_runtime.h"
#include "operators/pooling.h"
#include "test.h"
namespace infini {
template <class T>
void testPooling(const std::function<void(void *, size_t, DataType)> &generator,
const Shape &shape) {
// Runtime
Runtime cpuRuntime = NativeCpuRuntimeObj::getInstance();
auto xpuRuntime = make_ref<KUNLUNRuntimeObj>();
// Build input data on CPU
Tensor inputCpu = make_ref<TensorObj>(shape, DataType::Float32, cpuRuntime);
inputCpu->dataMalloc();
inputCpu->setData(generator);
// GPU
Graph xpuGraph = make_ref<GraphObj>(xpuRuntime);
auto inputGpu = xpuGraph->cloneTensor(inputCpu);
auto gpuOp =
xpuGraph->addOp<T>(inputGpu, nullptr, 3, 3, 1, 1, 0, 0, 2, 2, 0);
xpuGraph->dataMalloc();
inputGpu->setData(generator);
xpuRuntime->run(xpuGraph);
auto outputGpu = gpuOp->getOutput();
auto outputGpu2Cpu = outputGpu->clone(cpuRuntime);
// CPU
Graph cpuGraph = make_ref<GraphObj>(cpuRuntime);
cpuGraph->addTensor(inputCpu);
auto cpuOp =
cpuGraph->addOp<T>(inputCpu, nullptr, 3, 3, 1, 1, 0, 0, 2, 2, 0);
cpuGraph->dataMalloc();
inputCpu->setData(generator);
cpuRuntime->run(cpuGraph);
auto outputCpu = cpuOp->getOutput();
EXPECT_TRUE(outputCpu->equalData(outputGpu2Cpu));
}
TEST(xdnn_Pooling, run) {
testPooling<MaxPoolObj>(IncrementalGenerator(), Shape{1, 1, 5, 5});
testPooling<AvgPoolObj>(IncrementalGenerator(), Shape{1, 1, 5, 5});
}
} // namespace infini