mirror of https://github.com/alibaba/MNN.git
110 lines
4.7 KiB
C++
110 lines
4.7 KiB
C++
//
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// GatherTest.cpp
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// MNNTests
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//
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// Created by MNN on 2019/01/15.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include <MNN/expr/Expr.hpp>
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#include <MNN/expr/ExprCreator.hpp>
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#include "MNNTestSuite.h"
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#include "TestUtils.h"
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using namespace MNN::Express;
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class GatherNDTest : public MNNTestCase {
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public:
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virtual ~GatherNDTest() = default;
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bool _run(int precision, bool lazy) {
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{
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const float inpudata[] = {-1.0, -2.0, 3.0, 4.0};
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const int indices_data[] = {0, 0, 1, 1};
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auto params = _Const(inpudata, {2, 2}, NCHW, halide_type_of<float>());
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auto indices = _Const(indices_data, {2, 2}, NCHW, halide_type_of<int>());
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auto output = _GatherND(params, indices);
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const std::vector<float> expectedOutput = {-1.0, 4.0};
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auto gotOutput = output->readMap<float>();
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if (!checkVectorByRelativeError<float>(gotOutput, expectedOutput.data(), 2, 0.001)) {
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MNN_ERROR("GatherNDTest test failed!\n");
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return false;
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}
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}
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{
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const float inpudata[] = {1, 2, 3, 4, 5, 6, 7, 8};
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const int indices_data[] = {0, 0, 1, 1, 1, 0};
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auto params = _Const(inpudata, {2, 2, 2}, NCHW, halide_type_of<float>());
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auto indices = _Const(indices_data, {2, 3}, NCHW, halide_type_of<int>());
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auto output = _GatherND(params, indices);
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const std::vector<float> expectedOutput = {2, 7};
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auto gotOutput = output->readMap<float>();
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if (!checkVectorByRelativeError<float>(gotOutput, expectedOutput.data(), 2, 0.001)) {
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MNN_ERROR("GatherNDTest test failed!\n");
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return false;
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}
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}
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return true;
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}
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virtual bool run(int precision) {
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ExecutorScope::Current()->lazyEval = false;
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auto res = _run(precision, false);
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if (!res) {
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FUNC_PRINT(1);
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return false;
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}
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ExecutorScope::Current()->lazyEval = true;
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ExecutorScope::Current()->setLazyComputeMode(MNN::Express::Executor::LAZY_CONTENT);
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res = _run(precision, true);
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if (!res) {
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FUNC_PRINT(1);
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return false;
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}
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ExecutorScope::Current()->setLazyComputeMode(MNN::Express::Executor::LAZY_FULL);
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res = _run(precision, true);
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return res;
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}
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};
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class GatherTest : public MNNTestCase {
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public:
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virtual ~GatherTest() = default;
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bool _run(int precision, bool lazy) {
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auto params = _Input({4, 3, 2}, NCHW);
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params->setName("input_tensor");
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// set input data
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const float inpudata[] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0,
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14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21, 0, 22.0, 23.0, 24.0};
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auto inputPtr = params->writeMap<float>();
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memcpy(inputPtr, inpudata, 24 * sizeof(float));
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params->unMap();
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const int indices_data[] = {1, 0, 1, 0};
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auto indices = _Const(indices_data, {4}, NCHW, halide_type_of<int>());
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auto output = _Gather(params, indices);
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const std::vector<float> expectedOutput = {7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0,
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7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0};
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auto gotOutput = output->readMap<float>();
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if (!checkVector<float>(gotOutput, expectedOutput.data(), 24, 0.001)) {
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MNN_ERROR("GatherTest test failed!\n");
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return false;
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}
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return true;
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}
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virtual bool run(int precision) {
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ExecutorScope::Current()->lazyEval = false;
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auto res = _run(precision, false);
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if (!res) {
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FUNC_PRINT(1);
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return false;
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}
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ExecutorScope::Current()->lazyEval = true;
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ExecutorScope::Current()->setLazyComputeMode(MNN::Express::Executor::LAZY_CONTENT);
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res = _run(precision, true);
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if (!res) {
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FUNC_PRINT(1);
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return false;
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}
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ExecutorScope::Current()->setLazyComputeMode(MNN::Express::Executor::LAZY_FULL);
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res = _run(precision, true);
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return res;
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}
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};
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MNNTestSuiteRegister(GatherNDTest, "op/gather_nd");
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MNNTestSuiteRegister(GatherTest, "op/gather");
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