2019-04-17 10:49:11 +08:00
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//
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// RankTest.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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2020-11-05 16:41:56 +08:00
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2019-12-27 22:16:57 +08:00
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#include <MNN/expr/Expr.hpp>
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#include <MNN/expr/ExprCreator.hpp>
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2019-04-17 10:49:11 +08:00
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#include "MNNTestSuite.h"
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#include "TestUtils.h"
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2019-12-27 22:16:57 +08:00
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using namespace MNN::Express;
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2019-04-17 10:49:11 +08:00
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class RankTest : public MNNTestCase {
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public:
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virtual ~RankTest() = default;
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2021-06-11 17:17:13 +08:00
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virtual bool run(int precision) {
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2020-11-05 16:41:56 +08:00
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auto input = _Input({2, 2}, NCHW);
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2019-12-27 22:16:57 +08:00
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input->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};
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auto inputPtr = input->writeMap<float>();
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memcpy(inputPtr, inpudata, 4 * sizeof(float));
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input->unMap();
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2020-11-05 16:41:56 +08:00
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auto output = _Rank(input);
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2019-12-27 22:16:57 +08:00
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const std::vector<int> expectedOutput = {2};
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2020-11-05 16:41:56 +08:00
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auto gotOutput = output->readMap<int>();
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2019-12-27 22:16:57 +08:00
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if (!checkVector<int>(gotOutput, expectedOutput.data(), 1, 0)) {
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MNN_ERROR("RankTest test failed!\n");
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return false;
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}
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auto dims = output->getInfo()->dim;
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2020-11-05 16:41:56 +08:00
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if (dims.size() != 0) {
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2019-12-27 22:16:57 +08:00
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MNN_ERROR("RankTest test failed!\n");
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return false;
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2019-04-17 10:49:11 +08:00
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}
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2019-05-24 11:26:54 +08:00
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return true;
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2019-04-17 10:49:11 +08:00
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}
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};
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MNNTestSuiteRegister(RankTest, "op/rank");
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