/* * Copyright (c) 2022 Huawei Device Co., Ltd. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #include "ops/tanh_builder.h" #include #include "nn_tensor.h" #include "ops_test.h" using namespace testing; using namespace testing::ext; using namespace OHOS::NeuralNetworkRuntime::Ops; namespace OHOS { namespace NeuralNetworkRuntime { namespace UnitTest { class TanhBuilderTest : public OpsTest { protected: void InitTensor(const std::vector& inputsIndex, const std::vector& outputsIndex) override; protected: TanhBuilder m_builder; }; void TanhBuilderTest::InitTensor(const std::vector& inputsIndex, const std::vector& outputsIndex) { std::vector inputDim = {1, 5, 1, 1}; std::vector OutputDim = {1, 5, 1, 1}; SaveInputTensor(inputsIndex, OH_NN_FLOAT32, inputDim, nullptr); SaveOutputTensor(outputsIndex, OH_NN_FLOAT32, OutputDim, nullptr); } /** * @tc.name: tanh_build_001 * @tc.desc: Provide normal input, output to verify the normal behavior of the Build function * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_build_001, TestSize.Level0) { std::vector inputsIndex = { 0 }; std::vector outputsIndex = { 1 }; InitTensor(inputsIndex, outputsIndex); OH_NN_ReturnCode ret = m_builder.Build(m_paramsIndex, m_inputsIndex, m_outputsIndex, m_allTensors); EXPECT_EQ(OH_NN_SUCCESS, ret); } /** * @tc.name: tanh_build_002 * @tc.desc: Call Build func twice to verify the abnormal behavior of the Build function * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_build_002, TestSize.Level0) { std::vector inputsIndex = { 0 }; std::vector outputsIndex = { 1 }; InitTensor(inputsIndex, outputsIndex); EXPECT_EQ(OH_NN_SUCCESS, m_builder.Build(m_paramsIndex, m_inputsIndex, m_outputsIndex, m_allTensors)); OH_NN_ReturnCode ret = m_builder.Build(m_paramsIndex, m_inputsIndex, m_outputsIndex, m_allTensors); EXPECT_EQ(OH_NN_OPERATION_FORBIDDEN, ret); } /** * @tc.name: tanh_build_003 * @tc.desc: Provide one more than normal input to verify the abnormal behavior of the Build function * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_build_003, TestSize.Level0) { std::vector inputsIndex = { 0, 1 }; std::vector outputsIndex = { 2 }; InitTensor(inputsIndex, outputsIndex); OH_NN_ReturnCode ret = m_builder.Build(m_paramsIndex, m_inputsIndex, m_outputsIndex, m_allTensors); EXPECT_EQ(OH_NN_INVALID_PARAMETER, ret); } /** * @tc.name: tanh_build_004 * @tc.desc: Provide one more than normal output to verify the abnormal behavior of the Build function * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_build_004, TestSize.Level0) { std::vector inputsIndex = { 0 }; std::vector outputsIndex = { 1, 2 }; InitTensor(inputsIndex, outputsIndex); OH_NN_ReturnCode ret = m_builder.Build(m_paramsIndex, m_inputsIndex, m_outputsIndex, m_allTensors); EXPECT_EQ(OH_NN_INVALID_PARAMETER, ret); } /** * @tc.name: tanh_build_005 * @tc.desc: Provide empty input, output, and parameters to verify the abnormal behavior of the Build function * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_build_005, TestSize.Level0) { std::vector inputsIndex = { 0 }; std::vector outputsIndex = { 1 }; std::vector paramsIndex = {}; OH_NN_ReturnCode ret = m_builder.Build(paramsIndex, inputsIndex, outputsIndex, m_allTensors); EXPECT_EQ(OH_NN_INVALID_PARAMETER, ret); } /** * @tc.name: tanh_build_006 * @tc.desc: Provide empty output to verify the abnormal behavior of the Build function * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_build_006, TestSize.Level0) { std::vector inputsIndex = { 0 }; std::vector outputsIndex = { 1 }; std::vector inputDim = {1, 5, 1, 1}; SaveInputTensor(inputsIndex, OH_NN_FLOAT32, inputDim, nullptr); OH_NN_ReturnCode ret = m_builder.Build(m_paramsIndex, m_inputsIndex, outputsIndex, m_allTensors); EXPECT_EQ(OH_NN_INVALID_PARAMETER, ret); } /** * @tc.name: tanh_build_007 * @tc.desc: Provide a param to verify the abnormal behavior of the Build function * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_build_007, TestSize.Level0) { std::vector inputsIndex = { 0 }; std::vector outputsIndex = { 1 }; std::vector paramsIndex = { 4 }; m_paramsIndex = paramsIndex; InitTensor(inputsIndex, outputsIndex); OH_NN_ReturnCode ret = m_builder.Build(m_paramsIndex, m_inputsIndex, m_outputsIndex, m_allTensors); EXPECT_EQ(OH_NN_INVALID_PARAMETER, ret); } /** * @tc.name: tanh_get_primitive_001 * @tc.desc: Verify the GetPrimitive function return nullptr * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_get_primitive_001, TestSize.Level0) { LiteGraphTensorPtr primitive = m_builder.GetPrimitive(); LiteGraphTensorPtr expectPrimitive = { nullptr, DestroyLiteGraphPrimitive }; EXPECT_EQ(primitive, expectPrimitive); } /** * @tc.name: tanh_get_primitive_002 * @tc.desc: Verify the normal params return behavior of the getprimitive function * @tc.type: FUNC */ HWTEST_F(TanhBuilderTest, tanh_get_primitive_002, TestSize.Level0) { std::vector inputsIndex = { 0 }; std::vector outputsIndex = { 1 }; InitTensor(inputsIndex, outputsIndex); EXPECT_EQ(OH_NN_SUCCESS, m_builder.Build(m_paramsIndex, m_inputsIndex, m_outputsIndex, m_allTensors)); LiteGraphTensorPtr primitive = m_builder.GetPrimitive(); LiteGraphTensorPtr expectPrimitive = { nullptr, DestroyLiteGraphPrimitive }; EXPECT_NE(primitive, expectPrimitive); } } // namespace UnitTest } // namespace NeuralNetworkRuntime } // namespace OHOS