/** * Copyright 2020 Huawei Technologies 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 #include #include "common/common_test.h" #include "ops/l2_normalize.h" #include "ir/dtype/type.h" #include "ir/value.h" #include "abstract/dshape.h" #include "utils/tensor_construct_utils.h" namespace mindspore { namespace ops { class TestL2Normalize : public UT::Common { public: TestL2Normalize() {} void SetUp() {} void TearDown() {} }; TEST_F(TestL2Normalize, test_ops_l2_normalize1) { auto l2_normalize = std::make_shared(); l2_normalize->Init(std::vector{0, 1, 2}); auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector{2, 3, 4, 5}); MS_EXCEPTION_IF_NULL(tensor_x); auto abstract = l2_normalize->Infer({tensor_x->ToAbstract()}); MS_EXCEPTION_IF_NULL(abstract); EXPECT_EQ(abstract->isa(), true); auto shape_ptr = abstract->BuildShape(); MS_EXCEPTION_IF_NULL(shape_ptr); EXPECT_EQ(shape_ptr->isa(), true); auto shape = shape_ptr->cast(); MS_EXCEPTION_IF_NULL(shape); auto shape_vec = shape->shape(); auto type = abstract->BuildType(); MS_EXCEPTION_IF_NULL(type); EXPECT_EQ(type->isa(), true); auto tensor_type = type->cast(); MS_EXCEPTION_IF_NULL(tensor_type); auto data_type = tensor_type->element(); MS_EXCEPTION_IF_NULL(data_type); EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); EXPECT_EQ(shape_vec.size(), 4); EXPECT_EQ(shape_vec[0], 2); EXPECT_EQ(shape_vec[1], 3); EXPECT_EQ(shape_vec[2], 4); EXPECT_EQ(shape_vec[3], 5); } } // namespace ops } // namespace mindspore