1 /** 2 * Copyright 2020 Huawei Technologies Co., Ltd 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 #include <vector> 17 #include <memory> 18 #include "common/common_test.h" 19 #include "ops/addn.h" 20 #include "ir/dtype/type.h" 21 #include "ir/value.h" 22 #include "abstract/dshape.h" 23 #include "utils/tensor_construct_utils.h" 24 25 namespace mindspore { 26 namespace ops { 27 class TestAddN : public UT::Common { 28 public: 29 TestAddN() {} 30 void SetUp() {} 31 void TearDown() {} 32 }; 33 34 TEST_F(TestAddN, test_ops_addn1) { 35 auto addn = std::make_shared<AddN>(); 36 auto tensor_x1 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3, 2, 7, 7}); 37 auto tensor_x2 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3, 2, 7, 7}); 38 MS_EXCEPTION_IF_NULL(tensor_x1); 39 MS_EXCEPTION_IF_NULL(tensor_x2); 40 auto input_tuple = std::make_shared<ValueTuple>(std::vector<ValuePtr>{tensor_x1, tensor_x2}); 41 auto abstract = addn->Infer({input_tuple->ToAbstract()}); 42 MS_EXCEPTION_IF_NULL(abstract); 43 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 44 auto shape_ptr = abstract->BuildShape(); 45 MS_EXCEPTION_IF_NULL(shape_ptr); 46 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 47 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 48 MS_EXCEPTION_IF_NULL(shape); 49 auto shape_vec = shape->shape(); 50 auto type = abstract->BuildType(); 51 MS_EXCEPTION_IF_NULL(type); 52 EXPECT_EQ(type->isa<TensorType>(), true); 53 auto tensor_type = type->cast<TensorTypePtr>(); 54 MS_EXCEPTION_IF_NULL(tensor_type); 55 auto data_type = tensor_type->element(); 56 MS_EXCEPTION_IF_NULL(data_type); 57 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 58 EXPECT_EQ(shape_vec.size(), 4); 59 EXPECT_EQ(shape_vec[0], 3); 60 EXPECT_EQ(shape_vec[1], 2); 61 EXPECT_EQ(shape_vec[2], 7); 62 EXPECT_EQ(shape_vec[3], 7); 63 } 64 65 TEST_F(TestAddN, test_ops_addn2) { 66 auto addn = std::make_shared<AddN>(); 67 auto tensor_x1 = TensorConstructUtils::CreateOnesTensor(kNumberTypeBool, std::vector<int64_t>{3, 4, 5}); 68 auto tensor_x2 = TensorConstructUtils::CreateOnesTensor(kNumberTypeBool, std::vector<int64_t>{3, 4, 5}); 69 auto tensor_x3 = TensorConstructUtils::CreateOnesTensor(kNumberTypeBool, std::vector<int64_t>{3, 4, 5}); 70 MS_EXCEPTION_IF_NULL(tensor_x1); 71 MS_EXCEPTION_IF_NULL(tensor_x2); 72 MS_EXCEPTION_IF_NULL(tensor_x3); 73 auto input_tuple = std::make_shared<ValueTuple>(std::vector<ValuePtr>{tensor_x1, tensor_x2, tensor_x3}); 74 auto abstract = addn->Infer({input_tuple->ToAbstract()}); 75 MS_EXCEPTION_IF_NULL(abstract); 76 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 77 auto shape_ptr = abstract->BuildShape(); 78 MS_EXCEPTION_IF_NULL(shape_ptr); 79 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 80 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 81 MS_EXCEPTION_IF_NULL(shape); 82 auto shape_vec = shape->shape(); 83 auto type = abstract->BuildType(); 84 MS_EXCEPTION_IF_NULL(type); 85 EXPECT_EQ(type->isa<TensorType>(), true); 86 auto tensor_type = type->cast<TensorTypePtr>(); 87 MS_EXCEPTION_IF_NULL(tensor_type); 88 auto data_type = tensor_type->element(); 89 MS_EXCEPTION_IF_NULL(data_type); 90 EXPECT_EQ(data_type->type_id(), kNumberTypeBool); 91 EXPECT_EQ(shape_vec.size(), 3); 92 EXPECT_EQ(shape_vec[0], 3); 93 EXPECT_EQ(shape_vec[1], 4); 94 EXPECT_EQ(shape_vec[2], 5); 95 } 96 } // namespace ops 97 } // namespace mindspore 98