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/concat.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 TestConcat : public UT::Common { 28 public: 29 TestConcat() {} 30 void SetUp() {} 31 void TearDown() {} 32 }; 33 34 TEST_F(TestConcat, test_ops_concat1) { 35 auto concat = std::make_shared<Concat>(); 36 concat->Init(1); 37 auto tensor_x1 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3, 2, 7, 7}); 38 auto tensor_x2 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3, 3, 7, 7}); 39 auto tensor_x3 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3, 4, 7, 7}); 40 MS_EXCEPTION_IF_NULL(tensor_x1); 41 MS_EXCEPTION_IF_NULL(tensor_x2); 42 MS_EXCEPTION_IF_NULL(tensor_x3); 43 auto input_tuple = std::make_shared<ValueTuple>(std::vector<ValuePtr>{tensor_x1, tensor_x2, tensor_x3}); 44 auto abstract = concat->Infer({input_tuple->ToAbstract()}); 45 MS_EXCEPTION_IF_NULL(abstract); 46 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 47 auto shape_ptr = abstract->BuildShape(); 48 MS_EXCEPTION_IF_NULL(shape_ptr); 49 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 50 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 51 MS_EXCEPTION_IF_NULL(shape); 52 auto shape_vec = shape->shape(); 53 auto type = abstract->BuildType(); 54 MS_EXCEPTION_IF_NULL(type); 55 EXPECT_EQ(type->isa<TensorType>(), true); 56 auto tensor_type = type->cast<TensorTypePtr>(); 57 MS_EXCEPTION_IF_NULL(tensor_type); 58 auto data_type = tensor_type->element(); 59 MS_EXCEPTION_IF_NULL(data_type); 60 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 61 EXPECT_EQ(shape_vec.size(), 4); 62 EXPECT_EQ(shape_vec[0], 3); 63 EXPECT_EQ(shape_vec[1], 9); 64 EXPECT_EQ(shape_vec[2], 7); 65 EXPECT_EQ(shape_vec[3], 7); 66 } 67 68 TEST_F(TestConcat, test_ops_concat2) { 69 auto concat = std::make_shared<Concat>(); 70 concat->Init(2); 71 auto tensor_x1 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat16, std::vector<int64_t>{3, 4, 5}); 72 auto tensor_x2 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat16, std::vector<int64_t>{3, 4, 2}); 73 auto tensor_x3 = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat16, std::vector<int64_t>{3, 4, 3}); 74 MS_EXCEPTION_IF_NULL(tensor_x1); 75 MS_EXCEPTION_IF_NULL(tensor_x2); 76 MS_EXCEPTION_IF_NULL(tensor_x3); 77 auto input_tuple = std::make_shared<ValueTuple>(std::vector<ValuePtr>{tensor_x1, tensor_x2, tensor_x3}); 78 auto abstract = concat->Infer({input_tuple->ToAbstract()}); 79 MS_EXCEPTION_IF_NULL(abstract); 80 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 81 auto shape_ptr = abstract->BuildShape(); 82 MS_EXCEPTION_IF_NULL(shape_ptr); 83 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 84 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 85 MS_EXCEPTION_IF_NULL(shape); 86 auto shape_vec = shape->shape(); 87 auto type = abstract->BuildType(); 88 MS_EXCEPTION_IF_NULL(type); 89 EXPECT_EQ(type->isa<TensorType>(), true); 90 auto tensor_type = type->cast<TensorTypePtr>(); 91 MS_EXCEPTION_IF_NULL(tensor_type); 92 auto data_type = tensor_type->element(); 93 MS_EXCEPTION_IF_NULL(data_type); 94 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat16); 95 EXPECT_EQ(shape_vec.size(), 3); 96 EXPECT_EQ(shape_vec[0], 3); 97 EXPECT_EQ(shape_vec[1], 4); 98 EXPECT_EQ(shape_vec[2], 10); 99 } 100 } // namespace ops 101 } // namespace mindspore 102