1 /** 2 * Copyright 2021 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/unsqueeze.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 TestUnsqueeze : public UT::Common { 28 public: 29 TestUnsqueeze() {} 30 void SetUp() {} 31 void TearDown() {} 32 }; 33 34 /*TEST_F(TestUnsqueeze, test_unsqueeze_1) { 35 auto unsqueeze = std::make_shared<Unsqueeze>(); 36 std::vector<int64_t> axis = {}; 37 unsqueeze->Init(axis); 38 auto tensor_x = std::make_shared<tensor::Tensor>(kNumberTypeFloat16, std::vector<int64_t>{1, 3, 2}); 39 MS_EXCEPTION_IF_NULL(tensor_x); 40 auto tensor_x_data = reinterpret_cast<int *>(tensor_x->data_c()); 41 *tensor_x_data = 1; 42 tensor_x_data++; 43 *tensor_x_data = 2; 44 tensor_x_data++; 45 *tensor_x_data = 3; 46 tensor_x_data++; 47 *tensor_x_data = 4; 48 tensor_x_data++; 49 *tensor_x_data = 5; 50 tensor_x_data++; 51 *tensor_x_data = 6; 52 tensor_x_data++; 53 auto abstract = unsqueeze->Infer({tensor_x->ToAbstract()}); 54 MS_EXCEPTION_IF_NULL(abstract); 55 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 56 auto shape_ptr = abstract->BuildShape(); 57 MS_EXCEPTION_IF_NULL(shape_ptr); 58 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 59 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 60 MS_EXCEPTION_IF_NULL(shape); 61 auto shape_vec = shape->shape(); 62 EXPECT_EQ(shape_vec.size(), 2); 63 EXPECT_EQ(shape_vec[0], 3); 64 EXPECT_EQ(shape_vec[1], 2); 65 auto type = abstract->BuildType(); 66 MS_EXCEPTION_IF_NULL(type); 67 EXPECT_EQ(type->isa<TensorType>(), true); 68 auto tensor_type = type->cast<TensorTypePtr>(); 69 MS_EXCEPTION_IF_NULL(tensor_type); 70 auto data_type = tensor_type->element(); 71 MS_EXCEPTION_IF_NULL(data_type); 72 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat16); 73 } 74 */ 75 TEST_F(TestUnsqueeze, test_unsqueeze_1) { 76 auto unsqueeze = std::make_shared<Unsqueeze>(); 77 std::vector<int64_t> axis = {1, 2}; 78 unsqueeze->Init(axis); 79 auto tensor_x = std::make_shared<tensor::Tensor>(kNumberTypeFloat32, std::vector<int64_t>{1, 3}); 80 MS_EXCEPTION_IF_NULL(tensor_x); 81 auto tensor_x_data = reinterpret_cast<int *>(tensor_x->data_c()); 82 *tensor_x_data = 1; 83 tensor_x_data++; 84 *tensor_x_data = 2; 85 tensor_x_data++; 86 *tensor_x_data = 3; 87 tensor_x_data++; 88 auto abstract = unsqueeze->Infer({tensor_x->ToAbstract()}); 89 MS_EXCEPTION_IF_NULL(abstract); 90 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 91 auto shape_ptr = abstract->BuildShape(); 92 MS_EXCEPTION_IF_NULL(shape_ptr); 93 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 94 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 95 MS_EXCEPTION_IF_NULL(shape); 96 auto shape_vec = shape->shape(); 97 EXPECT_EQ(shape_vec.size(), 4); 98 EXPECT_EQ(shape_vec[0], 1); 99 EXPECT_EQ(shape_vec[1], 1); 100 EXPECT_EQ(shape_vec[2], 1); 101 EXPECT_EQ(shape_vec[3], 3); 102 auto type = abstract->BuildType(); 103 MS_EXCEPTION_IF_NULL(type); 104 EXPECT_EQ(type->isa<TensorType>(), true); 105 auto tensor_type = type->cast<TensorTypePtr>(); 106 MS_EXCEPTION_IF_NULL(tensor_type); 107 auto data_type = tensor_type->element(); 108 MS_EXCEPTION_IF_NULL(data_type); 109 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 110 } 111 } // namespace ops 112 } // namespace mindspore 113