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/strided_slice.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 namespace { 28 template <typename T> 29 void SetTensorData(void *data, std::vector<T> num) { 30 MS_EXCEPTION_IF_NULL(data); 31 auto tensor_data = reinterpret_cast<T *>(data); 32 MS_EXCEPTION_IF_NULL(tensor_data); 33 for (size_t index = 0; index < num.size(); ++index) { 34 *tensor_data = num[index]; 35 } 36 } 37 } // namespace 38 class TestStridedSlice : public UT::Common { 39 public: 40 TestStridedSlice() {} 41 void SetUp() {} 42 void TearDown() {} 43 }; 44 45 TEST_F(TestStridedSlice, test_ops_stridedslice1) { 46 auto stridedslice = std::make_shared<StridedSlice>(); 47 stridedslice->Init(0, 0, 0, 0, 0); 48 EXPECT_EQ(stridedslice->get_begin_mask(), 0); 49 EXPECT_EQ(stridedslice->get_end_mask(), 0); 50 EXPECT_EQ(stridedslice->get_ellipsis_mask(), 0); 51 EXPECT_EQ(stridedslice->get_new_axis_mask(), 0); 52 EXPECT_EQ(stridedslice->get_shrink_axis_mask(), 0); 53 auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3, 3, 3}); 54 auto begin = MakeValue(std::vector<int64_t>{1, 0, 0}); 55 auto end = MakeValue(std::vector<int64_t>{2, 1, 3}); 56 auto strides = MakeValue(std::vector<int64_t>{1, 1, 1}); 57 MS_EXCEPTION_IF_NULL(tensor_x); 58 MS_EXCEPTION_IF_NULL(begin); 59 MS_EXCEPTION_IF_NULL(end); 60 MS_EXCEPTION_IF_NULL(strides); 61 auto abstract = 62 stridedslice->Infer({tensor_x->ToAbstract(), begin->ToAbstract(), end->ToAbstract(), strides->ToAbstract()}); 63 MS_EXCEPTION_IF_NULL(abstract); 64 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 65 auto shape_ptr = abstract->BuildShape(); 66 MS_EXCEPTION_IF_NULL(shape_ptr); 67 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 68 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 69 MS_EXCEPTION_IF_NULL(shape); 70 auto shape_vec = shape->shape(); 71 auto type = abstract->BuildType(); 72 MS_EXCEPTION_IF_NULL(type); 73 EXPECT_EQ(type->isa<TensorType>(), true); 74 auto tensor_type = type->cast<TensorTypePtr>(); 75 MS_EXCEPTION_IF_NULL(tensor_type); 76 auto data_type = tensor_type->element(); 77 MS_EXCEPTION_IF_NULL(data_type); 78 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 79 EXPECT_EQ(shape_vec.size(), 3); 80 EXPECT_EQ(shape_vec[0], 1); 81 EXPECT_EQ(shape_vec[1], 1); 82 EXPECT_EQ(shape_vec[2], 3); 83 } 84 /* 85 TEST_F(TestStridedSlice, test_ops_stridedslice2) { 86 auto stridedslice = std::make_shared<StridedSlice>(); 87 stridedslice->Init(0, 0, 0, 0, 0); 88 EXPECT_EQ(stridedslice->get_begin_mask(), 0); 89 EXPECT_EQ(stridedslice->get_end_mask(), 0); 90 EXPECT_EQ(stridedslice->get_ellipsis_mask(), 0); 91 EXPECT_EQ(stridedslice->get_new_axis_mask(), 0); 92 EXPECT_EQ(stridedslice->get_shrink_axis_mask(), 0); 93 auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3,3,3}); 94 auto begin = MakeValue(std::vector<int64_t>{1,0,0}); 95 auto end = MakeValue(std::vector<int64_t>{2,2,3}); 96 auto strides =MakeValue(std::vector<int64_t>{1,1,1}); 97 MS_EXCEPTION_IF_NULL(tensor_x); 98 MS_EXCEPTION_IF_NULL(begin); 99 MS_EXCEPTION_IF_NULL(end); 100 MS_EXCEPTION_IF_NULL(strides); 101 auto abstract = 102 stridedslice->Infer({tensor_x->ToAbstract(),begin->ToAbstract(),end->ToAbstract(),strides->ToAbstract()}); 103 MS_EXCEPTION_IF_NULL(abstract); 104 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 105 auto shape_ptr = abstract->BuildShape(); 106 MS_EXCEPTION_IF_NULL(shape_ptr); 107 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 108 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 109 MS_EXCEPTION_IF_NULL(shape); 110 auto shape_vec = shape->shape(); 111 auto type = abstract->BuildType(); 112 MS_EXCEPTION_IF_NULL(type); 113 EXPECT_EQ(type->isa<TensorType>(), true); 114 auto tensor_type = type->cast<TensorTypePtr>(); 115 MS_EXCEPTION_IF_NULL(tensor_type); 116 auto data_type = tensor_type->element(); 117 MS_EXCEPTION_IF_NULL(data_type); 118 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 119 EXPECT_EQ(shape_vec.size(), 3); 120 EXPECT_EQ(shape_vec[0], 1); 121 EXPECT_EQ(shape_vec[1], 2); 122 EXPECT_EQ(shape_vec[2], 3); 123 } 124 125 TEST_F(TestStridedSlice, test_ops_stridedslice3) { 126 auto stridedslice = std::make_shared<StridedSlice>(); 127 stridedslice->Init(0, 0, 0, 0, 0); 128 EXPECT_EQ(stridedslice->get_begin_mask(), 0); 129 EXPECT_EQ(stridedslice->get_end_mask(), 0); 130 EXPECT_EQ(stridedslice->get_ellipsis_mask(), 0); 131 EXPECT_EQ(stridedslice->get_new_axis_mask(), 0); 132 EXPECT_EQ(stridedslice->get_shrink_axis_mask(), 0); 133 auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3,3,3}); 134 auto begin = MakeValue(std::vector<int64_t>{1,0,0}); 135 auto end = MakeValue(std::vector<int64_t>{2,-3,3}); 136 auto strides =MakeValue(std::vector<int64_t>{1,-1,1}); 137 MS_EXCEPTION_IF_NULL(tensor_x); 138 MS_EXCEPTION_IF_NULL(begin); 139 MS_EXCEPTION_IF_NULL(end); 140 MS_EXCEPTION_IF_NULL(strides); 141 auto abstract = 142 stridedslice->Infer({tensor_x->ToAbstract(),begin->ToAbstract(),end->ToAbstract(),strides->ToAbstract()}); 143 MS_EXCEPTION_IF_NULL(abstract); 144 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 145 auto shape_ptr = abstract->BuildShape(); 146 MS_EXCEPTION_IF_NULL(shape_ptr); 147 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 148 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 149 MS_EXCEPTION_IF_NULL(shape); 150 auto shape_vec = shape->shape(); 151 auto type = abstract->BuildType(); 152 MS_EXCEPTION_IF_NULL(type); 153 EXPECT_EQ(type->isa<TensorType>(), true); 154 auto tensor_type = type->cast<TensorTypePtr>(); 155 MS_EXCEPTION_IF_NULL(tensor_type); 156 auto data_type = tensor_type->element(); 157 MS_EXCEPTION_IF_NULL(data_type); 158 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 159 EXPECT_EQ(shape_vec.size(), 3); 160 EXPECT_EQ(shape_vec[0], 1); 161 EXPECT_EQ(shape_vec[1], 2); 162 EXPECT_EQ(shape_vec[2], 3); 163 } 164 165 TEST_F(TestStridedSlice, test_ops_stridedslice4) { 166 auto stridedslice = std::make_shared<StridedSlice>(); 167 stridedslice->Init(0, 0, 0, 0, 0); 168 EXPECT_EQ(stridedslice->get_begin_mask(), 0); 169 EXPECT_EQ(stridedslice->get_end_mask(), 0); 170 EXPECT_EQ(stridedslice->get_ellipsis_mask(), 0); 171 EXPECT_EQ(stridedslice->get_new_axis_mask(), 0); 172 EXPECT_EQ(stridedslice->get_shrink_axis_mask(), 0); 173 174 auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{5}); 175 auto begin = MakeValue(std::vector<int64_t>{1}); 176 auto end = MakeValue(std::vector<int64_t>{-2}); 177 auto strides =MakeValue(std::vector<int64_t>{1}); 178 MS_EXCEPTION_IF_NULL(tensor_x); 179 MS_EXCEPTION_IF_NULL(begin); 180 MS_EXCEPTION_IF_NULL(end); 181 MS_EXCEPTION_IF_NULL(strides); 182 auto abstract = 183 stridedslice->Infer({tensor_x->ToAbstract(),begin->ToAbstract(),end->ToAbstract(),strides->ToAbstract()}); 184 MS_EXCEPTION_IF_NULL(abstract); 185 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 186 auto shape_ptr = abstract->BuildShape(); 187 MS_EXCEPTION_IF_NULL(shape_ptr); 188 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 189 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 190 MS_EXCEPTION_IF_NULL(shape); 191 auto shape_vec = shape->shape(); 192 auto type = abstract->BuildType(); 193 MS_EXCEPTION_IF_NULL(type); 194 EXPECT_EQ(type->isa<TensorType>(), true); 195 auto tensor_type = type->cast<TensorTypePtr>(); 196 MS_EXCEPTION_IF_NULL(tensor_type); 197 auto data_type = tensor_type->element(); 198 MS_EXCEPTION_IF_NULL(data_type); 199 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 200 EXPECT_EQ(shape_vec.size(), 1); 201 EXPECT_EQ(shape_vec[0], 2); 202 }*/ 203 } // namespace ops 204 } // namespace mindspore