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/range.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 TestRange : public UT::Common { 28 public: 29 TestRange() {} 30 void SetUp() {} 31 void TearDown() {} 32 }; 33 34 TEST_F(TestRange, test_ops_range1) { 35 auto range = std::make_shared<Range>(); 36 range->Init(1, 3, 34, 4); 37 EXPECT_EQ(range->get_d_type(), 1); 38 EXPECT_EQ(range->get_start(), 3); 39 EXPECT_EQ(range->get_limit(), 34); 40 EXPECT_EQ(range->get_delta(), 4); 41 range->set_d_type(1); 42 range->set_start(3); 43 range->set_limit(34); 44 range->set_delta(4); 45 auto abstract = range->Infer({}); 46 MS_EXCEPTION_IF_NULL(abstract); 47 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 48 auto shape_ptr = abstract->BuildShape(); 49 MS_EXCEPTION_IF_NULL(shape_ptr); 50 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 51 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 52 MS_EXCEPTION_IF_NULL(shape); 53 auto shape_vec = shape->shape(); 54 auto type = abstract->BuildType(); 55 MS_EXCEPTION_IF_NULL(type); 56 EXPECT_EQ(type->isa<TensorType>(), true); 57 auto tensor_type = type->cast<TensorTypePtr>(); 58 MS_EXCEPTION_IF_NULL(tensor_type); 59 auto data_type = tensor_type->element(); 60 MS_EXCEPTION_IF_NULL(data_type); 61 EXPECT_EQ(data_type->type_id(), kNumberTypeInt32); 62 EXPECT_EQ(shape_vec.size(), 1); 63 EXPECT_EQ(shape_vec[0], 8); 64 EXPECT_EQ(range->get_d_type(), 1); 65 EXPECT_EQ(range->get_start(), 3); 66 EXPECT_EQ(range->get_limit(), 34); 67 EXPECT_EQ(range->get_delta(), 4); 68 } 69 70 TEST_F(TestRange, test_ops_range2) { 71 auto range = std::make_shared<Range>(); 72 range->Init(1, 1, 1, 1); 73 EXPECT_EQ(range->get_d_type(), 1); 74 EXPECT_EQ(range->get_start(), 1); 75 EXPECT_EQ(range->get_limit(), 1); 76 EXPECT_EQ(range->get_delta(), 1); 77 range->set_d_type(1); 78 range->set_start(1); 79 range->set_limit(1); 80 range->set_delta(1); 81 auto tensor_x1 = std::make_shared<tensor::Tensor>(kNumberTypeFloat32, std::vector<int64_t>{1}); 82 auto tensor_x2 = std::make_shared<tensor::Tensor>(kNumberTypeFloat32, std::vector<int64_t>{1}); 83 auto tensor_x3 = std::make_shared<tensor::Tensor>(kNumberTypeFloat32, std::vector<int64_t>{1}); 84 MS_EXCEPTION_IF_NULL(tensor_x1); 85 MS_EXCEPTION_IF_NULL(tensor_x2); 86 MS_EXCEPTION_IF_NULL(tensor_x3); 87 auto data_x1 = tensor_x1->data_c(); 88 MS_EXCEPTION_IF_NULL(data_x1); 89 auto val_x1 = reinterpret_cast<float *>(data_x1); 90 *val_x1 = 1.0; 91 auto data_x2 = tensor_x2->data_c(); 92 MS_EXCEPTION_IF_NULL(data_x2); 93 auto val_x2 = reinterpret_cast<float *>(data_x2); 94 *val_x2 = 42.0; 95 auto data_x3 = tensor_x3->data_c(); 96 MS_EXCEPTION_IF_NULL(data_x3); 97 auto val_x3 = reinterpret_cast<float *>(data_x3); 98 *val_x3 = 3.0; 99 auto abstract = range->Infer({tensor_x1->ToAbstract(), tensor_x2->ToAbstract(), tensor_x3->ToAbstract()}); 100 MS_EXCEPTION_IF_NULL(abstract); 101 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 102 auto shape_ptr = abstract->BuildShape(); 103 MS_EXCEPTION_IF_NULL(shape_ptr); 104 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 105 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 106 MS_EXCEPTION_IF_NULL(shape); 107 auto shape_vec = shape->shape(); 108 auto type = abstract->BuildType(); 109 MS_EXCEPTION_IF_NULL(type); 110 EXPECT_EQ(type->isa<TensorType>(), true); 111 auto tensor_type = type->cast<TensorTypePtr>(); 112 MS_EXCEPTION_IF_NULL(tensor_type); 113 auto data_type = tensor_type->element(); 114 MS_EXCEPTION_IF_NULL(data_type); 115 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 116 EXPECT_EQ(shape_vec.size(), 1); 117 EXPECT_EQ(shape_vec[0], 14); 118 EXPECT_EQ(range->get_d_type(), 1); 119 EXPECT_EQ(range->get_start(), 1); 120 EXPECT_EQ(range->get_limit(), 1); 121 EXPECT_EQ(range->get_delta(), 1); 122 } 123 } // namespace ops 124 } // namespace mindspore 125