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/prelu.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 TestPReLU : public UT::Common { 28 public: 29 TestPReLU() {} 30 void SetUp() {} 31 void TearDown() {} 32 }; 33 34 TEST_F(TestPReLU, test_ops_prelu1) { 35 auto prelu = std::make_shared<PReLU>(); 36 auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{2, 3, 4}); 37 auto tensor_w = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat32, std::vector<int64_t>{3}); 38 MS_EXCEPTION_IF_NULL(tensor_x); 39 MS_EXCEPTION_IF_NULL(tensor_w); 40 auto abstract = prelu->Infer({tensor_x->ToAbstract(), tensor_w->ToAbstract()}); 41 MS_EXCEPTION_IF_NULL(abstract); 42 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 43 auto shape_ptr = abstract->BuildShape(); 44 MS_EXCEPTION_IF_NULL(shape_ptr); 45 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 46 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 47 MS_EXCEPTION_IF_NULL(shape); 48 auto shape_vec = shape->shape(); 49 auto type = abstract->BuildType(); 50 MS_EXCEPTION_IF_NULL(type); 51 EXPECT_EQ(type->isa<TensorType>(), true); 52 auto tensor_type = type->cast<TensorTypePtr>(); 53 MS_EXCEPTION_IF_NULL(tensor_type); 54 auto data_type = tensor_type->element(); 55 MS_EXCEPTION_IF_NULL(data_type); 56 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat32); 57 EXPECT_EQ(shape_vec.size(), 3); 58 EXPECT_EQ(shape_vec[0], 2); 59 EXPECT_EQ(shape_vec[1], 3); 60 EXPECT_EQ(shape_vec[2], 4); 61 } 62 63 TEST_F(TestPReLU, test_ops_prelu2) { 64 auto prelu = std::make_shared<PReLU>(); 65 auto tensor_x = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat16, std::vector<int64_t>{5, 6, 7, 8}); 66 auto tensor_w = TensorConstructUtils::CreateOnesTensor(kNumberTypeFloat16, std::vector<int64_t>{1}); 67 MS_EXCEPTION_IF_NULL(tensor_x); 68 MS_EXCEPTION_IF_NULL(tensor_w); 69 auto abstract = prelu->Infer({tensor_x->ToAbstract(), tensor_w->ToAbstract()}); 70 MS_EXCEPTION_IF_NULL(abstract); 71 EXPECT_EQ(abstract->isa<abstract::AbstractTensor>(), true); 72 auto shape_ptr = abstract->BuildShape(); 73 MS_EXCEPTION_IF_NULL(shape_ptr); 74 EXPECT_EQ(shape_ptr->isa<abstract::Shape>(), true); 75 auto shape = shape_ptr->cast<abstract::ShapePtr>(); 76 MS_EXCEPTION_IF_NULL(shape); 77 auto shape_vec = shape->shape(); 78 auto type = abstract->BuildType(); 79 MS_EXCEPTION_IF_NULL(type); 80 EXPECT_EQ(type->isa<TensorType>(), true); 81 auto tensor_type = type->cast<TensorTypePtr>(); 82 MS_EXCEPTION_IF_NULL(tensor_type); 83 auto data_type = tensor_type->element(); 84 MS_EXCEPTION_IF_NULL(data_type); 85 EXPECT_EQ(data_type->type_id(), kNumberTypeFloat16); 86 EXPECT_EQ(shape_vec.size(), 4); 87 EXPECT_EQ(shape_vec[0], 5); 88 EXPECT_EQ(shape_vec[1], 6); 89 EXPECT_EQ(shape_vec[2], 7); 90 EXPECT_EQ(shape_vec[3], 8); 91 } 92 } // namespace ops 93 } // namespace mindspore 94