1 /* 2 * Copyright (c) 2019-2021 Arm Limited. 3 * 4 * SPDX-License-Identifier: MIT 5 * 6 * Permission is hereby granted, free of charge, to any person obtaining a copy 7 * of this software and associated documentation files (the "Software"), to 8 * deal in the Software without restriction, including without limitation the 9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or 10 * sell copies of the Software, and to permit persons to whom the Software is 11 * furnished to do so, subject to the following conditions: 12 * 13 * The above copyright notice and this permission notice shall be included in all 14 * copies or substantial portions of the Software. 15 * 16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 * SOFTWARE. 23 */ 24 #ifndef ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE 25 #define ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE 26 27 #include "arm_compute/core/Helpers.h" 28 #include "arm_compute/core/TensorShape.h" 29 #include "arm_compute/core/Types.h" 30 #include "arm_compute/runtime/Tensor.h" 31 #include "tests/AssetsLibrary.h" 32 #include "tests/Globals.h" 33 #include "tests/IAccessor.h" 34 #include "tests/framework/Asserts.h" 35 #include "tests/framework/Fixture.h" 36 #include "tests/validation/reference/NonMaxSuppression.h" 37 38 namespace arm_compute 39 { 40 namespace test 41 { 42 namespace validation 43 { 44 template <typename TensorType, typename AccessorType, typename FunctionType> 45 46 class NMSValidationFixture : public framework::Fixture 47 { 48 public: 49 template <typename...> setup(TensorShape input_shape,unsigned int max_output_size,float score_threshold,float nms_threshold)50 void setup(TensorShape input_shape, unsigned int max_output_size, float score_threshold, float nms_threshold) 51 { 52 ARM_COMPUTE_ERROR_ON(max_output_size == 0); 53 ARM_COMPUTE_ERROR_ON(input_shape.num_dimensions() != 2); 54 const TensorShape output_shape(max_output_size); 55 const TensorShape scores_shape(input_shape[1]); 56 _target = compute_target(input_shape, scores_shape, output_shape, max_output_size, score_threshold, nms_threshold); 57 _reference = compute_reference(input_shape, scores_shape, output_shape, max_output_size, score_threshold, nms_threshold); 58 } 59 60 protected: 61 template <typename U> fill(U && tensor,int i,float lo,float hi)62 void fill(U &&tensor, int i, float lo, float hi) 63 { 64 std::uniform_real_distribution<float> distribution(lo, hi); 65 library->fill_boxes(tensor, distribution, i); 66 } 67 compute_target(const TensorShape input_shape,const TensorShape scores_shape,const TensorShape output_shape,unsigned int max_output_size,float score_threshold,float nms_threshold)68 TensorType compute_target(const TensorShape input_shape, const TensorShape scores_shape, const TensorShape output_shape, 69 unsigned int max_output_size, float score_threshold, float nms_threshold) 70 { 71 // Create tensors 72 TensorType bboxes = create_tensor<TensorType>(input_shape, DataType::F32); 73 TensorType scores = create_tensor<TensorType>(scores_shape, DataType::F32); 74 TensorType indices = create_tensor<TensorType>(output_shape, DataType::S32); 75 76 // Create and configure function 77 FunctionType nms_func; 78 nms_func.configure(&bboxes, &scores, &indices, max_output_size, score_threshold, nms_threshold); 79 80 ARM_COMPUTE_ASSERT(bboxes.info()->is_resizable()); 81 ARM_COMPUTE_ASSERT(indices.info()->is_resizable()); 82 ARM_COMPUTE_ASSERT(scores.info()->is_resizable()); 83 84 // Allocate tensors 85 bboxes.allocator()->allocate(); 86 indices.allocator()->allocate(); 87 scores.allocator()->allocate(); 88 89 ARM_COMPUTE_ASSERT(!bboxes.info()->is_resizable()); 90 ARM_COMPUTE_ASSERT(!indices.info()->is_resizable()); 91 ARM_COMPUTE_ASSERT(!scores.info()->is_resizable()); 92 93 // Fill tensors 94 fill(AccessorType(bboxes), 0, 0.f, 1.f); 95 fill(AccessorType(scores), 1, 0.f, 1.f); 96 97 // Compute function 98 nms_func.run(); 99 return indices; 100 } 101 compute_reference(const TensorShape input_shape,const TensorShape scores_shape,const TensorShape output_shape,unsigned int max_output_size,float score_threshold,float nms_threshold)102 SimpleTensor<int> compute_reference(const TensorShape input_shape, const TensorShape scores_shape, const TensorShape output_shape, 103 unsigned int max_output_size, float score_threshold, float nms_threshold) 104 { 105 // Create reference 106 SimpleTensor<float> bboxes{ input_shape, DataType::F32 }; 107 SimpleTensor<float> scores{ scores_shape, DataType::F32 }; 108 SimpleTensor<int> indices{ output_shape, DataType::S32 }; 109 110 // Fill reference 111 fill(bboxes, 0, 0.f, 1.f); 112 fill(scores, 1, 0.f, 1.f); 113 114 return reference::non_max_suppression(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold); 115 } 116 117 TensorType _target{}; 118 SimpleTensor<int> _reference{}; 119 }; 120 121 } // namespace validation 122 } // namespace test 123 } // namespace arm_compute 124 #endif /* ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE */ 125