1 /* 2 * Copyright (c) 2017-2021 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_SCHARR_FIXTURE 25 #define ARM_COMPUTE_TEST_SCHARR_FIXTURE 26 27 #include "tests/Globals.h" 28 #include "tests/IAccessor.h" 29 #include "tests/Types.h" 30 #include "tests/framework/Asserts.h" 31 #include "tests/framework/Fixture.h" 32 #include "tests/validation/reference/Scharr.h" 33 34 #include <memory> 35 36 namespace arm_compute 37 { 38 class CLScharr3x3; 39 class NEScharr3x3; 40 41 namespace test 42 { 43 namespace validation 44 { 45 namespace 46 { 47 template <typename Function> 48 struct info; 49 50 template <> 51 struct info<NEScharr3x3> 52 { 53 static const Format dst_format = Format::S16; 54 static const int filter_size = 3; 55 }; 56 57 template <> 58 struct info<CLScharr3x3> 59 { 60 static const Format dst_format = Format::S16; 61 static const int filter_size = 3; 62 }; 63 } // namespace 64 65 template <typename TensorType, typename AccessorType, typename FunctionType, typename T, typename U> 66 class ScharrValidationFixture : public framework::Fixture 67 { 68 public: 69 template <typename...> 70 void setup(TensorShape shape, BorderMode border_mode, Format format, GradientDimension gradient_dimension) 71 { 72 // Generate a random constant value 73 std::mt19937 gen(library->seed()); 74 std::uniform_int_distribution<uint8_t> int_dist(0, 255); 75 const uint8_t constant_border_value = int_dist(gen); 76 77 _border_mode = border_mode; 78 _target = compute_target(shape, border_mode, format, constant_border_value, gradient_dimension); 79 _reference = compute_reference(shape, info<FunctionType>::filter_size, border_mode, format, constant_border_value, gradient_dimension); 80 } 81 82 protected: 83 template <typename V> 84 void fill(V &&tensor) 85 { 86 library->fill_tensor_uniform(tensor, 0); 87 } 88 89 template <typename V> 90 void fill_zero(V &&tensor) 91 { 92 library->fill_tensor_uniform(tensor, 0, static_cast<U>(0), static_cast<U>(0)); 93 } 94 95 std::pair<TensorType, TensorType> compute_target(const TensorShape &shape, BorderMode border_mode, Format format, uint8_t constant_border_value, GradientDimension gradient_dimension) 96 { 97 // Create tensors 98 TensorType src = create_tensor<TensorType>(shape, data_type_from_format(format)); 99 TensorType dst_x = create_tensor<TensorType>(shape, data_type_from_format(info<FunctionType>::dst_format)); 100 TensorType dst_y = create_tensor<TensorType>(shape, data_type_from_format(info<FunctionType>::dst_format)); 101 102 src.info()->set_format(format); 103 dst_x.info()->set_format(info<FunctionType>::dst_format); 104 dst_y.info()->set_format(info<FunctionType>::dst_format); 105 106 FunctionType scharr; 107 108 switch(gradient_dimension) 109 { 110 case GradientDimension::GRAD_X: 111 scharr.configure(&src, &dst_x, nullptr, border_mode, constant_border_value); 112 break; 113 case GradientDimension::GRAD_Y: 114 scharr.configure(&src, nullptr, &dst_y, border_mode, constant_border_value); 115 break; 116 case GradientDimension::GRAD_XY: 117 scharr.configure(&src, &dst_x, &dst_y, border_mode, constant_border_value); 118 break; 119 default: 120 ARM_COMPUTE_ERROR("Gradient dimension not supported"); 121 } 122 123 ARM_COMPUTE_ASSERT(src.info()->is_resizable()); 124 ARM_COMPUTE_ASSERT(dst_x.info()->is_resizable()); 125 ARM_COMPUTE_ASSERT(dst_y.info()->is_resizable()); 126 127 // Allocate tensors 128 src.allocator()->allocate(); 129 dst_x.allocator()->allocate(); 130 dst_y.allocator()->allocate(); 131 132 ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); 133 ARM_COMPUTE_ASSERT(!dst_x.info()->is_resizable()); 134 ARM_COMPUTE_ASSERT(!dst_y.info()->is_resizable()); 135 136 // Fill tensors 137 fill(AccessorType(src)); 138 fill_zero(AccessorType(dst_x)); 139 fill_zero(AccessorType(dst_y)); 140 141 // Compute function 142 scharr.run(); 143 144 return std::make_pair(std::move(dst_x), std::move(dst_y)); 145 } 146 147 std::pair<SimpleTensor<U>, SimpleTensor<U>> compute_reference(const TensorShape &shape, int filter_size, BorderMode border_mode, Format format, uint8_t constant_border_value, 148 GradientDimension gradient_dimension) 149 { 150 // Create reference 151 SimpleTensor<T> src{ shape, format }; 152 153 // Fill reference 154 fill(src); 155 156 return reference::scharr<U>(src, filter_size, border_mode, constant_border_value, gradient_dimension); 157 } 158 159 BorderMode _border_mode{ BorderMode::UNDEFINED }; 160 std::pair<TensorType, TensorType> _target{}; 161 std::pair<SimpleTensor<U>, SimpleTensor<U>> _reference{}; 162 }; 163 } // namespace validation 164 } // namespace test 165 } // namespace arm_compute 166 #endif /* ARM_COMPUTE_TEST_SCHARR_FIXTURE */ 167