1 /* 2 * Copyright (c) 2019-2022 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_FFT_FIXTURE 25 #define ARM_COMPUTE_TEST_FFT_FIXTURE 26 27 #include "arm_compute/core/Types.h" 28 #include "arm_compute/runtime/FunctionDescriptors.h" 29 #include "tests/AssetsLibrary.h" 30 #include "tests/Globals.h" 31 #include "tests/IAccessor.h" 32 #include "tests/framework/Asserts.h" 33 #include "tests/framework/Fixture.h" 34 #include "tests/validation/reference/ActivationLayer.h" 35 #include "tests/validation/reference/ConvolutionLayer.h" 36 #include "tests/validation/reference/DFT.h" 37 38 #include <random> 39 40 namespace arm_compute 41 { 42 namespace test 43 { 44 namespace validation 45 { 46 template <typename TensorType, typename AccessorType, typename FunctionType, typename InfoType, typename T> 47 class FFTValidationFixture : public framework::Fixture 48 { 49 public: 50 template <typename...> setup(TensorShape shape,DataType data_type)51 void setup(TensorShape shape, DataType data_type) 52 { 53 _target = compute_target(shape, data_type); 54 _reference = compute_reference(shape, data_type); 55 ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(_target.info()->tensor_shape(), _reference.shape()); 56 } 57 58 protected: 59 template <typename U> fill(U && tensor)60 void fill(U &&tensor) 61 { 62 switch(tensor.data_type()) 63 { 64 case DataType::F16: 65 { 66 arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -5.0f, 5.0f }; 67 library->fill(tensor, distribution, 0); 68 break; 69 } 70 case DataType::F32: 71 { 72 std::uniform_real_distribution<float> distribution(-5.0f, 5.0f); 73 library->fill(tensor, distribution, 0); 74 break; 75 } 76 default: 77 library->fill_tensor_uniform(tensor, 0); 78 } 79 } 80 compute_target(const TensorShape & shape,DataType data_type)81 TensorType compute_target(const TensorShape &shape, DataType data_type) 82 { 83 // Create tensors 84 TensorType src = create_tensor<TensorType>(shape, data_type, 2); 85 TensorType dst = create_tensor<TensorType>(shape, data_type, 2); 86 87 // Create and configure function 88 FunctionType fft; 89 fft.configure(&src, &dst, InfoType()); 90 91 ARM_COMPUTE_ASSERT(src.info()->is_resizable()); 92 ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); 93 94 add_padding_x({ &src, &dst }); 95 96 // Allocate tensors 97 src.allocator()->allocate(); 98 dst.allocator()->allocate(); 99 100 ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); 101 ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); 102 103 // Fill tensors 104 fill(AccessorType(src)); 105 106 // Compute function 107 fft.run(); 108 109 return dst; 110 } 111 compute_reference(const TensorShape & shape,DataType data_type)112 SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type) 113 { 114 // Create reference 115 SimpleTensor<T> src{ shape, data_type, 2 }; 116 117 // Fill reference 118 fill(src); 119 if(std::is_same<InfoType, FFT1DInfo>::value) 120 { 121 return reference::dft_1d(src, reference::FFTDirection::Forward); 122 } 123 else 124 { 125 return reference::dft_2d(src, reference::FFTDirection::Forward); 126 } 127 } 128 129 TensorType _target{}; 130 SimpleTensor<T> _reference{}; 131 }; 132 133 template <typename TensorType, typename AccessorType, typename FunctionType, typename T> 134 class FFTConvolutionValidationGenericFixture : public framework::Fixture 135 { 136 public: 137 template <typename...> 138 void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, 139 DataType data_type, DataLayout data_layout, ActivationLayerInfo act_info, bool mixed_layout = false) 140 { 141 _mixed_layout = mixed_layout; 142 _data_type = data_type; 143 _data_layout = data_layout; 144 145 _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info); 146 _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info); 147 } 148 149 protected: mix_layout(FunctionType & layer,TensorType & src,TensorType & dst)150 void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) 151 { 152 // Test Multi DataLayout graph cases, when the data layout changes after configure 153 src.info()->set_data_layout(_data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); 154 dst.info()->set_data_layout(_data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); 155 156 // Compute Convolution function 157 layer.run(); 158 159 // Reinstating original data layout for the test suite to properly check the values 160 src.info()->set_data_layout(_data_layout); 161 dst.info()->set_data_layout(_data_layout); 162 } 163 164 template <typename U> fill(U && tensor,int i)165 void fill(U &&tensor, int i) 166 { 167 switch(tensor.data_type()) 168 { 169 case DataType::F16: 170 { 171 arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -1.0f, 1.0f }; 172 library->fill(tensor, distribution, i); 173 break; 174 } 175 case DataType::F32: 176 { 177 std::uniform_real_distribution<float> distribution(-1.0f, 1.0f); 178 library->fill(tensor, distribution, i); 179 break; 180 } 181 default: 182 library->fill_tensor_uniform(tensor, i); 183 } 184 } 185 compute_target(TensorShape input_shape,TensorShape weights_shape,const TensorShape & bias_shape,TensorShape output_shape,const PadStrideInfo & info,const Size2D & dilation,const ActivationLayerInfo act_info)186 TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, const TensorShape &bias_shape, TensorShape output_shape, const PadStrideInfo &info, 187 const Size2D &dilation, const ActivationLayerInfo act_info) 188 { 189 ARM_COMPUTE_UNUSED(dilation); 190 ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0); 191 192 if(_data_layout == DataLayout::NHWC) 193 { 194 permute(input_shape, PermutationVector(2U, 0U, 1U)); 195 permute(weights_shape, PermutationVector(2U, 0U, 1U)); 196 permute(output_shape, PermutationVector(2U, 0U, 1U)); 197 } 198 199 // Create tensors 200 TensorType src = create_tensor<TensorType>(input_shape, _data_type, 1, QuantizationInfo(), _data_layout); 201 TensorType weights = create_tensor<TensorType>(weights_shape, _data_type, 1, QuantizationInfo(), _data_layout); 202 TensorType bias = create_tensor<TensorType>(bias_shape, _data_type, 1, QuantizationInfo(), _data_layout); 203 TensorType dst = create_tensor<TensorType>(output_shape, _data_type, 1, QuantizationInfo(), _data_layout); 204 205 add_padding_x({ &src, &weights, &bias, &dst }, _data_layout); 206 207 // Create and configure function 208 FunctionType conv; 209 conv.configure(&src, &weights, &bias, &dst, info, act_info, _data_type == DataType::F16); 210 211 ARM_COMPUTE_ASSERT(src.info()->is_resizable()); 212 ARM_COMPUTE_ASSERT(weights.info()->is_resizable()); 213 ARM_COMPUTE_ASSERT(bias.info()->is_resizable()); 214 ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); 215 216 // Allocate tensors 217 src.allocator()->allocate(); 218 weights.allocator()->allocate(); 219 bias.allocator()->allocate(); 220 dst.allocator()->allocate(); 221 222 ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); 223 ARM_COMPUTE_ASSERT(!weights.info()->is_resizable()); 224 ARM_COMPUTE_ASSERT(!bias.info()->is_resizable()); 225 ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); 226 227 // Fill tensors 228 fill(AccessorType(src), 0); 229 fill(AccessorType(weights), 1); 230 fill(AccessorType(bias), 2); 231 232 if(_mixed_layout) 233 { 234 mix_layout(conv, src, dst); 235 } 236 else 237 { 238 // Compute Convolution function 239 conv.run(); 240 } 241 return dst; 242 } 243 compute_reference(const TensorShape & input_shape,const TensorShape & weights_shape,const TensorShape & bias_shape,const TensorShape & output_shape,const PadStrideInfo & info,const Size2D & dilation,const ActivationLayerInfo act_info)244 SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, 245 const Size2D &dilation, const ActivationLayerInfo act_info) 246 { 247 ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0); 248 249 // Create reference 250 SimpleTensor<T> src{ input_shape, _data_type, 1 }; 251 SimpleTensor<T> weights{ weights_shape, _data_type, 1 }; 252 SimpleTensor<T> bias{ bias_shape, _data_type, 1 }; 253 254 // Fill reference 255 fill(src, 0); 256 fill(weights, 1); 257 fill(bias, 2); 258 259 return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation), act_info) : reference::convolution_layer<T>(src, 260 weights, bias, output_shape, info, dilation); 261 } 262 263 TensorType _target{}; 264 SimpleTensor<T> _reference{}; 265 DataType _data_type{}; 266 DataLayout _data_layout{}; 267 bool _mixed_layout{ false }; 268 }; 269 270 template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> 271 class FFTConvolutionValidationFixture : public FFTConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T> 272 { 273 public: 274 template <typename...> setup(TensorShape input_shape,TensorShape weights_shape,TensorShape bias_shape,TensorShape output_shape,PadStrideInfo info,Size2D dilation,DataType data_type,DataLayout data_layout,ActivationLayerInfo act_info)275 void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, 276 DataType data_type, DataLayout data_layout, ActivationLayerInfo act_info) 277 { 278 FFTConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, 279 data_type, data_layout, act_info, mixed_layout); 280 } 281 }; 282 } // namespace validation 283 } // namespace test 284 } // namespace arm_compute 285 #endif /* ARM_COMPUTE_TEST_FFT_FIXTURE */ 286