1 /* 2 * Copyright (c) 2017-2018 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 #include "arm_compute/core/TensorShape.h" 25 #include "arm_compute/core/Types.h" 26 #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" 27 #include "tests/AssetsLibrary.h" 28 #include "tests/Globals.h" 29 #include "tests/IAccessor.h" 30 #include "tests/framework/Asserts.h" 31 #include "tests/framework/Fixture.h" 32 #include "tests/validation/Helpers.h" 33 #include "tests/validation/fixtures/ConvolutionLayerFixture.h" 34 #include "tests/validation/reference/ConvolutionLayer.h" 35 36 #include <random> 37 38 namespace arm_compute 39 { 40 namespace test 41 { 42 namespace validation 43 { 44 template <typename TensorType, typename AccessorType, typename FunctionType, typename T> 45 class DirectConvolutionValidationGenericTensorShiftFixture : public framework::Fixture 46 { 47 public: 48 using TBias = typename std::conditional<std::is_same<typename std::decay<T>::type, uint8_t>::value, int32_t, T>::type; 49 50 public: 51 template <typename...> setup(TensorShape input_shape,int stride_x,int stride_y,int pad_x,int pad_y,unsigned int kernel_size,unsigned int num_kernels,DataType data_type,QuantizationInfo quantization_info)52 void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, 53 DataType data_type, QuantizationInfo quantization_info) 54 { 55 _quantization_info = quantization_info; 56 _data_type = data_type; 57 58 const TensorShape weights_shape(kernel_size, kernel_size, input_shape.z(), num_kernels); 59 const TensorShape bias_shape(num_kernels); 60 const PadStrideInfo info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR); 61 const TensorShape output_shape = get_output_shape(input_shape, weights_shape, info); 62 const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; 63 64 _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info); 65 _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info); 66 } 67 68 template <typename...> setup(TensorShape input_shape,TensorShape weights_shape,TensorShape bias_shape,TensorShape output_shape,PadStrideInfo info,unsigned int dilation_x,unsigned int dilation_y,DataType data_type,QuantizationInfo quantization_info)69 void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y, 70 DataType data_type, QuantizationInfo quantization_info) 71 { 72 ARM_COMPUTE_UNUSED(dilation_x, dilation_y); 73 74 _quantization_info = quantization_info; 75 _data_type = data_type; 76 77 const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; 78 79 _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info); 80 _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, quantization_info); 81 } 82 83 protected: 84 template <typename U> fill(U && tensor,int i)85 void fill(U &&tensor, int i) 86 { 87 switch(tensor.data_type()) 88 { 89 case DataType::QASYMM8: 90 { 91 std::uniform_int_distribution<uint8_t> distribution(0, 50); 92 library->fill(tensor, distribution, i); 93 break; 94 } 95 case DataType::F16: 96 case DataType::F32: 97 { 98 std::uniform_real_distribution<> distribution(-1.0f, 1.0f); 99 library->fill(tensor, distribution, i); 100 break; 101 } 102 case DataType::S32: 103 { 104 std::uniform_int_distribution<int32_t> distribution(-5, 5); 105 library->fill(tensor, distribution, i); 106 break; 107 } 108 default: 109 library->fill_tensor_uniform(tensor, i); 110 } 111 } 112 compute_target(const TensorShape & input_shape,const TensorShape & weights_shape,const TensorShape & bias_shape,const TensorShape & output_shape,const PadStrideInfo & info,DataType data_type,DataType bias_data_type,QuantizationInfo quantization_info)113 TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, 114 DataType data_type, DataType bias_data_type, QuantizationInfo quantization_info) 115 { 116 // Create tensors 117 TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, quantization_info); 118 TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, quantization_info); 119 TensorType bias = create_tensor<TensorType>(bias_shape, bias_data_type, 1, quantization_info); 120 TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, quantization_info); 121 122 TensorShape output_shape1 = get_output_shape(output_shape, weights_shape, info); 123 TensorType dst1 = create_tensor<TensorType>(output_shape1, data_type, 1, quantization_info); 124 125 // Create and configure function 126 FunctionType conv; 127 conv.configure(&src, &weights, &bias, &dst, info); 128 FunctionType conv1; 129 conv1.configure(&dst, &weights, &bias, &dst1, info); 130 131 ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); 132 ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); 133 ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); 134 ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); 135 ARM_COMPUTE_EXPECT(dst1.info()->is_resizable(), framework::LogLevel::ERRORS); 136 137 // Allocate tensors 138 src.allocator()->allocate(); 139 weights.allocator()->allocate(); 140 bias.allocator()->allocate(); 141 dst.allocator()->allocate(); 142 dst1.allocator()->allocate(); 143 144 ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); 145 ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS); 146 ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS); 147 ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); 148 ARM_COMPUTE_EXPECT(!dst1.info()->is_resizable(), framework::LogLevel::ERRORS); 149 150 // Fill tensors 151 fill(AccessorType(src), 0); 152 fill(AccessorType(weights), 1); 153 fill(AccessorType(bias), 2); 154 155 // Compute NEConvolutionLayer function 156 GCScheduler::get().memory_barrier(); 157 conv.run(); 158 GCScheduler::get().memory_barrier(); 159 conv1.run(); 160 161 return dst1; 162 } 163 compute_reference(const TensorShape & input_shape,const TensorShape & weights_shape,const TensorShape & bias_shape,const TensorShape & output_shape,const PadStrideInfo & info,DataType data_type,DataType bias_data_type,QuantizationInfo quantization_info)164 SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, 165 DataType data_type, DataType bias_data_type, QuantizationInfo quantization_info) 166 { 167 // Create reference 168 SimpleTensor<T> src{ input_shape, data_type, 1, quantization_info }; 169 SimpleTensor<T> weights{ weights_shape, data_type, 1, quantization_info }; 170 SimpleTensor<TBias> bias{ bias_shape, bias_data_type, 1, quantization_info }; 171 172 SimpleTensor<T> dst{ output_shape, data_type, 1, quantization_info }; 173 TensorShape output_shape1 = get_output_shape(output_shape, weights_shape, info); 174 175 // Fill reference 176 fill(src, 0); 177 fill(weights, 1); 178 fill(bias, 2); 179 180 dst = reference::convolution_layer<T>(src, weights, bias, output_shape, info); 181 return reference::convolution_layer<T>(dst, weights, bias, output_shape1, info); 182 } 183 184 TensorType _target{}; 185 SimpleTensor<T> _reference{}; 186 QuantizationInfo _quantization_info{}; 187 DataType _data_type{}; 188 189 private: get_output_shape(TensorShape in_shape,TensorShape kernel_shape,const PadStrideInfo & info)190 TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info) 191 { 192 TensorShape out_shape(in_shape); 193 const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(), 194 in_shape.y(), 195 kernel_shape.x(), 196 kernel_shape.y(), 197 info); 198 out_shape.set(0, scaled_dims.first); 199 out_shape.set(1, scaled_dims.second); 200 out_shape.set(2, kernel_shape[3]); 201 return out_shape; 202 } 203 }; 204 205 template <typename TensorType, typename AccessorType, typename FunctionType, typename T> 206 class DirectConvolutionValidationTensorShiftFixture : public DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T> 207 { 208 public: 209 template <typename...> setup(TensorShape input_shape,int stride_x,int stride_y,int pad_x,int pad_y,unsigned int kernel_size,unsigned int num_kernels,DataType data_type)210 void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type) 211 { 212 DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 213 QuantizationInfo()); 214 } 215 }; 216 217 template <typename TensorType, typename AccessorType, typename FunctionType, typename T> 218 class DirectConvolutionValidationQuantizedTensorShiftFixture : public DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T> 219 { 220 public: 221 template <typename...> setup(TensorShape input_shape,int stride_x,int stride_y,int pad_x,int pad_y,unsigned int kernel_size,unsigned int num_kernels,DataType data_type,QuantizationInfo quantization_info)222 void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, QuantizationInfo quantization_info) 223 { 224 DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 225 quantization_info); 226 } 227 }; 228 229 template <typename TensorType, typename AccessorType, typename FunctionType, typename T> 230 class DirectConvolutionValidationWithTensorShapesQuantizedTensorShiftFixture : public DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T> 231 { 232 public: 233 template <typename...> setup(TensorShape input_shape,TensorShape weights_shape,TensorShape bias_shape,TensorShape output_shape,PadStrideInfo info,unsigned int dilation_x,unsigned int dilation_y,DataType data_type,QuantizationInfo quantization_info)234 void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y, 235 DataType data_type, QuantizationInfo quantization_info) 236 { 237 DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation_x, dilation_y, data_type, 238 quantization_info); 239 } 240 }; 241 242 template <typename TensorType, typename AccessorType, typename FunctionType, typename T> 243 class DirectConvolutionValidationWithTensorShapesTensorShiftFixture : public DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T> 244 { 245 public: 246 template <typename...> setup(TensorShape input_shape,TensorShape weights_shape,TensorShape bias_shape,TensorShape output_shape,PadStrideInfo info,unsigned int dilation_x,unsigned int dilation_y,DataType data_type)247 void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, unsigned int dilation_x, unsigned int dilation_y, 248 DataType data_type) 249 { 250 DirectConvolutionValidationGenericTensorShiftFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation_x, dilation_y, data_type, 251 QuantizationInfo()); 252 } 253 }; 254 255 } // namespace validation 256 } // namespace test 257 } // namespace arm_compute 258