Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2020 Arm Ltd and Contributors. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #include "ConvolutionTestHelper.hpp" |
| 7 | |
| 8 | #include <armnn_delegate.hpp> |
| 9 | |
| 10 | #include <flatbuffers/flatbuffers.h> |
| 11 | #include <tensorflow/lite/interpreter.h> |
| 12 | #include <tensorflow/lite/kernels/register.h> |
| 13 | #include <tensorflow/lite/model.h> |
| 14 | #include <tensorflow/lite/schema/schema_generated.h> |
| 15 | #include <tensorflow/lite/version.h> |
| 16 | |
| 17 | #include <doctest/doctest.h> |
| 18 | |
| 19 | namespace armnnDelegate |
| 20 | { |
| 21 | |
| 22 | void Conv2DWithBiasesFp32Test(std::vector<armnn::BackendId>& backends) |
| 23 | { |
| 24 | // Set input data |
| 25 | std::vector<int32_t> inputShape { 1, 5, 5, 1 }; |
| 26 | std::vector<int32_t> filterShape { 1, 3, 3, 1 }; |
| 27 | std::vector<int32_t> biasShape { 1 }; |
| 28 | std::vector<int32_t> outputShape { 1, 3, 3, 1 }; |
| 29 | |
| 30 | static std::vector<float> inputValues = |
| 31 | { |
| 32 | 1, 5, 2, 3, 5, |
| 33 | 8, 7, 3, 6, 3, |
| 34 | 3, 3, 9, 1, 9, |
| 35 | 4, 1, 8, 1, 3, |
| 36 | 6, 8, 1, 9, 2 |
| 37 | }; |
| 38 | |
| 39 | std::vector<float> filterValues = |
| 40 | { |
| 41 | 4, 5, 6, |
| 42 | 0, 0, 0, |
| 43 | 3, 2, 1 |
| 44 | }; |
| 45 | |
| 46 | std::vector<float> biasValues = { 0 }; |
| 47 | |
| 48 | std::vector<float> expectedOutputValues = |
| 49 | { |
| 50 | 23, 33, 24, |
| 51 | 91, 99, 48, |
| 52 | 26, 50, 19 |
| 53 | }; |
| 54 | |
| 55 | tflite::Padding padding = tflite::Padding_SAME; |
| 56 | |
| 57 | ConvolutionTest<float>(tflite::BuiltinOperator_CONV_2D, |
| 58 | ::tflite::TensorType_FLOAT32, |
| 59 | 2, // strideX |
| 60 | 2, // strideY |
| 61 | 1, // dilationX |
| 62 | 1, // dilationY |
| 63 | padding, |
| 64 | tflite::ActivationFunctionType_NONE, |
| 65 | backends, |
| 66 | inputShape, |
| 67 | filterShape, |
| 68 | outputShape, |
| 69 | inputValues, |
| 70 | filterValues, |
| 71 | expectedOutputValues, |
| 72 | biasShape, |
| 73 | biasValues); |
| 74 | } |
| 75 | |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 76 | void Conv2DWithBiasesInt8Test(std::vector<armnn::BackendId>& backends) |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 77 | { |
| 78 | // Set input data |
| 79 | std::vector<int32_t> inputShape { 1, 2, 2, 1 }; |
| 80 | std::vector<int32_t> filterShape { 1, 2, 2, 1 }; |
| 81 | std::vector<int32_t> biasShape { 1 }; |
| 82 | std::vector<int32_t> outputShape { 1, 2, 2, 1 }; |
| 83 | |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 84 | static std::vector<int8_t> inputValues = { 1, 2, 3, 4 }; |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 85 | |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 86 | std::vector<int8_t> filterValues = { 2, 1, 0, 6 }; |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 87 | |
| 88 | std::vector<int32_t> biasValues = { 10 }; |
| 89 | |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 90 | std::vector<int8_t> expectedOutputValues = |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 91 | { |
| 92 | (1 * 2 + 2 * 1 + 3 * 0 + 4 * 6 + 10) / 2, // 19 |
| 93 | (2 * 2 + 0 * 1 + 4 * 0 + 0 * 6 + 10) / 2, // 7 |
| 94 | (3 * 2 + 4 * 1 + 0 * 0 + 0 * 6 + 10) / 2, // 10 |
| 95 | (4 * 2 + 0 * 1 + 0 * 0 + 0 * 6 + 10) / 2, // 9 |
| 96 | }; |
| 97 | |
| 98 | tflite::Padding padding = tflite::Padding_SAME; |
| 99 | |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 100 | ConvolutionTest<int8_t, int32_t>(tflite::BuiltinOperator_CONV_2D, |
| 101 | ::tflite::TensorType_INT8, |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 102 | 1, // strideX |
| 103 | 1, // strideY |
| 104 | 1, // dilationX |
| 105 | 1, // dilationY |
| 106 | padding, |
| 107 | tflite::ActivationFunctionType_NONE, |
| 108 | backends, |
| 109 | inputShape, |
| 110 | filterShape, |
| 111 | outputShape, |
| 112 | inputValues, |
| 113 | filterValues, |
| 114 | expectedOutputValues, |
| 115 | biasShape, |
| 116 | biasValues); |
| 117 | } |
| 118 | |
| 119 | void Conv2DWithBiasesReluUint8Test(std::vector<armnn::BackendId>& backends) |
| 120 | { |
| 121 | // Set input data |
| 122 | std::vector<int32_t> inputShape { 1, 2, 2, 1 }; |
| 123 | std::vector<int32_t> filterShape { 1, 2, 2, 1 }; |
| 124 | std::vector<int32_t> biasShape { 1 }; |
| 125 | std::vector<int32_t> outputShape { 1, 2, 2, 1 }; |
| 126 | |
| 127 | static std::vector<uint8_t> inputValues = { 1, 2, 4, 8 }; |
| 128 | |
| 129 | std::vector<uint8_t> filterValues = { 2, 1, 0, 6 }; |
| 130 | |
| 131 | std::vector<int32_t> biasValues = { 16 }; |
| 132 | |
| 133 | // factors to consider: |
| 134 | // - the filter zero point is non zero, hence the (x-fz) |
| 135 | // - the output scale is 2 hence the /2 |
| 136 | // - output zero point is non zero, hence the +outZero |
| 137 | // - RELU cuts negative values and then we add the output zero point |
| 138 | uint8_t bias = 16; |
| 139 | uint8_t outZero = 20; |
| 140 | uint8_t fz = 4; // filter zero point |
| 141 | |
| 142 | std::vector<uint8_t> expectedOutputValues = |
| 143 | { |
| 144 | std::max(outZero, static_cast<uint8_t>((1*(2-fz) + 2*(1-fz) + 4*(0-fz) + 8*(6-fz) + bias)/2 + outZero)), |
| 145 | std::max(outZero, static_cast<uint8_t>((2*(2-fz) + 0*(1-fz) + 8*(0-fz) + 0*(6-fz) + bias)/2 + outZero)), |
| 146 | std::max(outZero, static_cast<uint8_t>((4*(2-fz) + 8*(1-fz) + 0*(0-fz) + 0*(6-fz) + bias)/2 + outZero)), |
| 147 | std::max(outZero, static_cast<uint8_t>((8*(2-fz) + 0*(1-fz) + 0*(0-fz) + 0*(6-fz) + bias)/2 + outZero)) |
| 148 | }; |
| 149 | |
| 150 | tflite::Padding padding = tflite::Padding_SAME; |
| 151 | |
| 152 | ConvolutionTest<uint8_t, int32_t>(tflite::BuiltinOperator_CONV_2D, |
| 153 | ::tflite::TensorType_UINT8, |
| 154 | 1, // strideX |
| 155 | 1, // strideY |
| 156 | 1, // dilationX |
| 157 | 1, // dilationY |
| 158 | padding, |
| 159 | tflite::ActivationFunctionType_RELU, |
| 160 | backends, |
| 161 | inputShape, |
| 162 | filterShape, |
| 163 | outputShape, |
| 164 | inputValues, |
| 165 | filterValues, |
| 166 | expectedOutputValues, |
| 167 | biasShape, |
| 168 | biasValues, |
| 169 | 1, // filter scale |
| 170 | 4, // filter offset |
| 171 | 2, // output scale |
| 172 | 20); // output offset |
| 173 | } |
| 174 | |
| 175 | void Conv2DWithBiasesRelu6Uint8Test(std::vector<armnn::BackendId>& backends) |
| 176 | { |
| 177 | // Set input data |
| 178 | std::vector<int32_t> inputShape { 1, 2, 2, 1 }; |
| 179 | std::vector<int32_t> filterShape { 1, 2, 2, 1 }; |
| 180 | std::vector<int32_t> biasShape { 1 }; |
| 181 | std::vector<int32_t> outputShape { 1, 2, 2, 1 }; |
| 182 | |
| 183 | static std::vector<uint8_t> inputValues = { 1, 2, 4, 1 }; |
| 184 | |
| 185 | std::vector<uint8_t> filterValues = { 2, 1, 0, 6 }; |
| 186 | |
| 187 | std::vector<int32_t> biasValues = { 0 }; |
| 188 | |
| 189 | // factors to consider: |
| 190 | // - the output scale is 2 hence the /2 |
| 191 | // - RELU6 cuts output values at +6 |
| 192 | uint8_t relu6Min = 6 / 2; // divide by output scale |
| 193 | |
| 194 | std::vector<uint8_t> expectedOutputValues = |
| 195 | { |
| 196 | std::min(relu6Min, static_cast<uint8_t>((1 * 2 + 2 * 1 + 4 * 0 + 1 * 6) / 2)), |
| 197 | std::min(relu6Min, static_cast<uint8_t>((2 * 2 + 0 * 1 + 1 * 0 + 0 * 6) / 2)), |
| 198 | std::min(relu6Min, static_cast<uint8_t>((4 * 2 + 1 * 1 + 0 * 0 + 0 * 6) / 2)), |
| 199 | std::min(relu6Min, static_cast<uint8_t>((1 * 2 + 0 * 1 + 0 * 0 + 0 * 6) / 2)) |
| 200 | }; |
| 201 | |
| 202 | tflite::Padding padding = tflite::Padding_SAME; |
| 203 | |
| 204 | ConvolutionTest<uint8_t, int32_t>(tflite::BuiltinOperator_CONV_2D, |
| 205 | ::tflite::TensorType_UINT8, |
| 206 | 1, // strideX |
| 207 | 1, // strideY |
| 208 | 1, // dilationX |
| 209 | 1, // dilationY |
| 210 | padding, |
| 211 | tflite::ActivationFunctionType_RELU6, |
| 212 | backends, |
| 213 | inputShape, |
| 214 | filterShape, |
| 215 | outputShape, |
| 216 | inputValues, |
| 217 | filterValues, |
| 218 | expectedOutputValues, |
| 219 | biasShape, |
| 220 | biasValues); |
| 221 | } |
| 222 | |
Jan Eilers | 187b3a7 | 2020-11-19 17:50:34 +0000 | [diff] [blame] | 223 | TEST_SUITE("Convolution2dTest_CpuRefTests") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 224 | { |
| 225 | |
| 226 | TEST_CASE ("Conv2DWithBiases_Fp32_CpuRef_Test") |
| 227 | { |
| 228 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef}; |
| 229 | Conv2DWithBiasesFp32Test(backends); |
| 230 | } |
| 231 | |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 232 | TEST_CASE ("Conv2DWithBiases_Int8_CpuRef_Test") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 233 | { |
| 234 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef}; |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 235 | Conv2DWithBiasesInt8Test(backends); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 236 | } |
| 237 | |
| 238 | } //End of TEST_SUITE("Convolution2dTest_CpuRef") |
| 239 | |
Jan Eilers | 187b3a7 | 2020-11-19 17:50:34 +0000 | [diff] [blame] | 240 | TEST_SUITE("Convolution2dTest_CpuAccTests") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 241 | { |
| 242 | |
| 243 | TEST_CASE ("Conv2DWithBiases_Fp32_CpuAcc_Test") |
| 244 | { |
| 245 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuAcc}; |
| 246 | Conv2DWithBiasesFp32Test(backends); |
| 247 | } |
| 248 | |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 249 | TEST_CASE ("Conv2DWithBiases_Int8_CpuAcc_Test") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 250 | { |
| 251 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuAcc}; |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 252 | Conv2DWithBiasesInt8Test(backends); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 253 | } |
| 254 | |
| 255 | } //End of TEST_SUITE("Convolution2dTest_CpuAcc") |
| 256 | |
Jan Eilers | 187b3a7 | 2020-11-19 17:50:34 +0000 | [diff] [blame] | 257 | TEST_SUITE("Convolution2dTest_GpuAccTests") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 258 | { |
| 259 | |
| 260 | TEST_CASE ("Conv2DWithBiases_Fp32_GpuAcc_Test") |
| 261 | { |
| 262 | std::vector <armnn::BackendId> backends = {armnn::Compute::GpuAcc}; |
| 263 | Conv2DWithBiasesFp32Test(backends); |
| 264 | } |
| 265 | |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 266 | TEST_CASE ("Conv2DWithBiases_Int8_GpuAcc_Test") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 267 | { |
| 268 | std::vector <armnn::BackendId> backends = {armnn::Compute::GpuAcc}; |
Jan Eilers | eb61612 | 2020-11-20 11:59:40 +0000 | [diff] [blame] | 269 | Conv2DWithBiasesInt8Test(backends); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 270 | } |
| 271 | |
| 272 | } //End of TEST_SUITE("Convolution2dTest_GpuAcc") |
| 273 | |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 274 | void TransposeConvInt8Test(std::vector<armnn::BackendId>& backends) |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 275 | { |
| 276 | // Set input data |
| 277 | std::vector<int32_t> transposeTensorShape { 4 }; |
| 278 | std::vector<int32_t> filterShape { 1, 2, 2, 1 }; |
| 279 | std::vector<int32_t> inputShape { 1, 2, 2, 1 }; |
| 280 | std::vector<int32_t> outputShape { 1, 3, 3, 1 }; |
| 281 | |
| 282 | std::vector<int32_t> transposeData = { 1, 3, 3, 1 }; |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 283 | static std::vector<int8_t> inputValues = { 1, 2, 3, 4 }; |
| 284 | std::vector<int8_t> filterValues = { 0, 1, 2, 4 }; |
| 285 | std::vector<int8_t> expectedOutputValues = |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 286 | { |
| 287 | 0, 1, 2, |
| 288 | 2, 11, 12, |
| 289 | 6, 20, 16 |
| 290 | }; |
| 291 | |
| 292 | tflite::Padding padding = tflite::Padding_VALID; |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 293 | TransposeConvTest<int8_t>(backends, |
| 294 | ::tflite::TensorType_INT8, |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 295 | 1, // strideX |
| 296 | 1, // strideY |
| 297 | padding, |
| 298 | transposeTensorShape, |
| 299 | filterShape, |
| 300 | inputShape, |
| 301 | outputShape, |
| 302 | transposeData, |
| 303 | filterValues, |
| 304 | inputValues, |
| 305 | expectedOutputValues); |
| 306 | } |
| 307 | |
| 308 | void TransposeConvFp32Test(std::vector<armnn::BackendId>& backends) |
| 309 | { |
| 310 | std::vector<int32_t> transposeTensorShape { 4 }; |
| 311 | std::vector<int32_t> filterShape { 1, 2, 2, 1 }; |
| 312 | std::vector<int32_t> inputShape { 1, 2, 2, 1 }; |
| 313 | std::vector<int32_t> outputShape { 1, 3, 3, 1 }; |
| 314 | |
| 315 | std::vector<int32_t> transposeData = { 1, 3, 3, 1 }; |
| 316 | static std::vector<float> inputValues = { 1, 2, 3, 4 }; |
| 317 | std::vector<float> filterValues = { 0, 1, 2, 4 }; |
| 318 | std::vector<float> expectedOutputValues = |
| 319 | { |
| 320 | 0, 1, 2, |
| 321 | 2, 11, 12, |
| 322 | 6, 20, 16 |
| 323 | }; |
| 324 | |
| 325 | tflite::Padding padding = tflite::Padding_VALID; |
| 326 | TransposeConvTest<float>(backends, |
| 327 | ::tflite::TensorType_FLOAT32, |
| 328 | 1, // strideX |
| 329 | 1, // strideY |
| 330 | padding, |
| 331 | transposeTensorShape, |
| 332 | filterShape, |
| 333 | inputShape, |
| 334 | outputShape, |
| 335 | transposeData, |
| 336 | filterValues, |
| 337 | inputValues, |
| 338 | expectedOutputValues); |
| 339 | } |
| 340 | |
| 341 | TEST_SUITE("TransposeConv_CpuRef_Test") |
| 342 | { |
| 343 | |
| 344 | TEST_CASE ("TransposeConv_Fp32_Test") |
| 345 | { |
| 346 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef}; |
| 347 | TransposeConvFp32Test(backends); |
| 348 | } |
| 349 | |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 350 | TEST_CASE ("TransposeConv_Int8_Test") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 351 | { |
| 352 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef}; |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 353 | TransposeConvInt8Test(backends); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 354 | } |
| 355 | |
| 356 | } // End of TEST_SUITE(TransposeConv_CpuRef_Test) |
| 357 | |
| 358 | TEST_SUITE("TransposeConv_CpuAcc_Test") |
| 359 | { |
| 360 | |
| 361 | TEST_CASE ("TransposeConv_Fp32_Test") |
| 362 | { |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 363 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuAcc}; |
| 364 | TransposeConvFp32Test(backends); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 365 | } |
| 366 | |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 367 | TEST_CASE ("TransposeConv_Int8_Test") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 368 | { |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 369 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuAcc}; |
| 370 | TransposeConvInt8Test(backends); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 371 | } |
| 372 | |
| 373 | } // End of TEST_SUITE(TransposeConv_CpuAcc_Test) |
| 374 | |
| 375 | TEST_SUITE("TransposeConv_GpuAcc_Test") |
| 376 | { |
| 377 | |
| 378 | TEST_CASE ("TransposeConv_Fp32_Test") |
| 379 | { |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 380 | std::vector <armnn::BackendId> backends = {armnn::Compute::GpuAcc}; |
| 381 | TransposeConvFp32Test(backends); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 382 | } |
| 383 | |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 384 | TEST_CASE ("TransposeConv_Int8_Test") |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 385 | { |
David Monahan | 63e75dc | 2020-11-20 15:30:49 +0000 | [diff] [blame^] | 386 | std::vector <armnn::BackendId> backends = {armnn::Compute::GpuAcc}; |
| 387 | TransposeConvInt8Test(backends); |
Sadik Armagan | 32ca144 | 2020-11-13 17:51:56 +0000 | [diff] [blame] | 388 | } |
| 389 | |
| 390 | } // End of TEST_SUITE(TransposeConv_GpuAcc_Test) |
| 391 | |
| 392 | } // namespace armnnDelegate |