Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 1 | // |
Teresa Charlin | ad1b3d7 | 2023-03-14 12:10:28 +0000 | [diff] [blame] | 2 | // Copyright © 2021, 2023 Arm Ltd and Contributors. All rights reserved. |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 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> |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 14 | |
| 15 | #include <doctest/doctest.h> |
| 16 | |
| 17 | namespace armnnDelegate |
| 18 | { |
| 19 | |
| 20 | // Conv3d is currently only supports Float32 inputs, filter, bias and outputs in TFLite. |
| 21 | // Conv3d is only correctly supported for external delegates from TF Lite v2.6, as there was a breaking bug in v2.5. |
| 22 | #if defined(ARMNN_POST_TFLITE_2_5) |
| 23 | |
| 24 | // Create a vector from 0 to size divided to create smaller floating point values. |
| 25 | template <typename T> |
| 26 | std::vector<T> CreateFloatData(int32_t size, float divisor) |
| 27 | { |
| 28 | std::vector<float> data; |
| 29 | for (int32_t i = 0; i < size; ++i) |
| 30 | { |
| 31 | float value = static_cast<float>(i); |
| 32 | data.push_back(value/divisor); |
| 33 | } |
| 34 | return data; |
| 35 | } |
| 36 | |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 37 | void Conv3DWithBiasesSimpleWithPaddingFp32Test() |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 38 | { |
| 39 | // Set input data |
| 40 | std::vector<int32_t> inputShape { 1, 2, 2, 2, 1 }; |
| 41 | std::vector<int32_t> filterShape { 2, 2, 2, 1, 1 }; |
| 42 | std::vector<int32_t> biasShape { 1 }; |
| 43 | std::vector<int32_t> outputShape { 1, 2, 2, 2, 1 }; |
| 44 | |
| 45 | static std::vector<float> inputValues = |
| 46 | { |
| 47 | 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f |
| 48 | }; |
| 49 | |
| 50 | std::vector<float> filterValues = |
| 51 | { |
| 52 | 2.f,1.f, 1.f,0.f, 0.f,1.f, 1.f,1.f |
| 53 | }; |
| 54 | |
| 55 | std::vector<float> biasValues = { 5.f }; |
| 56 | |
| 57 | std::vector<float> expectedOutputValues = |
| 58 | { |
| 59 | 33.f, 21.f, 23.f, 13.f, 28.f, 25.f, 27.f, 21.f |
| 60 | }; |
| 61 | |
| 62 | Convolution3dTest<float>(tflite::BuiltinOperator_CONV_3D, |
| 63 | ::tflite::TensorType_FLOAT32, |
| 64 | { 1, 1, 1 }, // strideX, strideY, strideZ |
| 65 | { 1, 1, 1 }, // dilationX, dilationY, dilationZ |
| 66 | tflite::Padding_SAME, |
| 67 | tflite::ActivationFunctionType_NONE, |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 68 | inputShape, |
| 69 | filterShape, |
| 70 | outputShape, |
| 71 | inputValues, |
| 72 | filterValues, |
| 73 | expectedOutputValues, |
| 74 | biasShape, |
| 75 | biasValues); |
| 76 | } |
| 77 | |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 78 | void Conv3DWithBiasesStridesFp32Test() |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 79 | { |
| 80 | std::vector<int32_t> inputShape { 1, 3, 10, 10, 1 }; |
| 81 | std::vector<int32_t> filterShape { 3, 5, 5, 1, 1 }; |
| 82 | std::vector<int32_t> biasShape { 1 }; |
| 83 | std::vector<int32_t> outputShape { 1, 1, 3, 3, 1 }; |
| 84 | |
| 85 | std::vector<float> inputValues = CreateFloatData<float>(300, 1.0f); |
| 86 | |
| 87 | std::vector<float> filterValues = |
| 88 | { |
| 89 | 1.f, 1.f, 1.f, 1.f, 1.f, |
| 90 | 1.f, 1.f, 1.f, 1.f, 1.f, |
| 91 | 1.f, 1.f, 1.f, 1.f, 1.f, |
| 92 | 1.f, 1.f, 1.f, 1.f, 1.f, |
| 93 | 1.f, 1.f, 1.f, 1.f, 1.f, |
| 94 | |
| 95 | 0.f, 0.f, 0.f, 0.f, 0.f, |
| 96 | 0.f, 0.f, 0.f, 0.f, 0.f, |
| 97 | 0.f, 0.f, 0.f, 0.f, 0.f, |
| 98 | 0.f, 0.f, 0.f, 0.f, 0.f, |
| 99 | 0.f, 0.f, 0.f, 0.f, 0.f, |
| 100 | |
| 101 | 2.f, 2.f, 2.f, 2.f, 2.f, |
| 102 | 2.f, 2.f, 2.f, 2.f, 2.f, |
| 103 | 2.f, 2.f, 2.f, 2.f, 2.f, |
| 104 | 2.f, 2.f, 2.f, 2.f, 2.f, |
| 105 | 2.f, 2.f, 2.f, 2.f, 2.f |
| 106 | }; |
| 107 | |
| 108 | std::vector<float> biasValues = { 10.f }; |
| 109 | |
| 110 | std::vector<float> expectedOutputValues = |
| 111 | { |
| 112 | 11660.f, 11810.f, 11960.f, |
| 113 | |
| 114 | 13160.f, 13310.f, 13460.f, |
| 115 | |
| 116 | 14660.f, 14810.f, 14960.f |
| 117 | }; |
| 118 | |
| 119 | Convolution3dTest<float>(tflite::BuiltinOperator_CONV_3D, |
| 120 | ::tflite::TensorType_FLOAT32, |
| 121 | { 2, 2, 2 }, // strideX, strideY, strideZ |
| 122 | { 1, 1, 1 }, // dilationX, dilationY, dilationZ |
| 123 | tflite::Padding_VALID, |
| 124 | tflite::ActivationFunctionType_NONE, |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 125 | inputShape, |
| 126 | filterShape, |
| 127 | outputShape, |
| 128 | inputValues, |
| 129 | filterValues, |
| 130 | expectedOutputValues, |
| 131 | biasShape, |
| 132 | biasValues); |
| 133 | } |
| 134 | |
| 135 | |
| 136 | void Conv3DWithBiasesDilationFp32Test(std::vector<armnn::BackendId>& backends) |
| 137 | { |
| 138 | std::vector<int32_t> inputShape { 1, 5, 5, 5, 2 }; |
| 139 | std::vector<int32_t> filterShape { 2, 2, 2, 2, 2 }; |
| 140 | std::vector<int32_t> biasShape { 2 }; |
| 141 | std::vector<int32_t> outputShape { 1, 2, 2, 2, 2 }; |
| 142 | |
| 143 | std::vector<float> inputValues = CreateFloatData<float>(250, 1.0f); |
| 144 | |
| 145 | std::vector<float> filterValues = |
| 146 | { |
| 147 | -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, 1.f, 1.f, 1.f, -1.f, -1.f, |
| 148 | 1.f, 1.f, -1.f, 1.f, -1.f, 1.f, -1.f, 1.f, -1.f, -1.f, -1.f, 1.f, -1.f, 1.f, -1.f, 1.f, |
| 149 | }; |
| 150 | |
| 151 | std::vector<float> biasValues = { 0.f, 2.f }; |
| 152 | |
| 153 | // Since the dilation rate is 3 this will dilate the kernel to be 4x4, |
| 154 | // therefore the output will be 2x2 |
| 155 | std::vector<float> expectedOutputValues = |
| 156 | { |
| 157 | -1124.f, 976.f, |
| 158 | -1148.f, 980.f, |
| 159 | |
| 160 | -1244.f, 996.f, |
| 161 | -1268.f, 1000.f, |
| 162 | |
| 163 | -1724.f, 1076.f, |
| 164 | -1748.f, 1080.f, |
| 165 | |
| 166 | -1844.f, 1096.f, |
| 167 | -1868.f, 1100.f |
| 168 | }; |
| 169 | |
| 170 | Convolution3dTest<float>(tflite::BuiltinOperator_CONV_3D, |
| 171 | ::tflite::TensorType_FLOAT32, |
| 172 | { 1, 1, 1 }, // strideX, strideY, strideZ |
| 173 | { 3, 3, 3 }, // dilationX, dilationY, dilationZ |
| 174 | tflite::Padding_VALID, |
| 175 | tflite::ActivationFunctionType_NONE, |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 176 | inputShape, |
| 177 | filterShape, |
| 178 | outputShape, |
| 179 | inputValues, |
| 180 | filterValues, |
| 181 | expectedOutputValues, |
| 182 | biasShape, |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 183 | biasValues, |
| 184 | {1.0f}, |
| 185 | {0}, |
| 186 | {1.0f}, |
| 187 | {0}, |
| 188 | 2.0f, |
| 189 | 0, |
| 190 | 1.0f, |
| 191 | 0, |
| 192 | 1, |
| 193 | 3, |
| 194 | backends); |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 195 | } |
| 196 | |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 197 | void Conv3DFp32SmallTest() |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 198 | { |
| 199 | std::vector<int32_t> inputShape { 1, 3, 10, 10, 1 }; |
| 200 | std::vector<int32_t> filterShape { 3, 3, 3, 1, 1 }; |
| 201 | std::vector<int32_t> biasShape { 1 }; |
| 202 | std::vector<int32_t> outputShape { 1, 1, 4, 4, 1 }; |
| 203 | |
| 204 | std::vector<float> inputValues = CreateFloatData<float>(300, 100.0f); |
| 205 | |
| 206 | std::vector<float> filterValues = |
| 207 | { |
| 208 | 0.125977f, 0.150391f, 0.101562f, |
| 209 | 0.0585938f, 0.0864258f, 0.043457f, |
| 210 | 0.034668f, 0.0322266f, 0.0385742f, |
| 211 | |
| 212 | 0.125977f, 0.150391f, -0.101562f, |
| 213 | -0.0585938f,-0.0864258f,-0.043457f, |
| 214 | -0.0104630f, 0.0154114f, 0.0013768f, |
| 215 | |
| 216 | 0.0344238f, 0.035644f, 0.0495605f, |
| 217 | 0.0683594f, 0.099121f, -0.0461426f, |
| 218 | -0.0996094f,-0.126953f, -0.043457f, |
| 219 | }; |
| 220 | |
| 221 | std::vector<float> biasValues = { 0 }; |
| 222 | |
| 223 | std::vector<float> expectedOutputValues = |
| 224 | { |
| 225 | -0.08156067f, -0.06891209f, -0.05589598f, -0.04310101f, |
| 226 | 0.04584253f, 0.05855697f, 0.07129729f, 0.08325434f, |
| 227 | 0.17304349f, 0.18521416f, 0.19818866f, 0.21096253f, |
| 228 | 0.29965734f, 0.312698f, 0.32547557f, 0.33818722f |
| 229 | }; |
| 230 | |
| 231 | Convolution3dTest<float>(tflite::BuiltinOperator_CONV_3D, |
| 232 | ::tflite::TensorType_FLOAT32, |
| 233 | { 2, 2, 2 }, // strideX, strideY, strideZ |
| 234 | { 1, 1, 1 }, // dilationX, dilationY, dilationZ |
| 235 | tflite::Padding_VALID, |
| 236 | tflite::ActivationFunctionType_NONE, |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 237 | inputShape, |
| 238 | filterShape, |
| 239 | outputShape, |
| 240 | inputValues, |
| 241 | filterValues, |
| 242 | expectedOutputValues, |
| 243 | biasShape, |
| 244 | biasValues); |
| 245 | } |
| 246 | |
| 247 | TEST_SUITE("Convolution3dTest_CpuRefTests") |
| 248 | { |
| 249 | |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 250 | TEST_CASE ("Conv3DWithBiasesSimpleWithPadding_Fp32_Test") |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 251 | { |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 252 | Conv3DWithBiasesSimpleWithPaddingFp32Test(); |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 253 | } |
| 254 | |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 255 | TEST_CASE ("Conv3DWithBiasesStrides_Fp32_Test") |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 256 | { |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 257 | Conv3DWithBiasesStridesFp32Test(); |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 258 | } |
| 259 | |
| 260 | TEST_CASE ("Conv3DWithBiasesDilation_Fp32_CpuRef_Test") |
| 261 | { |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 262 | // Known to only work on CpuRef. |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 263 | std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef}; |
| 264 | Conv3DWithBiasesDilationFp32Test(backends); |
| 265 | } |
| 266 | |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 267 | TEST_CASE ("Conv3DFp32Small_Fp32_Test") |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 268 | { |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 269 | Conv3DFp32SmallTest(); |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 270 | } |
| 271 | |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 272 | } //End of TEST_SUITE("Convolution3dTest_Tests") |
Matthew Sloyan | 7afc92c | 2021-11-04 16:52:34 +0000 | [diff] [blame] | 273 | |
Matthew Sloyan | 81ec994 | 2021-10-12 10:26:30 +0100 | [diff] [blame] | 274 | #endif |
| 275 | |
| 276 | } // namespace armnnDelegate |