telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
David Beck | ecb56cd | 2018-09-05 12:52:57 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4 | // |
| 5 | #include "LayerTests.hpp" |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6 | #include "WorkloadTestUtils.hpp" |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 7 | #include "TensorUtils.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 8 | |
| 9 | #include "test/TensorHelpers.hpp" |
| 10 | #include "TensorCopyUtils.hpp" |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 11 | #include "Permute.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 12 | |
| 13 | #include <boost/test/unit_test.hpp> |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 14 | #include <boost/assert.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 15 | |
David Beck | 711fa31 | 2018-09-24 10:46:38 +0100 | [diff] [blame] | 16 | #include <armnn/LayerSupport.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 17 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 18 | #include <backendsCommon/CpuTensorHandle.hpp> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 19 | #include <backendsCommon/IBackendInternal.hpp> |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 20 | #include <backendsCommon/WorkloadFactory.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 21 | |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 22 | #include <reference/workloads/RefWorkloads.hpp> |
| 23 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 24 | #include <algorithm> |
| 25 | #include <boost/cast.hpp> |
| 26 | |
| 27 | #include "WorkloadTestUtils.hpp" |
| 28 | #include "Conv2dTestImpl.hpp" |
| 29 | #include "BatchNormTestImpl.hpp" |
| 30 | #include "ActivationTestImpl.hpp" |
| 31 | #include "Pooling2dTestImpl.hpp" |
| 32 | #include "ReshapeTestImpl.hpp" |
| 33 | #include "FullyConnectedTestImpl.hpp" |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 34 | #include "SpaceToBatchNdTestImpl.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 35 | #include "SplitterTestImpl.hpp" |
| 36 | #include "SoftmaxTestImpl.hpp" |
Nattapat Chaimanowong | 1216b58 | 2018-11-23 15:33:41 +0000 | [diff] [blame] | 37 | #include "StridedSliceTestImpl.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 38 | #include "NormTestImpl.hpp" |
| 39 | #include "PermuteTestImpl.hpp" |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 40 | #include "LstmTestImpl.hpp" |
| 41 | #include "ConvertFp16ToFp32TestImpl.hpp" |
| 42 | #include "ConvertFp32ToFp16TestImpl.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 43 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 44 | // 3-channel 16x8 image used as common input data for a number of Conv2d tests. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 45 | static std::vector<float> ConvInput3x8x16({ |
| 46 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 47 | 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, |
| 48 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 49 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 50 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 51 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 52 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 53 | 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, |
| 54 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 55 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 56 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 57 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 58 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 59 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 60 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 61 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 62 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 63 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 64 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 65 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 66 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 67 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 68 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 69 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 |
| 70 | }); |
| 71 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 72 | // 2-channel bias used by a number of Conv2d tests. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 73 | static std::vector<float> Bias2({0, 2}); |
| 74 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 75 | // Helper function that returns either Bias2 or an empty vector depending on whether bias is enabled. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 76 | template<typename T> |
| 77 | boost::multi_array<T, 1> GetBias2(bool biasEnabled, float qScale, int32_t qOffset) |
| 78 | { |
| 79 | if(biasEnabled) |
| 80 | { |
| 81 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(Bias2.size())}, armnn::GetDataType<T>()); |
| 82 | boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasDesc, QuantizedVector<T>(qScale, qOffset, Bias2)); |
| 83 | return bias; |
| 84 | } |
| 85 | else |
| 86 | { |
| 87 | return boost::multi_array<T, 1>(); |
| 88 | } |
| 89 | } |
| 90 | |
| 91 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 92 | LayerTestResult<T, 4> SimpleConvolution2d3x5TestCommon( |
| 93 | armnn::IWorkloadFactory& workloadFactory, |
| 94 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 95 | float qScale, |
| 96 | int32_t qOffset, |
| 97 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 98 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 99 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 100 | // Use common single-batch 3-channel 16x8 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 101 | armnn::TensorInfo inputDesc({1, 3, 8, 16}, armnn::GetDataType<T>()); |
| 102 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, QuantizedVector<T>(qScale, qOffset, ConvInput3x8x16)); |
| 103 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 104 | // Use a 2-element batch with 3-channel 3x5 kernels. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 105 | armnn::TensorInfo kernelDesc({2, 3, 5, 3}, armnn::GetDataType<T>()); |
| 106 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, std::vector<T>( |
| 107 | QuantizedVector<T>(qScale, qOffset, { |
| 108 | 1, 1, 1, |
| 109 | 1, -1, 1, |
| 110 | 1, 1, 1, |
| 111 | 1, 1, 1, |
| 112 | 1, 1, 1, |
| 113 | |
| 114 | 0, 0, 0, |
| 115 | 0, 0, 0, |
| 116 | 0, 0, 0, |
| 117 | 0, 0, 0, |
| 118 | 0, 0, 0, |
| 119 | |
| 120 | 2, 2, 2, |
| 121 | 2, 2, 2, |
| 122 | 2, 2, 2, |
| 123 | 2, 2, 2, |
| 124 | 2, 2, 2, |
| 125 | |
| 126 | |
| 127 | 0, 0, 0, |
| 128 | 0, 0, 0, |
| 129 | 0, 0, 0, |
| 130 | 0, 0, 0, |
| 131 | 0, 0, 0, |
| 132 | |
| 133 | 1, 1, 1, |
| 134 | 1, 1, 1, |
| 135 | 1, 1, 1, |
| 136 | 1, 1, 1, |
| 137 | 1, 1, 1, |
| 138 | |
| 139 | 0, 0, 0, |
| 140 | 0, 0, 0, |
| 141 | 0, 0, 0, |
| 142 | 0, 0, 0, |
| 143 | 0, 0, 0 |
| 144 | }))); |
| 145 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 146 | // Expected output is 2 batch elements of a 1-channel 14x4 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 147 | armnn::TensorInfo outputDesc({1, 2, 4, 14}, armnn::GetDataType<T>()); |
| 148 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, std::vector<T>( |
| 149 | QuantizedVector<T>(qScale, qOffset, { |
| 150 | -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, |
| 151 | -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, |
| 152 | -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, |
| 153 | -23.5f, -23.5f, -23.5f, |
| 154 | -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, |
| 155 | -23.5f, -23.5f, -23.5f, |
| 156 | |
| 157 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 158 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 159 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 160 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 161 | }))); |
| 162 | |
| 163 | return SimpleConvolution2dTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 164 | memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 165 | input, |
| 166 | kernel, |
| 167 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasEnabled, qScale, qOffset), |
| 168 | expectedOutput, |
| 169 | qScale, |
jimfly01 | 0a088a6 | 2018-10-25 17:05:05 +0100 | [diff] [blame] | 170 | qOffset, |
| 171 | layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 172 | } |
| 173 | |
| 174 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 175 | LayerTestResult<T, 4> SimpleConvolution2d3x3TestCommon( |
| 176 | armnn::IWorkloadFactory& workloadFactory, |
| 177 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 178 | float qScale, |
| 179 | int32_t qOffset, |
| 180 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 181 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 182 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 183 | // Use a 3x3 kernel, which exercises ArmCompute's direct convolution path. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 184 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 185 | // Use common single-batch 3-channel 16x8 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 186 | armnn::TensorInfo inputDesc({1, 3, 8, 16}, armnn::GetDataType<T>()); |
| 187 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, QuantizedVector<T>(qScale, qOffset, ConvInput3x8x16)); |
| 188 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 189 | // Use a 2-element batch of 3-channel 3x3 kernels. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 190 | armnn::TensorInfo kernelDesc({2, 3, 3, 3}, armnn::GetDataType<T>()); |
| 191 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, std::vector<T>( |
| 192 | QuantizedVector<T>(qScale, qOffset, { |
| 193 | 1, 1, 1, |
| 194 | 1, -1, 1, |
| 195 | 1, 1, 1, |
| 196 | |
| 197 | 0, 0, 0, |
| 198 | 0, 0, 0, |
| 199 | 0, 0, 0, |
| 200 | |
| 201 | 2, 2, 2, |
| 202 | 2, 2, 2, |
| 203 | 2, 2, 2, |
| 204 | |
| 205 | |
| 206 | 0, 0, 0, |
| 207 | 0, 0, 0, |
| 208 | 0, 0, 0, |
| 209 | |
| 210 | 1, 1, 1, |
| 211 | 1, 1, 1, |
| 212 | 1, 1, 1, |
| 213 | |
| 214 | 0, 0, 0, |
| 215 | 0, 0, 0, |
| 216 | 0, 0, 0 |
| 217 | }))); |
| 218 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 219 | // Expected output is 1 batch of a 2-channel 14x6 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 220 | armnn::TensorInfo outputDesc({1, 2, 6, 14}, armnn::GetDataType<T>()); |
| 221 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, std::vector<T>( |
| 222 | QuantizedVector<T>(qScale, qOffset, { |
| 223 | -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, |
| 224 | -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, |
| 225 | -14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f, |
| 226 | -14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f, |
| 227 | -14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f, |
| 228 | -14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f,-14.5f, |
| 229 | |
| 230 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 231 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 232 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 233 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 234 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 235 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 236 | }))); |
| 237 | |
| 238 | return SimpleConvolution2dTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 239 | memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 240 | input, |
| 241 | kernel, |
| 242 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasEnabled, qScale, qOffset), |
| 243 | expectedOutput, |
| 244 | qScale, |
narpra01 | 5f70318 | 2018-10-26 16:24:58 +0100 | [diff] [blame] | 245 | qOffset, |
| 246 | layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 247 | } |
| 248 | |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 249 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 250 | LayerTestResult<T, 4> SimpleConvolution2d3x3NhwcTestCommon( |
| 251 | armnn::IWorkloadFactory& workloadFactory, |
| 252 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 253 | float qScale, |
| 254 | int32_t qOffset, |
| 255 | bool biasEnabled, |
| 256 | armnn::DataLayout dataLayout) |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 257 | { |
| 258 | // Use common single-batch 5x5 image. |
| 259 | |
| 260 | armnn::TensorInfo inputDesc({1, 3, 4, 1}, armnn::GetDataType<T>()); |
| 261 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, |
| 262 | { |
| 263 | 1, 5, 2, 3, |
| 264 | 8, 7, 3, 6, |
| 265 | 3, 3, 9, 1 |
| 266 | }); |
| 267 | |
| 268 | |
| 269 | // Use a 2-element batch of 3-channel 3x3 kernels. |
| 270 | armnn::TensorInfo kernelDesc({1, 3, 3, 1}, armnn::GetDataType<T>()); |
| 271 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, { |
| 272 | 4, 5, 6, |
| 273 | 0, 0, 0, |
| 274 | 3, 2, 1 |
| 275 | }); |
| 276 | |
| 277 | // Expected output is 1 batch of a 5x5 image. |
| 278 | armnn::TensorInfo outputDesc({1, 3, 4, 1}, armnn::GetDataType<T>()); |
| 279 | |
| 280 | const std::vector<float> outputData = |
| 281 | { |
| 282 | 23, 41, 33, 21, |
| 283 | 44, 65, 76, 52, |
| 284 | 82, 85, 79, 42 |
| 285 | }; |
| 286 | |
| 287 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, outputData); |
| 288 | |
| 289 | return SimpleConvolution2dNhwcTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 290 | memoryManager, |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 291 | input, |
| 292 | kernel, |
| 293 | boost::multi_array<T, 1>(), |
| 294 | expectedOutput, |
| 295 | dataLayout, |
| 296 | qScale, |
| 297 | qOffset); |
| 298 | } |
| 299 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 300 | LayerTestResult<float, 4> SimpleConvolution2d3x5Test( |
| 301 | armnn::IWorkloadFactory& workloadFactory, |
| 302 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 303 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 304 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 305 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 306 | return SimpleConvolution2d3x5TestCommon<float>(workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 307 | } |
| 308 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 309 | LayerTestResult<uint8_t, 4> SimpleConvolution2d3x5Uint8Test( |
| 310 | armnn::IWorkloadFactory& workloadFactory, |
| 311 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 312 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 313 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 314 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 315 | return SimpleConvolution2d3x5TestCommon<uint8_t>(workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 316 | } |
| 317 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 318 | LayerTestResult<float, 4> SimpleConvolution2d3x3Test( |
| 319 | armnn::IWorkloadFactory& workloadFactory, |
| 320 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 321 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 322 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 323 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 324 | return SimpleConvolution2d3x3TestCommon<float>(workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 325 | } |
| 326 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 327 | LayerTestResult<float, 4> SimpleConvolution2d3x3NhwcTest( |
| 328 | armnn::IWorkloadFactory& workloadFactory, |
| 329 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 330 | bool biasEnabled) |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 331 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 332 | return SimpleConvolution2d3x3NhwcTestCommon<float>(workloadFactory, |
| 333 | memoryManager, |
| 334 | 0.f, |
| 335 | 0, |
| 336 | biasEnabled, |
| 337 | armnn::DataLayout::NHWC); |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 338 | } |
| 339 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 340 | LayerTestResult<uint8_t, 4> SimpleConvolution2d3x3Uint8Test( |
| 341 | armnn::IWorkloadFactory& workloadFactory, |
| 342 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 343 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 344 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 345 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 346 | return SimpleConvolution2d3x3TestCommon<uint8_t>(workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 347 | } |
| 348 | |
| 349 | template<typename T> |
| 350 | LayerTestResult<T, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon( |
| 351 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 352 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 353 | const armnn::DataLayout layout, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 354 | float qScale, |
| 355 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 356 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 357 | // Use a single-batch 1-channel 3x3 image as input. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 358 | armnn::TensorInfo inputDesc({1, 1, 3, 3}, armnn::GetDataType<T>()); |
| 359 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, std::vector<T>( |
| 360 | QuantizedVector<T>(qScale, qOffset, { |
| 361 | 11,21,31, |
| 362 | 12,22,32, |
| 363 | 13,23,33 |
| 364 | }))); |
| 365 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 366 | // Use 1 batch of a 1-channel 2x2 kernel. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 367 | armnn::TensorInfo kernelDesc({1, 1, 2, 2}, armnn::GetDataType<T>()); |
| 368 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, std::vector<T>( |
| 369 | QuantizedVector<T>(qScale, qOffset, { |
| 370 | -11,-21, |
| 371 | -12,-22, |
| 372 | }))); |
| 373 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 374 | // Expected output is 1 batch of a 1-channel 6x8 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 375 | // Manually calculated like this: |
| 376 | //[-11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ..] |
| 377 | //[-11*0 -21*0 -12*0 -22*11 ; -11*0 -21*0 -12*11 -22*21 ; -11*0 -21*0 -12*21 -22*31 ; -11*0 -21*0 -12*31 -22*0 ..] |
| 378 | //[-11*0 -21*11 -12*0 -22*12 ; -11*11 -21*21 -12*12 -22*22 ; -11*21 -21*31 -12*22 -22*32 ; -11*31 -21*0 -12*32 -22*0 ..] |
| 379 | //[-11*0 -21*12 -12*0 -22*13 ; -11*12 -21*22 -12*13 -22*23 ; -11*22 -21*32 -12*23 -22*33 ; -11*32 -21*0 -12*33 -22*0 ..] |
| 380 | //[-11*0 -21*13 -12*0 -22*0 ; -11*13 -21*23 -12*0 -22*0 ; -11*23 -21*33 -12*0 -22*0 ; -11*33 -21*0 -12*0 -22*0 ..] |
| 381 | //[-11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ; -11*0 -21*0 -12*0 -22*0 ..] |
| 382 | //[..... ..... ..... ..... ; ..... ..... ..... ..... ; ..... ..... ..... ..... ; ..... ..... ..... ..... ..] |
| 383 | armnn::TensorInfo outputDesc({1, 1, 8, 6}, armnn::GetDataType<T>()); |
| 384 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, std::vector<T>( |
| 385 | QuantizedVector<T>(qScale, qOffset, { |
| 386 | 0, 0, 0, 0, 0, 0, |
| 387 | -242, -594, -934, -372, 0, 0, |
| 388 | -495, -1190, -1850, -725, 0, 0, |
| 389 | -538, -1256, -1916, -748, 0, 0, |
| 390 | -273, -626, -946, -363, 0, 0, |
| 391 | 0, 0, 0, 0, 0, 0, |
| 392 | 0, 0, 0, 0, 0, 0, |
| 393 | 0, 0, 0, 0, 0, 0 |
| 394 | }))); |
| 395 | |
| 396 | return SimpleConvolution2dTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 397 | memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 398 | input, |
| 399 | kernel, |
| 400 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(false, qScale, qOffset), |
| 401 | expectedOutput, |
| 402 | qScale, |
| 403 | qOffset, |
narpra01 | 5f70318 | 2018-10-26 16:24:58 +0100 | [diff] [blame] | 404 | layout, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 405 | 1, // Padding left. |
| 406 | 2, // Padding top. |
| 407 | 3, // Padding right. |
| 408 | 4); // Padding bottom. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 409 | } |
| 410 | |
| 411 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 412 | LayerTestResult<T, 4> SimpleConvolution2dAsymmetricPaddingTestCommon( |
| 413 | armnn::IWorkloadFactory& workloadFactory, |
| 414 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 415 | const armnn::DataLayout layout, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 416 | float qScale, |
| 417 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 418 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 419 | // Use a single-batch 1-channel 5x5 image as input. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 420 | armnn::TensorInfo inputDesc({ 1, 1, 5, 5 }, armnn::GetDataType<T>()); |
| 421 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, std::vector<T>( |
| 422 | QuantizedVector<T>(qScale, qOffset, { |
| 423 | 11,21,31,41,51, |
| 424 | 12,22,32,42,52, |
| 425 | 13,23,33,43,53, |
| 426 | 14,24,34,44,54, |
| 427 | 15,25,35,45,55, |
| 428 | }))); |
| 429 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 430 | // Use 1 batch of a 1-channel 4x4 kernel. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 431 | armnn::TensorInfo kernelDesc({ 1, 1, 4, 4 }, armnn::GetDataType<T>()); |
| 432 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, std::vector<T>( |
| 433 | QuantizedVector<T>(qScale, qOffset, { |
| 434 | -11,-21,-31,-41, |
| 435 | -12,-22,-32,-42, |
| 436 | -13,-23,-33,-43, |
| 437 | -14,-24,-34,-44, |
| 438 | }))); |
| 439 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 440 | // Expected output is 1 batch of a 1-channel 5x5 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 441 | armnn::TensorInfo outputDesc({ 1, 1, 5, 5 }, armnn::GetDataType<T>()); |
| 442 | std::vector<T> myVec(outputDesc.GetNumElements(), 0); |
| 443 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, std::vector<T>( |
| 444 | QuantizedVector<T>(qScale, qOffset, { |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 445 | -7140, -10580, -13940, -9300, -5230, |
| 446 | -9590, -14120, -18520, -12290, -6860, |
| 447 | -9980, -14560, -18960, -12560, -7000, |
| 448 | -7518, -10904, -14144, -9318, -5152, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 449 | -5032, -7256, -9376, -6142, -3368, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 450 | }))); |
| 451 | |
| 452 | return SimpleConvolution2dTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 453 | memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 454 | input, |
| 455 | kernel, |
| 456 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(false, qScale, qOffset), |
| 457 | expectedOutput, |
| 458 | qScale, |
| 459 | qOffset, |
narpra01 | 5f70318 | 2018-10-26 16:24:58 +0100 | [diff] [blame] | 460 | layout, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 461 | 1, // Padding left. |
| 462 | 1, // Padding top. |
| 463 | 2, // Padding right. |
| 464 | 2); // Padding bottom. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 465 | } |
| 466 | |
| 467 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 468 | LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestCommon( |
| 469 | armnn::IWorkloadFactory& workloadFactory, |
| 470 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 471 | float qScale, |
| 472 | int32_t qOffset, |
| 473 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 474 | const armnn::DataLayout layout) |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 475 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 476 | // Use a single-batch 2-channel 5x5 image as input. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 477 | armnn::TensorInfo inputTensorInfo({ 1, 2, 5, 5 }, armnn::GetDataType<T>()); |
| 478 | auto input = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>( |
| 479 | QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(), inputTensorInfo.GetQuantizationOffset(), { |
| 480 | 0, 1, 2, 3, 4, |
| 481 | 5, 6, 7, 8, 9, |
| 482 | 10, 11, 12, 13, 14, |
| 483 | 15, 16, 17, 18, 19, |
| 484 | 20, 21, 22, 23, 24, |
| 485 | |
| 486 | 25, 26, 27, 28, 29, |
| 487 | 30, 31, 32, 33, 34, |
| 488 | 35, 36, 37, 38, 39, |
| 489 | 40, 41, 42, 43, 44, |
| 490 | 45, 46, 47, 48, 49 |
| 491 | }))); |
| 492 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 493 | // Use a depth multiplier of 1 on a 2-channel 4x4 kernel. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 494 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 4, 4 }, armnn::GetDataType<T>()); |
| 495 | auto kernel = MakeTensor<T, 4>(kernelTensorInfo, std::vector<T>( |
| 496 | QuantizedVector<T>(kernelTensorInfo.GetQuantizationScale(), kernelTensorInfo.GetQuantizationOffset(), { |
| 497 | 32, 31, 30, 29, |
| 498 | 28, 27, 26, 25, |
| 499 | 24, 23, 22, 21, |
| 500 | 20, 19, 18, 17, |
| 501 | |
| 502 | 16, 15, 14, 13, |
| 503 | 12, 11, 10, 9, |
| 504 | 8, 7, 6, 5, |
| 505 | 4, 3, 2, 1 |
| 506 | }))); |
| 507 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 508 | // Expected output is 1 batch of a 2-channel 5x5 image. |
| 509 | // Calculated using the python tensorflow library with strideX=1, strideY=1. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 510 | armnn::TensorInfo outputTensorInfo({ 1, 2, 5, 5 }, armnn::GetDataType<T>()); |
| 511 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputTensorInfo, std::vector<T>( |
| 512 | QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), { |
| 513 | 1062, 1580, 1850, 1530, 1117, |
| 514 | 2140, 3108, 3500, 2842, 2042, |
| 515 | 3580, 5068, 5460, 4342, 3062, |
| 516 | 3618, 5072, 5390, 4248, 2971, |
| 517 | 3074, 4282, 4510, 3533, 2457, |
| 518 | 1550, 2284, 2362, 1955, 1428, |
| 519 | 2910, 4206, 4342, 3528, 2536, |
| 520 | 3390, 4886, 5022, 4068, 2916, |
| 521 | 3566, 5056, 5182, 4133, 2922, |
| 522 | 3100, 4352, 4452, 3517, 2465 |
| 523 | }))); |
| 524 | |
| 525 | return DepthwiseConvolution2dAsymmetricTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 526 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 527 | input, |
| 528 | kernel, |
| 529 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasEnabled, qScale, qOffset), |
| 530 | expectedOutput, |
| 531 | qScale, |
| 532 | qOffset, |
jimfly01 | 382a91d | 2018-10-26 15:55:50 +0100 | [diff] [blame] | 533 | layout, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 534 | 1, // Padding left. |
| 535 | 1, // Padding top. |
| 536 | 2, // Padding right. |
| 537 | 2, // Padding bottom. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 538 | 1, // strideX |
| 539 | 1); // strideY |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 540 | } |
| 541 | |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 542 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 543 | LayerTestResult<T, 4> DepthwiseConvolution2dNhwcTestCommon( |
| 544 | armnn::IWorkloadFactory& workloadFactory, |
| 545 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 546 | float qScale, |
| 547 | int32_t qOffset, |
| 548 | bool biasEnabled) |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 549 | { |
| 550 | armnn::TensorInfo inputTensorInfo({ 1, 5, 5, 2}, armnn::GetDataType<T>()); |
| 551 | auto input = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>( |
| 552 | QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(), inputTensorInfo.GetQuantizationOffset(), { |
| 553 | 0, 25, |
| 554 | 1, 26, |
| 555 | 2, 27, |
| 556 | 3, 28, |
| 557 | 4, 29, |
| 558 | |
| 559 | 5, 30, |
| 560 | 6, 31, |
| 561 | 7, 32, |
| 562 | 8, 33, |
| 563 | 9, 34, |
| 564 | |
| 565 | 10, 35, |
| 566 | 11, 36, |
| 567 | 12, 37, |
| 568 | 13, 38, |
| 569 | 14, 39, |
| 570 | |
| 571 | 15, 40, |
| 572 | 16, 41, |
| 573 | 17, 42, |
| 574 | 18, 43, |
| 575 | 19, 44, |
| 576 | |
| 577 | 20, 45, |
| 578 | 21, 46, |
| 579 | 22, 47, |
| 580 | 23, 48, |
| 581 | 24, 49 |
| 582 | }))); |
| 583 | |
| 584 | armnn::TensorInfo kernelTensorInfo({ 1, 4, 4, 2}, armnn::GetDataType<T>()); |
| 585 | auto kernel = MakeTensor<T, 4>(kernelTensorInfo, std::vector<T>( |
| 586 | QuantizedVector<T>(kernelTensorInfo.GetQuantizationScale(), kernelTensorInfo.GetQuantizationOffset(), { |
| 587 | 32, 16, |
| 588 | 31, 15, |
| 589 | 30, 14, |
| 590 | 29, 13, |
| 591 | |
| 592 | 28, 12, |
| 593 | 27, 11, |
| 594 | 26, 10, |
| 595 | 25, 9, |
| 596 | |
| 597 | 24, 8, |
| 598 | 23, 7, |
| 599 | 22, 6, |
| 600 | 21, 5, |
| 601 | |
| 602 | 20, 4, |
| 603 | 19, 3, |
| 604 | 18, 2, |
| 605 | 17, 1 |
| 606 | }))); |
| 607 | |
| 608 | armnn::TensorInfo outputTensorInfo({ 1, 5, 5, 2}, armnn::GetDataType<T>()); |
| 609 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputTensorInfo, std::vector<T>( |
| 610 | QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), { |
| 611 | 1062, 1550, |
| 612 | 1580, 2284, |
| 613 | 1850, 2362, |
| 614 | 1530, 1955, |
| 615 | 1117, 1428, |
| 616 | |
| 617 | 2140, 2910, |
| 618 | 3108, 4206, |
| 619 | 3500, 4342, |
| 620 | 2842, 3528, |
| 621 | 2042, 2536, |
| 622 | |
| 623 | 3580, 3390, |
| 624 | 5068, 4886, |
| 625 | 5460, 5022, |
| 626 | 4342, 4068, |
| 627 | 3062, 2916, |
| 628 | |
| 629 | 3618, 3566, |
| 630 | 5072, 5056, |
| 631 | 5390, 5182, |
| 632 | 4248, 4133, |
| 633 | 2971, 2922, |
| 634 | |
| 635 | 3074, 3100, |
| 636 | 4282, 4352, |
| 637 | 4510, 4452, |
| 638 | 3533, 3517, |
| 639 | 2457, 2465 |
| 640 | }))); |
| 641 | |
| 642 | return DepthwiseConvolution2dNhwcTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 643 | memoryManager, |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 644 | input, |
| 645 | kernel, |
| 646 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasEnabled, qScale, qOffset), |
| 647 | expectedOutput, |
| 648 | qScale, |
| 649 | qOffset, |
| 650 | 1, // Padding left. |
| 651 | 1, // Padding top. |
| 652 | 2, // Padding right. |
| 653 | 2, // Padding bottom. |
| 654 | 1, // strideX |
| 655 | 1); // strideY |
| 656 | } |
| 657 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 658 | LayerTestResult<float, 4> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 659 | Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest( |
| 660 | armnn::IWorkloadFactory& workloadFactory, |
| 661 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 662 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 663 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 664 | return Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon<float>( |
| 665 | workloadFactory, memoryManager, layout, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 666 | } |
| 667 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 668 | LayerTestResult<float, 4> Convolution2dAsymmetricPaddingTest( |
| 669 | armnn::IWorkloadFactory& workloadFactory, |
| 670 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 671 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 672 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 673 | return SimpleConvolution2dAsymmetricPaddingTestCommon<float>( |
| 674 | workloadFactory, memoryManager, layout, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 675 | } |
| 676 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 677 | LayerTestResult<float, 4> DepthwiseConvolution2dTest( |
| 678 | armnn::IWorkloadFactory& workloadFactory, |
| 679 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 680 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 681 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 682 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 683 | return DepthwiseConvolution2dTestImpl<float, float>( |
| 684 | workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 685 | } |
| 686 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 687 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthNhwcTest( |
| 688 | armnn::IWorkloadFactory& workloadFactory, |
| 689 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 690 | bool biasEnabled) |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 691 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 692 | return DepthwiseConvolution2dNhwcTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0, biasEnabled); |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 693 | } |
| 694 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 695 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul1Test( |
| 696 | armnn::IWorkloadFactory& workloadFactory, |
| 697 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 698 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 699 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 700 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 701 | return DepthwiseConvolution2dDepthMul1TestImpl<float, float>( |
| 702 | workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 703 | } |
| 704 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 705 | LayerTestResult<float, 4> DepthwiseConvolution2dAsymmetricTest( |
| 706 | armnn::IWorkloadFactory& workloadFactory, |
| 707 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 708 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 709 | const armnn::DataLayout layout) |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 710 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 711 | return DepthwiseConvolution2dAsymmetricTestCommon<float>( |
| 712 | workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 713 | } |
| 714 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 715 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dUint8Test( |
| 716 | armnn::IWorkloadFactory& workloadFactory, |
| 717 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 718 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 719 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 720 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 721 | return DepthwiseConvolution2dTestImpl<uint8_t, int32_t>( |
| 722 | workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 723 | } |
| 724 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 725 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dDepthMul1Uint8Test( |
| 726 | armnn::IWorkloadFactory& workloadFactory, |
| 727 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 728 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 729 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 730 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 731 | return DepthwiseConvolution2dDepthMul1TestImpl<uint8_t, int32_t>( |
| 732 | workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 733 | } |
| 734 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 735 | LayerTestResult<float, 4> Convolution1dTest( |
| 736 | armnn::IWorkloadFactory& workloadFactory, |
| 737 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 738 | bool biasEnabled) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 739 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 740 | return Convolution1dTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0, biasEnabled); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 741 | } |
| 742 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 743 | LayerTestResult<uint8_t, 4> Convolution1dUint8Test( |
| 744 | armnn::IWorkloadFactory& workloadFactory, |
| 745 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 746 | bool biasEnabled) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 747 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 748 | return Convolution1dTestImpl<uint8_t>(workloadFactory, memoryManager, 0.1f, 128, biasEnabled); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 749 | } |
| 750 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 751 | LayerTestResult<float,4> CompareConvolution2dTest( |
| 752 | armnn::IWorkloadFactory& workloadFactory, |
| 753 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 754 | armnn::IWorkloadFactory& refWorkloadFactory) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 755 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 756 | return CompareConvolution2dTestImpl<float>(workloadFactory, memoryManager, refWorkloadFactory); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 757 | } |
| 758 | |
| 759 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 760 | LayerTestResult<T,4> CompareDepthwiseConvolution2dTest( |
| 761 | armnn::IWorkloadFactory& workloadFactory, |
| 762 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 763 | armnn::IWorkloadFactory& refWorkloadFactory, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 764 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 765 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 766 | return CompareDepthwiseConvolution2dTestImpl<T>(workloadFactory, memoryManager, refWorkloadFactory, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 767 | } |
| 768 | |
| 769 | template LayerTestResult<float, 4> CompareDepthwiseConvolution2dTest<float>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 770 | armnn::IWorkloadFactory&, |
| 771 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
| 772 | armnn::IWorkloadFactory&, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 773 | const armnn::DataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 774 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 775 | template LayerTestResult<uint8_t, 4> CompareDepthwiseConvolution2dTest<uint8_t>( |
| 776 | armnn::IWorkloadFactory&, |
| 777 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
| 778 | armnn::IWorkloadFactory&, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 779 | const armnn::DataLayout); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 780 | |
| 781 | LayerTestResult<float,4> SimpleNormalizationAcrossTest( |
| 782 | armnn::IWorkloadFactory& workloadFactory, |
| 783 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 784 | { |
| 785 | auto normMethod = armnn::NormalizationAlgorithmMethod::LocalBrightness; |
| 786 | auto normChannel = armnn::NormalizationAlgorithmChannel::Across; |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 787 | return SimpleNormalizationTestImpl(workloadFactory, memoryManager, normChannel, normMethod); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 788 | } |
| 789 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 790 | LayerTestResult<float,4> SimpleNormalizationWithinTest( |
| 791 | armnn::IWorkloadFactory& workloadFactory, |
| 792 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 793 | { |
| 794 | auto normMethod = armnn::NormalizationAlgorithmMethod::LocalBrightness; |
| 795 | auto normChannel = armnn::NormalizationAlgorithmChannel::Within; |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 796 | return SimpleNormalizationTestImpl(workloadFactory, memoryManager, normChannel, normMethod); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 797 | } |
| 798 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 799 | LayerTestResult<float,4> SimpleNormalizationAcrossNhwcTest( |
| 800 | armnn::IWorkloadFactory& workloadFactory, |
| 801 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 55a97bc | 2018-10-02 14:35:53 +0100 | [diff] [blame] | 802 | { |
| 803 | auto normMethod = armnn::NormalizationAlgorithmMethod::LocalBrightness; |
| 804 | auto normChannel = armnn::NormalizationAlgorithmChannel::Across; |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 805 | return SimpleNormalizationNhwcTestImpl(workloadFactory, memoryManager, normChannel, normMethod); |
narpra01 | 55a97bc | 2018-10-02 14:35:53 +0100 | [diff] [blame] | 806 | } |
| 807 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 808 | LayerTestResult<float,2> SimpleSoftmaxTest( |
| 809 | armnn::IWorkloadFactory& workloadFactory, |
| 810 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 811 | float beta) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 812 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 813 | return SimpleSoftmaxTestImpl<float>(workloadFactory, memoryManager, beta); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 814 | } |
| 815 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 816 | LayerTestResult<uint8_t,2> SimpleSoftmaxUint8Test( |
| 817 | armnn::IWorkloadFactory& workloadFactory, |
| 818 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 819 | float beta) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 820 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 821 | return SimpleSoftmaxTestImpl<uint8_t>(workloadFactory, memoryManager, beta); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 822 | } |
| 823 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 824 | LayerTestResult<float,4> CompareNormalizationTest( |
| 825 | armnn::IWorkloadFactory& workloadFactory, |
| 826 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 827 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 828 | armnn::NormalizationAlgorithmChannel normChannel, |
| 829 | armnn::NormalizationAlgorithmMethod normMethod) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 830 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 831 | return CompareNormalizationTestImpl(workloadFactory, memoryManager, refWorkloadFactory, normChannel, normMethod); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 832 | } |
| 833 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 834 | LayerTestResult<float,2> CompareSoftmaxTest( |
| 835 | armnn::IWorkloadFactory& workloadFactory, |
| 836 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 837 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 838 | float beta) |
| 839 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 840 | return CompareSoftmaxTestImpl<float>(workloadFactory, memoryManager, refWorkloadFactory, beta); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 841 | } |
| 842 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 843 | LayerTestResult<uint8_t,2> CompareSoftmaxUint8Test( |
| 844 | armnn::IWorkloadFactory& workloadFactory, |
| 845 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 846 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 847 | float beta) |
| 848 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 849 | return CompareSoftmaxTestImpl<uint8_t>(workloadFactory, memoryManager, refWorkloadFactory, beta); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 850 | } |
| 851 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 852 | std::vector<LayerTestResult<float,3>> SplitterTest( |
| 853 | armnn::IWorkloadFactory& workloadFactory, |
| 854 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 855 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 856 | return SplitterTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 857 | } |
| 858 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 859 | std::vector<LayerTestResult<uint8_t,3>> SplitterUint8Test( |
| 860 | armnn::IWorkloadFactory& workloadFactory, |
| 861 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 862 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 863 | return SplitterTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 864 | } |
| 865 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 866 | LayerTestResult<float, 3> CopyViaSplitterTest( |
| 867 | armnn::IWorkloadFactory& workloadFactory, |
| 868 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 869 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 870 | return CopyViaSplitterTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 871 | } |
| 872 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 873 | LayerTestResult<uint8_t, 3> CopyViaSplitterUint8Test( |
| 874 | armnn::IWorkloadFactory& workloadFactory, |
| 875 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 876 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 877 | return CopyViaSplitterTestImpl<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 878 | } |
| 879 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 880 | LayerTestResult<float, 2> LstmLayerFloat32WithCifgWithPeepholeNoProjectionTest( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 881 | armnn::IWorkloadFactory& workloadFactory, |
| 882 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 883 | { |
| 884 | armnn::TensorInfo inputDesc({ 2, 2 }, armnn::GetDataType<float>()); |
| 885 | boost::multi_array<float, 2> input = MakeTensor<float, 2>(inputDesc, std::vector<float>( |
| 886 | { 2., 3., 3., 4. })); |
| 887 | |
| 888 | armnn::TensorInfo outputDesc({ 2, 4 }, armnn::GetDataType<float>()); |
| 889 | boost::multi_array<float, 2> expectedOutput = MakeTensor<float, 2>(outputDesc, std::vector<float>( |
| 890 | {-0.36444446f, -0.00352185f, 0.12886585f, -0.05163646f, |
| 891 | -0.42734814f, -0.00478661f, 0.13455015f, -0.03560682f})); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 892 | return LstmLayerWithCifgWithPeepholeNoProjectionTestImpl( |
| 893 | workloadFactory, memoryManager, input, expectedOutput); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 894 | } |
| 895 | |
| 896 | LayerTestResult<float, 2> LstmLayerFloat32NoCifgWithPeepholeWithProjectionTest( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 897 | armnn::IWorkloadFactory& workloadFactory, |
| 898 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 899 | { |
| 900 | armnn::TensorInfo inputDesc({ 2, 5 }, armnn::GetDataType<float>()); |
| 901 | boost::multi_array<float, 2> input = MakeTensor<float, 2>(inputDesc, std::vector<float>( |
| 902 | {0.787926f, 0.151646f, 0.071352f, 0.118426f, 0.458058f, |
| 903 | 0.295743f, 0.544053f, 0.690064f, 0.858138f, 0.497181f})); |
| 904 | |
| 905 | armnn::TensorInfo outputDesc({ 2, 16 }, armnn::GetDataType<float>()); |
| 906 | boost::multi_array<float, 2> expectedOutput = MakeTensor<float, 2>(outputDesc, std::vector<float>( |
| 907 | {-0.00396806f, 0.029352f, -0.00279226f, 0.0159977f, -0.00835576f, |
| 908 | -0.0211779f, 0.0283512f, -0.0114597f, 0.00907307f, -0.0244004f, |
| 909 | -0.0152191f, -0.0259063f, 0.00914318f, 0.00415118f, 0.017147f, |
| 910 | 0.0134203f, -0.013869f, 0.0287268f, -0.00334693f, 0.00733398f, -0.0287926f, |
| 911 | -0.0186926f, 0.0193662f, -0.0115437f, 0.00422612f, -0.0345232f, |
| 912 | 0.00223253f, -0.00957321f, 0.0210624f, 0.013331f, 0.0150954f, |
| 913 | 0.02168f})); |
Matteo Martincigh | a65b7ae | 2018-11-14 12:39:55 +0000 | [diff] [blame] | 914 | return LstmLayerNoCifgWithPeepholeWithProjectionTestImpl(workloadFactory, memoryManager, input, expectedOutput); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 915 | } |
| 916 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 917 | LayerTestResult<float, 2> LstmLayerFloat32NoCifgNoPeepholeNoProjectionTest( |
| 918 | armnn::IWorkloadFactory& workloadFactory, |
| 919 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 920 | { |
| 921 | armnn::TensorInfo inputDesc({2, 2}, armnn::GetDataType<float>()); |
| 922 | boost::multi_array<float, 2> input = MakeTensor<float, 2>(inputDesc, std::vector<float>( |
| 923 | {2., 3., 3., 4.})); |
| 924 | |
| 925 | |
| 926 | armnn::TensorInfo outputDesc({2, 4}, armnn::GetDataType<float>()); |
| 927 | boost::multi_array<float, 2> expectedOutput = MakeTensor<float, 2>(outputDesc, std::vector<float>( |
| 928 | {{-0.02973187f, 0.1229473f, 0.20885126f, -0.15358765f, |
| 929 | -0.0185422f, 0.11281417f, 0.24466537f, -0.1826292f}})); |
| 930 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 931 | return LstmNoCifgNoPeepholeNoProjectionTestImpl( |
| 932 | workloadFactory, memoryManager, input, expectedOutput); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 933 | } |
| 934 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 935 | LayerTestResult<float,3> MergerTest( |
| 936 | armnn::IWorkloadFactory& workloadFactory, |
| 937 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 938 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 939 | unsigned int outputWidth = 3; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 940 | unsigned int outputHeight = 6; |
| 941 | unsigned int outputChannels = 3; |
| 942 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 943 | unsigned int inputWidth1 = 3; |
| 944 | unsigned int inputHeight1 = 6; |
| 945 | unsigned int inputChannels1 = 2; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 946 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 947 | unsigned int inputWidth2 = 3; |
| 948 | unsigned int inputHeight2 = 6; |
| 949 | unsigned int inputChannels2 = 1; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 950 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 951 | // Define the tensor descriptors. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 952 | armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::Float32); |
| 953 | armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::Float32); |
| 954 | armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::Float32); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 955 | |
| 956 | LayerTestResult<float,3> ret(outputTensorInfo); |
| 957 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 958 | ret.outputExpected = MakeTensor<float, 3>(outputTensorInfo, std::vector<float>( |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 959 | { |
| 960 | 1.0f, 2.0f, 3.0f, |
| 961 | 4.0f, 5.0f, 6.0f, |
| 962 | 7.0f, 8.0f, 9.0f, |
| 963 | 10.0f, 11.0f, 12.0f, |
| 964 | 13.0f, 14.0f, 15.0f, |
| 965 | 16.0f, 17.0f, 18.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 966 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 967 | 19.0f, 20.0f, 21.0f, |
| 968 | 22.0f, 23.0f, 24.0f, |
| 969 | 25.0f, 26.0f, 27.0f, |
| 970 | 28.0f, 29.0f, 30.0f, |
| 971 | 31.0f, 32.0f, 33.0f, |
| 972 | 34.0f, 35.0f, 36.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 973 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 974 | 37.0f, 38.0f, 39.0f, |
| 975 | 40.0f, 41.0f, 42.0f, |
| 976 | 43.0f, 44.0f, 45.0f, |
| 977 | 46.0f, 47.0f, 48.0f, |
| 978 | 49.0f, 50.0f, 51.0f, |
| 979 | 52.0f, 53.0f, 54.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 980 | }) |
| 981 | ); |
| 982 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 983 | auto input1 = MakeTensor<float, 3>(inputTensorInfo1, std::vector<float>( |
| 984 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 985 | 1.0f, 2.0f, 3.0f, |
| 986 | 4.0f, 5.0f, 6.0f, |
| 987 | 7.0f, 8.0f, 9.0f, |
| 988 | 10.0f, 11.0f, 12.0f, |
| 989 | 13.0f, 14.0f, 15.0f, |
| 990 | 16.0f, 17.0f, 18.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 991 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 992 | 19.0f, 20.0f, 21.0f, |
| 993 | 22.0f, 23.0f, 24.0f, |
| 994 | 25.0f, 26.0f, 27.0f, |
| 995 | 28.0f, 29.0f, 30.0f, |
| 996 | 31.0f, 32.0f, 33.0f, |
| 997 | 34.0f, 35.0f, 36.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 998 | }) |
| 999 | ); |
| 1000 | |
| 1001 | auto input2 = MakeTensor<float, 3>(inputTensorInfo2, std::vector<float>( |
| 1002 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1003 | 37.0f, 38.0f, 39.0f, |
| 1004 | 40.0f, 41.0f, 42.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1005 | 43.0f, 44.0f, 45.0f, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1006 | 46.0f, 47.0f, 48.0f, |
| 1007 | 49.0f, 50.0f, 51.0f, |
| 1008 | 52.0f, 53.0f, 54.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1009 | }) |
| 1010 | ); |
| 1011 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1012 | std::vector<unsigned int> wOrigin1 = {0, 0, 0}; //Extent of the window is defined by size of input[0]. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1013 | armnn::MergerQueueDescriptor::ViewOrigin window1(wOrigin1); |
| 1014 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1015 | std::vector<unsigned int> wOrigin2 = {2, 0, 0}; //Extent of the window is defined by size of input[1]. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1016 | armnn::MergerQueueDescriptor::ViewOrigin window2(wOrigin2); |
| 1017 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1018 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1019 | |
| 1020 | bool subTensorsSupported = workloadFactory.SupportsSubTensors(); |
| 1021 | |
| 1022 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = |
| 1023 | subTensorsSupported ? |
| 1024 | workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : |
| 1025 | workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1026 | |
| 1027 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = |
| 1028 | subTensorsSupported ? |
| 1029 | workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : |
| 1030 | workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1031 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1032 | armnn::MergerQueueDescriptor data; |
| 1033 | armnn::WorkloadInfo info; |
| 1034 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1035 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1036 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1037 | |
| 1038 | data.m_ViewOrigins.push_back(window1); |
| 1039 | data.m_ViewOrigins.push_back(window2); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1040 | |
| 1041 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMerger(data, info); |
| 1042 | |
| 1043 | inputHandle1->Allocate(); |
| 1044 | inputHandle2->Allocate(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1045 | outputHandle->Allocate(); |
| 1046 | |
| 1047 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]); |
| 1048 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1049 | |
| 1050 | workload->Execute(); |
| 1051 | |
| 1052 | CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get()); |
| 1053 | |
| 1054 | return ret; |
| 1055 | } |
| 1056 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1057 | LayerTestResult<float,4> AdditionTest( |
| 1058 | armnn::IWorkloadFactory& workloadFactory, |
| 1059 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1060 | { |
| 1061 | unsigned int batchSize = 2; |
| 1062 | unsigned int channels = 2; |
| 1063 | unsigned int height = 2; |
| 1064 | unsigned int width = 3; |
| 1065 | |
| 1066 | armnn::TensorInfo inputTensorInfo1, inputTensorInfo2; |
| 1067 | armnn::TensorInfo outputTensorInfo; |
| 1068 | |
| 1069 | unsigned int shape[] = {batchSize, channels, height, width}; |
| 1070 | |
| 1071 | inputTensorInfo1 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1072 | inputTensorInfo2 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1073 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1074 | |
| 1075 | |
| 1076 | auto input1 = MakeTensor<float, 4>(inputTensorInfo1, std::vector<float>( |
| 1077 | { |
| 1078 | 0.0f, 2.0f, 1.0f, |
| 1079 | 0.2f, 1.0f, 2.0f, |
| 1080 | |
| 1081 | 1.0f, 2.0f, 1.0f, |
| 1082 | 0.2f, 1.0f, 2.0f, |
| 1083 | |
| 1084 | 0.0f, 2.0f, 1.0f, |
| 1085 | 4.2f, 1.0f, 2.0f, |
| 1086 | |
| 1087 | 0.0f, 0.0f, 1.0f, |
| 1088 | 0.2f, 1.0f, 2.0f, |
| 1089 | })); |
| 1090 | |
| 1091 | auto input2 = MakeTensor<float, 4>(inputTensorInfo2, std::vector<float>( |
| 1092 | { |
| 1093 | 1.0f, 2.0f, 1.0f, |
| 1094 | 0.0f, 1.0f, 2.0f, |
| 1095 | |
| 1096 | 1.0f, 2.0f, -2.0f, |
| 1097 | 0.2f, 1.0f, 2.0f, |
| 1098 | |
| 1099 | 0.0f, 2.0f, 1.0f, |
| 1100 | 4.2f, 0.0f, -3.0f, |
| 1101 | |
| 1102 | 0.0f, 0.0f, 1.0f, |
| 1103 | 0.7f, 1.0f, 5.0f, |
| 1104 | })); |
| 1105 | |
| 1106 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 1107 | ret.outputExpected = MakeTensor<float, 4>(outputTensorInfo, std::vector<float>( |
| 1108 | { |
| 1109 | 1.0f, 4.0f, 2.0f, |
| 1110 | 0.2f, 2.0f, 4.0f, |
| 1111 | |
| 1112 | 2.0f, 4.0f, -1.0f, |
| 1113 | 0.4f, 2.0f, 4.0f, |
| 1114 | |
| 1115 | 0.0f, 4.0f, 2.0f, |
| 1116 | 8.4f, 1.0f, -1.0f, |
| 1117 | |
| 1118 | 0.0f, 0.0f, 2.0f, |
| 1119 | 0.9f, 2.0f, 7.0f, |
| 1120 | })); |
| 1121 | |
| 1122 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1123 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1124 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1125 | |
| 1126 | armnn::AdditionQueueDescriptor data; |
| 1127 | armnn::WorkloadInfo info; |
| 1128 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1129 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 1130 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1131 | |
| 1132 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 1133 | |
| 1134 | inputHandle1->Allocate(); |
| 1135 | inputHandle2->Allocate(); |
| 1136 | outputHandle->Allocate(); |
| 1137 | |
| 1138 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1139 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 1140 | |
| 1141 | workload->Execute(); |
| 1142 | |
| 1143 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1144 | |
| 1145 | return ret; |
| 1146 | } |
| 1147 | |
| 1148 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1149 | LayerTestResult<T, 4> AdditionBroadcastTestImpl( |
| 1150 | armnn::IWorkloadFactory& workloadFactory, |
| 1151 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1152 | float qScale, |
| 1153 | int32_t qOffset) |
| 1154 | { |
| 1155 | armnn::TensorInfo inputTensorInfo1 = armnn::TensorInfo({1, 3, 2, 1}, armnn::GetDataType<T>()); |
| 1156 | armnn::TensorInfo inputTensorInfo2 = armnn::TensorInfo({1, 1, 2, 3}, armnn::GetDataType<T>()); |
| 1157 | armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 2, 3}, armnn::GetDataType<T>()); |
| 1158 | |
| 1159 | if (armnn::IsQuantizedType<T>()) |
| 1160 | { |
| 1161 | inputTensorInfo1.SetQuantizationScale(qScale); |
| 1162 | inputTensorInfo1.SetQuantizationOffset(qOffset); |
| 1163 | inputTensorInfo2.SetQuantizationScale(qScale); |
| 1164 | inputTensorInfo2.SetQuantizationOffset(qOffset); |
| 1165 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1166 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1167 | } |
| 1168 | |
| 1169 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, |
| 1170 | { |
| 1171 | 0.0f, |
| 1172 | 1.0f, |
| 1173 | |
| 1174 | 2.0f, |
| 1175 | 3.0f, |
| 1176 | |
| 1177 | 4.0f, |
| 1178 | 5.0f, |
| 1179 | })); |
| 1180 | |
| 1181 | auto input2 = MakeTensor<T, 4>(inputTensorInfo2, QuantizedVector<T>(qScale, qOffset, |
| 1182 | { |
| 1183 | 0.5f, 1.5f, 2.5f, |
| 1184 | 3.5f, 4.5f, 5.5f, |
| 1185 | })); |
| 1186 | |
| 1187 | LayerTestResult<T,4> ret(outputTensorInfo); |
| 1188 | ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, |
| 1189 | { |
| 1190 | 0.5f, 1.5f, 2.5f, |
| 1191 | 4.5f, 5.5f, 6.5f, |
| 1192 | |
| 1193 | 2.5f, 3.5f, 4.5f, |
| 1194 | 6.5f, 7.5f, 8.5f, |
| 1195 | |
| 1196 | 4.5f, 5.5f, 6.5f, |
| 1197 | 8.5f, 9.5f, 10.5f, |
| 1198 | })); |
| 1199 | |
| 1200 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1201 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1202 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1203 | |
| 1204 | armnn::AdditionQueueDescriptor data; |
| 1205 | armnn::WorkloadInfo info; |
| 1206 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1207 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 1208 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1209 | |
| 1210 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 1211 | |
| 1212 | inputHandle1->Allocate(); |
| 1213 | inputHandle2->Allocate(); |
| 1214 | outputHandle->Allocate(); |
| 1215 | |
| 1216 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1217 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 1218 | |
| 1219 | workload->Execute(); |
| 1220 | |
| 1221 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1222 | |
| 1223 | return ret; |
| 1224 | } |
| 1225 | |
| 1226 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1227 | LayerTestResult<T, 4> AdditionBroadcast1ElementTestImpl( |
| 1228 | armnn::IWorkloadFactory& workloadFactory, |
| 1229 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1230 | float qScale, |
| 1231 | int32_t qOffset) |
| 1232 | { |
| 1233 | armnn::TensorInfo inputTensorInfo1 = armnn::TensorInfo({1, 3, 2, 3}, armnn::GetDataType<T>()); |
| 1234 | armnn::TensorInfo inputTensorInfo2 = armnn::TensorInfo({1, 1, 1, 1}, armnn::GetDataType<T>()); |
| 1235 | armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 2, 3}, armnn::GetDataType<T>()); |
| 1236 | |
| 1237 | if (armnn::IsQuantizedType<T>()) |
| 1238 | { |
| 1239 | inputTensorInfo1.SetQuantizationScale(qScale); |
| 1240 | inputTensorInfo1.SetQuantizationOffset(qOffset); |
| 1241 | inputTensorInfo2.SetQuantizationScale(qScale); |
| 1242 | inputTensorInfo2.SetQuantizationOffset(qOffset); |
| 1243 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1244 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1245 | } |
| 1246 | |
| 1247 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, |
| 1248 | { |
| 1249 | 0.0f, 1.0f, 2.0f, |
| 1250 | 3.0f, 4.0f, 5.0f, |
| 1251 | 6.0f, 7.0f, 8.0f, |
| 1252 | 9.0f, 10.0f, 11.0f, |
| 1253 | 12.0f, 13.0f, 14.0f, |
| 1254 | 15.0f, 16.0f, 17.0f, |
| 1255 | })); |
| 1256 | |
| 1257 | auto input2 = MakeTensor<T, 4>(inputTensorInfo2, QuantizedVector<T>(qScale, qOffset, |
| 1258 | { |
| 1259 | 0.5f, |
| 1260 | })); |
| 1261 | |
| 1262 | LayerTestResult<T,4> ret(outputTensorInfo); |
| 1263 | ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, |
| 1264 | { |
| 1265 | 0.5f, 1.5f, 2.5f, |
| 1266 | 3.5f, 4.5f, 5.5f, |
| 1267 | 6.5f, 7.5f, 8.5f, |
| 1268 | 9.5f, 10.5f, 11.5f, |
| 1269 | 12.5f, 13.5f, 14.5f, |
| 1270 | 15.5f, 16.5f, 17.5f, |
| 1271 | })); |
| 1272 | |
| 1273 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1274 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1275 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1276 | |
| 1277 | armnn::AdditionQueueDescriptor data; |
| 1278 | armnn::WorkloadInfo info; |
| 1279 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1280 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 1281 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1282 | |
| 1283 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 1284 | |
| 1285 | inputHandle1->Allocate(); |
| 1286 | inputHandle2->Allocate(); |
| 1287 | outputHandle->Allocate(); |
| 1288 | |
| 1289 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1290 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 1291 | |
| 1292 | workload->Execute(); |
| 1293 | |
| 1294 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1295 | |
| 1296 | return ret; |
| 1297 | } |
| 1298 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1299 | LayerTestResult<float, 4> AdditionBroadcastTest( |
| 1300 | armnn::IWorkloadFactory& workloadFactory, |
| 1301 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1302 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1303 | return AdditionBroadcastTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1304 | } |
| 1305 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1306 | LayerTestResult<uint8_t, 4> AdditionBroadcastUint8Test( |
| 1307 | armnn::IWorkloadFactory& workloadFactory, |
| 1308 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1309 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1310 | return AdditionBroadcastTestImpl<uint8_t>(workloadFactory, memoryManager, 2.f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1311 | } |
| 1312 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1313 | LayerTestResult<float, 4> AdditionBroadcast1ElementTest( |
| 1314 | armnn::IWorkloadFactory& workloadFactory, |
| 1315 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1316 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1317 | return AdditionBroadcast1ElementTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1318 | } |
| 1319 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1320 | LayerTestResult<uint8_t, 4> AdditionBroadcast1ElementUint8Test( |
| 1321 | armnn::IWorkloadFactory& workloadFactory, |
| 1322 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1323 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1324 | return AdditionBroadcast1ElementTestImpl<uint8_t>(workloadFactory, memoryManager, 0.1333333f, 128); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1325 | } |
| 1326 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1327 | LayerTestResult<float,4> CompareAdditionTest( |
| 1328 | armnn::IWorkloadFactory& workloadFactory, |
| 1329 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1330 | armnn::IWorkloadFactory& refWorkloadFactory) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1331 | { |
| 1332 | unsigned int batchSize = 4; |
| 1333 | unsigned int channels = 1; |
| 1334 | unsigned int height = 2; |
| 1335 | unsigned int width = 3; |
| 1336 | |
| 1337 | armnn::TensorInfo inputTensorInfo1, inputTensorInfo2; |
| 1338 | armnn::TensorInfo outputTensorInfo; |
| 1339 | |
| 1340 | unsigned int shape[] = {batchSize, channels, height, width}; |
| 1341 | |
| 1342 | inputTensorInfo1 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1343 | inputTensorInfo2 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1344 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1345 | |
| 1346 | auto input1 = MakeRandomTensor<float, 4>(inputTensorInfo1, 1232); |
| 1347 | auto input2 = MakeRandomTensor<float, 4>(inputTensorInfo2, 456); |
| 1348 | |
| 1349 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 1350 | |
| 1351 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1352 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1353 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1354 | |
| 1355 | std::unique_ptr<armnn::ITensorHandle> inputHandle1Ref = refWorkloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1356 | std::unique_ptr<armnn::ITensorHandle> inputHandle2Ref = refWorkloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1357 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1358 | |
| 1359 | armnn::AdditionQueueDescriptor data; |
| 1360 | armnn::WorkloadInfo info; |
| 1361 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1362 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 1363 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1364 | |
| 1365 | armnn::AdditionQueueDescriptor refData = data; |
| 1366 | armnn::WorkloadInfo refInfo = info; |
| 1367 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo1, inputHandle1Ref.get()); |
| 1368 | SetWorkloadInput(refData, refInfo, 1, inputTensorInfo2, inputHandle2Ref.get()); |
| 1369 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 1370 | |
| 1371 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 1372 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateAddition(refData, refInfo); |
| 1373 | |
| 1374 | inputHandle1->Allocate(); |
| 1375 | inputHandle2->Allocate(); |
| 1376 | outputHandle->Allocate(); |
| 1377 | inputHandle1Ref->Allocate(); |
| 1378 | inputHandle2Ref->Allocate(); |
| 1379 | outputHandleRef->Allocate(); |
| 1380 | |
| 1381 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1382 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 1383 | CopyDataToITensorHandle(inputHandle1Ref.get(), &input1[0][0][0][0]); |
| 1384 | CopyDataToITensorHandle(inputHandle2Ref.get(), &input2[0][0][0][0]); |
| 1385 | |
| 1386 | workload->Execute(); |
| 1387 | workloadRef->Execute(); |
| 1388 | |
| 1389 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1390 | CopyDataFromITensorHandle(&ret.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 1391 | |
| 1392 | return ret; |
| 1393 | } |
| 1394 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 1395 | namespace { |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1396 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1397 | LayerTestResult<T, 4> DivisionTestHelper( |
| 1398 | armnn::IWorkloadFactory& workloadFactory, |
| 1399 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1400 | const unsigned int shape0[4], |
| 1401 | const std::vector<T>& values0, |
| 1402 | float scale0, |
| 1403 | int32_t offset0, |
| 1404 | const unsigned int shape1[4], |
| 1405 | const std::vector<T> & values1, |
| 1406 | float scale1, |
| 1407 | int32_t offset1, |
| 1408 | const unsigned int outShape[4], |
| 1409 | const std::vector<T> & outValues, |
| 1410 | float outScale, |
| 1411 | int32_t outOffset) |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1412 | { |
| 1413 | auto dataType = (std::is_same<T, uint8_t>::value ? |
| 1414 | armnn::DataType::QuantisedAsymm8 : |
| 1415 | armnn::DataType::Float32); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1416 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1417 | armnn::TensorInfo inputTensorInfo0(4, shape0, dataType); |
| 1418 | armnn::TensorInfo inputTensorInfo1(4, shape1, dataType); |
| 1419 | armnn::TensorInfo outputTensorInfo(4, outShape, dataType); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1420 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1421 | inputTensorInfo0.SetQuantizationScale(scale0); |
| 1422 | inputTensorInfo0.SetQuantizationOffset(offset0); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1423 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1424 | inputTensorInfo1.SetQuantizationScale(scale1); |
| 1425 | inputTensorInfo1.SetQuantizationOffset(offset1); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1426 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1427 | outputTensorInfo.SetQuantizationScale(outScale); |
| 1428 | outputTensorInfo.SetQuantizationOffset(outOffset); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1429 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1430 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, values0); |
| 1431 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, values1); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1432 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1433 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 1434 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, outValues); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1435 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1436 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 1437 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1438 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1439 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1440 | armnn::DivisionQueueDescriptor data; |
| 1441 | armnn::WorkloadInfo info; |
| 1442 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 1443 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1444 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1445 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1446 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDivision(data, info); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1447 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1448 | inputHandle0->Allocate(); |
| 1449 | inputHandle1->Allocate(); |
| 1450 | outputHandle->Allocate(); |
| 1451 | |
| 1452 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 1453 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1454 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1455 | workload->Execute(); |
| 1456 | |
| 1457 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 1458 | |
| 1459 | return result; |
| 1460 | } |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1461 | } // anonymous namespace |
| 1462 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1463 | LayerTestResult<float,4> DivisionByZeroTest( |
| 1464 | armnn::IWorkloadFactory& workloadFactory, |
| 1465 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Francis Murtagh | 8c5e3dc | 2018-08-30 17:18:37 +0100 | [diff] [blame] | 1466 | { |
| 1467 | const unsigned int width = 2; |
| 1468 | const unsigned int height = 2; |
| 1469 | const unsigned int channelCount = 2; |
| 1470 | const unsigned int batchSize = 2; |
| 1471 | |
| 1472 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1473 | |
| 1474 | std::vector<float> input0({ |
| 1475 | 1.f, 1.f, 1.f, 1.f, 0.f, 0.f, 0.f, 0.f, |
| 1476 | -1.f, -1.f, -1.f, -1.f, 5.f, 5.f, 5.f, 5.f }); |
| 1477 | |
| 1478 | std::vector<float> input1({ |
| 1479 | 0.f, 0.f, -0.f, -0.f, 0.f, 0.f, -0.f, -0.f, |
| 1480 | 0.f, 0.f, -0.f, -0.f, 5.f, 5.f, 5.f, 5.f }); |
| 1481 | |
| 1482 | std::vector<float> output({ |
| 1483 | INFINITY, INFINITY, -INFINITY, -INFINITY, NAN, NAN, -NAN, -NAN, |
| 1484 | -INFINITY, -INFINITY, INFINITY, INFINITY, 1, 1, 1, 1 }); |
| 1485 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1486 | return DivisionTestHelper<float>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1487 | memoryManager, |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1488 | shape, input0, 1.0f, 0, |
| 1489 | shape, input1, 1.0f, 0, |
| 1490 | shape, output, 1.0f, 0); |
Francis Murtagh | 8c5e3dc | 2018-08-30 17:18:37 +0100 | [diff] [blame] | 1491 | } |
| 1492 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1493 | LayerTestResult<float,4> DivisionTest( |
| 1494 | armnn::IWorkloadFactory& workloadFactory, |
| 1495 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1496 | { |
| 1497 | const unsigned int width = 2; |
| 1498 | const unsigned int height = 2; |
| 1499 | const unsigned int channelCount = 2; |
| 1500 | const unsigned int batchSize = 2; |
| 1501 | |
| 1502 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1503 | |
| 1504 | std::vector<float> input0({ |
| 1505 | 2, 2, 2, 2, 3, 3, 3, 3, |
| 1506 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 1507 | |
| 1508 | std::vector<float> input1({ |
| 1509 | 1, 1, 1, 1, 2, 2, 2, 2, |
| 1510 | 4, 4, 4, 4, 4, 4, 4, 4 }); |
| 1511 | |
| 1512 | std::vector<float> output({ |
| 1513 | 2, 2, 2, 2, 1.5, 1.5, 1.5, 1.5, |
| 1514 | 1, 1, 1, 1, 1.25, 1.25, 1.25, 1.25 }); |
| 1515 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1516 | |
| 1517 | return DivisionTestHelper<float>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1518 | memoryManager, |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1519 | shape, input0, 1.0f, 0, |
| 1520 | shape, input1, 1.0f, 0, |
| 1521 | shape, output, 1.0f, 0); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1522 | } |
| 1523 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1524 | LayerTestResult<float, 4> DivisionBroadcast1ElementTest( |
| 1525 | armnn::IWorkloadFactory& workloadFactory, |
| 1526 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1527 | { |
| 1528 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 1529 | std::vector<float> input0({ 2, 4, 6, 8, 10, 12, 14, 16}); |
| 1530 | |
| 1531 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1532 | std::vector<float> input1({ 2 }); |
| 1533 | |
| 1534 | std::vector<float> output({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 1535 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1536 | |
| 1537 | return DivisionTestHelper<float>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1538 | memoryManager, |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1539 | shape0, input0, 1.0f, 0, |
| 1540 | shape1, input1, 1.0f, 0, |
| 1541 | shape0, output, 1.0f, 0); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1542 | } |
| 1543 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1544 | LayerTestResult<float, 4> DivisionBroadcast1DVectorTest( |
| 1545 | armnn::IWorkloadFactory& workloadFactory, |
| 1546 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1547 | { |
| 1548 | unsigned int shape0[] = { 1, 3, 3, 2 }; |
| 1549 | std::vector<float> input0({ |
| 1550 | 1, 4, 3, 8, 5, 12, |
| 1551 | 7, 16, 9, 20, 11, 24, |
| 1552 | 13, 28, 15, 32, 17, 36}); |
| 1553 | |
| 1554 | unsigned int shape1[] = { 1, 1, 1, 2 }; |
| 1555 | std::vector<float> input1({ 1, 2 }); |
| 1556 | |
| 1557 | std::vector<float> output({ |
| 1558 | 1, 2, 3, 4, 5, 6, |
| 1559 | 7, 8, 9, 10, 11, 12, |
| 1560 | 13, 14, 15, 16, 17, 18}); |
| 1561 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1562 | return DivisionTestHelper<float>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1563 | memoryManager, |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1564 | shape0, input0, 1.0f, 0, |
| 1565 | shape1, input1, 1.0f, 0, |
| 1566 | shape0, output, 1.0f, 0); |
| 1567 | } |
| 1568 | |
| 1569 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1570 | LayerTestResult<uint8_t,4> DivisionUint8Test( |
| 1571 | armnn::IWorkloadFactory& workloadFactory, |
| 1572 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1573 | { |
| 1574 | const unsigned int width = 2; |
| 1575 | const unsigned int height = 2; |
| 1576 | const unsigned int channelCount = 2; |
| 1577 | const unsigned int batchSize = 2; |
| 1578 | |
| 1579 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1580 | |
| 1581 | std::vector<uint8_t> input0({2, 2, 2, 2, 3, 3, 3, 3, |
| 1582 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 1583 | |
| 1584 | std::vector<uint8_t> input1({1, 1, 1, 1, 2, 2, 2, 2, |
| 1585 | 4, 4, 4, 4, 4, 4, 4, 4 }); |
| 1586 | |
| 1587 | std::vector<uint8_t> output({8, 8, 8, 8, 6, 6, 6, 6, |
| 1588 | 4, 4, 4, 4, 5, 5, 5, 5}); |
| 1589 | |
| 1590 | |
| 1591 | return DivisionTestHelper<uint8_t>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1592 | memoryManager, |
| 1593 | shape, input0, 1.0f, 0, |
| 1594 | shape, input1, 1.0f, 0, |
| 1595 | shape, output, 0.25f, 0); |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1596 | } |
| 1597 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1598 | LayerTestResult<uint8_t, 4> DivisionBroadcast1ElementUint8Test( |
| 1599 | armnn::IWorkloadFactory& workloadFactory, |
| 1600 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1601 | { |
| 1602 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 1603 | std::vector<uint8_t> input0({ 2, 4, 6, 8, 10, 12, 14, 16}); |
| 1604 | |
| 1605 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1606 | std::vector<uint8_t> input1({ 2 }); |
| 1607 | |
| 1608 | std::vector<uint8_t> output({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 1609 | |
| 1610 | return DivisionTestHelper<uint8_t>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1611 | memoryManager, |
| 1612 | shape0, input0, 1.0f, 0, |
| 1613 | shape1, input1, 1.0f, 0, |
| 1614 | shape0, output, 1.0f, 0); |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1615 | } |
| 1616 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1617 | LayerTestResult<uint8_t, 4> DivisionBroadcast1DVectorUint8Test( |
| 1618 | armnn::IWorkloadFactory& workloadFactory, |
| 1619 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1620 | { |
| 1621 | unsigned int shape0[] = { 1, 3, 3, 2 }; |
| 1622 | std::vector<uint8_t> input0({1, 4, 3, 8, 5, 12, |
| 1623 | 7, 16, 9, 20, 11, 24, |
| 1624 | 13, 28, 15, 32, 17, 36}); |
| 1625 | |
| 1626 | unsigned int shape1[] = { 1, 1, 1, 2 }; |
| 1627 | std::vector<uint8_t> input1({ 1, 2 }); |
| 1628 | |
| 1629 | std::vector<uint8_t> output({1, 2, 3, 4, 5, 6, |
| 1630 | 7, 8, 9, 10, 11, 12, |
| 1631 | 13, 14, 15, 16, 17, 18}); |
| 1632 | |
| 1633 | return DivisionTestHelper<uint8_t>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1634 | memoryManager, |
| 1635 | shape0, input0, 1.0f, 0, |
| 1636 | shape1, input1, 1.0f, 0, |
| 1637 | shape0, output, 1.0f, 0); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1638 | } |
| 1639 | |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 1640 | template<typename DescriptorType> |
| 1641 | std::unique_ptr<armnn::IWorkload> CreateWorkload( |
| 1642 | const armnn::IWorkloadFactory& workloadFactory, |
| 1643 | const armnn::WorkloadInfo& info, |
| 1644 | const DescriptorType& descriptor) |
| 1645 | { |
| 1646 | return CreateWorkload(workloadFactory, info, descriptor); |
| 1647 | }; |
| 1648 | |
| 1649 | template<> |
| 1650 | std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::MaximumQueueDescriptor>( |
| 1651 | const armnn::IWorkloadFactory& workloadFactory, |
| 1652 | const armnn::WorkloadInfo& info, |
| 1653 | const armnn::MaximumQueueDescriptor& descriptor) |
| 1654 | { |
| 1655 | return workloadFactory.CreateMaximum(descriptor, info); |
| 1656 | } |
| 1657 | |
Éanna Ó Catháin | 20e5880 | 2018-12-04 10:29:06 +0000 | [diff] [blame] | 1658 | template<> |
| 1659 | std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::MinimumQueueDescriptor>( |
| 1660 | const armnn::IWorkloadFactory& workloadFactory, |
| 1661 | const armnn::WorkloadInfo& info, |
| 1662 | const armnn::MinimumQueueDescriptor& descriptor) |
| 1663 | { |
| 1664 | return workloadFactory.CreateMinimum(descriptor, info); |
| 1665 | } |
| 1666 | |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 1667 | namespace { |
| 1668 | template <typename Descriptor, typename dataType> |
| 1669 | LayerTestResult<dataType, 4> ElementwiseTestHelper |
| 1670 | (armnn::IWorkloadFactory & workloadFactory, |
| 1671 | const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager, |
| 1672 | const unsigned int shape0[4], std::vector<dataType> values0, |
| 1673 | const unsigned int shape1[4], std::vector<dataType> values1, |
| 1674 | const unsigned int outShape[4], std::vector<dataType> outValues, |
| 1675 | float qScale = 0.0f, int qOffset = 0) |
| 1676 | { |
| 1677 | const size_t dimensionCount = 4; |
| 1678 | armnn::TensorInfo inputTensorInfo0{dimensionCount, shape0, armnn::GetDataType<dataType>()}; |
| 1679 | armnn::TensorInfo inputTensorInfo1{dimensionCount, shape1, armnn::GetDataType<dataType>()}; |
| 1680 | armnn::TensorInfo outputTensorInfo{dimensionCount, outShape, armnn::GetDataType<dataType>()}; |
| 1681 | |
| 1682 | auto input0 = MakeTensor<dataType, 4>(inputTensorInfo0, values0); |
| 1683 | auto input1 = MakeTensor<dataType, 4>(inputTensorInfo1, values1); |
| 1684 | |
| 1685 | if (armnn::IsQuantizedType<dataType>()) |
| 1686 | { |
| 1687 | inputTensorInfo0.SetQuantizationScale(qScale); |
| 1688 | inputTensorInfo0.SetQuantizationOffset(qOffset); |
| 1689 | |
| 1690 | inputTensorInfo1.SetQuantizationScale(qScale); |
| 1691 | inputTensorInfo1.SetQuantizationOffset(qOffset); |
| 1692 | |
| 1693 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1694 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1695 | } |
| 1696 | |
| 1697 | LayerTestResult<dataType,4> ret(outputTensorInfo); |
| 1698 | |
| 1699 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 1700 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1701 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1702 | |
| 1703 | Descriptor data; |
| 1704 | armnn::WorkloadInfo info; |
| 1705 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 1706 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1707 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1708 | auto workload = CreateWorkload<Descriptor>(workloadFactory, info, data); |
| 1709 | |
| 1710 | inputHandle0->Allocate(); |
| 1711 | inputHandle1->Allocate(); |
| 1712 | outputHandle->Allocate(); |
| 1713 | |
| 1714 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 1715 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1716 | |
| 1717 | ExecuteWorkload(*workload, memoryManager); |
| 1718 | |
| 1719 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1720 | |
| 1721 | ret.outputExpected = MakeTensor<dataType, 4>(outputTensorInfo, outValues); |
| 1722 | return ret; |
| 1723 | } |
| 1724 | } |
| 1725 | |
| 1726 | |
| 1727 | LayerTestResult<float, 4> MaximumSimpleTest(armnn::IWorkloadFactory& workloadFactory, |
| 1728 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1729 | { |
| 1730 | const unsigned int width = 2; |
| 1731 | const unsigned int height = 2; |
| 1732 | const unsigned int channelCount = 2; |
| 1733 | const unsigned int batchSize = 2; |
| 1734 | |
| 1735 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1736 | |
| 1737 | std::vector<float> input0({ 1, 1, 1, 1, 5, 5, 5, 5, |
| 1738 | 3, 3, 3, 3, 4, 4, 4, 4 }); |
| 1739 | |
| 1740 | std::vector<float> input1({ 2, 2, 2, 2, 3, 3, 3, 3, |
| 1741 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 1742 | |
| 1743 | std::vector<float> output({ 2, 2, 2, 2, 5, 5, 5, 5, |
| 1744 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 1745 | |
| 1746 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, float> |
| 1747 | (workloadFactory, |
| 1748 | memoryManager, |
| 1749 | shape, |
| 1750 | input0, |
| 1751 | shape, |
| 1752 | input1, |
| 1753 | shape, |
| 1754 | output); |
| 1755 | } |
| 1756 | |
| 1757 | LayerTestResult<float, 4> MaximumBroadcast1ElementTest( |
| 1758 | armnn::IWorkloadFactory& workloadFactory, |
| 1759 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1760 | { |
| 1761 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 1762 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 1763 | |
| 1764 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1765 | std::vector<float> input1({ 2 }); |
| 1766 | |
| 1767 | std::vector<float> output({ 2, 2, 3, 4, 5, 6, 7, 8}); |
| 1768 | |
| 1769 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, float> |
| 1770 | (workloadFactory, |
| 1771 | memoryManager, |
| 1772 | shape0, |
| 1773 | input0, |
| 1774 | shape1, |
| 1775 | input1, |
| 1776 | shape0, |
| 1777 | output); |
| 1778 | } |
| 1779 | |
| 1780 | LayerTestResult<float, 4> MaximumBroadcast1DVectorTest( |
| 1781 | armnn::IWorkloadFactory& workloadFactory, |
| 1782 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1783 | { |
| 1784 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 1785 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 1786 | |
| 1787 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, |
| 1788 | 7, 8, 9, 10, 11, 12 }); |
| 1789 | |
| 1790 | std::vector<float> input1({ 1, 2, 3}); |
| 1791 | |
| 1792 | std::vector<float> output({ 1, 2, 3, 4, 5, 6, |
| 1793 | 7, 8, 9, 10, 11, 12 }); |
| 1794 | |
| 1795 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, float> |
| 1796 | (workloadFactory, |
| 1797 | memoryManager, |
| 1798 | shape0, |
| 1799 | input0, |
| 1800 | shape1, |
| 1801 | input1, |
| 1802 | shape0, |
| 1803 | output); |
| 1804 | } |
| 1805 | |
| 1806 | LayerTestResult<uint8_t, 4> MaximumUint8Test( |
| 1807 | armnn::IWorkloadFactory& workloadFactory, |
| 1808 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1809 | { |
| 1810 | unsigned int shape[] = { 2, 2, 2, 2 }; |
| 1811 | |
| 1812 | // See dequantized values to the right. |
| 1813 | std::vector<uint8_t> input0({ 1, 1, 1, 1, 6, 6, 6, 6, |
| 1814 | 3, 3, 3, 3, 4, 4, 4, 4 }); |
| 1815 | |
| 1816 | std::vector<uint8_t> input1({ 2, 2, 2, 2, 3, 3, 3, 3, |
| 1817 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 1818 | |
| 1819 | std::vector<uint8_t> output({ 2, 2, 2, 2, 6, 6, 6, 6, |
| 1820 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 1821 | |
| 1822 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, uint8_t > |
| 1823 | (workloadFactory, |
| 1824 | memoryManager, |
| 1825 | shape, |
| 1826 | input0, |
| 1827 | shape, |
| 1828 | input1, |
| 1829 | shape, |
| 1830 | output, |
| 1831 | 1.0f, |
| 1832 | 0); |
| 1833 | } |
| 1834 | |
| 1835 | LayerTestResult<uint8_t, 4> MaximumBroadcast1ElementUint8Test( |
| 1836 | armnn::IWorkloadFactory& workloadFactory, |
| 1837 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1838 | { |
| 1839 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 1840 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1841 | |
| 1842 | std::vector<uint8_t> input0({ 1, 2, 3, 4, 5, 6, |
| 1843 | 7, 8, 9, 10, 11, 12 }); |
| 1844 | |
| 1845 | std::vector<uint8_t> input1({2}); |
| 1846 | |
| 1847 | std::vector<uint8_t> output({ 2, 2, 3, 4, 5, 6, |
| 1848 | 7, 8, 9, 10, 11, 12 }); |
| 1849 | |
| 1850 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, uint8_t > |
| 1851 | (workloadFactory, |
| 1852 | memoryManager, |
| 1853 | shape0, |
| 1854 | input0, |
| 1855 | shape1, |
| 1856 | input1, |
| 1857 | shape0, |
| 1858 | output, |
| 1859 | 1.0f, |
| 1860 | 0); |
| 1861 | } |
| 1862 | |
| 1863 | LayerTestResult<uint8_t, 4> MaximumBroadcast1DVectorUint8Test( |
| 1864 | armnn::IWorkloadFactory& workloadFactory, |
| 1865 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1866 | { |
| 1867 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 1868 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 1869 | |
| 1870 | std::vector<uint8_t> input0({ 1, 2, 3, 4, 5, 6, |
| 1871 | 7, 8, 9, 10, 11, 12 }); |
| 1872 | |
| 1873 | std::vector<uint8_t> input1({ 1, 10, 3}); |
| 1874 | |
| 1875 | std::vector<uint8_t> output({ 1, 10, 3, 4, 10, 6, |
| 1876 | 7, 10, 9, 10, 11, 12 }); |
| 1877 | |
Éanna Ó Catháin | 20e5880 | 2018-12-04 10:29:06 +0000 | [diff] [blame] | 1878 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, uint8_t> |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 1879 | (workloadFactory, |
| 1880 | memoryManager, |
| 1881 | shape0, |
| 1882 | input0, |
| 1883 | shape1, |
| 1884 | input1, |
| 1885 | shape0, |
| 1886 | output, |
| 1887 | 1.0f, |
| 1888 | 0); |
| 1889 | } |
| 1890 | |
Éanna Ó Catháin | 20e5880 | 2018-12-04 10:29:06 +0000 | [diff] [blame] | 1891 | LayerTestResult<float, 4> MinimumBroadcast1ElementTest1( |
| 1892 | armnn::IWorkloadFactory& workloadFactory, |
| 1893 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1894 | { |
| 1895 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 1896 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 1897 | |
| 1898 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1899 | std::vector<float> input1({ 2 }); |
| 1900 | |
| 1901 | std::vector<float> output({ 1, 2, 2, 2, 2, 2, 2, 2}); |
| 1902 | |
| 1903 | return ElementwiseTestHelper<armnn::MinimumQueueDescriptor, float>(workloadFactory, |
| 1904 | memoryManager, |
| 1905 | shape0, |
| 1906 | input0, |
| 1907 | shape1, |
| 1908 | input1, |
| 1909 | shape0, |
| 1910 | output); |
| 1911 | } |
| 1912 | |
| 1913 | |
| 1914 | LayerTestResult<float, 4> MinimumBroadcast1ElementTest2( |
| 1915 | armnn::IWorkloadFactory& workloadFactory, |
| 1916 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1917 | { |
| 1918 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 1919 | std::vector<float> input0({ 1, 6, 3, 2, 8, 9, 1, 10}); |
| 1920 | |
| 1921 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1922 | std::vector<float> input1({ 5 }); |
| 1923 | |
| 1924 | std::vector<float> output({ 1, 5, 3, 2, 5, 5, 1, 5}); |
| 1925 | |
| 1926 | return ElementwiseTestHelper<armnn::MinimumQueueDescriptor, float>(workloadFactory, |
| 1927 | memoryManager, |
| 1928 | shape0, |
| 1929 | input0, |
| 1930 | shape1, |
| 1931 | input1, |
| 1932 | shape0, |
| 1933 | output); |
| 1934 | } |
| 1935 | |
| 1936 | LayerTestResult<uint8_t, 4> MinimumBroadcast1DVectorUint8Test( |
| 1937 | armnn::IWorkloadFactory & workloadFactory, |
| 1938 | const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager) |
| 1939 | { |
| 1940 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 1941 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 1942 | |
| 1943 | std::vector<uint8_t> input0({ 1, 2, 3, 3, 2, 1, |
| 1944 | 7, 1, 2, 3, 4, 5 }); |
| 1945 | |
| 1946 | std::vector<uint8_t> input1({ 1, 2, 3}); |
| 1947 | |
| 1948 | std::vector<uint8_t> output({ 1, 2, 3, 1, 2, 1, |
| 1949 | 1, 1, 2, 1, 2, 3 }); |
| 1950 | |
| 1951 | return ElementwiseTestHelper<armnn::MinimumQueueDescriptor, uint8_t>(workloadFactory, |
| 1952 | memoryManager, |
| 1953 | shape0, |
| 1954 | input0, |
| 1955 | shape1, |
| 1956 | input1, |
| 1957 | shape0, |
| 1958 | output, |
| 1959 | 1.0f, |
| 1960 | 0); |
| 1961 | } |
| 1962 | |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1963 | namespace { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1964 | LayerTestResult<float,4> MultiplicationTestHelper( |
| 1965 | armnn::IWorkloadFactory& workloadFactory, |
| 1966 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1967 | const unsigned int shape0[4], |
| 1968 | const std::vector<float> & values0, |
| 1969 | const unsigned int shape1[4], |
| 1970 | const std::vector<float> & values1, |
| 1971 | const unsigned int outShape[4], |
| 1972 | const std::vector<float> & outValues) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1973 | { |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 1974 | const size_t dimensionCount = 4; |
| 1975 | armnn::TensorInfo inputTensorInfo0{dimensionCount, shape0, armnn::DataType::Float32}; |
| 1976 | armnn::TensorInfo inputTensorInfo1{dimensionCount, shape1, armnn::DataType::Float32}; |
| 1977 | armnn::TensorInfo outputTensorInfo{dimensionCount, outShape, armnn::DataType::Float32}; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1978 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 1979 | auto input0 = MakeTensor<float, 4>(inputTensorInfo0, values0); |
| 1980 | auto input1 = MakeTensor<float, 4>(inputTensorInfo1, values1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1981 | |
| 1982 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 1983 | |
| 1984 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 1985 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1986 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1987 | |
| 1988 | armnn::MultiplicationQueueDescriptor data; |
| 1989 | armnn::WorkloadInfo info; |
| 1990 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 1991 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1992 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1993 | |
| 1994 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMultiplication(data, info); |
| 1995 | |
| 1996 | inputHandle0->Allocate(); |
| 1997 | inputHandle1->Allocate(); |
| 1998 | outputHandle->Allocate(); |
| 1999 | |
| 2000 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 2001 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 2002 | |
| 2003 | workload->Execute(); |
| 2004 | |
| 2005 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 2006 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2007 | ret.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outValues); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2008 | return ret; |
| 2009 | } |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2010 | } // anonymous namespace |
| 2011 | |
| 2012 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2013 | LayerTestResult<float,4> MultiplicationTest( |
| 2014 | armnn::IWorkloadFactory& workloadFactory, |
| 2015 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2016 | { |
| 2017 | const unsigned int width = 2; |
| 2018 | const unsigned int height = 2; |
| 2019 | const unsigned int channelCount = 2; |
| 2020 | const unsigned int batchSize = 2; |
| 2021 | |
| 2022 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 2023 | |
| 2024 | std::vector<float> input0({ |
| 2025 | 1, 1, 1, 1, 2, 2, 2, 2, |
| 2026 | 3, 3, 3, 3, 4, 4, 4, 4 }); |
| 2027 | |
| 2028 | std::vector<float> input1({ |
| 2029 | 2, 2, 2, 2, 3, 3, 3, 3, |
| 2030 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 2031 | |
| 2032 | std::vector<float> output({ |
| 2033 | 2, 2, 2, 2, 6, 6, 6, 6, |
| 2034 | 12, 12, 12, 12, 20, 20, 20, 20 }); |
| 2035 | |
| 2036 | return MultiplicationTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2037 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2038 | shape, |
| 2039 | input0, |
| 2040 | shape, |
| 2041 | input1, |
| 2042 | shape, |
| 2043 | output); |
| 2044 | } |
| 2045 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2046 | LayerTestResult<float, 4> MultiplicationBroadcast1ElementTest( |
| 2047 | armnn::IWorkloadFactory& workloadFactory, |
| 2048 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2049 | { |
| 2050 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 2051 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 2052 | |
| 2053 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 2054 | std::vector<float> input1({ 2 }); |
| 2055 | |
| 2056 | std::vector<float> output({ 2, 4, 6, 8, 10, 12, 14, 16}); |
| 2057 | |
| 2058 | return MultiplicationTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2059 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2060 | shape0, |
| 2061 | input0, |
| 2062 | shape1, |
| 2063 | input1, |
| 2064 | shape0, |
| 2065 | output); |
| 2066 | } |
| 2067 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2068 | LayerTestResult<float, 4> MultiplicationBroadcast1DVectorTest( |
| 2069 | armnn::IWorkloadFactory& workloadFactory, |
| 2070 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2071 | { |
| 2072 | unsigned int shape0[] = { 1, 3, 3, 2 }; |
| 2073 | std::vector<float> input0({ |
| 2074 | 1, 2, 3, 4, 5, 6, |
| 2075 | 7, 8, 9, 10, 11, 12, |
| 2076 | 13, 14, 15, 16, 17, 18}); |
| 2077 | |
| 2078 | unsigned int shape1[] = { 1, 1, 1, 2 }; |
| 2079 | std::vector<float> input1({ 1, 2 }); |
| 2080 | |
| 2081 | std::vector<float> output({ |
| 2082 | 1, 4, 3, 8, 5, 12, |
| 2083 | 7, 16, 9, 20, 11, 24, |
| 2084 | 13, 28, 15, 32, 17, 36}); |
| 2085 | |
| 2086 | return MultiplicationTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2087 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2088 | shape0, |
| 2089 | input0, |
| 2090 | shape1, |
| 2091 | input1, |
| 2092 | shape0, |
| 2093 | output); |
| 2094 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2095 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2096 | LayerTestResult<float,4> CompareMultiplicationTest( |
| 2097 | armnn::IWorkloadFactory& workloadFactory, |
| 2098 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2099 | armnn::IWorkloadFactory& refWorkloadFactory) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2100 | { |
| 2101 | const unsigned int width = 16; |
| 2102 | const unsigned int height = 32; |
| 2103 | const unsigned int channelCount = 2; |
| 2104 | const unsigned int batchSize = 5; |
| 2105 | |
| 2106 | armnn::TensorInfo inputTensorInfo0; |
| 2107 | armnn::TensorInfo inputTensorInfo1; |
| 2108 | armnn::TensorInfo outputTensorInfo; |
| 2109 | |
| 2110 | constexpr unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 2111 | |
| 2112 | inputTensorInfo0 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2113 | inputTensorInfo1 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2114 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2115 | |
| 2116 | LayerTestResult<float,4> comparisonResult(outputTensorInfo); |
| 2117 | |
| 2118 | auto input0 = MakeRandomTensor<float, 4>(inputTensorInfo0, 803506992); |
| 2119 | auto input1 = MakeRandomTensor<float, 4>(inputTensorInfo1, 54902257); |
| 2120 | |
| 2121 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 2122 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 2123 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2124 | |
| 2125 | std::unique_ptr<armnn::ITensorHandle> inputHandle0Ref = refWorkloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 2126 | std::unique_ptr<armnn::ITensorHandle> inputHandle1Ref = refWorkloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 2127 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2128 | |
| 2129 | armnn::MultiplicationQueueDescriptor data; |
| 2130 | armnn::WorkloadInfo info; |
| 2131 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 2132 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 2133 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2134 | |
| 2135 | armnn::MultiplicationQueueDescriptor refData = data; |
| 2136 | armnn::WorkloadInfo refInfo = info; |
| 2137 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo0, inputHandle0Ref.get()); |
| 2138 | SetWorkloadInput(refData, refInfo, 1, inputTensorInfo1, inputHandle1Ref.get()); |
| 2139 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 2140 | |
| 2141 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMultiplication(data, info); |
| 2142 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateMultiplication(refData, refInfo); |
| 2143 | |
| 2144 | inputHandle0->Allocate(); |
| 2145 | inputHandle1->Allocate(); |
| 2146 | outputHandle->Allocate(); |
| 2147 | inputHandle0Ref->Allocate(); |
| 2148 | inputHandle1Ref->Allocate(); |
| 2149 | outputHandleRef->Allocate(); |
| 2150 | |
| 2151 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 2152 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 2153 | CopyDataToITensorHandle(inputHandle0Ref.get(), &input0[0][0][0][0]); |
| 2154 | CopyDataToITensorHandle(inputHandle1Ref.get(), &input1[0][0][0][0]); |
| 2155 | |
| 2156 | workload->Execute(); |
| 2157 | workloadRef->Execute(); |
| 2158 | |
| 2159 | CopyDataFromITensorHandle(&comparisonResult.output[0][0][0][0], outputHandle.get()); |
| 2160 | CopyDataFromITensorHandle(&comparisonResult.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 2161 | |
| 2162 | return comparisonResult; |
| 2163 | } |
| 2164 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2165 | LayerTestResult<float,4> CompareBatchNormTest( |
| 2166 | armnn::IWorkloadFactory& workloadFactory, |
| 2167 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2168 | armnn::IWorkloadFactory& refWorkloadFactory) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2169 | { |
| 2170 | const unsigned int width = 2; |
| 2171 | const unsigned int height = 3; |
| 2172 | const unsigned int channels = 5; |
| 2173 | const unsigned int batchSize = 3; |
| 2174 | |
| 2175 | armnn::TensorInfo inputTensorInfo; |
| 2176 | armnn::TensorInfo outputTensorInfo; |
| 2177 | armnn::TensorInfo tensorInfo; |
| 2178 | |
| 2179 | constexpr unsigned int shape[] = {batchSize, channels, height, width}; |
| 2180 | constexpr unsigned int tensorShape[] = {channels}; |
| 2181 | |
| 2182 | inputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2183 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2184 | tensorInfo = armnn::TensorInfo(1, tensorShape, armnn::DataType::Float32); |
| 2185 | |
| 2186 | auto input = MakeRandomTensor<float, 4>(inputTensorInfo, 21312); |
| 2187 | |
| 2188 | auto mean = MakeRandomTensor<float, 1>(tensorInfo, 123); |
| 2189 | auto variance = MakeRandomTensor<float, 1>(tensorInfo, 234, 0.0f); |
| 2190 | auto beta = MakeRandomTensor<float, 1>(tensorInfo, 123); |
| 2191 | auto gamma = MakeRandomTensor<float, 1>(tensorInfo, 345); |
| 2192 | |
| 2193 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 2194 | |
| 2195 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 2196 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2197 | |
| 2198 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refWorkloadFactory.CreateTensorHandle(inputTensorInfo); |
| 2199 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2200 | |
| 2201 | armnn::BatchNormalizationQueueDescriptor data; |
| 2202 | armnn::WorkloadInfo info; |
| 2203 | armnn::ScopedCpuTensorHandle meanTensor(tensorInfo); |
| 2204 | armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo); |
| 2205 | armnn::ScopedCpuTensorHandle betaTensor(tensorInfo); |
| 2206 | armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo); |
| 2207 | |
| 2208 | AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]); |
| 2209 | AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]); |
| 2210 | AllocateAndCopyDataToITensorHandle(&betaTensor, &beta[0]); |
| 2211 | AllocateAndCopyDataToITensorHandle(&gammaTensor, &gamma[0]); |
| 2212 | |
| 2213 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 2214 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2215 | data.m_Mean = &meanTensor; |
| 2216 | data.m_Variance = &varianceTensor; |
| 2217 | data.m_Beta = &betaTensor; |
| 2218 | data.m_Gamma = &gammaTensor; |
| 2219 | data.m_Parameters.m_Eps = 0.01f; |
| 2220 | |
| 2221 | armnn::BatchNormalizationQueueDescriptor refData = data; |
| 2222 | armnn::WorkloadInfo refInfo = info; |
| 2223 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 2224 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 2225 | |
| 2226 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(data, info); |
| 2227 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateBatchNormalization(refData, refInfo); |
| 2228 | |
| 2229 | inputHandle->Allocate(); |
| 2230 | outputHandle->Allocate(); |
| 2231 | inputHandleRef->Allocate(); |
| 2232 | outputHandleRef->Allocate(); |
| 2233 | |
| 2234 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 2235 | CopyDataToITensorHandle(inputHandleRef.get(), &input[0][0][0][0]); |
| 2236 | |
| 2237 | workload->Execute(); |
| 2238 | workloadRef->Execute(); |
| 2239 | |
| 2240 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 2241 | CopyDataFromITensorHandle(&ret.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 2242 | |
| 2243 | return ret; |
| 2244 | } |
| 2245 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2246 | template<typename T> |
| 2247 | void PermuteTensorData( |
| 2248 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2249 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2250 | const armnn::PermutationVector& mappings, |
| 2251 | armnn::TensorInfo & inputTensorInfo, |
| 2252 | const T * inputData, |
| 2253 | std::vector<T>& outputData) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2254 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2255 | BOOST_ASSERT_MSG(inputData != nullptr, "inputData must not be null"); |
| 2256 | if (inputData == nullptr) |
| 2257 | { |
| 2258 | // Nullptr is an error in the test. By returning without doing the concatenation |
| 2259 | // I expect the caller to fail the test. It still makes sense to report this as |
| 2260 | // an assert for Debug builds. |
| 2261 | return; |
| 2262 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2263 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2264 | armnn::TensorInfo outputTensorInfo = armnnUtils::Permuted(inputTensorInfo, mappings); |
| 2265 | |
| 2266 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 2267 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2268 | |
| 2269 | armnn::PermuteQueueDescriptor queueDescriptor; |
| 2270 | queueDescriptor.m_Parameters = armnn::PermuteDescriptor{mappings}; |
| 2271 | armnn::WorkloadInfo workloadInfo; |
| 2272 | AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 2273 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 2274 | |
| 2275 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePermute(queueDescriptor, workloadInfo); |
| 2276 | |
| 2277 | inputHandle->Allocate(); |
| 2278 | outputHandle->Allocate(); |
| 2279 | |
| 2280 | CopyDataToITensorHandle(inputHandle.get(), inputData); |
| 2281 | |
| 2282 | workload->Execute(); |
| 2283 | |
| 2284 | outputData.resize(outputTensorInfo.GetNumElements()); |
| 2285 | CopyDataFromITensorHandle(&outputData[0], outputHandle.get()); |
| 2286 | inputTensorInfo = outputTensorInfo; |
| 2287 | } |
| 2288 | |
| 2289 | armnn::OriginsDescriptor CreateMergerDescriptorForConcatenation( |
| 2290 | const std::vector<armnn::TensorInfo> & inputTensorInfos, |
| 2291 | unsigned int concatDim) |
| 2292 | { |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2293 | std::vector<armnn::TensorShape> shapes; |
| 2294 | shapes.reserve(inputTensorInfos.size()); |
| 2295 | for (const armnn::TensorInfo& it: inputTensorInfos) |
| 2296 | { |
| 2297 | shapes.push_back(it.GetShape()); |
| 2298 | } |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2299 | |
| 2300 | return armnn::CreateMergerDescriptorForConcatenation(shapes.begin(), |
| 2301 | shapes.end(), |
| 2302 | concatDim); |
| 2303 | } |
| 2304 | |
| 2305 | // |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2306 | // Concatenation is only supported for N and C dimensions for NCHW and the inner most dimension |
| 2307 | // In case of <4 dimensions we need to make sure that the concat dimensions are at least |
| 2308 | // the 3rd slowest iterating one or the inner most dimension. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2309 | // |
| 2310 | |
| 2311 | bool NeedPermuteForConcat( |
| 2312 | const std::vector<armnn::TensorInfo> & inputTensorInfos, |
| 2313 | unsigned int concatDim) |
| 2314 | { |
| 2315 | // See note above. Additionally we expect the input shapes to have the |
| 2316 | // same number of dimensions. |
| 2317 | unsigned int nDimensions = 0; |
| 2318 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2319 | // Determine the number of dimensions as well as sanity check them |
| 2320 | // agains test implementation issues. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2321 | for (auto && tensorInfo : inputTensorInfos) |
| 2322 | { |
| 2323 | if (!nDimensions) |
| 2324 | { |
| 2325 | nDimensions = tensorInfo.GetShape().GetNumDimensions(); |
| 2326 | } |
| 2327 | else |
| 2328 | { |
| 2329 | BOOST_ASSERT_MSG(nDimensions == tensorInfo.GetShape().GetNumDimensions(), |
| 2330 | "Input shapes must have the same number of dimensions"); |
| 2331 | } |
| 2332 | } |
| 2333 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2334 | return (nDimensions < 3 || (nDimensions == 3 && (nDimensions-concatDim) < 3 && (nDimensions-concatDim) != 1)); |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2335 | } |
| 2336 | |
| 2337 | armnn::TensorShape ExpandTensorShapeTo3dForPermute(const armnn::TensorShape & inputShape) |
| 2338 | { |
| 2339 | unsigned int numDims = inputShape.GetNumDimensions(); |
| 2340 | if (numDims >= 3) |
| 2341 | { |
| 2342 | // Nothing to do if the inputShape has at least 3 dimensions. |
| 2343 | return inputShape; |
| 2344 | } |
| 2345 | |
| 2346 | std::vector<unsigned int> newDims(size_t(3), 1u); |
| 2347 | unsigned int expandedBy = 3 - numDims; |
| 2348 | for (unsigned int i=0; i<numDims; ++i) |
| 2349 | { |
| 2350 | newDims[expandedBy+i] = inputShape[i]; |
| 2351 | } |
| 2352 | return armnn::TensorShape(3u, &newDims[0]); |
| 2353 | } |
| 2354 | |
| 2355 | void Generate3dPermuteVectorForConcat( |
| 2356 | unsigned int numDimensions, |
| 2357 | unsigned int & concatDim, |
| 2358 | std::pair<armnn::PermutationVector, armnn::PermutationVector> & permutations) |
| 2359 | { |
| 2360 | BOOST_ASSERT_MSG(numDimensions <= 3, |
| 2361 | "Only dimensions 1,2 and 3 are supported by this helper"); |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2362 | unsigned int expandedBy = 3 - numDimensions; |
| 2363 | unsigned int expandedConcatAxis = concatDim + expandedBy; |
| 2364 | |
| 2365 | if (expandedConcatAxis == 2) |
| 2366 | { |
| 2367 | concatDim = 0; |
| 2368 | armnn::PermutationVector forwardPermutation({1, 2, 0}); |
| 2369 | armnn::PermutationVector reversePermutation({2, 0, 1}); |
| 2370 | permutations = std::make_pair(forwardPermutation, reversePermutation); |
| 2371 | } |
| 2372 | else if (expandedConcatAxis == 1) |
| 2373 | { |
| 2374 | concatDim = 0; |
| 2375 | armnn::PermutationVector forwardPermutation({2, 0, 1}); |
| 2376 | armnn::PermutationVector reversePermutation({1, 2, 0}); |
| 2377 | permutations = std::make_pair(forwardPermutation, reversePermutation); |
| 2378 | } |
| 2379 | else |
| 2380 | { |
| 2381 | BOOST_ASSERT(expandedConcatAxis == 0); |
| 2382 | concatDim = 0; |
| 2383 | } |
| 2384 | } |
| 2385 | |
| 2386 | // |
| 2387 | // Permute the input tensors so we can do a supported concatenation. |
| 2388 | // Also treat lower than 3d tensors as 3d by adding dummy 1 dimensions |
| 2389 | // at the front. Finally this function tells what the output shape |
| 2390 | // of the permuted concatenated tensor is going to be. |
| 2391 | // |
| 2392 | template <typename T> |
| 2393 | void PermuteInputsForConcat( |
| 2394 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2395 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2396 | std::vector<armnn::TensorInfo> & inputTensorInfos, |
| 2397 | std::vector<T *> & inputData, |
| 2398 | std::vector<std::vector<T>> & inputDataStorage, |
| 2399 | armnn::PermutationVector & permuteVector, |
| 2400 | unsigned int & concatDim, |
| 2401 | armnn::TensorInfo & outputTensorInfo) |
| 2402 | { |
| 2403 | BOOST_ASSERT_MSG(inputTensorInfos.size() > 1, |
| 2404 | "Expecting more than one tensor to be concatenated here"); |
| 2405 | |
| 2406 | unsigned int numDims = 0; |
| 2407 | unsigned int nthInput = 0; |
| 2408 | const armnn::PermutationVector identity({0, 1, 2}); |
| 2409 | |
| 2410 | std::pair<armnn::PermutationVector, armnn::PermutationVector> permutations = |
| 2411 | std::make_pair(identity, identity); |
| 2412 | |
| 2413 | inputDataStorage.resize(inputData.size()); |
| 2414 | |
| 2415 | for (auto && tensorInfo : inputTensorInfos) |
| 2416 | { |
| 2417 | if (numDims == 0) |
| 2418 | { |
| 2419 | numDims = tensorInfo.GetShape().GetNumDimensions(); |
| 2420 | Generate3dPermuteVectorForConcat(numDims, concatDim, permutations); |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2421 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2422 | // Store the reverese permutation. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2423 | permuteVector = permutations.second; |
| 2424 | BOOST_ASSERT_MSG(!permuteVector.IsEqual(identity), |
| 2425 | "Test logic error, we don't need permutation, so we shouldn't arrive here"); |
| 2426 | } |
| 2427 | else |
| 2428 | { |
| 2429 | BOOST_ASSERT_MSG(numDims == tensorInfo.GetShape().GetNumDimensions(), |
| 2430 | "All inputs must have the same number of dimensions"); |
| 2431 | } |
| 2432 | |
| 2433 | armnn::TensorInfo newTensorInfo = tensorInfo; |
| 2434 | newTensorInfo.SetShape(ExpandTensorShapeTo3dForPermute(tensorInfo.GetShape())); |
| 2435 | |
| 2436 | PermuteTensorData<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2437 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2438 | permutations.first, |
| 2439 | newTensorInfo, |
| 2440 | inputData[nthInput], |
| 2441 | inputDataStorage[nthInput]); |
| 2442 | |
| 2443 | inputData[nthInput] = inputDataStorage[nthInput].data(); |
| 2444 | inputTensorInfos[nthInput] = newTensorInfo; |
| 2445 | |
| 2446 | ++nthInput; |
| 2447 | } |
| 2448 | |
| 2449 | outputTensorInfo.SetShape( |
| 2450 | armnnUtils::Permuted( |
| 2451 | ExpandTensorShapeTo3dForPermute(outputTensorInfo.GetShape()), |
| 2452 | permutations.first)); |
| 2453 | } |
| 2454 | |
| 2455 | |
| 2456 | // |
| 2457 | // This is the pair of PermuteInputsForConcat(...) which permutes back |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2458 | // the output of the concatenation so we can check it against an expected |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2459 | // output. |
| 2460 | // |
| 2461 | template <typename T> |
| 2462 | void PermuteOutputForConcat( |
| 2463 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2464 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2465 | const armnn::TensorInfo & tensorInfo, |
| 2466 | const armnn::PermutationVector & permuteVector, |
| 2467 | std::unique_ptr<armnn::ITensorHandle> && inputDataHandle, |
| 2468 | T * data) |
| 2469 | { |
| 2470 | BOOST_ASSERT_MSG(data != nullptr, "data must not be null"); |
| 2471 | if (data == nullptr) |
| 2472 | { |
| 2473 | // Nullptr is an error in the test. By returning without doing the permutation |
| 2474 | // I expect the caller to fail the test. It still makes sense to report this as |
| 2475 | // an assert for Debug builds. |
| 2476 | return; |
| 2477 | } |
| 2478 | |
| 2479 | armnn::TensorInfo resultTensorInfo = tensorInfo; |
| 2480 | std::vector<T> inputData(tensorInfo.GetNumElements()); |
| 2481 | std::vector<T> outputData; |
| 2482 | |
| 2483 | CopyDataFromITensorHandle(&inputData[0], inputDataHandle.get()); |
| 2484 | |
| 2485 | PermuteTensorData<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2486 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2487 | permuteVector, |
| 2488 | resultTensorInfo, |
| 2489 | &inputData[0], |
| 2490 | outputData); |
| 2491 | |
| 2492 | ::memcpy(data, &outputData[0], sizeof(T)*outputData.size()); |
| 2493 | } |
| 2494 | |
| 2495 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2496 | void Concatenate( |
| 2497 | armnn::IWorkloadFactory& workloadFactory, |
| 2498 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2499 | std::initializer_list<const armnn::TensorInfo> inputTensorInfosOrig, |
| 2500 | std::initializer_list<T *> inputsOrig, |
| 2501 | const armnn::TensorInfo& outputTensorInfoOrig, |
| 2502 | T * output, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2503 | unsigned int concatDim, |
| 2504 | bool useSubtensor) |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2505 | { |
| 2506 | BOOST_ASSERT_MSG(output != nullptr, "output must not be null"); |
| 2507 | if (output == nullptr) |
| 2508 | { |
| 2509 | // Nullptr is an error in the test. By returning without doing the permutation |
| 2510 | // I expect the caller to fail the test. It still makes sense to report this as |
| 2511 | // an assert for Debug builds. |
| 2512 | return; |
| 2513 | } |
| 2514 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2515 | // Saves a copy of the parameters which we might need to change. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2516 | std::vector<armnn::TensorInfo> inputTensorInfos(inputTensorInfosOrig.begin(), inputTensorInfosOrig.end()); |
| 2517 | std::vector<T *> inputs = inputsOrig; |
| 2518 | armnn::TensorInfo outputTensorInfo = outputTensorInfoOrig; |
| 2519 | |
| 2520 | armnn::PermutationVector permuteVector{0, 1, 2}; |
| 2521 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2522 | // Holds and automatically releases memory for the reshaped input data. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2523 | std::vector<std::vector<T>> tmpInputDataStorage; |
| 2524 | |
| 2525 | const size_t inputCount = inputTensorInfos.size(); |
| 2526 | |
| 2527 | bool needPermuteForConcat = NeedPermuteForConcat(inputTensorInfos, concatDim); |
| 2528 | |
| 2529 | if (needPermuteForConcat) |
| 2530 | { |
| 2531 | // |
| 2532 | // We need to permute the inputs, because concatenation along |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2533 | // the requested axis is not supported. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2534 | // |
| 2535 | PermuteInputsForConcat<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2536 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2537 | inputTensorInfos, |
| 2538 | inputs, |
| 2539 | tmpInputDataStorage, |
| 2540 | permuteVector, |
| 2541 | concatDim, |
| 2542 | outputTensorInfo); |
| 2543 | } |
| 2544 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2545 | armnn::WorkloadInfo workloadInfo; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2546 | |
| 2547 | std::vector<std::unique_ptr<armnn::ITensorHandle>> inputHandles; |
| 2548 | inputHandles.reserve(inputCount); |
| 2549 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2550 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2551 | |
| 2552 | armnn::MergerQueueDescriptor queueDescriptor; |
| 2553 | armnn::OriginsDescriptor viewsDescriptor = CreateMergerDescriptorForConcatenation(inputTensorInfos, concatDim); |
| 2554 | queueDescriptor.m_Parameters = viewsDescriptor; |
| 2555 | |
| 2556 | if (useSubtensor) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2557 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2558 | queueDescriptor.m_ViewOrigins.reserve(viewsDescriptor.GetNumViews()); |
| 2559 | for (unsigned int i = 0; i < viewsDescriptor.GetNumViews(); ++i) |
| 2560 | { |
| 2561 | queueDescriptor.m_ViewOrigins.emplace_back(std::vector<unsigned int>(viewsDescriptor.GetViewOrigin(i), |
| 2562 | viewsDescriptor.GetViewOrigin(i) + viewsDescriptor.GetNumDimensions())); |
| 2563 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2564 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2565 | outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2566 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2567 | const bool subTensorsSupported = workloadFactory.SupportsSubTensors(); |
| 2568 | for (unsigned int i = 0; i < inputCount; ++i) |
| 2569 | { |
| 2570 | const armnn::TensorInfo& inputTensorInfo = inputTensorInfos[i]; |
| 2571 | std::unique_ptr<armnn::ITensorHandle> inputHandle = |
| 2572 | subTensorsSupported ? |
| 2573 | workloadFactory.CreateSubTensorHandle(*outputHandle, |
| 2574 | inputTensorInfo.GetShape(), |
| 2575 | queueDescriptor.m_ViewOrigins[i].m_Origin.data()) : |
| 2576 | workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 2577 | |
| 2578 | inputHandles.emplace_back(std::move(inputHandle)); |
| 2579 | } |
| 2580 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2581 | } |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2582 | else |
| 2583 | { |
| 2584 | for (unsigned int i = 0; i < inputCount; ++i) |
| 2585 | { |
| 2586 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfos[i]); |
| 2587 | inputHandles.emplace_back(std::move(inputHandle)); |
| 2588 | } |
| 2589 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2590 | |
| 2591 | for (unsigned int i = 0; i < inputCount; ++i) |
| 2592 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2593 | AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfos[i], inputHandles[i].get()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2594 | } |
| 2595 | |
| 2596 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 2597 | |
| 2598 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMerger(queueDescriptor, workloadInfo); |
| 2599 | |
| 2600 | for (auto& inputHandle : inputHandles) |
| 2601 | { |
| 2602 | inputHandle->Allocate(); |
| 2603 | } |
| 2604 | |
| 2605 | outputHandle->Allocate(); |
| 2606 | |
| 2607 | unsigned int nextInputId = 0; |
| 2608 | for (auto& inputHandle : inputHandles) |
| 2609 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2610 | CopyDataToITensorHandle(inputHandle.get(), inputs[nextInputId]); |
| 2611 | ++nextInputId; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2612 | } |
| 2613 | |
| 2614 | workload->Execute(); |
| 2615 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2616 | if (needPermuteForConcat) |
| 2617 | { |
| 2618 | PermuteOutputForConcat<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2619 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2620 | outputTensorInfo, |
| 2621 | permuteVector, |
| 2622 | std::move(outputHandle), |
| 2623 | output); |
| 2624 | } |
| 2625 | else |
| 2626 | { |
| 2627 | CopyDataFromITensorHandle(output, outputHandle.get()); |
| 2628 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2629 | } |
| 2630 | |
| 2631 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2632 | LayerTestResult<T, 1> Concatenation1dTestImpl( |
| 2633 | armnn::IWorkloadFactory& workloadFactory, |
| 2634 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2635 | float qScale, |
| 2636 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2637 | { |
| 2638 | armnn::TensorInfo inputTensorInfo({ 3 }, armnn::GetDataType<T>()); |
| 2639 | |
| 2640 | auto input0 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 1.0f, 2.0f, 3.0f })); |
| 2641 | auto input1 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 4.0f, 5.0f, 6.0f })); |
| 2642 | auto input2 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 7.0f, 8.0f, 9.0f })); |
| 2643 | |
| 2644 | armnn::TensorInfo outputTensorInfo({ 9 }, armnn::GetDataType<T>()); |
| 2645 | |
| 2646 | LayerTestResult<T, 1> result(outputTensorInfo); |
| 2647 | |
| 2648 | std::vector<T> output; |
| 2649 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2650 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2651 | { inputTensorInfo, inputTensorInfo, inputTensorInfo }, |
| 2652 | { input0.data(), input1.data(), input2.data() }, |
| 2653 | outputTensorInfo, |
| 2654 | output.data(), |
| 2655 | 0, |
| 2656 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2657 | |
| 2658 | result.output = MakeTensor<T, 1>(outputTensorInfo, output); |
| 2659 | result.outputExpected = MakeTensor<T, 1>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2660 | 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f |
| 2661 | })); |
| 2662 | |
| 2663 | return result; |
| 2664 | } |
| 2665 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2666 | LayerTestResult<float, 1> Concatenation1dTest( |
| 2667 | armnn::IWorkloadFactory& workloadFactory, |
| 2668 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2669 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2670 | return Concatenation1dTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2671 | } |
| 2672 | |
| 2673 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2674 | LayerTestResult<T, 2> Concatenation2dTestImpl( |
| 2675 | armnn::IWorkloadFactory& workloadFactory, |
| 2676 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2677 | const armnn::TensorInfo& outputTensorInfo, |
| 2678 | unsigned int dimension, |
| 2679 | const float qScale, |
| 2680 | const int32_t qOffset) |
| 2681 | { |
| 2682 | armnn::TensorInfo inputTensorInfo({ 2, 3 }, armnn::GetDataType<T>()); |
| 2683 | |
| 2684 | auto input0 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2685 | // Batch 0 |
| 2686 | 1.0f, 2.0f, 3.0f, |
| 2687 | |
| 2688 | // Batch 1 |
| 2689 | 10.0f, 11.0f, 12.0f, |
| 2690 | })); |
| 2691 | |
| 2692 | auto input1 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2693 | // Batch 0 |
| 2694 | 4.0f, 5.0f, 6.0f, |
| 2695 | |
| 2696 | // Batch 1 |
| 2697 | 13.0f, 14.0f, 15.0f, |
| 2698 | })); |
| 2699 | |
| 2700 | auto input2 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2701 | // Batch 0 |
| 2702 | 7.0f, 8.0f, 9.0f, |
| 2703 | |
| 2704 | // Batch 1 |
| 2705 | 16.0f, 17.0f, 18.0f, |
| 2706 | })); |
| 2707 | |
| 2708 | LayerTestResult<T, 2> result(outputTensorInfo); |
| 2709 | |
| 2710 | std::vector<T> output; |
| 2711 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2712 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2713 | { inputTensorInfo, inputTensorInfo, inputTensorInfo }, |
| 2714 | { input0.data(), input1.data(), input2.data() }, |
| 2715 | outputTensorInfo, |
| 2716 | output.data(), |
| 2717 | dimension, |
| 2718 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2719 | |
| 2720 | result.output = MakeTensor<T, 2>(outputTensorInfo, output); |
| 2721 | return result; |
| 2722 | } |
| 2723 | |
| 2724 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2725 | LayerTestResult<T, 2> Concatenation2dDim0TestImpl( |
| 2726 | armnn::IWorkloadFactory& workloadFactory, |
| 2727 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2728 | float qScale, |
| 2729 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2730 | { |
| 2731 | armnn::TensorInfo outputTensorInfo({ 6, 3 }, armnn::GetDataType<T>()); |
| 2732 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2733 | LayerTestResult<T, 2> result = |
| 2734 | Concatenation2dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 0, qScale, qOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2735 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2736 | // Batch 0 |
| 2737 | 1.0f, 2.0f, 3.0f, |
| 2738 | |
| 2739 | // Batch 1 |
| 2740 | 10.0f, 11.0f, 12.0f, |
| 2741 | |
| 2742 | // Batch 2 |
| 2743 | 4.0f, 5.0f, 6.0f, |
| 2744 | |
| 2745 | // Batch 3 |
| 2746 | 13.0f, 14.0f, 15.0f, |
| 2747 | |
| 2748 | // Batch 4 |
| 2749 | 7.0f, 8.0f, 9.0f, |
| 2750 | |
| 2751 | // Batch 5 |
| 2752 | 16.0f, 17.0f, 18.0f, |
| 2753 | })); |
| 2754 | |
| 2755 | return result; |
| 2756 | } |
| 2757 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2758 | LayerTestResult<float, 2> Concatenation2dDim0Test( |
| 2759 | armnn::IWorkloadFactory& workloadFactory, |
| 2760 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2761 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2762 | return Concatenation2dDim0TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2763 | } |
| 2764 | |
| 2765 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2766 | LayerTestResult<T, 2> Concatenation2dDim1TestImpl( |
| 2767 | armnn::IWorkloadFactory& workloadFactory, |
| 2768 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2769 | float qScale, |
| 2770 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2771 | { |
| 2772 | armnn::TensorInfo outputTensorInfo({ 2, 9 }, armnn::GetDataType<T>()); |
| 2773 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2774 | LayerTestResult<T, 2> result = |
| 2775 | Concatenation2dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 1, qScale, qOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2776 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2777 | // Batch 0 |
| 2778 | 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, |
| 2779 | |
| 2780 | // Batch 1 |
| 2781 | 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f |
| 2782 | })); |
| 2783 | |
| 2784 | return result; |
| 2785 | } |
| 2786 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2787 | LayerTestResult<float, 2> Concatenation2dDim1Test( |
| 2788 | armnn::IWorkloadFactory& workloadFactory, |
| 2789 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2790 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2791 | return Concatenation2dDim1TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2792 | } |
| 2793 | |
| 2794 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2795 | LayerTestResult<T, 2> Concatenation2dDim0DiffInputDimsTestImpl( |
| 2796 | armnn::IWorkloadFactory& workloadFactory, |
| 2797 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2798 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2799 | int32_t qOffset) |
| 2800 | { |
| 2801 | armnn::TensorInfo input0TensorInfo({ 2, 3 }, armnn::GetDataType<T>()); |
| 2802 | auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2803 | // Batch 0 |
| 2804 | 1.0f, 2.0f, 3.0f, |
| 2805 | |
| 2806 | // Batch 1 |
| 2807 | 10.0f, 11.0f, 12.0f, |
| 2808 | })); |
| 2809 | |
| 2810 | armnn::TensorInfo input1TensorInfo({ 3, 3 }, armnn::GetDataType<T>()); |
| 2811 | auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2812 | // Batch 0 |
| 2813 | 4.0f, 5.0f, 6.0f, |
| 2814 | |
| 2815 | // Batch 1 |
| 2816 | 13.0f, 14.0f, 15.0f, |
| 2817 | |
| 2818 | // Batch 0 |
| 2819 | 7.0f, 8.0f, 9.0f, |
| 2820 | })); |
| 2821 | |
| 2822 | armnn::TensorInfo input2TensorInfo({ 1, 3 }, armnn::GetDataType<T>()); |
| 2823 | auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2824 | // Batch 1 |
| 2825 | 16.0f, 17.0f, 18.0f, |
| 2826 | })); |
| 2827 | |
| 2828 | armnn::TensorInfo outputTensorInfo({ 6, 3 }, armnn::GetDataType<T>()); |
| 2829 | LayerTestResult<T, 2> result(outputTensorInfo); |
| 2830 | |
| 2831 | std::vector<T> output; |
| 2832 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2833 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2834 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 2835 | { input0.data(), input1.data(), input2.data() }, |
| 2836 | outputTensorInfo, |
| 2837 | output.data(), |
| 2838 | 0, |
| 2839 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2840 | |
| 2841 | result.output = MakeTensor<T, 2>(outputTensorInfo, output); |
| 2842 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2843 | // Batch 0 |
| 2844 | 1.0f, 2.0f, 3.0f, |
| 2845 | |
| 2846 | // Batch 1 |
| 2847 | 10.0f, 11.0f, 12.0f, |
| 2848 | |
| 2849 | // Batch 2 |
| 2850 | 4.0f, 5.0f, 6.0f, |
| 2851 | |
| 2852 | // Batch 3 |
| 2853 | 13.0f, 14.0f, 15.0f, |
| 2854 | |
| 2855 | // Batch 4 |
| 2856 | 7.0f, 8.0f, 9.0f, |
| 2857 | |
| 2858 | // Batch 5 |
| 2859 | 16.0f, 17.0f, 18.0f, |
| 2860 | })); |
| 2861 | |
| 2862 | return result; |
| 2863 | } |
| 2864 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2865 | LayerTestResult<float, 2> Concatenation2dDim0DiffInputDimsTest( |
| 2866 | armnn::IWorkloadFactory& workloadFactory, |
| 2867 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2868 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2869 | return Concatenation2dDim0DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2870 | } |
| 2871 | |
| 2872 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2873 | LayerTestResult<T, 2> Concatenation2dDim1DiffInputDimsTestImpl( |
| 2874 | armnn::IWorkloadFactory& workloadFactory, |
| 2875 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2876 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2877 | int32_t qOffset) |
| 2878 | { |
| 2879 | armnn::TensorInfo input0TensorInfo({ 2, 3 }, armnn::GetDataType<T>()); |
| 2880 | auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2881 | // Batch 0 |
| 2882 | 1.0f, 2.0f, 3.0f, |
| 2883 | |
| 2884 | // Batch 1 |
| 2885 | 10.0f, 11.0f, 12.0f, |
| 2886 | })); |
| 2887 | |
| 2888 | armnn::TensorInfo input1TensorInfo({ 2, 5 }, armnn::GetDataType<T>()); |
| 2889 | auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2890 | // Batch 0 |
| 2891 | 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, |
| 2892 | |
| 2893 | // Batch 1 |
| 2894 | 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, |
| 2895 | })); |
| 2896 | |
| 2897 | armnn::TensorInfo input2TensorInfo({ 2, 1 }, armnn::GetDataType<T>()); |
| 2898 | auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2899 | // Batch 0 |
| 2900 | 9.0f, |
| 2901 | |
| 2902 | // Batch 1 |
| 2903 | 18.0f |
| 2904 | })); |
| 2905 | |
| 2906 | armnn::TensorInfo outputTensorInfo({ 2, 9 }, armnn::GetDataType<T>()); |
| 2907 | LayerTestResult<T, 2> result(outputTensorInfo); |
| 2908 | |
| 2909 | std::vector<T> output; |
| 2910 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2911 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2912 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 2913 | { input0.data(), input1.data(), input2.data() }, |
| 2914 | outputTensorInfo, |
| 2915 | output.data(), |
| 2916 | 1, |
| 2917 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2918 | |
| 2919 | result.output = MakeTensor<T, 2>(outputTensorInfo, output); |
| 2920 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2921 | // Batch 0 |
| 2922 | 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, |
| 2923 | |
| 2924 | // Batch 1 |
| 2925 | 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, |
| 2926 | })); |
| 2927 | |
| 2928 | return result; |
| 2929 | } |
| 2930 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2931 | LayerTestResult<float, 2> Concatenation2dDim1DiffInputDimsTest( |
| 2932 | armnn::IWorkloadFactory& workloadFactory, |
| 2933 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2934 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2935 | return Concatenation2dDim1DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2936 | } |
| 2937 | |
| 2938 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2939 | LayerTestResult<T, 3> Concatenation3dTestImpl( |
| 2940 | armnn::IWorkloadFactory& workloadFactory, |
| 2941 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2942 | const armnn::TensorInfo& outputTensorInfo, |
| 2943 | unsigned int dimension, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2944 | bool useSubtensor, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2945 | float qScale, |
| 2946 | int32_t qOffset) |
| 2947 | { |
| 2948 | armnn::TensorInfo inputTensorInfo({ 2, 3, 2 }, armnn::GetDataType<T>()); |
| 2949 | |
| 2950 | auto input0 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2951 | // Batch 0, Channel 0 |
| 2952 | 1.0f, 2.0f, |
| 2953 | |
| 2954 | // Batch 0, Channel 1 |
| 2955 | 3.0f, 4.0f, |
| 2956 | |
| 2957 | // Batch 0, Channel 2 |
| 2958 | 5.0f, 6.0f, |
| 2959 | |
| 2960 | // Batch 1, Channel 0 |
| 2961 | 19.0f, 20.0f, |
| 2962 | |
| 2963 | // Batch 1, Channel 1 |
| 2964 | 21.0f, 22.0f, |
| 2965 | |
| 2966 | // Batch 1, Channel 2 |
| 2967 | 23.0f, 24.0f |
| 2968 | })); |
| 2969 | |
| 2970 | auto input1 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2971 | // Batch 0, Channel 0 |
| 2972 | 7.0f, 8.0f, |
| 2973 | |
| 2974 | // Batch 0, Channel 1 |
| 2975 | 9.0f, 10.0f, |
| 2976 | |
| 2977 | // Batch 0, Channel 2 |
| 2978 | 11.0f, 12.0f, |
| 2979 | |
| 2980 | // Batch 1, Channel 0 |
| 2981 | 25.0f, 26.0f, |
| 2982 | |
| 2983 | // Batch 1, Channel 1 |
| 2984 | 27.0f, 28.0f, |
| 2985 | |
| 2986 | // Batch 1, Channel 2 |
| 2987 | 29.0f, 30.0f |
| 2988 | })); |
| 2989 | |
| 2990 | auto input2 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 2991 | // Batch 0, Channel 0 |
| 2992 | 13.0f, 14.0f, |
| 2993 | |
| 2994 | // Batch 0, Channel 1 |
| 2995 | 15.0f, 16.0f, |
| 2996 | |
| 2997 | // Batch 0, Channel 2 |
| 2998 | 17.0f, 18.0f, |
| 2999 | |
| 3000 | // Batch 1, Channel 0 |
| 3001 | 31.0f, 32.0f, |
| 3002 | |
| 3003 | // Batch 1, Channel 1 |
| 3004 | 33.0f, 34.0f, |
| 3005 | |
| 3006 | // Batch 1, Channel 2 |
| 3007 | 35.0f, 36.0f |
| 3008 | })); |
| 3009 | |
| 3010 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 3011 | |
| 3012 | std::vector<T> output; |
| 3013 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3014 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3015 | { inputTensorInfo, inputTensorInfo, inputTensorInfo }, |
| 3016 | { input0.data(), input1.data(), input2.data() }, |
| 3017 | outputTensorInfo, |
| 3018 | output.data(), |
| 3019 | dimension, |
| 3020 | useSubtensor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3021 | |
| 3022 | result.output = MakeTensor<T, 3>(outputTensorInfo, output); |
| 3023 | return result; |
| 3024 | } |
| 3025 | |
| 3026 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3027 | LayerTestResult<T, 3> Concatenation3dDim0TestImpl( |
| 3028 | armnn::IWorkloadFactory& workloadFactory, |
| 3029 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3030 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3031 | int32_t qOffset) |
| 3032 | { |
| 3033 | armnn::TensorInfo outputTensorInfo({ 6, 3, 2 }, armnn::GetDataType<T>()); |
| 3034 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3035 | LayerTestResult<T, 3> result = |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3036 | Concatenation3dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 0, true, qScale, qOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3037 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3038 | // Batch 0, Channel 0 |
| 3039 | 1.0f, 2.0f, |
| 3040 | |
| 3041 | // Batch 0, Channel 1 |
| 3042 | 3.0f, 4.0f, |
| 3043 | |
| 3044 | // Batch 0, Channel 2 |
| 3045 | 5.0f, 6.0f, |
| 3046 | |
| 3047 | // Batch 1, Channel 0 |
| 3048 | 19.0f, 20.0f, |
| 3049 | |
| 3050 | // Batch 1, Channel 1 |
| 3051 | 21.0f, 22.0f, |
| 3052 | |
| 3053 | // Batch 1, Channel 2 |
| 3054 | 23.0f, 24.0f, |
| 3055 | |
| 3056 | // Batch 2, Channel 0 |
| 3057 | 7.0f, 8.0f, |
| 3058 | |
| 3059 | // Batch 2, Channel 1 |
| 3060 | 9.0f, 10.0f, |
| 3061 | |
| 3062 | // Batch 2, Channel 2 |
| 3063 | 11.0f, 12.0f, |
| 3064 | |
| 3065 | // Batch 3, Channel 0 |
| 3066 | 25.0f, 26.0f, |
| 3067 | |
| 3068 | // Batch 3, Channel 1 |
| 3069 | 27.0f, 28.0f, |
| 3070 | |
| 3071 | // Batch 3, Channel 2 |
| 3072 | 29.0f, 30.0f, |
| 3073 | |
| 3074 | // Batch 4, Channel 0 |
| 3075 | 13.0f, 14.0f, |
| 3076 | |
| 3077 | // Batch 4, Channel 1 |
| 3078 | 15.0f, 16.0f, |
| 3079 | |
| 3080 | // Batch 4, Channel 2 |
| 3081 | 17.0f, 18.0f, |
| 3082 | |
| 3083 | // Batch 5, Channel 0 |
| 3084 | 31.0f, 32.0f, |
| 3085 | |
| 3086 | // Batch 5, Channel 1 |
| 3087 | 33.0f, 34.0f, |
| 3088 | |
| 3089 | // Batch 5, Channel 2 |
| 3090 | 35.0f, 36.0f |
| 3091 | })); |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3092 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3093 | return result; |
| 3094 | } |
| 3095 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3096 | LayerTestResult<float, 3> Concatenation3dDim0Test( |
| 3097 | armnn::IWorkloadFactory& workloadFactory, |
| 3098 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3099 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3100 | return Concatenation3dDim0TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3101 | } |
| 3102 | |
| 3103 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3104 | LayerTestResult<T, 3> Concatenation3dDim1TestImpl( |
| 3105 | armnn::IWorkloadFactory& workloadFactory, |
| 3106 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3107 | float qScale, |
| 3108 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3109 | { |
| 3110 | armnn::TensorInfo outputTensorInfo({ 2, 9, 2 }, armnn::GetDataType<T>()); |
| 3111 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3112 | LayerTestResult<T, 3> result = |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3113 | Concatenation3dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 1, true, qScale, qOffset); |
| 3114 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3115 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3116 | // Batch 0, Channel 0 |
| 3117 | 1.0f, 2.0f, |
| 3118 | |
| 3119 | // Batch 0, Channel 1 |
| 3120 | 3.0f, 4.0f, |
| 3121 | |
| 3122 | // Batch 0, Channel 2 |
| 3123 | 5.0f, 6.0f, |
| 3124 | |
| 3125 | // Batch 0, Channel 3 |
| 3126 | 7.0f, 8.0f, |
| 3127 | |
| 3128 | // Batch 0, Channel 4 |
| 3129 | 9.0f, 10.0f, |
| 3130 | |
| 3131 | // Batch 0, Channel 5 |
| 3132 | 11.0f, 12.0f, |
| 3133 | |
| 3134 | // Batch 0, Channel 6 |
| 3135 | 13.0f, 14.0f, |
| 3136 | |
| 3137 | // Batch 0, Channel 7 |
| 3138 | 15.0f, 16.0f, |
| 3139 | |
| 3140 | // Batch 0, Channel 8 |
| 3141 | 17.0f, 18.0f, |
| 3142 | |
| 3143 | // Batch 1, Channel 0 |
| 3144 | 19.0f, 20.0f, |
| 3145 | |
| 3146 | // Batch 1, Channel 1 |
| 3147 | 21.0f, 22.0f, |
| 3148 | |
| 3149 | // Batch 1, Channel 2 |
| 3150 | 23.0f, 24.0f, |
| 3151 | |
| 3152 | // Batch 1, Channel 3 |
| 3153 | 25.0f, 26.0f, |
| 3154 | |
| 3155 | // Batch 1, Channel 4 |
| 3156 | 27.0f, 28.0f, |
| 3157 | |
| 3158 | // Batch 1, Channel 5 |
| 3159 | 29.0f, 30.0f, |
| 3160 | |
| 3161 | // Batch 1, Channel 6 |
| 3162 | 31.0f, 32.0f, |
| 3163 | |
| 3164 | // Batch 1, Channel 7 |
| 3165 | 33.0f, 34.0f, |
| 3166 | |
| 3167 | // Batch 1, Channel 8 |
| 3168 | 35.0f, 36.0f |
| 3169 | })); |
| 3170 | |
| 3171 | return result; |
| 3172 | } |
| 3173 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3174 | LayerTestResult<float, 3> Concatenation3dDim1Test( |
| 3175 | armnn::IWorkloadFactory& workloadFactory, |
| 3176 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3177 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3178 | return Concatenation3dDim1TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3179 | } |
| 3180 | |
| 3181 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3182 | LayerTestResult<T, 3> Concatenation3dDim2TestImpl( |
| 3183 | armnn::IWorkloadFactory& workloadFactory, |
| 3184 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3185 | bool useSubtensor, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3186 | float qScale, |
| 3187 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3188 | { |
| 3189 | armnn::TensorInfo outputTensorInfo({ 2, 3, 6 }, armnn::GetDataType<T>()); |
| 3190 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3191 | LayerTestResult<T, 3> result = |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3192 | Concatenation3dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 2, useSubtensor, qScale, qOffset); |
| 3193 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3194 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3195 | // Batch 0, Channel 0 |
| 3196 | 1.0f, 2.0f, 7.0f, 8.0f, 13.0f, 14.0f, |
| 3197 | |
| 3198 | // Batch 0, Channel 1 |
| 3199 | 3.0f, 4.0f, 9.0f, 10.0f, 15.0f, 16.0f, |
| 3200 | |
| 3201 | // Batch 0, Channel 2 |
| 3202 | 5.0f, 6.0f, 11.0f, 12.0f, 17.0f, 18.0f, |
| 3203 | |
| 3204 | // Batch 1, Channel 0 |
| 3205 | 19.0f, 20.0f, 25.0f, 26.0f, 31.0f, 32.0f, |
| 3206 | |
| 3207 | // Batch 1, Channel 1 |
| 3208 | 21.0f, 22.0f, 27.0f, 28.0f, 33.0f, 34.0f, |
| 3209 | |
| 3210 | // Batch 1, Channel 2 |
| 3211 | 23.0f, 24.0f, 29.0f, 30.0f, 35.0f, 36.0f, |
| 3212 | })); |
| 3213 | |
| 3214 | return result; |
| 3215 | } |
| 3216 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3217 | LayerTestResult<float, 3> Concatenation3dDim2Test( |
| 3218 | armnn::IWorkloadFactory& workloadFactory, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3219 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3220 | bool useSubtensor) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3221 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3222 | return Concatenation3dDim2TestImpl<float>(workloadFactory, memoryManager, useSubtensor, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3223 | } |
| 3224 | |
| 3225 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3226 | LayerTestResult<T, 3> Concatenation3dDim0DiffInputDimsTestImpl( |
| 3227 | armnn::IWorkloadFactory& workloadFactory, |
| 3228 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3229 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3230 | int32_t qOffset) |
| 3231 | { |
| 3232 | armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, armnn::GetDataType<T>()); |
| 3233 | auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3234 | // Batch 0, Channel 0 |
| 3235 | 1.0f, 2.0f, |
| 3236 | |
| 3237 | // Batch 0, Channel 1 |
| 3238 | 3.0f, 4.0f, |
| 3239 | |
| 3240 | // Batch 0, Channel 2 |
| 3241 | 5.0f, 6.0f, |
| 3242 | |
| 3243 | // Batch 1, Channel 0 |
| 3244 | 19.0f, 20.0f, |
| 3245 | |
| 3246 | // Batch 1, Channel 1 |
| 3247 | 21.0f, 22.0f, |
| 3248 | |
| 3249 | // Batch 1, Channel 2 |
| 3250 | 23.0f, 24.0f |
| 3251 | })); |
| 3252 | |
| 3253 | armnn::TensorInfo input1TensorInfo({ 1, 3, 2 }, armnn::GetDataType<T>()); |
| 3254 | auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3255 | // Batch 0, Channel 0 |
| 3256 | 7.0f, 8.0f, |
| 3257 | |
| 3258 | // Batch 0, Channel 1 |
| 3259 | 9.0f, 10.0f, |
| 3260 | |
| 3261 | // Batch 0, Channel 2 |
| 3262 | 11.0f, 12.0f, |
| 3263 | })); |
| 3264 | |
| 3265 | armnn::TensorInfo input2TensorInfo({ 3, 3, 2 }, armnn::GetDataType<T>()); |
| 3266 | auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3267 | // Batch 0, Channel 0 |
| 3268 | 25.0f, 26.0f, |
| 3269 | |
| 3270 | // Batch 0, Channel 1 |
| 3271 | 27.0f, 28.0f, |
| 3272 | |
| 3273 | // Batch 0, Channel 2 |
| 3274 | 29.0f, 30.0f, |
| 3275 | |
| 3276 | // Batch 1, Channel 0 |
| 3277 | 13.0f, 14.0f, |
| 3278 | |
| 3279 | // Batch 1, Channel 1 |
| 3280 | 15.0f, 16.0f, |
| 3281 | |
| 3282 | // Batch 1, Channel 2 |
| 3283 | 17.0f, 18.0f, |
| 3284 | |
| 3285 | // Batch 2, Channel 0 |
| 3286 | 31.0f, 32.0f, |
| 3287 | |
| 3288 | // Batch 2, Channel 1 |
| 3289 | 33.0f, 34.0f, |
| 3290 | |
| 3291 | // Batch 2, Channel 2 |
| 3292 | 35.0f, 36.0f |
| 3293 | })); |
| 3294 | |
| 3295 | armnn::TensorInfo outputTensorInfo({ 6, 3, 2 }, armnn::GetDataType<T>()); |
| 3296 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 3297 | |
| 3298 | std::vector<T> output; |
| 3299 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3300 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3301 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 3302 | { input0.data(), input1.data(), input2.data() }, |
| 3303 | outputTensorInfo, |
| 3304 | output.data(), |
| 3305 | 0, |
| 3306 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3307 | |
| 3308 | result.output = MakeTensor<T, 3>(outputTensorInfo, output); |
| 3309 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3310 | // Batch 0, Channel 0 |
| 3311 | 1.0f, 2.0f, |
| 3312 | |
| 3313 | // Batch 0, Channel 1 |
| 3314 | 3.0f, 4.0f, |
| 3315 | |
| 3316 | // Batch 0, Channel 2 |
| 3317 | 5.0f, 6.0f, |
| 3318 | |
| 3319 | // Batch 1, Channel 0 |
| 3320 | 19.0f, 20.0f, |
| 3321 | |
| 3322 | // Batch 1, Channel 1 |
| 3323 | 21.0f, 22.0f, |
| 3324 | |
| 3325 | // Batch 1, Channel 2 |
| 3326 | 23.0f, 24.0f, |
| 3327 | |
| 3328 | // Batch 2, Channel 0 |
| 3329 | 7.0f, 8.0f, |
| 3330 | |
| 3331 | // Batch 2, Channel 1 |
| 3332 | 9.0f, 10.0f, |
| 3333 | |
| 3334 | // Batch 2, Channel 2 |
| 3335 | 11.0f, 12.0f, |
| 3336 | |
| 3337 | // Batch 3, Channel 0 |
| 3338 | 25.0f, 26.0f, |
| 3339 | |
| 3340 | // Batch 3, Channel 1 |
| 3341 | 27.0f, 28.0f, |
| 3342 | |
| 3343 | // Batch 3, Channel 2 |
| 3344 | 29.0f, 30.0f, |
| 3345 | |
| 3346 | // Batch 4, Channel 0 |
| 3347 | 13.0f, 14.0f, |
| 3348 | |
| 3349 | // Batch 4, Channel 1 |
| 3350 | 15.0f, 16.0f, |
| 3351 | |
| 3352 | // Batch 4, Channel 2 |
| 3353 | 17.0f, 18.0f, |
| 3354 | |
| 3355 | // Batch 5, Channel 0 |
| 3356 | 31.0f, 32.0f, |
| 3357 | |
| 3358 | // Batch 5, Channel 1 |
| 3359 | 33.0f, 34.0f, |
| 3360 | |
| 3361 | // Batch 5, Channel 2 |
| 3362 | 35.0f, 36.0f |
| 3363 | })); |
| 3364 | |
| 3365 | return result; |
| 3366 | } |
| 3367 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3368 | LayerTestResult<float, 3> Concatenation3dDim0DiffInputDimsTest( |
| 3369 | armnn::IWorkloadFactory& workloadFactory, |
| 3370 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3371 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3372 | return Concatenation3dDim0DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3373 | } |
| 3374 | |
| 3375 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3376 | LayerTestResult<T, 3> Concatenation3dDim1DiffInputDimsTestImpl( |
| 3377 | armnn::IWorkloadFactory& workloadFactory, |
| 3378 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3379 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3380 | int32_t qOffset) |
| 3381 | { |
| 3382 | armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, armnn::GetDataType<T>()); |
| 3383 | auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3384 | // Batch 0, Channel 0 |
| 3385 | 1.0f, 2.0f, |
| 3386 | |
| 3387 | // Batch 0, Channel 1 |
| 3388 | 3.0f, 4.0f, |
| 3389 | |
| 3390 | // Batch 0, Channel 2 |
| 3391 | 5.0f, 6.0f, |
| 3392 | |
| 3393 | // Batch 1, Channel 0 |
| 3394 | 19.0f, 20.0f, |
| 3395 | |
| 3396 | // Batch 1, Channel 1 |
| 3397 | 21.0f, 22.0f, |
| 3398 | |
| 3399 | // Batch 1, Channel 2 |
| 3400 | 23.0f, 24.0f |
| 3401 | })); |
| 3402 | |
| 3403 | armnn::TensorInfo input1TensorInfo({ 2, 4, 2 }, armnn::GetDataType<T>()); |
| 3404 | auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3405 | // Batch 0, Channel 0 |
| 3406 | 7.0f, 8.0f, |
| 3407 | |
| 3408 | // Batch 0, Channel 1 |
| 3409 | 9.0f, 10.0f, |
| 3410 | |
| 3411 | // Batch 0, Channel 2 |
| 3412 | 11.0f, 12.0f, |
| 3413 | |
| 3414 | // Batch 0, Channel 3 |
| 3415 | 25.0f, 26.0f, |
| 3416 | |
| 3417 | // Batch 1, Channel 0 |
| 3418 | 27.0f, 28.0f, |
| 3419 | |
| 3420 | // Batch 1, Channel 1 |
| 3421 | 29.0f, 30.0f, |
| 3422 | |
| 3423 | // Batch 1, Channel 2 |
| 3424 | 13.0f, 14.0f, |
| 3425 | |
| 3426 | // Batch 1, Channel 3 |
| 3427 | 15.0f, 16.0f, |
| 3428 | })); |
| 3429 | |
| 3430 | armnn::TensorInfo input2TensorInfo({ 2, 1, 2 }, armnn::GetDataType<T>()); |
| 3431 | auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3432 | // Batch 0, Channel 0 |
| 3433 | 17.0f, 18.0f, |
| 3434 | |
| 3435 | // Batch 1, Channel 0 |
| 3436 | 31.0f, 32.0f, |
| 3437 | })); |
| 3438 | |
| 3439 | armnn::TensorInfo outputTensorInfo({ 2, 8, 2 }, armnn::GetDataType<T>()); |
| 3440 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 3441 | |
| 3442 | std::vector<T> output; |
| 3443 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3444 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3445 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 3446 | { input0.data(), input1.data(), input2.data() }, |
| 3447 | outputTensorInfo, |
| 3448 | output.data(), |
| 3449 | 1, |
| 3450 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3451 | |
| 3452 | result.output = MakeTensor<T, 3>(outputTensorInfo, output); |
| 3453 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3454 | // Batch 0, Channel 0 |
| 3455 | 1.0f, 2.0f, |
| 3456 | |
| 3457 | // Batch 0, Channel 1 |
| 3458 | 3.0f, 4.0f, |
| 3459 | |
| 3460 | // Batch 0, Channel 2 |
| 3461 | 5.0f, 6.0f, |
| 3462 | |
| 3463 | // Batch 0, Channel 3 |
| 3464 | 7.0f, 8.0f, |
| 3465 | |
| 3466 | // Batch 0, Channel 4 |
| 3467 | 9.0f, 10.0f, |
| 3468 | |
| 3469 | // Batch 0, Channel 5 |
| 3470 | 11.0f, 12.0f, |
| 3471 | |
| 3472 | // Batch 0, Channel 6 |
| 3473 | 25.0f, 26.0f, |
| 3474 | |
| 3475 | // Batch 0, Channel 7 |
| 3476 | 17.0f, 18.0f, |
| 3477 | |
| 3478 | // Batch 1, Channel 0 |
| 3479 | 19.0f, 20.0f, |
| 3480 | |
| 3481 | // Batch 1, Channel 1 |
| 3482 | 21.0f, 22.0f, |
| 3483 | |
| 3484 | // Batch 1, Channel 2 |
| 3485 | 23.0f, 24.0f, |
| 3486 | |
| 3487 | // Batch 1, Channel 3 |
| 3488 | 27.0f, 28.0f, |
| 3489 | |
| 3490 | // Batch 1, Channel 4 |
| 3491 | 29.0f, 30.0f, |
| 3492 | |
| 3493 | // Batch 1, Channel 5 |
| 3494 | 13.0f, 14.0f, |
| 3495 | |
| 3496 | // Batch 1, Channel 6 |
| 3497 | 15.0f, 16.0f, |
| 3498 | |
| 3499 | // Batch 1, Channel 7 |
| 3500 | 31.0f, 32.0f, |
| 3501 | })); |
| 3502 | |
| 3503 | return result; |
| 3504 | } |
| 3505 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3506 | LayerTestResult<float, 3> Concatenation3dDim1DiffInputDimsTest( |
| 3507 | armnn::IWorkloadFactory& workloadFactory, |
| 3508 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3509 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3510 | return Concatenation3dDim1DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3511 | } |
| 3512 | |
| 3513 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3514 | LayerTestResult<T, 3> Concatenation3dDim2DiffInputDimsTestImpl( |
| 3515 | armnn::IWorkloadFactory& workloadFactory, |
| 3516 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3517 | bool useSubtensor, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3518 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3519 | int32_t qOffset) |
| 3520 | { |
| 3521 | armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, armnn::GetDataType<T>()); |
| 3522 | auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3523 | // Batch 0, Channel 0 |
| 3524 | 1.0f, 2.0f, |
| 3525 | |
| 3526 | // Batch 0, Channel 1 |
| 3527 | 3.0f, 4.0f, |
| 3528 | |
| 3529 | // Batch 0, Channel 2 |
| 3530 | 5.0f, 6.0f, |
| 3531 | |
| 3532 | // Batch 1, Channel 0 |
| 3533 | 19.0f, 20.0f, |
| 3534 | |
| 3535 | // Batch 1, Channel 1 |
| 3536 | 21.0f, 22.0f, |
| 3537 | |
| 3538 | // Batch 1, Channel 2 |
| 3539 | 23.0f, 24.0f |
| 3540 | })); |
| 3541 | |
| 3542 | armnn::TensorInfo input1TensorInfo({ 2, 3, 1 }, armnn::GetDataType<T>()); |
| 3543 | auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3544 | // Batch 0, Channel 0 |
| 3545 | 7.0f, |
| 3546 | |
| 3547 | // Batch 0, Channel 1 |
| 3548 | 9.0f, |
| 3549 | |
| 3550 | // Batch 0, Channel 2 |
| 3551 | 11.0f, |
| 3552 | |
| 3553 | // Batch 1, Channel 0 |
| 3554 | 25.0f, |
| 3555 | |
| 3556 | // Batch 1, Channel 1 |
| 3557 | 27.0f, |
| 3558 | |
| 3559 | // Batch 1, Channel 2 |
| 3560 | 29.0f |
| 3561 | })); |
| 3562 | |
| 3563 | armnn::TensorInfo input2TensorInfo({ 2, 3, 3 }, armnn::GetDataType<T>()); |
| 3564 | auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3565 | // Batch 0, Channel 0 |
| 3566 | 13.0f, 14.0f, 50.0f, |
| 3567 | |
| 3568 | // Batch 0, Channel 1 |
| 3569 | 15.0f, 16.0f, 51.0f, |
| 3570 | |
| 3571 | // Batch 0, Channel 2 |
| 3572 | 17.0f, 18.0f, 52.0f, |
| 3573 | |
| 3574 | // Batch 1, Channel 0 |
| 3575 | 31.0f, 32.0f, 53.0f, |
| 3576 | |
| 3577 | // Batch 1, Channel 1 |
| 3578 | 33.0f, 34.0f, 54.0f, |
| 3579 | |
| 3580 | // Batch 1, Channel 2 |
| 3581 | 35.0f, 36.0f, 55.0f, |
| 3582 | })); |
| 3583 | |
| 3584 | armnn::TensorInfo outputTensorInfo({ 2, 3, 6 }, armnn::GetDataType<T>()); |
| 3585 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 3586 | |
| 3587 | std::vector<T> output; |
| 3588 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3589 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3590 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 3591 | { input0.data(), input1.data(), input2.data() }, |
| 3592 | outputTensorInfo, |
| 3593 | output.data(), |
| 3594 | 2, |
| 3595 | useSubtensor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3596 | |
| 3597 | result.output = MakeTensor<T, 3>(outputTensorInfo, output); |
| 3598 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3599 | // Batch 0, Channel 0 |
| 3600 | 1.0f, 2.0f, 7.0f, 13.0f, 14.0f, 50.0f, |
| 3601 | |
| 3602 | // Batch 0, Channel 1 |
| 3603 | 3.0f, 4.0f, 9.0f, 15.0f, 16.0f, 51.0f, |
| 3604 | |
| 3605 | // Batch 0, Channel 2 |
| 3606 | 5.0f, 6.0f, 11.0f, 17.0f, 18.0f, 52.0f, |
| 3607 | |
| 3608 | // Batch 1, Channel 0 |
| 3609 | 19.0f, 20.0f, 25.0f, 31.0f, 32.0f, 53.0f, |
| 3610 | |
| 3611 | // Batch 1, Channel 1 |
| 3612 | 21.0f, 22.0f, 27.0f, 33.0f, 34.0f, 54.0f, |
| 3613 | |
| 3614 | // Batch 1, Channel 2 |
| 3615 | 23.0f, 24.0f, 29.0f, 35.0f, 36.0f, 55.0f, |
| 3616 | })); |
| 3617 | |
| 3618 | return result; |
| 3619 | } |
| 3620 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3621 | LayerTestResult<float, 3> Concatenation3dDim2DiffInputDimsTest( |
| 3622 | armnn::IWorkloadFactory& workloadFactory, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3623 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3624 | bool useSubtensor) |
| 3625 | { |
| 3626 | return Concatenation3dDim2DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, useSubtensor, 0.0f, 0); |
| 3627 | } |
| 3628 | |
| 3629 | template <typename T> |
| 3630 | LayerTestResult<T, 4> Concatenation4dTestImpl( |
| 3631 | armnn::IWorkloadFactory& workloadFactory, |
| 3632 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3633 | const armnn::TensorInfo& outputTensorInfo, |
| 3634 | unsigned int dimension, |
| 3635 | bool useSubtensor, |
| 3636 | float qScale, |
| 3637 | int32_t qOffset) |
| 3638 | { |
| 3639 | armnn::TensorInfo inputTensorInfo({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 3640 | |
| 3641 | auto input0 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3642 | 1.0f, 2.0f, |
| 3643 | 3.0f, 4.0f, |
| 3644 | 5.0f, 6.0f, |
| 3645 | 7.0f, 8.0f, |
| 3646 | 9.0f, 10.0f, |
| 3647 | 11.0f, 12.0f |
| 3648 | })); |
| 3649 | |
| 3650 | auto input1 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3651 | 11.0f, 12.0f, |
| 3652 | 13.0f, 14.0f, |
| 3653 | 15.0f, 16.0f, |
| 3654 | 17.0f, 18.0f, |
| 3655 | 19.0f, 20.0f, |
| 3656 | 21.0f, 22.0f |
| 3657 | })); |
| 3658 | |
| 3659 | auto input2 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3660 | 21.0f, 22.0f, |
| 3661 | 23.0f, 24.0f, |
| 3662 | 25.0f, 26.0f, |
| 3663 | 27.0f, 28.0f, |
| 3664 | 29.0f, 30.0f, |
| 3665 | 31.0f, 32.0f |
| 3666 | })); |
| 3667 | |
| 3668 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 3669 | |
| 3670 | std::vector<T> output; |
| 3671 | output.resize(outputTensorInfo.GetNumElements()); |
| 3672 | |
| 3673 | Concatenate<T>(workloadFactory, |
| 3674 | memoryManager, |
| 3675 | {inputTensorInfo, inputTensorInfo, inputTensorInfo}, |
| 3676 | {input0.data(), input1.data(), input2.data()}, |
| 3677 | outputTensorInfo, |
| 3678 | output.data(), |
| 3679 | dimension, |
| 3680 | useSubtensor); |
| 3681 | |
| 3682 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 3683 | return result; |
| 3684 | } |
| 3685 | |
| 3686 | template <typename T> |
| 3687 | LayerTestResult<T, 4> Concatenation4dDim0TestImpl( |
| 3688 | armnn::IWorkloadFactory& workloadFactory, |
| 3689 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3690 | float qScale, |
| 3691 | int32_t qOffset) |
| 3692 | { |
| 3693 | armnn::TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 3694 | |
| 3695 | LayerTestResult<T, 4> result = Concatenation4dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 0, |
| 3696 | true, qScale, qOffset); |
| 3697 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3698 | 1.0f, 2.0f, |
| 3699 | 3.0f, 4.0f, |
| 3700 | 5.0f, 6.0f, |
| 3701 | 7.0f, 8.0f, |
| 3702 | 9.0f, 10.0f, |
| 3703 | 11.0f, 12.0f, |
| 3704 | |
| 3705 | 11.0f, 12.0f, |
| 3706 | 13.0f, 14.0f, |
| 3707 | 15.0f, 16.0f, |
| 3708 | 17.0f, 18.0f, |
| 3709 | 19.0f, 20.0f, |
| 3710 | 21.0f, 22.0f, |
| 3711 | |
| 3712 | 21.0f, 22.0f, |
| 3713 | 23.0f, 24.0f, |
| 3714 | 25.0f, 26.0f, |
| 3715 | 27.0f, 28.0f, |
| 3716 | 29.0f, 30.0f, |
| 3717 | 31.0f, 32.0f |
| 3718 | })); |
| 3719 | return result; |
| 3720 | } |
| 3721 | |
| 3722 | LayerTestResult<float, 4> Concatenation4dDim0Test( |
| 3723 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3724 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3725 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3726 | return Concatenation4dDim0TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 3727 | } |
| 3728 | |
| 3729 | template <typename T> |
| 3730 | LayerTestResult<T, 4> Concatenation4dDim1TestImpl( |
| 3731 | armnn::IWorkloadFactory& workloadFactory, |
| 3732 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3733 | float qScale, |
| 3734 | int32_t qOffset) |
| 3735 | { |
| 3736 | armnn::TensorInfo outputTensorInfo({ 1, 9, 2, 2 }, armnn::GetDataType<T>()); |
| 3737 | |
| 3738 | LayerTestResult<T, 4> result = Concatenation4dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 1, |
| 3739 | true, qScale, qOffset); |
| 3740 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3741 | 1.0f, 2.0f, |
| 3742 | 3.0f, 4.0f, |
| 3743 | 5.0f, 6.0f, |
| 3744 | 7.0f, 8.0f, |
| 3745 | 9.0f, 10.0f, |
| 3746 | 11.0f, 12.0f, |
| 3747 | |
| 3748 | 11.0f, 12.0f, |
| 3749 | 13.0f, 14.0f, |
| 3750 | 15.0f, 16.0f, |
| 3751 | 17.0f, 18.0f, |
| 3752 | 19.0f, 20.0f, |
| 3753 | 21.0f, 22.0f, |
| 3754 | |
| 3755 | 21.0f, 22.0f, |
| 3756 | 23.0f, 24.0f, |
| 3757 | 25.0f, 26.0f, |
| 3758 | 27.0f, 28.0f, |
| 3759 | 29.0f, 30.0f, |
| 3760 | 31.0f, 32.0f |
| 3761 | })); |
| 3762 | |
| 3763 | return result; |
| 3764 | } |
| 3765 | |
| 3766 | LayerTestResult<float, 4> Concatenation4dDim1Test( |
| 3767 | armnn::IWorkloadFactory& workloadFactory, |
| 3768 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 3769 | { |
| 3770 | return Concatenation4dDim1TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 3771 | } |
| 3772 | |
| 3773 | template <typename T> |
| 3774 | LayerTestResult<T, 4> Concatenation4dDim2TestImpl( |
| 3775 | armnn::IWorkloadFactory& workloadFactory, |
| 3776 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3777 | float qScale, |
| 3778 | int32_t qOffset) |
| 3779 | { |
| 3780 | armnn::TensorInfo outputTensorInfo({ 1, 3, 6, 2 }, armnn::GetDataType<T>()); |
| 3781 | |
| 3782 | LayerTestResult<T, 4> result = Concatenation4dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 2, |
| 3783 | true, qScale, qOffset); |
| 3784 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3785 | 1.0f, 2.0f, |
| 3786 | 3.0f, 4.0f, |
| 3787 | 11.0f, 12.0f, |
| 3788 | 13.0f, 14.0f, |
| 3789 | 21.0f, 22.0f, |
| 3790 | 23.0f, 24.0f, |
| 3791 | |
| 3792 | 5.0f, 6.0f, |
| 3793 | 7.0f, 8.0f, |
| 3794 | 15.0f, 16.0f, |
| 3795 | 17.0f, 18.0f, |
| 3796 | 25.0f, 26.0f, |
| 3797 | 27.0f, 28.0f, |
| 3798 | |
| 3799 | 9.0f, 10.0f, |
| 3800 | 11.0f, 12.0f, |
| 3801 | 19.0f, 20.0f, |
| 3802 | 21.0f, 22.0f, |
| 3803 | 29.0f, 30.0f, |
| 3804 | 31.0f, 32.0f |
| 3805 | })); |
| 3806 | |
| 3807 | return result; |
| 3808 | } |
| 3809 | |
| 3810 | LayerTestResult<float, 4> Concatenation4dDim2Test( |
| 3811 | armnn::IWorkloadFactory& workloadFactory, |
| 3812 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 3813 | { |
| 3814 | return Concatenation4dDim2TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 3815 | } |
| 3816 | |
| 3817 | template <typename T> |
| 3818 | LayerTestResult<T, 4> Concatenation4dDim3TestImpl( |
| 3819 | armnn::IWorkloadFactory& workloadFactory, |
| 3820 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3821 | float qScale, |
| 3822 | int32_t qOffset, |
| 3823 | bool useSubtensor) |
| 3824 | { |
| 3825 | armnn::TensorInfo outputTensorInfo({ 1, 3, 2, 6 }, armnn::GetDataType<T>()); |
| 3826 | |
| 3827 | LayerTestResult<T, 4> result = Concatenation4dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 3, |
| 3828 | useSubtensor, qScale, qOffset); |
| 3829 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3830 | 1.0f, 2.0f, |
| 3831 | 11.0f, 12.0f, |
| 3832 | 21.0f, 22.0f, |
| 3833 | 3.0f, 4.0f, |
| 3834 | 13.0f, 14.0f, |
| 3835 | 23.0f, 24.0f, |
| 3836 | |
| 3837 | 5.0f, 6.0f, |
| 3838 | 15.0f, 16.0f, |
| 3839 | 25.0f, 26.0f, |
| 3840 | 7.0f, 8.0f, |
| 3841 | 17.0f, 18.0f, |
| 3842 | 27.0f, 28.0f, |
| 3843 | |
| 3844 | 9.0f, 10.0f, |
| 3845 | 19.0f, 20.0f, |
| 3846 | 29.0f, 30.0f, |
| 3847 | 11.0f, 12.0f, |
| 3848 | 21.0f, 22.0f, |
| 3849 | 31.0f, 32.0f |
| 3850 | })); |
| 3851 | |
| 3852 | return result; |
| 3853 | } |
| 3854 | |
| 3855 | LayerTestResult<float, 4> Concatenation4dDim3Test( |
| 3856 | armnn::IWorkloadFactory& workloadFactory, |
| 3857 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3858 | bool useSubtensor) |
| 3859 | { |
| 3860 | return Concatenation4dDim3TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0, useSubtensor); |
| 3861 | } |
| 3862 | |
| 3863 | template <typename T> |
| 3864 | LayerTestResult<T, 4> Concatenation4dDiffShapeDim0TestImpl( |
| 3865 | armnn::IWorkloadFactory& workloadFactory, |
| 3866 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3867 | float qScale, |
| 3868 | int32_t qOffset) |
| 3869 | { |
| 3870 | unsigned int dimension = 0; |
| 3871 | armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 3872 | |
| 3873 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { |
| 3874 | 1.0f, 2.0f, |
| 3875 | 3.0f, 4.0f, |
| 3876 | 5.0f, 6.0f, |
| 3877 | 7.0f, 8.0f, |
| 3878 | 9.0f, 10.0f, |
| 3879 | 11.0f, 12.0f |
| 3880 | })); |
| 3881 | |
| 3882 | armnn::TensorInfo inputTensorInfo1({ 2, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 3883 | |
| 3884 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { |
| 3885 | 11.0f, 12.0f, |
| 3886 | 13.0f, 14.0f, |
| 3887 | 15.0f, 16.0f, |
| 3888 | 17.0f, 18.0f, |
| 3889 | 19.0f, 20.0f, |
| 3890 | 21.0f, 22.0f, |
| 3891 | |
| 3892 | 21.0f, 22.0f, |
| 3893 | 23.0f, 24.0f, |
| 3894 | 25.0f, 26.0f, |
| 3895 | 27.0f, 28.0f, |
| 3896 | 29.0f, 30.0f, |
| 3897 | 31.0f, 32.0f |
| 3898 | |
| 3899 | })); |
| 3900 | |
| 3901 | armnn::TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 3902 | |
| 3903 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 3904 | |
| 3905 | std::vector<T> output; |
| 3906 | output.resize(outputTensorInfo.GetNumElements()); |
| 3907 | Concatenate<T>(workloadFactory, |
| 3908 | memoryManager, |
| 3909 | {inputTensorInfo0, inputTensorInfo1}, |
| 3910 | {input0.data(), input1.data()}, |
| 3911 | outputTensorInfo, |
| 3912 | output.data(), |
| 3913 | dimension, |
| 3914 | true); |
| 3915 | |
| 3916 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 3917 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3918 | 1.0f, 2.0f, |
| 3919 | 3.0f, 4.0f, |
| 3920 | 5.0f, 6.0f, |
| 3921 | 7.0f, 8.0f, |
| 3922 | 9.0f, 10.0f, |
| 3923 | 11.0f, 12.0f, |
| 3924 | |
| 3925 | 11.0f, 12.0f, |
| 3926 | 13.0f, 14.0f, |
| 3927 | 15.0f, 16.0f, |
| 3928 | 17.0f, 18.0f, |
| 3929 | 19.0f, 20.0f, |
| 3930 | 21.0f, 22.0f, |
| 3931 | |
| 3932 | 21.0f, 22.0f, |
| 3933 | 23.0f, 24.0f, |
| 3934 | 25.0f, 26.0f, |
| 3935 | 27.0f, 28.0f, |
| 3936 | 29.0f, 30.0f, |
| 3937 | 31.0f, 32.0f |
| 3938 | })); |
| 3939 | |
| 3940 | return result; |
| 3941 | } |
| 3942 | |
| 3943 | LayerTestResult<float, 4> Concatenation4dDiffShapeDim0Test( |
| 3944 | armnn::IWorkloadFactory& workloadFactory, |
| 3945 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 3946 | { |
| 3947 | return Concatenation4dDiffShapeDim0TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 3948 | } |
| 3949 | |
| 3950 | template <typename T> |
| 3951 | LayerTestResult<T, 4> Concatenation4dDiffShapeDim1TestImpl( |
| 3952 | armnn::IWorkloadFactory& workloadFactory, |
| 3953 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3954 | float qScale, |
| 3955 | int32_t qOffset) |
| 3956 | { |
| 3957 | unsigned int dimension = 1; |
| 3958 | armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 3959 | |
| 3960 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { |
| 3961 | 1.0f, 2.0f, |
| 3962 | 3.0f, 4.0f, |
| 3963 | 5.0f, 6.0f, |
| 3964 | 7.0f, 8.0f, |
| 3965 | 9.0f, 10.0f, |
| 3966 | 11.0f, 12.0f |
| 3967 | })); |
| 3968 | |
| 3969 | armnn::TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, armnn::GetDataType<T>()); |
| 3970 | |
| 3971 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { |
| 3972 | 11.0f, 12.0f, |
| 3973 | 13.0f, 14.0f, |
| 3974 | 15.0f, 16.0f, |
| 3975 | 17.0f, 18.0f, |
| 3976 | |
| 3977 | })); |
| 3978 | |
| 3979 | armnn::TensorInfo outputTensorInfo({ 1, 5, 2, 2 }, armnn::GetDataType<T>()); |
| 3980 | |
| 3981 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 3982 | |
| 3983 | std::vector<T> output; |
| 3984 | output.resize(outputTensorInfo.GetNumElements()); |
| 3985 | Concatenate<T>(workloadFactory, |
| 3986 | memoryManager, |
| 3987 | {inputTensorInfo0, inputTensorInfo1}, |
| 3988 | {input0.data(), input1.data()}, |
| 3989 | outputTensorInfo, |
| 3990 | output.data(), |
| 3991 | dimension, |
| 3992 | true); |
| 3993 | |
| 3994 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 3995 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3996 | 1.0f, 2.0f, |
| 3997 | 3.0f, 4.0f, |
| 3998 | 5.0f, 6.0f, |
| 3999 | 7.0f, 8.0f, |
| 4000 | 9.0f, 10.0f, |
| 4001 | 11.0f, 12.0f, |
| 4002 | 11.0f, 12.0f, |
| 4003 | 13.0f, 14.0f, |
| 4004 | 15.0f, 16.0f, |
| 4005 | 17.0f, 18.0f |
| 4006 | })); |
| 4007 | |
| 4008 | return result; |
| 4009 | } |
| 4010 | |
| 4011 | LayerTestResult<float, 4> Concatenation4dDiffShapeDim1Test( |
| 4012 | armnn::IWorkloadFactory& workloadFactory, |
| 4013 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 4014 | { |
| 4015 | return Concatenation4dDiffShapeDim1TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 4016 | } |
| 4017 | |
| 4018 | template <typename T> |
| 4019 | LayerTestResult<T, 4> Concatenation4dDiffShapeDim2TestImpl( |
| 4020 | armnn::IWorkloadFactory& workloadFactory, |
| 4021 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4022 | float qScale, |
| 4023 | int32_t qOffset) |
| 4024 | { |
| 4025 | unsigned int dimension = 2; |
| 4026 | armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4027 | |
| 4028 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { |
| 4029 | 1.0f, 2.0f, |
| 4030 | 3.0f, 4.0f, |
| 4031 | 5.0f, 6.0f, |
| 4032 | 7.0f, 8.0f, |
| 4033 | 9.0f, 10.0f, |
| 4034 | 11.0f, 12.0f |
| 4035 | })); |
| 4036 | |
| 4037 | armnn::TensorInfo inputTensorInfo1({ 1, 3, 3, 2 }, armnn::GetDataType<T>()); |
| 4038 | |
| 4039 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { |
| 4040 | 11.0f, 12.0f, |
| 4041 | 13.0f, 14.0f, |
| 4042 | 15.0f, 16.0f, |
| 4043 | 17.0f, 18.0f, |
| 4044 | 19.0f, 20.0f, |
| 4045 | 21.0f, 22.0f, |
| 4046 | 23.0f, 24.0f, |
| 4047 | 25.0f, 26.0f, |
| 4048 | 27.0f, 28.0f |
| 4049 | })); |
| 4050 | |
| 4051 | armnn::TensorInfo outputTensorInfo({ 1, 3, 5, 2 }, armnn::GetDataType<T>()); |
| 4052 | |
| 4053 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 4054 | |
| 4055 | std::vector<T> output; |
| 4056 | output.resize(outputTensorInfo.GetNumElements()); |
| 4057 | Concatenate<T>(workloadFactory, |
| 4058 | memoryManager, |
| 4059 | {inputTensorInfo0, inputTensorInfo1}, |
| 4060 | {input0.data(), input1.data()}, |
| 4061 | outputTensorInfo, |
| 4062 | output.data(), |
| 4063 | dimension, |
| 4064 | true); |
| 4065 | |
| 4066 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 4067 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4068 | 1.0f, 2.0f, |
| 4069 | 3.0f, 4.0f, |
| 4070 | 11.0f, 12.0f, |
| 4071 | 13.0f, 14.0f, |
| 4072 | 15.0f, 16.0f, |
| 4073 | |
| 4074 | 5.0f, 6.0f, |
| 4075 | 7.0f, 8.0f, |
| 4076 | 17.0f, 18.0f, |
| 4077 | 19.0f, 20.0f, |
| 4078 | 21.0f, 22.0f, |
| 4079 | |
| 4080 | 9.0f, 10.0f, |
| 4081 | 11.0f, 12.0f, |
| 4082 | 23.0f, 24.0f, |
| 4083 | 25.0f, 26.0f, |
| 4084 | 27.0f, 28.0f |
| 4085 | })); |
| 4086 | |
| 4087 | return result; |
| 4088 | } |
| 4089 | |
| 4090 | LayerTestResult<float, 4> Concatenation4dDiffShapeDim2Test( |
| 4091 | armnn::IWorkloadFactory& workloadFactory, |
| 4092 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 4093 | { |
| 4094 | return Concatenation4dDiffShapeDim2TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 4095 | } |
| 4096 | |
| 4097 | template <typename T> |
| 4098 | LayerTestResult<T, 4> Concatenation4dDiffShapeDim3TestImpl( |
| 4099 | armnn::IWorkloadFactory& workloadFactory, |
| 4100 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4101 | float qScale, |
| 4102 | int32_t qOffset, |
| 4103 | bool useSubtensor) |
| 4104 | { |
| 4105 | unsigned int dimension = 3; |
| 4106 | armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4107 | |
| 4108 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { |
| 4109 | 1.0f, 2.0f, |
| 4110 | 3.0f, 4.0f, |
| 4111 | 5.0f, 6.0f, |
| 4112 | 7.0f, 8.0f, |
| 4113 | 9.0f, 10.0f, |
| 4114 | 11.0f, 12.0f |
| 4115 | })); |
| 4116 | |
| 4117 | armnn::TensorInfo inputTensorInfo1({ 1, 3, 2, 3 }, armnn::GetDataType<T>()); |
| 4118 | |
| 4119 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { |
| 4120 | 11.0f, 12.0f, 13.0f, |
| 4121 | 14.0f, 15.0f, 16.0f, |
| 4122 | |
| 4123 | 17.0f, 18.0f, 19.0f, |
| 4124 | 20.0f, 21.0f, 22.0f, |
| 4125 | |
| 4126 | 23.0f, 24.0f, 25.0f, |
| 4127 | 26.0f, 27.0f, 28.0f |
| 4128 | })); |
| 4129 | |
| 4130 | armnn::TensorInfo outputTensorInfo({ 1, 3, 2, 5 }, armnn::GetDataType<T>()); |
| 4131 | |
| 4132 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 4133 | |
| 4134 | std::vector<T> output; |
| 4135 | output.resize(outputTensorInfo.GetNumElements()); |
| 4136 | Concatenate<T>(workloadFactory, |
| 4137 | memoryManager, |
| 4138 | {inputTensorInfo0, inputTensorInfo1}, |
| 4139 | {input0.data(), input1.data()}, |
| 4140 | outputTensorInfo, |
| 4141 | output.data(), |
| 4142 | dimension, |
| 4143 | useSubtensor); |
| 4144 | |
| 4145 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 4146 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4147 | 1.0f, 2.0f, 11.0f, 12.0f, 13.0f, |
| 4148 | 3.0f, 4.0f, 14.0f, 15.0f, 16.0f, |
| 4149 | 5.0f, 6.0f, 17.0f, 18.0f, 19.0f, |
| 4150 | 7.0f, 8.0f, 20.0f, 21.0f, 22.0f, |
| 4151 | 9.0f, 10.0f, 23.0f, 24.0f, 25.0f, |
| 4152 | 11.0f, 12.0f, 26.0f, 27.0f, 28.0f |
| 4153 | })); |
| 4154 | |
| 4155 | return result; |
| 4156 | } |
| 4157 | |
| 4158 | LayerTestResult<float, 4> Concatenation4dDiffShapeDim3Test( |
| 4159 | armnn::IWorkloadFactory& workloadFactory, |
| 4160 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4161 | bool useSubtensor) |
| 4162 | { |
| 4163 | return Concatenation4dDiffShapeDim3TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0, useSubtensor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4164 | } |
| 4165 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4166 | LayerTestResult<float, 4> ResizeBilinearNopTest( |
| 4167 | armnn::IWorkloadFactory& workloadFactory, |
| 4168 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4169 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4170 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4171 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); |
| 4172 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4173 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4174 | std::vector<float> inputData({ |
| 4175 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 4176 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 4177 | 3.0f, 4.0f, 5.0f, 6.0f, |
| 4178 | 4.0f, 5.0f, 6.0f, 7.0f, |
| 4179 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4180 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 4181 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 4182 | 3.0f, 4.0f, 5.0f, 6.0f, |
| 4183 | 4.0f, 5.0f, 6.0f, 7.0f |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4184 | }); |
| 4185 | |
| 4186 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4187 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4188 | { |
| 4189 | std::vector<float> tmp(inputData.size()); |
| 4190 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); |
| 4191 | inputData = tmp; |
| 4192 | } |
| 4193 | |
| 4194 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4195 | |
| 4196 | LayerTestResult<float, 4> result(outputTensorInfo); |
| 4197 | result.outputExpected = input; |
| 4198 | |
| 4199 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4200 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4201 | |
| 4202 | armnn::ResizeBilinearQueueDescriptor descriptor; |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4203 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
| 4204 | armnn::WorkloadInfo info; |
| 4205 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4206 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4207 | |
| 4208 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4209 | |
| 4210 | inputHandle->Allocate(); |
| 4211 | outputHandle->Allocate(); |
| 4212 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4213 | |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4214 | workload->Execute(); |
| 4215 | |
| 4216 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4217 | return result; |
| 4218 | } |
| 4219 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4220 | LayerTestResult<float, 4> SimpleResizeBilinearTest( |
| 4221 | armnn::IWorkloadFactory& workloadFactory, |
| 4222 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4223 | const armnn::DataLayout dataLayout) |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4224 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4225 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 2, dataLayout); |
| 4226 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 1, 1, dataLayout); |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4227 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4228 | std::vector<float> inputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4229 | 1.0f, 255.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4230 | 200.0f, 250.0f, |
| 4231 | |
| 4232 | 250.0f, 200.0f, |
| 4233 | 250.0f, 1.0f |
| 4234 | }); |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4235 | |
| 4236 | // The 'resize bilinear' operation projects the top-left corner of output texels into the input image, |
| 4237 | // then figures out the interpolants and weights. Note this is different to projecting the centre of the |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4238 | // output texel. Thus, for a input matrix of 2x2, we'll expect the output 1x1 matrix to contain, as |
| 4239 | // its single element, the value that was at position (0,0) of the input matrix (rather than an average, |
| 4240 | // which we would expect if projecting the centre). |
| 4241 | |
| 4242 | std::vector<float> outputData({ |
| 4243 | 1.0f, |
| 4244 | |
| 4245 | 250.0f |
| 4246 | }); |
| 4247 | |
| 4248 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4249 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4250 | { |
| 4251 | std::vector<float> tmp(inputData.size()); |
| 4252 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); |
| 4253 | inputData = tmp; |
| 4254 | |
| 4255 | std::vector<float> tmp1(outputData.size()); |
| 4256 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data()); |
| 4257 | outputData = tmp1; |
| 4258 | } |
| 4259 | |
| 4260 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
| 4261 | |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4262 | LayerTestResult<float, 4> result(outputTensorInfo); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4263 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4264 | |
| 4265 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4266 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4267 | |
| 4268 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 4269 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4270 | armnn::WorkloadInfo info; |
| 4271 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4272 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4273 | |
| 4274 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4275 | |
| 4276 | inputHandle->Allocate(); |
| 4277 | outputHandle->Allocate(); |
| 4278 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4279 | |
| 4280 | workload->Execute(); |
| 4281 | |
| 4282 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4283 | return result; |
| 4284 | } |
| 4285 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4286 | LayerTestResult<float, 4> ResizeBilinearSqMinTest( |
| 4287 | armnn::IWorkloadFactory& workloadFactory, |
| 4288 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4289 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4290 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4291 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); |
| 4292 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 2, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4293 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4294 | std::vector<float> inputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4295 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 4296 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 4297 | 3.0f, 4.0f, 5.0f, 6.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4298 | 4.0f, 5.0f, 6.0f, 7.0f, |
| 4299 | |
| 4300 | 7.0f, 6.0f, 5.0f, 4.0f, |
| 4301 | 6.0f, 5.0f, 4.0f, 3.0f, |
| 4302 | 5.0f, 4.0f, 3.0f, 2.0f, |
| 4303 | 4.0f, 3.0f, 2.0f, 1.0f |
| 4304 | }); |
| 4305 | |
| 4306 | std::vector<float> outputData({ |
| 4307 | 1.0f, 3.0f, |
| 4308 | 3.0f, 5.0f, |
| 4309 | |
| 4310 | 7.0f, 5.0f, |
| 4311 | 5.0f, 3.0f |
| 4312 | }); |
| 4313 | |
| 4314 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4315 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4316 | { |
| 4317 | std::vector<float> tmp(inputData.size()); |
| 4318 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); |
| 4319 | inputData = tmp; |
| 4320 | |
| 4321 | std::vector<float> tmp1(outputData.size()); |
| 4322 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data()); |
| 4323 | outputData = tmp1; |
| 4324 | } |
| 4325 | |
| 4326 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4327 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4328 | LayerTestResult<float, 4> result(outputTensorInfo); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4329 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4330 | |
| 4331 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4332 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4333 | |
| 4334 | armnn::ResizeBilinearQueueDescriptor descriptor; |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4335 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4336 | armnn::WorkloadInfo info; |
| 4337 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4338 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4339 | |
| 4340 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4341 | |
| 4342 | inputHandle->Allocate(); |
| 4343 | outputHandle->Allocate(); |
| 4344 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4345 | |
| 4346 | workload->Execute(); |
| 4347 | |
| 4348 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4349 | return result; |
| 4350 | } |
| 4351 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4352 | LayerTestResult<float, 4> ResizeBilinearMinTest( |
| 4353 | armnn::IWorkloadFactory& workloadFactory, |
| 4354 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4355 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4356 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4357 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 5, dataLayout); |
| 4358 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 3, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4359 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4360 | std::vector<float> inputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4361 | 1.0f, 2.0f, 3.0f, 5.0f, 8.0f, |
| 4362 | 13.0f, 21.0f, 34.0f, 55.0f, 89.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4363 | 144.0f, 233.0f, 377.0f, 610.0f, 987.0f, |
| 4364 | |
| 4365 | 987.0f, 610.0f, 377.0f, 233.0f, 144.0f, |
| 4366 | 89.0f, 55.0f, 34.0f, 21.0f, 13.0f, |
| 4367 | 8.0f, 5.0f, 3.0f, 2.0f, 1.0f |
| 4368 | }); |
| 4369 | |
| 4370 | std::vector<float> outputData({ |
| 4371 | 1.0f, 2.6666f, 6.00f, |
| 4372 | 78.5f, 179.3333f, 401.00f, |
| 4373 | |
| 4374 | 987.0f, 454.6670f, 203.33f, |
| 4375 | 48.5f, 22.3333f, 10.00f |
| 4376 | }); |
| 4377 | |
| 4378 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4379 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4380 | { |
| 4381 | std::vector<float> tmp(inputData.size()); |
| 4382 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); |
| 4383 | inputData = tmp; |
| 4384 | |
| 4385 | std::vector<float> tmp1(outputData.size()); |
| 4386 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data()); |
| 4387 | outputData = tmp1; |
| 4388 | } |
| 4389 | |
| 4390 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4391 | |
| 4392 | LayerTestResult<float, 4> result(outputTensorInfo); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4393 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4394 | |
| 4395 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4396 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4397 | |
| 4398 | armnn::ResizeBilinearQueueDescriptor descriptor; |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4399 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4400 | armnn::WorkloadInfo info; |
| 4401 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4402 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4403 | |
| 4404 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4405 | |
| 4406 | inputHandle->Allocate(); |
| 4407 | outputHandle->Allocate(); |
| 4408 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4409 | |
| 4410 | workload->Execute(); |
| 4411 | |
| 4412 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4413 | return result; |
| 4414 | } |
| 4415 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4416 | LayerTestResult<float, 4> ResizeBilinearMagTest( |
| 4417 | armnn::IWorkloadFactory& workloadFactory, |
| 4418 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4419 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4420 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4421 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 2, dataLayout); |
| 4422 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 5, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4423 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4424 | std::vector<float> inputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4425 | 1.0f, 2.0f, |
| 4426 | 13.0f, 21.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4427 | 144.0f, 233.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4428 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4429 | 233.0f, 144.0f, |
| 4430 | 21.0f, 13.0f, |
| 4431 | 2.0f, 1.0f |
| 4432 | }); |
| 4433 | |
| 4434 | std::vector<float> outputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4435 | 1.0f, 1.4f, 1.8f, 2.0f, 2.0f, |
| 4436 | 13.0f, 16.2f, 19.4f, 21.0f, 21.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4437 | 144.0f, 179.6f, 215.2f, 233.0f, 233.0f, |
| 4438 | |
| 4439 | 233.0f, 197.4f, 161.8f, 144.0f, 144.0f, |
| 4440 | 21.0f, 17.8f, 14.6f, 13.0f, 13.0f, |
| 4441 | 2.0f, 1.6f, 1.2f, 1.0f, 1.0f |
| 4442 | }); |
| 4443 | |
| 4444 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4445 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4446 | { |
| 4447 | std::vector<float> tmp(inputData.size()); |
| 4448 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); |
| 4449 | inputData = tmp; |
| 4450 | |
| 4451 | std::vector<float> tmp1(outputData.size()); |
| 4452 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data()); |
| 4453 | outputData = tmp1; |
| 4454 | } |
| 4455 | |
| 4456 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
| 4457 | |
| 4458 | LayerTestResult<float, 4> result(outputTensorInfo); |
| 4459 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4460 | |
| 4461 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4462 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4463 | |
| 4464 | armnn::ResizeBilinearQueueDescriptor descriptor; |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4465 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4466 | armnn::WorkloadInfo info; |
| 4467 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4468 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4469 | |
| 4470 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4471 | |
| 4472 | inputHandle->Allocate(); |
| 4473 | outputHandle->Allocate(); |
| 4474 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4475 | |
| 4476 | workload->Execute(); |
| 4477 | |
| 4478 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4479 | return result; |
| 4480 | } |
| 4481 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4482 | LayerTestResult<float, 2> FakeQuantizationTest( |
| 4483 | armnn::IWorkloadFactory& workloadFactory, |
| 4484 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4485 | { |
| 4486 | constexpr unsigned int width = 2; |
| 4487 | constexpr unsigned int height = 3; |
| 4488 | |
| 4489 | const armnn::TensorInfo tensorInfo({height, width }, |
| 4490 | armnn::DataType::Float32); |
| 4491 | auto input = MakeTensor<float, 2>(tensorInfo, std::vector<float>({ |
| 4492 | -10.0f, -5.0f, |
| 4493 | 0.0f, 5.0f, |
| 4494 | 10.0f, 10.0f |
| 4495 | })); |
| 4496 | |
| 4497 | LayerTestResult<float, 2> ret(tensorInfo); |
| 4498 | |
| 4499 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(tensorInfo); |
| 4500 | |
| 4501 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(tensorInfo); |
| 4502 | |
| 4503 | armnn::FakeQuantizationQueueDescriptor data; |
| 4504 | armnn::WorkloadInfo info; |
| 4505 | |
| 4506 | AddInputToWorkload(data, info, tensorInfo, inputHandle.get()); |
| 4507 | AddOutputToWorkload(data, info, tensorInfo, outputHandle.get()); |
| 4508 | float min = -10.f; |
| 4509 | float max = 10.f; |
| 4510 | |
| 4511 | data.m_Parameters.m_Min = min; |
| 4512 | data.m_Parameters.m_Max = max; |
| 4513 | |
| 4514 | armnn::PassthroughCpuTensorHandle refHandle(tensorInfo, &ret.outputExpected[0][0]); |
| 4515 | armnn::FakeQuantizationQueueDescriptor refData = data; |
| 4516 | armnn::WorkloadInfo refInfo = info; |
| 4517 | SetWorkloadOutput(refData, refInfo, 0, tensorInfo, &refHandle); |
| 4518 | |
| 4519 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateFakeQuantization(data, info); |
| 4520 | |
| 4521 | inputHandle->Allocate(); |
| 4522 | outputHandle->Allocate(); |
| 4523 | |
| 4524 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0]); |
| 4525 | |
| 4526 | workload->Execute(); |
| 4527 | |
| 4528 | CopyDataFromITensorHandle(&ret.output[0][0], outputHandle.get()); |
| 4529 | |
| 4530 | ret.outputExpected = MakeTensor<float, 2>(tensorInfo, std::vector<float>({ |
| 4531 | 0.0f, 63.0f, |
| 4532 | 128.0f, 191.0f, |
| 4533 | 255.0f, 255.0f |
| 4534 | })); |
| 4535 | return ret; |
| 4536 | } |
| 4537 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4538 | namespace |
| 4539 | { |
| 4540 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4541 | LayerTestResult<float, 4> L2NormalizationTestImpl( |
| 4542 | armnn::IWorkloadFactory& workloadFactory, |
| 4543 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4544 | const armnn::TensorShape& inputOutputTensorShape, |
| 4545 | const std::vector<float>& inputValues, |
| 4546 | const std::vector<float>& expectedOutputValues, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4547 | const armnn::DataLayout layout) |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4548 | { |
| 4549 | const armnn::TensorInfo inputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32); |
| 4550 | const armnn::TensorInfo outputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32); |
| 4551 | |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4552 | // at this point if we require it permute the input data |
| 4553 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 4554 | std::vector<float> inputData = inputValues; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4555 | if (layout == armnn::DataLayout::NHWC) |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4556 | { |
| 4557 | std::vector<float> tmp(inputData.size()); |
| 4558 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); |
| 4559 | inputData = tmp; |
| 4560 | } |
| 4561 | |
| 4562 | auto inputTensor = MakeTensor<float, 4>(inputTensorInfo, std::vector<float>(inputData)); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4563 | |
| 4564 | LayerTestResult<float, 4> result(outputTensorInfo); |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4565 | std::vector<float> expectedOutputData = expectedOutputValues; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4566 | if (layout == armnn::DataLayout::NHWC) |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4567 | { |
| 4568 | std::vector<float> tmp(expectedOutputData.size()); |
| 4569 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, expectedOutputData.data(), tmp.data()); |
| 4570 | expectedOutputData = tmp; |
| 4571 | } |
| 4572 | result.outputExpected = MakeTensor<float, 4>(inputTensorInfo, std::vector<float>(expectedOutputData)); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4573 | |
| 4574 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4575 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4576 | |
| 4577 | armnn::L2NormalizationQueueDescriptor descriptor; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4578 | descriptor.m_Parameters.m_DataLayout = layout; |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4579 | armnn::WorkloadInfo info; |
| 4580 | |
| 4581 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4582 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4583 | |
| 4584 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateL2Normalization(descriptor, info); |
| 4585 | |
| 4586 | inputHandle->Allocate(); |
| 4587 | outputHandle->Allocate(); |
| 4588 | |
| 4589 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0][0]); |
| 4590 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4591 | ExecuteWorkload(*workload, memoryManager); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4592 | |
| 4593 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4594 | |
| 4595 | return result; |
| 4596 | } |
| 4597 | |
| 4598 | float CalcInvL2Norm(std::initializer_list<float> elements) |
| 4599 | { |
| 4600 | const float reduction = std::accumulate(elements.begin(), elements.end(), 0.0f, |
| 4601 | [](float acc, float element) { return acc + element * element; }); |
| 4602 | return 1.0f / sqrtf(reduction); |
| 4603 | } |
| 4604 | |
| 4605 | } // anonymous namespace |
| 4606 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4607 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4608 | LayerTestResult<T, 2> Pad2dTestCommon( |
| 4609 | armnn::IWorkloadFactory& workloadFactory, |
| 4610 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4611 | float qScale, |
| 4612 | int32_t qOffset) |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4613 | { |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4614 | const armnn::TensorShape inputShape{ 3, 3 }; |
| 4615 | const armnn::TensorShape outputShape{ 7, 7 }; |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4616 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4617 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>()); |
| 4618 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4619 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4620 | std::vector<T> inputValues( |
| 4621 | QuantizedVector<T>(qScale, qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4622 | { |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4623 | // Height (3) x Width (3) |
| 4624 | 4, 8, 6, |
| 4625 | 7, 4, 4, |
| 4626 | 3, 2, 4 |
| 4627 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4628 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4629 | std::vector<T> expectedOutputValues( |
| 4630 | QuantizedVector<T>(qScale, qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4631 | { |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4632 | 0, 0, 0, 0, 0, 0, 0, |
| 4633 | 0, 0, 0, 0, 0, 0, 0, |
| 4634 | 0, 0, 4, 8, 6, 0, 0, |
| 4635 | 0, 0, 7, 4, 4, 0, 0, |
| 4636 | 0, 0, 3, 2, 4, 0, 0, |
| 4637 | 0, 0, 0, 0, 0, 0, 0, |
| 4638 | 0, 0, 0, 0, 0, 0, 0 |
| 4639 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4640 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4641 | auto inputTensor = MakeTensor<T, 2>(inputTensorInfo, std::vector<T>(inputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4642 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4643 | LayerTestResult<T, 2> result(outputTensorInfo); |
| 4644 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, std::vector<T>(expectedOutputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4645 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4646 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4647 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4648 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4649 | armnn::PadQueueDescriptor descriptor; |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4650 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4651 | std::vector<std::pair<unsigned int, unsigned int>> PadList; |
| 4652 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,2)); |
| 4653 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,2)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4654 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4655 | descriptor.m_Parameters.m_PadList = PadList; |
| 4656 | armnn::WorkloadInfo info; |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4657 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4658 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4659 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4660 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4661 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4662 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4663 | inputHandle->Allocate(); |
| 4664 | outputHandle->Allocate(); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4665 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4666 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4667 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4668 | workload->Execute(); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4669 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4670 | CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4671 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4672 | return result; |
| 4673 | } |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4674 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4675 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4676 | LayerTestResult<T, 3> Pad3dTestCommon( |
| 4677 | armnn::IWorkloadFactory& workloadFactory, |
| 4678 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4679 | float qScale, |
| 4680 | int32_t qOffset) |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4681 | { |
| 4682 | const armnn::TensorShape inputShape{ 2, 2, 2 }; |
| 4683 | const armnn::TensorShape outputShape{ 3, 5, 6 }; |
| 4684 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4685 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>()); |
| 4686 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4687 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4688 | std::vector<T> inputValues( |
| 4689 | QuantizedVector<T>(qScale,qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4690 | { |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4691 | // Channel 0, Height (2) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4692 | 0, 4, |
| 4693 | 2, 5, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4694 | |
| 4695 | // Channel 1, Height (2) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4696 | 6, 1, |
| 4697 | 5, 2 |
| 4698 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4699 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4700 | std::vector<T> expectedOutputValues( |
| 4701 | QuantizedVector<T>(qScale,qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4702 | { |
| 4703 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4704 | 0, 0, 0, 0, 0, 0, |
| 4705 | 0, 0, 0, 0, 0, 0, |
| 4706 | 0, 0, 0, 4, 0, 0, |
| 4707 | 0, 0, 2, 5, 0, 0, |
| 4708 | 0, 0, 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4709 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4710 | 0, 0, 0, 0, 0, 0, |
| 4711 | 0, 0, 0, 0, 0, 0, |
| 4712 | 0, 0, 6, 1, 0, 0, |
| 4713 | 0, 0, 5, 2, 0, 0, |
| 4714 | 0, 0, 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4715 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4716 | 0, 0, 0, 0, 0, 0, |
| 4717 | 0, 0, 0, 0, 0, 0, |
| 4718 | 0, 0, 0, 0, 0, 0, |
| 4719 | 0, 0, 0, 0, 0, 0, |
| 4720 | 0, 0, 0, 0, 0, 0 |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4721 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4722 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4723 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4724 | auto inputTensor = MakeTensor<T, 3>(inputTensorInfo, std::vector<T>(inputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4725 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4726 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 4727 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, std::vector<T>(expectedOutputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4728 | |
| 4729 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4730 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4731 | |
| 4732 | armnn::PadQueueDescriptor descriptor; |
| 4733 | |
| 4734 | std::vector<std::pair<unsigned int, unsigned int>> PadList; |
| 4735 | PadList.push_back(std::pair<unsigned int, unsigned int>(0,1)); |
| 4736 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,1)); |
| 4737 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,2)); |
| 4738 | |
| 4739 | descriptor.m_Parameters.m_PadList = PadList; |
| 4740 | armnn::WorkloadInfo info; |
| 4741 | |
| 4742 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4743 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4744 | |
| 4745 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info); |
| 4746 | |
| 4747 | inputHandle->Allocate(); |
| 4748 | outputHandle->Allocate(); |
| 4749 | |
| 4750 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0]); |
| 4751 | |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4752 | workload->Execute(); |
| 4753 | |
| 4754 | CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get()); |
| 4755 | |
| 4756 | return result; |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4757 | } |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4758 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4759 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4760 | LayerTestResult<T, 4> Pad4dTestCommon( |
| 4761 | armnn::IWorkloadFactory& workloadFactory, |
| 4762 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4763 | float qScale, |
| 4764 | int32_t qOffset) |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4765 | { |
| 4766 | const armnn::TensorShape inputShape{ 2, 2, 3, 2 }; |
| 4767 | const armnn::TensorShape outputShape{ 4, 5, 7, 4 }; |
| 4768 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4769 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>()); |
| 4770 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4771 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4772 | std::vector<T> inputValues( |
| 4773 | QuantizedVector<T>(qScale,qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4774 | { |
| 4775 | // Batch 0, Channel 0, Height (3) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4776 | 0, 1, |
| 4777 | 2, 3, |
| 4778 | 4, 5, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4779 | |
| 4780 | // Batch 0, Channel 1, Height (3) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4781 | 6, 7, |
| 4782 | 8, 9, |
| 4783 | 10, 11, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4784 | |
| 4785 | // Batch 1, Channel 0, Height (3) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4786 | 12, 13, |
| 4787 | 14, 15, |
| 4788 | 16, 17, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4789 | |
| 4790 | // Batch 1, Channel 1, Height (3) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4791 | 18, 19, |
| 4792 | 20, 21, |
| 4793 | 22, 23 |
| 4794 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4795 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4796 | std::vector<T> expectedOutputValues( |
| 4797 | QuantizedVector<T>(qScale,qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4798 | { |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4799 | 0, 0, 0, 0, |
| 4800 | 0, 0, 0, 0, |
| 4801 | 0, 0, 0, 0, |
| 4802 | 0, 0, 0, 0, |
| 4803 | 0, 0, 0, 0, |
| 4804 | 0, 0, 0, 0, |
| 4805 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4806 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4807 | 0, 0, 0, 0, |
| 4808 | 0, 0, 0, 0, |
| 4809 | 0, 0, 0, 0, |
| 4810 | 0, 0, 0, 0, |
| 4811 | 0, 0, 0, 0, |
| 4812 | 0, 0, 0, 0, |
| 4813 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4814 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4815 | 0, 0, 0, 0, |
| 4816 | 0, 0, 0, 0, |
| 4817 | 0, 0, 0, 0, |
| 4818 | 0, 0, 0, 0, |
| 4819 | 0, 0, 0, 0, |
| 4820 | 0, 0, 0, 0, |
| 4821 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4822 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4823 | 0, 0, 0, 0, |
| 4824 | 0, 0, 0, 0, |
| 4825 | 0, 0, 0, 0, |
| 4826 | 0, 0, 0, 0, |
| 4827 | 0, 0, 0, 0, |
| 4828 | 0, 0, 0, 0, |
| 4829 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4830 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4831 | 0, 0, 0, 0, |
| 4832 | 0, 0, 0, 0, |
| 4833 | 0, 0, 0, 0, |
| 4834 | 0, 0, 0, 0, |
| 4835 | 0, 0, 0, 0, |
| 4836 | 0, 0, 0, 0, |
| 4837 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4838 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4839 | 0, 0, 0, 0, |
| 4840 | 0, 0, 0, 0, |
| 4841 | 0, 0, 0, 0, |
| 4842 | 0, 0, 0, 0, |
| 4843 | 0, 0, 0, 0, |
| 4844 | 0, 0, 0, 0, |
| 4845 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4846 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4847 | 0, 0, 0, 0, |
| 4848 | 0, 0, 0, 0, |
| 4849 | 0, 0, 0, 0, |
| 4850 | 0, 0, 0, 0, |
| 4851 | 0, 0, 0, 0, |
| 4852 | 0, 0, 0, 0, |
| 4853 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4854 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4855 | 0, 0, 0, 0, |
| 4856 | 0, 0, 0, 0, |
| 4857 | 0, 0, 0, 0, |
| 4858 | 0, 0, 1, 0, |
| 4859 | 0, 2, 3, 0, |
| 4860 | 0, 4, 5, 0, |
| 4861 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4862 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4863 | 0, 0, 0, 0, |
| 4864 | 0, 0, 0, 0, |
| 4865 | 0, 0, 0, 0, |
| 4866 | 0, 6, 7, 0, |
| 4867 | 0, 8, 9, 0, |
| 4868 | 0, 10, 11, 0, |
| 4869 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4870 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4871 | 0, 0, 0, 0, |
| 4872 | 0, 0, 0, 0, |
| 4873 | 0, 0, 0, 0, |
| 4874 | 0, 0, 0, 0, |
| 4875 | 0, 0, 0, 0, |
| 4876 | 0, 0, 0, 0, |
| 4877 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4878 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4879 | 0, 0, 0, 0, |
| 4880 | 0, 0, 0, 0, |
| 4881 | 0, 0, 0, 0, |
| 4882 | 0, 0, 0, 0, |
| 4883 | 0, 0, 0, 0, |
| 4884 | 0, 0, 0, 0, |
| 4885 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4886 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4887 | 0, 0, 0, 0, |
| 4888 | 0, 0, 0, 0, |
| 4889 | 0, 0, 0, 0, |
| 4890 | 0, 0, 0, 0, |
| 4891 | 0, 0, 0, 0, |
| 4892 | 0, 0, 0, 0, |
| 4893 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4894 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4895 | 0, 0, 0, 0, |
| 4896 | 0, 0, 0, 0, |
| 4897 | 0, 0, 0, 0, |
| 4898 | 0, 12, 13, 0, |
| 4899 | 0, 14, 15, 0, |
| 4900 | 0, 16, 17, 0, |
| 4901 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4902 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4903 | 0, 0, 0, 0, |
| 4904 | 0, 0, 0, 0, |
| 4905 | 0, 0, 0, 0, |
| 4906 | 0, 18, 19, 0, |
| 4907 | 0, 20, 21, 0, |
| 4908 | 0, 22, 23, 0, |
| 4909 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4910 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4911 | 0, 0, 0, 0, |
| 4912 | 0, 0, 0, 0, |
| 4913 | 0, 0, 0, 0, |
| 4914 | 0, 0, 0, 0, |
| 4915 | 0, 0, 0, 0, |
| 4916 | 0, 0, 0, 0, |
| 4917 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4918 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4919 | 0, 0, 0, 0, |
| 4920 | 0, 0, 0, 0, |
| 4921 | 0, 0, 0, 0, |
| 4922 | 0, 0, 0, 0, |
| 4923 | 0, 0, 0, 0, |
| 4924 | 0, 0, 0, 0, |
| 4925 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4926 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4927 | 0, 0, 0, 0, |
| 4928 | 0, 0, 0, 0, |
| 4929 | 0, 0, 0, 0, |
| 4930 | 0, 0, 0, 0, |
| 4931 | 0, 0, 0, 0, |
| 4932 | 0, 0, 0, 0, |
| 4933 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4934 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4935 | 0, 0, 0, 0, |
| 4936 | 0, 0, 0, 0, |
| 4937 | 0, 0, 0, 0, |
| 4938 | 0, 0, 0, 0, |
| 4939 | 0, 0, 0, 0, |
| 4940 | 0, 0, 0, 0, |
| 4941 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4942 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4943 | 0, 0, 0, 0, |
| 4944 | 0, 0, 0, 0, |
| 4945 | 0, 0, 0, 0, |
| 4946 | 0, 0, 0, 0, |
| 4947 | 0, 0, 0, 0, |
| 4948 | 0, 0, 0, 0, |
| 4949 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4950 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4951 | 0, 0, 0, 0, |
| 4952 | 0, 0, 0, 0, |
| 4953 | 0, 0, 0, 0, |
| 4954 | 0, 0, 0, 0, |
| 4955 | 0, 0, 0, 0, |
| 4956 | 0, 0, 0, 0, |
| 4957 | 0, 0, 0, 0 |
| 4958 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4959 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4960 | auto inputTensor = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>(inputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4961 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4962 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 4963 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, std::vector<T>(expectedOutputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4964 | |
| 4965 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4966 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4967 | |
| 4968 | armnn::PadQueueDescriptor descriptor; |
| 4969 | |
| 4970 | std::vector<std::pair<unsigned int, unsigned int>> PadList; |
| 4971 | PadList.push_back(std::pair<unsigned int, unsigned int>(1,1)); |
| 4972 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,1)); |
| 4973 | PadList.push_back(std::pair<unsigned int, unsigned int>(3,1)); |
| 4974 | PadList.push_back(std::pair<unsigned int, unsigned int>(1,1)); |
| 4975 | |
| 4976 | descriptor.m_Parameters.m_PadList = PadList; |
| 4977 | armnn::WorkloadInfo info; |
| 4978 | |
| 4979 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4980 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4981 | |
| 4982 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info); |
| 4983 | |
| 4984 | inputHandle->Allocate(); |
| 4985 | outputHandle->Allocate(); |
| 4986 | |
| 4987 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0][0]); |
| 4988 | |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 4989 | workload->Execute(); |
| 4990 | |
| 4991 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4992 | |
| 4993 | return result; |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4994 | } |
| 4995 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4996 | LayerTestResult<uint8_t, 2> PadUint82dTest( |
| 4997 | armnn::IWorkloadFactory& workloadFactory, |
| 4998 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 4999 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5000 | return Pad2dTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5001 | } |
| 5002 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5003 | LayerTestResult<uint8_t, 3> PadUint83dTest( |
| 5004 | armnn::IWorkloadFactory& workloadFactory, |
| 5005 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5006 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5007 | return Pad3dTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5008 | } |
| 5009 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5010 | LayerTestResult<uint8_t, 4> PadUint84dTest( |
| 5011 | armnn::IWorkloadFactory& workloadFactory, |
| 5012 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5013 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5014 | return Pad4dTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5015 | } |
| 5016 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5017 | LayerTestResult<float, 2> PadFloat322dTest( |
| 5018 | armnn::IWorkloadFactory& workloadFactory, |
| 5019 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5020 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5021 | return Pad2dTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5022 | } |
| 5023 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5024 | LayerTestResult<float, 3> PadFloat323dTest( |
| 5025 | armnn::IWorkloadFactory& workloadFactory, |
| 5026 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5027 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5028 | return Pad3dTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5029 | } |
| 5030 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5031 | LayerTestResult<float, 4> PadFloat324dTest( |
| 5032 | armnn::IWorkloadFactory& workloadFactory, |
| 5033 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5034 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5035 | return Pad4dTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5036 | } |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5037 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5038 | LayerTestResult<float, 4> L2Normalization1dTest( |
| 5039 | armnn::IWorkloadFactory& workloadFactory, |
| 5040 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 5041 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5042 | { |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5043 | // Width: 1 |
| 5044 | // Height: 1 |
| 5045 | // Channels: 10 |
| 5046 | // BatchSize: 1 |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5047 | unsigned int numberOfBatches = 1; |
| 5048 | unsigned int numberOfChannels = 10; |
| 5049 | unsigned int height = 1; |
| 5050 | unsigned int width = 1; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5051 | |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5052 | |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 5053 | const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5054 | numberOfBatches, numberOfChannels, height, width, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5055 | std::vector<float> inputValues |
| 5056 | { |
| 5057 | // Batch 0, Channel 0, Height (1) x Width (1) |
| 5058 | 1.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5059 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5060 | // Batch 0, Channel 1, Height (1) x Width (1) |
| 5061 | 2.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5062 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5063 | // Batch 0, Channel 2, Height (1) x Width (1) |
| 5064 | 3.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5065 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5066 | // Batch 0, Channel 3, Height (1) x Width (1) |
| 5067 | 4.0f, |
| 5068 | |
| 5069 | // Batch 0, Channel 4, Height (1) x Width (1) |
| 5070 | 5.0f, |
| 5071 | |
| 5072 | // Batch 0, Channel 5, Height (1) x Width (1) |
| 5073 | 6.0f, |
| 5074 | |
| 5075 | // Batch 0, Channel 6, Height (1) x Width (1) |
| 5076 | 7.0f, |
| 5077 | |
| 5078 | // Batch 0, Channel 7, Height (1) x Width (1) |
| 5079 | 8.0f, |
| 5080 | |
| 5081 | // Batch 0, Channel 8, Height (1) x Width (1) |
| 5082 | 9.0f, |
| 5083 | |
| 5084 | // Batch 0, Channel 9, Height (1) x Width (1) |
| 5085 | 10.0f |
| 5086 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5087 | const float approxInvL2Norm = 0.050964719f; |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5088 | std::vector<float> expectedOutputValues |
| 5089 | { |
| 5090 | // Batch 0, Channel 0, Height (1) x Width (1) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5091 | 1.0f * approxInvL2Norm, |
| 5092 | 2.0f * approxInvL2Norm, |
| 5093 | 3.0f * approxInvL2Norm, |
| 5094 | 4.0f * approxInvL2Norm, |
| 5095 | 5.0f * approxInvL2Norm, |
| 5096 | 6.0f * approxInvL2Norm, |
| 5097 | 7.0f * approxInvL2Norm, |
| 5098 | 8.0f * approxInvL2Norm, |
| 5099 | 9.0f * approxInvL2Norm, |
| 5100 | 10.0f * approxInvL2Norm |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5101 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5102 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5103 | |
| 5104 | return L2NormalizationTestImpl(workloadFactory, memoryManager, inputOutputShape, |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5105 | inputValues, expectedOutputValues, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5106 | } |
| 5107 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5108 | LayerTestResult<float, 4> L2Normalization2dTest( |
| 5109 | armnn::IWorkloadFactory& workloadFactory, |
| 5110 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 5111 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5112 | { |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5113 | // Width: 5 |
| 5114 | // Height: 1 |
| 5115 | // Channels: 2 |
| 5116 | // BatchSize: 1 |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5117 | unsigned int numberOfBatches = 1; |
| 5118 | unsigned int numberOfChannels = 2; |
| 5119 | unsigned int height = 1; |
| 5120 | unsigned int width = 5; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5121 | |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 5122 | const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5123 | numberOfBatches, numberOfChannels, height, width, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5124 | std::vector<float> inputValues |
| 5125 | { |
| 5126 | // Batch 0, Channel 0, Height (1) x Width (5) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5127 | 1.0f, 3.0f, 5.0f, 7.0f, 9.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5128 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5129 | // Batch 0, Channel 1, Height (1) x Width (5) |
| 5130 | 2.0f, 4.0f, 6.0f, 8.0f, 10.0f |
| 5131 | }; |
| 5132 | std::vector<float> expectedOutputValues |
| 5133 | { |
| 5134 | // Batch 0, Channel 0, Height (1) x Width (5) |
| 5135 | 1.0f * CalcInvL2Norm({ 1.0f, 2.0f }), |
| 5136 | 3.0f * CalcInvL2Norm({ 3.0f, 4.0f }), |
| 5137 | 5.0f * CalcInvL2Norm({ 5.0f, 6.0f }), |
| 5138 | 7.0f * CalcInvL2Norm({ 7.0f, 8.0f }), |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5139 | 9.0f * CalcInvL2Norm({ 9.0f, 10.0f }), |
| 5140 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5141 | // Batch 0, Channel 1, Height (1) x Width (5) |
| 5142 | 2.0f * CalcInvL2Norm({ 1.0f, 2.0f }), |
| 5143 | 4.0f * CalcInvL2Norm({ 3.0f, 4.0f }), |
| 5144 | 6.0f * CalcInvL2Norm({ 5.0f, 6.0f }), |
| 5145 | 8.0f * CalcInvL2Norm({ 7.0f, 8.0f }), |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5146 | 10.0f * CalcInvL2Norm({ 9.0f, 10.0f }) |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5147 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5148 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5149 | return L2NormalizationTestImpl(workloadFactory, memoryManager, inputOutputShape, |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5150 | inputValues, expectedOutputValues, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5151 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5152 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5153 | LayerTestResult<float, 4> L2Normalization3dTest( |
| 5154 | armnn::IWorkloadFactory& workloadFactory, |
| 5155 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 5156 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5157 | { |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5158 | // Width: 3 |
| 5159 | // Height: 4 |
| 5160 | // Channels: 2 |
| 5161 | // BatchSize: 1 |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5162 | unsigned int numberOfBatches = 1; |
| 5163 | unsigned int numberOfChannels = 2; |
| 5164 | unsigned int height = 4; |
| 5165 | unsigned int width = 3; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5166 | |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 5167 | const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5168 | numberOfBatches, numberOfChannels, height, width, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5169 | std::vector<float> inputValues |
| 5170 | { |
| 5171 | // Batch 0, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5172 | 119.0f, 21.0f, 150.0f, |
| 5173 | 149.0f, 32.0f, 179.0f, |
| 5174 | 15.0f, 227.0f, 141.0f, |
| 5175 | 147.0f, 199.0f, 220.0f, |
| 5176 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5177 | // Batch 0, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5178 | 110.0f, 140.0f, 73.0f, |
| 5179 | 211.0f, 212.0f, 89.0f, |
| 5180 | 24.0f, 138.0f, 188.0f, |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5181 | 162.0f, 12.0f, 161.0f |
| 5182 | }; |
| 5183 | std::vector<float> expectedOutputValues |
| 5184 | { |
| 5185 | // Batch 0, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5186 | 119.0f * CalcInvL2Norm({ 119.0f, 110.0f }), |
| 5187 | 21.0f * CalcInvL2Norm({ 21.0f, 140.0f }), |
| 5188 | 150.0f * CalcInvL2Norm({ 150.0f, 73.0f }), |
| 5189 | 149.0f * CalcInvL2Norm({ 149.0f, 211.0f }), |
| 5190 | 32.0f * CalcInvL2Norm({ 32.0f, 212.0f }), |
| 5191 | 179.0f * CalcInvL2Norm({ 179.0f, 89.0f }), |
| 5192 | 15.0f * CalcInvL2Norm({ 15.0f, 24.0f }), |
| 5193 | 227.0f * CalcInvL2Norm({ 227.0f, 138.0f }), |
| 5194 | 141.0f * CalcInvL2Norm({ 141.0f, 188.0f }), |
| 5195 | 147.0f * CalcInvL2Norm({ 147.0f, 162.0f }), |
| 5196 | 199.0f * CalcInvL2Norm({ 199.0f, 12.0f }), |
| 5197 | 220.0f * CalcInvL2Norm({ 220.0f, 161.0f }), |
| 5198 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5199 | // Batch 0, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5200 | 110.0f * CalcInvL2Norm({ 119.0f, 110.0f }), |
| 5201 | 140.0f * CalcInvL2Norm({ 21.0f, 140.0f }), |
| 5202 | 73.0f * CalcInvL2Norm({ 150.0f, 73.0f }), |
| 5203 | 211.0f * CalcInvL2Norm({ 149.0f, 211.0f }), |
| 5204 | 212.0f * CalcInvL2Norm({ 32.0f, 212.0f }), |
| 5205 | 89.0f * CalcInvL2Norm({ 179.0f, 89.0f }), |
| 5206 | 24.0f * CalcInvL2Norm({ 15.0f, 24.0f }), |
| 5207 | 138.0f * CalcInvL2Norm({ 227.0f, 138.0f }), |
| 5208 | 188.0f * CalcInvL2Norm({ 141.0f, 188.0f }), |
| 5209 | 162.0f * CalcInvL2Norm({ 147.0f, 162.0f }), |
| 5210 | 12.0f * CalcInvL2Norm({ 199.0f, 12.0f }), |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5211 | 161.0f * CalcInvL2Norm({ 220.0f, 161.0f }) |
| 5212 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5213 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5214 | return L2NormalizationTestImpl(workloadFactory, memoryManager, inputOutputShape, |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5215 | inputValues, expectedOutputValues, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5216 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5217 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5218 | LayerTestResult<float, 4> L2Normalization4dTest( |
| 5219 | armnn::IWorkloadFactory& workloadFactory, |
| 5220 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 5221 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5222 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5223 | // Width: 3 |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5224 | // Height: 4 |
| 5225 | // Channels: 3 |
| 5226 | // BatchSize: 2 |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5227 | unsigned int numberOfBatches = 2; |
| 5228 | unsigned int numberOfChannels = 3; |
| 5229 | unsigned int height = 4; |
| 5230 | unsigned int width = 3; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5231 | |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 5232 | const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5233 | numberOfBatches, numberOfChannels, height, width, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5234 | std::vector<float> inputValues |
| 5235 | { |
| 5236 | // Batch 0, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5237 | 235.0f, 46.0f, 178.0f, |
| 5238 | 100.0f, 123.0f, 19.0f, |
| 5239 | 172.0f, 74.0f, 250.0f, |
| 5240 | 6.0f, 195.0f, 80.0f, |
| 5241 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5242 | // Batch 0, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5243 | 113.0f, 95.0f, 202.0f, |
| 5244 | 77.0f, 114.0f, 71.0f, |
| 5245 | 122.0f, 246.0f, 166.0f, |
| 5246 | 82.0f, 28.0f, 37.0f, |
| 5247 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5248 | // Batch 0, Channel 2, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5249 | 56.0f, 170.0f, 162.0f, |
| 5250 | 194.0f, 89.0f, 254.0f, |
| 5251 | 12.0f, 209.0f, 200.0f, |
| 5252 | 1.0f, 64.0f, 54.0f, |
| 5253 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5254 | // Batch 1, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5255 | 67.0f, 90.0f, 49.0f, |
| 5256 | 7.0f, 163.0f, 18.0f, |
| 5257 | 25.0f, 117.0f, 103.0f, |
| 5258 | 247.0f, 59.0f, 189.0f, |
| 5259 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5260 | // Batch 1, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5261 | 239.0f, 104.0f, 199.0f, |
| 5262 | 17.0f, 124.0f, 153.0f, |
| 5263 | 222.0f, 217.0f, 75.0f, |
| 5264 | 32.0f, 126.0f, 21.0f, |
| 5265 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5266 | // Batch 1, Channel 2, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5267 | 97.0f, 145.0f, 215.0f, |
| 5268 | 115.0f, 116.0f, 238.0f, |
| 5269 | 226.0f, 16.0f, 132.0f, |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5270 | 92.0f, 125.0f, 88.0f |
| 5271 | }; |
| 5272 | std::vector<float> expectedOutputValues |
| 5273 | { |
| 5274 | // Batch 0, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5275 | 235.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }), |
| 5276 | 46.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }), |
| 5277 | 178.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }), |
| 5278 | 100.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }), |
| 5279 | 123.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }), |
| 5280 | 19.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }), |
| 5281 | 172.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }), |
| 5282 | 74.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }), |
| 5283 | 250.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }), |
| 5284 | 6.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }), |
| 5285 | 195.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }), |
| 5286 | 80.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }), |
| 5287 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5288 | // Batch 0, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5289 | 113.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }), |
| 5290 | 95.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }), |
| 5291 | 202.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }), |
| 5292 | 77.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }), |
| 5293 | 114.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }), |
| 5294 | 71.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }), |
| 5295 | 122.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }), |
| 5296 | 246.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }), |
| 5297 | 166.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }), |
| 5298 | 82.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }), |
| 5299 | 28.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }), |
| 5300 | 37.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }), |
| 5301 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5302 | // Batch 0, Channel 2, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5303 | 56.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }), |
| 5304 | 170.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }), |
| 5305 | 162.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }), |
| 5306 | 194.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }), |
| 5307 | 89.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }), |
| 5308 | 254.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }), |
| 5309 | 12.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }), |
| 5310 | 209.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }), |
| 5311 | 200.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }), |
| 5312 | 1.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }), |
| 5313 | 64.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }), |
| 5314 | 54.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }), |
| 5315 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5316 | // Batch 1, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5317 | 67.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }), |
| 5318 | 90.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }), |
| 5319 | 49.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }), |
| 5320 | 7.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }), |
| 5321 | 163.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }), |
| 5322 | 18.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }), |
| 5323 | 25.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }), |
| 5324 | 117.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }), |
| 5325 | 103.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }), |
| 5326 | 247.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }), |
| 5327 | 59.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }), |
| 5328 | 189.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f }), |
| 5329 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5330 | // Batch 1, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5331 | 239.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }), |
| 5332 | 104.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }), |
| 5333 | 199.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }), |
| 5334 | 17.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }), |
| 5335 | 124.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }), |
| 5336 | 153.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }), |
| 5337 | 222.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }), |
| 5338 | 217.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }), |
| 5339 | 75.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }), |
| 5340 | 32.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }), |
| 5341 | 126.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }), |
| 5342 | 21.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f }), |
| 5343 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5344 | // Batch 1, Channel 2, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5345 | 97.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }), |
| 5346 | 145.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }), |
| 5347 | 215.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }), |
| 5348 | 115.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }), |
| 5349 | 116.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }), |
| 5350 | 238.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }), |
| 5351 | 226.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }), |
| 5352 | 16.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }), |
| 5353 | 132.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }), |
| 5354 | 92.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }), |
| 5355 | 125.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }), |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5356 | 88.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f }) |
| 5357 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5358 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5359 | return L2NormalizationTestImpl(workloadFactory, memoryManager, inputOutputShape, |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5360 | inputValues, expectedOutputValues, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5361 | } |
| 5362 | |
| 5363 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5364 | LayerTestResult<T, 4> ConstantTestImpl( |
| 5365 | armnn::IWorkloadFactory& workloadFactory, |
| 5366 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5367 | float qScale, |
| 5368 | int32_t qOffset) |
| 5369 | { |
| 5370 | constexpr unsigned int inputWidth = 3; |
| 5371 | constexpr unsigned int inputHeight = 4; |
| 5372 | constexpr unsigned int inputChannels = 3; |
| 5373 | constexpr unsigned int inputBatchSize = 2; |
| 5374 | |
| 5375 | constexpr unsigned int outputWidth = inputWidth; |
| 5376 | constexpr unsigned int outputHeight = inputHeight; |
| 5377 | constexpr unsigned int outputChannels = inputChannels; |
| 5378 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 5379 | |
| 5380 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 5381 | armnn::GetDataType<T>()); |
| 5382 | |
| 5383 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 5384 | armnn::GetDataType<T>()); |
| 5385 | |
| 5386 | // Set quantization parameters if the requested type is a quantized type. |
| 5387 | if(armnn::IsQuantizedType<T>()) |
| 5388 | { |
| 5389 | inputTensorInfo.SetQuantizationScale(qScale); |
| 5390 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 5391 | outputTensorInfo.SetQuantizationScale(qScale); |
| 5392 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 5393 | } |
| 5394 | |
| 5395 | auto input = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>( |
| 5396 | QuantizedVector<T>(qScale, qOffset, { |
| 5397 | // Batch 0, Channel 0 |
| 5398 | 235.0f, 46.0f, 178.0f, |
| 5399 | 100.0f, 123.0f, 19.0f, |
| 5400 | 172.0f, 74.0f, 250.0f, |
| 5401 | 6.0f, 195.0f, 80.0f, |
| 5402 | |
| 5403 | // Batch 0, Channel 1 |
| 5404 | 113.0f, 95.0f, 202.0f, |
| 5405 | 77.0f, 114.0f, 71.0f, |
| 5406 | 122.0f, 246.0f, 166.0f, |
| 5407 | 82.0f, 28.0f, 37.0f, |
| 5408 | |
| 5409 | // Batch 0, Channel 2 |
| 5410 | 56.0f, 170.0f, 162.0f, |
| 5411 | 194.0f, 89.0f, 254.0f, |
| 5412 | 12.0f, 209.0f, 200.0f, |
| 5413 | 1.0f, 64.0f, 54.0f, |
| 5414 | |
| 5415 | // Batch 1, Channel 0 |
| 5416 | 67.0f, 90.0f, 49.0f, |
| 5417 | 7.0f, 163.0f, 18.0f, |
| 5418 | 25.0f, 117.0f, 103.0f, |
| 5419 | 247.0f, 59.0f, 189.0f, |
| 5420 | |
| 5421 | // Batch 1, Channel 1 |
| 5422 | 239.0f, 104.0f, 199.0f, |
| 5423 | 17.0f, 124.0f, 153.0f, |
| 5424 | 222.0f, 217.0f, 75.0f, |
| 5425 | 32.0f, 126.0f, 21.0f, |
| 5426 | |
| 5427 | // Batch 1, Channel 2 |
| 5428 | 97.0f, 145.0f, 215.0f, |
| 5429 | 115.0f, 116.0f, 238.0f, |
| 5430 | 226.0f, 16.0f, 132.0f, |
| 5431 | 92.0f, 125.0f, 88.0f, |
| 5432 | }))); |
| 5433 | |
| 5434 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 5435 | result.outputExpected = input; |
| 5436 | |
| 5437 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5438 | |
| 5439 | armnn::ScopedCpuTensorHandle constantTensor(inputTensorInfo); |
| 5440 | AllocateAndCopyDataToITensorHandle(&constantTensor, &input[0][0][0][0]); |
| 5441 | |
| 5442 | armnn::ConstantQueueDescriptor descriptor; |
| 5443 | descriptor.m_LayerOutput = &constantTensor; |
| 5444 | |
| 5445 | armnn::WorkloadInfo info; |
| 5446 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 5447 | |
| 5448 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConstant(descriptor, info); |
| 5449 | |
| 5450 | outputHandle->Allocate(); |
| 5451 | |
| 5452 | workload->Execute(); |
| 5453 | |
| 5454 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 5455 | return result; |
| 5456 | } |
| 5457 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5458 | LayerTestResult<float, 4> ConstantTest( |
| 5459 | armnn::IWorkloadFactory& workloadFactory, |
| 5460 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5461 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5462 | return ConstantTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5463 | } |
| 5464 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5465 | LayerTestResult<uint8_t, 4> ConstantTestUint8( |
| 5466 | armnn::IWorkloadFactory& workloadFactory, |
| 5467 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5468 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5469 | return ConstantTestImpl<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5470 | } |
| 5471 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5472 | LayerTestResult<uint8_t, 3> MergerUint8Test( |
| 5473 | armnn::IWorkloadFactory& workloadFactory, |
| 5474 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5475 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5476 | unsigned int outputWidth = 3; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5477 | unsigned int outputHeight = 6; |
| 5478 | unsigned int outputChannels = 3; |
| 5479 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5480 | unsigned int inputWidth1 = 3; |
| 5481 | unsigned int inputHeight1 = 6; |
| 5482 | unsigned int inputChannels1 = 2; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5483 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5484 | unsigned int inputWidth2 = 3; |
| 5485 | unsigned int inputHeight2 = 6; |
| 5486 | unsigned int inputChannels2 = 1; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5487 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5488 | // Defines the tensor descriptors. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5489 | armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::QuantisedAsymm8); |
| 5490 | armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::QuantisedAsymm8); |
| 5491 | armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::QuantisedAsymm8); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5492 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5493 | // Arbitrary scale and offsets. They don't really matter as the merger operator doesn't dequantize/quantize them. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5494 | const float scale = 0.13497836f; |
| 5495 | const int32_t offset = -7; |
| 5496 | |
| 5497 | outputTensorInfo.SetQuantizationScale(scale); |
| 5498 | outputTensorInfo.SetQuantizationOffset(offset); |
| 5499 | inputTensorInfo1.SetQuantizationScale(scale); |
| 5500 | inputTensorInfo1.SetQuantizationOffset(offset); |
| 5501 | inputTensorInfo2.SetQuantizationScale(scale); |
| 5502 | inputTensorInfo2.SetQuantizationOffset(offset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5503 | |
| 5504 | LayerTestResult<uint8_t, 3> ret(outputTensorInfo); |
| 5505 | |
| 5506 | ret.outputExpected = MakeTensor<uint8_t, 3>(outputTensorInfo, std::vector<uint8_t>( |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5507 | { |
| 5508 | 1, 2, 3, |
| 5509 | 4, 5, 6, |
| 5510 | 7, 8, 9, |
| 5511 | 10, 11, 12, |
| 5512 | 13, 14, 15, |
| 5513 | 16, 17, 18, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5514 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5515 | 19, 20, 21, |
| 5516 | 22, 23, 24, |
| 5517 | 25, 26, 27, |
| 5518 | 28, 29, 30, |
| 5519 | 31, 32, 33, |
| 5520 | 34, 35, 36, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5521 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5522 | 37, 38, 39, |
| 5523 | 40, 41, 42, |
| 5524 | 43, 44, 45, |
| 5525 | 46, 47, 48, |
| 5526 | 49, 50, 51, |
| 5527 | 52, 53, 54, |
| 5528 | }) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5529 | ); |
| 5530 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5531 | auto input1 = MakeTensor<uint8_t, 3>(inputTensorInfo1, std::vector<uint8_t>( |
| 5532 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5533 | 1, 2, 3, |
| 5534 | 4, 5, 6, |
| 5535 | 7, 8, 9, |
| 5536 | 10, 11, 12, |
| 5537 | 13, 14, 15, |
| 5538 | 16, 17, 18, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5539 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5540 | 19, 20, 21, |
| 5541 | 22, 23, 24, |
| 5542 | 25, 26, 27, |
| 5543 | 28, 29, 30, |
| 5544 | 31, 32, 33, |
| 5545 | 34, 35, 36, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5546 | }) |
| 5547 | ); |
| 5548 | |
| 5549 | auto input2 = MakeTensor<uint8_t, 3>(inputTensorInfo2, std::vector<uint8_t>( |
| 5550 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5551 | 37, 38, 39, |
| 5552 | 40, 41, 42, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5553 | 43, 44, 45, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5554 | 46, 47, 48, |
| 5555 | 49, 50, 51, |
| 5556 | 52, 53, 54, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5557 | }) |
| 5558 | ); |
| 5559 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5560 | std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0]. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5561 | armnn::MergerQueueDescriptor::ViewOrigin window1(wOrigin1); |
| 5562 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5563 | std::vector<unsigned int> wOrigin2 = { 2, 0, 0 }; //Extent of the window is defined by size of input[1]. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5564 | armnn::MergerQueueDescriptor::ViewOrigin window2(wOrigin2); |
| 5565 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5566 | |
| 5567 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5568 | |
| 5569 | bool subTensorsSupported = workloadFactory.SupportsSubTensors(); |
| 5570 | |
| 5571 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = |
| 5572 | subTensorsSupported ? |
| 5573 | workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : |
| 5574 | workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 5575 | |
| 5576 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = |
| 5577 | subTensorsSupported ? |
| 5578 | workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : |
| 5579 | workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 5580 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5581 | |
| 5582 | armnn::MergerQueueDescriptor data; |
| 5583 | armnn::WorkloadInfo info; |
| 5584 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 5585 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5586 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 5587 | |
| 5588 | data.m_ViewOrigins.push_back(window1); |
| 5589 | data.m_ViewOrigins.push_back(window2); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5590 | |
| 5591 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMerger(data, info); |
| 5592 | |
| 5593 | inputHandle1->Allocate(); |
| 5594 | inputHandle2->Allocate(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5595 | outputHandle->Allocate(); |
| 5596 | |
| 5597 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]); |
| 5598 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5599 | |
| 5600 | workload->Execute(); |
| 5601 | |
| 5602 | CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get()); |
| 5603 | |
| 5604 | return ret; |
| 5605 | } |
| 5606 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5607 | LayerTestResult<uint8_t, 4> AdditionUint8Test( |
| 5608 | armnn::IWorkloadFactory& workloadFactory, |
| 5609 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5610 | { |
| 5611 | unsigned int batchSize = 1; |
| 5612 | unsigned int channels = 2; |
| 5613 | unsigned int height = 2; |
| 5614 | unsigned int width = 3; |
| 5615 | |
| 5616 | const float scale = 7.0f; |
| 5617 | const int32_t offset = 3; |
| 5618 | |
| 5619 | armnn::TensorInfo inputTensorInfo1, inputTensorInfo2; |
| 5620 | armnn::TensorInfo outputTensorInfo; |
| 5621 | |
| 5622 | const unsigned int shape[] = { batchSize, channels, height, width }; |
| 5623 | inputTensorInfo1 = armnn::TensorInfo(4, shape, armnn::DataType::QuantisedAsymm8); |
| 5624 | inputTensorInfo1.SetQuantizationScale(scale); |
| 5625 | inputTensorInfo1.SetQuantizationOffset(offset); |
| 5626 | |
| 5627 | inputTensorInfo2 = armnn::TensorInfo(4, shape, armnn::DataType::QuantisedAsymm8); |
| 5628 | inputTensorInfo2.SetQuantizationScale(scale); |
| 5629 | inputTensorInfo2.SetQuantizationOffset(offset); |
| 5630 | |
| 5631 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::QuantisedAsymm8); |
| 5632 | outputTensorInfo.SetQuantizationScale(scale); |
| 5633 | outputTensorInfo.SetQuantizationOffset(offset); |
| 5634 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5635 | // See dequantized values to the right. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5636 | auto input1 = MakeTensor<uint8_t, 4>(inputTensorInfo1, std::vector<uint8_t>( |
| 5637 | { |
| 5638 | 63, 35, 77, 70, 56, 112, // 420, 224, 518, 469, 371, 763 |
| 5639 | 203, 28, 252, 168, 245, 91 // 1400, 175, 1743, 1155, 1694, 616 |
| 5640 | })); |
| 5641 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5642 | // See dequantized values to the right. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5643 | auto input2 = MakeTensor<uint8_t, 4>(inputTensorInfo1, std::vector<uint8_t>( |
| 5644 | { |
| 5645 | 21, 7, 175, 231, 175, 210, // 126, 28, 1204, 1596, 1204, 1449 |
| 5646 | 126, 161, 63, 21, 105, 126 // 861, 1106, 420, 126, 714, 861 |
| 5647 | })); |
| 5648 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5649 | // See dequantized values to the right. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5650 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 5651 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>( |
| 5652 | { |
| 5653 | 81, 39, 249, 255, 228, 255, // 546, 252, 1722, 2065(clamped), 1575, 2212(clamped) |
| 5654 | 255, 186, 255, 186, 255, 214, // 2261(clamped), 1281, 2163(clamped), 1281, 2408(clamped), 1477 |
| 5655 | })); |
| 5656 | |
| 5657 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 5658 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 5659 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5660 | |
| 5661 | armnn::AdditionQueueDescriptor data; |
| 5662 | armnn::WorkloadInfo info; |
| 5663 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 5664 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 5665 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 5666 | |
| 5667 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 5668 | |
| 5669 | inputHandle1->Allocate(); |
| 5670 | inputHandle2->Allocate(); |
| 5671 | outputHandle->Allocate(); |
| 5672 | |
| 5673 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 5674 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 5675 | |
| 5676 | workload->Execute(); |
| 5677 | |
| 5678 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 5679 | |
| 5680 | return result; |
| 5681 | } |
| 5682 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5683 | namespace |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5684 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5685 | LayerTestResult<uint8_t, 4> MultiplicationUint8TestHelper( |
| 5686 | armnn::IWorkloadFactory& workloadFactory, |
| 5687 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 5688 | const unsigned int shape0[4], |
| 5689 | const std::vector<uint8_t> & values0, |
| 5690 | float scale0, |
| 5691 | int32_t offset0, |
| 5692 | const unsigned int shape1[4], |
| 5693 | const std::vector<uint8_t> & values1, |
| 5694 | float scale1, |
| 5695 | int32_t offset1, |
| 5696 | const unsigned int outShape[4], |
| 5697 | const std::vector<uint8_t> & outValues, |
| 5698 | float outScale, |
| 5699 | int32_t outOffset) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5700 | { |
| 5701 | armnn::TensorInfo inputTensorInfo0(4, shape0, armnn::DataType::QuantisedAsymm8); |
| 5702 | armnn::TensorInfo inputTensorInfo1(4, shape1, armnn::DataType::QuantisedAsymm8); |
| 5703 | armnn::TensorInfo outputTensorInfo(4, outShape, armnn::DataType::QuantisedAsymm8); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5704 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5705 | inputTensorInfo0.SetQuantizationScale(scale0); |
| 5706 | inputTensorInfo0.SetQuantizationOffset(offset0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5707 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5708 | inputTensorInfo1.SetQuantizationScale(scale1); |
| 5709 | inputTensorInfo1.SetQuantizationOffset(offset1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5710 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5711 | outputTensorInfo.SetQuantizationScale(outScale); |
| 5712 | outputTensorInfo.SetQuantizationOffset(outOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5713 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5714 | auto input0 = MakeTensor<uint8_t, 4>(inputTensorInfo0, values0); |
| 5715 | auto input1 = MakeTensor<uint8_t, 4>(inputTensorInfo1, values1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5716 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5717 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5718 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, outValues); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5719 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5720 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5721 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5722 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5723 | |
| 5724 | armnn::MultiplicationQueueDescriptor data; |
| 5725 | armnn::WorkloadInfo info; |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5726 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 5727 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5728 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 5729 | |
| 5730 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMultiplication(data, info); |
| 5731 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5732 | inputHandle0->Allocate(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5733 | inputHandle1->Allocate(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5734 | outputHandle->Allocate(); |
| 5735 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5736 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5737 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5738 | |
| 5739 | workload->Execute(); |
| 5740 | |
| 5741 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 5742 | |
| 5743 | return result; |
| 5744 | } |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5745 | } // anonymous namespace |
| 5746 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5747 | LayerTestResult<uint8_t, 4> MultiplicationUint8Test( |
| 5748 | armnn::IWorkloadFactory& workloadFactory, |
| 5749 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5750 | { |
| 5751 | unsigned int batchSize = 1; |
| 5752 | unsigned int channels = 2; |
| 5753 | unsigned int height = 2; |
| 5754 | unsigned int width = 3; |
| 5755 | const unsigned int shape[] = { batchSize, channels, height, width }; |
| 5756 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5757 | // See dequantized values to the right. |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5758 | std::vector<uint8_t> input0({ |
| 5759 | 62, 37, 3, 172, 13, 111, // 244, 144, 8, 684, 48, 440, |
| 5760 | 188, 20, 73, 31, 23, 31 // 748, 76, 288, 120, 88, 120 |
| 5761 | }); |
| 5762 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5763 | // See dequantized values to the right. |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5764 | std::vector<uint8_t> input1({ |
| 5765 | 126, 240, 252, 183, 121, 247, // 384, 726, 762, 555, 369, 747, |
| 5766 | 48, 115, 151, 79, 78, 97 // 150, 351, 459, 243, 240, 297 |
| 5767 | }); |
| 5768 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5769 | // See dequantized values to the right. |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5770 | std::vector<uint8_t> output( |
| 5771 | { |
| 5772 | 64, 72, 0, 255, 8, 236, // 93696, 104544, 6096(clamped), 379620(clamped), 17712, 328680, |
| 5773 | 77, 15, 92, 16, 10, 21, // 112200, 26676, 132192, 29160, 21120, 35640 |
| 5774 | }); |
| 5775 | |
| 5776 | return MultiplicationUint8TestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5777 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5778 | shape, |
| 5779 | input0, |
| 5780 | 4.0f, |
| 5781 | 1, |
| 5782 | shape, |
| 5783 | input1, |
| 5784 | 3.0f, |
| 5785 | -2, |
| 5786 | shape, |
| 5787 | output, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5788 | 1366.255f, // Scale/offset chosen to have output values out of range. |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5789 | -5); |
| 5790 | } |
| 5791 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5792 | LayerTestResult<uint8_t, 4> MultiplicationBroadcast1ElementUint8Test( |
| 5793 | armnn::IWorkloadFactory& workloadFactory, |
| 5794 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5795 | { |
| 5796 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 5797 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 5798 | |
| 5799 | std::vector<uint8_t> input0({ |
| 5800 | 1, 2, 3, 4, 5, 6, |
| 5801 | 7, 8, 9, 10, 11, 12 |
| 5802 | }); |
| 5803 | |
| 5804 | std::vector<uint8_t> input1({2}); |
| 5805 | |
| 5806 | std::vector<uint8_t> output({ |
| 5807 | 2, 4, 6, 8, 10, 12, |
| 5808 | 14, 16, 18, 20, 22, 24 |
| 5809 | }); |
| 5810 | |
| 5811 | return MultiplicationUint8TestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5812 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5813 | shape0, |
| 5814 | input0, |
| 5815 | 1.0f, |
| 5816 | 0, |
| 5817 | shape1, |
| 5818 | input1, |
| 5819 | 1.0f, |
| 5820 | 0, |
| 5821 | shape0, |
| 5822 | output, |
| 5823 | 1.0f, |
| 5824 | 0); |
| 5825 | } |
| 5826 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5827 | LayerTestResult<uint8_t, 4> MultiplicationBroadcast1DVectorUint8Test( |
| 5828 | armnn::IWorkloadFactory& workloadFactory, |
| 5829 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5830 | { |
| 5831 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 5832 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 5833 | |
| 5834 | std::vector<uint8_t> input0({ |
| 5835 | 1, 2, 3, 4, 5, 6, |
| 5836 | 7, 8, 9, 10, 11, 12 |
| 5837 | }); |
| 5838 | |
| 5839 | std::vector<uint8_t> input1({1, 2, 3}); |
| 5840 | |
| 5841 | std::vector<uint8_t> output({ |
| 5842 | 1, 4, 9, 4, 10, 18, |
| 5843 | 7, 16, 27, 10, 22, 36 |
| 5844 | }); |
| 5845 | |
| 5846 | return MultiplicationUint8TestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5847 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 5848 | shape0, |
| 5849 | input0, |
| 5850 | 1.0f, |
| 5851 | 0, |
| 5852 | shape1, |
| 5853 | input1, |
| 5854 | 1.0f, |
| 5855 | 0, |
| 5856 | shape0, |
| 5857 | output, |
| 5858 | 1.0f, |
| 5859 | 0); |
| 5860 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5861 | |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5862 | namespace |
| 5863 | { |
| 5864 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5865 | LayerTestResult<T, 4> SubtractionTestHelper( |
| 5866 | armnn::IWorkloadFactory& workloadFactory, |
| 5867 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 5868 | const unsigned int shape0[4], |
| 5869 | const std::vector<T>& values0, |
| 5870 | float scale0, |
| 5871 | int32_t offset0, |
| 5872 | const unsigned int shape1[4], |
| 5873 | const std::vector<T> & values1, |
| 5874 | float scale1, |
| 5875 | int32_t offset1, |
| 5876 | const unsigned int outShape[4], |
| 5877 | const std::vector<T> & outValues, |
| 5878 | float outScale, |
| 5879 | int32_t outOffset) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5880 | { |
| 5881 | auto dataType = (std::is_same<T, uint8_t>::value ? |
| 5882 | armnn::DataType::QuantisedAsymm8 : |
| 5883 | armnn::DataType::Float32); |
| 5884 | |
| 5885 | armnn::TensorInfo inputTensorInfo0(4, shape0, dataType); |
| 5886 | armnn::TensorInfo inputTensorInfo1(4, shape1, dataType); |
| 5887 | armnn::TensorInfo outputTensorInfo(4, outShape, dataType); |
| 5888 | |
| 5889 | inputTensorInfo0.SetQuantizationScale(scale0); |
| 5890 | inputTensorInfo0.SetQuantizationOffset(offset0); |
| 5891 | |
| 5892 | inputTensorInfo1.SetQuantizationScale(scale1); |
| 5893 | inputTensorInfo1.SetQuantizationOffset(offset1); |
| 5894 | |
| 5895 | outputTensorInfo.SetQuantizationScale(outScale); |
| 5896 | outputTensorInfo.SetQuantizationOffset(outOffset); |
| 5897 | |
| 5898 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, values0); |
| 5899 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, values1); |
| 5900 | |
| 5901 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 5902 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, outValues); |
| 5903 | |
| 5904 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 5905 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 5906 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5907 | |
| 5908 | armnn::SubtractionQueueDescriptor data; |
| 5909 | armnn::WorkloadInfo info; |
| 5910 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 5911 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 5912 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 5913 | |
| 5914 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateSubtraction(data, info); |
| 5915 | |
| 5916 | inputHandle0->Allocate(); |
| 5917 | inputHandle1->Allocate(); |
| 5918 | outputHandle->Allocate(); |
| 5919 | |
| 5920 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 5921 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 5922 | |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5923 | workload->Execute(); |
| 5924 | |
| 5925 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 5926 | |
| 5927 | return result; |
| 5928 | } |
| 5929 | } // anonymous namespace |
| 5930 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5931 | LayerTestResult<uint8_t, 4> SubtractionUint8Test( |
| 5932 | armnn::IWorkloadFactory& workloadFactory, |
| 5933 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5934 | { |
| 5935 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 5936 | const unsigned int shape1[] = { 1, 1, 2, 2 }; |
| 5937 | |
| 5938 | std::vector<uint8_t> input0({ 10, 12, 14, 16 }); |
| 5939 | std::vector<uint8_t> input1({ 1, 2, 1, 2 }); |
| 5940 | std::vector<uint8_t> output({ 3, 3, 5, 5 }); |
| 5941 | |
| 5942 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5943 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5944 | shape0, input0, 0.5f, 2, |
| 5945 | shape1, input1, 1.0f, 0, |
| 5946 | shape0, output, 1.0f, 0); |
| 5947 | } |
| 5948 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5949 | LayerTestResult<uint8_t, 4> SubtractionBroadcast1ElementUint8Test( |
| 5950 | armnn::IWorkloadFactory& workloadFactory, |
| 5951 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5952 | { |
| 5953 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 5954 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 5955 | |
| 5956 | std::vector<uint8_t> input0({ 10, 12, 14, 16 }); |
| 5957 | std::vector<uint8_t> input1({ 2 }); |
| 5958 | std::vector<uint8_t> output({ 5, 6, 7, 8 }); |
| 5959 | |
| 5960 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5961 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5962 | shape0, input0, 0.5f, 2, |
| 5963 | shape1, input1, 1.0f, 0, |
| 5964 | shape0, output, 1.0f, 3); |
| 5965 | } |
| 5966 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5967 | LayerTestResult<uint8_t, 4> SubtractionBroadcastUint8Test( |
| 5968 | armnn::IWorkloadFactory& workloadFactory, |
| 5969 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5970 | { |
| 5971 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 5972 | const unsigned int shape1[] = { 1, 1, 2, 1 }; |
| 5973 | |
| 5974 | std::vector<uint8_t> input0({ 10, 12, 14, 16 }); |
| 5975 | std::vector<uint8_t> input1({ 2, 1 }); |
| 5976 | std::vector<uint8_t> output({ 8, 11, 12, 15 }); |
| 5977 | |
| 5978 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5979 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5980 | shape0, input0, 1.0f, 0, |
| 5981 | shape1, input1, 1.0f, 0, |
| 5982 | shape0, output, 1.0f, 0); |
| 5983 | } |
| 5984 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5985 | LayerTestResult<float, 4> SubtractionTest( |
| 5986 | armnn::IWorkloadFactory& workloadFactory, |
| 5987 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5988 | { |
| 5989 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 5990 | const unsigned int shape1[] = { 1, 1, 2, 2 }; |
| 5991 | |
| 5992 | std::vector<float> input0({ 1, 2, 3, 4 }); |
| 5993 | std::vector<float> input1({ 1, -1, 0, 2 }); |
| 5994 | std::vector<float> output({ 0, 3, 3, 2 }); |
| 5995 | |
| 5996 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5997 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 5998 | shape0, input0, 1.0f, 0, |
| 5999 | shape1, input1, 1.0f, 0, |
| 6000 | shape0, output, 1.0f, 0); |
| 6001 | } |
| 6002 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6003 | LayerTestResult<float, 4> SubtractionBroadcast1ElementTest( |
| 6004 | armnn::IWorkloadFactory& workloadFactory, |
| 6005 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6006 | { |
| 6007 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 6008 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 6009 | |
| 6010 | std::vector<float> input0({ 1, 2, 3, 4 }); |
| 6011 | std::vector<float> input1({ 10 }); |
| 6012 | std::vector<float> output({ -9, -8, -7, -6 }); |
| 6013 | |
| 6014 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6015 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6016 | shape0, input0, 1.0f, 0, |
| 6017 | shape1, input1, 1.0f, 0, |
| 6018 | shape0, output, 1.0f, 0); |
| 6019 | } |
| 6020 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6021 | LayerTestResult<float, 4> SubtractionBroadcastTest( |
| 6022 | armnn::IWorkloadFactory& workloadFactory, |
| 6023 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6024 | { |
| 6025 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 6026 | const unsigned int shape1[] = { 1, 1, 1, 2 }; |
| 6027 | |
| 6028 | std::vector<float> input0({ 1, 2, 3, 4 }); |
| 6029 | std::vector<float> input1({ 10, -5 }); |
| 6030 | std::vector<float> output({ -9, 7, -7, 9 }); |
| 6031 | |
| 6032 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6033 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6034 | shape0, input0, 1.0f, 0, |
| 6035 | shape1, input1, 1.0f, 0, |
| 6036 | shape0, output, 1.0f, 0); |
| 6037 | } |
| 6038 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6039 | LayerTestResult<uint8_t, 4> ResizeBilinearNopUint8Test( |
| 6040 | armnn::IWorkloadFactory& workloadFactory, |
| 6041 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6042 | { |
| 6043 | constexpr unsigned int inputWidth = 4; |
| 6044 | constexpr unsigned int inputHeight = 4; |
| 6045 | constexpr unsigned int inputChannels = 1; |
| 6046 | constexpr unsigned int inputBatchSize = 1; |
| 6047 | |
| 6048 | constexpr unsigned int outputWidth = inputWidth; |
| 6049 | constexpr unsigned int outputHeight = inputHeight; |
| 6050 | constexpr unsigned int outputChannels = inputChannels; |
| 6051 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6052 | |
| 6053 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6054 | armnn::DataType::QuantisedAsymm8); |
| 6055 | inputTensorInfo.SetQuantizationScale(1.5f); |
| 6056 | inputTensorInfo.SetQuantizationOffset(-3); |
| 6057 | |
| 6058 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6059 | armnn::DataType::QuantisedAsymm8); |
| 6060 | outputTensorInfo.SetQuantizationScale(1.5f); |
| 6061 | outputTensorInfo.SetQuantizationOffset(-3); |
| 6062 | |
| 6063 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6064 | 1, 2, 3, 4, |
| 6065 | 2, 3, 4, 5, |
| 6066 | 3, 4, 5, 6, |
| 6067 | 4, 5, 6, 7 |
| 6068 | })); |
| 6069 | |
| 6070 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6071 | result.outputExpected = input; |
| 6072 | |
| 6073 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6074 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6075 | |
| 6076 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6077 | armnn::WorkloadInfo info; |
| 6078 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6079 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6080 | |
| 6081 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6082 | |
| 6083 | inputHandle->Allocate(); |
| 6084 | outputHandle->Allocate(); |
| 6085 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6086 | |
| 6087 | workload->Execute(); |
| 6088 | |
| 6089 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6090 | return result; |
| 6091 | } |
| 6092 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6093 | LayerTestResult<uint8_t, 4> SimpleResizeBilinearUint8Test( |
| 6094 | armnn::IWorkloadFactory& workloadFactory, |
| 6095 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6096 | { |
| 6097 | constexpr unsigned int inputWidth = 2; |
| 6098 | constexpr unsigned int inputHeight = 2; |
| 6099 | constexpr unsigned int inputChannels = 1; |
| 6100 | constexpr unsigned int inputBatchSize = 1; |
| 6101 | |
| 6102 | constexpr unsigned int outputWidth = inputWidth / 2; |
| 6103 | constexpr unsigned int outputHeight = inputHeight / 2; |
| 6104 | constexpr unsigned int outputChannels = inputChannels; |
| 6105 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6106 | |
| 6107 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6108 | armnn::DataType::QuantisedAsymm8); |
| 6109 | inputTensorInfo.SetQuantizationScale(0.1567f); |
| 6110 | inputTensorInfo.SetQuantizationOffset(1); |
| 6111 | |
| 6112 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6113 | armnn::DataType::QuantisedAsymm8); |
| 6114 | outputTensorInfo.SetQuantizationScale(0.1567f); |
| 6115 | outputTensorInfo.SetQuantizationOffset(1); |
| 6116 | |
| 6117 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6118 | 1, 255, |
| 6119 | 200, 250 |
| 6120 | })); |
| 6121 | |
| 6122 | // The 'resize bilinear' operation projects the top-left corner of output texels into the input image, |
| 6123 | // then figures out the interpolants and weights. Note this is different to projecting the centre of the |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 6124 | // output texel - and thus we'll expect the output 1x1 matrix to contain, as its single element, the value |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6125 | // that was at position (0,0) of the input matrix (rather than an average, which we would expect if projecting |
| 6126 | // the centre). |
| 6127 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6128 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>({ |
| 6129 | 1 |
| 6130 | })); |
| 6131 | |
| 6132 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6133 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6134 | |
| 6135 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6136 | armnn::WorkloadInfo info; |
| 6137 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6138 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6139 | |
| 6140 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6141 | |
| 6142 | inputHandle->Allocate(); |
| 6143 | outputHandle->Allocate(); |
| 6144 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6145 | |
| 6146 | workload->Execute(); |
| 6147 | |
| 6148 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6149 | return result; |
| 6150 | } |
| 6151 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6152 | LayerTestResult<uint8_t, 4> ResizeBilinearSqMinUint8Test( |
| 6153 | armnn::IWorkloadFactory& workloadFactory, |
| 6154 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6155 | { |
| 6156 | constexpr unsigned int inputWidth = 4; |
| 6157 | constexpr unsigned int inputHeight = 4; |
| 6158 | constexpr unsigned int inputChannels = 1; |
| 6159 | constexpr unsigned int inputBatchSize = 1; |
| 6160 | |
| 6161 | constexpr unsigned int outputWidth = inputWidth / 2; |
| 6162 | constexpr unsigned int outputHeight = inputHeight / 2; |
| 6163 | constexpr unsigned int outputChannels = inputChannels; |
| 6164 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6165 | |
| 6166 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6167 | armnn::DataType::QuantisedAsymm8); |
| 6168 | inputTensorInfo.SetQuantizationScale(3.141592f); |
| 6169 | inputTensorInfo.SetQuantizationOffset(3); |
| 6170 | |
| 6171 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6172 | armnn::DataType::QuantisedAsymm8); |
| 6173 | outputTensorInfo.SetQuantizationScale(3.141592f); |
| 6174 | outputTensorInfo.SetQuantizationOffset(3); |
| 6175 | |
| 6176 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6177 | 1, 2, 3, 4, |
| 6178 | 2, 3, 4, 5, |
| 6179 | 3, 4, 5, 6, |
| 6180 | 4, 5, 6, 7 |
| 6181 | })); |
| 6182 | |
| 6183 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6184 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>({ |
| 6185 | 1, 3, |
| 6186 | 3, 5 |
| 6187 | })); |
| 6188 | |
| 6189 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6190 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6191 | |
| 6192 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6193 | armnn::WorkloadInfo info; |
| 6194 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6195 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6196 | |
| 6197 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6198 | |
| 6199 | inputHandle->Allocate(); |
| 6200 | outputHandle->Allocate(); |
| 6201 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6202 | |
| 6203 | workload->Execute(); |
| 6204 | |
| 6205 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6206 | return result; |
| 6207 | } |
| 6208 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6209 | LayerTestResult<uint8_t, 4> ResizeBilinearMinUint8Test( |
| 6210 | armnn::IWorkloadFactory& workloadFactory, |
| 6211 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6212 | { |
| 6213 | constexpr unsigned int inputWidth = 3; |
| 6214 | constexpr unsigned int inputHeight = 2; |
| 6215 | constexpr unsigned int inputChannels = 1; |
| 6216 | constexpr unsigned int inputBatchSize = 1; |
| 6217 | |
| 6218 | constexpr unsigned int outputWidth = 2; |
| 6219 | constexpr unsigned int outputHeight = 1; |
| 6220 | constexpr unsigned int outputChannels = inputChannels; |
| 6221 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6222 | |
| 6223 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6224 | armnn::DataType::QuantisedAsymm8); |
| 6225 | inputTensorInfo.SetQuantizationScale(1.5f); |
| 6226 | inputTensorInfo.SetQuantizationOffset(-1); |
| 6227 | |
| 6228 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6229 | armnn::DataType::QuantisedAsymm8); |
| 6230 | outputTensorInfo.SetQuantizationScale(1.5f); |
| 6231 | outputTensorInfo.SetQuantizationOffset(-1); |
| 6232 | |
| 6233 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6234 | 1, 2, 3, // 3.0, 4.5, 6.0 |
| 6235 | 5, 8, 13 // 9.0, 13.5, 21.0 |
| 6236 | })); |
| 6237 | |
| 6238 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6239 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>({ |
| 6240 | 1, 3 // 3.0, 5.25 |
| 6241 | })); |
| 6242 | |
| 6243 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6244 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6245 | |
| 6246 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6247 | armnn::WorkloadInfo info; |
| 6248 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6249 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6250 | |
| 6251 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6252 | |
| 6253 | inputHandle->Allocate(); |
| 6254 | outputHandle->Allocate(); |
| 6255 | |
| 6256 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6257 | |
| 6258 | workload->Execute(); |
| 6259 | |
| 6260 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6261 | return result; |
| 6262 | } |
| 6263 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6264 | LayerTestResult<uint8_t, 4> ResizeBilinearMagUint8Test( |
| 6265 | armnn::IWorkloadFactory& workloadFactory, |
| 6266 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6267 | { |
| 6268 | constexpr unsigned int inputWidth = 2; |
| 6269 | constexpr unsigned int inputHeight = 3; |
| 6270 | constexpr unsigned int inputChannels = 1; |
| 6271 | constexpr unsigned int inputBatchSize = 1; |
| 6272 | |
| 6273 | constexpr unsigned int outputWidth = 5; |
| 6274 | constexpr unsigned int outputHeight = 3; |
| 6275 | constexpr unsigned int outputChannels = inputChannels; |
| 6276 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6277 | |
| 6278 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6279 | armnn::DataType::QuantisedAsymm8); |
| 6280 | inputTensorInfo.SetQuantizationScale(0.010765f); |
| 6281 | inputTensorInfo.SetQuantizationOffset(7); |
| 6282 | |
| 6283 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6284 | armnn::DataType::QuantisedAsymm8); |
| 6285 | outputTensorInfo.SetQuantizationScale(0.010132f); |
| 6286 | outputTensorInfo.SetQuantizationOffset(-18); |
| 6287 | |
| 6288 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6289 | 24, 228, // 0.183005, 2.379065, |
| 6290 | 105, 128, // 1.05497, 1.302565 |
| 6291 | 230, 71 // 2.400595, 0.68896 |
| 6292 | })); |
| 6293 | |
| 6294 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6295 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>({ |
| 6296 | 0, 87, 173, 217, 217, // 0.18300501, 1.06142902, 1.93985295, 2.37906504, 2.37906504 |
| 6297 | 86, 96, 106, 111, 111, // 1.05497003, 1.15400803, 1.25304604, 1.30256498, 1.30256498 |
| 6298 | 219, 151, 84, 50, 50 // 2.40059495, 1.71594095, 1.03128707, 0.68896002, 0.68896002 |
| 6299 | })); |
| 6300 | |
| 6301 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6302 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6303 | |
| 6304 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6305 | armnn::WorkloadInfo info; |
| 6306 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6307 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6308 | |
| 6309 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6310 | |
| 6311 | inputHandle->Allocate(); |
| 6312 | outputHandle->Allocate(); |
| 6313 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6314 | |
| 6315 | workload->Execute(); |
| 6316 | |
| 6317 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6318 | return result; |
| 6319 | } |
| 6320 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6321 | LayerTestResult<float, 4> BatchNormTest( |
| 6322 | armnn::IWorkloadFactory& workloadFactory, |
| 6323 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6324 | { |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6325 | // BatchSize: 1 |
| 6326 | // Channels: 2 |
| 6327 | // Height: 3 |
| 6328 | // Width: 2 |
| 6329 | |
| 6330 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 6331 | std::vector<float> inputValues |
| 6332 | { |
| 6333 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 6334 | 1.f, 4.f, |
| 6335 | 4.f, 2.f, |
| 6336 | 1.f, 6.f, |
| 6337 | |
| 6338 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 6339 | 1.f, 1.f, |
| 6340 | 4.f, 1.f, |
| 6341 | -2.f, 4.f |
| 6342 | }; |
| 6343 | std::vector<float> expectedOutputValues |
| 6344 | { |
| 6345 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 6346 | 1.f, 4.f, |
| 6347 | 4.f, 2.f, |
| 6348 | 1.f, 6.f, |
| 6349 | |
| 6350 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 6351 | 3.f, 3.f, |
| 6352 | 4.f, 3.f, |
| 6353 | 2.f, 4.f |
| 6354 | }; |
| 6355 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6356 | return BatchNormTestImpl<float>(workloadFactory, memoryManager, |
| 6357 | inputOutputShape, inputValues, expectedOutputValues, |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6358 | 0.f, 0, armnn::DataLayout::NCHW); |
| 6359 | } |
| 6360 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6361 | LayerTestResult<float, 4> BatchNormNhwcTest( |
| 6362 | armnn::IWorkloadFactory& workloadFactory, |
| 6363 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6364 | { |
| 6365 | // BatchSize: 1 |
| 6366 | // Height: 3 |
| 6367 | // Width: 2 |
| 6368 | // Channels: 2 |
| 6369 | |
| 6370 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 6371 | std::vector<float> inputValues |
| 6372 | { |
| 6373 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 6374 | 1.f, 1.f, |
| 6375 | 4.f, 1.f, |
| 6376 | |
| 6377 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 6378 | 4.f, 4.f, |
| 6379 | 2.f, 1.f, |
| 6380 | |
| 6381 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 6382 | 1.f, -2.f, |
| 6383 | 6.f, 4.f |
| 6384 | }; |
| 6385 | std::vector<float> expectedOutputValues |
| 6386 | { |
| 6387 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 6388 | 1.f, 3.f, |
| 6389 | 4.f, 3.f, |
| 6390 | |
| 6391 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 6392 | 4.f, 4.f, |
| 6393 | 2.f, 3.f, |
| 6394 | |
| 6395 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 6396 | 1.f, 2.f, |
| 6397 | 6.f, 4.f |
| 6398 | }; |
| 6399 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6400 | return BatchNormTestImpl<float>(workloadFactory, memoryManager, |
| 6401 | inputOutputShape, inputValues, expectedOutputValues, |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6402 | 0.f, 0, armnn::DataLayout::NHWC); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6403 | } |
| 6404 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6405 | LayerTestResult<uint8_t, 4> BatchNormUint8Test( |
| 6406 | armnn::IWorkloadFactory& workloadFactory, |
| 6407 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6408 | { |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6409 | // BatchSize: 1 |
| 6410 | // Channels: 2 |
| 6411 | // Height: 3 |
| 6412 | // Width: 2 |
| 6413 | |
| 6414 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 6415 | std::vector<float> inputValues |
| 6416 | { |
| 6417 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 6418 | 1.f, 4.f, |
| 6419 | 4.f, 2.f, |
| 6420 | 1.f, 6.f, |
| 6421 | |
| 6422 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 6423 | 1.f, 1.f, |
| 6424 | 4.f, 1.f, |
| 6425 | -2.f, 4.f |
| 6426 | }; |
| 6427 | std::vector<float> expectedOutputValues |
| 6428 | { |
| 6429 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 6430 | 1.f, 4.f, |
| 6431 | 4.f, 2.f, |
| 6432 | 1.f, 6.f, |
| 6433 | |
| 6434 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 6435 | 3.f, 3.f, |
| 6436 | 4.f, 3.f, |
| 6437 | 2.f, 4.f |
| 6438 | }; |
| 6439 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6440 | return BatchNormTestImpl<uint8_t>(workloadFactory, memoryManager, |
| 6441 | inputOutputShape, inputValues, expectedOutputValues, |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6442 | 1.f/20.f, 50, armnn::DataLayout::NCHW); |
| 6443 | } |
| 6444 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6445 | LayerTestResult<uint8_t, 4> BatchNormUint8NhwcTest( |
| 6446 | armnn::IWorkloadFactory& workloadFactory, |
| 6447 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6448 | { |
| 6449 | // BatchSize: 1 |
| 6450 | // Height: 3 |
| 6451 | // Width: 2 |
| 6452 | // Channels: 2 |
| 6453 | |
| 6454 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 6455 | std::vector<float> inputValues |
| 6456 | { |
| 6457 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 6458 | 1.f, 1.f, |
| 6459 | 4.f, 1.f, |
| 6460 | |
| 6461 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 6462 | 4.f, 4.f, |
| 6463 | 2.f, 1.f, |
| 6464 | |
| 6465 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 6466 | 1.f, -2.f, |
| 6467 | 6.f, 4.f |
| 6468 | }; |
| 6469 | std::vector<float> expectedOutputValues |
| 6470 | { |
| 6471 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 6472 | 1.f, 3.f, |
| 6473 | 4.f, 3.f, |
| 6474 | |
| 6475 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 6476 | 4.f, 4.f, |
| 6477 | 2.f, 3.f, |
| 6478 | |
| 6479 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 6480 | 1.f, 2.f, |
| 6481 | 6.f, 4.f |
| 6482 | }; |
| 6483 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6484 | return BatchNormTestImpl<uint8_t>(workloadFactory, memoryManager, |
| 6485 | inputOutputShape, inputValues, expectedOutputValues, |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6486 | 1.f/20.f, 50, armnn::DataLayout::NHWC); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6487 | } |
| 6488 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6489 | LayerTestResult<uint8_t, 4> ConstantUint8Test( |
| 6490 | armnn::IWorkloadFactory& workloadFactory, |
| 6491 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6492 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6493 | return ConstantTestImpl<uint8_t>(workloadFactory, memoryManager, 2e-6f, 1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6494 | } |
| 6495 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6496 | LayerTestResult<uint8_t, 1> Concatenation1dUint8Test( |
| 6497 | armnn::IWorkloadFactory& workloadFactory, |
| 6498 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6499 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6500 | return Concatenation1dTestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6501 | } |
| 6502 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6503 | LayerTestResult<uint8_t, 2> Concatenation2dDim0Uint8Test( |
| 6504 | armnn::IWorkloadFactory& workloadFactory, |
| 6505 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6506 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6507 | return Concatenation2dDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6508 | } |
| 6509 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6510 | LayerTestResult<uint8_t, 2> Concatenation2dDim1Uint8Test( |
| 6511 | armnn::IWorkloadFactory& workloadFactory, |
| 6512 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6513 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6514 | return Concatenation2dDim1TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6515 | } |
| 6516 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6517 | LayerTestResult<uint8_t, 2> Concatenation2dDim0DiffInputDimsUint8Test( |
| 6518 | armnn::IWorkloadFactory& workloadFactory, |
| 6519 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6520 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6521 | return Concatenation2dDim0DiffInputDimsTestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6522 | } |
| 6523 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6524 | LayerTestResult<uint8_t, 2> Concatenation2dDim1DiffInputDimsUint8Test( |
| 6525 | armnn::IWorkloadFactory& workloadFactory, |
| 6526 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6527 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6528 | return Concatenation2dDim1DiffInputDimsTestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6529 | } |
| 6530 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6531 | LayerTestResult<uint8_t, 3> Concatenation3dDim0Uint8Test( |
| 6532 | armnn::IWorkloadFactory& workloadFactory, |
| 6533 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6534 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6535 | return Concatenation3dDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6536 | } |
| 6537 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6538 | LayerTestResult<uint8_t, 3> Concatenation3dDim1Uint8Test( |
| 6539 | armnn::IWorkloadFactory& workloadFactory, |
| 6540 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6541 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6542 | return Concatenation3dDim1TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6543 | } |
| 6544 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6545 | LayerTestResult<uint8_t, 3> Concatenation3dDim2Uint8Test( |
| 6546 | armnn::IWorkloadFactory& workloadFactory, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 6547 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6548 | bool useSubtensor) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6549 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 6550 | return Concatenation3dDim2TestImpl<uint8_t>(workloadFactory, memoryManager, useSubtensor, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6551 | } |
| 6552 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6553 | LayerTestResult<uint8_t, 3> Concatenation3dDim0DiffInputDimsUint8Test( |
| 6554 | armnn::IWorkloadFactory& workloadFactory, |
| 6555 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6556 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6557 | return Concatenation3dDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6558 | } |
| 6559 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6560 | LayerTestResult<uint8_t, 3> Concatenation3dDim1DiffInputDimsUint8Test( |
| 6561 | armnn::IWorkloadFactory& workloadFactory, |
| 6562 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6563 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6564 | return Concatenation3dDim1DiffInputDimsTestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6565 | } |
| 6566 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6567 | LayerTestResult<uint8_t, 3> Concatenation3dDim2DiffInputDimsUint8Test( |
| 6568 | armnn::IWorkloadFactory& workloadFactory, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 6569 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6570 | bool useSubtensor) |
| 6571 | { |
| 6572 | return Concatenation3dDim2DiffInputDimsTestImpl<uint8_t>(workloadFactory, memoryManager, useSubtensor, 0.5f, -1); |
| 6573 | } |
| 6574 | |
| 6575 | LayerTestResult<uint8_t, 4> Concatenation4dDim0Uint8Test( |
| 6576 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6577 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6578 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 6579 | return Concatenation4dDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 6580 | } |
| 6581 | |
| 6582 | LayerTestResult<uint8_t, 4> Concatenation4dDim1Uint8Test( |
| 6583 | armnn::IWorkloadFactory& workloadFactory, |
| 6584 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6585 | { |
| 6586 | return Concatenation4dDim1TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 6587 | } |
| 6588 | |
| 6589 | LayerTestResult<uint8_t, 4> Concatenation4dDim2Uint8Test( |
| 6590 | armnn::IWorkloadFactory& workloadFactory, |
| 6591 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6592 | { |
| 6593 | return Concatenation4dDim2TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 6594 | } |
| 6595 | |
| 6596 | LayerTestResult<uint8_t, 4> Concatenation4dDim3Uint8Test( |
| 6597 | armnn::IWorkloadFactory& workloadFactory, |
| 6598 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) |
| 6599 | { |
| 6600 | return Concatenation4dDim3TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1, useSubtensor); |
| 6601 | } |
| 6602 | |
| 6603 | LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim0Uint8Test( |
| 6604 | armnn::IWorkloadFactory& workloadFactory, |
| 6605 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6606 | { |
| 6607 | return Concatenation4dDiffShapeDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 6608 | } |
| 6609 | |
| 6610 | LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim1Uint8Test( |
| 6611 | armnn::IWorkloadFactory& workloadFactory, |
| 6612 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6613 | { |
| 6614 | return Concatenation4dDiffShapeDim1TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 6615 | } |
| 6616 | |
| 6617 | LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim2Uint8Test( |
| 6618 | armnn::IWorkloadFactory& workloadFactory, |
| 6619 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6620 | { |
| 6621 | return Concatenation4dDiffShapeDim2TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 6622 | } |
| 6623 | |
| 6624 | LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim3Uint8Test( |
| 6625 | armnn::IWorkloadFactory& workloadFactory, |
| 6626 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6627 | bool useSubtensor) |
| 6628 | { |
| 6629 | return Concatenation4dDiffShapeDim3TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1, useSubtensor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6630 | } |
| 6631 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6632 | LayerTestResult<float, 4> SimpleMaxPooling2dSize2x2Stride2x2Test( |
| 6633 | armnn::IWorkloadFactory& workloadFactory, |
| 6634 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6635 | bool forceNoPadding) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6636 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6637 | return SimpleMaxPooling2dSize2x2Stride2x2TestCommon<float>(workloadFactory, memoryManager, forceNoPadding); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6638 | } |
| 6639 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6640 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize2x2Stride2x2Uint8Test( |
| 6641 | armnn::IWorkloadFactory& workloadFactory, |
| 6642 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6643 | bool forceNoPadding) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6644 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6645 | return SimpleMaxPooling2dSize2x2Stride2x2TestCommon<uint8_t>( |
| 6646 | workloadFactory, memoryManager, forceNoPadding, 3.0f, -5); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6647 | } |
| 6648 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6649 | LayerTestResult<float, 4> SimpleMaxPooling2dSize3x3Stride2x4Test( |
| 6650 | armnn::IWorkloadFactory& workloadFactory, |
| 6651 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6652 | bool forceNoPadding) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6653 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6654 | return SimpleMaxPooling2dSize3x3Stride2x4TestCommon<float>(workloadFactory, memoryManager, forceNoPadding); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6655 | } |
| 6656 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6657 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize3x3Stride2x4Uint8Test( |
| 6658 | armnn::IWorkloadFactory& workloadFactory, |
| 6659 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6660 | bool forceNoPadding) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6661 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6662 | return SimpleMaxPooling2dSize3x3Stride2x4TestCommon<uint8_t>( |
| 6663 | workloadFactory, memoryManager, forceNoPadding, 0.1f, 128); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6664 | } |
| 6665 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6666 | LayerTestResult<float, 4> SimpleMaxPooling2dTest( |
| 6667 | armnn::IWorkloadFactory& workloadFactory, |
| 6668 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 6669 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6670 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6671 | return SimpleMaxPooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6672 | } |
| 6673 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6674 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dUint8Test( |
| 6675 | armnn::IWorkloadFactory& workloadFactory, |
| 6676 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 6677 | const armnn::DataLayout dataLayout) |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 6678 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6679 | return SimpleMaxPooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, dataLayout); |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 6680 | } |
| 6681 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6682 | LayerTestResult<float, 4> SimpleAveragePooling2dTest( |
| 6683 | armnn::IWorkloadFactory& workloadFactory, |
| 6684 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 6685 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6686 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6687 | return SimpleAveragePooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout); |
James Conroy | 6948227 | 2018-10-19 10:41:35 +0100 | [diff] [blame] | 6688 | } |
| 6689 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6690 | LayerTestResult<uint8_t, 4> SimpleAveragePooling2dUint8Test( |
| 6691 | armnn::IWorkloadFactory& workloadFactory, |
| 6692 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 6693 | const armnn::DataLayout dataLayout) |
James Conroy | 6948227 | 2018-10-19 10:41:35 +0100 | [diff] [blame] | 6694 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6695 | return SimpleAveragePooling2dTestCommon<uint8_t>( |
| 6696 | workloadFactory, memoryManager, dataLayout, 0.5, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6697 | } |
| 6698 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6699 | LayerTestResult<float, 4> IgnorePaddingAveragePooling2dSize3x2Stride2x2Test( |
| 6700 | armnn::IWorkloadFactory& workloadFactory, |
| 6701 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6702 | bool forceNoPadding) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6703 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6704 | return IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon<float>( |
| 6705 | workloadFactory, memoryManager, forceNoPadding); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6706 | } |
| 6707 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6708 | LayerTestResult<float, 4> LargeTensorsAveragePooling2dTest( |
| 6709 | armnn::IWorkloadFactory& workloadFactory, |
| 6710 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6711 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6712 | return LargeTensorsAveragePooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6713 | } |
| 6714 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6715 | LayerTestResult<uint8_t, 4> LargeTensorsAveragePooling2dUint8Test( |
| 6716 | armnn::IWorkloadFactory& workloadFactory, |
| 6717 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6718 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6719 | return LargeTensorsAveragePooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, 0.5, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6720 | } |
| 6721 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6722 | LayerTestResult<float, 4> SimpleL2Pooling2dTest( |
| 6723 | armnn::IWorkloadFactory& workloadFactory, |
| 6724 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 6725 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6726 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6727 | return SimpleL2Pooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6728 | } |
| 6729 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6730 | LayerTestResult<uint8_t, 4> SimpleL2Pooling2dUint8Test( |
| 6731 | armnn::IWorkloadFactory& workloadFactory, |
| 6732 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 6733 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6734 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6735 | return SimpleL2Pooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6736 | } |
| 6737 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6738 | LayerTestResult<float, 4> L2Pooling2dSize3Stride1Test( |
| 6739 | armnn::IWorkloadFactory& workloadFactory, |
| 6740 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6741 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6742 | return L2Pooling2dSize3Stride1TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6743 | } |
| 6744 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6745 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride1Uint8Test( |
| 6746 | armnn::IWorkloadFactory& workloadFactory, |
| 6747 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6748 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6749 | return L2Pooling2dSize3Stride1TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6750 | } |
| 6751 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6752 | LayerTestResult<float, 4> L2Pooling2dSize3Stride3Test( |
| 6753 | armnn::IWorkloadFactory& workloadFactory, |
| 6754 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6755 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6756 | return L2Pooling2dSize3Stride3TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6757 | } |
| 6758 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6759 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride3Uint8Test( |
| 6760 | armnn::IWorkloadFactory& workloadFactory, |
| 6761 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6762 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6763 | return L2Pooling2dSize3Stride3TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6764 | } |
| 6765 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6766 | LayerTestResult<float, 4> L2Pooling2dSize3Stride4Test( |
| 6767 | armnn::IWorkloadFactory& workloadFactory, |
| 6768 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6769 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6770 | return L2Pooling2dSize3Stride4TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6771 | } |
| 6772 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6773 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride4Uint8Test( |
| 6774 | armnn::IWorkloadFactory& workloadFactory, |
| 6775 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6776 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6777 | return L2Pooling2dSize3Stride4TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6778 | } |
| 6779 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6780 | LayerTestResult<float, 4> L2Pooling2dSize7Test( |
| 6781 | armnn::IWorkloadFactory& workloadFactory, |
| 6782 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6783 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6784 | return L2Pooling2dSize7TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6785 | } |
| 6786 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6787 | LayerTestResult<uint8_t, 4> L2Pooling2dSize7Uint8Test( |
| 6788 | armnn::IWorkloadFactory& workloadFactory, |
| 6789 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6790 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6791 | return L2Pooling2dSize7TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6792 | } |
| 6793 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6794 | LayerTestResult<float, 4> L2Pooling2dSize9Test( |
| 6795 | armnn::IWorkloadFactory& workloadFactory, |
| 6796 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6797 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6798 | return L2Pooling2dSize9TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6799 | } |
| 6800 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6801 | LayerTestResult<uint8_t, 4> L2Pooling2dSize9Uint8Test( |
| 6802 | armnn::IWorkloadFactory& workloadFactory, |
| 6803 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6804 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6805 | return L2Pooling2dSize9TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6806 | } |
| 6807 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6808 | LayerTestResult<float, 4> AsymmetricNonSquarePooling2dTest( |
| 6809 | armnn::IWorkloadFactory& workloadFactory, |
| 6810 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6811 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6812 | return AsymmetricNonSquarePooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6813 | } |
| 6814 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6815 | LayerTestResult<uint8_t, 4> AsymmetricNonSquarePooling2dUint8Test( |
| 6816 | armnn::IWorkloadFactory& workloadFactory, |
| 6817 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6818 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6819 | return AsymmetricNonSquarePooling2dTestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6820 | } |
| 6821 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6822 | LayerTestResult<float, 4> ComparePooling2dTest( |
| 6823 | armnn::IWorkloadFactory& workloadFactory, |
| 6824 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6825 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 6826 | armnn::PoolingAlgorithm poolingType) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6827 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6828 | return ComparePooling2dTestCommon<float>( |
| 6829 | workloadFactory, memoryManager, refWorkloadFactory, poolingType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6830 | } |
| 6831 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6832 | LayerTestResult<uint8_t, 4> ComparePooling2dUint8Test( |
| 6833 | armnn::IWorkloadFactory& workloadFactory, |
| 6834 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6835 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 6836 | armnn::PoolingAlgorithm poolingType) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6837 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6838 | return ComparePooling2dTestCommon<uint8_t>( |
| 6839 | workloadFactory, memoryManager, refWorkloadFactory, poolingType, 0.1f, 128); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6840 | } |
| 6841 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6842 | LayerTestResult<float, 2> FullyConnectedLargeTest( |
| 6843 | armnn::IWorkloadFactory& workloadFactory, |
| 6844 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6845 | bool transposeWeights) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6846 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6847 | return FullyConnectedLargeTestCommon<float>(workloadFactory, memoryManager, transposeWeights); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6848 | } |
| 6849 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6850 | LayerTestResult<float, 4> IgnorePaddingSimpleMaxPooling2dTest( |
| 6851 | armnn::IWorkloadFactory& workloadFactory, |
| 6852 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6853 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6854 | return IgnorePaddingSimpleMaxPooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6855 | } |
| 6856 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6857 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleMaxPooling2dUint8Test( |
| 6858 | armnn::IWorkloadFactory& workloadFactory, |
| 6859 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6860 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6861 | return IgnorePaddingSimpleMaxPooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, -5); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6862 | } |
| 6863 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6864 | LayerTestResult<float, 4> IgnorePaddingMaxPooling2dSize3Test( |
| 6865 | armnn::IWorkloadFactory& workloadFactory, |
| 6866 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6867 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6868 | return IgnorePaddingMaxPooling2dSize3TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6869 | } |
| 6870 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6871 | LayerTestResult<uint8_t, 4> IgnorePaddingMaxPooling2dSize3Uint8Test( |
| 6872 | armnn::IWorkloadFactory& workloadFactory, |
| 6873 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6874 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6875 | return IgnorePaddingMaxPooling2dSize3TestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, -5); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6876 | } |
| 6877 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6878 | LayerTestResult<float, 4> IgnorePaddingSimpleAveragePooling2dTest( |
| 6879 | armnn::IWorkloadFactory& workloadFactory, |
| 6880 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6881 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6882 | return IgnorePaddingSimpleAveragePooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6883 | } |
| 6884 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6885 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleAveragePooling2dUint8Test( |
| 6886 | armnn::IWorkloadFactory& workloadFactory, |
| 6887 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6888 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6889 | return IgnorePaddingSimpleAveragePooling2dTestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6890 | } |
| 6891 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6892 | LayerTestResult<float, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingTest( |
| 6893 | armnn::IWorkloadFactory& workloadFactory, |
| 6894 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6895 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6896 | return IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6897 | } |
| 6898 | |
| 6899 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6900 | armnn::IWorkloadFactory& workloadFactory, |
| 6901 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6902 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6903 | return IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6904 | } |
| 6905 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6906 | LayerTestResult<float, 4> IgnorePaddingAveragePooling2dSize3Test( |
| 6907 | armnn::IWorkloadFactory& workloadFactory, |
| 6908 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6909 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6910 | return IgnorePaddingAveragePooling2dSize3TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6911 | } |
| 6912 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6913 | LayerTestResult<uint8_t, 4> IgnorePaddingAveragePooling2dSize3Uint8Test( |
| 6914 | armnn::IWorkloadFactory& workloadFactory, |
| 6915 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6916 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6917 | return IgnorePaddingAveragePooling2dSize3TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6918 | } |
| 6919 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6920 | LayerTestResult<float, 4> IgnorePaddingSimpleL2Pooling2dTest( |
| 6921 | armnn::IWorkloadFactory& workloadFactory, |
| 6922 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6923 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6924 | return IgnorePaddingSimpleL2Pooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6925 | } |
| 6926 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6927 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleL2Pooling2dUint8Test( |
| 6928 | armnn::IWorkloadFactory& workloadFactory, |
| 6929 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6930 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6931 | return IgnorePaddingSimpleL2Pooling2dTestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6932 | } |
| 6933 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6934 | LayerTestResult<float, 4> IgnorePaddingL2Pooling2dSize3Test( |
| 6935 | armnn::IWorkloadFactory& workloadFactory, |
| 6936 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6937 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6938 | return IgnorePaddingL2Pooling2dSize3TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6939 | } |
| 6940 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6941 | LayerTestResult<uint8_t, 4> IgnorePaddingL2Pooling2dSize3Uint8Test( |
| 6942 | armnn::IWorkloadFactory& workloadFactory, |
| 6943 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6944 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6945 | return IgnorePaddingL2Pooling2dSize3TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6946 | } |
| 6947 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6948 | LayerTestResult<float, 4> SimplePermuteFloat32Test( |
| 6949 | armnn::IWorkloadFactory& workloadFactory, |
| 6950 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6951 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6952 | return SimplePermuteFloat32TestCommon(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6953 | }; |
| 6954 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6955 | LayerTestResult<uint8_t, 4> SimplePermuteUint8Test( |
| 6956 | armnn::IWorkloadFactory& workloadFactory, |
| 6957 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6958 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6959 | return SimplePermuteUint8TestCommon(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6960 | }; |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6961 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6962 | LayerTestResult<float, 4> PermuteFloat32ValueSet1Test( |
| 6963 | armnn::IWorkloadFactory& workloadFactory, |
| 6964 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6965 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6966 | return PermuteFloat32ValueSet1TestCommon(workloadFactory, memoryManager); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6967 | }; |
| 6968 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6969 | LayerTestResult<float, 4> PermuteFloat32ValueSet2Test( |
| 6970 | armnn::IWorkloadFactory& workloadFactory, |
| 6971 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6972 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6973 | return PermuteFloat32ValueSet2TestCommon(workloadFactory, memoryManager); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6974 | }; |
| 6975 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6976 | LayerTestResult<float, 4> PermuteFloat32ValueSet3Test( |
| 6977 | armnn::IWorkloadFactory& workloadFactory, |
| 6978 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6979 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6980 | return PermuteFloat32ValueSet3TestCommon(workloadFactory, memoryManager); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 6981 | }; |
| 6982 | |
| 6983 | namespace |
| 6984 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 6985 | |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 6986 | template <typename T, std::size_t InputDim, std::size_t OutputDim> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6987 | LayerTestResult<T, OutputDim> MeanTestHelper( |
| 6988 | armnn::IWorkloadFactory& workloadFactory, |
| 6989 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6990 | const unsigned int* inputShape, |
| 6991 | const std::vector<T>& inputData, |
| 6992 | const std::vector<unsigned int>& axis, |
| 6993 | bool keepDims, |
| 6994 | const unsigned int* outputShape, |
| 6995 | const std::vector<T>& outputData, |
| 6996 | float scale = 1.0f, |
| 6997 | int32_t offset = 0) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 6998 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 6999 | auto dataType = (std::is_same<T, uint8_t>::value ? armnn::DataType::QuantisedAsymm8 : armnn::DataType::Float32); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7000 | |
| 7001 | armnn::TensorInfo inputTensorInfo(InputDim, inputShape, dataType); |
| 7002 | armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, dataType); |
| 7003 | |
| 7004 | inputTensorInfo.SetQuantizationScale(scale); |
| 7005 | inputTensorInfo.SetQuantizationOffset(offset); |
| 7006 | |
| 7007 | outputTensorInfo.SetQuantizationScale(scale); |
| 7008 | outputTensorInfo.SetQuantizationOffset(offset); |
| 7009 | |
| 7010 | auto input = MakeTensor<T, InputDim>(inputTensorInfo, inputData); |
| 7011 | |
| 7012 | LayerTestResult<T, OutputDim> result(outputTensorInfo); |
| 7013 | result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo, outputData); |
| 7014 | |
| 7015 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 7016 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 7017 | |
| 7018 | armnn::MeanQueueDescriptor data; |
| 7019 | data.m_Parameters.m_Axis = axis; |
| 7020 | data.m_Parameters.m_KeepDims = keepDims; |
| 7021 | armnn::WorkloadInfo info; |
| 7022 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 7023 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 7024 | |
| 7025 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMean(data, info); |
| 7026 | |
| 7027 | inputHandle->Allocate(); |
| 7028 | outputHandle->Allocate(); |
| 7029 | |
| 7030 | CopyDataToITensorHandle(inputHandle.get(), input.origin()); |
| 7031 | |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7032 | workload->Execute(); |
| 7033 | |
| 7034 | CopyDataFromITensorHandle(result.output.origin(), outputHandle.get()); |
| 7035 | |
| 7036 | return result; |
| 7037 | } |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7038 | |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7039 | } // anonymous namespace |
| 7040 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7041 | LayerTestResult<uint8_t, 1> MeanUint8SimpleTest( |
| 7042 | armnn::IWorkloadFactory& workloadFactory, |
| 7043 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7044 | { |
| 7045 | const unsigned int inputShape[] = { 3, 2 }; |
| 7046 | const unsigned int outputShape[] = { 1 }; |
| 7047 | |
| 7048 | std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); |
| 7049 | std::vector<uint8_t> output({ 2 }); |
| 7050 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7051 | return MeanTestHelper<uint8_t, 2, 1>( |
| 7052 | workloadFactory, memoryManager, inputShape, input, {}, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7053 | } |
| 7054 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7055 | LayerTestResult<uint8_t, 3> MeanUint8SimpleAxisTest( |
| 7056 | armnn::IWorkloadFactory& workloadFactory, |
| 7057 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7058 | { |
| 7059 | const unsigned int inputShape[] = { 1, 1, 3, 2 }; |
| 7060 | const unsigned int outputShape[] = { 1, 1, 2 }; |
| 7061 | |
| 7062 | std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); |
| 7063 | std::vector<uint8_t> output({ 2, 2 }); |
| 7064 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7065 | return MeanTestHelper<uint8_t, 4, 3>( |
| 7066 | workloadFactory, memoryManager, inputShape, input, { 2 }, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7067 | } |
| 7068 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7069 | LayerTestResult<uint8_t, 4> MeanUint8KeepDimsTest( |
| 7070 | armnn::IWorkloadFactory& workloadFactory, |
| 7071 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7072 | { |
| 7073 | const unsigned int inputShape[] = { 1, 1, 3, 2 }; |
| 7074 | const unsigned int outputShape[] = { 1, 1, 1, 2 }; |
| 7075 | |
| 7076 | std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); |
| 7077 | std::vector<uint8_t> output({ 2, 2 }); |
| 7078 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7079 | return MeanTestHelper<uint8_t, 4, 4>( |
| 7080 | workloadFactory, memoryManager, inputShape, input, { 2 }, true, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7081 | } |
| 7082 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7083 | LayerTestResult<uint8_t, 4> MeanUint8MultipleDimsTest( |
| 7084 | armnn::IWorkloadFactory& workloadFactory, |
| 7085 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7086 | { |
| 7087 | const unsigned int inputShape[] = { 2, 3, 1, 2 }; |
| 7088 | const unsigned int outputShape[] = { 1, 3, 1, 1 }; |
| 7089 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7090 | std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6 }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7091 | std::vector<uint8_t> output({ 1, 3, 5 }); |
| 7092 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7093 | return MeanTestHelper<uint8_t, 4, 4>( |
| 7094 | workloadFactory, memoryManager, inputShape, input, { 0, 3 }, true, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7095 | } |
| 7096 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7097 | LayerTestResult<uint8_t, 1> MeanVtsUint8Test( |
| 7098 | armnn::IWorkloadFactory& workloadFactory, |
| 7099 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7100 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7101 | const unsigned int inputShape[] = { 4, 3, 2 }; |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7102 | const unsigned int outputShape[] = { 2 }; |
| 7103 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7104 | std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, |
| 7105 | 24 }); |
| 7106 | std::vector<uint8_t> output({ 12, 13 }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7107 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7108 | return MeanTestHelper<uint8_t, 3, 1>(workloadFactory, memoryManager, |
| 7109 | inputShape, input, { 0, 1 }, false, outputShape, |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7110 | output, 0.8f, 5); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7111 | } |
| 7112 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7113 | LayerTestResult<float, 1> MeanFloatSimpleTest( |
| 7114 | armnn::IWorkloadFactory& workloadFactory, |
| 7115 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7116 | { |
| 7117 | const unsigned int inputShape[] = { 3, 2 }; |
| 7118 | const unsigned int outputShape[] = { 1 }; |
| 7119 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7120 | std::vector<float> input({ 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f }); |
| 7121 | std::vector<float> output({ 2.0f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7122 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7123 | return MeanTestHelper<float, 2, 1>( |
| 7124 | workloadFactory, memoryManager, inputShape, input, {}, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7125 | } |
| 7126 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7127 | LayerTestResult<float, 3> MeanFloatSimpleAxisTest( |
| 7128 | armnn::IWorkloadFactory& workloadFactory, |
| 7129 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7130 | { |
| 7131 | const unsigned int inputShape[] = { 2, 3, 1, 2 }; |
| 7132 | const unsigned int outputShape[] = { 3, 1, 2 }; |
| 7133 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7134 | std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }); |
| 7135 | std::vector<float> output({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7136 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7137 | return MeanTestHelper<float, 4, 3>( |
| 7138 | workloadFactory, memoryManager, inputShape, input, { 0 }, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7139 | } |
| 7140 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7141 | LayerTestResult<float, 4> MeanFloatKeepDimsTest( |
| 7142 | armnn::IWorkloadFactory& workloadFactory, |
| 7143 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7144 | { |
| 7145 | const unsigned int inputShape[] = { 1, 1, 3, 2 }; |
| 7146 | const unsigned int outputShape[] = { 1, 1, 1, 2 }; |
| 7147 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7148 | std::vector<float> input({ 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f }); |
| 7149 | std::vector<float> output({ 2.0f, 2.0f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7150 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7151 | return MeanTestHelper<float, 4, 4>( |
| 7152 | workloadFactory, memoryManager, inputShape, input, { 2 }, true, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7153 | } |
| 7154 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7155 | LayerTestResult<float, 4> MeanFloatMultipleDimsTest( |
| 7156 | armnn::IWorkloadFactory& workloadFactory, |
| 7157 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7158 | { |
| 7159 | const unsigned int inputShape[] = { 2, 3, 1, 2 }; |
| 7160 | const unsigned int outputShape[] = { 1, 3, 1, 1 }; |
| 7161 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7162 | std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }); |
| 7163 | std::vector<float> output({ 1.5f, 3.5f, 5.5f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7164 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7165 | return MeanTestHelper<float, 4, 4>( |
| 7166 | workloadFactory, memoryManager, inputShape, input, { 0, 3 }, true, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7167 | } |
| 7168 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7169 | LayerTestResult<float, 1> MeanVtsFloat1Test( |
| 7170 | armnn::IWorkloadFactory& workloadFactory, |
| 7171 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7172 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7173 | const unsigned int inputShape[] = { 4, 3, 2 }; |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7174 | const unsigned int outputShape[] = { 2 }; |
| 7175 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7176 | std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, |
| 7177 | 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f }); |
| 7178 | std::vector<float> output({ 12.0f, 13.0f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7179 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7180 | return MeanTestHelper<float, 3, 1>( |
| 7181 | workloadFactory, memoryManager, inputShape, input, { 0, 1 }, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7182 | } |
| 7183 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7184 | LayerTestResult<float, 3> MeanVtsFloat2Test( |
| 7185 | armnn::IWorkloadFactory& workloadFactory, |
| 7186 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7187 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7188 | const unsigned int inputShape[] = { 4, 3, 2 }; |
| 7189 | const unsigned int outputShape[] = { 1, 3, 1 }; |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7190 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7191 | std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, |
| 7192 | 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f }); |
| 7193 | std::vector<float> output({ 10.5f, 12.5f, 14.5f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7194 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7195 | return MeanTestHelper<float, 3, 3>( |
| 7196 | workloadFactory, memoryManager, inputShape, input, { 0, 2 }, true, outputShape, output); |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7197 | } |
| 7198 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7199 | LayerTestResult<float, 3> MeanVtsFloat3Test( |
| 7200 | armnn::IWorkloadFactory& workloadFactory, |
| 7201 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7202 | { |
| 7203 | const unsigned int inputShape[] = { 1, 2, 2, 1 }; |
| 7204 | const unsigned int outputShape[] = { 1, 2, 1 }; |
| 7205 | |
| 7206 | std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f }); |
| 7207 | std::vector<float> output({ 1.5f, 3.5f }); |
| 7208 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7209 | return MeanTestHelper<float, 4, 3>( |
| 7210 | workloadFactory, memoryManager, inputShape, input, { 2 }, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7211 | } |
Éanna Ó Catháin | 47c1ddb | 2018-10-12 14:24:13 +0100 | [diff] [blame] | 7212 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7213 | LayerTestResult<float, 4> AdditionAfterMaxPoolTest( |
| 7214 | armnn::IWorkloadFactory& workloadFactory, |
| 7215 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 47c1ddb | 2018-10-12 14:24:13 +0100 | [diff] [blame] | 7216 | { |
| 7217 | // Create Initial Tensor |
| 7218 | // 1, 2, 3 |
| 7219 | // 4, 5, 6 |
| 7220 | // 7, 8, 9 |
| 7221 | |
| 7222 | armnn::TensorInfo poolingInputTensorInfo({ 1, 1, 3, 3}, armnn::GetDataType<float>()); |
| 7223 | armnn::TensorInfo poolingOutputTensorInfo({ 1, 1, 2, 2}, armnn::GetDataType<float>()); |
| 7224 | |
| 7225 | boost::multi_array<float, 4> poolingInput = MakeTensor<float,4>(poolingInputTensorInfo, |
| 7226 | {1, 2, 3, |
| 7227 | 4, 5, 6, |
| 7228 | 7, 8, 9 |
| 7229 | }); |
| 7230 | |
| 7231 | std::unique_ptr<armnn::ITensorHandle> poolingInputHandle = |
| 7232 | workloadFactory.CreateTensorHandle(poolingInputTensorInfo); |
| 7233 | std::unique_ptr<armnn::ITensorHandle> poolingOutputHandle = |
| 7234 | workloadFactory.CreateTensorHandle(poolingOutputTensorInfo); |
| 7235 | |
| 7236 | // Apply MaxPool poolSize = 1x1, stride=2x2 |
| 7237 | // Result = |
| 7238 | // 1, 3 |
| 7239 | // 7, 9 |
| 7240 | armnn::Pooling2dDescriptor descriptor; |
| 7241 | descriptor.m_PoolHeight = 1; |
| 7242 | descriptor.m_PoolWidth = 1; |
| 7243 | descriptor.m_StrideX = 2; |
| 7244 | descriptor.m_StrideY = 2; |
| 7245 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 7246 | |
| 7247 | armnn::Pooling2dQueueDescriptor queueDescriptor; |
| 7248 | queueDescriptor.m_Parameters = descriptor; |
| 7249 | armnn::WorkloadInfo workloadInfo; |
| 7250 | AddInputToWorkload(queueDescriptor, workloadInfo, poolingInputTensorInfo, poolingInputHandle.get()); |
| 7251 | AddOutputToWorkload(queueDescriptor, workloadInfo, poolingOutputTensorInfo, poolingOutputHandle.get()); |
| 7252 | |
| 7253 | // Create the MaxPool |
| 7254 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePooling2d(queueDescriptor, workloadInfo); |
| 7255 | |
| 7256 | //LayerTestResult<float, 4> result(poolingOutputTensorInfo); |
| 7257 | auto shape( GetTensorShapeAsArray<4>(poolingOutputTensorInfo)); |
| 7258 | boost::multi_array<float, 4> resultMaxPool; |
| 7259 | resultMaxPool.resize(shape); |
| 7260 | |
| 7261 | |
| 7262 | // Create addition with another tensor the same size |
| 7263 | // This would be the result to apply a Conv2d with kernel ones(2) and stride 1x1 |
| 7264 | // with the initial tensor. |
| 7265 | // 12, 16 |
| 7266 | // 24, 28 |
| 7267 | |
| 7268 | armnn::TensorInfo addInputTensorInfo({ 1,1,2,2}, armnn::GetDataType<float>()); |
| 7269 | armnn::TensorInfo addOutputTensorInfo({ 1,1,2,2}, armnn::GetDataType<float>()); |
| 7270 | |
| 7271 | boost::multi_array<float, 4> addInput = MakeTensor<float,4>(addInputTensorInfo, |
| 7272 | {12, 16, |
| 7273 | 24, 28, |
| 7274 | }); |
| 7275 | |
| 7276 | // Expected output tensor after MaxPool and Addition. |
| 7277 | LayerTestResult<float,4> addRet(addOutputTensorInfo); |
| 7278 | addRet.outputExpected = MakeTensor<float, 4>(addOutputTensorInfo, std::vector<float>( |
| 7279 | { |
| 7280 | 13, 19, |
| 7281 | 31, 37 |
| 7282 | })); |
| 7283 | |
| 7284 | std::unique_ptr<armnn::ITensorHandle> addInputHandle = workloadFactory.CreateTensorHandle(addInputTensorInfo); |
| 7285 | std::unique_ptr<armnn::ITensorHandle> addOutputHandle = workloadFactory.CreateTensorHandle(addOutputTensorInfo); |
| 7286 | |
| 7287 | armnn::AdditionQueueDescriptor data; |
| 7288 | armnn::WorkloadInfo info; |
| 7289 | |
| 7290 | // Add the output of the MaxPool and the new tensor |
| 7291 | AddInputToWorkload(data, info, poolingOutputTensorInfo, poolingOutputHandle.get()); |
| 7292 | AddInputToWorkload(data, info, addInputTensorInfo, addInputHandle.get()); |
| 7293 | AddOutputToWorkload(data, info, addOutputTensorInfo, addOutputHandle.get()); |
| 7294 | |
| 7295 | std::unique_ptr<armnn::IWorkload> addWorkload = workloadFactory.CreateAddition(data, info); |
| 7296 | |
| 7297 | poolingInputHandle->Allocate(); |
| 7298 | poolingOutputHandle->Allocate(); |
| 7299 | addInputHandle->Allocate(); |
| 7300 | addOutputHandle->Allocate(); |
| 7301 | |
| 7302 | CopyDataToITensorHandle(poolingInputHandle.get(), &poolingInput[0][0][0][0]); |
| 7303 | CopyDataFromITensorHandle(&resultMaxPool[0][0][0][0], poolingOutputHandle.get()); |
| 7304 | |
| 7305 | CopyDataToITensorHandle(poolingOutputHandle.get(), &resultMaxPool[0][0][0][0]); |
| 7306 | CopyDataToITensorHandle(addInputHandle.get(), &addInput[0][0][0][0]); |
| 7307 | |
| 7308 | workload->Execute(); |
| 7309 | addWorkload->Execute(); |
| 7310 | |
| 7311 | CopyDataFromITensorHandle(&addRet.output[0][0][0][0], addOutputHandle.get()); |
| 7312 | |
Éanna Ó Catháin | 47c1ddb | 2018-10-12 14:24:13 +0100 | [diff] [blame] | 7313 | return addRet; |
| 7314 | } |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7315 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7316 | LayerTestResult<float, 4> SpaceToBatchNdSimpleFloat32Test( |
| 7317 | armnn::IWorkloadFactory& workloadFactory, |
| 7318 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7319 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7320 | return SpaceToBatchNdSimpleTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7321 | } |
| 7322 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7323 | LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsFloat32Test( |
| 7324 | armnn::IWorkloadFactory& workloadFactory, |
| 7325 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7326 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7327 | return SpaceToBatchNdMultiChannelsTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7328 | } |
| 7329 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7330 | LayerTestResult<float, 4> SpaceToBatchNdMultiBlockFloat32Test( |
| 7331 | armnn::IWorkloadFactory& workloadFactory, |
| 7332 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7333 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7334 | return SpaceToBatchNdMultiBlockTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7335 | } |
| 7336 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7337 | LayerTestResult<float, 4> SpaceToBatchNdPaddingFloat32Test( |
| 7338 | armnn::IWorkloadFactory& workloadFactory, |
| 7339 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7340 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7341 | return SpaceToBatchNdPaddingTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7342 | } |
| 7343 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7344 | LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleUint8Test( |
| 7345 | armnn::IWorkloadFactory& workloadFactory, |
| 7346 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7347 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7348 | return SpaceToBatchNdSimpleTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7349 | } |
| 7350 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7351 | LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsUint8Test( |
| 7352 | armnn::IWorkloadFactory& workloadFactory, |
| 7353 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7354 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7355 | return SpaceToBatchNdMultiChannelsTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7356 | } |
| 7357 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7358 | LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockUint8Test( |
| 7359 | armnn::IWorkloadFactory& workloadFactory, |
| 7360 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7361 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7362 | return SpaceToBatchNdMultiBlockTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7363 | } |
| 7364 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7365 | LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingUint8Test( |
| 7366 | armnn::IWorkloadFactory& workloadFactory, |
| 7367 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7368 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7369 | return SpaceToBatchNdPaddingTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7370 | } |
| 7371 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7372 | LayerTestResult<float, 4> SpaceToBatchNdSimpleNHWCFloat32Test( |
| 7373 | armnn::IWorkloadFactory& workloadFactory, |
| 7374 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7375 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7376 | return SpaceToBatchNdSimpleNHWCTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7377 | } |
| 7378 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7379 | LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsNHWCFloat32Test( |
| 7380 | armnn::IWorkloadFactory& workloadFactory, |
| 7381 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7382 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7383 | return SpaceToBatchNdMultiChannelsNHWCTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7384 | } |
| 7385 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7386 | LayerTestResult<float, 4> SpaceToBatchNdMultiBlockNHWCFloat32Test( |
| 7387 | armnn::IWorkloadFactory& workloadFactory, |
| 7388 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7389 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7390 | return SpaceToBatchNdMultiBlockNHWCTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7391 | } |
| 7392 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7393 | LayerTestResult<float, 4> SpaceToBatchNdPaddingNHWCFloat32Test( |
| 7394 | armnn::IWorkloadFactory& workloadFactory, |
| 7395 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7396 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7397 | return SpaceToBatchNdPaddingNHWCTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7398 | } |
| 7399 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7400 | LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleNHWCUint8Test( |
| 7401 | armnn::IWorkloadFactory& workloadFactory, |
| 7402 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7403 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7404 | return SpaceToBatchNdSimpleNHWCTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7405 | } |
| 7406 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7407 | LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsNHWCUint8Test( |
| 7408 | armnn::IWorkloadFactory& workloadFactory, |
| 7409 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7410 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7411 | return SpaceToBatchNdMultiChannelsNHWCTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7412 | } |
| 7413 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7414 | LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockNHWCUint8Test( |
| 7415 | armnn::IWorkloadFactory& workloadFactory, |
| 7416 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7417 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7418 | return SpaceToBatchNdMultiBlockNHWCTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7419 | } |
| 7420 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7421 | LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingNHWCUint8Test( |
| 7422 | armnn::IWorkloadFactory& workloadFactory, |
| 7423 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7424 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7425 | return SpaceToBatchNdPaddingNHWCTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7426 | } |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7427 | |
| 7428 | namespace { |
| 7429 | |
| 7430 | template<typename T, std::size_t InputDim, std::size_t OutputDim> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7431 | LayerTestResult<T, OutputDim> BatchToSpaceNdHelper( |
| 7432 | armnn::IWorkloadFactory &workloadFactory, |
| 7433 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7434 | const armnn::DataLayout& dataLayout, |
| 7435 | const unsigned int *inputShape, |
| 7436 | const std::vector<T> &inputData, |
| 7437 | const std::vector<unsigned int> &blockShape, |
| 7438 | const std::vector<std::pair<unsigned int, unsigned int>> &crops, |
| 7439 | const unsigned int *outputShape, |
| 7440 | const std::vector<T> &outputData, |
| 7441 | float scale = 1.0f, |
| 7442 | int32_t offset = 0) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7443 | { |
| 7444 | auto dataType = (std::is_same<T, uint8_t>::value ? armnn::DataType::QuantisedAsymm8 : armnn::DataType::Float32); |
| 7445 | |
| 7446 | armnn::TensorInfo inputTensorInfo(InputDim, inputShape, dataType); |
| 7447 | armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, dataType); |
| 7448 | |
| 7449 | inputTensorInfo.SetQuantizationScale(scale); |
| 7450 | inputTensorInfo.SetQuantizationOffset(offset); |
| 7451 | |
| 7452 | outputTensorInfo.SetQuantizationScale(scale); |
| 7453 | outputTensorInfo.SetQuantizationOffset(offset); |
| 7454 | |
| 7455 | auto input = MakeTensor<T, InputDim>(inputTensorInfo, inputData); |
| 7456 | |
| 7457 | LayerTestResult<T, OutputDim> result(outputTensorInfo); |
| 7458 | result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo, outputData); |
| 7459 | |
| 7460 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 7461 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 7462 | |
| 7463 | armnn::BatchToSpaceNdQueueDescriptor data; |
| 7464 | data.m_Parameters.m_DataLayout = dataLayout; |
| 7465 | data.m_Parameters.m_BlockShape = blockShape; |
| 7466 | data.m_Parameters.m_Crops = crops; |
| 7467 | armnn::WorkloadInfo info; |
| 7468 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 7469 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 7470 | |
| 7471 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchToSpaceNd(data, info); |
| 7472 | |
| 7473 | inputHandle->Allocate(); |
| 7474 | outputHandle->Allocate(); |
| 7475 | |
| 7476 | CopyDataToITensorHandle(inputHandle.get(), input.origin()); |
| 7477 | |
| 7478 | workload->Execute(); |
| 7479 | |
| 7480 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 7481 | |
| 7482 | return result; |
| 7483 | } |
| 7484 | |
| 7485 | } // anonymous namespace |
| 7486 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7487 | LayerTestResult<float, 4> BatchToSpaceNdNhwcFloat32Test1( |
| 7488 | armnn::IWorkloadFactory& workloadFactory, |
| 7489 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7490 | { |
| 7491 | const unsigned int inputShape[] = {4, 2, 2, 1}; |
| 7492 | const unsigned int outputShape[] = {1, 4, 4, 1 }; |
| 7493 | |
| 7494 | std::vector<float> input |
| 7495 | ({ |
| 7496 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 7497 | 1.0f, 3.0f, |
| 7498 | // Batch 0, Height 1, Width (2) x Channel (1) |
| 7499 | 9.0f, 11.0f, |
| 7500 | |
| 7501 | |
| 7502 | // Batch 1, Height 0, Width (2) x Channel (1) |
| 7503 | 2.0f, 4.0f, |
| 7504 | // Batch 1, Height 1, Width (2) x Channel (1) |
| 7505 | 10.0f, 12.0f, |
| 7506 | |
| 7507 | |
| 7508 | // Batch 2, Height 0, Width (2) x Channel (1) |
| 7509 | 5.0f, 7.0f, |
| 7510 | // Batch 2, Height 1, Width (2) x Channel (1) |
| 7511 | 13.0f, 15.0f, |
| 7512 | |
| 7513 | // Batch 3, Height 0, Width (2) x Channel (3) |
| 7514 | 6.0f, 8.0f, |
| 7515 | // Batch 3, Height 1, Width (2) x Channel (1) |
| 7516 | 14.0f, 16.0f |
| 7517 | }); |
| 7518 | |
| 7519 | std::vector<float> expectedOutput |
| 7520 | ({ |
| 7521 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 7522 | 5.0f, 6.0f, 7.0f, 8.0f, |
| 7523 | 9.0f, 10.0f, 11.0f, 12.0f, |
| 7524 | 13.0f, 14.0f, 15.0f, 16.0f |
| 7525 | }); |
| 7526 | |
| 7527 | std::vector<unsigned int> blockShape {2, 2}; |
Éanna Ó Catháin | 95807ce | 2018-11-12 17:14:43 +0000 | [diff] [blame] | 7528 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7529 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7530 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 7531 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7532 | crops, outputShape, expectedOutput); |
| 7533 | } |
| 7534 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7535 | LayerTestResult<float, 4> BatchToSpaceNdNhwcFloat32Test2( |
| 7536 | armnn::IWorkloadFactory& workloadFactory, |
| 7537 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7538 | { |
| 7539 | const unsigned int inputShape[] = {4, 1, 1, 1}; |
| 7540 | const unsigned int outputShape[] = {1, 2, 2, 1}; |
| 7541 | |
| 7542 | std::vector<float> input |
| 7543 | ({ |
| 7544 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 7545 | 1.0f, 2.0f, 3.0f, 4.0f |
| 7546 | }); |
| 7547 | |
| 7548 | std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f}); |
| 7549 | |
| 7550 | std::vector<unsigned int> blockShape({2, 2}); |
Éanna Ó Catháin | 95807ce | 2018-11-12 17:14:43 +0000 | [diff] [blame] | 7551 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7552 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7553 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 7554 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| 7555 | crops, outputShape, expectedOutput); |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7556 | } |
| 7557 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7558 | LayerTestResult<float, 4> BatchToSpaceNdNhwcFloat32Test3( |
| 7559 | armnn::IWorkloadFactory& workloadFactory, |
| 7560 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7561 | { |
| 7562 | const unsigned int inputShape[] = {4, 1, 1, 3}; |
| 7563 | const unsigned int outputShape[] = {1, 2, 2, 3}; |
| 7564 | |
| 7565 | std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f }); |
| 7566 | |
| 7567 | std::vector<float> expectedOutput({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f }); |
| 7568 | |
| 7569 | std::vector<unsigned int> blockShape({2, 2}); |
Éanna Ó Catháin | 95807ce | 2018-11-12 17:14:43 +0000 | [diff] [blame] | 7570 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7571 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7572 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 7573 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| 7574 | crops, outputShape, expectedOutput); |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7575 | } |
| 7576 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7577 | LayerTestResult<float, 4> BatchToSpaceNdNchwFloat32Test1( |
| 7578 | armnn::IWorkloadFactory &workloadFactory, |
| 7579 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7580 | { |
| 7581 | const unsigned int inputShape[] = {4, 3, 1, 1}; |
| 7582 | const unsigned int outputShape[] = {1, 3, 2, 2}; |
| 7583 | |
| 7584 | std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f }); |
| 7585 | |
| 7586 | std::vector<float> expectedOutput |
| 7587 | ({ |
| 7588 | // Batch 0, Channel 0, Height (2) x Width (2) |
| 7589 | 1.0f, 4.0f, |
| 7590 | 7.0f, 10.0f, |
| 7591 | |
| 7592 | // Batch 0, Channel 1, Height (2) x Width (2) |
| 7593 | 2.0f, 5.0f, |
| 7594 | 8.0f, 11.0f, |
| 7595 | |
| 7596 | // Batch 0, Channel 2, Height (2) x Width (2) |
| 7597 | 3.0f, 6.0f, |
| 7598 | 9.0f, 12.0f, |
| 7599 | }); |
| 7600 | |
| 7601 | std::vector<unsigned int> blockShape({2, 2}); |
Éanna Ó Catháin | 95807ce | 2018-11-12 17:14:43 +0000 | [diff] [blame] | 7602 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7603 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7604 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 7605 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 7606 | crops, outputShape, expectedOutput); |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 7607 | } |
Éanna Ó Catháin | 262553e | 2018-11-14 11:26:23 +0000 | [diff] [blame] | 7608 | |
Mike Kelly | 831faed | 2018-11-28 11:52:08 +0000 | [diff] [blame] | 7609 | LayerTestResult<float, 4> BatchToSpaceNdNchwFloat32Test2( |
| 7610 | armnn::IWorkloadFactory& workloadFactory, |
| 7611 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7612 | { |
| 7613 | const unsigned int inputShape[] = {4, 1, 1, 1}; |
| 7614 | const unsigned int outputShape[] = {1, 1, 2, 2}; |
| 7615 | |
| 7616 | std::vector<float> input |
| 7617 | ({ |
| 7618 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 7619 | 1.0f, 2.0f, 3.0f, 4.0f |
| 7620 | }); |
| 7621 | |
| 7622 | std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f}); |
| 7623 | |
| 7624 | std::vector<unsigned int> blockShape({2, 2}); |
| 7625 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 7626 | |
| 7627 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 7628 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 7629 | crops, outputShape, expectedOutput); |
| 7630 | } |
| 7631 | |
| 7632 | LayerTestResult<float, 4> BatchToSpaceNdNchwFloat32Test3( |
| 7633 | armnn::IWorkloadFactory& workloadFactory, |
| 7634 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7635 | { |
| 7636 | const unsigned int inputShape[] = {4, 3, 1, 1}; |
| 7637 | const unsigned int outputShape[] = {1, 3, 2, 2}; |
| 7638 | |
| 7639 | std::vector<float> input({ 1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f }); |
| 7640 | |
| 7641 | std::vector<float> expectedOutput |
| 7642 | ({ |
| 7643 | // Batch 0, Channel 0, Height (2) x Width (2) |
| 7644 | 1.0f, 7.0f, |
| 7645 | 2.0f, 8.0f, |
| 7646 | |
| 7647 | // Batch 0, Channel 1, Height (2) x Width (2) |
| 7648 | 3.0f, 9.0f, |
| 7649 | 4.0f, 10.0f, |
| 7650 | |
| 7651 | // Batch 0, Channel 2, Height (2) x Width (2) |
| 7652 | 5.0f, 11.0f, |
| 7653 | 6.0f, 12.0f, |
| 7654 | }); |
| 7655 | |
| 7656 | std::vector<unsigned int> blockShape({2, 2}); |
| 7657 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 7658 | |
| 7659 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 7660 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 7661 | crops, outputShape, expectedOutput); |
| 7662 | } |
Éanna Ó Catháin | 262553e | 2018-11-14 11:26:23 +0000 | [diff] [blame] | 7663 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7664 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcUintTest1( |
| 7665 | armnn::IWorkloadFactory& workloadFactory, |
| 7666 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 262553e | 2018-11-14 11:26:23 +0000 | [diff] [blame] | 7667 | { |
| 7668 | const unsigned int inputShape[] = {4, 2, 2, 1}; |
| 7669 | const unsigned int outputShape[] = {1, 4, 4, 1}; |
| 7670 | |
| 7671 | std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 }); |
| 7672 | std::vector<uint8_t> expectedOutput({ 1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16}); |
| 7673 | |
| 7674 | std::vector<unsigned int> blockShape({2, 2}); |
| 7675 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 7676 | |
Matteo Martincigh | a65b7ae | 2018-11-14 12:39:55 +0000 | [diff] [blame] | 7677 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, armnn::DataLayout::NHWC, inputShape, |
| 7678 | input, blockShape, crops, outputShape, expectedOutput); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7679 | } |
Nattapat Chaimanowong | 1216b58 | 2018-11-23 15:33:41 +0000 | [diff] [blame] | 7680 | |
| 7681 | LayerTestResult<float, 4> StridedSlice4DFloat32Test( |
| 7682 | armnn::IWorkloadFactory& workloadFactory, |
| 7683 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7684 | { |
| 7685 | return StridedSlice4DTest<float>(workloadFactory, memoryManager); |
| 7686 | } |
| 7687 | |
| 7688 | LayerTestResult<float, 4> StridedSlice4DReverseFloat32Test( |
| 7689 | armnn::IWorkloadFactory& workloadFactory, |
| 7690 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7691 | { |
| 7692 | return StridedSlice4DReverseTest<float>(workloadFactory, memoryManager); |
| 7693 | } |
| 7694 | |
| 7695 | LayerTestResult<float, 4> StridedSliceSimpleStrideFloat32Test( |
| 7696 | armnn::IWorkloadFactory& workloadFactory, |
| 7697 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7698 | { |
| 7699 | return StridedSliceSimpleStrideTest<float>(workloadFactory, memoryManager); |
| 7700 | } |
| 7701 | |
| 7702 | LayerTestResult<float, 4> StridedSliceSimpleRangeMaskFloat32Test( |
| 7703 | armnn::IWorkloadFactory& workloadFactory, |
| 7704 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7705 | { |
| 7706 | return StridedSliceSimpleRangeMaskTest<float>(workloadFactory, memoryManager); |
| 7707 | } |
| 7708 | |
| 7709 | LayerTestResult<float, 2> StridedSliceShrinkAxisMaskFloat32Test( |
| 7710 | armnn::IWorkloadFactory& workloadFactory, |
| 7711 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7712 | { |
| 7713 | return StridedSliceShrinkAxisMaskTest<float>(workloadFactory, memoryManager); |
| 7714 | } |
| 7715 | |
| 7716 | LayerTestResult<float, 3> StridedSlice3DFloat32Test( |
| 7717 | armnn::IWorkloadFactory& workloadFactory, |
| 7718 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7719 | { |
| 7720 | return StridedSlice3DTest<float>(workloadFactory, memoryManager); |
| 7721 | } |
| 7722 | |
| 7723 | LayerTestResult<float, 3> StridedSlice3DReverseFloat32Test( |
| 7724 | armnn::IWorkloadFactory& workloadFactory, |
| 7725 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7726 | { |
| 7727 | return StridedSlice3DReverseTest<float>(workloadFactory, memoryManager); |
| 7728 | } |
| 7729 | |
| 7730 | LayerTestResult<float, 2> StridedSlice2DFloat32Test( |
| 7731 | armnn::IWorkloadFactory& workloadFactory, |
| 7732 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7733 | { |
| 7734 | return StridedSlice2DTest<float>(workloadFactory, memoryManager); |
| 7735 | } |
| 7736 | |
| 7737 | LayerTestResult<float, 2> StridedSlice2DReverseFloat32Test( |
| 7738 | armnn::IWorkloadFactory& workloadFactory, |
| 7739 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7740 | { |
| 7741 | return StridedSlice2DReverseTest<float>(workloadFactory, memoryManager); |
| 7742 | } |
| 7743 | |
| 7744 | LayerTestResult<uint8_t, 4> StridedSlice4DUint8Test( |
| 7745 | armnn::IWorkloadFactory& workloadFactory, |
| 7746 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7747 | { |
| 7748 | return StridedSlice4DTest<uint8_t>(workloadFactory, memoryManager); |
| 7749 | } |
| 7750 | |
| 7751 | LayerTestResult<uint8_t, 4> StridedSlice4DReverseUint8Test( |
| 7752 | armnn::IWorkloadFactory& workloadFactory, |
| 7753 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7754 | { |
| 7755 | return StridedSlice4DReverseTest<uint8_t>(workloadFactory, memoryManager); |
| 7756 | } |
| 7757 | |
| 7758 | LayerTestResult<uint8_t, 4> StridedSliceSimpleStrideUint8Test( |
| 7759 | armnn::IWorkloadFactory& workloadFactory, |
| 7760 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7761 | { |
| 7762 | return StridedSliceSimpleStrideTest<uint8_t>(workloadFactory, memoryManager); |
| 7763 | } |
| 7764 | |
| 7765 | LayerTestResult<uint8_t, 4> StridedSliceSimpleRangeMaskUint8Test( |
| 7766 | armnn::IWorkloadFactory& workloadFactory, |
| 7767 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7768 | { |
| 7769 | return StridedSliceSimpleRangeMaskTest<uint8_t>(workloadFactory, memoryManager); |
| 7770 | } |
| 7771 | |
| 7772 | LayerTestResult<uint8_t, 2> StridedSliceShrinkAxisMaskUint8Test( |
| 7773 | armnn::IWorkloadFactory& workloadFactory, |
| 7774 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7775 | { |
| 7776 | return StridedSliceShrinkAxisMaskTest<uint8_t>(workloadFactory, memoryManager); |
| 7777 | } |
| 7778 | |
| 7779 | LayerTestResult<uint8_t, 3> StridedSlice3DUint8Test( |
| 7780 | armnn::IWorkloadFactory& workloadFactory, |
| 7781 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7782 | { |
| 7783 | return StridedSlice3DTest<uint8_t>(workloadFactory, memoryManager); |
| 7784 | } |
| 7785 | |
| 7786 | LayerTestResult<uint8_t, 3> StridedSlice3DReverseUint8Test( |
| 7787 | armnn::IWorkloadFactory& workloadFactory, |
| 7788 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7789 | { |
| 7790 | return StridedSlice3DReverseTest<uint8_t>(workloadFactory, memoryManager); |
| 7791 | } |
| 7792 | |
| 7793 | LayerTestResult<uint8_t, 2> StridedSlice2DUint8Test( |
| 7794 | armnn::IWorkloadFactory& workloadFactory, |
| 7795 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7796 | { |
| 7797 | return StridedSlice2DTest<uint8_t>(workloadFactory, memoryManager); |
| 7798 | } |
| 7799 | |
| 7800 | LayerTestResult<uint8_t, 2> StridedSlice2DReverseUint8Test( |
| 7801 | armnn::IWorkloadFactory& workloadFactory, |
| 7802 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7803 | { |
| 7804 | return StridedSlice2DReverseTest<uint8_t>(workloadFactory, memoryManager); |
| 7805 | } |
Mike Kelly | 831faed | 2018-11-28 11:52:08 +0000 | [diff] [blame] | 7806 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcUintTest2( |
| 7807 | armnn::IWorkloadFactory& workloadFactory, |
| 7808 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7809 | { |
| 7810 | const unsigned int inputShape[] = {4, 1, 1, 1}; |
| 7811 | const unsigned int outputShape[] = {1, 2, 2, 1}; |
| 7812 | |
| 7813 | std::vector<uint8_t> input |
| 7814 | ({ |
| 7815 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 7816 | 1, 2, 3, 4 |
| 7817 | }); |
| 7818 | |
| 7819 | std::vector<uint8_t> expectedOutput({1, 2, 3, 4}); |
| 7820 | |
| 7821 | std::vector<unsigned int> blockShape({2, 2}); |
| 7822 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 7823 | |
| 7824 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 7825 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| 7826 | crops, outputShape, expectedOutput); |
| 7827 | } |
| 7828 | |
| 7829 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcUintTest3( |
| 7830 | armnn::IWorkloadFactory& workloadFactory, |
| 7831 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7832 | { |
| 7833 | const unsigned int inputShape[] = {4, 1, 1, 3}; |
| 7834 | const unsigned int outputShape[] = {1, 2, 2, 3}; |
| 7835 | |
| 7836 | std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }); |
| 7837 | |
| 7838 | std::vector<uint8_t> expectedOutput({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }); |
| 7839 | |
| 7840 | std::vector<unsigned int> blockShape({2, 2}); |
| 7841 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 7842 | |
| 7843 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 7844 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| 7845 | crops, outputShape, expectedOutput); |
| 7846 | } |
| 7847 | |
| 7848 | |
| 7849 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwUintTest1( |
| 7850 | armnn::IWorkloadFactory &workloadFactory, |
| 7851 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7852 | { |
| 7853 | const unsigned int inputShape[] = {4, 3, 1, 1}; |
| 7854 | const unsigned int outputShape[] = {1, 3, 2, 2}; |
| 7855 | |
| 7856 | std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }); |
| 7857 | |
| 7858 | std::vector<uint8_t> expectedOutput |
| 7859 | ({ |
| 7860 | // Batch 0, Channel 0, Height (2) x Width (2) |
| 7861 | 1, 4, |
| 7862 | 7, 10, |
| 7863 | |
| 7864 | // Batch 0, Channel 1, Height (2) x Width (2) |
| 7865 | 2, 5, |
| 7866 | 8, 11, |
| 7867 | |
| 7868 | // Batch 0, Channel 2, Height (2) x Width (2) |
| 7869 | 3, 6, |
| 7870 | 9, 12, |
| 7871 | }); |
| 7872 | |
| 7873 | std::vector<unsigned int> blockShape({2, 2}); |
| 7874 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 7875 | |
| 7876 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 7877 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 7878 | crops, outputShape, expectedOutput); |
| 7879 | } |
| 7880 | |
| 7881 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwUintTest2( |
| 7882 | armnn::IWorkloadFactory& workloadFactory, |
| 7883 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7884 | { |
| 7885 | const unsigned int inputShape[] = {4, 1, 1, 1}; |
| 7886 | const unsigned int outputShape[] = {1, 1, 2, 2}; |
| 7887 | |
| 7888 | std::vector<uint8_t> input |
| 7889 | ({ |
| 7890 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 7891 | 1, 2, 3, 4 |
| 7892 | }); |
| 7893 | |
| 7894 | std::vector<uint8_t> expectedOutput({1, 2, 3, 4}); |
| 7895 | |
| 7896 | std::vector<unsigned int> blockShape({2, 2}); |
| 7897 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 7898 | |
| 7899 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 7900 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 7901 | crops, outputShape, expectedOutput); |
| 7902 | } |
| 7903 | |
| 7904 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwUintTest3( |
| 7905 | armnn::IWorkloadFactory& workloadFactory, |
| 7906 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7907 | { |
| 7908 | const unsigned int inputShape[] = {4, 3, 1, 1}; |
| 7909 | const unsigned int outputShape[] = {1, 3, 2, 2}; |
| 7910 | |
| 7911 | std::vector<uint8_t> input({ 1, 3, 5, 7, 9, 11, 2, 4, 6, 8, 10, 12 }); |
| 7912 | |
| 7913 | std::vector<uint8_t> expectedOutput |
| 7914 | ({ |
| 7915 | // Batch 0, Channel 0, Height (2) x Width (2) |
| 7916 | 1, 7, |
| 7917 | 2, 8, |
| 7918 | |
| 7919 | // Batch 0, Channel 1, Height (2) x Width (2) |
| 7920 | 3, 9, |
| 7921 | 4, 10, |
| 7922 | |
| 7923 | // Batch 0, Channel 2, Height (2) x Width (2) |
| 7924 | 5, 11, |
| 7925 | 6, 12, |
| 7926 | }); |
| 7927 | std::vector<unsigned int> blockShape({2, 2}); |
| 7928 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 7929 | |
| 7930 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 7931 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 7932 | crops, outputShape, expectedOutput); |
| 7933 | } |