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" |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 40 | #include "PreCompiledTestImpl.hpp" |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 41 | #include "LstmTestImpl.hpp" |
| 42 | #include "ConvertFp16ToFp32TestImpl.hpp" |
| 43 | #include "ConvertFp32ToFp16TestImpl.hpp" |
Nattapat Chaimanowong | cfdcadf | 2018-12-06 11:54:33 +0000 | [diff] [blame] | 44 | #include "DebugTestImpl.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 45 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 46 | // 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] | 47 | static std::vector<float> ConvInput3x8x16({ |
| 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 | 0.0f, 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, |
| 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 | 0.5f, 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, |
| 55 | 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, |
| 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 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 63 | 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 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 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, |
| 71 | -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 |
| 72 | }); |
| 73 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 74 | // 2-channel bias used by a number of Conv2d tests. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 75 | static std::vector<float> Bias2({0, 2}); |
| 76 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 77 | // 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] | 78 | template<typename T> |
| 79 | boost::multi_array<T, 1> GetBias2(bool biasEnabled, float qScale, int32_t qOffset) |
| 80 | { |
| 81 | if(biasEnabled) |
| 82 | { |
| 83 | armnn::TensorInfo biasDesc({static_cast<unsigned int>(Bias2.size())}, armnn::GetDataType<T>()); |
| 84 | boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasDesc, QuantizedVector<T>(qScale, qOffset, Bias2)); |
| 85 | return bias; |
| 86 | } |
| 87 | else |
| 88 | { |
| 89 | return boost::multi_array<T, 1>(); |
| 90 | } |
| 91 | } |
| 92 | |
| 93 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 94 | LayerTestResult<T, 4> SimpleConvolution2d3x5TestCommon( |
| 95 | armnn::IWorkloadFactory& workloadFactory, |
| 96 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 97 | float qScale, |
| 98 | int32_t qOffset, |
| 99 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 100 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 101 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 102 | // Use common single-batch 3-channel 16x8 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 103 | armnn::TensorInfo inputDesc({1, 3, 8, 16}, armnn::GetDataType<T>()); |
| 104 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, QuantizedVector<T>(qScale, qOffset, ConvInput3x8x16)); |
| 105 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 106 | // Use a 2-element batch with 3-channel 3x5 kernels. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 107 | armnn::TensorInfo kernelDesc({2, 3, 5, 3}, armnn::GetDataType<T>()); |
| 108 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, std::vector<T>( |
| 109 | QuantizedVector<T>(qScale, qOffset, { |
| 110 | 1, 1, 1, |
| 111 | 1, -1, 1, |
| 112 | 1, 1, 1, |
| 113 | 1, 1, 1, |
| 114 | 1, 1, 1, |
| 115 | |
| 116 | 0, 0, 0, |
| 117 | 0, 0, 0, |
| 118 | 0, 0, 0, |
| 119 | 0, 0, 0, |
| 120 | 0, 0, 0, |
| 121 | |
| 122 | 2, 2, 2, |
| 123 | 2, 2, 2, |
| 124 | 2, 2, 2, |
| 125 | 2, 2, 2, |
| 126 | 2, 2, 2, |
| 127 | |
| 128 | |
| 129 | 0, 0, 0, |
| 130 | 0, 0, 0, |
| 131 | 0, 0, 0, |
| 132 | 0, 0, 0, |
| 133 | 0, 0, 0, |
| 134 | |
| 135 | 1, 1, 1, |
| 136 | 1, 1, 1, |
| 137 | 1, 1, 1, |
| 138 | 1, 1, 1, |
| 139 | 1, 1, 1, |
| 140 | |
| 141 | 0, 0, 0, |
| 142 | 0, 0, 0, |
| 143 | 0, 0, 0, |
| 144 | 0, 0, 0, |
| 145 | 0, 0, 0 |
| 146 | }))); |
| 147 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 148 | // Expected output is 2 batch elements of a 1-channel 14x4 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 149 | armnn::TensorInfo outputDesc({1, 2, 4, 14}, armnn::GetDataType<T>()); |
| 150 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, std::vector<T>( |
| 151 | QuantizedVector<T>(qScale, qOffset, { |
| 152 | -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, -24, |
| 153 | -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, -25, |
| 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 | -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, -23.5f, |
| 157 | -23.5f, -23.5f, -23.5f, |
| 158 | |
| 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 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 162 | 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 163 | }))); |
| 164 | |
| 165 | return SimpleConvolution2dTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 166 | memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 167 | input, |
| 168 | kernel, |
| 169 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasEnabled, qScale, qOffset), |
| 170 | expectedOutput, |
| 171 | qScale, |
jimfly01 | 0a088a6 | 2018-10-25 17:05:05 +0100 | [diff] [blame] | 172 | qOffset, |
| 173 | layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 174 | } |
| 175 | |
| 176 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 177 | LayerTestResult<T, 4> SimpleConvolution2d3x3TestCommon( |
| 178 | armnn::IWorkloadFactory& workloadFactory, |
| 179 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 180 | float qScale, |
| 181 | int32_t qOffset, |
| 182 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 183 | const armnn::DataLayout layout) |
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 a 3x3 kernel, which exercises ArmCompute's direct convolution path. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 186 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 187 | // Use common single-batch 3-channel 16x8 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 188 | armnn::TensorInfo inputDesc({1, 3, 8, 16}, armnn::GetDataType<T>()); |
| 189 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, QuantizedVector<T>(qScale, qOffset, ConvInput3x8x16)); |
| 190 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 191 | // Use a 2-element batch of 3-channel 3x3 kernels. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 192 | armnn::TensorInfo kernelDesc({2, 3, 3, 3}, armnn::GetDataType<T>()); |
| 193 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, std::vector<T>( |
| 194 | QuantizedVector<T>(qScale, qOffset, { |
| 195 | 1, 1, 1, |
| 196 | 1, -1, 1, |
| 197 | 1, 1, 1, |
| 198 | |
| 199 | 0, 0, 0, |
| 200 | 0, 0, 0, |
| 201 | 0, 0, 0, |
| 202 | |
| 203 | 2, 2, 2, |
| 204 | 2, 2, 2, |
| 205 | 2, 2, 2, |
| 206 | |
| 207 | |
| 208 | 0, 0, 0, |
| 209 | 0, 0, 0, |
| 210 | 0, 0, 0, |
| 211 | |
| 212 | 1, 1, 1, |
| 213 | 1, 1, 1, |
| 214 | 1, 1, 1, |
| 215 | |
| 216 | 0, 0, 0, |
| 217 | 0, 0, 0, |
| 218 | 0, 0, 0 |
| 219 | }))); |
| 220 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 221 | // Expected output is 1 batch of a 2-channel 14x6 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 222 | armnn::TensorInfo outputDesc({1, 2, 6, 14}, armnn::GetDataType<T>()); |
| 223 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, std::vector<T>( |
| 224 | QuantizedVector<T>(qScale, qOffset, { |
| 225 | -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, -15, |
| 226 | -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, -16, |
| 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 | -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, |
| 230 | -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, |
| 231 | |
| 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 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
| 237 | 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| 238 | }))); |
| 239 | |
| 240 | return SimpleConvolution2dTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 241 | memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 242 | input, |
| 243 | kernel, |
| 244 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasEnabled, qScale, qOffset), |
| 245 | expectedOutput, |
| 246 | qScale, |
narpra01 | 5f70318 | 2018-10-26 16:24:58 +0100 | [diff] [blame] | 247 | qOffset, |
| 248 | layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 249 | } |
| 250 | |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 251 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 252 | LayerTestResult<T, 4> SimpleConvolution2d3x3NhwcTestCommon( |
| 253 | armnn::IWorkloadFactory& workloadFactory, |
| 254 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 255 | float qScale, |
| 256 | int32_t qOffset, |
| 257 | bool biasEnabled, |
| 258 | armnn::DataLayout dataLayout) |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 259 | { |
| 260 | // Use common single-batch 5x5 image. |
| 261 | |
| 262 | armnn::TensorInfo inputDesc({1, 3, 4, 1}, armnn::GetDataType<T>()); |
| 263 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, |
| 264 | { |
| 265 | 1, 5, 2, 3, |
| 266 | 8, 7, 3, 6, |
| 267 | 3, 3, 9, 1 |
| 268 | }); |
| 269 | |
| 270 | |
| 271 | // Use a 2-element batch of 3-channel 3x3 kernels. |
| 272 | armnn::TensorInfo kernelDesc({1, 3, 3, 1}, armnn::GetDataType<T>()); |
| 273 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, { |
| 274 | 4, 5, 6, |
| 275 | 0, 0, 0, |
| 276 | 3, 2, 1 |
| 277 | }); |
| 278 | |
| 279 | // Expected output is 1 batch of a 5x5 image. |
| 280 | armnn::TensorInfo outputDesc({1, 3, 4, 1}, armnn::GetDataType<T>()); |
| 281 | |
| 282 | const std::vector<float> outputData = |
| 283 | { |
| 284 | 23, 41, 33, 21, |
| 285 | 44, 65, 76, 52, |
| 286 | 82, 85, 79, 42 |
| 287 | }; |
| 288 | |
| 289 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, outputData); |
| 290 | |
| 291 | return SimpleConvolution2dNhwcTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 292 | memoryManager, |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 293 | input, |
| 294 | kernel, |
| 295 | boost::multi_array<T, 1>(), |
| 296 | expectedOutput, |
| 297 | dataLayout, |
| 298 | qScale, |
| 299 | qOffset); |
| 300 | } |
| 301 | |
Mike Kelly | 7332ed8 | 2018-12-20 17:03:06 +0000 | [diff] [blame] | 302 | template<typename T> |
| 303 | LayerTestResult<T, 4> SimpleConvolution2d3x3Stride2x2TestCommon( |
| 304 | armnn::IWorkloadFactory& workloadFactory, |
| 305 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 306 | float qScale, |
| 307 | int32_t qOffset, |
| 308 | bool biasEnabled, |
| 309 | const armnn::DataLayout& dataLayout) |
| 310 | { |
| 311 | // Input is a single-batch, 1 channel, 5x5 image. |
| 312 | armnn::TensorInfo inputDesc({1, 5, 5, 1}, armnn::GetDataType<T>()); |
| 313 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, |
| 314 | { |
| 315 | 1, 5, 2, 3, 5, |
| 316 | 8, 7, 3, 6, 3, |
| 317 | 3, 3, 9, 1, 9, |
| 318 | 4, 1, 8, 1, 3, |
| 319 | 6, 8, 1, 9, 2 |
| 320 | }); |
| 321 | |
| 322 | // Use a 3x3 kernel. |
| 323 | armnn::TensorInfo kernelDesc({1, 3, 3, 1}, armnn::GetDataType<T>()); |
| 324 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, |
| 325 | { |
| 326 | 4, 5, 6, |
| 327 | 0, 0, 0, |
| 328 | 3, 2, 1 |
| 329 | }); |
| 330 | |
| 331 | // Expected output is a single-batch, 1 channel, 3x3 image. |
| 332 | armnn::TensorInfo outputDesc({1, 3, 3, 1}, armnn::GetDataType<T>()); |
| 333 | |
| 334 | const std::vector<T> outputData = |
| 335 | { |
| 336 | 23, 33, 24, |
| 337 | 91, 99, 48, |
| 338 | 26, 50, 19 |
| 339 | }; |
| 340 | |
| 341 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, outputData); |
| 342 | |
| 343 | uint32_t padLeft = 1; |
| 344 | uint32_t padTop = 1; |
| 345 | uint32_t padRight = 1; |
| 346 | uint32_t padBottom = 1; |
| 347 | uint32_t strideX = 2; |
| 348 | uint32_t strideY = 2; |
| 349 | |
| 350 | return SimpleConvolution2dNhwcTestImpl<T>(workloadFactory, |
| 351 | memoryManager, |
| 352 | input, |
| 353 | kernel, |
| 354 | boost::multi_array<T, 1>(), |
| 355 | expectedOutput, |
| 356 | dataLayout, |
| 357 | qScale, |
| 358 | qOffset, |
| 359 | padLeft, |
| 360 | padTop, |
| 361 | padRight, |
| 362 | padBottom, |
| 363 | strideX, |
| 364 | strideY); |
| 365 | } |
| 366 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 367 | LayerTestResult<float, 4> SimpleConvolution2d3x5Test( |
| 368 | armnn::IWorkloadFactory& workloadFactory, |
| 369 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 370 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 371 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 372 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 373 | return SimpleConvolution2d3x5TestCommon<float>(workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 374 | } |
| 375 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 376 | LayerTestResult<uint8_t, 4> SimpleConvolution2d3x5Uint8Test( |
| 377 | armnn::IWorkloadFactory& workloadFactory, |
| 378 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 379 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 380 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 381 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 382 | return SimpleConvolution2d3x5TestCommon<uint8_t>(workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 383 | } |
| 384 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 385 | LayerTestResult<float, 4> SimpleConvolution2d3x3Test( |
| 386 | armnn::IWorkloadFactory& workloadFactory, |
| 387 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 388 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 389 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 390 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 391 | return SimpleConvolution2d3x3TestCommon<float>(workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 392 | } |
| 393 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 394 | LayerTestResult<float, 4> SimpleConvolution2d3x3NhwcTest( |
| 395 | armnn::IWorkloadFactory& workloadFactory, |
| 396 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 397 | bool biasEnabled) |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 398 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 399 | return SimpleConvolution2d3x3NhwcTestCommon<float>(workloadFactory, |
| 400 | memoryManager, |
| 401 | 0.f, |
| 402 | 0, |
| 403 | biasEnabled, |
| 404 | armnn::DataLayout::NHWC); |
Francis Murtagh | d59116e | 2018-10-04 16:03:07 +0100 | [diff] [blame] | 405 | } |
| 406 | |
Mike Kelly | 7332ed8 | 2018-12-20 17:03:06 +0000 | [diff] [blame] | 407 | LayerTestResult<float, 4> SimpleConvolution2d3x3Stride2x2Test( |
| 408 | armnn::IWorkloadFactory& workloadFactory, |
| 409 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 410 | bool biasEnabled, |
| 411 | const armnn::DataLayout layout) |
| 412 | { |
| 413 | return SimpleConvolution2d3x3Stride2x2TestCommon<float>(workloadFactory, |
| 414 | memoryManager, |
| 415 | 0.f, |
| 416 | 0, |
| 417 | biasEnabled, |
| 418 | layout); |
| 419 | } |
| 420 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 421 | LayerTestResult<uint8_t, 4> SimpleConvolution2d3x3Uint8Test( |
| 422 | armnn::IWorkloadFactory& workloadFactory, |
| 423 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 424 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 425 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 426 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 427 | return SimpleConvolution2d3x3TestCommon<uint8_t>(workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 428 | } |
| 429 | |
| 430 | template<typename T> |
| 431 | LayerTestResult<T, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon( |
| 432 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 433 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 434 | const armnn::DataLayout layout, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 435 | float qScale, |
| 436 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 437 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 438 | // Use a single-batch 1-channel 3x3 image as input. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 439 | armnn::TensorInfo inputDesc({1, 1, 3, 3}, armnn::GetDataType<T>()); |
| 440 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, std::vector<T>( |
| 441 | QuantizedVector<T>(qScale, qOffset, { |
| 442 | 11,21,31, |
| 443 | 12,22,32, |
| 444 | 13,23,33 |
| 445 | }))); |
| 446 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 447 | // Use 1 batch of a 1-channel 2x2 kernel. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 448 | armnn::TensorInfo kernelDesc({1, 1, 2, 2}, armnn::GetDataType<T>()); |
| 449 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, std::vector<T>( |
| 450 | QuantizedVector<T>(qScale, qOffset, { |
| 451 | -11,-21, |
| 452 | -12,-22, |
| 453 | }))); |
| 454 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 455 | // Expected output is 1 batch of a 1-channel 6x8 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 456 | // Manually calculated like this: |
| 457 | //[-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 ..] |
| 458 | //[-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 ..] |
| 459 | //[-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 ..] |
| 460 | //[-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 ..] |
| 461 | //[-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 ..] |
| 462 | //[-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 ..] |
| 463 | //[..... ..... ..... ..... ; ..... ..... ..... ..... ; ..... ..... ..... ..... ; ..... ..... ..... ..... ..] |
| 464 | armnn::TensorInfo outputDesc({1, 1, 8, 6}, armnn::GetDataType<T>()); |
| 465 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, std::vector<T>( |
| 466 | QuantizedVector<T>(qScale, qOffset, { |
| 467 | 0, 0, 0, 0, 0, 0, |
| 468 | -242, -594, -934, -372, 0, 0, |
| 469 | -495, -1190, -1850, -725, 0, 0, |
| 470 | -538, -1256, -1916, -748, 0, 0, |
| 471 | -273, -626, -946, -363, 0, 0, |
| 472 | 0, 0, 0, 0, 0, 0, |
| 473 | 0, 0, 0, 0, 0, 0, |
| 474 | 0, 0, 0, 0, 0, 0 |
| 475 | }))); |
| 476 | |
| 477 | return SimpleConvolution2dTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 478 | memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 479 | input, |
| 480 | kernel, |
| 481 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(false, qScale, qOffset), |
| 482 | expectedOutput, |
| 483 | qScale, |
| 484 | qOffset, |
narpra01 | 5f70318 | 2018-10-26 16:24:58 +0100 | [diff] [blame] | 485 | layout, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 486 | 1, // Padding left. |
| 487 | 2, // Padding top. |
| 488 | 3, // Padding right. |
| 489 | 4); // Padding bottom. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 490 | } |
| 491 | |
| 492 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 493 | LayerTestResult<T, 4> SimpleConvolution2dAsymmetricPaddingTestCommon( |
| 494 | armnn::IWorkloadFactory& workloadFactory, |
| 495 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 496 | const armnn::DataLayout layout, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 497 | float qScale, |
| 498 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 499 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 500 | // Use a single-batch 1-channel 5x5 image as input. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 501 | armnn::TensorInfo inputDesc({ 1, 1, 5, 5 }, armnn::GetDataType<T>()); |
| 502 | boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputDesc, std::vector<T>( |
| 503 | QuantizedVector<T>(qScale, qOffset, { |
| 504 | 11,21,31,41,51, |
| 505 | 12,22,32,42,52, |
| 506 | 13,23,33,43,53, |
| 507 | 14,24,34,44,54, |
| 508 | 15,25,35,45,55, |
| 509 | }))); |
| 510 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 511 | // Use 1 batch of a 1-channel 4x4 kernel. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 512 | armnn::TensorInfo kernelDesc({ 1, 1, 4, 4 }, armnn::GetDataType<T>()); |
| 513 | boost::multi_array<T, 4> kernel = MakeTensor<T, 4>(kernelDesc, std::vector<T>( |
| 514 | QuantizedVector<T>(qScale, qOffset, { |
| 515 | -11,-21,-31,-41, |
| 516 | -12,-22,-32,-42, |
| 517 | -13,-23,-33,-43, |
| 518 | -14,-24,-34,-44, |
| 519 | }))); |
| 520 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 521 | // Expected output is 1 batch of a 1-channel 5x5 image. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 522 | armnn::TensorInfo outputDesc({ 1, 1, 5, 5 }, armnn::GetDataType<T>()); |
| 523 | std::vector<T> myVec(outputDesc.GetNumElements(), 0); |
| 524 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputDesc, std::vector<T>( |
| 525 | QuantizedVector<T>(qScale, qOffset, { |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 526 | -7140, -10580, -13940, -9300, -5230, |
| 527 | -9590, -14120, -18520, -12290, -6860, |
| 528 | -9980, -14560, -18960, -12560, -7000, |
| 529 | -7518, -10904, -14144, -9318, -5152, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 530 | -5032, -7256, -9376, -6142, -3368, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 531 | }))); |
| 532 | |
| 533 | return SimpleConvolution2dTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 534 | memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 535 | input, |
| 536 | kernel, |
| 537 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(false, qScale, qOffset), |
| 538 | expectedOutput, |
| 539 | qScale, |
| 540 | qOffset, |
narpra01 | 5f70318 | 2018-10-26 16:24:58 +0100 | [diff] [blame] | 541 | layout, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 542 | 1, // Padding left. |
| 543 | 1, // Padding top. |
| 544 | 2, // Padding right. |
| 545 | 2); // Padding bottom. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 546 | } |
| 547 | |
| 548 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 549 | LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestCommon( |
| 550 | armnn::IWorkloadFactory& workloadFactory, |
| 551 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 552 | float qScale, |
| 553 | int32_t qOffset, |
| 554 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 555 | const armnn::DataLayout layout) |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 556 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 557 | // Use a single-batch 2-channel 5x5 image as input. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 558 | armnn::TensorInfo inputTensorInfo({ 1, 2, 5, 5 }, armnn::GetDataType<T>()); |
| 559 | auto input = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>( |
| 560 | QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(), inputTensorInfo.GetQuantizationOffset(), { |
| 561 | 0, 1, 2, 3, 4, |
| 562 | 5, 6, 7, 8, 9, |
| 563 | 10, 11, 12, 13, 14, |
| 564 | 15, 16, 17, 18, 19, |
| 565 | 20, 21, 22, 23, 24, |
| 566 | |
| 567 | 25, 26, 27, 28, 29, |
| 568 | 30, 31, 32, 33, 34, |
| 569 | 35, 36, 37, 38, 39, |
| 570 | 40, 41, 42, 43, 44, |
| 571 | 45, 46, 47, 48, 49 |
| 572 | }))); |
| 573 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 574 | // Use a depth multiplier of 1 on a 2-channel 4x4 kernel. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 575 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 4, 4 }, armnn::GetDataType<T>()); |
| 576 | auto kernel = MakeTensor<T, 4>(kernelTensorInfo, std::vector<T>( |
| 577 | QuantizedVector<T>(kernelTensorInfo.GetQuantizationScale(), kernelTensorInfo.GetQuantizationOffset(), { |
| 578 | 32, 31, 30, 29, |
| 579 | 28, 27, 26, 25, |
| 580 | 24, 23, 22, 21, |
| 581 | 20, 19, 18, 17, |
| 582 | |
| 583 | 16, 15, 14, 13, |
| 584 | 12, 11, 10, 9, |
| 585 | 8, 7, 6, 5, |
| 586 | 4, 3, 2, 1 |
| 587 | }))); |
| 588 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 589 | // Expected output is 1 batch of a 2-channel 5x5 image. |
| 590 | // Calculated using the python tensorflow library with strideX=1, strideY=1. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 591 | armnn::TensorInfo outputTensorInfo({ 1, 2, 5, 5 }, armnn::GetDataType<T>()); |
| 592 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputTensorInfo, std::vector<T>( |
| 593 | QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), { |
| 594 | 1062, 1580, 1850, 1530, 1117, |
| 595 | 2140, 3108, 3500, 2842, 2042, |
| 596 | 3580, 5068, 5460, 4342, 3062, |
| 597 | 3618, 5072, 5390, 4248, 2971, |
| 598 | 3074, 4282, 4510, 3533, 2457, |
| 599 | 1550, 2284, 2362, 1955, 1428, |
| 600 | 2910, 4206, 4342, 3528, 2536, |
| 601 | 3390, 4886, 5022, 4068, 2916, |
| 602 | 3566, 5056, 5182, 4133, 2922, |
| 603 | 3100, 4352, 4452, 3517, 2465 |
| 604 | }))); |
| 605 | |
| 606 | return DepthwiseConvolution2dAsymmetricTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 607 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 608 | input, |
| 609 | kernel, |
| 610 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasEnabled, qScale, qOffset), |
| 611 | expectedOutput, |
| 612 | qScale, |
| 613 | qOffset, |
jimfly01 | 382a91d | 2018-10-26 15:55:50 +0100 | [diff] [blame] | 614 | layout, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 615 | 1, // Padding left. |
| 616 | 1, // Padding top. |
| 617 | 2, // Padding right. |
| 618 | 2, // Padding bottom. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 619 | 1, // strideX |
| 620 | 1); // strideY |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 621 | } |
| 622 | |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 623 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 624 | LayerTestResult<T, 4> DepthwiseConvolution2dNhwcTestCommon( |
| 625 | armnn::IWorkloadFactory& workloadFactory, |
| 626 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 627 | float qScale, |
| 628 | int32_t qOffset, |
| 629 | bool biasEnabled) |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 630 | { |
| 631 | armnn::TensorInfo inputTensorInfo({ 1, 5, 5, 2}, armnn::GetDataType<T>()); |
| 632 | auto input = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>( |
| 633 | QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(), inputTensorInfo.GetQuantizationOffset(), { |
| 634 | 0, 25, |
| 635 | 1, 26, |
| 636 | 2, 27, |
| 637 | 3, 28, |
| 638 | 4, 29, |
| 639 | |
| 640 | 5, 30, |
| 641 | 6, 31, |
| 642 | 7, 32, |
| 643 | 8, 33, |
| 644 | 9, 34, |
| 645 | |
| 646 | 10, 35, |
| 647 | 11, 36, |
| 648 | 12, 37, |
| 649 | 13, 38, |
| 650 | 14, 39, |
| 651 | |
| 652 | 15, 40, |
| 653 | 16, 41, |
| 654 | 17, 42, |
| 655 | 18, 43, |
| 656 | 19, 44, |
| 657 | |
| 658 | 20, 45, |
| 659 | 21, 46, |
| 660 | 22, 47, |
| 661 | 23, 48, |
| 662 | 24, 49 |
| 663 | }))); |
| 664 | |
Matteo Martincigh | 747ef82 | 2018-12-18 09:26:39 +0000 | [diff] [blame] | 665 | armnn::TensorInfo kernelTensorInfo({ 1, 2, 4, 4 }, armnn::GetDataType<T>()); |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 666 | auto kernel = MakeTensor<T, 4>(kernelTensorInfo, std::vector<T>( |
| 667 | QuantizedVector<T>(kernelTensorInfo.GetQuantizationScale(), kernelTensorInfo.GetQuantizationOffset(), { |
Matteo Martincigh | 747ef82 | 2018-12-18 09:26:39 +0000 | [diff] [blame] | 668 | 32, 31, 30, 29, |
| 669 | 28, 27, 26, 25, |
| 670 | 24, 23, 22, 21, |
| 671 | 20, 19, 18, 17, |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 672 | |
Matteo Martincigh | 747ef82 | 2018-12-18 09:26:39 +0000 | [diff] [blame] | 673 | 16, 15, 14, 13, |
| 674 | 12, 11, 10, 9, |
| 675 | 8, 7, 6, 5, |
| 676 | 4, 3, 2, 1 |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 677 | }))); |
| 678 | |
| 679 | armnn::TensorInfo outputTensorInfo({ 1, 5, 5, 2}, armnn::GetDataType<T>()); |
| 680 | boost::multi_array<T, 4> expectedOutput = MakeTensor<T, 4>(outputTensorInfo, std::vector<T>( |
| 681 | QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(), { |
| 682 | 1062, 1550, |
| 683 | 1580, 2284, |
| 684 | 1850, 2362, |
| 685 | 1530, 1955, |
| 686 | 1117, 1428, |
| 687 | |
| 688 | 2140, 2910, |
| 689 | 3108, 4206, |
| 690 | 3500, 4342, |
| 691 | 2842, 3528, |
| 692 | 2042, 2536, |
| 693 | |
| 694 | 3580, 3390, |
| 695 | 5068, 4886, |
| 696 | 5460, 5022, |
| 697 | 4342, 4068, |
| 698 | 3062, 2916, |
| 699 | |
| 700 | 3618, 3566, |
| 701 | 5072, 5056, |
| 702 | 5390, 5182, |
| 703 | 4248, 4133, |
| 704 | 2971, 2922, |
| 705 | |
| 706 | 3074, 3100, |
| 707 | 4282, 4352, |
| 708 | 4510, 4452, |
| 709 | 3533, 3517, |
| 710 | 2457, 2465 |
| 711 | }))); |
| 712 | |
| 713 | return DepthwiseConvolution2dNhwcTestImpl<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 714 | memoryManager, |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 715 | input, |
| 716 | kernel, |
| 717 | GetBias2<typename FullyConnectedBiasTypeForInputType<T>::Type>(biasEnabled, qScale, qOffset), |
| 718 | expectedOutput, |
| 719 | qScale, |
| 720 | qOffset, |
| 721 | 1, // Padding left. |
| 722 | 1, // Padding top. |
| 723 | 2, // Padding right. |
| 724 | 2, // Padding bottom. |
| 725 | 1, // strideX |
| 726 | 1); // strideY |
| 727 | } |
| 728 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 729 | LayerTestResult<float, 4> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 730 | Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest( |
| 731 | armnn::IWorkloadFactory& workloadFactory, |
| 732 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 733 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 734 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 735 | return Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon<float>( |
| 736 | workloadFactory, memoryManager, layout, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 737 | } |
| 738 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 739 | LayerTestResult<float, 4> Convolution2dAsymmetricPaddingTest( |
| 740 | armnn::IWorkloadFactory& workloadFactory, |
| 741 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 742 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 743 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 744 | return SimpleConvolution2dAsymmetricPaddingTestCommon<float>( |
| 745 | workloadFactory, memoryManager, layout, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 746 | } |
| 747 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 748 | LayerTestResult<float, 4> DepthwiseConvolution2dTest( |
| 749 | armnn::IWorkloadFactory& workloadFactory, |
| 750 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 751 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 752 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 753 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 754 | return DepthwiseConvolution2dTestImpl<float, float>( |
| 755 | workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 756 | } |
| 757 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 758 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthNhwcTest( |
| 759 | armnn::IWorkloadFactory& workloadFactory, |
| 760 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 761 | bool biasEnabled) |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 762 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 763 | return DepthwiseConvolution2dNhwcTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0, biasEnabled); |
Nikhil Raj | cec6b65 | 2018-10-12 13:51:57 +0100 | [diff] [blame] | 764 | } |
| 765 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 766 | LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul1Test( |
| 767 | armnn::IWorkloadFactory& workloadFactory, |
| 768 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 769 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 770 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 771 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 772 | return DepthwiseConvolution2dDepthMul1TestImpl<float, float>( |
| 773 | workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 774 | } |
| 775 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 776 | LayerTestResult<float, 4> DepthwiseConvolution2dAsymmetricTest( |
| 777 | armnn::IWorkloadFactory& workloadFactory, |
| 778 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 779 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 780 | const armnn::DataLayout layout) |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 781 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 782 | return DepthwiseConvolution2dAsymmetricTestCommon<float>( |
| 783 | workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 784 | } |
| 785 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 786 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dUint8Test( |
| 787 | armnn::IWorkloadFactory& workloadFactory, |
| 788 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 789 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 790 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 791 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 792 | return DepthwiseConvolution2dTestImpl<uint8_t, int32_t>( |
| 793 | workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 794 | } |
| 795 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 796 | LayerTestResult<uint8_t, 4> DepthwiseConvolution2dDepthMul1Uint8Test( |
| 797 | armnn::IWorkloadFactory& workloadFactory, |
| 798 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 799 | bool biasEnabled, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 800 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 801 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 802 | return DepthwiseConvolution2dDepthMul1TestImpl<uint8_t, int32_t>( |
| 803 | workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 804 | } |
| 805 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 806 | LayerTestResult<float, 4> Convolution1dTest( |
| 807 | armnn::IWorkloadFactory& workloadFactory, |
| 808 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 809 | bool biasEnabled) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 810 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 811 | return Convolution1dTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0, biasEnabled); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 812 | } |
| 813 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 814 | LayerTestResult<uint8_t, 4> Convolution1dUint8Test( |
| 815 | armnn::IWorkloadFactory& workloadFactory, |
| 816 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 817 | bool biasEnabled) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 818 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 819 | return Convolution1dTestImpl<uint8_t>(workloadFactory, memoryManager, 0.1f, 128, biasEnabled); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 820 | } |
| 821 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 822 | LayerTestResult<float,4> CompareConvolution2dTest( |
| 823 | armnn::IWorkloadFactory& workloadFactory, |
| 824 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 825 | armnn::IWorkloadFactory& refWorkloadFactory) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 826 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 827 | return CompareConvolution2dTestImpl<float>(workloadFactory, memoryManager, refWorkloadFactory); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 828 | } |
| 829 | |
| 830 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 831 | LayerTestResult<T,4> CompareDepthwiseConvolution2dTest( |
| 832 | armnn::IWorkloadFactory& workloadFactory, |
| 833 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 834 | armnn::IWorkloadFactory& refWorkloadFactory, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 835 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 836 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 837 | return CompareDepthwiseConvolution2dTestImpl<T>(workloadFactory, memoryManager, refWorkloadFactory, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 838 | } |
| 839 | |
| 840 | template LayerTestResult<float, 4> CompareDepthwiseConvolution2dTest<float>( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 841 | armnn::IWorkloadFactory&, |
| 842 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
| 843 | armnn::IWorkloadFactory&, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 844 | const armnn::DataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 845 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 846 | template LayerTestResult<uint8_t, 4> CompareDepthwiseConvolution2dTest<uint8_t>( |
| 847 | armnn::IWorkloadFactory&, |
| 848 | const armnn::IBackendInternal::IMemoryManagerSharedPtr&, |
| 849 | armnn::IWorkloadFactory&, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 850 | const armnn::DataLayout); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 851 | |
| 852 | LayerTestResult<float,4> SimpleNormalizationAcrossTest( |
| 853 | armnn::IWorkloadFactory& workloadFactory, |
| 854 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 855 | { |
| 856 | auto normMethod = armnn::NormalizationAlgorithmMethod::LocalBrightness; |
| 857 | auto normChannel = armnn::NormalizationAlgorithmChannel::Across; |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 858 | return SimpleNormalizationTestImpl(workloadFactory, memoryManager, normChannel, normMethod); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 859 | } |
| 860 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 861 | LayerTestResult<float,4> SimpleNormalizationWithinTest( |
| 862 | armnn::IWorkloadFactory& workloadFactory, |
| 863 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 864 | { |
| 865 | auto normMethod = armnn::NormalizationAlgorithmMethod::LocalBrightness; |
| 866 | auto normChannel = armnn::NormalizationAlgorithmChannel::Within; |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 867 | return SimpleNormalizationTestImpl(workloadFactory, memoryManager, normChannel, normMethod); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 868 | } |
| 869 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 870 | LayerTestResult<float,4> SimpleNormalizationAcrossNhwcTest( |
| 871 | armnn::IWorkloadFactory& workloadFactory, |
| 872 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 55a97bc | 2018-10-02 14:35:53 +0100 | [diff] [blame] | 873 | { |
| 874 | auto normMethod = armnn::NormalizationAlgorithmMethod::LocalBrightness; |
| 875 | auto normChannel = armnn::NormalizationAlgorithmChannel::Across; |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 876 | return SimpleNormalizationNhwcTestImpl(workloadFactory, memoryManager, normChannel, normMethod); |
narpra01 | 55a97bc | 2018-10-02 14:35:53 +0100 | [diff] [blame] | 877 | } |
| 878 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 879 | LayerTestResult<float,2> SimpleSoftmaxTest( |
| 880 | armnn::IWorkloadFactory& workloadFactory, |
| 881 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 882 | float beta) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 883 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 884 | return SimpleSoftmaxTestImpl<float>(workloadFactory, memoryManager, beta); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 885 | } |
| 886 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 887 | LayerTestResult<uint8_t,2> SimpleSoftmaxUint8Test( |
| 888 | armnn::IWorkloadFactory& workloadFactory, |
| 889 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 890 | float beta) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 891 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 892 | return SimpleSoftmaxTestImpl<uint8_t>(workloadFactory, memoryManager, beta); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 893 | } |
| 894 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 895 | LayerTestResult<float,4> CompareNormalizationTest( |
| 896 | armnn::IWorkloadFactory& workloadFactory, |
| 897 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 898 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 899 | armnn::NormalizationAlgorithmChannel normChannel, |
| 900 | armnn::NormalizationAlgorithmMethod normMethod) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 901 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 902 | return CompareNormalizationTestImpl(workloadFactory, memoryManager, refWorkloadFactory, normChannel, normMethod); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 903 | } |
| 904 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 905 | LayerTestResult<float,2> CompareSoftmaxTest( |
| 906 | armnn::IWorkloadFactory& workloadFactory, |
| 907 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 908 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 909 | float beta) |
| 910 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 911 | return CompareSoftmaxTestImpl<float>(workloadFactory, memoryManager, refWorkloadFactory, beta); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 912 | } |
| 913 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 914 | LayerTestResult<uint8_t,2> CompareSoftmaxUint8Test( |
| 915 | armnn::IWorkloadFactory& workloadFactory, |
| 916 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 917 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 918 | float beta) |
| 919 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 920 | return CompareSoftmaxTestImpl<uint8_t>(workloadFactory, memoryManager, refWorkloadFactory, beta); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 921 | } |
| 922 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 923 | std::vector<LayerTestResult<float,3>> SplitterTest( |
| 924 | armnn::IWorkloadFactory& workloadFactory, |
| 925 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 926 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 927 | return SplitterTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 928 | } |
| 929 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 930 | std::vector<LayerTestResult<uint8_t,3>> SplitterUint8Test( |
| 931 | armnn::IWorkloadFactory& workloadFactory, |
| 932 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 933 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 934 | return SplitterTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 935 | } |
| 936 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 937 | LayerTestResult<float, 3> CopyViaSplitterTest( |
| 938 | armnn::IWorkloadFactory& workloadFactory, |
| 939 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 940 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 941 | return CopyViaSplitterTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 942 | } |
| 943 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 944 | LayerTestResult<uint8_t, 3> CopyViaSplitterUint8Test( |
| 945 | armnn::IWorkloadFactory& workloadFactory, |
| 946 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 947 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 948 | return CopyViaSplitterTestImpl<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 949 | } |
| 950 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 951 | LayerTestResult<float, 2> LstmLayerFloat32WithCifgWithPeepholeNoProjectionTest( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 952 | armnn::IWorkloadFactory& workloadFactory, |
| 953 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 954 | { |
| 955 | armnn::TensorInfo inputDesc({ 2, 2 }, armnn::GetDataType<float>()); |
| 956 | boost::multi_array<float, 2> input = MakeTensor<float, 2>(inputDesc, std::vector<float>( |
| 957 | { 2., 3., 3., 4. })); |
| 958 | |
| 959 | armnn::TensorInfo outputDesc({ 2, 4 }, armnn::GetDataType<float>()); |
| 960 | boost::multi_array<float, 2> expectedOutput = MakeTensor<float, 2>(outputDesc, std::vector<float>( |
| 961 | {-0.36444446f, -0.00352185f, 0.12886585f, -0.05163646f, |
| 962 | -0.42734814f, -0.00478661f, 0.13455015f, -0.03560682f})); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 963 | return LstmLayerWithCifgWithPeepholeNoProjectionTestImpl( |
| 964 | workloadFactory, memoryManager, input, expectedOutput); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 965 | } |
| 966 | |
| 967 | LayerTestResult<float, 2> LstmLayerFloat32NoCifgWithPeepholeWithProjectionTest( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 968 | armnn::IWorkloadFactory& workloadFactory, |
| 969 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 970 | { |
| 971 | armnn::TensorInfo inputDesc({ 2, 5 }, armnn::GetDataType<float>()); |
| 972 | boost::multi_array<float, 2> input = MakeTensor<float, 2>(inputDesc, std::vector<float>( |
| 973 | {0.787926f, 0.151646f, 0.071352f, 0.118426f, 0.458058f, |
| 974 | 0.295743f, 0.544053f, 0.690064f, 0.858138f, 0.497181f})); |
| 975 | |
| 976 | armnn::TensorInfo outputDesc({ 2, 16 }, armnn::GetDataType<float>()); |
| 977 | boost::multi_array<float, 2> expectedOutput = MakeTensor<float, 2>(outputDesc, std::vector<float>( |
| 978 | {-0.00396806f, 0.029352f, -0.00279226f, 0.0159977f, -0.00835576f, |
| 979 | -0.0211779f, 0.0283512f, -0.0114597f, 0.00907307f, -0.0244004f, |
| 980 | -0.0152191f, -0.0259063f, 0.00914318f, 0.00415118f, 0.017147f, |
| 981 | 0.0134203f, -0.013869f, 0.0287268f, -0.00334693f, 0.00733398f, -0.0287926f, |
| 982 | -0.0186926f, 0.0193662f, -0.0115437f, 0.00422612f, -0.0345232f, |
| 983 | 0.00223253f, -0.00957321f, 0.0210624f, 0.013331f, 0.0150954f, |
| 984 | 0.02168f})); |
Matteo Martincigh | a65b7ae | 2018-11-14 12:39:55 +0000 | [diff] [blame] | 985 | return LstmLayerNoCifgWithPeepholeWithProjectionTestImpl(workloadFactory, memoryManager, input, expectedOutput); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 986 | } |
| 987 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 988 | LayerTestResult<float, 2> LstmLayerFloat32NoCifgNoPeepholeNoProjectionTest( |
| 989 | armnn::IWorkloadFactory& workloadFactory, |
| 990 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 991 | { |
| 992 | armnn::TensorInfo inputDesc({2, 2}, armnn::GetDataType<float>()); |
| 993 | boost::multi_array<float, 2> input = MakeTensor<float, 2>(inputDesc, std::vector<float>( |
| 994 | {2., 3., 3., 4.})); |
| 995 | |
| 996 | |
| 997 | armnn::TensorInfo outputDesc({2, 4}, armnn::GetDataType<float>()); |
| 998 | boost::multi_array<float, 2> expectedOutput = MakeTensor<float, 2>(outputDesc, std::vector<float>( |
| 999 | {{-0.02973187f, 0.1229473f, 0.20885126f, -0.15358765f, |
| 1000 | -0.0185422f, 0.11281417f, 0.24466537f, -0.1826292f}})); |
| 1001 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1002 | return LstmNoCifgNoPeepholeNoProjectionTestImpl( |
| 1003 | workloadFactory, memoryManager, input, expectedOutput); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1004 | } |
| 1005 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1006 | LayerTestResult<float,3> MergerTest( |
| 1007 | armnn::IWorkloadFactory& workloadFactory, |
| 1008 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1009 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1010 | unsigned int outputWidth = 3; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1011 | unsigned int outputHeight = 6; |
| 1012 | unsigned int outputChannels = 3; |
| 1013 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1014 | unsigned int inputWidth1 = 3; |
| 1015 | unsigned int inputHeight1 = 6; |
| 1016 | unsigned int inputChannels1 = 2; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1017 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1018 | unsigned int inputWidth2 = 3; |
| 1019 | unsigned int inputHeight2 = 6; |
| 1020 | unsigned int inputChannels2 = 1; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1021 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1022 | // Define the tensor descriptors. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1023 | armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::Float32); |
| 1024 | armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::Float32); |
| 1025 | armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::Float32); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1026 | |
| 1027 | LayerTestResult<float,3> ret(outputTensorInfo); |
| 1028 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1029 | ret.outputExpected = MakeTensor<float, 3>(outputTensorInfo, std::vector<float>( |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1030 | { |
| 1031 | 1.0f, 2.0f, 3.0f, |
| 1032 | 4.0f, 5.0f, 6.0f, |
| 1033 | 7.0f, 8.0f, 9.0f, |
| 1034 | 10.0f, 11.0f, 12.0f, |
| 1035 | 13.0f, 14.0f, 15.0f, |
| 1036 | 16.0f, 17.0f, 18.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1037 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1038 | 19.0f, 20.0f, 21.0f, |
| 1039 | 22.0f, 23.0f, 24.0f, |
| 1040 | 25.0f, 26.0f, 27.0f, |
| 1041 | 28.0f, 29.0f, 30.0f, |
| 1042 | 31.0f, 32.0f, 33.0f, |
| 1043 | 34.0f, 35.0f, 36.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1044 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1045 | 37.0f, 38.0f, 39.0f, |
| 1046 | 40.0f, 41.0f, 42.0f, |
| 1047 | 43.0f, 44.0f, 45.0f, |
| 1048 | 46.0f, 47.0f, 48.0f, |
| 1049 | 49.0f, 50.0f, 51.0f, |
| 1050 | 52.0f, 53.0f, 54.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1051 | }) |
| 1052 | ); |
| 1053 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1054 | auto input1 = MakeTensor<float, 3>(inputTensorInfo1, std::vector<float>( |
| 1055 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1056 | 1.0f, 2.0f, 3.0f, |
| 1057 | 4.0f, 5.0f, 6.0f, |
| 1058 | 7.0f, 8.0f, 9.0f, |
| 1059 | 10.0f, 11.0f, 12.0f, |
| 1060 | 13.0f, 14.0f, 15.0f, |
| 1061 | 16.0f, 17.0f, 18.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1062 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1063 | 19.0f, 20.0f, 21.0f, |
| 1064 | 22.0f, 23.0f, 24.0f, |
| 1065 | 25.0f, 26.0f, 27.0f, |
| 1066 | 28.0f, 29.0f, 30.0f, |
| 1067 | 31.0f, 32.0f, 33.0f, |
| 1068 | 34.0f, 35.0f, 36.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1069 | }) |
| 1070 | ); |
| 1071 | |
| 1072 | auto input2 = MakeTensor<float, 3>(inputTensorInfo2, std::vector<float>( |
| 1073 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1074 | 37.0f, 38.0f, 39.0f, |
| 1075 | 40.0f, 41.0f, 42.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1076 | 43.0f, 44.0f, 45.0f, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 1077 | 46.0f, 47.0f, 48.0f, |
| 1078 | 49.0f, 50.0f, 51.0f, |
| 1079 | 52.0f, 53.0f, 54.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1080 | }) |
| 1081 | ); |
| 1082 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1083 | 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] | 1084 | armnn::MergerQueueDescriptor::ViewOrigin window1(wOrigin1); |
| 1085 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1086 | 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] | 1087 | armnn::MergerQueueDescriptor::ViewOrigin window2(wOrigin2); |
| 1088 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1089 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1090 | |
| 1091 | bool subTensorsSupported = workloadFactory.SupportsSubTensors(); |
| 1092 | |
| 1093 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = |
| 1094 | subTensorsSupported ? |
| 1095 | workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : |
| 1096 | workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1097 | |
| 1098 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = |
| 1099 | subTensorsSupported ? |
| 1100 | workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : |
| 1101 | workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1102 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1103 | armnn::MergerQueueDescriptor data; |
| 1104 | armnn::WorkloadInfo info; |
| 1105 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1106 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1107 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1108 | |
| 1109 | data.m_ViewOrigins.push_back(window1); |
| 1110 | data.m_ViewOrigins.push_back(window2); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1111 | |
| 1112 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMerger(data, info); |
| 1113 | |
| 1114 | inputHandle1->Allocate(); |
| 1115 | inputHandle2->Allocate(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1116 | outputHandle->Allocate(); |
| 1117 | |
| 1118 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]); |
| 1119 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1120 | |
| 1121 | workload->Execute(); |
| 1122 | |
| 1123 | CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get()); |
| 1124 | |
| 1125 | return ret; |
| 1126 | } |
| 1127 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1128 | LayerTestResult<float,4> AdditionTest( |
| 1129 | armnn::IWorkloadFactory& workloadFactory, |
| 1130 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1131 | { |
| 1132 | unsigned int batchSize = 2; |
| 1133 | unsigned int channels = 2; |
| 1134 | unsigned int height = 2; |
| 1135 | unsigned int width = 3; |
| 1136 | |
| 1137 | armnn::TensorInfo inputTensorInfo1, inputTensorInfo2; |
| 1138 | armnn::TensorInfo outputTensorInfo; |
| 1139 | |
| 1140 | unsigned int shape[] = {batchSize, channels, height, width}; |
| 1141 | |
| 1142 | inputTensorInfo1 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1143 | inputTensorInfo2 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1144 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1145 | |
| 1146 | |
| 1147 | auto input1 = MakeTensor<float, 4>(inputTensorInfo1, std::vector<float>( |
| 1148 | { |
| 1149 | 0.0f, 2.0f, 1.0f, |
| 1150 | 0.2f, 1.0f, 2.0f, |
| 1151 | |
| 1152 | 1.0f, 2.0f, 1.0f, |
| 1153 | 0.2f, 1.0f, 2.0f, |
| 1154 | |
| 1155 | 0.0f, 2.0f, 1.0f, |
| 1156 | 4.2f, 1.0f, 2.0f, |
| 1157 | |
| 1158 | 0.0f, 0.0f, 1.0f, |
| 1159 | 0.2f, 1.0f, 2.0f, |
| 1160 | })); |
| 1161 | |
| 1162 | auto input2 = MakeTensor<float, 4>(inputTensorInfo2, std::vector<float>( |
| 1163 | { |
| 1164 | 1.0f, 2.0f, 1.0f, |
| 1165 | 0.0f, 1.0f, 2.0f, |
| 1166 | |
| 1167 | 1.0f, 2.0f, -2.0f, |
| 1168 | 0.2f, 1.0f, 2.0f, |
| 1169 | |
| 1170 | 0.0f, 2.0f, 1.0f, |
| 1171 | 4.2f, 0.0f, -3.0f, |
| 1172 | |
| 1173 | 0.0f, 0.0f, 1.0f, |
| 1174 | 0.7f, 1.0f, 5.0f, |
| 1175 | })); |
| 1176 | |
| 1177 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 1178 | ret.outputExpected = MakeTensor<float, 4>(outputTensorInfo, std::vector<float>( |
| 1179 | { |
| 1180 | 1.0f, 4.0f, 2.0f, |
| 1181 | 0.2f, 2.0f, 4.0f, |
| 1182 | |
| 1183 | 2.0f, 4.0f, -1.0f, |
| 1184 | 0.4f, 2.0f, 4.0f, |
| 1185 | |
| 1186 | 0.0f, 4.0f, 2.0f, |
| 1187 | 8.4f, 1.0f, -1.0f, |
| 1188 | |
| 1189 | 0.0f, 0.0f, 2.0f, |
| 1190 | 0.9f, 2.0f, 7.0f, |
| 1191 | })); |
| 1192 | |
| 1193 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1194 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1195 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1196 | |
| 1197 | armnn::AdditionQueueDescriptor data; |
| 1198 | armnn::WorkloadInfo info; |
| 1199 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1200 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 1201 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1202 | |
| 1203 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 1204 | |
| 1205 | inputHandle1->Allocate(); |
| 1206 | inputHandle2->Allocate(); |
| 1207 | outputHandle->Allocate(); |
| 1208 | |
| 1209 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1210 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 1211 | |
| 1212 | workload->Execute(); |
| 1213 | |
| 1214 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1215 | |
| 1216 | return ret; |
| 1217 | } |
| 1218 | |
| 1219 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1220 | LayerTestResult<T, 4> AdditionBroadcastTestImpl( |
| 1221 | armnn::IWorkloadFactory& workloadFactory, |
| 1222 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1223 | float qScale, |
| 1224 | int32_t qOffset) |
| 1225 | { |
| 1226 | armnn::TensorInfo inputTensorInfo1 = armnn::TensorInfo({1, 3, 2, 1}, armnn::GetDataType<T>()); |
| 1227 | armnn::TensorInfo inputTensorInfo2 = armnn::TensorInfo({1, 1, 2, 3}, armnn::GetDataType<T>()); |
| 1228 | armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 2, 3}, armnn::GetDataType<T>()); |
| 1229 | |
| 1230 | if (armnn::IsQuantizedType<T>()) |
| 1231 | { |
| 1232 | inputTensorInfo1.SetQuantizationScale(qScale); |
| 1233 | inputTensorInfo1.SetQuantizationOffset(qOffset); |
| 1234 | inputTensorInfo2.SetQuantizationScale(qScale); |
| 1235 | inputTensorInfo2.SetQuantizationOffset(qOffset); |
| 1236 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1237 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1238 | } |
| 1239 | |
| 1240 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, |
| 1241 | { |
| 1242 | 0.0f, |
| 1243 | 1.0f, |
| 1244 | |
| 1245 | 2.0f, |
| 1246 | 3.0f, |
| 1247 | |
| 1248 | 4.0f, |
| 1249 | 5.0f, |
| 1250 | })); |
| 1251 | |
| 1252 | auto input2 = MakeTensor<T, 4>(inputTensorInfo2, QuantizedVector<T>(qScale, qOffset, |
| 1253 | { |
| 1254 | 0.5f, 1.5f, 2.5f, |
| 1255 | 3.5f, 4.5f, 5.5f, |
| 1256 | })); |
| 1257 | |
| 1258 | LayerTestResult<T,4> ret(outputTensorInfo); |
| 1259 | ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, |
| 1260 | { |
| 1261 | 0.5f, 1.5f, 2.5f, |
| 1262 | 4.5f, 5.5f, 6.5f, |
| 1263 | |
| 1264 | 2.5f, 3.5f, 4.5f, |
| 1265 | 6.5f, 7.5f, 8.5f, |
| 1266 | |
| 1267 | 4.5f, 5.5f, 6.5f, |
| 1268 | 8.5f, 9.5f, 10.5f, |
| 1269 | })); |
| 1270 | |
| 1271 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1272 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1273 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1274 | |
| 1275 | armnn::AdditionQueueDescriptor data; |
| 1276 | armnn::WorkloadInfo info; |
| 1277 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1278 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 1279 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1280 | |
| 1281 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 1282 | |
| 1283 | inputHandle1->Allocate(); |
| 1284 | inputHandle2->Allocate(); |
| 1285 | outputHandle->Allocate(); |
| 1286 | |
| 1287 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1288 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 1289 | |
| 1290 | workload->Execute(); |
| 1291 | |
| 1292 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1293 | |
| 1294 | return ret; |
| 1295 | } |
| 1296 | |
| 1297 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1298 | LayerTestResult<T, 4> AdditionBroadcast1ElementTestImpl( |
| 1299 | armnn::IWorkloadFactory& workloadFactory, |
| 1300 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1301 | float qScale, |
| 1302 | int32_t qOffset) |
| 1303 | { |
| 1304 | armnn::TensorInfo inputTensorInfo1 = armnn::TensorInfo({1, 3, 2, 3}, armnn::GetDataType<T>()); |
| 1305 | armnn::TensorInfo inputTensorInfo2 = armnn::TensorInfo({1, 1, 1, 1}, armnn::GetDataType<T>()); |
| 1306 | armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 2, 3}, armnn::GetDataType<T>()); |
| 1307 | |
| 1308 | if (armnn::IsQuantizedType<T>()) |
| 1309 | { |
| 1310 | inputTensorInfo1.SetQuantizationScale(qScale); |
| 1311 | inputTensorInfo1.SetQuantizationOffset(qOffset); |
| 1312 | inputTensorInfo2.SetQuantizationScale(qScale); |
| 1313 | inputTensorInfo2.SetQuantizationOffset(qOffset); |
| 1314 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1315 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1316 | } |
| 1317 | |
| 1318 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, |
| 1319 | { |
| 1320 | 0.0f, 1.0f, 2.0f, |
| 1321 | 3.0f, 4.0f, 5.0f, |
| 1322 | 6.0f, 7.0f, 8.0f, |
| 1323 | 9.0f, 10.0f, 11.0f, |
| 1324 | 12.0f, 13.0f, 14.0f, |
| 1325 | 15.0f, 16.0f, 17.0f, |
| 1326 | })); |
| 1327 | |
| 1328 | auto input2 = MakeTensor<T, 4>(inputTensorInfo2, QuantizedVector<T>(qScale, qOffset, |
| 1329 | { |
| 1330 | 0.5f, |
| 1331 | })); |
| 1332 | |
| 1333 | LayerTestResult<T,4> ret(outputTensorInfo); |
| 1334 | ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, |
| 1335 | { |
| 1336 | 0.5f, 1.5f, 2.5f, |
| 1337 | 3.5f, 4.5f, 5.5f, |
| 1338 | 6.5f, 7.5f, 8.5f, |
| 1339 | 9.5f, 10.5f, 11.5f, |
| 1340 | 12.5f, 13.5f, 14.5f, |
| 1341 | 15.5f, 16.5f, 17.5f, |
| 1342 | })); |
| 1343 | |
| 1344 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1345 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1346 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1347 | |
| 1348 | armnn::AdditionQueueDescriptor data; |
| 1349 | armnn::WorkloadInfo info; |
| 1350 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1351 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 1352 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1353 | |
| 1354 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 1355 | |
| 1356 | inputHandle1->Allocate(); |
| 1357 | inputHandle2->Allocate(); |
| 1358 | outputHandle->Allocate(); |
| 1359 | |
| 1360 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1361 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 1362 | |
| 1363 | workload->Execute(); |
| 1364 | |
| 1365 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1366 | |
| 1367 | return ret; |
| 1368 | } |
| 1369 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1370 | LayerTestResult<float, 4> AdditionBroadcastTest( |
| 1371 | armnn::IWorkloadFactory& workloadFactory, |
| 1372 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1373 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1374 | return AdditionBroadcastTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1375 | } |
| 1376 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1377 | LayerTestResult<uint8_t, 4> AdditionBroadcastUint8Test( |
| 1378 | armnn::IWorkloadFactory& workloadFactory, |
| 1379 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1380 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1381 | return AdditionBroadcastTestImpl<uint8_t>(workloadFactory, memoryManager, 2.f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1382 | } |
| 1383 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1384 | LayerTestResult<float, 4> AdditionBroadcast1ElementTest( |
| 1385 | armnn::IWorkloadFactory& workloadFactory, |
| 1386 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1387 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1388 | return AdditionBroadcast1ElementTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1389 | } |
| 1390 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1391 | LayerTestResult<uint8_t, 4> AdditionBroadcast1ElementUint8Test( |
| 1392 | armnn::IWorkloadFactory& workloadFactory, |
| 1393 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1394 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1395 | return AdditionBroadcast1ElementTestImpl<uint8_t>(workloadFactory, memoryManager, 0.1333333f, 128); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1396 | } |
| 1397 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1398 | LayerTestResult<float,4> CompareAdditionTest( |
| 1399 | armnn::IWorkloadFactory& workloadFactory, |
| 1400 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1401 | armnn::IWorkloadFactory& refWorkloadFactory) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1402 | { |
| 1403 | unsigned int batchSize = 4; |
| 1404 | unsigned int channels = 1; |
| 1405 | unsigned int height = 2; |
| 1406 | unsigned int width = 3; |
| 1407 | |
| 1408 | armnn::TensorInfo inputTensorInfo1, inputTensorInfo2; |
| 1409 | armnn::TensorInfo outputTensorInfo; |
| 1410 | |
| 1411 | unsigned int shape[] = {batchSize, channels, height, width}; |
| 1412 | |
| 1413 | inputTensorInfo1 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1414 | inputTensorInfo2 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1415 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 1416 | |
| 1417 | auto input1 = MakeRandomTensor<float, 4>(inputTensorInfo1, 1232); |
| 1418 | auto input2 = MakeRandomTensor<float, 4>(inputTensorInfo2, 456); |
| 1419 | |
| 1420 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 1421 | |
| 1422 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1423 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1424 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1425 | |
| 1426 | std::unique_ptr<armnn::ITensorHandle> inputHandle1Ref = refWorkloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1427 | std::unique_ptr<armnn::ITensorHandle> inputHandle2Ref = refWorkloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 1428 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1429 | |
| 1430 | armnn::AdditionQueueDescriptor data; |
| 1431 | armnn::WorkloadInfo info; |
| 1432 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1433 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 1434 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1435 | |
| 1436 | armnn::AdditionQueueDescriptor refData = data; |
| 1437 | armnn::WorkloadInfo refInfo = info; |
| 1438 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo1, inputHandle1Ref.get()); |
| 1439 | SetWorkloadInput(refData, refInfo, 1, inputTensorInfo2, inputHandle2Ref.get()); |
| 1440 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 1441 | |
| 1442 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 1443 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateAddition(refData, refInfo); |
| 1444 | |
| 1445 | inputHandle1->Allocate(); |
| 1446 | inputHandle2->Allocate(); |
| 1447 | outputHandle->Allocate(); |
| 1448 | inputHandle1Ref->Allocate(); |
| 1449 | inputHandle2Ref->Allocate(); |
| 1450 | outputHandleRef->Allocate(); |
| 1451 | |
| 1452 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1453 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 1454 | CopyDataToITensorHandle(inputHandle1Ref.get(), &input1[0][0][0][0]); |
| 1455 | CopyDataToITensorHandle(inputHandle2Ref.get(), &input2[0][0][0][0]); |
| 1456 | |
| 1457 | workload->Execute(); |
| 1458 | workloadRef->Execute(); |
| 1459 | |
| 1460 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1461 | CopyDataFromITensorHandle(&ret.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 1462 | |
| 1463 | return ret; |
| 1464 | } |
| 1465 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 1466 | namespace { |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1467 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1468 | LayerTestResult<T, 4> DivisionTestHelper( |
| 1469 | armnn::IWorkloadFactory& workloadFactory, |
| 1470 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 1471 | const unsigned int shape0[4], |
| 1472 | const std::vector<T>& values0, |
| 1473 | float scale0, |
| 1474 | int32_t offset0, |
| 1475 | const unsigned int shape1[4], |
| 1476 | const std::vector<T> & values1, |
| 1477 | float scale1, |
| 1478 | int32_t offset1, |
| 1479 | const unsigned int outShape[4], |
| 1480 | const std::vector<T> & outValues, |
| 1481 | float outScale, |
| 1482 | int32_t outOffset) |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1483 | { |
| 1484 | auto dataType = (std::is_same<T, uint8_t>::value ? |
| 1485 | armnn::DataType::QuantisedAsymm8 : |
| 1486 | armnn::DataType::Float32); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1487 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1488 | armnn::TensorInfo inputTensorInfo0(4, shape0, dataType); |
| 1489 | armnn::TensorInfo inputTensorInfo1(4, shape1, dataType); |
| 1490 | armnn::TensorInfo outputTensorInfo(4, outShape, dataType); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1491 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1492 | inputTensorInfo0.SetQuantizationScale(scale0); |
| 1493 | inputTensorInfo0.SetQuantizationOffset(offset0); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1494 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1495 | inputTensorInfo1.SetQuantizationScale(scale1); |
| 1496 | inputTensorInfo1.SetQuantizationOffset(offset1); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1497 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1498 | outputTensorInfo.SetQuantizationScale(outScale); |
| 1499 | outputTensorInfo.SetQuantizationOffset(outOffset); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1500 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1501 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, values0); |
| 1502 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, values1); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1503 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1504 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 1505 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, outValues); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1506 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1507 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 1508 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1509 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1510 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1511 | armnn::DivisionQueueDescriptor data; |
| 1512 | armnn::WorkloadInfo info; |
| 1513 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 1514 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1515 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1516 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1517 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDivision(data, info); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1518 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1519 | inputHandle0->Allocate(); |
| 1520 | inputHandle1->Allocate(); |
| 1521 | outputHandle->Allocate(); |
| 1522 | |
| 1523 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 1524 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1525 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1526 | workload->Execute(); |
| 1527 | |
| 1528 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 1529 | |
| 1530 | return result; |
| 1531 | } |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1532 | } // anonymous namespace |
| 1533 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1534 | LayerTestResult<float,4> DivisionByZeroTest( |
| 1535 | armnn::IWorkloadFactory& workloadFactory, |
| 1536 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Francis Murtagh | 8c5e3dc | 2018-08-30 17:18:37 +0100 | [diff] [blame] | 1537 | { |
| 1538 | const unsigned int width = 2; |
| 1539 | const unsigned int height = 2; |
| 1540 | const unsigned int channelCount = 2; |
| 1541 | const unsigned int batchSize = 2; |
| 1542 | |
| 1543 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1544 | |
| 1545 | std::vector<float> input0({ |
| 1546 | 1.f, 1.f, 1.f, 1.f, 0.f, 0.f, 0.f, 0.f, |
| 1547 | -1.f, -1.f, -1.f, -1.f, 5.f, 5.f, 5.f, 5.f }); |
| 1548 | |
| 1549 | std::vector<float> input1({ |
| 1550 | 0.f, 0.f, -0.f, -0.f, 0.f, 0.f, -0.f, -0.f, |
| 1551 | 0.f, 0.f, -0.f, -0.f, 5.f, 5.f, 5.f, 5.f }); |
| 1552 | |
| 1553 | std::vector<float> output({ |
| 1554 | INFINITY, INFINITY, -INFINITY, -INFINITY, NAN, NAN, -NAN, -NAN, |
| 1555 | -INFINITY, -INFINITY, INFINITY, INFINITY, 1, 1, 1, 1 }); |
| 1556 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1557 | return DivisionTestHelper<float>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1558 | memoryManager, |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1559 | shape, input0, 1.0f, 0, |
| 1560 | shape, input1, 1.0f, 0, |
| 1561 | shape, output, 1.0f, 0); |
Francis Murtagh | 8c5e3dc | 2018-08-30 17:18:37 +0100 | [diff] [blame] | 1562 | } |
| 1563 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1564 | LayerTestResult<float,4> DivisionTest( |
| 1565 | armnn::IWorkloadFactory& workloadFactory, |
| 1566 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1567 | { |
| 1568 | const unsigned int width = 2; |
| 1569 | const unsigned int height = 2; |
| 1570 | const unsigned int channelCount = 2; |
| 1571 | const unsigned int batchSize = 2; |
| 1572 | |
| 1573 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1574 | |
| 1575 | std::vector<float> input0({ |
| 1576 | 2, 2, 2, 2, 3, 3, 3, 3, |
| 1577 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 1578 | |
| 1579 | std::vector<float> input1({ |
| 1580 | 1, 1, 1, 1, 2, 2, 2, 2, |
| 1581 | 4, 4, 4, 4, 4, 4, 4, 4 }); |
| 1582 | |
| 1583 | std::vector<float> output({ |
| 1584 | 2, 2, 2, 2, 1.5, 1.5, 1.5, 1.5, |
| 1585 | 1, 1, 1, 1, 1.25, 1.25, 1.25, 1.25 }); |
| 1586 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1587 | |
| 1588 | return DivisionTestHelper<float>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1589 | memoryManager, |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1590 | shape, input0, 1.0f, 0, |
| 1591 | shape, input1, 1.0f, 0, |
| 1592 | shape, output, 1.0f, 0); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1593 | } |
| 1594 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1595 | LayerTestResult<float, 4> DivisionBroadcast1ElementTest( |
| 1596 | armnn::IWorkloadFactory& workloadFactory, |
| 1597 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1598 | { |
| 1599 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 1600 | std::vector<float> input0({ 2, 4, 6, 8, 10, 12, 14, 16}); |
| 1601 | |
| 1602 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1603 | std::vector<float> input1({ 2 }); |
| 1604 | |
| 1605 | std::vector<float> output({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 1606 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1607 | |
| 1608 | return DivisionTestHelper<float>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1609 | memoryManager, |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1610 | shape0, input0, 1.0f, 0, |
| 1611 | shape1, input1, 1.0f, 0, |
| 1612 | shape0, output, 1.0f, 0); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1613 | } |
| 1614 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1615 | LayerTestResult<float, 4> DivisionBroadcast1DVectorTest( |
| 1616 | armnn::IWorkloadFactory& workloadFactory, |
| 1617 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1618 | { |
| 1619 | unsigned int shape0[] = { 1, 3, 3, 2 }; |
| 1620 | std::vector<float> input0({ |
| 1621 | 1, 4, 3, 8, 5, 12, |
| 1622 | 7, 16, 9, 20, 11, 24, |
| 1623 | 13, 28, 15, 32, 17, 36}); |
| 1624 | |
| 1625 | unsigned int shape1[] = { 1, 1, 1, 2 }; |
| 1626 | std::vector<float> input1({ 1, 2 }); |
| 1627 | |
| 1628 | std::vector<float> output({ |
| 1629 | 1, 2, 3, 4, 5, 6, |
| 1630 | 7, 8, 9, 10, 11, 12, |
| 1631 | 13, 14, 15, 16, 17, 18}); |
| 1632 | |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1633 | return DivisionTestHelper<float>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1634 | memoryManager, |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1635 | shape0, input0, 1.0f, 0, |
| 1636 | shape1, input1, 1.0f, 0, |
| 1637 | shape0, output, 1.0f, 0); |
| 1638 | } |
| 1639 | |
| 1640 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1641 | LayerTestResult<uint8_t,4> DivisionUint8Test( |
| 1642 | armnn::IWorkloadFactory& workloadFactory, |
| 1643 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1644 | { |
| 1645 | const unsigned int width = 2; |
| 1646 | const unsigned int height = 2; |
| 1647 | const unsigned int channelCount = 2; |
| 1648 | const unsigned int batchSize = 2; |
| 1649 | |
| 1650 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1651 | |
| 1652 | std::vector<uint8_t> input0({2, 2, 2, 2, 3, 3, 3, 3, |
| 1653 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 1654 | |
| 1655 | std::vector<uint8_t> input1({1, 1, 1, 1, 2, 2, 2, 2, |
| 1656 | 4, 4, 4, 4, 4, 4, 4, 4 }); |
| 1657 | |
| 1658 | std::vector<uint8_t> output({8, 8, 8, 8, 6, 6, 6, 6, |
| 1659 | 4, 4, 4, 4, 5, 5, 5, 5}); |
| 1660 | |
| 1661 | |
| 1662 | return DivisionTestHelper<uint8_t>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1663 | memoryManager, |
| 1664 | shape, input0, 1.0f, 0, |
| 1665 | shape, input1, 1.0f, 0, |
| 1666 | shape, output, 0.25f, 0); |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1667 | } |
| 1668 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1669 | LayerTestResult<uint8_t, 4> DivisionBroadcast1ElementUint8Test( |
| 1670 | armnn::IWorkloadFactory& workloadFactory, |
| 1671 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1672 | { |
| 1673 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 1674 | std::vector<uint8_t> input0({ 2, 4, 6, 8, 10, 12, 14, 16}); |
| 1675 | |
| 1676 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1677 | std::vector<uint8_t> input1({ 2 }); |
| 1678 | |
| 1679 | std::vector<uint8_t> output({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 1680 | |
| 1681 | return DivisionTestHelper<uint8_t>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1682 | memoryManager, |
| 1683 | shape0, input0, 1.0f, 0, |
| 1684 | shape1, input1, 1.0f, 0, |
| 1685 | shape0, output, 1.0f, 0); |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1686 | } |
| 1687 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1688 | LayerTestResult<uint8_t, 4> DivisionBroadcast1DVectorUint8Test( |
| 1689 | armnn::IWorkloadFactory& workloadFactory, |
| 1690 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | 5cd01f3 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1691 | { |
| 1692 | unsigned int shape0[] = { 1, 3, 3, 2 }; |
| 1693 | std::vector<uint8_t> input0({1, 4, 3, 8, 5, 12, |
| 1694 | 7, 16, 9, 20, 11, 24, |
| 1695 | 13, 28, 15, 32, 17, 36}); |
| 1696 | |
| 1697 | unsigned int shape1[] = { 1, 1, 1, 2 }; |
| 1698 | std::vector<uint8_t> input1({ 1, 2 }); |
| 1699 | |
| 1700 | std::vector<uint8_t> output({1, 2, 3, 4, 5, 6, |
| 1701 | 7, 8, 9, 10, 11, 12, |
| 1702 | 13, 14, 15, 16, 17, 18}); |
| 1703 | |
| 1704 | return DivisionTestHelper<uint8_t>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 1705 | memoryManager, |
| 1706 | shape0, input0, 1.0f, 0, |
| 1707 | shape1, input1, 1.0f, 0, |
| 1708 | shape0, output, 1.0f, 0); |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1709 | } |
| 1710 | |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 1711 | template<typename DescriptorType> |
| 1712 | std::unique_ptr<armnn::IWorkload> CreateWorkload( |
| 1713 | const armnn::IWorkloadFactory& workloadFactory, |
| 1714 | const armnn::WorkloadInfo& info, |
| 1715 | const DescriptorType& descriptor) |
| 1716 | { |
| 1717 | return CreateWorkload(workloadFactory, info, descriptor); |
| 1718 | }; |
| 1719 | |
| 1720 | template<> |
| 1721 | std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::MaximumQueueDescriptor>( |
| 1722 | const armnn::IWorkloadFactory& workloadFactory, |
| 1723 | const armnn::WorkloadInfo& info, |
| 1724 | const armnn::MaximumQueueDescriptor& descriptor) |
| 1725 | { |
| 1726 | return workloadFactory.CreateMaximum(descriptor, info); |
| 1727 | } |
| 1728 | |
Éanna Ó Catháin | 20e5880 | 2018-12-04 10:29:06 +0000 | [diff] [blame] | 1729 | template<> |
| 1730 | std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::MinimumQueueDescriptor>( |
| 1731 | const armnn::IWorkloadFactory& workloadFactory, |
| 1732 | const armnn::WorkloadInfo& info, |
| 1733 | const armnn::MinimumQueueDescriptor& descriptor) |
| 1734 | { |
| 1735 | return workloadFactory.CreateMinimum(descriptor, info); |
| 1736 | } |
| 1737 | |
FrancisMurtagh | 30cdfca | 2018-12-18 12:57:35 +0000 | [diff] [blame] | 1738 | template<> |
| 1739 | std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::EqualQueueDescriptor>( |
| 1740 | const armnn::IWorkloadFactory& workloadFactory, |
| 1741 | const armnn::WorkloadInfo& info, |
| 1742 | const armnn::EqualQueueDescriptor& descriptor) |
| 1743 | { |
| 1744 | return workloadFactory.CreateEqual(descriptor, info); |
| 1745 | } |
| 1746 | |
FrancisMurtagh | 878f023 | 2018-12-19 10:56:15 +0000 | [diff] [blame] | 1747 | template<> |
| 1748 | std::unique_ptr<armnn::IWorkload> CreateWorkload<armnn::GreaterQueueDescriptor>( |
| 1749 | const armnn::IWorkloadFactory& workloadFactory, |
| 1750 | const armnn::WorkloadInfo& info, |
| 1751 | const armnn::GreaterQueueDescriptor& descriptor) |
| 1752 | { |
| 1753 | return workloadFactory.CreateGreater(descriptor, info); |
| 1754 | } |
| 1755 | |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 1756 | namespace { |
| 1757 | template <typename Descriptor, typename dataType> |
| 1758 | LayerTestResult<dataType, 4> ElementwiseTestHelper |
| 1759 | (armnn::IWorkloadFactory & workloadFactory, |
| 1760 | const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager, |
| 1761 | const unsigned int shape0[4], std::vector<dataType> values0, |
| 1762 | const unsigned int shape1[4], std::vector<dataType> values1, |
| 1763 | const unsigned int outShape[4], std::vector<dataType> outValues, |
| 1764 | float qScale = 0.0f, int qOffset = 0) |
| 1765 | { |
| 1766 | const size_t dimensionCount = 4; |
| 1767 | armnn::TensorInfo inputTensorInfo0{dimensionCount, shape0, armnn::GetDataType<dataType>()}; |
| 1768 | armnn::TensorInfo inputTensorInfo1{dimensionCount, shape1, armnn::GetDataType<dataType>()}; |
| 1769 | armnn::TensorInfo outputTensorInfo{dimensionCount, outShape, armnn::GetDataType<dataType>()}; |
| 1770 | |
| 1771 | auto input0 = MakeTensor<dataType, 4>(inputTensorInfo0, values0); |
| 1772 | auto input1 = MakeTensor<dataType, 4>(inputTensorInfo1, values1); |
| 1773 | |
| 1774 | if (armnn::IsQuantizedType<dataType>()) |
| 1775 | { |
| 1776 | inputTensorInfo0.SetQuantizationScale(qScale); |
| 1777 | inputTensorInfo0.SetQuantizationOffset(qOffset); |
| 1778 | |
| 1779 | inputTensorInfo1.SetQuantizationScale(qScale); |
| 1780 | inputTensorInfo1.SetQuantizationOffset(qOffset); |
| 1781 | |
| 1782 | outputTensorInfo.SetQuantizationScale(qScale); |
| 1783 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 1784 | } |
| 1785 | |
| 1786 | LayerTestResult<dataType,4> ret(outputTensorInfo); |
| 1787 | |
| 1788 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 1789 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 1790 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 1791 | |
| 1792 | Descriptor data; |
| 1793 | armnn::WorkloadInfo info; |
| 1794 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 1795 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 1796 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 1797 | auto workload = CreateWorkload<Descriptor>(workloadFactory, info, data); |
| 1798 | |
| 1799 | inputHandle0->Allocate(); |
| 1800 | inputHandle1->Allocate(); |
| 1801 | outputHandle->Allocate(); |
| 1802 | |
| 1803 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 1804 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 1805 | |
| 1806 | ExecuteWorkload(*workload, memoryManager); |
| 1807 | |
| 1808 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 1809 | |
| 1810 | ret.outputExpected = MakeTensor<dataType, 4>(outputTensorInfo, outValues); |
| 1811 | return ret; |
| 1812 | } |
| 1813 | } |
| 1814 | |
FrancisMurtagh | 30cdfca | 2018-12-18 12:57:35 +0000 | [diff] [blame] | 1815 | LayerTestResult<float, 4> EqualSimpleTest(armnn::IWorkloadFactory& workloadFactory, |
| 1816 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1817 | { |
| 1818 | const unsigned int width = 2; |
| 1819 | const unsigned int height = 2; |
| 1820 | const unsigned int channelCount = 2; |
| 1821 | const unsigned int batchSize = 2; |
| 1822 | |
| 1823 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1824 | |
| 1825 | std::vector<float> input0({ 1, 1, 1, 1, 5, 5, 5, 5, |
| 1826 | 3, 3, 3, 3, 4, 4, 4, 4 }); |
| 1827 | |
| 1828 | std::vector<float> input1({ 1, 1, 1, 1, 3, 3, 3, 3, |
| 1829 | 5, 5, 5, 5, 4, 4, 4, 4 }); |
| 1830 | |
| 1831 | std::vector<float> output({ 1, 1, 1, 1, 0, 0, 0, 0, |
| 1832 | 0, 0, 0, 0, 1, 1, 1, 1 }); |
| 1833 | |
| 1834 | return ElementwiseTestHelper<armnn::EqualQueueDescriptor, float> |
| 1835 | (workloadFactory, |
| 1836 | memoryManager, |
| 1837 | shape, |
| 1838 | input0, |
| 1839 | shape, |
| 1840 | input1, |
| 1841 | shape, |
| 1842 | output); |
| 1843 | } |
| 1844 | |
| 1845 | LayerTestResult<float, 4> EqualBroadcast1ElementTest( |
| 1846 | armnn::IWorkloadFactory& workloadFactory, |
| 1847 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1848 | { |
| 1849 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 1850 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 1851 | |
| 1852 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1853 | std::vector<float> input1({ 1 }); |
| 1854 | |
| 1855 | std::vector<float> output({ 1, 0, 0, 0, 0, 0, 0, 0}); |
| 1856 | |
| 1857 | return ElementwiseTestHelper<armnn::EqualQueueDescriptor, float> |
| 1858 | (workloadFactory, |
| 1859 | memoryManager, |
| 1860 | shape0, |
| 1861 | input0, |
| 1862 | shape1, |
| 1863 | input1, |
| 1864 | shape0, |
| 1865 | output); |
| 1866 | } |
| 1867 | |
| 1868 | LayerTestResult<float, 4> EqualBroadcast1DVectorTest( |
| 1869 | armnn::IWorkloadFactory& workloadFactory, |
| 1870 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1871 | { |
| 1872 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 1873 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 1874 | |
| 1875 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, |
| 1876 | 7, 8, 9, 10, 11, 12 }); |
| 1877 | |
| 1878 | std::vector<float> input1({ 1, 2, 3}); |
| 1879 | |
| 1880 | std::vector<float> output({ 1, 1, 1, 0, 0, 0, |
| 1881 | 0, 0, 0, 0, 0, 0 }); |
| 1882 | |
| 1883 | return ElementwiseTestHelper<armnn::EqualQueueDescriptor, float> |
| 1884 | (workloadFactory, |
| 1885 | memoryManager, |
| 1886 | shape0, |
| 1887 | input0, |
| 1888 | shape1, |
| 1889 | input1, |
| 1890 | shape0, |
| 1891 | output); |
| 1892 | } |
| 1893 | |
| 1894 | LayerTestResult<uint8_t, 4> EqualUint8Test( |
| 1895 | armnn::IWorkloadFactory& workloadFactory, |
| 1896 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1897 | { |
| 1898 | unsigned int shape[] = { 2, 2, 2, 2 }; |
| 1899 | |
| 1900 | // See dequantized values to the right. |
| 1901 | std::vector<uint8_t> input0({ 1, 1, 1, 1, 6, 6, 6, 6, |
| 1902 | 3, 3, 3, 3, 5, 5, 5, 5 }); |
| 1903 | |
| 1904 | std::vector<uint8_t> input1({ 2, 2, 2, 2, 6, 6, 6, 6, |
| 1905 | 3, 3, 3, 3, 5, 5, 5, 5 }); |
| 1906 | |
| 1907 | std::vector<uint8_t> output({ 0, 0, 0, 0, 1, 1, 1, 1, |
| 1908 | 1, 1, 1, 1, 0, 0, 0, 0 }); |
| 1909 | |
| 1910 | return ElementwiseTestHelper<armnn::EqualQueueDescriptor, uint8_t > |
| 1911 | (workloadFactory, |
| 1912 | memoryManager, |
| 1913 | shape, |
| 1914 | input0, |
| 1915 | shape, |
| 1916 | input1, |
| 1917 | shape, |
| 1918 | output, |
| 1919 | 1.0f, |
| 1920 | 0); |
| 1921 | } |
| 1922 | |
| 1923 | LayerTestResult<uint8_t, 4> EqualBroadcast1ElementUint8Test( |
| 1924 | armnn::IWorkloadFactory& workloadFactory, |
| 1925 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1926 | { |
| 1927 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 1928 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 1929 | |
| 1930 | std::vector<uint8_t> input0({ 1, 2, 3, 4, 5, 6, |
| 1931 | 7, 8, 9, 10, 11, 12 }); |
| 1932 | |
| 1933 | std::vector<uint8_t> input1({ 1 }); |
| 1934 | |
| 1935 | std::vector<uint8_t> output({ 1, 0, 0, 0, 0, 0, |
| 1936 | 0, 0, 0, 0, 0, 0 }); |
| 1937 | |
| 1938 | return ElementwiseTestHelper<armnn::EqualQueueDescriptor, uint8_t > |
| 1939 | (workloadFactory, |
| 1940 | memoryManager, |
| 1941 | shape0, |
| 1942 | input0, |
| 1943 | shape1, |
| 1944 | input1, |
| 1945 | shape0, |
| 1946 | output, |
| 1947 | 1.0f, |
| 1948 | 0); |
| 1949 | } |
| 1950 | |
| 1951 | LayerTestResult<uint8_t, 4> EqualBroadcast1DVectorUint8Test( |
| 1952 | armnn::IWorkloadFactory& workloadFactory, |
| 1953 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1954 | { |
| 1955 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 1956 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 1957 | |
| 1958 | std::vector<uint8_t> input0({ 1, 2, 3, 4, 5, 6, |
| 1959 | 7, 8, 9, 10, 11, 12 }); |
| 1960 | |
| 1961 | std::vector<uint8_t> input1({ 1, 1, 3}); |
| 1962 | |
| 1963 | std::vector<uint8_t> output({ 1, 0, 1, 0, 0, 0, |
| 1964 | 0, 0, 0, 0, 0, 0 }); |
| 1965 | |
| 1966 | return ElementwiseTestHelper<armnn::EqualQueueDescriptor, uint8_t> |
| 1967 | (workloadFactory, |
| 1968 | memoryManager, |
| 1969 | shape0, |
| 1970 | input0, |
| 1971 | shape1, |
| 1972 | input1, |
| 1973 | shape0, |
| 1974 | output, |
| 1975 | 1.0f, |
| 1976 | 0); |
| 1977 | } |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 1978 | |
FrancisMurtagh | 878f023 | 2018-12-19 10:56:15 +0000 | [diff] [blame] | 1979 | LayerTestResult<float, 4> GreaterSimpleTest(armnn::IWorkloadFactory& workloadFactory, |
| 1980 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 1981 | { |
| 1982 | const unsigned int width = 2; |
| 1983 | const unsigned int height = 2; |
| 1984 | const unsigned int channelCount = 2; |
| 1985 | const unsigned int batchSize = 2; |
| 1986 | |
| 1987 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 1988 | |
| 1989 | std::vector<float> input0({ 1, 1, 1, 1, 5, 5, 5, 5, |
| 1990 | 3, 3, 3, 3, 4, 4, 4, 4 }); |
| 1991 | |
| 1992 | std::vector<float> input1({ 1, 1, 1, 1, 3, 3, 3, 3, |
| 1993 | 5, 5, 5, 5, 4, 4, 4, 4 }); |
| 1994 | |
| 1995 | std::vector<float> output({ 0, 0, 0, 0, 1, 1, 1, 1, |
| 1996 | 0, 0, 0, 0, 0, 0, 0, 0 }); |
| 1997 | |
| 1998 | return ElementwiseTestHelper<armnn::GreaterQueueDescriptor, float> |
| 1999 | (workloadFactory, |
| 2000 | memoryManager, |
| 2001 | shape, |
| 2002 | input0, |
| 2003 | shape, |
| 2004 | input1, |
| 2005 | shape, |
| 2006 | output); |
| 2007 | } |
| 2008 | |
| 2009 | LayerTestResult<float, 4> GreaterBroadcast1ElementTest( |
| 2010 | armnn::IWorkloadFactory& workloadFactory, |
| 2011 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2012 | { |
| 2013 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 2014 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 2015 | |
| 2016 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 2017 | std::vector<float> input1({ 1 }); |
| 2018 | |
| 2019 | std::vector<float> output({ 0, 1, 1, 1, 1, 1, 1, 1}); |
| 2020 | |
| 2021 | return ElementwiseTestHelper<armnn::GreaterQueueDescriptor, float> |
| 2022 | (workloadFactory, |
| 2023 | memoryManager, |
| 2024 | shape0, |
| 2025 | input0, |
| 2026 | shape1, |
| 2027 | input1, |
| 2028 | shape0, |
| 2029 | output); |
| 2030 | } |
| 2031 | |
| 2032 | LayerTestResult<float, 4> GreaterBroadcast1DVectorTest( |
| 2033 | armnn::IWorkloadFactory& workloadFactory, |
| 2034 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2035 | { |
| 2036 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 2037 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 2038 | |
| 2039 | std::vector<float> input0({ 1, 2.9f, 2.1f, 4, 5, 6, |
| 2040 | 7, 8, 9, 10, 11, 12 }); |
| 2041 | |
| 2042 | std::vector<float> input1({ 1, 3, 2}); |
| 2043 | |
| 2044 | std::vector<float> output({ 0, 0, 1, 1, 1, 1, |
| 2045 | 1, 1, 1, 1, 1, 1 }); |
| 2046 | |
| 2047 | return ElementwiseTestHelper<armnn::GreaterQueueDescriptor, float> |
| 2048 | (workloadFactory, |
| 2049 | memoryManager, |
| 2050 | shape0, |
| 2051 | input0, |
| 2052 | shape1, |
| 2053 | input1, |
| 2054 | shape0, |
| 2055 | output); |
| 2056 | } |
| 2057 | |
| 2058 | LayerTestResult<uint8_t, 4> GreaterUint8Test( |
| 2059 | armnn::IWorkloadFactory& workloadFactory, |
| 2060 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2061 | { |
| 2062 | unsigned int shape[] = { 2, 2, 2, 2 }; |
| 2063 | |
| 2064 | // See dequantized values to the right. |
| 2065 | std::vector<uint8_t> input0({ 1, 1, 1, 1, 6, 6, 6, 6, |
| 2066 | 3, 3, 3, 3, 5, 5, 5, 5 }); |
| 2067 | |
| 2068 | std::vector<uint8_t> input1({ 2, 2, 2, 2, 6, 6, 6, 6, |
| 2069 | 2, 2, 2, 2, 5, 5, 5, 5 }); |
| 2070 | |
| 2071 | std::vector<uint8_t> output({ 0, 0, 0, 0, 0, 0, 0, 0, |
| 2072 | 1, 1, 1, 1, 0, 0, 0, 0 }); |
| 2073 | |
| 2074 | return ElementwiseTestHelper<armnn::GreaterQueueDescriptor, uint8_t > |
| 2075 | (workloadFactory, |
| 2076 | memoryManager, |
| 2077 | shape, |
| 2078 | input0, |
| 2079 | shape, |
| 2080 | input1, |
| 2081 | shape, |
| 2082 | output, |
| 2083 | 1.0f, |
| 2084 | 0); |
| 2085 | } |
| 2086 | |
| 2087 | LayerTestResult<uint8_t, 4> GreaterBroadcast1ElementUint8Test( |
| 2088 | armnn::IWorkloadFactory& workloadFactory, |
| 2089 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2090 | { |
| 2091 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 2092 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 2093 | |
| 2094 | std::vector<uint8_t> input0({ 1, 2, 3, 4, 5, 6, |
| 2095 | 7, 8, 9, 10, 11, 12 }); |
| 2096 | |
| 2097 | std::vector<uint8_t> input1({ 1 }); |
| 2098 | |
| 2099 | std::vector<uint8_t> output({ 0, 1, 1, 1, 1, 1, |
| 2100 | 1, 1, 1, 1, 1, 1 }); |
| 2101 | |
| 2102 | return ElementwiseTestHelper<armnn::GreaterQueueDescriptor, uint8_t > |
| 2103 | (workloadFactory, |
| 2104 | memoryManager, |
| 2105 | shape0, |
| 2106 | input0, |
| 2107 | shape1, |
| 2108 | input1, |
| 2109 | shape0, |
| 2110 | output, |
| 2111 | 1.0f, |
| 2112 | 0); |
| 2113 | } |
| 2114 | |
| 2115 | LayerTestResult<uint8_t, 4> GreaterBroadcast1DVectorUint8Test( |
| 2116 | armnn::IWorkloadFactory& workloadFactory, |
| 2117 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2118 | { |
| 2119 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 2120 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 2121 | |
| 2122 | std::vector<uint8_t> input0({ 1, 2, 3, 4, 5, 6, |
| 2123 | 7, 8, 9, 10, 11, 12 }); |
| 2124 | |
| 2125 | std::vector<uint8_t> input1({ 1, 1, 3}); |
| 2126 | |
| 2127 | std::vector<uint8_t> output({ 0, 1, 0, 1, 1, 1, |
| 2128 | 1, 1, 1, 1, 1, 1 }); |
| 2129 | |
| 2130 | return ElementwiseTestHelper<armnn::GreaterQueueDescriptor, uint8_t> |
| 2131 | (workloadFactory, |
| 2132 | memoryManager, |
| 2133 | shape0, |
| 2134 | input0, |
| 2135 | shape1, |
| 2136 | input1, |
| 2137 | shape0, |
| 2138 | output, |
| 2139 | 1.0f, |
| 2140 | 0); |
| 2141 | } |
| 2142 | |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 2143 | LayerTestResult<float, 4> MaximumSimpleTest(armnn::IWorkloadFactory& workloadFactory, |
| 2144 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2145 | { |
| 2146 | const unsigned int width = 2; |
| 2147 | const unsigned int height = 2; |
| 2148 | const unsigned int channelCount = 2; |
| 2149 | const unsigned int batchSize = 2; |
| 2150 | |
| 2151 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 2152 | |
| 2153 | std::vector<float> input0({ 1, 1, 1, 1, 5, 5, 5, 5, |
| 2154 | 3, 3, 3, 3, 4, 4, 4, 4 }); |
| 2155 | |
| 2156 | std::vector<float> input1({ 2, 2, 2, 2, 3, 3, 3, 3, |
| 2157 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 2158 | |
| 2159 | std::vector<float> output({ 2, 2, 2, 2, 5, 5, 5, 5, |
| 2160 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 2161 | |
| 2162 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, float> |
| 2163 | (workloadFactory, |
| 2164 | memoryManager, |
| 2165 | shape, |
| 2166 | input0, |
| 2167 | shape, |
| 2168 | input1, |
| 2169 | shape, |
| 2170 | output); |
| 2171 | } |
| 2172 | |
| 2173 | LayerTestResult<float, 4> MaximumBroadcast1ElementTest( |
| 2174 | armnn::IWorkloadFactory& workloadFactory, |
| 2175 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2176 | { |
| 2177 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 2178 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 2179 | |
| 2180 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 2181 | std::vector<float> input1({ 2 }); |
| 2182 | |
| 2183 | std::vector<float> output({ 2, 2, 3, 4, 5, 6, 7, 8}); |
| 2184 | |
| 2185 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, float> |
| 2186 | (workloadFactory, |
| 2187 | memoryManager, |
| 2188 | shape0, |
| 2189 | input0, |
| 2190 | shape1, |
| 2191 | input1, |
| 2192 | shape0, |
| 2193 | output); |
| 2194 | } |
| 2195 | |
| 2196 | LayerTestResult<float, 4> MaximumBroadcast1DVectorTest( |
| 2197 | armnn::IWorkloadFactory& workloadFactory, |
| 2198 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2199 | { |
| 2200 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 2201 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 2202 | |
| 2203 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, |
| 2204 | 7, 8, 9, 10, 11, 12 }); |
| 2205 | |
| 2206 | std::vector<float> input1({ 1, 2, 3}); |
| 2207 | |
| 2208 | std::vector<float> output({ 1, 2, 3, 4, 5, 6, |
| 2209 | 7, 8, 9, 10, 11, 12 }); |
| 2210 | |
| 2211 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, float> |
| 2212 | (workloadFactory, |
| 2213 | memoryManager, |
| 2214 | shape0, |
| 2215 | input0, |
| 2216 | shape1, |
| 2217 | input1, |
| 2218 | shape0, |
| 2219 | output); |
| 2220 | } |
| 2221 | |
| 2222 | LayerTestResult<uint8_t, 4> MaximumUint8Test( |
| 2223 | armnn::IWorkloadFactory& workloadFactory, |
| 2224 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2225 | { |
| 2226 | unsigned int shape[] = { 2, 2, 2, 2 }; |
| 2227 | |
| 2228 | // See dequantized values to the right. |
| 2229 | std::vector<uint8_t> input0({ 1, 1, 1, 1, 6, 6, 6, 6, |
| 2230 | 3, 3, 3, 3, 4, 4, 4, 4 }); |
| 2231 | |
| 2232 | std::vector<uint8_t> input1({ 2, 2, 2, 2, 3, 3, 3, 3, |
| 2233 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 2234 | |
| 2235 | std::vector<uint8_t> output({ 2, 2, 2, 2, 6, 6, 6, 6, |
| 2236 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 2237 | |
| 2238 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, uint8_t > |
| 2239 | (workloadFactory, |
| 2240 | memoryManager, |
| 2241 | shape, |
| 2242 | input0, |
| 2243 | shape, |
| 2244 | input1, |
| 2245 | shape, |
| 2246 | output, |
| 2247 | 1.0f, |
| 2248 | 0); |
| 2249 | } |
| 2250 | |
| 2251 | LayerTestResult<uint8_t, 4> MaximumBroadcast1ElementUint8Test( |
| 2252 | armnn::IWorkloadFactory& workloadFactory, |
| 2253 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2254 | { |
| 2255 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 2256 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 2257 | |
| 2258 | std::vector<uint8_t> input0({ 1, 2, 3, 4, 5, 6, |
| 2259 | 7, 8, 9, 10, 11, 12 }); |
| 2260 | |
| 2261 | std::vector<uint8_t> input1({2}); |
| 2262 | |
| 2263 | std::vector<uint8_t> output({ 2, 2, 3, 4, 5, 6, |
| 2264 | 7, 8, 9, 10, 11, 12 }); |
| 2265 | |
| 2266 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, uint8_t > |
| 2267 | (workloadFactory, |
| 2268 | memoryManager, |
| 2269 | shape0, |
| 2270 | input0, |
| 2271 | shape1, |
| 2272 | input1, |
| 2273 | shape0, |
| 2274 | output, |
| 2275 | 1.0f, |
| 2276 | 0); |
| 2277 | } |
| 2278 | |
| 2279 | LayerTestResult<uint8_t, 4> MaximumBroadcast1DVectorUint8Test( |
| 2280 | armnn::IWorkloadFactory& workloadFactory, |
| 2281 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2282 | { |
| 2283 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 2284 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 2285 | |
| 2286 | std::vector<uint8_t> input0({ 1, 2, 3, 4, 5, 6, |
| 2287 | 7, 8, 9, 10, 11, 12 }); |
| 2288 | |
| 2289 | std::vector<uint8_t> input1({ 1, 10, 3}); |
| 2290 | |
| 2291 | std::vector<uint8_t> output({ 1, 10, 3, 4, 10, 6, |
| 2292 | 7, 10, 9, 10, 11, 12 }); |
| 2293 | |
Éanna Ó Catháin | 20e5880 | 2018-12-04 10:29:06 +0000 | [diff] [blame] | 2294 | return ElementwiseTestHelper<armnn::MaximumQueueDescriptor, uint8_t> |
Éanna Ó Catháin | de70558 | 2018-12-03 13:04:22 +0000 | [diff] [blame] | 2295 | (workloadFactory, |
| 2296 | memoryManager, |
| 2297 | shape0, |
| 2298 | input0, |
| 2299 | shape1, |
| 2300 | input1, |
| 2301 | shape0, |
| 2302 | output, |
| 2303 | 1.0f, |
| 2304 | 0); |
| 2305 | } |
| 2306 | |
Éanna Ó Catháin | 20e5880 | 2018-12-04 10:29:06 +0000 | [diff] [blame] | 2307 | LayerTestResult<float, 4> MinimumBroadcast1ElementTest1( |
| 2308 | armnn::IWorkloadFactory& workloadFactory, |
| 2309 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2310 | { |
| 2311 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 2312 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 2313 | |
| 2314 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 2315 | std::vector<float> input1({ 2 }); |
| 2316 | |
| 2317 | std::vector<float> output({ 1, 2, 2, 2, 2, 2, 2, 2}); |
| 2318 | |
| 2319 | return ElementwiseTestHelper<armnn::MinimumQueueDescriptor, float>(workloadFactory, |
| 2320 | memoryManager, |
| 2321 | shape0, |
| 2322 | input0, |
| 2323 | shape1, |
| 2324 | input1, |
| 2325 | shape0, |
| 2326 | output); |
| 2327 | } |
| 2328 | |
| 2329 | |
| 2330 | LayerTestResult<float, 4> MinimumBroadcast1ElementTest2( |
| 2331 | armnn::IWorkloadFactory& workloadFactory, |
| 2332 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 2333 | { |
| 2334 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 2335 | std::vector<float> input0({ 1, 6, 3, 2, 8, 9, 1, 10}); |
| 2336 | |
| 2337 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 2338 | std::vector<float> input1({ 5 }); |
| 2339 | |
| 2340 | std::vector<float> output({ 1, 5, 3, 2, 5, 5, 1, 5}); |
| 2341 | |
| 2342 | return ElementwiseTestHelper<armnn::MinimumQueueDescriptor, float>(workloadFactory, |
| 2343 | memoryManager, |
| 2344 | shape0, |
| 2345 | input0, |
| 2346 | shape1, |
| 2347 | input1, |
| 2348 | shape0, |
| 2349 | output); |
| 2350 | } |
| 2351 | |
| 2352 | LayerTestResult<uint8_t, 4> MinimumBroadcast1DVectorUint8Test( |
| 2353 | armnn::IWorkloadFactory & workloadFactory, |
| 2354 | const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager) |
| 2355 | { |
| 2356 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 2357 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 2358 | |
| 2359 | std::vector<uint8_t> input0({ 1, 2, 3, 3, 2, 1, |
| 2360 | 7, 1, 2, 3, 4, 5 }); |
| 2361 | |
| 2362 | std::vector<uint8_t> input1({ 1, 2, 3}); |
| 2363 | |
| 2364 | std::vector<uint8_t> output({ 1, 2, 3, 1, 2, 1, |
| 2365 | 1, 1, 2, 1, 2, 3 }); |
| 2366 | |
| 2367 | return ElementwiseTestHelper<armnn::MinimumQueueDescriptor, uint8_t>(workloadFactory, |
| 2368 | memoryManager, |
| 2369 | shape0, |
| 2370 | input0, |
| 2371 | shape1, |
| 2372 | input1, |
| 2373 | shape0, |
| 2374 | output, |
| 2375 | 1.0f, |
| 2376 | 0); |
| 2377 | } |
| 2378 | |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 2379 | namespace { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2380 | LayerTestResult<float,4> MultiplicationTestHelper( |
| 2381 | armnn::IWorkloadFactory& workloadFactory, |
| 2382 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2383 | const unsigned int shape0[4], |
| 2384 | const std::vector<float> & values0, |
| 2385 | const unsigned int shape1[4], |
| 2386 | const std::vector<float> & values1, |
| 2387 | const unsigned int outShape[4], |
| 2388 | const std::vector<float> & outValues) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2389 | { |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2390 | const size_t dimensionCount = 4; |
| 2391 | armnn::TensorInfo inputTensorInfo0{dimensionCount, shape0, armnn::DataType::Float32}; |
| 2392 | armnn::TensorInfo inputTensorInfo1{dimensionCount, shape1, armnn::DataType::Float32}; |
| 2393 | armnn::TensorInfo outputTensorInfo{dimensionCount, outShape, armnn::DataType::Float32}; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2394 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2395 | auto input0 = MakeTensor<float, 4>(inputTensorInfo0, values0); |
| 2396 | auto input1 = MakeTensor<float, 4>(inputTensorInfo1, values1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2397 | |
| 2398 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 2399 | |
| 2400 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 2401 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 2402 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2403 | |
| 2404 | armnn::MultiplicationQueueDescriptor data; |
| 2405 | armnn::WorkloadInfo info; |
| 2406 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 2407 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 2408 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2409 | |
| 2410 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMultiplication(data, info); |
| 2411 | |
| 2412 | inputHandle0->Allocate(); |
| 2413 | inputHandle1->Allocate(); |
| 2414 | outputHandle->Allocate(); |
| 2415 | |
| 2416 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 2417 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 2418 | |
| 2419 | workload->Execute(); |
| 2420 | |
| 2421 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 2422 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2423 | ret.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outValues); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2424 | return ret; |
| 2425 | } |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2426 | } // anonymous namespace |
| 2427 | |
| 2428 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2429 | LayerTestResult<float,4> MultiplicationTest( |
| 2430 | armnn::IWorkloadFactory& workloadFactory, |
| 2431 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2432 | { |
| 2433 | const unsigned int width = 2; |
| 2434 | const unsigned int height = 2; |
| 2435 | const unsigned int channelCount = 2; |
| 2436 | const unsigned int batchSize = 2; |
| 2437 | |
| 2438 | unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 2439 | |
| 2440 | std::vector<float> input0({ |
| 2441 | 1, 1, 1, 1, 2, 2, 2, 2, |
| 2442 | 3, 3, 3, 3, 4, 4, 4, 4 }); |
| 2443 | |
| 2444 | std::vector<float> input1({ |
| 2445 | 2, 2, 2, 2, 3, 3, 3, 3, |
| 2446 | 4, 4, 4, 4, 5, 5, 5, 5 }); |
| 2447 | |
| 2448 | std::vector<float> output({ |
| 2449 | 2, 2, 2, 2, 6, 6, 6, 6, |
| 2450 | 12, 12, 12, 12, 20, 20, 20, 20 }); |
| 2451 | |
| 2452 | return MultiplicationTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2453 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2454 | shape, |
| 2455 | input0, |
| 2456 | shape, |
| 2457 | input1, |
| 2458 | shape, |
| 2459 | output); |
| 2460 | } |
| 2461 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2462 | LayerTestResult<float, 4> MultiplicationBroadcast1ElementTest( |
| 2463 | armnn::IWorkloadFactory& workloadFactory, |
| 2464 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2465 | { |
| 2466 | unsigned int shape0[] = { 1, 2, 2, 2 }; |
| 2467 | std::vector<float> input0({ 1, 2, 3, 4, 5, 6, 7, 8}); |
| 2468 | |
| 2469 | unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 2470 | std::vector<float> input1({ 2 }); |
| 2471 | |
| 2472 | std::vector<float> output({ 2, 4, 6, 8, 10, 12, 14, 16}); |
| 2473 | |
| 2474 | return MultiplicationTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2475 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2476 | shape0, |
| 2477 | input0, |
| 2478 | shape1, |
| 2479 | input1, |
| 2480 | shape0, |
| 2481 | output); |
| 2482 | } |
| 2483 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2484 | LayerTestResult<float, 4> MultiplicationBroadcast1DVectorTest( |
| 2485 | armnn::IWorkloadFactory& workloadFactory, |
| 2486 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2487 | { |
| 2488 | unsigned int shape0[] = { 1, 3, 3, 2 }; |
| 2489 | std::vector<float> input0({ |
| 2490 | 1, 2, 3, 4, 5, 6, |
| 2491 | 7, 8, 9, 10, 11, 12, |
| 2492 | 13, 14, 15, 16, 17, 18}); |
| 2493 | |
| 2494 | unsigned int shape1[] = { 1, 1, 1, 2 }; |
| 2495 | std::vector<float> input1({ 1, 2 }); |
| 2496 | |
| 2497 | std::vector<float> output({ |
| 2498 | 1, 4, 3, 8, 5, 12, |
| 2499 | 7, 16, 9, 20, 11, 24, |
| 2500 | 13, 28, 15, 32, 17, 36}); |
| 2501 | |
| 2502 | return MultiplicationTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2503 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 2504 | shape0, |
| 2505 | input0, |
| 2506 | shape1, |
| 2507 | input1, |
| 2508 | shape0, |
| 2509 | output); |
| 2510 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2511 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2512 | LayerTestResult<float,4> CompareMultiplicationTest( |
| 2513 | armnn::IWorkloadFactory& workloadFactory, |
| 2514 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2515 | armnn::IWorkloadFactory& refWorkloadFactory) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2516 | { |
| 2517 | const unsigned int width = 16; |
| 2518 | const unsigned int height = 32; |
| 2519 | const unsigned int channelCount = 2; |
| 2520 | const unsigned int batchSize = 5; |
| 2521 | |
| 2522 | armnn::TensorInfo inputTensorInfo0; |
| 2523 | armnn::TensorInfo inputTensorInfo1; |
| 2524 | armnn::TensorInfo outputTensorInfo; |
| 2525 | |
| 2526 | constexpr unsigned int shape[] = { batchSize, channelCount, height, width }; |
| 2527 | |
| 2528 | inputTensorInfo0 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2529 | inputTensorInfo1 = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2530 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2531 | |
| 2532 | LayerTestResult<float,4> comparisonResult(outputTensorInfo); |
| 2533 | |
| 2534 | auto input0 = MakeRandomTensor<float, 4>(inputTensorInfo0, 803506992); |
| 2535 | auto input1 = MakeRandomTensor<float, 4>(inputTensorInfo1, 54902257); |
| 2536 | |
| 2537 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 2538 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 2539 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2540 | |
| 2541 | std::unique_ptr<armnn::ITensorHandle> inputHandle0Ref = refWorkloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 2542 | std::unique_ptr<armnn::ITensorHandle> inputHandle1Ref = refWorkloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 2543 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2544 | |
| 2545 | armnn::MultiplicationQueueDescriptor data; |
| 2546 | armnn::WorkloadInfo info; |
| 2547 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 2548 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 2549 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2550 | |
| 2551 | armnn::MultiplicationQueueDescriptor refData = data; |
| 2552 | armnn::WorkloadInfo refInfo = info; |
| 2553 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo0, inputHandle0Ref.get()); |
| 2554 | SetWorkloadInput(refData, refInfo, 1, inputTensorInfo1, inputHandle1Ref.get()); |
| 2555 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 2556 | |
| 2557 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMultiplication(data, info); |
| 2558 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateMultiplication(refData, refInfo); |
| 2559 | |
| 2560 | inputHandle0->Allocate(); |
| 2561 | inputHandle1->Allocate(); |
| 2562 | outputHandle->Allocate(); |
| 2563 | inputHandle0Ref->Allocate(); |
| 2564 | inputHandle1Ref->Allocate(); |
| 2565 | outputHandleRef->Allocate(); |
| 2566 | |
| 2567 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 2568 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 2569 | CopyDataToITensorHandle(inputHandle0Ref.get(), &input0[0][0][0][0]); |
| 2570 | CopyDataToITensorHandle(inputHandle1Ref.get(), &input1[0][0][0][0]); |
| 2571 | |
| 2572 | workload->Execute(); |
| 2573 | workloadRef->Execute(); |
| 2574 | |
| 2575 | CopyDataFromITensorHandle(&comparisonResult.output[0][0][0][0], outputHandle.get()); |
| 2576 | CopyDataFromITensorHandle(&comparisonResult.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 2577 | |
| 2578 | return comparisonResult; |
| 2579 | } |
| 2580 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2581 | LayerTestResult<float,4> CompareBatchNormTest( |
| 2582 | armnn::IWorkloadFactory& workloadFactory, |
| 2583 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2584 | armnn::IWorkloadFactory& refWorkloadFactory) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2585 | { |
| 2586 | const unsigned int width = 2; |
| 2587 | const unsigned int height = 3; |
| 2588 | const unsigned int channels = 5; |
| 2589 | const unsigned int batchSize = 3; |
| 2590 | |
| 2591 | armnn::TensorInfo inputTensorInfo; |
| 2592 | armnn::TensorInfo outputTensorInfo; |
| 2593 | armnn::TensorInfo tensorInfo; |
| 2594 | |
| 2595 | constexpr unsigned int shape[] = {batchSize, channels, height, width}; |
| 2596 | constexpr unsigned int tensorShape[] = {channels}; |
| 2597 | |
| 2598 | inputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2599 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32); |
| 2600 | tensorInfo = armnn::TensorInfo(1, tensorShape, armnn::DataType::Float32); |
| 2601 | |
| 2602 | auto input = MakeRandomTensor<float, 4>(inputTensorInfo, 21312); |
| 2603 | |
| 2604 | auto mean = MakeRandomTensor<float, 1>(tensorInfo, 123); |
| 2605 | auto variance = MakeRandomTensor<float, 1>(tensorInfo, 234, 0.0f); |
| 2606 | auto beta = MakeRandomTensor<float, 1>(tensorInfo, 123); |
| 2607 | auto gamma = MakeRandomTensor<float, 1>(tensorInfo, 345); |
| 2608 | |
| 2609 | LayerTestResult<float,4> ret(outputTensorInfo); |
| 2610 | |
| 2611 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 2612 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2613 | |
| 2614 | std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refWorkloadFactory.CreateTensorHandle(inputTensorInfo); |
| 2615 | std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2616 | |
| 2617 | armnn::BatchNormalizationQueueDescriptor data; |
| 2618 | armnn::WorkloadInfo info; |
| 2619 | armnn::ScopedCpuTensorHandle meanTensor(tensorInfo); |
| 2620 | armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo); |
| 2621 | armnn::ScopedCpuTensorHandle betaTensor(tensorInfo); |
| 2622 | armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo); |
| 2623 | |
| 2624 | AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]); |
| 2625 | AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]); |
| 2626 | AllocateAndCopyDataToITensorHandle(&betaTensor, &beta[0]); |
| 2627 | AllocateAndCopyDataToITensorHandle(&gammaTensor, &gamma[0]); |
| 2628 | |
| 2629 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 2630 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 2631 | data.m_Mean = &meanTensor; |
| 2632 | data.m_Variance = &varianceTensor; |
| 2633 | data.m_Beta = &betaTensor; |
| 2634 | data.m_Gamma = &gammaTensor; |
| 2635 | data.m_Parameters.m_Eps = 0.01f; |
| 2636 | |
| 2637 | armnn::BatchNormalizationQueueDescriptor refData = data; |
| 2638 | armnn::WorkloadInfo refInfo = info; |
| 2639 | SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get()); |
| 2640 | SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); |
| 2641 | |
| 2642 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(data, info); |
| 2643 | std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateBatchNormalization(refData, refInfo); |
| 2644 | |
| 2645 | inputHandle->Allocate(); |
| 2646 | outputHandle->Allocate(); |
| 2647 | inputHandleRef->Allocate(); |
| 2648 | outputHandleRef->Allocate(); |
| 2649 | |
| 2650 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 2651 | CopyDataToITensorHandle(inputHandleRef.get(), &input[0][0][0][0]); |
| 2652 | |
| 2653 | workload->Execute(); |
| 2654 | workloadRef->Execute(); |
| 2655 | |
| 2656 | CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| 2657 | CopyDataFromITensorHandle(&ret.outputExpected[0][0][0][0], outputHandleRef.get()); |
| 2658 | |
| 2659 | return ret; |
| 2660 | } |
| 2661 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2662 | template<typename T> |
| 2663 | void PermuteTensorData( |
| 2664 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2665 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2666 | const armnn::PermutationVector& mappings, |
| 2667 | armnn::TensorInfo & inputTensorInfo, |
| 2668 | const T * inputData, |
| 2669 | std::vector<T>& outputData) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2670 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2671 | BOOST_ASSERT_MSG(inputData != nullptr, "inputData must not be null"); |
| 2672 | if (inputData == nullptr) |
| 2673 | { |
| 2674 | // Nullptr is an error in the test. By returning without doing the concatenation |
| 2675 | // I expect the caller to fail the test. It still makes sense to report this as |
| 2676 | // an assert for Debug builds. |
| 2677 | return; |
| 2678 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2679 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2680 | armnn::TensorInfo outputTensorInfo = armnnUtils::Permuted(inputTensorInfo, mappings); |
| 2681 | |
| 2682 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 2683 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2684 | |
| 2685 | armnn::PermuteQueueDescriptor queueDescriptor; |
| 2686 | queueDescriptor.m_Parameters = armnn::PermuteDescriptor{mappings}; |
| 2687 | armnn::WorkloadInfo workloadInfo; |
| 2688 | AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| 2689 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 2690 | |
| 2691 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePermute(queueDescriptor, workloadInfo); |
| 2692 | |
| 2693 | inputHandle->Allocate(); |
| 2694 | outputHandle->Allocate(); |
| 2695 | |
| 2696 | CopyDataToITensorHandle(inputHandle.get(), inputData); |
| 2697 | |
| 2698 | workload->Execute(); |
| 2699 | |
| 2700 | outputData.resize(outputTensorInfo.GetNumElements()); |
| 2701 | CopyDataFromITensorHandle(&outputData[0], outputHandle.get()); |
| 2702 | inputTensorInfo = outputTensorInfo; |
| 2703 | } |
| 2704 | |
| 2705 | armnn::OriginsDescriptor CreateMergerDescriptorForConcatenation( |
| 2706 | const std::vector<armnn::TensorInfo> & inputTensorInfos, |
| 2707 | unsigned int concatDim) |
| 2708 | { |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2709 | std::vector<armnn::TensorShape> shapes; |
| 2710 | shapes.reserve(inputTensorInfos.size()); |
| 2711 | for (const armnn::TensorInfo& it: inputTensorInfos) |
| 2712 | { |
| 2713 | shapes.push_back(it.GetShape()); |
| 2714 | } |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2715 | |
| 2716 | return armnn::CreateMergerDescriptorForConcatenation(shapes.begin(), |
| 2717 | shapes.end(), |
| 2718 | concatDim); |
| 2719 | } |
| 2720 | |
| 2721 | // |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2722 | // Concatenation is only supported for N and C dimensions for NCHW and the inner most dimension |
| 2723 | // In case of <4 dimensions we need to make sure that the concat dimensions are at least |
| 2724 | // the 3rd slowest iterating one or the inner most dimension. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2725 | // |
| 2726 | |
| 2727 | bool NeedPermuteForConcat( |
| 2728 | const std::vector<armnn::TensorInfo> & inputTensorInfos, |
| 2729 | unsigned int concatDim) |
| 2730 | { |
| 2731 | // See note above. Additionally we expect the input shapes to have the |
| 2732 | // same number of dimensions. |
| 2733 | unsigned int nDimensions = 0; |
| 2734 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2735 | // Determine the number of dimensions as well as sanity check them |
| 2736 | // agains test implementation issues. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2737 | for (auto && tensorInfo : inputTensorInfos) |
| 2738 | { |
| 2739 | if (!nDimensions) |
| 2740 | { |
| 2741 | nDimensions = tensorInfo.GetShape().GetNumDimensions(); |
| 2742 | } |
| 2743 | else |
| 2744 | { |
| 2745 | BOOST_ASSERT_MSG(nDimensions == tensorInfo.GetShape().GetNumDimensions(), |
| 2746 | "Input shapes must have the same number of dimensions"); |
| 2747 | } |
| 2748 | } |
| 2749 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2750 | return (nDimensions < 3 || (nDimensions == 3 && (nDimensions-concatDim) < 3 && (nDimensions-concatDim) != 1)); |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2751 | } |
| 2752 | |
| 2753 | armnn::TensorShape ExpandTensorShapeTo3dForPermute(const armnn::TensorShape & inputShape) |
| 2754 | { |
| 2755 | unsigned int numDims = inputShape.GetNumDimensions(); |
| 2756 | if (numDims >= 3) |
| 2757 | { |
| 2758 | // Nothing to do if the inputShape has at least 3 dimensions. |
| 2759 | return inputShape; |
| 2760 | } |
| 2761 | |
| 2762 | std::vector<unsigned int> newDims(size_t(3), 1u); |
| 2763 | unsigned int expandedBy = 3 - numDims; |
| 2764 | for (unsigned int i=0; i<numDims; ++i) |
| 2765 | { |
| 2766 | newDims[expandedBy+i] = inputShape[i]; |
| 2767 | } |
| 2768 | return armnn::TensorShape(3u, &newDims[0]); |
| 2769 | } |
| 2770 | |
| 2771 | void Generate3dPermuteVectorForConcat( |
| 2772 | unsigned int numDimensions, |
| 2773 | unsigned int & concatDim, |
| 2774 | std::pair<armnn::PermutationVector, armnn::PermutationVector> & permutations) |
| 2775 | { |
| 2776 | BOOST_ASSERT_MSG(numDimensions <= 3, |
| 2777 | "Only dimensions 1,2 and 3 are supported by this helper"); |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2778 | unsigned int expandedBy = 3 - numDimensions; |
| 2779 | unsigned int expandedConcatAxis = concatDim + expandedBy; |
| 2780 | |
| 2781 | if (expandedConcatAxis == 2) |
| 2782 | { |
| 2783 | concatDim = 0; |
| 2784 | armnn::PermutationVector forwardPermutation({1, 2, 0}); |
| 2785 | armnn::PermutationVector reversePermutation({2, 0, 1}); |
| 2786 | permutations = std::make_pair(forwardPermutation, reversePermutation); |
| 2787 | } |
| 2788 | else if (expandedConcatAxis == 1) |
| 2789 | { |
| 2790 | concatDim = 0; |
| 2791 | armnn::PermutationVector forwardPermutation({2, 0, 1}); |
| 2792 | armnn::PermutationVector reversePermutation({1, 2, 0}); |
| 2793 | permutations = std::make_pair(forwardPermutation, reversePermutation); |
| 2794 | } |
| 2795 | else |
| 2796 | { |
| 2797 | BOOST_ASSERT(expandedConcatAxis == 0); |
| 2798 | concatDim = 0; |
| 2799 | } |
| 2800 | } |
| 2801 | |
| 2802 | // |
| 2803 | // Permute the input tensors so we can do a supported concatenation. |
| 2804 | // Also treat lower than 3d tensors as 3d by adding dummy 1 dimensions |
| 2805 | // at the front. Finally this function tells what the output shape |
| 2806 | // of the permuted concatenated tensor is going to be. |
| 2807 | // |
| 2808 | template <typename T> |
| 2809 | void PermuteInputsForConcat( |
| 2810 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2811 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2812 | std::vector<armnn::TensorInfo> & inputTensorInfos, |
| 2813 | std::vector<T *> & inputData, |
| 2814 | std::vector<std::vector<T>> & inputDataStorage, |
| 2815 | armnn::PermutationVector & permuteVector, |
| 2816 | unsigned int & concatDim, |
| 2817 | armnn::TensorInfo & outputTensorInfo) |
| 2818 | { |
| 2819 | BOOST_ASSERT_MSG(inputTensorInfos.size() > 1, |
| 2820 | "Expecting more than one tensor to be concatenated here"); |
| 2821 | |
| 2822 | unsigned int numDims = 0; |
| 2823 | unsigned int nthInput = 0; |
| 2824 | const armnn::PermutationVector identity({0, 1, 2}); |
| 2825 | |
| 2826 | std::pair<armnn::PermutationVector, armnn::PermutationVector> permutations = |
| 2827 | std::make_pair(identity, identity); |
| 2828 | |
| 2829 | inputDataStorage.resize(inputData.size()); |
| 2830 | |
| 2831 | for (auto && tensorInfo : inputTensorInfos) |
| 2832 | { |
| 2833 | if (numDims == 0) |
| 2834 | { |
| 2835 | numDims = tensorInfo.GetShape().GetNumDimensions(); |
| 2836 | Generate3dPermuteVectorForConcat(numDims, concatDim, permutations); |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2837 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2838 | // Store the reverese permutation. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2839 | permuteVector = permutations.second; |
| 2840 | BOOST_ASSERT_MSG(!permuteVector.IsEqual(identity), |
| 2841 | "Test logic error, we don't need permutation, so we shouldn't arrive here"); |
| 2842 | } |
| 2843 | else |
| 2844 | { |
| 2845 | BOOST_ASSERT_MSG(numDims == tensorInfo.GetShape().GetNumDimensions(), |
| 2846 | "All inputs must have the same number of dimensions"); |
| 2847 | } |
| 2848 | |
| 2849 | armnn::TensorInfo newTensorInfo = tensorInfo; |
| 2850 | newTensorInfo.SetShape(ExpandTensorShapeTo3dForPermute(tensorInfo.GetShape())); |
| 2851 | |
| 2852 | PermuteTensorData<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2853 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2854 | permutations.first, |
| 2855 | newTensorInfo, |
| 2856 | inputData[nthInput], |
| 2857 | inputDataStorage[nthInput]); |
| 2858 | |
| 2859 | inputData[nthInput] = inputDataStorage[nthInput].data(); |
| 2860 | inputTensorInfos[nthInput] = newTensorInfo; |
| 2861 | |
| 2862 | ++nthInput; |
| 2863 | } |
| 2864 | |
| 2865 | outputTensorInfo.SetShape( |
| 2866 | armnnUtils::Permuted( |
| 2867 | ExpandTensorShapeTo3dForPermute(outputTensorInfo.GetShape()), |
| 2868 | permutations.first)); |
| 2869 | } |
| 2870 | |
| 2871 | |
| 2872 | // |
| 2873 | // This is the pair of PermuteInputsForConcat(...) which permutes back |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2874 | // the output of the concatenation so we can check it against an expected |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2875 | // output. |
| 2876 | // |
| 2877 | template <typename T> |
| 2878 | void PermuteOutputForConcat( |
| 2879 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2880 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2881 | const armnn::TensorInfo & tensorInfo, |
| 2882 | const armnn::PermutationVector & permuteVector, |
| 2883 | std::unique_ptr<armnn::ITensorHandle> && inputDataHandle, |
| 2884 | T * data) |
| 2885 | { |
| 2886 | BOOST_ASSERT_MSG(data != nullptr, "data must not be null"); |
| 2887 | if (data == nullptr) |
| 2888 | { |
| 2889 | // Nullptr is an error in the test. By returning without doing the permutation |
| 2890 | // I expect the caller to fail the test. It still makes sense to report this as |
| 2891 | // an assert for Debug builds. |
| 2892 | return; |
| 2893 | } |
| 2894 | |
| 2895 | armnn::TensorInfo resultTensorInfo = tensorInfo; |
| 2896 | std::vector<T> inputData(tensorInfo.GetNumElements()); |
| 2897 | std::vector<T> outputData; |
| 2898 | |
| 2899 | CopyDataFromITensorHandle(&inputData[0], inputDataHandle.get()); |
| 2900 | |
| 2901 | PermuteTensorData<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2902 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2903 | permuteVector, |
| 2904 | resultTensorInfo, |
| 2905 | &inputData[0], |
| 2906 | outputData); |
| 2907 | |
| 2908 | ::memcpy(data, &outputData[0], sizeof(T)*outputData.size()); |
| 2909 | } |
| 2910 | |
| 2911 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2912 | void Concatenate( |
| 2913 | armnn::IWorkloadFactory& workloadFactory, |
| 2914 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 2915 | std::initializer_list<const armnn::TensorInfo> inputTensorInfosOrig, |
| 2916 | std::initializer_list<T *> inputsOrig, |
| 2917 | const armnn::TensorInfo& outputTensorInfoOrig, |
| 2918 | T * output, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2919 | unsigned int concatDim, |
| 2920 | bool useSubtensor) |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2921 | { |
| 2922 | BOOST_ASSERT_MSG(output != nullptr, "output must not be null"); |
| 2923 | if (output == nullptr) |
| 2924 | { |
| 2925 | // Nullptr is an error in the test. By returning without doing the permutation |
| 2926 | // I expect the caller to fail the test. It still makes sense to report this as |
| 2927 | // an assert for Debug builds. |
| 2928 | return; |
| 2929 | } |
| 2930 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2931 | // Saves a copy of the parameters which we might need to change. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2932 | std::vector<armnn::TensorInfo> inputTensorInfos(inputTensorInfosOrig.begin(), inputTensorInfosOrig.end()); |
| 2933 | std::vector<T *> inputs = inputsOrig; |
| 2934 | armnn::TensorInfo outputTensorInfo = outputTensorInfoOrig; |
| 2935 | |
| 2936 | armnn::PermutationVector permuteVector{0, 1, 2}; |
| 2937 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2938 | // Holds and automatically releases memory for the reshaped input data. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2939 | std::vector<std::vector<T>> tmpInputDataStorage; |
| 2940 | |
| 2941 | const size_t inputCount = inputTensorInfos.size(); |
| 2942 | |
| 2943 | bool needPermuteForConcat = NeedPermuteForConcat(inputTensorInfos, concatDim); |
| 2944 | |
| 2945 | if (needPermuteForConcat) |
| 2946 | { |
| 2947 | // |
| 2948 | // We need to permute the inputs, because concatenation along |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 2949 | // the requested axis is not supported. |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2950 | // |
| 2951 | PermuteInputsForConcat<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 2952 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 2953 | inputTensorInfos, |
| 2954 | inputs, |
| 2955 | tmpInputDataStorage, |
| 2956 | permuteVector, |
| 2957 | concatDim, |
| 2958 | outputTensorInfo); |
| 2959 | } |
| 2960 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2961 | armnn::WorkloadInfo workloadInfo; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2962 | |
| 2963 | std::vector<std::unique_ptr<armnn::ITensorHandle>> inputHandles; |
| 2964 | inputHandles.reserve(inputCount); |
| 2965 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2966 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 2967 | |
| 2968 | armnn::MergerQueueDescriptor queueDescriptor; |
| 2969 | armnn::OriginsDescriptor viewsDescriptor = CreateMergerDescriptorForConcatenation(inputTensorInfos, concatDim); |
| 2970 | queueDescriptor.m_Parameters = viewsDescriptor; |
| 2971 | |
| 2972 | if (useSubtensor) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2973 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2974 | queueDescriptor.m_ViewOrigins.reserve(viewsDescriptor.GetNumViews()); |
| 2975 | for (unsigned int i = 0; i < viewsDescriptor.GetNumViews(); ++i) |
| 2976 | { |
| 2977 | queueDescriptor.m_ViewOrigins.emplace_back(std::vector<unsigned int>(viewsDescriptor.GetViewOrigin(i), |
| 2978 | viewsDescriptor.GetViewOrigin(i) + viewsDescriptor.GetNumDimensions())); |
| 2979 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2980 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2981 | outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2982 | |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2983 | const bool subTensorsSupported = workloadFactory.SupportsSubTensors(); |
| 2984 | for (unsigned int i = 0; i < inputCount; ++i) |
| 2985 | { |
| 2986 | const armnn::TensorInfo& inputTensorInfo = inputTensorInfos[i]; |
| 2987 | std::unique_ptr<armnn::ITensorHandle> inputHandle = |
| 2988 | subTensorsSupported ? |
| 2989 | workloadFactory.CreateSubTensorHandle(*outputHandle, |
| 2990 | inputTensorInfo.GetShape(), |
| 2991 | queueDescriptor.m_ViewOrigins[i].m_Origin.data()) : |
| 2992 | workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 2993 | |
| 2994 | inputHandles.emplace_back(std::move(inputHandle)); |
| 2995 | } |
| 2996 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 2997 | } |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 2998 | else |
| 2999 | { |
| 3000 | for (unsigned int i = 0; i < inputCount; ++i) |
| 3001 | { |
| 3002 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfos[i]); |
| 3003 | inputHandles.emplace_back(std::move(inputHandle)); |
| 3004 | } |
| 3005 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3006 | |
| 3007 | for (unsigned int i = 0; i < inputCount; ++i) |
| 3008 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 3009 | AddInputToWorkload(queueDescriptor, workloadInfo, inputTensorInfos[i], inputHandles[i].get()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3010 | } |
| 3011 | |
| 3012 | AddOutputToWorkload(queueDescriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| 3013 | |
| 3014 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMerger(queueDescriptor, workloadInfo); |
| 3015 | |
| 3016 | for (auto& inputHandle : inputHandles) |
| 3017 | { |
| 3018 | inputHandle->Allocate(); |
| 3019 | } |
| 3020 | |
| 3021 | outputHandle->Allocate(); |
| 3022 | |
| 3023 | unsigned int nextInputId = 0; |
| 3024 | for (auto& inputHandle : inputHandles) |
| 3025 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 3026 | CopyDataToITensorHandle(inputHandle.get(), inputs[nextInputId]); |
| 3027 | ++nextInputId; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3028 | } |
| 3029 | |
| 3030 | workload->Execute(); |
| 3031 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 3032 | if (needPermuteForConcat) |
| 3033 | { |
| 3034 | PermuteOutputForConcat<T>(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3035 | memoryManager, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 3036 | outputTensorInfo, |
| 3037 | permuteVector, |
| 3038 | std::move(outputHandle), |
| 3039 | output); |
| 3040 | } |
| 3041 | else |
| 3042 | { |
| 3043 | CopyDataFromITensorHandle(output, outputHandle.get()); |
| 3044 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3045 | } |
| 3046 | |
| 3047 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3048 | LayerTestResult<T, 1> Concatenation1dTestImpl( |
| 3049 | armnn::IWorkloadFactory& workloadFactory, |
| 3050 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3051 | float qScale, |
| 3052 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3053 | { |
| 3054 | armnn::TensorInfo inputTensorInfo({ 3 }, armnn::GetDataType<T>()); |
| 3055 | |
| 3056 | auto input0 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 1.0f, 2.0f, 3.0f })); |
| 3057 | auto input1 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 4.0f, 5.0f, 6.0f })); |
| 3058 | auto input2 = MakeTensor<T, 1>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { 7.0f, 8.0f, 9.0f })); |
| 3059 | |
| 3060 | armnn::TensorInfo outputTensorInfo({ 9 }, armnn::GetDataType<T>()); |
| 3061 | |
| 3062 | LayerTestResult<T, 1> result(outputTensorInfo); |
| 3063 | |
| 3064 | std::vector<T> output; |
| 3065 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3066 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3067 | { inputTensorInfo, inputTensorInfo, inputTensorInfo }, |
| 3068 | { input0.data(), input1.data(), input2.data() }, |
| 3069 | outputTensorInfo, |
| 3070 | output.data(), |
| 3071 | 0, |
| 3072 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3073 | |
| 3074 | result.output = MakeTensor<T, 1>(outputTensorInfo, output); |
| 3075 | result.outputExpected = MakeTensor<T, 1>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3076 | 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f |
| 3077 | })); |
| 3078 | |
| 3079 | return result; |
| 3080 | } |
| 3081 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3082 | LayerTestResult<float, 1> Concatenation1dTest( |
| 3083 | armnn::IWorkloadFactory& workloadFactory, |
| 3084 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3085 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3086 | return Concatenation1dTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3087 | } |
| 3088 | |
| 3089 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3090 | LayerTestResult<T, 2> Concatenation2dTestImpl( |
| 3091 | armnn::IWorkloadFactory& workloadFactory, |
| 3092 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3093 | const armnn::TensorInfo& outputTensorInfo, |
| 3094 | unsigned int dimension, |
| 3095 | const float qScale, |
| 3096 | const int32_t qOffset) |
| 3097 | { |
| 3098 | armnn::TensorInfo inputTensorInfo({ 2, 3 }, armnn::GetDataType<T>()); |
| 3099 | |
| 3100 | auto input0 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3101 | // Batch 0 |
| 3102 | 1.0f, 2.0f, 3.0f, |
| 3103 | |
| 3104 | // Batch 1 |
| 3105 | 10.0f, 11.0f, 12.0f, |
| 3106 | })); |
| 3107 | |
| 3108 | auto input1 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3109 | // Batch 0 |
| 3110 | 4.0f, 5.0f, 6.0f, |
| 3111 | |
| 3112 | // Batch 1 |
| 3113 | 13.0f, 14.0f, 15.0f, |
| 3114 | })); |
| 3115 | |
| 3116 | auto input2 = MakeTensor<T, 2>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3117 | // Batch 0 |
| 3118 | 7.0f, 8.0f, 9.0f, |
| 3119 | |
| 3120 | // Batch 1 |
| 3121 | 16.0f, 17.0f, 18.0f, |
| 3122 | })); |
| 3123 | |
| 3124 | LayerTestResult<T, 2> result(outputTensorInfo); |
| 3125 | |
| 3126 | std::vector<T> output; |
| 3127 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3128 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3129 | { inputTensorInfo, inputTensorInfo, inputTensorInfo }, |
| 3130 | { input0.data(), input1.data(), input2.data() }, |
| 3131 | outputTensorInfo, |
| 3132 | output.data(), |
| 3133 | dimension, |
| 3134 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3135 | |
| 3136 | result.output = MakeTensor<T, 2>(outputTensorInfo, output); |
| 3137 | return result; |
| 3138 | } |
| 3139 | |
| 3140 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3141 | LayerTestResult<T, 2> Concatenation2dDim0TestImpl( |
| 3142 | armnn::IWorkloadFactory& workloadFactory, |
| 3143 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3144 | float qScale, |
| 3145 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3146 | { |
| 3147 | armnn::TensorInfo outputTensorInfo({ 6, 3 }, armnn::GetDataType<T>()); |
| 3148 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3149 | LayerTestResult<T, 2> result = |
| 3150 | Concatenation2dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 0, qScale, qOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3151 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3152 | // Batch 0 |
| 3153 | 1.0f, 2.0f, 3.0f, |
| 3154 | |
| 3155 | // Batch 1 |
| 3156 | 10.0f, 11.0f, 12.0f, |
| 3157 | |
| 3158 | // Batch 2 |
| 3159 | 4.0f, 5.0f, 6.0f, |
| 3160 | |
| 3161 | // Batch 3 |
| 3162 | 13.0f, 14.0f, 15.0f, |
| 3163 | |
| 3164 | // Batch 4 |
| 3165 | 7.0f, 8.0f, 9.0f, |
| 3166 | |
| 3167 | // Batch 5 |
| 3168 | 16.0f, 17.0f, 18.0f, |
| 3169 | })); |
| 3170 | |
| 3171 | return result; |
| 3172 | } |
| 3173 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3174 | LayerTestResult<float, 2> Concatenation2dDim0Test( |
| 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 Concatenation2dDim0TestImpl<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, 2> Concatenation2dDim1TestImpl( |
| 3183 | armnn::IWorkloadFactory& workloadFactory, |
| 3184 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3185 | float qScale, |
| 3186 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3187 | { |
| 3188 | armnn::TensorInfo outputTensorInfo({ 2, 9 }, armnn::GetDataType<T>()); |
| 3189 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3190 | LayerTestResult<T, 2> result = |
| 3191 | Concatenation2dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 1, qScale, qOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3192 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3193 | // Batch 0 |
| 3194 | 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, |
| 3195 | |
| 3196 | // Batch 1 |
| 3197 | 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f |
| 3198 | })); |
| 3199 | |
| 3200 | return result; |
| 3201 | } |
| 3202 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3203 | LayerTestResult<float, 2> Concatenation2dDim1Test( |
| 3204 | armnn::IWorkloadFactory& workloadFactory, |
| 3205 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3206 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3207 | return Concatenation2dDim1TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3208 | } |
| 3209 | |
| 3210 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3211 | LayerTestResult<T, 2> Concatenation2dDim0DiffInputDimsTestImpl( |
| 3212 | armnn::IWorkloadFactory& workloadFactory, |
| 3213 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3214 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3215 | int32_t qOffset) |
| 3216 | { |
| 3217 | armnn::TensorInfo input0TensorInfo({ 2, 3 }, armnn::GetDataType<T>()); |
| 3218 | auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3219 | // Batch 0 |
| 3220 | 1.0f, 2.0f, 3.0f, |
| 3221 | |
| 3222 | // Batch 1 |
| 3223 | 10.0f, 11.0f, 12.0f, |
| 3224 | })); |
| 3225 | |
| 3226 | armnn::TensorInfo input1TensorInfo({ 3, 3 }, armnn::GetDataType<T>()); |
| 3227 | auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3228 | // Batch 0 |
| 3229 | 4.0f, 5.0f, 6.0f, |
| 3230 | |
| 3231 | // Batch 1 |
| 3232 | 13.0f, 14.0f, 15.0f, |
| 3233 | |
| 3234 | // Batch 0 |
| 3235 | 7.0f, 8.0f, 9.0f, |
| 3236 | })); |
| 3237 | |
| 3238 | armnn::TensorInfo input2TensorInfo({ 1, 3 }, armnn::GetDataType<T>()); |
| 3239 | auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3240 | // Batch 1 |
| 3241 | 16.0f, 17.0f, 18.0f, |
| 3242 | })); |
| 3243 | |
| 3244 | armnn::TensorInfo outputTensorInfo({ 6, 3 }, armnn::GetDataType<T>()); |
| 3245 | LayerTestResult<T, 2> result(outputTensorInfo); |
| 3246 | |
| 3247 | std::vector<T> output; |
| 3248 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3249 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3250 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 3251 | { input0.data(), input1.data(), input2.data() }, |
| 3252 | outputTensorInfo, |
| 3253 | output.data(), |
| 3254 | 0, |
| 3255 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3256 | |
| 3257 | result.output = MakeTensor<T, 2>(outputTensorInfo, output); |
| 3258 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3259 | // Batch 0 |
| 3260 | 1.0f, 2.0f, 3.0f, |
| 3261 | |
| 3262 | // Batch 1 |
| 3263 | 10.0f, 11.0f, 12.0f, |
| 3264 | |
| 3265 | // Batch 2 |
| 3266 | 4.0f, 5.0f, 6.0f, |
| 3267 | |
| 3268 | // Batch 3 |
| 3269 | 13.0f, 14.0f, 15.0f, |
| 3270 | |
| 3271 | // Batch 4 |
| 3272 | 7.0f, 8.0f, 9.0f, |
| 3273 | |
| 3274 | // Batch 5 |
| 3275 | 16.0f, 17.0f, 18.0f, |
| 3276 | })); |
| 3277 | |
| 3278 | return result; |
| 3279 | } |
| 3280 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3281 | LayerTestResult<float, 2> Concatenation2dDim0DiffInputDimsTest( |
| 3282 | armnn::IWorkloadFactory& workloadFactory, |
| 3283 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3284 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3285 | return Concatenation2dDim0DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3286 | } |
| 3287 | |
| 3288 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3289 | LayerTestResult<T, 2> Concatenation2dDim1DiffInputDimsTestImpl( |
| 3290 | armnn::IWorkloadFactory& workloadFactory, |
| 3291 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3292 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3293 | int32_t qOffset) |
| 3294 | { |
| 3295 | armnn::TensorInfo input0TensorInfo({ 2, 3 }, armnn::GetDataType<T>()); |
| 3296 | auto input0 = MakeTensor<T, 2>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3297 | // Batch 0 |
| 3298 | 1.0f, 2.0f, 3.0f, |
| 3299 | |
| 3300 | // Batch 1 |
| 3301 | 10.0f, 11.0f, 12.0f, |
| 3302 | })); |
| 3303 | |
| 3304 | armnn::TensorInfo input1TensorInfo({ 2, 5 }, armnn::GetDataType<T>()); |
| 3305 | auto input1 = MakeTensor<T, 2>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3306 | // Batch 0 |
| 3307 | 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, |
| 3308 | |
| 3309 | // Batch 1 |
| 3310 | 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, |
| 3311 | })); |
| 3312 | |
| 3313 | armnn::TensorInfo input2TensorInfo({ 2, 1 }, armnn::GetDataType<T>()); |
| 3314 | auto input2 = MakeTensor<T, 2>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3315 | // Batch 0 |
| 3316 | 9.0f, |
| 3317 | |
| 3318 | // Batch 1 |
| 3319 | 18.0f |
| 3320 | })); |
| 3321 | |
| 3322 | armnn::TensorInfo outputTensorInfo({ 2, 9 }, armnn::GetDataType<T>()); |
| 3323 | LayerTestResult<T, 2> result(outputTensorInfo); |
| 3324 | |
| 3325 | std::vector<T> output; |
| 3326 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3327 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3328 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 3329 | { input0.data(), input1.data(), input2.data() }, |
| 3330 | outputTensorInfo, |
| 3331 | output.data(), |
| 3332 | 1, |
| 3333 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3334 | |
| 3335 | result.output = MakeTensor<T, 2>(outputTensorInfo, output); |
| 3336 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3337 | // Batch 0 |
| 3338 | 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, |
| 3339 | |
| 3340 | // Batch 1 |
| 3341 | 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, |
| 3342 | })); |
| 3343 | |
| 3344 | return result; |
| 3345 | } |
| 3346 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3347 | LayerTestResult<float, 2> Concatenation2dDim1DiffInputDimsTest( |
| 3348 | armnn::IWorkloadFactory& workloadFactory, |
| 3349 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3350 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3351 | return Concatenation2dDim1DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3352 | } |
| 3353 | |
| 3354 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3355 | LayerTestResult<T, 3> Concatenation3dTestImpl( |
| 3356 | armnn::IWorkloadFactory& workloadFactory, |
| 3357 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3358 | const armnn::TensorInfo& outputTensorInfo, |
| 3359 | unsigned int dimension, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3360 | bool useSubtensor, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3361 | float qScale, |
| 3362 | int32_t qOffset) |
| 3363 | { |
| 3364 | armnn::TensorInfo inputTensorInfo({ 2, 3, 2 }, armnn::GetDataType<T>()); |
| 3365 | |
| 3366 | auto input0 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3367 | // Batch 0, Channel 0 |
| 3368 | 1.0f, 2.0f, |
| 3369 | |
| 3370 | // Batch 0, Channel 1 |
| 3371 | 3.0f, 4.0f, |
| 3372 | |
| 3373 | // Batch 0, Channel 2 |
| 3374 | 5.0f, 6.0f, |
| 3375 | |
| 3376 | // Batch 1, Channel 0 |
| 3377 | 19.0f, 20.0f, |
| 3378 | |
| 3379 | // Batch 1, Channel 1 |
| 3380 | 21.0f, 22.0f, |
| 3381 | |
| 3382 | // Batch 1, Channel 2 |
| 3383 | 23.0f, 24.0f |
| 3384 | })); |
| 3385 | |
| 3386 | auto input1 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3387 | // Batch 0, Channel 0 |
| 3388 | 7.0f, 8.0f, |
| 3389 | |
| 3390 | // Batch 0, Channel 1 |
| 3391 | 9.0f, 10.0f, |
| 3392 | |
| 3393 | // Batch 0, Channel 2 |
| 3394 | 11.0f, 12.0f, |
| 3395 | |
| 3396 | // Batch 1, Channel 0 |
| 3397 | 25.0f, 26.0f, |
| 3398 | |
| 3399 | // Batch 1, Channel 1 |
| 3400 | 27.0f, 28.0f, |
| 3401 | |
| 3402 | // Batch 1, Channel 2 |
| 3403 | 29.0f, 30.0f |
| 3404 | })); |
| 3405 | |
| 3406 | auto input2 = MakeTensor<T, 3>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3407 | // Batch 0, Channel 0 |
| 3408 | 13.0f, 14.0f, |
| 3409 | |
| 3410 | // Batch 0, Channel 1 |
| 3411 | 15.0f, 16.0f, |
| 3412 | |
| 3413 | // Batch 0, Channel 2 |
| 3414 | 17.0f, 18.0f, |
| 3415 | |
| 3416 | // Batch 1, Channel 0 |
| 3417 | 31.0f, 32.0f, |
| 3418 | |
| 3419 | // Batch 1, Channel 1 |
| 3420 | 33.0f, 34.0f, |
| 3421 | |
| 3422 | // Batch 1, Channel 2 |
| 3423 | 35.0f, 36.0f |
| 3424 | })); |
| 3425 | |
| 3426 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 3427 | |
| 3428 | std::vector<T> output; |
| 3429 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3430 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3431 | { inputTensorInfo, inputTensorInfo, inputTensorInfo }, |
| 3432 | { input0.data(), input1.data(), input2.data() }, |
| 3433 | outputTensorInfo, |
| 3434 | output.data(), |
| 3435 | dimension, |
| 3436 | useSubtensor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3437 | |
| 3438 | result.output = MakeTensor<T, 3>(outputTensorInfo, output); |
| 3439 | return result; |
| 3440 | } |
| 3441 | |
| 3442 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3443 | LayerTestResult<T, 3> Concatenation3dDim0TestImpl( |
| 3444 | armnn::IWorkloadFactory& workloadFactory, |
| 3445 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3446 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3447 | int32_t qOffset) |
| 3448 | { |
| 3449 | armnn::TensorInfo outputTensorInfo({ 6, 3, 2 }, armnn::GetDataType<T>()); |
| 3450 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3451 | LayerTestResult<T, 3> result = |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3452 | Concatenation3dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 0, true, qScale, qOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 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 1, Channel 0 |
| 3464 | 19.0f, 20.0f, |
| 3465 | |
| 3466 | // Batch 1, Channel 1 |
| 3467 | 21.0f, 22.0f, |
| 3468 | |
| 3469 | // Batch 1, Channel 2 |
| 3470 | 23.0f, 24.0f, |
| 3471 | |
| 3472 | // Batch 2, Channel 0 |
| 3473 | 7.0f, 8.0f, |
| 3474 | |
| 3475 | // Batch 2, Channel 1 |
| 3476 | 9.0f, 10.0f, |
| 3477 | |
| 3478 | // Batch 2, Channel 2 |
| 3479 | 11.0f, 12.0f, |
| 3480 | |
| 3481 | // Batch 3, Channel 0 |
| 3482 | 25.0f, 26.0f, |
| 3483 | |
| 3484 | // Batch 3, Channel 1 |
| 3485 | 27.0f, 28.0f, |
| 3486 | |
| 3487 | // Batch 3, Channel 2 |
| 3488 | 29.0f, 30.0f, |
| 3489 | |
| 3490 | // Batch 4, Channel 0 |
| 3491 | 13.0f, 14.0f, |
| 3492 | |
| 3493 | // Batch 4, Channel 1 |
| 3494 | 15.0f, 16.0f, |
| 3495 | |
| 3496 | // Batch 4, Channel 2 |
| 3497 | 17.0f, 18.0f, |
| 3498 | |
| 3499 | // Batch 5, Channel 0 |
| 3500 | 31.0f, 32.0f, |
| 3501 | |
| 3502 | // Batch 5, Channel 1 |
| 3503 | 33.0f, 34.0f, |
| 3504 | |
| 3505 | // Batch 5, Channel 2 |
| 3506 | 35.0f, 36.0f |
| 3507 | })); |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3508 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3509 | return result; |
| 3510 | } |
| 3511 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3512 | LayerTestResult<float, 3> Concatenation3dDim0Test( |
| 3513 | armnn::IWorkloadFactory& workloadFactory, |
| 3514 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3515 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3516 | return Concatenation3dDim0TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3517 | } |
| 3518 | |
| 3519 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3520 | LayerTestResult<T, 3> Concatenation3dDim1TestImpl( |
| 3521 | armnn::IWorkloadFactory& workloadFactory, |
| 3522 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3523 | float qScale, |
| 3524 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3525 | { |
| 3526 | armnn::TensorInfo outputTensorInfo({ 2, 9, 2 }, armnn::GetDataType<T>()); |
| 3527 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3528 | LayerTestResult<T, 3> result = |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3529 | Concatenation3dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 1, true, qScale, qOffset); |
| 3530 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3531 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3532 | // Batch 0, Channel 0 |
| 3533 | 1.0f, 2.0f, |
| 3534 | |
| 3535 | // Batch 0, Channel 1 |
| 3536 | 3.0f, 4.0f, |
| 3537 | |
| 3538 | // Batch 0, Channel 2 |
| 3539 | 5.0f, 6.0f, |
| 3540 | |
| 3541 | // Batch 0, Channel 3 |
| 3542 | 7.0f, 8.0f, |
| 3543 | |
| 3544 | // Batch 0, Channel 4 |
| 3545 | 9.0f, 10.0f, |
| 3546 | |
| 3547 | // Batch 0, Channel 5 |
| 3548 | 11.0f, 12.0f, |
| 3549 | |
| 3550 | // Batch 0, Channel 6 |
| 3551 | 13.0f, 14.0f, |
| 3552 | |
| 3553 | // Batch 0, Channel 7 |
| 3554 | 15.0f, 16.0f, |
| 3555 | |
| 3556 | // Batch 0, Channel 8 |
| 3557 | 17.0f, 18.0f, |
| 3558 | |
| 3559 | // Batch 1, Channel 0 |
| 3560 | 19.0f, 20.0f, |
| 3561 | |
| 3562 | // Batch 1, Channel 1 |
| 3563 | 21.0f, 22.0f, |
| 3564 | |
| 3565 | // Batch 1, Channel 2 |
| 3566 | 23.0f, 24.0f, |
| 3567 | |
| 3568 | // Batch 1, Channel 3 |
| 3569 | 25.0f, 26.0f, |
| 3570 | |
| 3571 | // Batch 1, Channel 4 |
| 3572 | 27.0f, 28.0f, |
| 3573 | |
| 3574 | // Batch 1, Channel 5 |
| 3575 | 29.0f, 30.0f, |
| 3576 | |
| 3577 | // Batch 1, Channel 6 |
| 3578 | 31.0f, 32.0f, |
| 3579 | |
| 3580 | // Batch 1, Channel 7 |
| 3581 | 33.0f, 34.0f, |
| 3582 | |
| 3583 | // Batch 1, Channel 8 |
| 3584 | 35.0f, 36.0f |
| 3585 | })); |
| 3586 | |
| 3587 | return result; |
| 3588 | } |
| 3589 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3590 | LayerTestResult<float, 3> Concatenation3dDim1Test( |
| 3591 | armnn::IWorkloadFactory& workloadFactory, |
| 3592 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3593 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3594 | return Concatenation3dDim1TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3595 | } |
| 3596 | |
| 3597 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3598 | LayerTestResult<T, 3> Concatenation3dDim2TestImpl( |
| 3599 | armnn::IWorkloadFactory& workloadFactory, |
| 3600 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3601 | bool useSubtensor, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3602 | float qScale, |
| 3603 | int32_t qOffset) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3604 | { |
| 3605 | armnn::TensorInfo outputTensorInfo({ 2, 3, 6 }, armnn::GetDataType<T>()); |
| 3606 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3607 | LayerTestResult<T, 3> result = |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3608 | Concatenation3dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 2, useSubtensor, qScale, qOffset); |
| 3609 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3610 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3611 | // Batch 0, Channel 0 |
| 3612 | 1.0f, 2.0f, 7.0f, 8.0f, 13.0f, 14.0f, |
| 3613 | |
| 3614 | // Batch 0, Channel 1 |
| 3615 | 3.0f, 4.0f, 9.0f, 10.0f, 15.0f, 16.0f, |
| 3616 | |
| 3617 | // Batch 0, Channel 2 |
| 3618 | 5.0f, 6.0f, 11.0f, 12.0f, 17.0f, 18.0f, |
| 3619 | |
| 3620 | // Batch 1, Channel 0 |
| 3621 | 19.0f, 20.0f, 25.0f, 26.0f, 31.0f, 32.0f, |
| 3622 | |
| 3623 | // Batch 1, Channel 1 |
| 3624 | 21.0f, 22.0f, 27.0f, 28.0f, 33.0f, 34.0f, |
| 3625 | |
| 3626 | // Batch 1, Channel 2 |
| 3627 | 23.0f, 24.0f, 29.0f, 30.0f, 35.0f, 36.0f, |
| 3628 | })); |
| 3629 | |
| 3630 | return result; |
| 3631 | } |
| 3632 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3633 | LayerTestResult<float, 3> Concatenation3dDim2Test( |
| 3634 | armnn::IWorkloadFactory& workloadFactory, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3635 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3636 | bool useSubtensor) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3637 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3638 | return Concatenation3dDim2TestImpl<float>(workloadFactory, memoryManager, useSubtensor, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3639 | } |
| 3640 | |
| 3641 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3642 | LayerTestResult<T, 3> Concatenation3dDim0DiffInputDimsTestImpl( |
| 3643 | armnn::IWorkloadFactory& workloadFactory, |
| 3644 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3645 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3646 | int32_t qOffset) |
| 3647 | { |
| 3648 | armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, armnn::GetDataType<T>()); |
| 3649 | auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3650 | // Batch 0, Channel 0 |
| 3651 | 1.0f, 2.0f, |
| 3652 | |
| 3653 | // Batch 0, Channel 1 |
| 3654 | 3.0f, 4.0f, |
| 3655 | |
| 3656 | // Batch 0, Channel 2 |
| 3657 | 5.0f, 6.0f, |
| 3658 | |
| 3659 | // Batch 1, Channel 0 |
| 3660 | 19.0f, 20.0f, |
| 3661 | |
| 3662 | // Batch 1, Channel 1 |
| 3663 | 21.0f, 22.0f, |
| 3664 | |
| 3665 | // Batch 1, Channel 2 |
| 3666 | 23.0f, 24.0f |
| 3667 | })); |
| 3668 | |
| 3669 | armnn::TensorInfo input1TensorInfo({ 1, 3, 2 }, armnn::GetDataType<T>()); |
| 3670 | auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3671 | // Batch 0, Channel 0 |
| 3672 | 7.0f, 8.0f, |
| 3673 | |
| 3674 | // Batch 0, Channel 1 |
| 3675 | 9.0f, 10.0f, |
| 3676 | |
| 3677 | // Batch 0, Channel 2 |
| 3678 | 11.0f, 12.0f, |
| 3679 | })); |
| 3680 | |
| 3681 | armnn::TensorInfo input2TensorInfo({ 3, 3, 2 }, armnn::GetDataType<T>()); |
| 3682 | auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3683 | // Batch 0, Channel 0 |
| 3684 | 25.0f, 26.0f, |
| 3685 | |
| 3686 | // Batch 0, Channel 1 |
| 3687 | 27.0f, 28.0f, |
| 3688 | |
| 3689 | // Batch 0, Channel 2 |
| 3690 | 29.0f, 30.0f, |
| 3691 | |
| 3692 | // Batch 1, Channel 0 |
| 3693 | 13.0f, 14.0f, |
| 3694 | |
| 3695 | // Batch 1, Channel 1 |
| 3696 | 15.0f, 16.0f, |
| 3697 | |
| 3698 | // Batch 1, Channel 2 |
| 3699 | 17.0f, 18.0f, |
| 3700 | |
| 3701 | // Batch 2, Channel 0 |
| 3702 | 31.0f, 32.0f, |
| 3703 | |
| 3704 | // Batch 2, Channel 1 |
| 3705 | 33.0f, 34.0f, |
| 3706 | |
| 3707 | // Batch 2, Channel 2 |
| 3708 | 35.0f, 36.0f |
| 3709 | })); |
| 3710 | |
| 3711 | armnn::TensorInfo outputTensorInfo({ 6, 3, 2 }, armnn::GetDataType<T>()); |
| 3712 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 3713 | |
| 3714 | std::vector<T> output; |
| 3715 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3716 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3717 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 3718 | { input0.data(), input1.data(), input2.data() }, |
| 3719 | outputTensorInfo, |
| 3720 | output.data(), |
| 3721 | 0, |
| 3722 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3723 | |
| 3724 | result.output = MakeTensor<T, 3>(outputTensorInfo, output); |
| 3725 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3726 | // Batch 0, Channel 0 |
| 3727 | 1.0f, 2.0f, |
| 3728 | |
| 3729 | // Batch 0, Channel 1 |
| 3730 | 3.0f, 4.0f, |
| 3731 | |
| 3732 | // Batch 0, Channel 2 |
| 3733 | 5.0f, 6.0f, |
| 3734 | |
| 3735 | // Batch 1, Channel 0 |
| 3736 | 19.0f, 20.0f, |
| 3737 | |
| 3738 | // Batch 1, Channel 1 |
| 3739 | 21.0f, 22.0f, |
| 3740 | |
| 3741 | // Batch 1, Channel 2 |
| 3742 | 23.0f, 24.0f, |
| 3743 | |
| 3744 | // Batch 2, Channel 0 |
| 3745 | 7.0f, 8.0f, |
| 3746 | |
| 3747 | // Batch 2, Channel 1 |
| 3748 | 9.0f, 10.0f, |
| 3749 | |
| 3750 | // Batch 2, Channel 2 |
| 3751 | 11.0f, 12.0f, |
| 3752 | |
| 3753 | // Batch 3, Channel 0 |
| 3754 | 25.0f, 26.0f, |
| 3755 | |
| 3756 | // Batch 3, Channel 1 |
| 3757 | 27.0f, 28.0f, |
| 3758 | |
| 3759 | // Batch 3, Channel 2 |
| 3760 | 29.0f, 30.0f, |
| 3761 | |
| 3762 | // Batch 4, Channel 0 |
| 3763 | 13.0f, 14.0f, |
| 3764 | |
| 3765 | // Batch 4, Channel 1 |
| 3766 | 15.0f, 16.0f, |
| 3767 | |
| 3768 | // Batch 4, Channel 2 |
| 3769 | 17.0f, 18.0f, |
| 3770 | |
| 3771 | // Batch 5, Channel 0 |
| 3772 | 31.0f, 32.0f, |
| 3773 | |
| 3774 | // Batch 5, Channel 1 |
| 3775 | 33.0f, 34.0f, |
| 3776 | |
| 3777 | // Batch 5, Channel 2 |
| 3778 | 35.0f, 36.0f |
| 3779 | })); |
| 3780 | |
| 3781 | return result; |
| 3782 | } |
| 3783 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3784 | LayerTestResult<float, 3> Concatenation3dDim0DiffInputDimsTest( |
| 3785 | armnn::IWorkloadFactory& workloadFactory, |
| 3786 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3787 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3788 | return Concatenation3dDim0DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3789 | } |
| 3790 | |
| 3791 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3792 | LayerTestResult<T, 3> Concatenation3dDim1DiffInputDimsTestImpl( |
| 3793 | armnn::IWorkloadFactory& workloadFactory, |
| 3794 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 3795 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3796 | int32_t qOffset) |
| 3797 | { |
| 3798 | armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, armnn::GetDataType<T>()); |
| 3799 | auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3800 | // Batch 0, Channel 0 |
| 3801 | 1.0f, 2.0f, |
| 3802 | |
| 3803 | // Batch 0, Channel 1 |
| 3804 | 3.0f, 4.0f, |
| 3805 | |
| 3806 | // Batch 0, Channel 2 |
| 3807 | 5.0f, 6.0f, |
| 3808 | |
| 3809 | // Batch 1, Channel 0 |
| 3810 | 19.0f, 20.0f, |
| 3811 | |
| 3812 | // Batch 1, Channel 1 |
| 3813 | 21.0f, 22.0f, |
| 3814 | |
| 3815 | // Batch 1, Channel 2 |
| 3816 | 23.0f, 24.0f |
| 3817 | })); |
| 3818 | |
| 3819 | armnn::TensorInfo input1TensorInfo({ 2, 4, 2 }, armnn::GetDataType<T>()); |
| 3820 | auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3821 | // Batch 0, Channel 0 |
| 3822 | 7.0f, 8.0f, |
| 3823 | |
| 3824 | // Batch 0, Channel 1 |
| 3825 | 9.0f, 10.0f, |
| 3826 | |
| 3827 | // Batch 0, Channel 2 |
| 3828 | 11.0f, 12.0f, |
| 3829 | |
| 3830 | // Batch 0, Channel 3 |
| 3831 | 25.0f, 26.0f, |
| 3832 | |
| 3833 | // Batch 1, Channel 0 |
| 3834 | 27.0f, 28.0f, |
| 3835 | |
| 3836 | // Batch 1, Channel 1 |
| 3837 | 29.0f, 30.0f, |
| 3838 | |
| 3839 | // Batch 1, Channel 2 |
| 3840 | 13.0f, 14.0f, |
| 3841 | |
| 3842 | // Batch 1, Channel 3 |
| 3843 | 15.0f, 16.0f, |
| 3844 | })); |
| 3845 | |
| 3846 | armnn::TensorInfo input2TensorInfo({ 2, 1, 2 }, armnn::GetDataType<T>()); |
| 3847 | auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3848 | // Batch 0, Channel 0 |
| 3849 | 17.0f, 18.0f, |
| 3850 | |
| 3851 | // Batch 1, Channel 0 |
| 3852 | 31.0f, 32.0f, |
| 3853 | })); |
| 3854 | |
| 3855 | armnn::TensorInfo outputTensorInfo({ 2, 8, 2 }, armnn::GetDataType<T>()); |
| 3856 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 3857 | |
| 3858 | std::vector<T> output; |
| 3859 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3860 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3861 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 3862 | { input0.data(), input1.data(), input2.data() }, |
| 3863 | outputTensorInfo, |
| 3864 | output.data(), |
| 3865 | 1, |
| 3866 | true); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3867 | |
| 3868 | result.output = MakeTensor<T, 3>(outputTensorInfo, output); |
| 3869 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3870 | // Batch 0, Channel 0 |
| 3871 | 1.0f, 2.0f, |
| 3872 | |
| 3873 | // Batch 0, Channel 1 |
| 3874 | 3.0f, 4.0f, |
| 3875 | |
| 3876 | // Batch 0, Channel 2 |
| 3877 | 5.0f, 6.0f, |
| 3878 | |
| 3879 | // Batch 0, Channel 3 |
| 3880 | 7.0f, 8.0f, |
| 3881 | |
| 3882 | // Batch 0, Channel 4 |
| 3883 | 9.0f, 10.0f, |
| 3884 | |
| 3885 | // Batch 0, Channel 5 |
| 3886 | 11.0f, 12.0f, |
| 3887 | |
| 3888 | // Batch 0, Channel 6 |
| 3889 | 25.0f, 26.0f, |
| 3890 | |
| 3891 | // Batch 0, Channel 7 |
| 3892 | 17.0f, 18.0f, |
| 3893 | |
| 3894 | // Batch 1, Channel 0 |
| 3895 | 19.0f, 20.0f, |
| 3896 | |
| 3897 | // Batch 1, Channel 1 |
| 3898 | 21.0f, 22.0f, |
| 3899 | |
| 3900 | // Batch 1, Channel 2 |
| 3901 | 23.0f, 24.0f, |
| 3902 | |
| 3903 | // Batch 1, Channel 3 |
| 3904 | 27.0f, 28.0f, |
| 3905 | |
| 3906 | // Batch 1, Channel 4 |
| 3907 | 29.0f, 30.0f, |
| 3908 | |
| 3909 | // Batch 1, Channel 5 |
| 3910 | 13.0f, 14.0f, |
| 3911 | |
| 3912 | // Batch 1, Channel 6 |
| 3913 | 15.0f, 16.0f, |
| 3914 | |
| 3915 | // Batch 1, Channel 7 |
| 3916 | 31.0f, 32.0f, |
| 3917 | })); |
| 3918 | |
| 3919 | return result; |
| 3920 | } |
| 3921 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3922 | LayerTestResult<float, 3> Concatenation3dDim1DiffInputDimsTest( |
| 3923 | armnn::IWorkloadFactory& workloadFactory, |
| 3924 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3925 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3926 | return Concatenation3dDim1DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3927 | } |
| 3928 | |
| 3929 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3930 | LayerTestResult<T, 3> Concatenation3dDim2DiffInputDimsTestImpl( |
| 3931 | armnn::IWorkloadFactory& workloadFactory, |
| 3932 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 3933 | bool useSubtensor, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 3934 | float qScale, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 3935 | int32_t qOffset) |
| 3936 | { |
| 3937 | armnn::TensorInfo input0TensorInfo({ 2, 3, 2 }, armnn::GetDataType<T>()); |
| 3938 | auto input0 = MakeTensor<T, 3>(input0TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3939 | // Batch 0, Channel 0 |
| 3940 | 1.0f, 2.0f, |
| 3941 | |
| 3942 | // Batch 0, Channel 1 |
| 3943 | 3.0f, 4.0f, |
| 3944 | |
| 3945 | // Batch 0, Channel 2 |
| 3946 | 5.0f, 6.0f, |
| 3947 | |
| 3948 | // Batch 1, Channel 0 |
| 3949 | 19.0f, 20.0f, |
| 3950 | |
| 3951 | // Batch 1, Channel 1 |
| 3952 | 21.0f, 22.0f, |
| 3953 | |
| 3954 | // Batch 1, Channel 2 |
| 3955 | 23.0f, 24.0f |
| 3956 | })); |
| 3957 | |
| 3958 | armnn::TensorInfo input1TensorInfo({ 2, 3, 1 }, armnn::GetDataType<T>()); |
| 3959 | auto input1 = MakeTensor<T, 3>(input1TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3960 | // Batch 0, Channel 0 |
| 3961 | 7.0f, |
| 3962 | |
| 3963 | // Batch 0, Channel 1 |
| 3964 | 9.0f, |
| 3965 | |
| 3966 | // Batch 0, Channel 2 |
| 3967 | 11.0f, |
| 3968 | |
| 3969 | // Batch 1, Channel 0 |
| 3970 | 25.0f, |
| 3971 | |
| 3972 | // Batch 1, Channel 1 |
| 3973 | 27.0f, |
| 3974 | |
| 3975 | // Batch 1, Channel 2 |
| 3976 | 29.0f |
| 3977 | })); |
| 3978 | |
| 3979 | armnn::TensorInfo input2TensorInfo({ 2, 3, 3 }, armnn::GetDataType<T>()); |
| 3980 | auto input2 = MakeTensor<T, 3>(input2TensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 3981 | // Batch 0, Channel 0 |
| 3982 | 13.0f, 14.0f, 50.0f, |
| 3983 | |
| 3984 | // Batch 0, Channel 1 |
| 3985 | 15.0f, 16.0f, 51.0f, |
| 3986 | |
| 3987 | // Batch 0, Channel 2 |
| 3988 | 17.0f, 18.0f, 52.0f, |
| 3989 | |
| 3990 | // Batch 1, Channel 0 |
| 3991 | 31.0f, 32.0f, 53.0f, |
| 3992 | |
| 3993 | // Batch 1, Channel 1 |
| 3994 | 33.0f, 34.0f, 54.0f, |
| 3995 | |
| 3996 | // Batch 1, Channel 2 |
| 3997 | 35.0f, 36.0f, 55.0f, |
| 3998 | })); |
| 3999 | |
| 4000 | armnn::TensorInfo outputTensorInfo({ 2, 3, 6 }, armnn::GetDataType<T>()); |
| 4001 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 4002 | |
| 4003 | std::vector<T> output; |
| 4004 | output.resize(outputTensorInfo.GetNumElements()); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4005 | Concatenate<T>(workloadFactory, memoryManager, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 4006 | { input0TensorInfo, input1TensorInfo, input2TensorInfo }, |
| 4007 | { input0.data(), input1.data(), input2.data() }, |
| 4008 | outputTensorInfo, |
| 4009 | output.data(), |
| 4010 | 2, |
| 4011 | useSubtensor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4012 | |
| 4013 | result.output = MakeTensor<T, 3>(outputTensorInfo, output); |
| 4014 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4015 | // Batch 0, Channel 0 |
| 4016 | 1.0f, 2.0f, 7.0f, 13.0f, 14.0f, 50.0f, |
| 4017 | |
| 4018 | // Batch 0, Channel 1 |
| 4019 | 3.0f, 4.0f, 9.0f, 15.0f, 16.0f, 51.0f, |
| 4020 | |
| 4021 | // Batch 0, Channel 2 |
| 4022 | 5.0f, 6.0f, 11.0f, 17.0f, 18.0f, 52.0f, |
| 4023 | |
| 4024 | // Batch 1, Channel 0 |
| 4025 | 19.0f, 20.0f, 25.0f, 31.0f, 32.0f, 53.0f, |
| 4026 | |
| 4027 | // Batch 1, Channel 1 |
| 4028 | 21.0f, 22.0f, 27.0f, 33.0f, 34.0f, 54.0f, |
| 4029 | |
| 4030 | // Batch 1, Channel 2 |
| 4031 | 23.0f, 24.0f, 29.0f, 35.0f, 36.0f, 55.0f, |
| 4032 | })); |
| 4033 | |
| 4034 | return result; |
| 4035 | } |
| 4036 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4037 | LayerTestResult<float, 3> Concatenation3dDim2DiffInputDimsTest( |
| 4038 | armnn::IWorkloadFactory& workloadFactory, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 4039 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4040 | bool useSubtensor) |
| 4041 | { |
| 4042 | return Concatenation3dDim2DiffInputDimsTestImpl<float>(workloadFactory, memoryManager, useSubtensor, 0.0f, 0); |
| 4043 | } |
| 4044 | |
| 4045 | template <typename T> |
| 4046 | LayerTestResult<T, 4> Concatenation4dTestImpl( |
| 4047 | armnn::IWorkloadFactory& workloadFactory, |
| 4048 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4049 | const armnn::TensorInfo& outputTensorInfo, |
| 4050 | unsigned int dimension, |
| 4051 | bool useSubtensor, |
| 4052 | float qScale, |
| 4053 | int32_t qOffset) |
| 4054 | { |
| 4055 | armnn::TensorInfo inputTensorInfo({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4056 | |
| 4057 | auto input0 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4058 | 1.0f, 2.0f, |
| 4059 | 3.0f, 4.0f, |
| 4060 | 5.0f, 6.0f, |
| 4061 | 7.0f, 8.0f, |
| 4062 | 9.0f, 10.0f, |
| 4063 | 11.0f, 12.0f |
| 4064 | })); |
| 4065 | |
| 4066 | auto input1 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4067 | 11.0f, 12.0f, |
| 4068 | 13.0f, 14.0f, |
| 4069 | 15.0f, 16.0f, |
| 4070 | 17.0f, 18.0f, |
| 4071 | 19.0f, 20.0f, |
| 4072 | 21.0f, 22.0f |
| 4073 | })); |
| 4074 | |
| 4075 | auto input2 = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4076 | 21.0f, 22.0f, |
| 4077 | 23.0f, 24.0f, |
| 4078 | 25.0f, 26.0f, |
| 4079 | 27.0f, 28.0f, |
| 4080 | 29.0f, 30.0f, |
| 4081 | 31.0f, 32.0f |
| 4082 | })); |
| 4083 | |
| 4084 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 4085 | |
| 4086 | std::vector<T> output; |
| 4087 | output.resize(outputTensorInfo.GetNumElements()); |
| 4088 | |
| 4089 | Concatenate<T>(workloadFactory, |
| 4090 | memoryManager, |
| 4091 | {inputTensorInfo, inputTensorInfo, inputTensorInfo}, |
| 4092 | {input0.data(), input1.data(), input2.data()}, |
| 4093 | outputTensorInfo, |
| 4094 | output.data(), |
| 4095 | dimension, |
| 4096 | useSubtensor); |
| 4097 | |
| 4098 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 4099 | return result; |
| 4100 | } |
| 4101 | |
| 4102 | template <typename T> |
| 4103 | LayerTestResult<T, 4> Concatenation4dDim0TestImpl( |
| 4104 | armnn::IWorkloadFactory& workloadFactory, |
| 4105 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4106 | float qScale, |
| 4107 | int32_t qOffset) |
| 4108 | { |
| 4109 | armnn::TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4110 | |
| 4111 | LayerTestResult<T, 4> result = Concatenation4dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 0, |
| 4112 | true, qScale, qOffset); |
| 4113 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4114 | 1.0f, 2.0f, |
| 4115 | 3.0f, 4.0f, |
| 4116 | 5.0f, 6.0f, |
| 4117 | 7.0f, 8.0f, |
| 4118 | 9.0f, 10.0f, |
| 4119 | 11.0f, 12.0f, |
| 4120 | |
| 4121 | 11.0f, 12.0f, |
| 4122 | 13.0f, 14.0f, |
| 4123 | 15.0f, 16.0f, |
| 4124 | 17.0f, 18.0f, |
| 4125 | 19.0f, 20.0f, |
| 4126 | 21.0f, 22.0f, |
| 4127 | |
| 4128 | 21.0f, 22.0f, |
| 4129 | 23.0f, 24.0f, |
| 4130 | 25.0f, 26.0f, |
| 4131 | 27.0f, 28.0f, |
| 4132 | 29.0f, 30.0f, |
| 4133 | 31.0f, 32.0f |
| 4134 | })); |
| 4135 | return result; |
| 4136 | } |
| 4137 | |
| 4138 | LayerTestResult<float, 4> Concatenation4dDim0Test( |
| 4139 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4140 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4141 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 4142 | return Concatenation4dDim0TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 4143 | } |
| 4144 | |
| 4145 | template <typename T> |
| 4146 | LayerTestResult<T, 4> Concatenation4dDim1TestImpl( |
| 4147 | armnn::IWorkloadFactory& workloadFactory, |
| 4148 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4149 | float qScale, |
| 4150 | int32_t qOffset) |
| 4151 | { |
| 4152 | armnn::TensorInfo outputTensorInfo({ 1, 9, 2, 2 }, armnn::GetDataType<T>()); |
| 4153 | |
| 4154 | LayerTestResult<T, 4> result = Concatenation4dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 1, |
| 4155 | true, qScale, qOffset); |
| 4156 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4157 | 1.0f, 2.0f, |
| 4158 | 3.0f, 4.0f, |
| 4159 | 5.0f, 6.0f, |
| 4160 | 7.0f, 8.0f, |
| 4161 | 9.0f, 10.0f, |
| 4162 | 11.0f, 12.0f, |
| 4163 | |
| 4164 | 11.0f, 12.0f, |
| 4165 | 13.0f, 14.0f, |
| 4166 | 15.0f, 16.0f, |
| 4167 | 17.0f, 18.0f, |
| 4168 | 19.0f, 20.0f, |
| 4169 | 21.0f, 22.0f, |
| 4170 | |
| 4171 | 21.0f, 22.0f, |
| 4172 | 23.0f, 24.0f, |
| 4173 | 25.0f, 26.0f, |
| 4174 | 27.0f, 28.0f, |
| 4175 | 29.0f, 30.0f, |
| 4176 | 31.0f, 32.0f |
| 4177 | })); |
| 4178 | |
| 4179 | return result; |
| 4180 | } |
| 4181 | |
| 4182 | LayerTestResult<float, 4> Concatenation4dDim1Test( |
| 4183 | armnn::IWorkloadFactory& workloadFactory, |
| 4184 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 4185 | { |
| 4186 | return Concatenation4dDim1TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 4187 | } |
| 4188 | |
| 4189 | template <typename T> |
| 4190 | LayerTestResult<T, 4> Concatenation4dDim2TestImpl( |
| 4191 | armnn::IWorkloadFactory& workloadFactory, |
| 4192 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4193 | float qScale, |
| 4194 | int32_t qOffset) |
| 4195 | { |
| 4196 | armnn::TensorInfo outputTensorInfo({ 1, 3, 6, 2 }, armnn::GetDataType<T>()); |
| 4197 | |
| 4198 | LayerTestResult<T, 4> result = Concatenation4dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 2, |
| 4199 | true, qScale, qOffset); |
| 4200 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4201 | 1.0f, 2.0f, |
| 4202 | 3.0f, 4.0f, |
| 4203 | 11.0f, 12.0f, |
| 4204 | 13.0f, 14.0f, |
| 4205 | 21.0f, 22.0f, |
| 4206 | 23.0f, 24.0f, |
| 4207 | |
| 4208 | 5.0f, 6.0f, |
| 4209 | 7.0f, 8.0f, |
| 4210 | 15.0f, 16.0f, |
| 4211 | 17.0f, 18.0f, |
| 4212 | 25.0f, 26.0f, |
| 4213 | 27.0f, 28.0f, |
| 4214 | |
| 4215 | 9.0f, 10.0f, |
| 4216 | 11.0f, 12.0f, |
| 4217 | 19.0f, 20.0f, |
| 4218 | 21.0f, 22.0f, |
| 4219 | 29.0f, 30.0f, |
| 4220 | 31.0f, 32.0f |
| 4221 | })); |
| 4222 | |
| 4223 | return result; |
| 4224 | } |
| 4225 | |
| 4226 | LayerTestResult<float, 4> Concatenation4dDim2Test( |
| 4227 | armnn::IWorkloadFactory& workloadFactory, |
| 4228 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 4229 | { |
| 4230 | return Concatenation4dDim2TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 4231 | } |
| 4232 | |
| 4233 | template <typename T> |
| 4234 | LayerTestResult<T, 4> Concatenation4dDim3TestImpl( |
| 4235 | armnn::IWorkloadFactory& workloadFactory, |
| 4236 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4237 | float qScale, |
| 4238 | int32_t qOffset, |
| 4239 | bool useSubtensor) |
| 4240 | { |
| 4241 | armnn::TensorInfo outputTensorInfo({ 1, 3, 2, 6 }, armnn::GetDataType<T>()); |
| 4242 | |
| 4243 | LayerTestResult<T, 4> result = Concatenation4dTestImpl<T>(workloadFactory, memoryManager, outputTensorInfo, 3, |
| 4244 | useSubtensor, qScale, qOffset); |
| 4245 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4246 | 1.0f, 2.0f, |
| 4247 | 11.0f, 12.0f, |
| 4248 | 21.0f, 22.0f, |
| 4249 | 3.0f, 4.0f, |
| 4250 | 13.0f, 14.0f, |
| 4251 | 23.0f, 24.0f, |
| 4252 | |
| 4253 | 5.0f, 6.0f, |
| 4254 | 15.0f, 16.0f, |
| 4255 | 25.0f, 26.0f, |
| 4256 | 7.0f, 8.0f, |
| 4257 | 17.0f, 18.0f, |
| 4258 | 27.0f, 28.0f, |
| 4259 | |
| 4260 | 9.0f, 10.0f, |
| 4261 | 19.0f, 20.0f, |
| 4262 | 29.0f, 30.0f, |
| 4263 | 11.0f, 12.0f, |
| 4264 | 21.0f, 22.0f, |
| 4265 | 31.0f, 32.0f |
| 4266 | })); |
| 4267 | |
| 4268 | return result; |
| 4269 | } |
| 4270 | |
| 4271 | LayerTestResult<float, 4> Concatenation4dDim3Test( |
| 4272 | armnn::IWorkloadFactory& workloadFactory, |
| 4273 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4274 | bool useSubtensor) |
| 4275 | { |
| 4276 | return Concatenation4dDim3TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0, useSubtensor); |
| 4277 | } |
| 4278 | |
| 4279 | template <typename T> |
| 4280 | LayerTestResult<T, 4> Concatenation4dDiffShapeDim0TestImpl( |
| 4281 | armnn::IWorkloadFactory& workloadFactory, |
| 4282 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4283 | float qScale, |
| 4284 | int32_t qOffset) |
| 4285 | { |
| 4286 | unsigned int dimension = 0; |
| 4287 | armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4288 | |
| 4289 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { |
| 4290 | 1.0f, 2.0f, |
| 4291 | 3.0f, 4.0f, |
| 4292 | 5.0f, 6.0f, |
| 4293 | 7.0f, 8.0f, |
| 4294 | 9.0f, 10.0f, |
| 4295 | 11.0f, 12.0f |
| 4296 | })); |
| 4297 | |
| 4298 | armnn::TensorInfo inputTensorInfo1({ 2, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4299 | |
| 4300 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { |
| 4301 | 11.0f, 12.0f, |
| 4302 | 13.0f, 14.0f, |
| 4303 | 15.0f, 16.0f, |
| 4304 | 17.0f, 18.0f, |
| 4305 | 19.0f, 20.0f, |
| 4306 | 21.0f, 22.0f, |
| 4307 | |
| 4308 | 21.0f, 22.0f, |
| 4309 | 23.0f, 24.0f, |
| 4310 | 25.0f, 26.0f, |
| 4311 | 27.0f, 28.0f, |
| 4312 | 29.0f, 30.0f, |
| 4313 | 31.0f, 32.0f |
| 4314 | |
| 4315 | })); |
| 4316 | |
| 4317 | armnn::TensorInfo outputTensorInfo({ 3, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4318 | |
| 4319 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 4320 | |
| 4321 | std::vector<T> output; |
| 4322 | output.resize(outputTensorInfo.GetNumElements()); |
| 4323 | Concatenate<T>(workloadFactory, |
| 4324 | memoryManager, |
| 4325 | {inputTensorInfo0, inputTensorInfo1}, |
| 4326 | {input0.data(), input1.data()}, |
| 4327 | outputTensorInfo, |
| 4328 | output.data(), |
| 4329 | dimension, |
| 4330 | true); |
| 4331 | |
| 4332 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 4333 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4334 | 1.0f, 2.0f, |
| 4335 | 3.0f, 4.0f, |
| 4336 | 5.0f, 6.0f, |
| 4337 | 7.0f, 8.0f, |
| 4338 | 9.0f, 10.0f, |
| 4339 | 11.0f, 12.0f, |
| 4340 | |
| 4341 | 11.0f, 12.0f, |
| 4342 | 13.0f, 14.0f, |
| 4343 | 15.0f, 16.0f, |
| 4344 | 17.0f, 18.0f, |
| 4345 | 19.0f, 20.0f, |
| 4346 | 21.0f, 22.0f, |
| 4347 | |
| 4348 | 21.0f, 22.0f, |
| 4349 | 23.0f, 24.0f, |
| 4350 | 25.0f, 26.0f, |
| 4351 | 27.0f, 28.0f, |
| 4352 | 29.0f, 30.0f, |
| 4353 | 31.0f, 32.0f |
| 4354 | })); |
| 4355 | |
| 4356 | return result; |
| 4357 | } |
| 4358 | |
| 4359 | LayerTestResult<float, 4> Concatenation4dDiffShapeDim0Test( |
| 4360 | armnn::IWorkloadFactory& workloadFactory, |
| 4361 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 4362 | { |
| 4363 | return Concatenation4dDiffShapeDim0TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 4364 | } |
| 4365 | |
| 4366 | template <typename T> |
| 4367 | LayerTestResult<T, 4> Concatenation4dDiffShapeDim1TestImpl( |
| 4368 | armnn::IWorkloadFactory& workloadFactory, |
| 4369 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4370 | float qScale, |
| 4371 | int32_t qOffset) |
| 4372 | { |
| 4373 | unsigned int dimension = 1; |
| 4374 | armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4375 | |
| 4376 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { |
| 4377 | 1.0f, 2.0f, |
| 4378 | 3.0f, 4.0f, |
| 4379 | 5.0f, 6.0f, |
| 4380 | 7.0f, 8.0f, |
| 4381 | 9.0f, 10.0f, |
| 4382 | 11.0f, 12.0f |
| 4383 | })); |
| 4384 | |
| 4385 | armnn::TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, armnn::GetDataType<T>()); |
| 4386 | |
| 4387 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { |
| 4388 | 11.0f, 12.0f, |
| 4389 | 13.0f, 14.0f, |
| 4390 | 15.0f, 16.0f, |
| 4391 | 17.0f, 18.0f, |
| 4392 | |
| 4393 | })); |
| 4394 | |
| 4395 | armnn::TensorInfo outputTensorInfo({ 1, 5, 2, 2 }, armnn::GetDataType<T>()); |
| 4396 | |
| 4397 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 4398 | |
| 4399 | std::vector<T> output; |
| 4400 | output.resize(outputTensorInfo.GetNumElements()); |
| 4401 | Concatenate<T>(workloadFactory, |
| 4402 | memoryManager, |
| 4403 | {inputTensorInfo0, inputTensorInfo1}, |
| 4404 | {input0.data(), input1.data()}, |
| 4405 | outputTensorInfo, |
| 4406 | output.data(), |
| 4407 | dimension, |
| 4408 | true); |
| 4409 | |
| 4410 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 4411 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4412 | 1.0f, 2.0f, |
| 4413 | 3.0f, 4.0f, |
| 4414 | 5.0f, 6.0f, |
| 4415 | 7.0f, 8.0f, |
| 4416 | 9.0f, 10.0f, |
| 4417 | 11.0f, 12.0f, |
| 4418 | 11.0f, 12.0f, |
| 4419 | 13.0f, 14.0f, |
| 4420 | 15.0f, 16.0f, |
| 4421 | 17.0f, 18.0f |
| 4422 | })); |
| 4423 | |
| 4424 | return result; |
| 4425 | } |
| 4426 | |
| 4427 | LayerTestResult<float, 4> Concatenation4dDiffShapeDim1Test( |
| 4428 | armnn::IWorkloadFactory& workloadFactory, |
| 4429 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 4430 | { |
| 4431 | return Concatenation4dDiffShapeDim1TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 4432 | } |
| 4433 | |
| 4434 | template <typename T> |
| 4435 | LayerTestResult<T, 4> Concatenation4dDiffShapeDim2TestImpl( |
| 4436 | armnn::IWorkloadFactory& workloadFactory, |
| 4437 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4438 | float qScale, |
| 4439 | int32_t qOffset) |
| 4440 | { |
| 4441 | unsigned int dimension = 2; |
| 4442 | armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4443 | |
| 4444 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { |
| 4445 | 1.0f, 2.0f, |
| 4446 | 3.0f, 4.0f, |
| 4447 | 5.0f, 6.0f, |
| 4448 | 7.0f, 8.0f, |
| 4449 | 9.0f, 10.0f, |
| 4450 | 11.0f, 12.0f |
| 4451 | })); |
| 4452 | |
| 4453 | armnn::TensorInfo inputTensorInfo1({ 1, 3, 3, 2 }, armnn::GetDataType<T>()); |
| 4454 | |
| 4455 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { |
| 4456 | 11.0f, 12.0f, |
| 4457 | 13.0f, 14.0f, |
| 4458 | 15.0f, 16.0f, |
| 4459 | 17.0f, 18.0f, |
| 4460 | 19.0f, 20.0f, |
| 4461 | 21.0f, 22.0f, |
| 4462 | 23.0f, 24.0f, |
| 4463 | 25.0f, 26.0f, |
| 4464 | 27.0f, 28.0f |
| 4465 | })); |
| 4466 | |
| 4467 | armnn::TensorInfo outputTensorInfo({ 1, 3, 5, 2 }, armnn::GetDataType<T>()); |
| 4468 | |
| 4469 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 4470 | |
| 4471 | std::vector<T> output; |
| 4472 | output.resize(outputTensorInfo.GetNumElements()); |
| 4473 | Concatenate<T>(workloadFactory, |
| 4474 | memoryManager, |
| 4475 | {inputTensorInfo0, inputTensorInfo1}, |
| 4476 | {input0.data(), input1.data()}, |
| 4477 | outputTensorInfo, |
| 4478 | output.data(), |
| 4479 | dimension, |
| 4480 | true); |
| 4481 | |
| 4482 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 4483 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4484 | 1.0f, 2.0f, |
| 4485 | 3.0f, 4.0f, |
| 4486 | 11.0f, 12.0f, |
| 4487 | 13.0f, 14.0f, |
| 4488 | 15.0f, 16.0f, |
| 4489 | |
| 4490 | 5.0f, 6.0f, |
| 4491 | 7.0f, 8.0f, |
| 4492 | 17.0f, 18.0f, |
| 4493 | 19.0f, 20.0f, |
| 4494 | 21.0f, 22.0f, |
| 4495 | |
| 4496 | 9.0f, 10.0f, |
| 4497 | 11.0f, 12.0f, |
| 4498 | 23.0f, 24.0f, |
| 4499 | 25.0f, 26.0f, |
| 4500 | 27.0f, 28.0f |
| 4501 | })); |
| 4502 | |
| 4503 | return result; |
| 4504 | } |
| 4505 | |
| 4506 | LayerTestResult<float, 4> Concatenation4dDiffShapeDim2Test( |
| 4507 | armnn::IWorkloadFactory& workloadFactory, |
| 4508 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 4509 | { |
| 4510 | return Concatenation4dDiffShapeDim2TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
| 4511 | } |
| 4512 | |
| 4513 | template <typename T> |
| 4514 | LayerTestResult<T, 4> Concatenation4dDiffShapeDim3TestImpl( |
| 4515 | armnn::IWorkloadFactory& workloadFactory, |
| 4516 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4517 | float qScale, |
| 4518 | int32_t qOffset, |
| 4519 | bool useSubtensor) |
| 4520 | { |
| 4521 | unsigned int dimension = 3; |
| 4522 | armnn::TensorInfo inputTensorInfo0({ 1, 3, 2, 2 }, armnn::GetDataType<T>()); |
| 4523 | |
| 4524 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, QuantizedVector<T>(qScale, qOffset, { |
| 4525 | 1.0f, 2.0f, |
| 4526 | 3.0f, 4.0f, |
| 4527 | 5.0f, 6.0f, |
| 4528 | 7.0f, 8.0f, |
| 4529 | 9.0f, 10.0f, |
| 4530 | 11.0f, 12.0f |
| 4531 | })); |
| 4532 | |
| 4533 | armnn::TensorInfo inputTensorInfo1({ 1, 3, 2, 3 }, armnn::GetDataType<T>()); |
| 4534 | |
| 4535 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, QuantizedVector<T>(qScale, qOffset, { |
| 4536 | 11.0f, 12.0f, 13.0f, |
| 4537 | 14.0f, 15.0f, 16.0f, |
| 4538 | |
| 4539 | 17.0f, 18.0f, 19.0f, |
| 4540 | 20.0f, 21.0f, 22.0f, |
| 4541 | |
| 4542 | 23.0f, 24.0f, 25.0f, |
| 4543 | 26.0f, 27.0f, 28.0f |
| 4544 | })); |
| 4545 | |
| 4546 | armnn::TensorInfo outputTensorInfo({ 1, 3, 2, 5 }, armnn::GetDataType<T>()); |
| 4547 | |
| 4548 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 4549 | |
| 4550 | std::vector<T> output; |
| 4551 | output.resize(outputTensorInfo.GetNumElements()); |
| 4552 | Concatenate<T>(workloadFactory, |
| 4553 | memoryManager, |
| 4554 | {inputTensorInfo0, inputTensorInfo1}, |
| 4555 | {input0.data(), input1.data()}, |
| 4556 | outputTensorInfo, |
| 4557 | output.data(), |
| 4558 | dimension, |
| 4559 | useSubtensor); |
| 4560 | |
| 4561 | result.output = MakeTensor<T, 4>(outputTensorInfo, output); |
| 4562 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, { |
| 4563 | 1.0f, 2.0f, 11.0f, 12.0f, 13.0f, |
| 4564 | 3.0f, 4.0f, 14.0f, 15.0f, 16.0f, |
| 4565 | 5.0f, 6.0f, 17.0f, 18.0f, 19.0f, |
| 4566 | 7.0f, 8.0f, 20.0f, 21.0f, 22.0f, |
| 4567 | 9.0f, 10.0f, 23.0f, 24.0f, 25.0f, |
| 4568 | 11.0f, 12.0f, 26.0f, 27.0f, 28.0f |
| 4569 | })); |
| 4570 | |
| 4571 | return result; |
| 4572 | } |
| 4573 | |
| 4574 | LayerTestResult<float, 4> Concatenation4dDiffShapeDim3Test( |
| 4575 | armnn::IWorkloadFactory& workloadFactory, |
| 4576 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4577 | bool useSubtensor) |
| 4578 | { |
| 4579 | return Concatenation4dDiffShapeDim3TestImpl<float>(workloadFactory, memoryManager, 0.0f, 0, useSubtensor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4580 | } |
| 4581 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4582 | LayerTestResult<float, 4> ResizeBilinearNopTest( |
| 4583 | armnn::IWorkloadFactory& workloadFactory, |
| 4584 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4585 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4586 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4587 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); |
| 4588 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4589 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4590 | std::vector<float> inputData({ |
| 4591 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 4592 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 4593 | 3.0f, 4.0f, 5.0f, 6.0f, |
| 4594 | 4.0f, 5.0f, 6.0f, 7.0f, |
| 4595 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4596 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 4597 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 4598 | 3.0f, 4.0f, 5.0f, 6.0f, |
| 4599 | 4.0f, 5.0f, 6.0f, 7.0f |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4600 | }); |
| 4601 | |
| 4602 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4603 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4604 | { |
| 4605 | std::vector<float> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4606 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4607 | inputData = tmp; |
| 4608 | } |
| 4609 | |
| 4610 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4611 | |
| 4612 | LayerTestResult<float, 4> result(outputTensorInfo); |
| 4613 | result.outputExpected = input; |
| 4614 | |
| 4615 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4616 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4617 | |
| 4618 | armnn::ResizeBilinearQueueDescriptor descriptor; |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4619 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
| 4620 | armnn::WorkloadInfo info; |
| 4621 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4622 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4623 | |
| 4624 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4625 | |
| 4626 | inputHandle->Allocate(); |
| 4627 | outputHandle->Allocate(); |
| 4628 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4629 | |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4630 | workload->Execute(); |
| 4631 | |
| 4632 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4633 | return result; |
| 4634 | } |
| 4635 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4636 | LayerTestResult<float, 4> SimpleResizeBilinearTest( |
| 4637 | armnn::IWorkloadFactory& workloadFactory, |
| 4638 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4639 | const armnn::DataLayout dataLayout) |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4640 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4641 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 2, dataLayout); |
| 4642 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 1, 1, dataLayout); |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4643 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4644 | std::vector<float> inputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4645 | 1.0f, 255.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4646 | 200.0f, 250.0f, |
| 4647 | |
| 4648 | 250.0f, 200.0f, |
| 4649 | 250.0f, 1.0f |
| 4650 | }); |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4651 | |
| 4652 | // The 'resize bilinear' operation projects the top-left corner of output texels into the input image, |
| 4653 | // 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] | 4654 | // output texel. Thus, for a input matrix of 2x2, we'll expect the output 1x1 matrix to contain, as |
| 4655 | // its single element, the value that was at position (0,0) of the input matrix (rather than an average, |
| 4656 | // which we would expect if projecting the centre). |
| 4657 | |
| 4658 | std::vector<float> outputData({ |
| 4659 | 1.0f, |
| 4660 | |
| 4661 | 250.0f |
| 4662 | }); |
| 4663 | |
| 4664 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4665 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4666 | { |
| 4667 | std::vector<float> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4668 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4669 | inputData = tmp; |
| 4670 | |
| 4671 | std::vector<float> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4672 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4673 | outputData = tmp1; |
| 4674 | } |
| 4675 | |
| 4676 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
| 4677 | |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4678 | LayerTestResult<float, 4> result(outputTensorInfo); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4679 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4680 | |
| 4681 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4682 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4683 | |
| 4684 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 4685 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4686 | armnn::WorkloadInfo info; |
| 4687 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4688 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4689 | |
| 4690 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4691 | |
| 4692 | inputHandle->Allocate(); |
| 4693 | outputHandle->Allocate(); |
| 4694 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4695 | |
| 4696 | workload->Execute(); |
| 4697 | |
| 4698 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4699 | return result; |
| 4700 | } |
| 4701 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4702 | LayerTestResult<float, 4> ResizeBilinearSqMinTest( |
| 4703 | armnn::IWorkloadFactory& workloadFactory, |
| 4704 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4705 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4706 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4707 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); |
| 4708 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 2, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4709 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4710 | std::vector<float> inputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4711 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 4712 | 2.0f, 3.0f, 4.0f, 5.0f, |
| 4713 | 3.0f, 4.0f, 5.0f, 6.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4714 | 4.0f, 5.0f, 6.0f, 7.0f, |
| 4715 | |
| 4716 | 7.0f, 6.0f, 5.0f, 4.0f, |
| 4717 | 6.0f, 5.0f, 4.0f, 3.0f, |
| 4718 | 5.0f, 4.0f, 3.0f, 2.0f, |
| 4719 | 4.0f, 3.0f, 2.0f, 1.0f |
| 4720 | }); |
| 4721 | |
| 4722 | std::vector<float> outputData({ |
| 4723 | 1.0f, 3.0f, |
| 4724 | 3.0f, 5.0f, |
| 4725 | |
| 4726 | 7.0f, 5.0f, |
| 4727 | 5.0f, 3.0f |
| 4728 | }); |
| 4729 | |
| 4730 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4731 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4732 | { |
| 4733 | std::vector<float> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4734 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4735 | inputData = tmp; |
| 4736 | |
| 4737 | std::vector<float> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4738 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4739 | outputData = tmp1; |
| 4740 | } |
| 4741 | |
| 4742 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4743 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4744 | LayerTestResult<float, 4> result(outputTensorInfo); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4745 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4746 | |
| 4747 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4748 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4749 | |
| 4750 | armnn::ResizeBilinearQueueDescriptor descriptor; |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4751 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4752 | armnn::WorkloadInfo info; |
| 4753 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4754 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4755 | |
| 4756 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4757 | |
| 4758 | inputHandle->Allocate(); |
| 4759 | outputHandle->Allocate(); |
| 4760 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4761 | |
| 4762 | workload->Execute(); |
| 4763 | |
| 4764 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4765 | return result; |
| 4766 | } |
| 4767 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4768 | LayerTestResult<float, 4> ResizeBilinearMinTest( |
| 4769 | armnn::IWorkloadFactory& workloadFactory, |
| 4770 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4771 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4772 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4773 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 5, dataLayout); |
| 4774 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 3, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4775 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4776 | std::vector<float> inputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4777 | 1.0f, 2.0f, 3.0f, 5.0f, 8.0f, |
| 4778 | 13.0f, 21.0f, 34.0f, 55.0f, 89.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4779 | 144.0f, 233.0f, 377.0f, 610.0f, 987.0f, |
| 4780 | |
| 4781 | 987.0f, 610.0f, 377.0f, 233.0f, 144.0f, |
| 4782 | 89.0f, 55.0f, 34.0f, 21.0f, 13.0f, |
| 4783 | 8.0f, 5.0f, 3.0f, 2.0f, 1.0f |
| 4784 | }); |
| 4785 | |
| 4786 | std::vector<float> outputData({ |
| 4787 | 1.0f, 2.6666f, 6.00f, |
| 4788 | 78.5f, 179.3333f, 401.00f, |
| 4789 | |
| 4790 | 987.0f, 454.6670f, 203.33f, |
| 4791 | 48.5f, 22.3333f, 10.00f |
| 4792 | }); |
| 4793 | |
| 4794 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4795 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4796 | { |
| 4797 | std::vector<float> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4798 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4799 | inputData = tmp; |
| 4800 | |
| 4801 | std::vector<float> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4802 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4803 | outputData = tmp1; |
| 4804 | } |
| 4805 | |
| 4806 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4807 | |
| 4808 | LayerTestResult<float, 4> result(outputTensorInfo); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4809 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4810 | |
| 4811 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4812 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4813 | |
| 4814 | armnn::ResizeBilinearQueueDescriptor descriptor; |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4815 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4816 | armnn::WorkloadInfo info; |
| 4817 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4818 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4819 | |
| 4820 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4821 | |
| 4822 | inputHandle->Allocate(); |
| 4823 | outputHandle->Allocate(); |
| 4824 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4825 | |
| 4826 | workload->Execute(); |
| 4827 | |
| 4828 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4829 | return result; |
| 4830 | } |
| 4831 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4832 | LayerTestResult<float, 4> ResizeBilinearMagTest( |
| 4833 | armnn::IWorkloadFactory& workloadFactory, |
| 4834 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4835 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4836 | { |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 4837 | const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 2, dataLayout); |
| 4838 | const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 5, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4839 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4840 | std::vector<float> inputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4841 | 1.0f, 2.0f, |
| 4842 | 13.0f, 21.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4843 | 144.0f, 233.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4844 | |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4845 | 233.0f, 144.0f, |
| 4846 | 21.0f, 13.0f, |
| 4847 | 2.0f, 1.0f |
| 4848 | }); |
| 4849 | |
| 4850 | std::vector<float> outputData({ |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4851 | 1.0f, 1.4f, 1.8f, 2.0f, 2.0f, |
| 4852 | 13.0f, 16.2f, 19.4f, 21.0f, 21.0f, |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4853 | 144.0f, 179.6f, 215.2f, 233.0f, 233.0f, |
| 4854 | |
| 4855 | 233.0f, 197.4f, 161.8f, 144.0f, 144.0f, |
| 4856 | 21.0f, 17.8f, 14.6f, 13.0f, 13.0f, |
| 4857 | 2.0f, 1.6f, 1.2f, 1.0f, 1.0f |
| 4858 | }); |
| 4859 | |
| 4860 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4861 | if (dataLayout == armnn::DataLayout::NHWC) |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4862 | { |
| 4863 | std::vector<float> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4864 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4865 | inputData = tmp; |
| 4866 | |
| 4867 | std::vector<float> tmp1(outputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4868 | armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float)); |
James Conroy | 6b96582 | 2018-11-01 11:33:09 +0000 | [diff] [blame] | 4869 | outputData = tmp1; |
| 4870 | } |
| 4871 | |
| 4872 | auto input = MakeTensor<float, 4>(inputTensorInfo, inputData); |
| 4873 | |
| 4874 | LayerTestResult<float, 4> result(outputTensorInfo); |
| 4875 | result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4876 | |
| 4877 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4878 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4879 | |
| 4880 | armnn::ResizeBilinearQueueDescriptor descriptor; |
James Conroy | 074f371 | 2018-10-03 09:32:03 +0100 | [diff] [blame] | 4881 | descriptor.m_Parameters.m_DataLayout = dataLayout; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4882 | armnn::WorkloadInfo info; |
| 4883 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4884 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 4885 | |
| 4886 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 4887 | |
| 4888 | inputHandle->Allocate(); |
| 4889 | outputHandle->Allocate(); |
| 4890 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 4891 | |
| 4892 | workload->Execute(); |
| 4893 | |
| 4894 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 4895 | return result; |
| 4896 | } |
| 4897 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4898 | LayerTestResult<float, 2> FakeQuantizationTest( |
| 4899 | armnn::IWorkloadFactory& workloadFactory, |
| 4900 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4901 | { |
| 4902 | constexpr unsigned int width = 2; |
| 4903 | constexpr unsigned int height = 3; |
| 4904 | |
| 4905 | const armnn::TensorInfo tensorInfo({height, width }, |
| 4906 | armnn::DataType::Float32); |
| 4907 | auto input = MakeTensor<float, 2>(tensorInfo, std::vector<float>({ |
| 4908 | -10.0f, -5.0f, |
| 4909 | 0.0f, 5.0f, |
| 4910 | 10.0f, 10.0f |
| 4911 | })); |
| 4912 | |
| 4913 | LayerTestResult<float, 2> ret(tensorInfo); |
| 4914 | |
| 4915 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(tensorInfo); |
| 4916 | |
| 4917 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(tensorInfo); |
| 4918 | |
| 4919 | armnn::FakeQuantizationQueueDescriptor data; |
| 4920 | armnn::WorkloadInfo info; |
| 4921 | |
| 4922 | AddInputToWorkload(data, info, tensorInfo, inputHandle.get()); |
| 4923 | AddOutputToWorkload(data, info, tensorInfo, outputHandle.get()); |
| 4924 | float min = -10.f; |
| 4925 | float max = 10.f; |
| 4926 | |
| 4927 | data.m_Parameters.m_Min = min; |
| 4928 | data.m_Parameters.m_Max = max; |
| 4929 | |
| 4930 | armnn::PassthroughCpuTensorHandle refHandle(tensorInfo, &ret.outputExpected[0][0]); |
| 4931 | armnn::FakeQuantizationQueueDescriptor refData = data; |
| 4932 | armnn::WorkloadInfo refInfo = info; |
| 4933 | SetWorkloadOutput(refData, refInfo, 0, tensorInfo, &refHandle); |
| 4934 | |
| 4935 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateFakeQuantization(data, info); |
| 4936 | |
| 4937 | inputHandle->Allocate(); |
| 4938 | outputHandle->Allocate(); |
| 4939 | |
| 4940 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0]); |
| 4941 | |
| 4942 | workload->Execute(); |
| 4943 | |
| 4944 | CopyDataFromITensorHandle(&ret.output[0][0], outputHandle.get()); |
| 4945 | |
| 4946 | ret.outputExpected = MakeTensor<float, 2>(tensorInfo, std::vector<float>({ |
| 4947 | 0.0f, 63.0f, |
| 4948 | 128.0f, 191.0f, |
| 4949 | 255.0f, 255.0f |
| 4950 | })); |
| 4951 | return ret; |
| 4952 | } |
| 4953 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4954 | namespace |
| 4955 | { |
| 4956 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 4957 | LayerTestResult<float, 4> L2NormalizationTestImpl( |
| 4958 | armnn::IWorkloadFactory& workloadFactory, |
| 4959 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 4960 | const armnn::TensorShape& inputOutputTensorShape, |
| 4961 | const std::vector<float>& inputValues, |
| 4962 | const std::vector<float>& expectedOutputValues, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4963 | const armnn::DataLayout layout) |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4964 | { |
| 4965 | const armnn::TensorInfo inputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32); |
| 4966 | const armnn::TensorInfo outputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32); |
| 4967 | |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4968 | // at this point if we require it permute the input data |
| 4969 | const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; |
| 4970 | std::vector<float> inputData = inputValues; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4971 | if (layout == armnn::DataLayout::NHWC) |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4972 | { |
| 4973 | std::vector<float> tmp(inputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4974 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float)); |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4975 | inputData = tmp; |
| 4976 | } |
| 4977 | |
| 4978 | auto inputTensor = MakeTensor<float, 4>(inputTensorInfo, std::vector<float>(inputData)); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4979 | |
| 4980 | LayerTestResult<float, 4> result(outputTensorInfo); |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4981 | std::vector<float> expectedOutputData = expectedOutputValues; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4982 | if (layout == armnn::DataLayout::NHWC) |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4983 | { |
| 4984 | std::vector<float> tmp(expectedOutputData.size()); |
Matteo Martincigh | d5b9e64 | 2019-01-04 18:01:21 +0000 | [diff] [blame] | 4985 | armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, |
| 4986 | expectedOutputData.data(), tmp.data(), sizeof(float)); |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 4987 | expectedOutputData = tmp; |
| 4988 | } |
| 4989 | result.outputExpected = MakeTensor<float, 4>(inputTensorInfo, std::vector<float>(expectedOutputData)); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4990 | |
| 4991 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 4992 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 4993 | |
| 4994 | armnn::L2NormalizationQueueDescriptor descriptor; |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 4995 | descriptor.m_Parameters.m_DataLayout = layout; |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 4996 | armnn::WorkloadInfo info; |
| 4997 | |
| 4998 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 4999 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 5000 | |
| 5001 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateL2Normalization(descriptor, info); |
| 5002 | |
| 5003 | inputHandle->Allocate(); |
| 5004 | outputHandle->Allocate(); |
| 5005 | |
| 5006 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0][0]); |
| 5007 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5008 | ExecuteWorkload(*workload, memoryManager); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5009 | |
| 5010 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 5011 | |
| 5012 | return result; |
| 5013 | } |
| 5014 | |
| 5015 | float CalcInvL2Norm(std::initializer_list<float> elements) |
| 5016 | { |
| 5017 | const float reduction = std::accumulate(elements.begin(), elements.end(), 0.0f, |
| 5018 | [](float acc, float element) { return acc + element * element; }); |
| 5019 | return 1.0f / sqrtf(reduction); |
| 5020 | } |
| 5021 | |
| 5022 | } // anonymous namespace |
| 5023 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5024 | template<typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5025 | LayerTestResult<T, 2> Pad2dTestCommon( |
| 5026 | armnn::IWorkloadFactory& workloadFactory, |
| 5027 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 5028 | float qScale, |
| 5029 | int32_t qOffset) |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5030 | { |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5031 | const armnn::TensorShape inputShape{ 3, 3 }; |
| 5032 | const armnn::TensorShape outputShape{ 7, 7 }; |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5033 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5034 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>()); |
| 5035 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5036 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5037 | std::vector<T> inputValues( |
| 5038 | QuantizedVector<T>(qScale, qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5039 | { |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5040 | // Height (3) x Width (3) |
| 5041 | 4, 8, 6, |
| 5042 | 7, 4, 4, |
| 5043 | 3, 2, 4 |
| 5044 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5045 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5046 | std::vector<T> expectedOutputValues( |
| 5047 | QuantizedVector<T>(qScale, qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5048 | { |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5049 | 0, 0, 0, 0, 0, 0, 0, |
| 5050 | 0, 0, 0, 0, 0, 0, 0, |
| 5051 | 0, 0, 4, 8, 6, 0, 0, |
| 5052 | 0, 0, 7, 4, 4, 0, 0, |
| 5053 | 0, 0, 3, 2, 4, 0, 0, |
| 5054 | 0, 0, 0, 0, 0, 0, 0, |
| 5055 | 0, 0, 0, 0, 0, 0, 0 |
| 5056 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5057 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5058 | auto inputTensor = MakeTensor<T, 2>(inputTensorInfo, std::vector<T>(inputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5059 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5060 | LayerTestResult<T, 2> result(outputTensorInfo); |
| 5061 | result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, std::vector<T>(expectedOutputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5062 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5063 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 5064 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5065 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5066 | armnn::PadQueueDescriptor descriptor; |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5067 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5068 | std::vector<std::pair<unsigned int, unsigned int>> PadList; |
| 5069 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,2)); |
| 5070 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,2)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5071 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5072 | descriptor.m_Parameters.m_PadList = PadList; |
| 5073 | armnn::WorkloadInfo info; |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5074 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5075 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 5076 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5077 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5078 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5079 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5080 | inputHandle->Allocate(); |
| 5081 | outputHandle->Allocate(); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5082 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5083 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5084 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5085 | workload->Execute(); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5086 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5087 | CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5088 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5089 | return result; |
| 5090 | } |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5091 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5092 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5093 | LayerTestResult<T, 3> Pad3dTestCommon( |
| 5094 | armnn::IWorkloadFactory& workloadFactory, |
| 5095 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 5096 | float qScale, |
| 5097 | int32_t qOffset) |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5098 | { |
| 5099 | const armnn::TensorShape inputShape{ 2, 2, 2 }; |
| 5100 | const armnn::TensorShape outputShape{ 3, 5, 6 }; |
| 5101 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5102 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>()); |
| 5103 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5104 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5105 | std::vector<T> inputValues( |
| 5106 | QuantizedVector<T>(qScale,qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5107 | { |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5108 | // Channel 0, Height (2) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5109 | 0, 4, |
| 5110 | 2, 5, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5111 | |
| 5112 | // Channel 1, Height (2) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5113 | 6, 1, |
| 5114 | 5, 2 |
| 5115 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5116 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5117 | std::vector<T> expectedOutputValues( |
| 5118 | QuantizedVector<T>(qScale,qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5119 | { |
| 5120 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5121 | 0, 0, 0, 0, 0, 0, |
| 5122 | 0, 0, 0, 0, 0, 0, |
| 5123 | 0, 0, 0, 4, 0, 0, |
| 5124 | 0, 0, 2, 5, 0, 0, |
| 5125 | 0, 0, 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5126 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5127 | 0, 0, 0, 0, 0, 0, |
| 5128 | 0, 0, 0, 0, 0, 0, |
| 5129 | 0, 0, 6, 1, 0, 0, |
| 5130 | 0, 0, 5, 2, 0, 0, |
| 5131 | 0, 0, 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5132 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5133 | 0, 0, 0, 0, 0, 0, |
| 5134 | 0, 0, 0, 0, 0, 0, |
| 5135 | 0, 0, 0, 0, 0, 0, |
| 5136 | 0, 0, 0, 0, 0, 0, |
| 5137 | 0, 0, 0, 0, 0, 0 |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5138 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5139 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5140 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5141 | auto inputTensor = MakeTensor<T, 3>(inputTensorInfo, std::vector<T>(inputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5142 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5143 | LayerTestResult<T, 3> result(outputTensorInfo); |
| 5144 | result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, std::vector<T>(expectedOutputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5145 | |
| 5146 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 5147 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5148 | |
| 5149 | armnn::PadQueueDescriptor descriptor; |
| 5150 | |
| 5151 | std::vector<std::pair<unsigned int, unsigned int>> PadList; |
| 5152 | PadList.push_back(std::pair<unsigned int, unsigned int>(0,1)); |
| 5153 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,1)); |
| 5154 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,2)); |
| 5155 | |
| 5156 | descriptor.m_Parameters.m_PadList = PadList; |
| 5157 | armnn::WorkloadInfo info; |
| 5158 | |
| 5159 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 5160 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 5161 | |
| 5162 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info); |
| 5163 | |
| 5164 | inputHandle->Allocate(); |
| 5165 | outputHandle->Allocate(); |
| 5166 | |
| 5167 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0]); |
| 5168 | |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5169 | workload->Execute(); |
| 5170 | |
| 5171 | CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get()); |
| 5172 | |
| 5173 | return result; |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5174 | } |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5175 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5176 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5177 | LayerTestResult<T, 4> Pad4dTestCommon( |
| 5178 | armnn::IWorkloadFactory& workloadFactory, |
| 5179 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 5180 | float qScale, |
| 5181 | int32_t qOffset) |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5182 | { |
| 5183 | const armnn::TensorShape inputShape{ 2, 2, 3, 2 }; |
| 5184 | const armnn::TensorShape outputShape{ 4, 5, 7, 4 }; |
| 5185 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5186 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>()); |
| 5187 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>()); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5188 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5189 | std::vector<T> inputValues( |
| 5190 | QuantizedVector<T>(qScale,qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5191 | { |
| 5192 | // Batch 0, Channel 0, Height (3) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5193 | 0, 1, |
| 5194 | 2, 3, |
| 5195 | 4, 5, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5196 | |
| 5197 | // Batch 0, Channel 1, Height (3) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5198 | 6, 7, |
| 5199 | 8, 9, |
| 5200 | 10, 11, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5201 | |
| 5202 | // Batch 1, Channel 0, Height (3) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5203 | 12, 13, |
| 5204 | 14, 15, |
| 5205 | 16, 17, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5206 | |
| 5207 | // Batch 1, Channel 1, Height (3) x Width (2) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5208 | 18, 19, |
| 5209 | 20, 21, |
| 5210 | 22, 23 |
| 5211 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5212 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5213 | std::vector<T> expectedOutputValues( |
| 5214 | QuantizedVector<T>(qScale,qOffset, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5215 | { |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5216 | 0, 0, 0, 0, |
| 5217 | 0, 0, 0, 0, |
| 5218 | 0, 0, 0, 0, |
| 5219 | 0, 0, 0, 0, |
| 5220 | 0, 0, 0, 0, |
| 5221 | 0, 0, 0, 0, |
| 5222 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5223 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5224 | 0, 0, 0, 0, |
| 5225 | 0, 0, 0, 0, |
| 5226 | 0, 0, 0, 0, |
| 5227 | 0, 0, 0, 0, |
| 5228 | 0, 0, 0, 0, |
| 5229 | 0, 0, 0, 0, |
| 5230 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5231 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5232 | 0, 0, 0, 0, |
| 5233 | 0, 0, 0, 0, |
| 5234 | 0, 0, 0, 0, |
| 5235 | 0, 0, 0, 0, |
| 5236 | 0, 0, 0, 0, |
| 5237 | 0, 0, 0, 0, |
| 5238 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5239 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5240 | 0, 0, 0, 0, |
| 5241 | 0, 0, 0, 0, |
| 5242 | 0, 0, 0, 0, |
| 5243 | 0, 0, 0, 0, |
| 5244 | 0, 0, 0, 0, |
| 5245 | 0, 0, 0, 0, |
| 5246 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5247 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5248 | 0, 0, 0, 0, |
| 5249 | 0, 0, 0, 0, |
| 5250 | 0, 0, 0, 0, |
| 5251 | 0, 0, 0, 0, |
| 5252 | 0, 0, 0, 0, |
| 5253 | 0, 0, 0, 0, |
| 5254 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5255 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5256 | 0, 0, 0, 0, |
| 5257 | 0, 0, 0, 0, |
| 5258 | 0, 0, 0, 0, |
| 5259 | 0, 0, 0, 0, |
| 5260 | 0, 0, 0, 0, |
| 5261 | 0, 0, 0, 0, |
| 5262 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5263 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5264 | 0, 0, 0, 0, |
| 5265 | 0, 0, 0, 0, |
| 5266 | 0, 0, 0, 0, |
| 5267 | 0, 0, 0, 0, |
| 5268 | 0, 0, 0, 0, |
| 5269 | 0, 0, 0, 0, |
| 5270 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5271 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5272 | 0, 0, 0, 0, |
| 5273 | 0, 0, 0, 0, |
| 5274 | 0, 0, 0, 0, |
| 5275 | 0, 0, 1, 0, |
| 5276 | 0, 2, 3, 0, |
| 5277 | 0, 4, 5, 0, |
| 5278 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5279 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5280 | 0, 0, 0, 0, |
| 5281 | 0, 0, 0, 0, |
| 5282 | 0, 0, 0, 0, |
| 5283 | 0, 6, 7, 0, |
| 5284 | 0, 8, 9, 0, |
| 5285 | 0, 10, 11, 0, |
| 5286 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5287 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5288 | 0, 0, 0, 0, |
| 5289 | 0, 0, 0, 0, |
| 5290 | 0, 0, 0, 0, |
| 5291 | 0, 0, 0, 0, |
| 5292 | 0, 0, 0, 0, |
| 5293 | 0, 0, 0, 0, |
| 5294 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5295 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5296 | 0, 0, 0, 0, |
| 5297 | 0, 0, 0, 0, |
| 5298 | 0, 0, 0, 0, |
| 5299 | 0, 0, 0, 0, |
| 5300 | 0, 0, 0, 0, |
| 5301 | 0, 0, 0, 0, |
| 5302 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5303 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5304 | 0, 0, 0, 0, |
| 5305 | 0, 0, 0, 0, |
| 5306 | 0, 0, 0, 0, |
| 5307 | 0, 0, 0, 0, |
| 5308 | 0, 0, 0, 0, |
| 5309 | 0, 0, 0, 0, |
| 5310 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5311 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5312 | 0, 0, 0, 0, |
| 5313 | 0, 0, 0, 0, |
| 5314 | 0, 0, 0, 0, |
| 5315 | 0, 12, 13, 0, |
| 5316 | 0, 14, 15, 0, |
| 5317 | 0, 16, 17, 0, |
| 5318 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5319 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5320 | 0, 0, 0, 0, |
| 5321 | 0, 0, 0, 0, |
| 5322 | 0, 0, 0, 0, |
| 5323 | 0, 18, 19, 0, |
| 5324 | 0, 20, 21, 0, |
| 5325 | 0, 22, 23, 0, |
| 5326 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5327 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5328 | 0, 0, 0, 0, |
| 5329 | 0, 0, 0, 0, |
| 5330 | 0, 0, 0, 0, |
| 5331 | 0, 0, 0, 0, |
| 5332 | 0, 0, 0, 0, |
| 5333 | 0, 0, 0, 0, |
| 5334 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5335 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5336 | 0, 0, 0, 0, |
| 5337 | 0, 0, 0, 0, |
| 5338 | 0, 0, 0, 0, |
| 5339 | 0, 0, 0, 0, |
| 5340 | 0, 0, 0, 0, |
| 5341 | 0, 0, 0, 0, |
| 5342 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5343 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5344 | 0, 0, 0, 0, |
| 5345 | 0, 0, 0, 0, |
| 5346 | 0, 0, 0, 0, |
| 5347 | 0, 0, 0, 0, |
| 5348 | 0, 0, 0, 0, |
| 5349 | 0, 0, 0, 0, |
| 5350 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5351 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5352 | 0, 0, 0, 0, |
| 5353 | 0, 0, 0, 0, |
| 5354 | 0, 0, 0, 0, |
| 5355 | 0, 0, 0, 0, |
| 5356 | 0, 0, 0, 0, |
| 5357 | 0, 0, 0, 0, |
| 5358 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5359 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5360 | 0, 0, 0, 0, |
| 5361 | 0, 0, 0, 0, |
| 5362 | 0, 0, 0, 0, |
| 5363 | 0, 0, 0, 0, |
| 5364 | 0, 0, 0, 0, |
| 5365 | 0, 0, 0, 0, |
| 5366 | 0, 0, 0, 0, |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5367 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5368 | 0, 0, 0, 0, |
| 5369 | 0, 0, 0, 0, |
| 5370 | 0, 0, 0, 0, |
| 5371 | 0, 0, 0, 0, |
| 5372 | 0, 0, 0, 0, |
| 5373 | 0, 0, 0, 0, |
| 5374 | 0, 0, 0, 0 |
| 5375 | })); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5376 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5377 | auto inputTensor = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>(inputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5378 | |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5379 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 5380 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, std::vector<T>(expectedOutputValues)); |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5381 | |
| 5382 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 5383 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5384 | |
| 5385 | armnn::PadQueueDescriptor descriptor; |
| 5386 | |
| 5387 | std::vector<std::pair<unsigned int, unsigned int>> PadList; |
| 5388 | PadList.push_back(std::pair<unsigned int, unsigned int>(1,1)); |
| 5389 | PadList.push_back(std::pair<unsigned int, unsigned int>(2,1)); |
| 5390 | PadList.push_back(std::pair<unsigned int, unsigned int>(3,1)); |
| 5391 | PadList.push_back(std::pair<unsigned int, unsigned int>(1,1)); |
| 5392 | |
| 5393 | descriptor.m_Parameters.m_PadList = PadList; |
| 5394 | armnn::WorkloadInfo info; |
| 5395 | |
| 5396 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 5397 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 5398 | |
| 5399 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info); |
| 5400 | |
| 5401 | inputHandle->Allocate(); |
| 5402 | outputHandle->Allocate(); |
| 5403 | |
| 5404 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0][0]); |
| 5405 | |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5406 | workload->Execute(); |
| 5407 | |
| 5408 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 5409 | |
| 5410 | return result; |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5411 | } |
| 5412 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5413 | LayerTestResult<uint8_t, 2> PadUint82dTest( |
| 5414 | armnn::IWorkloadFactory& workloadFactory, |
| 5415 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5416 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5417 | return Pad2dTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5418 | } |
| 5419 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5420 | LayerTestResult<uint8_t, 3> PadUint83dTest( |
| 5421 | armnn::IWorkloadFactory& workloadFactory, |
| 5422 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5423 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5424 | return Pad3dTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5425 | } |
| 5426 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5427 | LayerTestResult<uint8_t, 4> PadUint84dTest( |
| 5428 | armnn::IWorkloadFactory& workloadFactory, |
| 5429 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5430 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5431 | return Pad4dTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5432 | } |
| 5433 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5434 | LayerTestResult<float, 2> PadFloat322dTest( |
| 5435 | armnn::IWorkloadFactory& workloadFactory, |
| 5436 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5437 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5438 | return Pad2dTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5439 | } |
| 5440 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5441 | LayerTestResult<float, 3> PadFloat323dTest( |
| 5442 | armnn::IWorkloadFactory& workloadFactory, |
| 5443 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5444 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5445 | return Pad3dTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5446 | } |
| 5447 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5448 | LayerTestResult<float, 4> PadFloat324dTest( |
| 5449 | armnn::IWorkloadFactory& workloadFactory, |
| 5450 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5451 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5452 | return Pad4dTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0); |
Mohamed Nour Abouelseoud | dd6acea | 2018-10-18 12:26:19 +0100 | [diff] [blame] | 5453 | } |
Mohamed Nour Abouelseoud | 7420e55 | 2018-10-12 12:26:24 +0100 | [diff] [blame] | 5454 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5455 | LayerTestResult<float, 4> L2Normalization1dTest( |
| 5456 | armnn::IWorkloadFactory& workloadFactory, |
| 5457 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 5458 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5459 | { |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5460 | // Width: 1 |
| 5461 | // Height: 1 |
| 5462 | // Channels: 10 |
| 5463 | // BatchSize: 1 |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5464 | unsigned int numberOfBatches = 1; |
| 5465 | unsigned int numberOfChannels = 10; |
| 5466 | unsigned int height = 1; |
| 5467 | unsigned int width = 1; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5468 | |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5469 | |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 5470 | const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5471 | numberOfBatches, numberOfChannels, height, width, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5472 | std::vector<float> inputValues |
| 5473 | { |
| 5474 | // Batch 0, Channel 0, Height (1) x Width (1) |
| 5475 | 1.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5476 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5477 | // Batch 0, Channel 1, Height (1) x Width (1) |
| 5478 | 2.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5479 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5480 | // Batch 0, Channel 2, Height (1) x Width (1) |
| 5481 | 3.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5482 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5483 | // Batch 0, Channel 3, Height (1) x Width (1) |
| 5484 | 4.0f, |
| 5485 | |
| 5486 | // Batch 0, Channel 4, Height (1) x Width (1) |
| 5487 | 5.0f, |
| 5488 | |
| 5489 | // Batch 0, Channel 5, Height (1) x Width (1) |
| 5490 | 6.0f, |
| 5491 | |
| 5492 | // Batch 0, Channel 6, Height (1) x Width (1) |
| 5493 | 7.0f, |
| 5494 | |
| 5495 | // Batch 0, Channel 7, Height (1) x Width (1) |
| 5496 | 8.0f, |
| 5497 | |
| 5498 | // Batch 0, Channel 8, Height (1) x Width (1) |
| 5499 | 9.0f, |
| 5500 | |
| 5501 | // Batch 0, Channel 9, Height (1) x Width (1) |
| 5502 | 10.0f |
| 5503 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5504 | const float approxInvL2Norm = 0.050964719f; |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5505 | std::vector<float> expectedOutputValues |
| 5506 | { |
| 5507 | // Batch 0, Channel 0, Height (1) x Width (1) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5508 | 1.0f * approxInvL2Norm, |
| 5509 | 2.0f * approxInvL2Norm, |
| 5510 | 3.0f * approxInvL2Norm, |
| 5511 | 4.0f * approxInvL2Norm, |
| 5512 | 5.0f * approxInvL2Norm, |
| 5513 | 6.0f * approxInvL2Norm, |
| 5514 | 7.0f * approxInvL2Norm, |
| 5515 | 8.0f * approxInvL2Norm, |
| 5516 | 9.0f * approxInvL2Norm, |
| 5517 | 10.0f * approxInvL2Norm |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5518 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5519 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5520 | |
| 5521 | return L2NormalizationTestImpl(workloadFactory, memoryManager, inputOutputShape, |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5522 | inputValues, expectedOutputValues, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5523 | } |
| 5524 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5525 | LayerTestResult<float, 4> L2Normalization2dTest( |
| 5526 | armnn::IWorkloadFactory& workloadFactory, |
| 5527 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 5528 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5529 | { |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5530 | // Width: 5 |
| 5531 | // Height: 1 |
| 5532 | // Channels: 2 |
| 5533 | // BatchSize: 1 |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5534 | unsigned int numberOfBatches = 1; |
| 5535 | unsigned int numberOfChannels = 2; |
| 5536 | unsigned int height = 1; |
| 5537 | unsigned int width = 5; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5538 | |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 5539 | const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5540 | numberOfBatches, numberOfChannels, height, width, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5541 | std::vector<float> inputValues |
| 5542 | { |
| 5543 | // Batch 0, Channel 0, Height (1) x Width (5) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5544 | 1.0f, 3.0f, 5.0f, 7.0f, 9.0f, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5545 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5546 | // Batch 0, Channel 1, Height (1) x Width (5) |
| 5547 | 2.0f, 4.0f, 6.0f, 8.0f, 10.0f |
| 5548 | }; |
| 5549 | std::vector<float> expectedOutputValues |
| 5550 | { |
| 5551 | // Batch 0, Channel 0, Height (1) x Width (5) |
| 5552 | 1.0f * CalcInvL2Norm({ 1.0f, 2.0f }), |
| 5553 | 3.0f * CalcInvL2Norm({ 3.0f, 4.0f }), |
| 5554 | 5.0f * CalcInvL2Norm({ 5.0f, 6.0f }), |
| 5555 | 7.0f * CalcInvL2Norm({ 7.0f, 8.0f }), |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5556 | 9.0f * CalcInvL2Norm({ 9.0f, 10.0f }), |
| 5557 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5558 | // Batch 0, Channel 1, Height (1) x Width (5) |
| 5559 | 2.0f * CalcInvL2Norm({ 1.0f, 2.0f }), |
| 5560 | 4.0f * CalcInvL2Norm({ 3.0f, 4.0f }), |
| 5561 | 6.0f * CalcInvL2Norm({ 5.0f, 6.0f }), |
| 5562 | 8.0f * CalcInvL2Norm({ 7.0f, 8.0f }), |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5563 | 10.0f * CalcInvL2Norm({ 9.0f, 10.0f }) |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5564 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5565 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5566 | return L2NormalizationTestImpl(workloadFactory, memoryManager, inputOutputShape, |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5567 | inputValues, expectedOutputValues, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5568 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5569 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5570 | LayerTestResult<float, 4> L2Normalization3dTest( |
| 5571 | armnn::IWorkloadFactory& workloadFactory, |
| 5572 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 5573 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5574 | { |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5575 | // Width: 3 |
| 5576 | // Height: 4 |
| 5577 | // Channels: 2 |
| 5578 | // BatchSize: 1 |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5579 | unsigned int numberOfBatches = 1; |
| 5580 | unsigned int numberOfChannels = 2; |
| 5581 | unsigned int height = 4; |
| 5582 | unsigned int width = 3; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5583 | |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 5584 | const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5585 | numberOfBatches, numberOfChannels, height, width, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5586 | std::vector<float> inputValues |
| 5587 | { |
| 5588 | // Batch 0, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5589 | 119.0f, 21.0f, 150.0f, |
| 5590 | 149.0f, 32.0f, 179.0f, |
| 5591 | 15.0f, 227.0f, 141.0f, |
| 5592 | 147.0f, 199.0f, 220.0f, |
| 5593 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5594 | // Batch 0, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5595 | 110.0f, 140.0f, 73.0f, |
| 5596 | 211.0f, 212.0f, 89.0f, |
| 5597 | 24.0f, 138.0f, 188.0f, |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5598 | 162.0f, 12.0f, 161.0f |
| 5599 | }; |
| 5600 | std::vector<float> expectedOutputValues |
| 5601 | { |
| 5602 | // Batch 0, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5603 | 119.0f * CalcInvL2Norm({ 119.0f, 110.0f }), |
| 5604 | 21.0f * CalcInvL2Norm({ 21.0f, 140.0f }), |
| 5605 | 150.0f * CalcInvL2Norm({ 150.0f, 73.0f }), |
| 5606 | 149.0f * CalcInvL2Norm({ 149.0f, 211.0f }), |
| 5607 | 32.0f * CalcInvL2Norm({ 32.0f, 212.0f }), |
| 5608 | 179.0f * CalcInvL2Norm({ 179.0f, 89.0f }), |
| 5609 | 15.0f * CalcInvL2Norm({ 15.0f, 24.0f }), |
| 5610 | 227.0f * CalcInvL2Norm({ 227.0f, 138.0f }), |
| 5611 | 141.0f * CalcInvL2Norm({ 141.0f, 188.0f }), |
| 5612 | 147.0f * CalcInvL2Norm({ 147.0f, 162.0f }), |
| 5613 | 199.0f * CalcInvL2Norm({ 199.0f, 12.0f }), |
| 5614 | 220.0f * CalcInvL2Norm({ 220.0f, 161.0f }), |
| 5615 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5616 | // Batch 0, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5617 | 110.0f * CalcInvL2Norm({ 119.0f, 110.0f }), |
| 5618 | 140.0f * CalcInvL2Norm({ 21.0f, 140.0f }), |
| 5619 | 73.0f * CalcInvL2Norm({ 150.0f, 73.0f }), |
| 5620 | 211.0f * CalcInvL2Norm({ 149.0f, 211.0f }), |
| 5621 | 212.0f * CalcInvL2Norm({ 32.0f, 212.0f }), |
| 5622 | 89.0f * CalcInvL2Norm({ 179.0f, 89.0f }), |
| 5623 | 24.0f * CalcInvL2Norm({ 15.0f, 24.0f }), |
| 5624 | 138.0f * CalcInvL2Norm({ 227.0f, 138.0f }), |
| 5625 | 188.0f * CalcInvL2Norm({ 141.0f, 188.0f }), |
| 5626 | 162.0f * CalcInvL2Norm({ 147.0f, 162.0f }), |
| 5627 | 12.0f * CalcInvL2Norm({ 199.0f, 12.0f }), |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5628 | 161.0f * CalcInvL2Norm({ 220.0f, 161.0f }) |
| 5629 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5630 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5631 | return L2NormalizationTestImpl(workloadFactory, memoryManager, inputOutputShape, |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5632 | inputValues, expectedOutputValues, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5633 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5634 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5635 | LayerTestResult<float, 4> L2Normalization4dTest( |
| 5636 | armnn::IWorkloadFactory& workloadFactory, |
| 5637 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 5638 | const armnn::DataLayout layout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5639 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5640 | // Width: 3 |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5641 | // Height: 4 |
| 5642 | // Channels: 3 |
| 5643 | // BatchSize: 2 |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5644 | unsigned int numberOfBatches = 2; |
| 5645 | unsigned int numberOfChannels = 3; |
| 5646 | unsigned int height = 4; |
| 5647 | unsigned int width = 3; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5648 | |
Nina Drozd | d41b259 | 2018-11-19 13:03:36 +0000 | [diff] [blame] | 5649 | const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5650 | numberOfBatches, numberOfChannels, height, width, layout); |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5651 | std::vector<float> inputValues |
| 5652 | { |
| 5653 | // Batch 0, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5654 | 235.0f, 46.0f, 178.0f, |
| 5655 | 100.0f, 123.0f, 19.0f, |
| 5656 | 172.0f, 74.0f, 250.0f, |
| 5657 | 6.0f, 195.0f, 80.0f, |
| 5658 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5659 | // Batch 0, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5660 | 113.0f, 95.0f, 202.0f, |
| 5661 | 77.0f, 114.0f, 71.0f, |
| 5662 | 122.0f, 246.0f, 166.0f, |
| 5663 | 82.0f, 28.0f, 37.0f, |
| 5664 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5665 | // Batch 0, Channel 2, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5666 | 56.0f, 170.0f, 162.0f, |
| 5667 | 194.0f, 89.0f, 254.0f, |
| 5668 | 12.0f, 209.0f, 200.0f, |
| 5669 | 1.0f, 64.0f, 54.0f, |
| 5670 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5671 | // Batch 1, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5672 | 67.0f, 90.0f, 49.0f, |
| 5673 | 7.0f, 163.0f, 18.0f, |
| 5674 | 25.0f, 117.0f, 103.0f, |
| 5675 | 247.0f, 59.0f, 189.0f, |
| 5676 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5677 | // Batch 1, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5678 | 239.0f, 104.0f, 199.0f, |
| 5679 | 17.0f, 124.0f, 153.0f, |
| 5680 | 222.0f, 217.0f, 75.0f, |
| 5681 | 32.0f, 126.0f, 21.0f, |
| 5682 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5683 | // Batch 1, Channel 2, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5684 | 97.0f, 145.0f, 215.0f, |
| 5685 | 115.0f, 116.0f, 238.0f, |
| 5686 | 226.0f, 16.0f, 132.0f, |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5687 | 92.0f, 125.0f, 88.0f |
| 5688 | }; |
| 5689 | std::vector<float> expectedOutputValues |
| 5690 | { |
| 5691 | // Batch 0, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5692 | 235.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }), |
| 5693 | 46.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }), |
| 5694 | 178.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }), |
| 5695 | 100.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }), |
| 5696 | 123.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }), |
| 5697 | 19.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }), |
| 5698 | 172.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }), |
| 5699 | 74.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }), |
| 5700 | 250.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }), |
| 5701 | 6.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }), |
| 5702 | 195.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }), |
| 5703 | 80.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }), |
| 5704 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5705 | // Batch 0, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5706 | 113.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }), |
| 5707 | 95.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }), |
| 5708 | 202.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }), |
| 5709 | 77.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }), |
| 5710 | 114.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }), |
| 5711 | 71.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }), |
| 5712 | 122.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }), |
| 5713 | 246.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }), |
| 5714 | 166.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }), |
| 5715 | 82.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }), |
| 5716 | 28.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }), |
| 5717 | 37.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }), |
| 5718 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5719 | // Batch 0, Channel 2, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5720 | 56.0f * CalcInvL2Norm({ 235.0f, 113.0f, 56.0f }), |
| 5721 | 170.0f * CalcInvL2Norm({ 46.0f, 95.0f, 170.0f }), |
| 5722 | 162.0f * CalcInvL2Norm({ 178.0f, 202.0F, 162.0f }), |
| 5723 | 194.0f * CalcInvL2Norm({ 100.0f, 77.0f, 194.0f }), |
| 5724 | 89.0f * CalcInvL2Norm({ 123.0f, 114.0f, 89.0f }), |
| 5725 | 254.0f * CalcInvL2Norm({ 19.0f, 71.0f, 254.0f }), |
| 5726 | 12.0f * CalcInvL2Norm({ 172.0f, 122.0f, 12.0f }), |
| 5727 | 209.0f * CalcInvL2Norm({ 74.0f, 246.0f, 209.0f }), |
| 5728 | 200.0f * CalcInvL2Norm({ 250.0f, 166.0f, 200.0f }), |
| 5729 | 1.0f * CalcInvL2Norm({ 6.0f, 82.0f, 1.0f }), |
| 5730 | 64.0f * CalcInvL2Norm({ 195.0f, 28.0f, 64.0f }), |
| 5731 | 54.0f * CalcInvL2Norm({ 80.0f, 37.0f, 54.0f }), |
| 5732 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5733 | // Batch 1, Channel 0, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5734 | 67.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }), |
| 5735 | 90.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }), |
| 5736 | 49.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }), |
| 5737 | 7.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }), |
| 5738 | 163.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }), |
| 5739 | 18.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }), |
| 5740 | 25.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }), |
| 5741 | 117.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }), |
| 5742 | 103.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }), |
| 5743 | 247.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }), |
| 5744 | 59.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }), |
| 5745 | 189.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f }), |
| 5746 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5747 | // Batch 1, Channel 1, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5748 | 239.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }), |
| 5749 | 104.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }), |
| 5750 | 199.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }), |
| 5751 | 17.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }), |
| 5752 | 124.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }), |
| 5753 | 153.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }), |
| 5754 | 222.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }), |
| 5755 | 217.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }), |
| 5756 | 75.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }), |
| 5757 | 32.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }), |
| 5758 | 126.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }), |
| 5759 | 21.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f }), |
| 5760 | |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5761 | // Batch 1, Channel 2, Height (4) x Width (3) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5762 | 97.0f * CalcInvL2Norm({ 67.0f, 239.0f, 97.0f }), |
| 5763 | 145.0f * CalcInvL2Norm({ 90.0f, 104.0f, 145.0f }), |
| 5764 | 215.0f * CalcInvL2Norm({ 49.0f, 199.0f, 215.0f }), |
| 5765 | 115.0f * CalcInvL2Norm({ 7.0f, 17.0f, 115.0f }), |
| 5766 | 116.0f * CalcInvL2Norm({ 163.0f, 124.0f, 116.0f }), |
| 5767 | 238.0f * CalcInvL2Norm({ 18.0f, 153.0f, 238.0f }), |
| 5768 | 226.0f * CalcInvL2Norm({ 25.0f, 222.0f, 226.0f }), |
| 5769 | 16.0f * CalcInvL2Norm({ 117.0f, 217.0f, 16.0f }), |
| 5770 | 132.0f * CalcInvL2Norm({ 103.0f, 75.0f, 132.0f }), |
| 5771 | 92.0f * CalcInvL2Norm({ 247.0f, 32.0f, 92.0f }), |
| 5772 | 125.0f * CalcInvL2Norm({ 59.0f, 126.0f, 125.0f }), |
Matteo Martincigh | 539b44d | 2018-10-01 09:26:39 +0100 | [diff] [blame] | 5773 | 88.0f * CalcInvL2Norm({ 189.0f, 21.0f, 88.0f }) |
| 5774 | }; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5775 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5776 | return L2NormalizationTestImpl(workloadFactory, memoryManager, inputOutputShape, |
jimfly01 | 3aab7c3 | 2018-11-12 13:32:08 +0000 | [diff] [blame] | 5777 | inputValues, expectedOutputValues, layout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5778 | } |
| 5779 | |
| 5780 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5781 | LayerTestResult<T, 4> ConstantTestImpl( |
| 5782 | armnn::IWorkloadFactory& workloadFactory, |
| 5783 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5784 | float qScale, |
| 5785 | int32_t qOffset) |
| 5786 | { |
| 5787 | constexpr unsigned int inputWidth = 3; |
| 5788 | constexpr unsigned int inputHeight = 4; |
| 5789 | constexpr unsigned int inputChannels = 3; |
| 5790 | constexpr unsigned int inputBatchSize = 2; |
| 5791 | |
| 5792 | constexpr unsigned int outputWidth = inputWidth; |
| 5793 | constexpr unsigned int outputHeight = inputHeight; |
| 5794 | constexpr unsigned int outputChannels = inputChannels; |
| 5795 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 5796 | |
| 5797 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 5798 | armnn::GetDataType<T>()); |
| 5799 | |
| 5800 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 5801 | armnn::GetDataType<T>()); |
| 5802 | |
| 5803 | // Set quantization parameters if the requested type is a quantized type. |
| 5804 | if(armnn::IsQuantizedType<T>()) |
| 5805 | { |
| 5806 | inputTensorInfo.SetQuantizationScale(qScale); |
| 5807 | inputTensorInfo.SetQuantizationOffset(qOffset); |
| 5808 | outputTensorInfo.SetQuantizationScale(qScale); |
| 5809 | outputTensorInfo.SetQuantizationOffset(qOffset); |
| 5810 | } |
| 5811 | |
| 5812 | auto input = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>( |
| 5813 | QuantizedVector<T>(qScale, qOffset, { |
| 5814 | // Batch 0, Channel 0 |
| 5815 | 235.0f, 46.0f, 178.0f, |
| 5816 | 100.0f, 123.0f, 19.0f, |
| 5817 | 172.0f, 74.0f, 250.0f, |
| 5818 | 6.0f, 195.0f, 80.0f, |
| 5819 | |
| 5820 | // Batch 0, Channel 1 |
| 5821 | 113.0f, 95.0f, 202.0f, |
| 5822 | 77.0f, 114.0f, 71.0f, |
| 5823 | 122.0f, 246.0f, 166.0f, |
| 5824 | 82.0f, 28.0f, 37.0f, |
| 5825 | |
| 5826 | // Batch 0, Channel 2 |
| 5827 | 56.0f, 170.0f, 162.0f, |
| 5828 | 194.0f, 89.0f, 254.0f, |
| 5829 | 12.0f, 209.0f, 200.0f, |
| 5830 | 1.0f, 64.0f, 54.0f, |
| 5831 | |
| 5832 | // Batch 1, Channel 0 |
| 5833 | 67.0f, 90.0f, 49.0f, |
| 5834 | 7.0f, 163.0f, 18.0f, |
| 5835 | 25.0f, 117.0f, 103.0f, |
| 5836 | 247.0f, 59.0f, 189.0f, |
| 5837 | |
| 5838 | // Batch 1, Channel 1 |
| 5839 | 239.0f, 104.0f, 199.0f, |
| 5840 | 17.0f, 124.0f, 153.0f, |
| 5841 | 222.0f, 217.0f, 75.0f, |
| 5842 | 32.0f, 126.0f, 21.0f, |
| 5843 | |
| 5844 | // Batch 1, Channel 2 |
| 5845 | 97.0f, 145.0f, 215.0f, |
| 5846 | 115.0f, 116.0f, 238.0f, |
| 5847 | 226.0f, 16.0f, 132.0f, |
| 5848 | 92.0f, 125.0f, 88.0f, |
| 5849 | }))); |
| 5850 | |
| 5851 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 5852 | result.outputExpected = input; |
| 5853 | |
| 5854 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5855 | |
| 5856 | armnn::ScopedCpuTensorHandle constantTensor(inputTensorInfo); |
| 5857 | AllocateAndCopyDataToITensorHandle(&constantTensor, &input[0][0][0][0]); |
| 5858 | |
| 5859 | armnn::ConstantQueueDescriptor descriptor; |
| 5860 | descriptor.m_LayerOutput = &constantTensor; |
| 5861 | |
| 5862 | armnn::WorkloadInfo info; |
| 5863 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 5864 | |
| 5865 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConstant(descriptor, info); |
| 5866 | |
| 5867 | outputHandle->Allocate(); |
| 5868 | |
| 5869 | workload->Execute(); |
| 5870 | |
| 5871 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 5872 | return result; |
| 5873 | } |
| 5874 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5875 | LayerTestResult<float, 4> ConstantTest( |
| 5876 | armnn::IWorkloadFactory& workloadFactory, |
| 5877 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5878 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5879 | return ConstantTestImpl<float>(workloadFactory, memoryManager, 0.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5880 | } |
| 5881 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5882 | LayerTestResult<uint8_t, 4> ConstantTestUint8( |
| 5883 | armnn::IWorkloadFactory& workloadFactory, |
| 5884 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5885 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5886 | return ConstantTestImpl<uint8_t>(workloadFactory, memoryManager, 1.0f, 0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5887 | } |
| 5888 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 5889 | LayerTestResult<uint8_t, 3> MergerUint8Test( |
| 5890 | armnn::IWorkloadFactory& workloadFactory, |
| 5891 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5892 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5893 | unsigned int outputWidth = 3; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5894 | unsigned int outputHeight = 6; |
| 5895 | unsigned int outputChannels = 3; |
| 5896 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5897 | unsigned int inputWidth1 = 3; |
| 5898 | unsigned int inputHeight1 = 6; |
| 5899 | unsigned int inputChannels1 = 2; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5900 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5901 | unsigned int inputWidth2 = 3; |
| 5902 | unsigned int inputHeight2 = 6; |
| 5903 | unsigned int inputChannels2 = 1; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5904 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5905 | // Defines the tensor descriptors. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5906 | armnn::TensorInfo outputTensorInfo({ outputChannels, outputHeight, outputWidth }, armnn::DataType::QuantisedAsymm8); |
| 5907 | armnn::TensorInfo inputTensorInfo1({ inputChannels1, inputHeight1, inputWidth1 }, armnn::DataType::QuantisedAsymm8); |
| 5908 | armnn::TensorInfo inputTensorInfo2({ inputChannels2, inputHeight2, inputWidth2 }, armnn::DataType::QuantisedAsymm8); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5909 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5910 | // 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] | 5911 | const float scale = 0.13497836f; |
| 5912 | const int32_t offset = -7; |
| 5913 | |
| 5914 | outputTensorInfo.SetQuantizationScale(scale); |
| 5915 | outputTensorInfo.SetQuantizationOffset(offset); |
| 5916 | inputTensorInfo1.SetQuantizationScale(scale); |
| 5917 | inputTensorInfo1.SetQuantizationOffset(offset); |
| 5918 | inputTensorInfo2.SetQuantizationScale(scale); |
| 5919 | inputTensorInfo2.SetQuantizationOffset(offset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5920 | |
| 5921 | LayerTestResult<uint8_t, 3> ret(outputTensorInfo); |
| 5922 | |
| 5923 | ret.outputExpected = MakeTensor<uint8_t, 3>(outputTensorInfo, std::vector<uint8_t>( |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5924 | { |
| 5925 | 1, 2, 3, |
| 5926 | 4, 5, 6, |
| 5927 | 7, 8, 9, |
| 5928 | 10, 11, 12, |
| 5929 | 13, 14, 15, |
| 5930 | 16, 17, 18, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5931 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5932 | 19, 20, 21, |
| 5933 | 22, 23, 24, |
| 5934 | 25, 26, 27, |
| 5935 | 28, 29, 30, |
| 5936 | 31, 32, 33, |
| 5937 | 34, 35, 36, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5938 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5939 | 37, 38, 39, |
| 5940 | 40, 41, 42, |
| 5941 | 43, 44, 45, |
| 5942 | 46, 47, 48, |
| 5943 | 49, 50, 51, |
| 5944 | 52, 53, 54, |
| 5945 | }) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5946 | ); |
| 5947 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5948 | auto input1 = MakeTensor<uint8_t, 3>(inputTensorInfo1, std::vector<uint8_t>( |
| 5949 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5950 | 1, 2, 3, |
| 5951 | 4, 5, 6, |
| 5952 | 7, 8, 9, |
| 5953 | 10, 11, 12, |
| 5954 | 13, 14, 15, |
| 5955 | 16, 17, 18, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5956 | |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5957 | 19, 20, 21, |
| 5958 | 22, 23, 24, |
| 5959 | 25, 26, 27, |
| 5960 | 28, 29, 30, |
| 5961 | 31, 32, 33, |
| 5962 | 34, 35, 36, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5963 | }) |
| 5964 | ); |
| 5965 | |
| 5966 | auto input2 = MakeTensor<uint8_t, 3>(inputTensorInfo2, std::vector<uint8_t>( |
| 5967 | { |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5968 | 37, 38, 39, |
| 5969 | 40, 41, 42, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5970 | 43, 44, 45, |
surmeh01 | 3537c2c | 2018-05-18 16:31:43 +0100 | [diff] [blame] | 5971 | 46, 47, 48, |
| 5972 | 49, 50, 51, |
| 5973 | 52, 53, 54, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5974 | }) |
| 5975 | ); |
| 5976 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5977 | 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] | 5978 | armnn::MergerQueueDescriptor::ViewOrigin window1(wOrigin1); |
| 5979 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 5980 | 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] | 5981 | armnn::MergerQueueDescriptor::ViewOrigin window2(wOrigin2); |
| 5982 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5983 | |
| 5984 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 5985 | |
| 5986 | bool subTensorsSupported = workloadFactory.SupportsSubTensors(); |
| 5987 | |
| 5988 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = |
| 5989 | subTensorsSupported ? |
| 5990 | workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) : |
| 5991 | workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 5992 | |
| 5993 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = |
| 5994 | subTensorsSupported ? |
| 5995 | workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) : |
| 5996 | workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 5997 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 5998 | |
| 5999 | armnn::MergerQueueDescriptor data; |
| 6000 | armnn::WorkloadInfo info; |
| 6001 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 6002 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6003 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 6004 | |
| 6005 | data.m_ViewOrigins.push_back(window1); |
| 6006 | data.m_ViewOrigins.push_back(window2); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6007 | |
| 6008 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMerger(data, info); |
| 6009 | |
| 6010 | inputHandle1->Allocate(); |
| 6011 | inputHandle2->Allocate(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6012 | outputHandle->Allocate(); |
| 6013 | |
| 6014 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]); |
| 6015 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6016 | |
| 6017 | workload->Execute(); |
| 6018 | |
| 6019 | CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get()); |
| 6020 | |
| 6021 | return ret; |
| 6022 | } |
| 6023 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6024 | LayerTestResult<uint8_t, 4> AdditionUint8Test( |
| 6025 | armnn::IWorkloadFactory& workloadFactory, |
| 6026 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6027 | { |
| 6028 | unsigned int batchSize = 1; |
| 6029 | unsigned int channels = 2; |
| 6030 | unsigned int height = 2; |
| 6031 | unsigned int width = 3; |
| 6032 | |
| 6033 | const float scale = 7.0f; |
| 6034 | const int32_t offset = 3; |
| 6035 | |
| 6036 | armnn::TensorInfo inputTensorInfo1, inputTensorInfo2; |
| 6037 | armnn::TensorInfo outputTensorInfo; |
| 6038 | |
| 6039 | const unsigned int shape[] = { batchSize, channels, height, width }; |
| 6040 | inputTensorInfo1 = armnn::TensorInfo(4, shape, armnn::DataType::QuantisedAsymm8); |
| 6041 | inputTensorInfo1.SetQuantizationScale(scale); |
| 6042 | inputTensorInfo1.SetQuantizationOffset(offset); |
| 6043 | |
| 6044 | inputTensorInfo2 = armnn::TensorInfo(4, shape, armnn::DataType::QuantisedAsymm8); |
| 6045 | inputTensorInfo2.SetQuantizationScale(scale); |
| 6046 | inputTensorInfo2.SetQuantizationOffset(offset); |
| 6047 | |
| 6048 | outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::QuantisedAsymm8); |
| 6049 | outputTensorInfo.SetQuantizationScale(scale); |
| 6050 | outputTensorInfo.SetQuantizationOffset(offset); |
| 6051 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 6052 | // See dequantized values to the right. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6053 | auto input1 = MakeTensor<uint8_t, 4>(inputTensorInfo1, std::vector<uint8_t>( |
| 6054 | { |
| 6055 | 63, 35, 77, 70, 56, 112, // 420, 224, 518, 469, 371, 763 |
| 6056 | 203, 28, 252, 168, 245, 91 // 1400, 175, 1743, 1155, 1694, 616 |
| 6057 | })); |
| 6058 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 6059 | // See dequantized values to the right. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6060 | auto input2 = MakeTensor<uint8_t, 4>(inputTensorInfo1, std::vector<uint8_t>( |
| 6061 | { |
| 6062 | 21, 7, 175, 231, 175, 210, // 126, 28, 1204, 1596, 1204, 1449 |
| 6063 | 126, 161, 63, 21, 105, 126 // 861, 1106, 420, 126, 714, 861 |
| 6064 | })); |
| 6065 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 6066 | // See dequantized values to the right. |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6067 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6068 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>( |
| 6069 | { |
| 6070 | 81, 39, 249, 255, 228, 255, // 546, 252, 1722, 2065(clamped), 1575, 2212(clamped) |
| 6071 | 255, 186, 255, 186, 255, 214, // 2261(clamped), 1281, 2163(clamped), 1281, 2408(clamped), 1477 |
| 6072 | })); |
| 6073 | |
| 6074 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 6075 | std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.CreateTensorHandle(inputTensorInfo2); |
| 6076 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6077 | |
| 6078 | armnn::AdditionQueueDescriptor data; |
| 6079 | armnn::WorkloadInfo info; |
| 6080 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 6081 | AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get()); |
| 6082 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 6083 | |
| 6084 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAddition(data, info); |
| 6085 | |
| 6086 | inputHandle1->Allocate(); |
| 6087 | inputHandle2->Allocate(); |
| 6088 | outputHandle->Allocate(); |
| 6089 | |
| 6090 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 6091 | CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0][0]); |
| 6092 | |
| 6093 | workload->Execute(); |
| 6094 | |
| 6095 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6096 | |
| 6097 | return result; |
| 6098 | } |
| 6099 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6100 | namespace |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6101 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6102 | LayerTestResult<uint8_t, 4> MultiplicationUint8TestHelper( |
| 6103 | armnn::IWorkloadFactory& workloadFactory, |
| 6104 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6105 | const unsigned int shape0[4], |
| 6106 | const std::vector<uint8_t> & values0, |
| 6107 | float scale0, |
| 6108 | int32_t offset0, |
| 6109 | const unsigned int shape1[4], |
| 6110 | const std::vector<uint8_t> & values1, |
| 6111 | float scale1, |
| 6112 | int32_t offset1, |
| 6113 | const unsigned int outShape[4], |
| 6114 | const std::vector<uint8_t> & outValues, |
| 6115 | float outScale, |
| 6116 | int32_t outOffset) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6117 | { |
| 6118 | armnn::TensorInfo inputTensorInfo0(4, shape0, armnn::DataType::QuantisedAsymm8); |
| 6119 | armnn::TensorInfo inputTensorInfo1(4, shape1, armnn::DataType::QuantisedAsymm8); |
| 6120 | armnn::TensorInfo outputTensorInfo(4, outShape, armnn::DataType::QuantisedAsymm8); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6121 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6122 | inputTensorInfo0.SetQuantizationScale(scale0); |
| 6123 | inputTensorInfo0.SetQuantizationOffset(offset0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6124 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6125 | inputTensorInfo1.SetQuantizationScale(scale1); |
| 6126 | inputTensorInfo1.SetQuantizationOffset(offset1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6127 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6128 | outputTensorInfo.SetQuantizationScale(outScale); |
| 6129 | outputTensorInfo.SetQuantizationOffset(outOffset); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6130 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6131 | auto input0 = MakeTensor<uint8_t, 4>(inputTensorInfo0, values0); |
| 6132 | auto input1 = MakeTensor<uint8_t, 4>(inputTensorInfo1, values1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6133 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6134 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6135 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, outValues); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6136 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6137 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6138 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6139 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6140 | |
| 6141 | armnn::MultiplicationQueueDescriptor data; |
| 6142 | armnn::WorkloadInfo info; |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6143 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 6144 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6145 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 6146 | |
| 6147 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMultiplication(data, info); |
| 6148 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6149 | inputHandle0->Allocate(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6150 | inputHandle1->Allocate(); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6151 | outputHandle->Allocate(); |
| 6152 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6153 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6154 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6155 | |
| 6156 | workload->Execute(); |
| 6157 | |
| 6158 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6159 | |
| 6160 | return result; |
| 6161 | } |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6162 | } // anonymous namespace |
| 6163 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6164 | LayerTestResult<uint8_t, 4> MultiplicationUint8Test( |
| 6165 | armnn::IWorkloadFactory& workloadFactory, |
| 6166 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6167 | { |
| 6168 | unsigned int batchSize = 1; |
| 6169 | unsigned int channels = 2; |
| 6170 | unsigned int height = 2; |
| 6171 | unsigned int width = 3; |
| 6172 | const unsigned int shape[] = { batchSize, channels, height, width }; |
| 6173 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 6174 | // See dequantized values to the right. |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6175 | std::vector<uint8_t> input0({ |
| 6176 | 62, 37, 3, 172, 13, 111, // 244, 144, 8, 684, 48, 440, |
| 6177 | 188, 20, 73, 31, 23, 31 // 748, 76, 288, 120, 88, 120 |
| 6178 | }); |
| 6179 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 6180 | // See dequantized values to the right. |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6181 | std::vector<uint8_t> input1({ |
| 6182 | 126, 240, 252, 183, 121, 247, // 384, 726, 762, 555, 369, 747, |
| 6183 | 48, 115, 151, 79, 78, 97 // 150, 351, 459, 243, 240, 297 |
| 6184 | }); |
| 6185 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 6186 | // See dequantized values to the right. |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6187 | std::vector<uint8_t> output( |
| 6188 | { |
| 6189 | 64, 72, 0, 255, 8, 236, // 93696, 104544, 6096(clamped), 379620(clamped), 17712, 328680, |
| 6190 | 77, 15, 92, 16, 10, 21, // 112200, 26676, 132192, 29160, 21120, 35640 |
| 6191 | }); |
| 6192 | |
| 6193 | return MultiplicationUint8TestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6194 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6195 | shape, |
| 6196 | input0, |
| 6197 | 4.0f, |
| 6198 | 1, |
| 6199 | shape, |
| 6200 | input1, |
| 6201 | 3.0f, |
| 6202 | -2, |
| 6203 | shape, |
| 6204 | output, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 6205 | 1366.255f, // Scale/offset chosen to have output values out of range. |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6206 | -5); |
| 6207 | } |
| 6208 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6209 | LayerTestResult<uint8_t, 4> MultiplicationBroadcast1ElementUint8Test( |
| 6210 | armnn::IWorkloadFactory& workloadFactory, |
| 6211 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6212 | { |
| 6213 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 6214 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 6215 | |
| 6216 | std::vector<uint8_t> input0({ |
| 6217 | 1, 2, 3, 4, 5, 6, |
| 6218 | 7, 8, 9, 10, 11, 12 |
| 6219 | }); |
| 6220 | |
| 6221 | std::vector<uint8_t> input1({2}); |
| 6222 | |
| 6223 | std::vector<uint8_t> output({ |
| 6224 | 2, 4, 6, 8, 10, 12, |
| 6225 | 14, 16, 18, 20, 22, 24 |
| 6226 | }); |
| 6227 | |
| 6228 | return MultiplicationUint8TestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6229 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6230 | shape0, |
| 6231 | input0, |
| 6232 | 1.0f, |
| 6233 | 0, |
| 6234 | shape1, |
| 6235 | input1, |
| 6236 | 1.0f, |
| 6237 | 0, |
| 6238 | shape0, |
| 6239 | output, |
| 6240 | 1.0f, |
| 6241 | 0); |
| 6242 | } |
| 6243 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6244 | LayerTestResult<uint8_t, 4> MultiplicationBroadcast1DVectorUint8Test( |
| 6245 | armnn::IWorkloadFactory& workloadFactory, |
| 6246 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6247 | { |
| 6248 | const unsigned int shape0[] = { 1, 2, 2, 3 }; |
| 6249 | const unsigned int shape1[] = { 1, 1, 1, 3 }; |
| 6250 | |
| 6251 | std::vector<uint8_t> input0({ |
| 6252 | 1, 2, 3, 4, 5, 6, |
| 6253 | 7, 8, 9, 10, 11, 12 |
| 6254 | }); |
| 6255 | |
| 6256 | std::vector<uint8_t> input1({1, 2, 3}); |
| 6257 | |
| 6258 | std::vector<uint8_t> output({ |
| 6259 | 1, 4, 9, 4, 10, 18, |
| 6260 | 7, 16, 27, 10, 22, 36 |
| 6261 | }); |
| 6262 | |
| 6263 | return MultiplicationUint8TestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6264 | memoryManager, |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 6265 | shape0, |
| 6266 | input0, |
| 6267 | 1.0f, |
| 6268 | 0, |
| 6269 | shape1, |
| 6270 | input1, |
| 6271 | 1.0f, |
| 6272 | 0, |
| 6273 | shape0, |
| 6274 | output, |
| 6275 | 1.0f, |
| 6276 | 0); |
| 6277 | } |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6278 | |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6279 | namespace |
| 6280 | { |
| 6281 | template <typename T> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6282 | LayerTestResult<T, 4> SubtractionTestHelper( |
| 6283 | armnn::IWorkloadFactory& workloadFactory, |
| 6284 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6285 | const unsigned int shape0[4], |
| 6286 | const std::vector<T>& values0, |
| 6287 | float scale0, |
| 6288 | int32_t offset0, |
| 6289 | const unsigned int shape1[4], |
| 6290 | const std::vector<T> & values1, |
| 6291 | float scale1, |
| 6292 | int32_t offset1, |
| 6293 | const unsigned int outShape[4], |
| 6294 | const std::vector<T> & outValues, |
| 6295 | float outScale, |
| 6296 | int32_t outOffset) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6297 | { |
| 6298 | auto dataType = (std::is_same<T, uint8_t>::value ? |
| 6299 | armnn::DataType::QuantisedAsymm8 : |
| 6300 | armnn::DataType::Float32); |
| 6301 | |
| 6302 | armnn::TensorInfo inputTensorInfo0(4, shape0, dataType); |
| 6303 | armnn::TensorInfo inputTensorInfo1(4, shape1, dataType); |
| 6304 | armnn::TensorInfo outputTensorInfo(4, outShape, dataType); |
| 6305 | |
| 6306 | inputTensorInfo0.SetQuantizationScale(scale0); |
| 6307 | inputTensorInfo0.SetQuantizationOffset(offset0); |
| 6308 | |
| 6309 | inputTensorInfo1.SetQuantizationScale(scale1); |
| 6310 | inputTensorInfo1.SetQuantizationOffset(offset1); |
| 6311 | |
| 6312 | outputTensorInfo.SetQuantizationScale(outScale); |
| 6313 | outputTensorInfo.SetQuantizationOffset(outOffset); |
| 6314 | |
| 6315 | auto input0 = MakeTensor<T, 4>(inputTensorInfo0, values0); |
| 6316 | auto input1 = MakeTensor<T, 4>(inputTensorInfo1, values1); |
| 6317 | |
| 6318 | LayerTestResult<T, 4> result(outputTensorInfo); |
| 6319 | result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, outValues); |
| 6320 | |
| 6321 | std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0); |
| 6322 | std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1); |
| 6323 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6324 | |
| 6325 | armnn::SubtractionQueueDescriptor data; |
| 6326 | armnn::WorkloadInfo info; |
| 6327 | AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get()); |
| 6328 | AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get()); |
| 6329 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 6330 | |
| 6331 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateSubtraction(data, info); |
| 6332 | |
| 6333 | inputHandle0->Allocate(); |
| 6334 | inputHandle1->Allocate(); |
| 6335 | outputHandle->Allocate(); |
| 6336 | |
| 6337 | CopyDataToITensorHandle(inputHandle0.get(), &input0[0][0][0][0]); |
| 6338 | CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0][0]); |
| 6339 | |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6340 | workload->Execute(); |
| 6341 | |
| 6342 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6343 | |
| 6344 | return result; |
| 6345 | } |
| 6346 | } // anonymous namespace |
| 6347 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6348 | LayerTestResult<uint8_t, 4> SubtractionUint8Test( |
| 6349 | armnn::IWorkloadFactory& workloadFactory, |
| 6350 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6351 | { |
| 6352 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 6353 | const unsigned int shape1[] = { 1, 1, 2, 2 }; |
| 6354 | |
| 6355 | std::vector<uint8_t> input0({ 10, 12, 14, 16 }); |
| 6356 | std::vector<uint8_t> input1({ 1, 2, 1, 2 }); |
| 6357 | std::vector<uint8_t> output({ 3, 3, 5, 5 }); |
| 6358 | |
| 6359 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6360 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6361 | shape0, input0, 0.5f, 2, |
| 6362 | shape1, input1, 1.0f, 0, |
| 6363 | shape0, output, 1.0f, 0); |
| 6364 | } |
| 6365 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6366 | LayerTestResult<uint8_t, 4> SubtractionBroadcast1ElementUint8Test( |
| 6367 | armnn::IWorkloadFactory& workloadFactory, |
| 6368 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6369 | { |
| 6370 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 6371 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 6372 | |
| 6373 | std::vector<uint8_t> input0({ 10, 12, 14, 16 }); |
| 6374 | std::vector<uint8_t> input1({ 2 }); |
| 6375 | std::vector<uint8_t> output({ 5, 6, 7, 8 }); |
| 6376 | |
| 6377 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6378 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6379 | shape0, input0, 0.5f, 2, |
| 6380 | shape1, input1, 1.0f, 0, |
| 6381 | shape0, output, 1.0f, 3); |
| 6382 | } |
| 6383 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6384 | LayerTestResult<uint8_t, 4> SubtractionBroadcastUint8Test( |
| 6385 | armnn::IWorkloadFactory& workloadFactory, |
| 6386 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6387 | { |
| 6388 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 6389 | const unsigned int shape1[] = { 1, 1, 2, 1 }; |
| 6390 | |
| 6391 | std::vector<uint8_t> input0({ 10, 12, 14, 16 }); |
| 6392 | std::vector<uint8_t> input1({ 2, 1 }); |
| 6393 | std::vector<uint8_t> output({ 8, 11, 12, 15 }); |
| 6394 | |
| 6395 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6396 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6397 | shape0, input0, 1.0f, 0, |
| 6398 | shape1, input1, 1.0f, 0, |
| 6399 | shape0, output, 1.0f, 0); |
| 6400 | } |
| 6401 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6402 | LayerTestResult<float, 4> SubtractionTest( |
| 6403 | armnn::IWorkloadFactory& workloadFactory, |
| 6404 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6405 | { |
| 6406 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 6407 | const unsigned int shape1[] = { 1, 1, 2, 2 }; |
| 6408 | |
| 6409 | std::vector<float> input0({ 1, 2, 3, 4 }); |
| 6410 | std::vector<float> input1({ 1, -1, 0, 2 }); |
| 6411 | std::vector<float> output({ 0, 3, 3, 2 }); |
| 6412 | |
| 6413 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6414 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6415 | shape0, input0, 1.0f, 0, |
| 6416 | shape1, input1, 1.0f, 0, |
| 6417 | shape0, output, 1.0f, 0); |
| 6418 | } |
| 6419 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6420 | LayerTestResult<float, 4> SubtractionBroadcast1ElementTest( |
| 6421 | armnn::IWorkloadFactory& workloadFactory, |
| 6422 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6423 | { |
| 6424 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 6425 | const unsigned int shape1[] = { 1, 1, 1, 1 }; |
| 6426 | |
| 6427 | std::vector<float> input0({ 1, 2, 3, 4 }); |
| 6428 | std::vector<float> input1({ 10 }); |
| 6429 | std::vector<float> output({ -9, -8, -7, -6 }); |
| 6430 | |
| 6431 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6432 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6433 | shape0, input0, 1.0f, 0, |
| 6434 | shape1, input1, 1.0f, 0, |
| 6435 | shape0, output, 1.0f, 0); |
| 6436 | } |
| 6437 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6438 | LayerTestResult<float, 4> SubtractionBroadcastTest( |
| 6439 | armnn::IWorkloadFactory& workloadFactory, |
| 6440 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6441 | { |
| 6442 | const unsigned int shape0[] = { 1, 1, 2, 2 }; |
| 6443 | const unsigned int shape1[] = { 1, 1, 1, 2 }; |
| 6444 | |
| 6445 | std::vector<float> input0({ 1, 2, 3, 4 }); |
| 6446 | std::vector<float> input1({ 10, -5 }); |
| 6447 | std::vector<float> output({ -9, 7, -7, 9 }); |
| 6448 | |
| 6449 | return SubtractionTestHelper(workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6450 | memoryManager, |
David Beck | f195f03 | 2018-09-06 16:46:34 +0100 | [diff] [blame] | 6451 | shape0, input0, 1.0f, 0, |
| 6452 | shape1, input1, 1.0f, 0, |
| 6453 | shape0, output, 1.0f, 0); |
| 6454 | } |
| 6455 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6456 | LayerTestResult<uint8_t, 4> ResizeBilinearNopUint8Test( |
| 6457 | armnn::IWorkloadFactory& workloadFactory, |
| 6458 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6459 | { |
| 6460 | constexpr unsigned int inputWidth = 4; |
| 6461 | constexpr unsigned int inputHeight = 4; |
| 6462 | constexpr unsigned int inputChannels = 1; |
| 6463 | constexpr unsigned int inputBatchSize = 1; |
| 6464 | |
| 6465 | constexpr unsigned int outputWidth = inputWidth; |
| 6466 | constexpr unsigned int outputHeight = inputHeight; |
| 6467 | constexpr unsigned int outputChannels = inputChannels; |
| 6468 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6469 | |
| 6470 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6471 | armnn::DataType::QuantisedAsymm8); |
| 6472 | inputTensorInfo.SetQuantizationScale(1.5f); |
| 6473 | inputTensorInfo.SetQuantizationOffset(-3); |
| 6474 | |
| 6475 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6476 | armnn::DataType::QuantisedAsymm8); |
| 6477 | outputTensorInfo.SetQuantizationScale(1.5f); |
| 6478 | outputTensorInfo.SetQuantizationOffset(-3); |
| 6479 | |
| 6480 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6481 | 1, 2, 3, 4, |
| 6482 | 2, 3, 4, 5, |
| 6483 | 3, 4, 5, 6, |
| 6484 | 4, 5, 6, 7 |
| 6485 | })); |
| 6486 | |
| 6487 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6488 | result.outputExpected = input; |
| 6489 | |
| 6490 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6491 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6492 | |
| 6493 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6494 | armnn::WorkloadInfo info; |
| 6495 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6496 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6497 | |
| 6498 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6499 | |
| 6500 | inputHandle->Allocate(); |
| 6501 | outputHandle->Allocate(); |
| 6502 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6503 | |
| 6504 | workload->Execute(); |
| 6505 | |
| 6506 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6507 | return result; |
| 6508 | } |
| 6509 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6510 | LayerTestResult<uint8_t, 4> SimpleResizeBilinearUint8Test( |
| 6511 | armnn::IWorkloadFactory& workloadFactory, |
| 6512 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6513 | { |
| 6514 | constexpr unsigned int inputWidth = 2; |
| 6515 | constexpr unsigned int inputHeight = 2; |
| 6516 | constexpr unsigned int inputChannels = 1; |
| 6517 | constexpr unsigned int inputBatchSize = 1; |
| 6518 | |
| 6519 | constexpr unsigned int outputWidth = inputWidth / 2; |
| 6520 | constexpr unsigned int outputHeight = inputHeight / 2; |
| 6521 | constexpr unsigned int outputChannels = inputChannels; |
| 6522 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6523 | |
| 6524 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6525 | armnn::DataType::QuantisedAsymm8); |
| 6526 | inputTensorInfo.SetQuantizationScale(0.1567f); |
| 6527 | inputTensorInfo.SetQuantizationOffset(1); |
| 6528 | |
| 6529 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6530 | armnn::DataType::QuantisedAsymm8); |
| 6531 | outputTensorInfo.SetQuantizationScale(0.1567f); |
| 6532 | outputTensorInfo.SetQuantizationOffset(1); |
| 6533 | |
| 6534 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6535 | 1, 255, |
| 6536 | 200, 250 |
| 6537 | })); |
| 6538 | |
| 6539 | // The 'resize bilinear' operation projects the top-left corner of output texels into the input image, |
| 6540 | // 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] | 6541 | // 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] | 6542 | // that was at position (0,0) of the input matrix (rather than an average, which we would expect if projecting |
| 6543 | // the centre). |
| 6544 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6545 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>({ |
| 6546 | 1 |
| 6547 | })); |
| 6548 | |
| 6549 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6550 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6551 | |
| 6552 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6553 | armnn::WorkloadInfo info; |
| 6554 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6555 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6556 | |
| 6557 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6558 | |
| 6559 | inputHandle->Allocate(); |
| 6560 | outputHandle->Allocate(); |
| 6561 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6562 | |
| 6563 | workload->Execute(); |
| 6564 | |
| 6565 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6566 | return result; |
| 6567 | } |
| 6568 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6569 | LayerTestResult<uint8_t, 4> ResizeBilinearSqMinUint8Test( |
| 6570 | armnn::IWorkloadFactory& workloadFactory, |
| 6571 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6572 | { |
| 6573 | constexpr unsigned int inputWidth = 4; |
| 6574 | constexpr unsigned int inputHeight = 4; |
| 6575 | constexpr unsigned int inputChannels = 1; |
| 6576 | constexpr unsigned int inputBatchSize = 1; |
| 6577 | |
| 6578 | constexpr unsigned int outputWidth = inputWidth / 2; |
| 6579 | constexpr unsigned int outputHeight = inputHeight / 2; |
| 6580 | constexpr unsigned int outputChannels = inputChannels; |
| 6581 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6582 | |
| 6583 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6584 | armnn::DataType::QuantisedAsymm8); |
| 6585 | inputTensorInfo.SetQuantizationScale(3.141592f); |
| 6586 | inputTensorInfo.SetQuantizationOffset(3); |
| 6587 | |
| 6588 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6589 | armnn::DataType::QuantisedAsymm8); |
| 6590 | outputTensorInfo.SetQuantizationScale(3.141592f); |
| 6591 | outputTensorInfo.SetQuantizationOffset(3); |
| 6592 | |
| 6593 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6594 | 1, 2, 3, 4, |
| 6595 | 2, 3, 4, 5, |
| 6596 | 3, 4, 5, 6, |
| 6597 | 4, 5, 6, 7 |
| 6598 | })); |
| 6599 | |
| 6600 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6601 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>({ |
| 6602 | 1, 3, |
| 6603 | 3, 5 |
| 6604 | })); |
| 6605 | |
| 6606 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6607 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6608 | |
| 6609 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6610 | armnn::WorkloadInfo info; |
| 6611 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6612 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6613 | |
| 6614 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6615 | |
| 6616 | inputHandle->Allocate(); |
| 6617 | outputHandle->Allocate(); |
| 6618 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6619 | |
| 6620 | workload->Execute(); |
| 6621 | |
| 6622 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6623 | return result; |
| 6624 | } |
| 6625 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6626 | LayerTestResult<uint8_t, 4> ResizeBilinearMinUint8Test( |
| 6627 | armnn::IWorkloadFactory& workloadFactory, |
| 6628 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6629 | { |
| 6630 | constexpr unsigned int inputWidth = 3; |
| 6631 | constexpr unsigned int inputHeight = 2; |
| 6632 | constexpr unsigned int inputChannels = 1; |
| 6633 | constexpr unsigned int inputBatchSize = 1; |
| 6634 | |
| 6635 | constexpr unsigned int outputWidth = 2; |
| 6636 | constexpr unsigned int outputHeight = 1; |
| 6637 | constexpr unsigned int outputChannels = inputChannels; |
| 6638 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6639 | |
| 6640 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6641 | armnn::DataType::QuantisedAsymm8); |
| 6642 | inputTensorInfo.SetQuantizationScale(1.5f); |
| 6643 | inputTensorInfo.SetQuantizationOffset(-1); |
| 6644 | |
| 6645 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6646 | armnn::DataType::QuantisedAsymm8); |
| 6647 | outputTensorInfo.SetQuantizationScale(1.5f); |
| 6648 | outputTensorInfo.SetQuantizationOffset(-1); |
| 6649 | |
| 6650 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6651 | 1, 2, 3, // 3.0, 4.5, 6.0 |
| 6652 | 5, 8, 13 // 9.0, 13.5, 21.0 |
| 6653 | })); |
| 6654 | |
| 6655 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6656 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>({ |
| 6657 | 1, 3 // 3.0, 5.25 |
| 6658 | })); |
| 6659 | |
| 6660 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6661 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6662 | |
| 6663 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6664 | armnn::WorkloadInfo info; |
| 6665 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6666 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6667 | |
| 6668 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6669 | |
| 6670 | inputHandle->Allocate(); |
| 6671 | outputHandle->Allocate(); |
| 6672 | |
| 6673 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6674 | |
| 6675 | workload->Execute(); |
| 6676 | |
| 6677 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6678 | return result; |
| 6679 | } |
| 6680 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6681 | LayerTestResult<uint8_t, 4> ResizeBilinearMagUint8Test( |
| 6682 | armnn::IWorkloadFactory& workloadFactory, |
| 6683 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6684 | { |
| 6685 | constexpr unsigned int inputWidth = 2; |
| 6686 | constexpr unsigned int inputHeight = 3; |
| 6687 | constexpr unsigned int inputChannels = 1; |
| 6688 | constexpr unsigned int inputBatchSize = 1; |
| 6689 | |
| 6690 | constexpr unsigned int outputWidth = 5; |
| 6691 | constexpr unsigned int outputHeight = 3; |
| 6692 | constexpr unsigned int outputChannels = inputChannels; |
| 6693 | constexpr unsigned int outputBatchSize = inputBatchSize; |
| 6694 | |
| 6695 | armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| 6696 | armnn::DataType::QuantisedAsymm8); |
| 6697 | inputTensorInfo.SetQuantizationScale(0.010765f); |
| 6698 | inputTensorInfo.SetQuantizationOffset(7); |
| 6699 | |
| 6700 | armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| 6701 | armnn::DataType::QuantisedAsymm8); |
| 6702 | outputTensorInfo.SetQuantizationScale(0.010132f); |
| 6703 | outputTensorInfo.SetQuantizationOffset(-18); |
| 6704 | |
| 6705 | auto input = MakeTensor<uint8_t, 4>(inputTensorInfo, std::vector<uint8_t>({ |
| 6706 | 24, 228, // 0.183005, 2.379065, |
| 6707 | 105, 128, // 1.05497, 1.302565 |
| 6708 | 230, 71 // 2.400595, 0.68896 |
| 6709 | })); |
| 6710 | |
| 6711 | LayerTestResult<uint8_t, 4> result(outputTensorInfo); |
| 6712 | result.outputExpected = MakeTensor<uint8_t, 4>(outputTensorInfo, std::vector<uint8_t>({ |
| 6713 | 0, 87, 173, 217, 217, // 0.18300501, 1.06142902, 1.93985295, 2.37906504, 2.37906504 |
| 6714 | 86, 96, 106, 111, 111, // 1.05497003, 1.15400803, 1.25304604, 1.30256498, 1.30256498 |
| 6715 | 219, 151, 84, 50, 50 // 2.40059495, 1.71594095, 1.03128707, 0.68896002, 0.68896002 |
| 6716 | })); |
| 6717 | |
| 6718 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6719 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6720 | |
| 6721 | armnn::ResizeBilinearQueueDescriptor descriptor; |
| 6722 | armnn::WorkloadInfo info; |
| 6723 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6724 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6725 | |
| 6726 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResizeBilinear(descriptor, info); |
| 6727 | |
| 6728 | inputHandle->Allocate(); |
| 6729 | outputHandle->Allocate(); |
| 6730 | CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| 6731 | |
| 6732 | workload->Execute(); |
| 6733 | |
| 6734 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 6735 | return result; |
| 6736 | } |
| 6737 | |
Mohamed Nour Abouelseoud | a1d3c6a | 2018-12-27 12:39:16 +0000 | [diff] [blame] | 6738 | LayerTestResult<float, 2> Rsqrt2dTestCommon( |
| 6739 | armnn::IWorkloadFactory& workloadFactory, |
| 6740 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 6741 | const armnn::TensorInfo inputTensorInfo, |
| 6742 | const armnn::TensorInfo outputTensorInfo, |
| 6743 | std::vector<float> inputValues, |
| 6744 | std::vector<float> expectedOutputValues) |
| 6745 | { |
| 6746 | auto inputTensor = MakeTensor<float, 2>(inputTensorInfo, std::vector<float>(inputValues)); |
| 6747 | |
| 6748 | LayerTestResult<float, 2> result(outputTensorInfo); |
| 6749 | result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, std::vector<float>(expectedOutputValues)); |
| 6750 | |
| 6751 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6752 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6753 | |
| 6754 | armnn::RsqrtQueueDescriptor descriptor; |
| 6755 | |
| 6756 | armnn::WorkloadInfo info; |
| 6757 | |
| 6758 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6759 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6760 | |
| 6761 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateRsqrt(descriptor, info); |
| 6762 | |
| 6763 | inputHandle->Allocate(); |
| 6764 | outputHandle->Allocate(); |
| 6765 | |
| 6766 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]); |
| 6767 | |
| 6768 | workload->Execute(); |
| 6769 | |
| 6770 | CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get()); |
| 6771 | |
| 6772 | return result; |
| 6773 | } |
| 6774 | LayerTestResult<float, 2> Rsqrt2dTest( |
| 6775 | armnn::IWorkloadFactory& workloadFactory, |
| 6776 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6777 | { |
| 6778 | const armnn::TensorShape inputShape{ 2, 2 }; |
| 6779 | const armnn::TensorShape outputShape{ 2, 2 }; |
| 6780 | |
| 6781 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32); |
| 6782 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 6783 | |
| 6784 | std::vector<float> inputValues |
| 6785 | { |
| 6786 | 1.f, 4.f, |
| 6787 | 16.f, 25.f |
| 6788 | }; |
| 6789 | |
| 6790 | std::vector<float> expectedOutputValues |
| 6791 | { |
| 6792 | 1.f, 0.5f, |
| 6793 | 0.25f, 0.2f |
| 6794 | }; |
| 6795 | |
| 6796 | return Rsqrt2dTestCommon(workloadFactory, memoryManager, |
| 6797 | inputTensorInfo, outputTensorInfo, |
| 6798 | inputValues, expectedOutputValues); |
| 6799 | } |
| 6800 | |
| 6801 | LayerTestResult<float, 3> Rsqrt3dTest( |
| 6802 | armnn::IWorkloadFactory& workloadFactory, |
| 6803 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6804 | { |
| 6805 | const armnn::TensorShape inputShape{ 3, 1, 2 }; |
| 6806 | const armnn::TensorShape outputShape{ 3, 1, 2 }; |
| 6807 | |
| 6808 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32); |
| 6809 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 6810 | |
| 6811 | std::vector<float> inputValues |
| 6812 | { |
| 6813 | 1.f, 4.f, 16.f, |
| 6814 | 25.f, 64.f, 100.f |
| 6815 | }; |
| 6816 | |
| 6817 | std::vector<float> expectedOutputValues |
| 6818 | { |
| 6819 | 1.f, 0.5f, 0.25f, |
| 6820 | 0.2f, 0.125f, 0.1f |
| 6821 | }; |
| 6822 | |
| 6823 | auto inputTensor = MakeTensor<float, 3>(inputTensorInfo, std::vector<float>(inputValues)); |
| 6824 | |
| 6825 | LayerTestResult<float, 3> result(outputTensorInfo); |
| 6826 | result.outputExpected = MakeTensor<float, 3>(outputTensorInfo, std::vector<float >(expectedOutputValues)); |
| 6827 | |
| 6828 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 6829 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 6830 | |
| 6831 | armnn::RsqrtQueueDescriptor descriptor; |
| 6832 | |
| 6833 | armnn::WorkloadInfo info; |
| 6834 | |
| 6835 | AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| 6836 | AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| 6837 | |
| 6838 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateRsqrt(descriptor, info); |
| 6839 | |
| 6840 | inputHandle->Allocate(); |
| 6841 | outputHandle->Allocate(); |
| 6842 | |
| 6843 | CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0]); |
| 6844 | |
| 6845 | workload->Execute(); |
| 6846 | |
| 6847 | CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get()); |
| 6848 | |
| 6849 | return result; |
| 6850 | } |
| 6851 | |
| 6852 | LayerTestResult<float, 2> RsqrtZeroTest( |
| 6853 | armnn::IWorkloadFactory& workloadFactory, |
| 6854 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6855 | { |
| 6856 | const armnn::TensorShape inputShape{ 1, 2 }; |
| 6857 | const armnn::TensorShape outputShape{ 1, 2 }; |
| 6858 | |
| 6859 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32); |
| 6860 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 6861 | |
| 6862 | std::vector<float> inputValues |
| 6863 | { |
| 6864 | 0.f, -0.f |
| 6865 | }; |
| 6866 | |
| 6867 | std::vector<float> expectedOutputValues |
| 6868 | { |
| 6869 | INFINITY, -INFINITY |
| 6870 | }; |
| 6871 | |
| 6872 | return Rsqrt2dTestCommon(workloadFactory, memoryManager, |
| 6873 | inputTensorInfo, outputTensorInfo, |
| 6874 | inputValues, expectedOutputValues); |
| 6875 | } |
| 6876 | |
| 6877 | LayerTestResult<float, 2> RsqrtNegativeTest( |
| 6878 | armnn::IWorkloadFactory& workloadFactory, |
| 6879 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 6880 | { |
| 6881 | const armnn::TensorShape inputShape{ 1, 2 }; |
| 6882 | const armnn::TensorShape outputShape{ 1, 2 }; |
| 6883 | |
| 6884 | const armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32); |
| 6885 | const armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| 6886 | |
| 6887 | std::vector<float> inputValues |
| 6888 | { |
| 6889 | -25.f, -16.f |
| 6890 | }; |
| 6891 | |
| 6892 | std::vector<float> expectedOutputValues |
| 6893 | { |
| 6894 | -NAN, -NAN |
| 6895 | }; |
| 6896 | |
| 6897 | return Rsqrt2dTestCommon(workloadFactory, memoryManager, |
| 6898 | inputTensorInfo, outputTensorInfo, |
| 6899 | inputValues, expectedOutputValues); |
| 6900 | } |
| 6901 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6902 | LayerTestResult<float, 4> BatchNormTest( |
| 6903 | armnn::IWorkloadFactory& workloadFactory, |
| 6904 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6905 | { |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6906 | // BatchSize: 1 |
| 6907 | // Channels: 2 |
| 6908 | // Height: 3 |
| 6909 | // Width: 2 |
| 6910 | |
| 6911 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 6912 | std::vector<float> inputValues |
| 6913 | { |
| 6914 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 6915 | 1.f, 4.f, |
| 6916 | 4.f, 2.f, |
| 6917 | 1.f, 6.f, |
| 6918 | |
| 6919 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 6920 | 1.f, 1.f, |
| 6921 | 4.f, 1.f, |
| 6922 | -2.f, 4.f |
| 6923 | }; |
| 6924 | std::vector<float> expectedOutputValues |
| 6925 | { |
| 6926 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 6927 | 1.f, 4.f, |
| 6928 | 4.f, 2.f, |
| 6929 | 1.f, 6.f, |
| 6930 | |
| 6931 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 6932 | 3.f, 3.f, |
| 6933 | 4.f, 3.f, |
| 6934 | 2.f, 4.f |
| 6935 | }; |
| 6936 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6937 | return BatchNormTestImpl<float>(workloadFactory, memoryManager, |
| 6938 | inputOutputShape, inputValues, expectedOutputValues, |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6939 | 0.f, 0, armnn::DataLayout::NCHW); |
| 6940 | } |
| 6941 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6942 | LayerTestResult<float, 4> BatchNormNhwcTest( |
| 6943 | armnn::IWorkloadFactory& workloadFactory, |
| 6944 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6945 | { |
| 6946 | // BatchSize: 1 |
| 6947 | // Height: 3 |
| 6948 | // Width: 2 |
| 6949 | // Channels: 2 |
| 6950 | |
| 6951 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 6952 | std::vector<float> inputValues |
| 6953 | { |
| 6954 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 6955 | 1.f, 1.f, |
| 6956 | 4.f, 1.f, |
| 6957 | |
| 6958 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 6959 | 4.f, 4.f, |
| 6960 | 2.f, 1.f, |
| 6961 | |
| 6962 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 6963 | 1.f, -2.f, |
| 6964 | 6.f, 4.f |
| 6965 | }; |
| 6966 | std::vector<float> expectedOutputValues |
| 6967 | { |
| 6968 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 6969 | 1.f, 3.f, |
| 6970 | 4.f, 3.f, |
| 6971 | |
| 6972 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 6973 | 4.f, 4.f, |
| 6974 | 2.f, 3.f, |
| 6975 | |
| 6976 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 6977 | 1.f, 2.f, |
| 6978 | 6.f, 4.f |
| 6979 | }; |
| 6980 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6981 | return BatchNormTestImpl<float>(workloadFactory, memoryManager, |
| 6982 | inputOutputShape, inputValues, expectedOutputValues, |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6983 | 0.f, 0, armnn::DataLayout::NHWC); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6984 | } |
| 6985 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 6986 | LayerTestResult<uint8_t, 4> BatchNormUint8Test( |
| 6987 | armnn::IWorkloadFactory& workloadFactory, |
| 6988 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6989 | { |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 6990 | // BatchSize: 1 |
| 6991 | // Channels: 2 |
| 6992 | // Height: 3 |
| 6993 | // Width: 2 |
| 6994 | |
| 6995 | const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 }; |
| 6996 | std::vector<float> inputValues |
| 6997 | { |
| 6998 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 6999 | 1.f, 4.f, |
| 7000 | 4.f, 2.f, |
| 7001 | 1.f, 6.f, |
| 7002 | |
| 7003 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 7004 | 1.f, 1.f, |
| 7005 | 4.f, 1.f, |
| 7006 | -2.f, 4.f |
| 7007 | }; |
| 7008 | std::vector<float> expectedOutputValues |
| 7009 | { |
| 7010 | // Batch 0, Channel 0, Height (3) x Width (2) |
| 7011 | 1.f, 4.f, |
| 7012 | 4.f, 2.f, |
| 7013 | 1.f, 6.f, |
| 7014 | |
| 7015 | // Batch 0, Channel 1, Height (3) x Width (2) |
| 7016 | 3.f, 3.f, |
| 7017 | 4.f, 3.f, |
| 7018 | 2.f, 4.f |
| 7019 | }; |
| 7020 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7021 | return BatchNormTestImpl<uint8_t>(workloadFactory, memoryManager, |
| 7022 | inputOutputShape, inputValues, expectedOutputValues, |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 7023 | 1.f/20.f, 50, armnn::DataLayout::NCHW); |
| 7024 | } |
| 7025 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7026 | LayerTestResult<uint8_t, 4> BatchNormUint8NhwcTest( |
| 7027 | armnn::IWorkloadFactory& workloadFactory, |
| 7028 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 7029 | { |
| 7030 | // BatchSize: 1 |
| 7031 | // Height: 3 |
| 7032 | // Width: 2 |
| 7033 | // Channels: 2 |
| 7034 | |
| 7035 | const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 }; |
| 7036 | std::vector<float> inputValues |
| 7037 | { |
| 7038 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 7039 | 1.f, 1.f, |
| 7040 | 4.f, 1.f, |
| 7041 | |
| 7042 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 7043 | 4.f, 4.f, |
| 7044 | 2.f, 1.f, |
| 7045 | |
| 7046 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 7047 | 1.f, -2.f, |
| 7048 | 6.f, 4.f |
| 7049 | }; |
| 7050 | std::vector<float> expectedOutputValues |
| 7051 | { |
| 7052 | // Batch 0, Height 0, Width (2) x Channel (2) |
| 7053 | 1.f, 3.f, |
| 7054 | 4.f, 3.f, |
| 7055 | |
| 7056 | // Batch 0, Height 1, Width (2) x Channel (2) |
| 7057 | 4.f, 4.f, |
| 7058 | 2.f, 3.f, |
| 7059 | |
| 7060 | // Batch 0, Height 2, Width (2) x Channel (2) |
| 7061 | 1.f, 2.f, |
| 7062 | 6.f, 4.f |
| 7063 | }; |
| 7064 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7065 | return BatchNormTestImpl<uint8_t>(workloadFactory, memoryManager, |
| 7066 | inputOutputShape, inputValues, expectedOutputValues, |
Matteo Martincigh | 8eb675e | 2018-10-17 14:43:29 +0100 | [diff] [blame] | 7067 | 1.f/20.f, 50, armnn::DataLayout::NHWC); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7068 | } |
| 7069 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7070 | LayerTestResult<uint8_t, 4> ConstantUint8Test( |
| 7071 | armnn::IWorkloadFactory& workloadFactory, |
| 7072 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7073 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7074 | return ConstantTestImpl<uint8_t>(workloadFactory, memoryManager, 2e-6f, 1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7075 | } |
| 7076 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7077 | LayerTestResult<uint8_t, 1> Concatenation1dUint8Test( |
| 7078 | armnn::IWorkloadFactory& workloadFactory, |
| 7079 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7080 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7081 | return Concatenation1dTestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7082 | } |
| 7083 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7084 | LayerTestResult<uint8_t, 2> Concatenation2dDim0Uint8Test( |
| 7085 | armnn::IWorkloadFactory& workloadFactory, |
| 7086 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7087 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7088 | return Concatenation2dDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7089 | } |
| 7090 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7091 | LayerTestResult<uint8_t, 2> Concatenation2dDim1Uint8Test( |
| 7092 | armnn::IWorkloadFactory& workloadFactory, |
| 7093 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7094 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7095 | return Concatenation2dDim1TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7096 | } |
| 7097 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7098 | LayerTestResult<uint8_t, 2> Concatenation2dDim0DiffInputDimsUint8Test( |
| 7099 | armnn::IWorkloadFactory& workloadFactory, |
| 7100 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7101 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7102 | return Concatenation2dDim0DiffInputDimsTestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7103 | } |
| 7104 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7105 | LayerTestResult<uint8_t, 2> Concatenation2dDim1DiffInputDimsUint8Test( |
| 7106 | armnn::IWorkloadFactory& workloadFactory, |
| 7107 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7108 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7109 | return Concatenation2dDim1DiffInputDimsTestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7110 | } |
| 7111 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7112 | LayerTestResult<uint8_t, 3> Concatenation3dDim0Uint8Test( |
| 7113 | armnn::IWorkloadFactory& workloadFactory, |
| 7114 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7115 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7116 | return Concatenation3dDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7117 | } |
| 7118 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7119 | LayerTestResult<uint8_t, 3> Concatenation3dDim1Uint8Test( |
| 7120 | armnn::IWorkloadFactory& workloadFactory, |
| 7121 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7122 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7123 | return Concatenation3dDim1TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7124 | } |
| 7125 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7126 | LayerTestResult<uint8_t, 3> Concatenation3dDim2Uint8Test( |
| 7127 | armnn::IWorkloadFactory& workloadFactory, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 7128 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7129 | bool useSubtensor) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7130 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 7131 | return Concatenation3dDim2TestImpl<uint8_t>(workloadFactory, memoryManager, useSubtensor, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7132 | } |
| 7133 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7134 | LayerTestResult<uint8_t, 3> Concatenation3dDim0DiffInputDimsUint8Test( |
| 7135 | armnn::IWorkloadFactory& workloadFactory, |
| 7136 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7137 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7138 | return Concatenation3dDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7139 | } |
| 7140 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7141 | LayerTestResult<uint8_t, 3> Concatenation3dDim1DiffInputDimsUint8Test( |
| 7142 | armnn::IWorkloadFactory& workloadFactory, |
| 7143 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7144 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7145 | return Concatenation3dDim1DiffInputDimsTestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7146 | } |
| 7147 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7148 | LayerTestResult<uint8_t, 3> Concatenation3dDim2DiffInputDimsUint8Test( |
| 7149 | armnn::IWorkloadFactory& workloadFactory, |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 7150 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7151 | bool useSubtensor) |
| 7152 | { |
| 7153 | return Concatenation3dDim2DiffInputDimsTestImpl<uint8_t>(workloadFactory, memoryManager, useSubtensor, 0.5f, -1); |
| 7154 | } |
| 7155 | |
| 7156 | LayerTestResult<uint8_t, 4> Concatenation4dDim0Uint8Test( |
| 7157 | armnn::IWorkloadFactory& workloadFactory, |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7158 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7159 | { |
narpra01 | 5cdda35 | 2018-11-19 15:30:27 +0000 | [diff] [blame] | 7160 | return Concatenation4dDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 7161 | } |
| 7162 | |
| 7163 | LayerTestResult<uint8_t, 4> Concatenation4dDim1Uint8Test( |
| 7164 | armnn::IWorkloadFactory& workloadFactory, |
| 7165 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7166 | { |
| 7167 | return Concatenation4dDim1TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 7168 | } |
| 7169 | |
| 7170 | LayerTestResult<uint8_t, 4> Concatenation4dDim2Uint8Test( |
| 7171 | armnn::IWorkloadFactory& workloadFactory, |
| 7172 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7173 | { |
| 7174 | return Concatenation4dDim2TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 7175 | } |
| 7176 | |
| 7177 | LayerTestResult<uint8_t, 4> Concatenation4dDim3Uint8Test( |
| 7178 | armnn::IWorkloadFactory& workloadFactory, |
| 7179 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool useSubtensor) |
| 7180 | { |
| 7181 | return Concatenation4dDim3TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1, useSubtensor); |
| 7182 | } |
| 7183 | |
| 7184 | LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim0Uint8Test( |
| 7185 | armnn::IWorkloadFactory& workloadFactory, |
| 7186 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7187 | { |
| 7188 | return Concatenation4dDiffShapeDim0TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 7189 | } |
| 7190 | |
| 7191 | LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim1Uint8Test( |
| 7192 | armnn::IWorkloadFactory& workloadFactory, |
| 7193 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7194 | { |
| 7195 | return Concatenation4dDiffShapeDim1TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 7196 | } |
| 7197 | |
| 7198 | LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim2Uint8Test( |
| 7199 | armnn::IWorkloadFactory& workloadFactory, |
| 7200 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 7201 | { |
| 7202 | return Concatenation4dDiffShapeDim2TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1); |
| 7203 | } |
| 7204 | |
| 7205 | LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim3Uint8Test( |
| 7206 | armnn::IWorkloadFactory& workloadFactory, |
| 7207 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7208 | bool useSubtensor) |
| 7209 | { |
| 7210 | return Concatenation4dDiffShapeDim3TestImpl<uint8_t>(workloadFactory, memoryManager, 0.5f, -1, useSubtensor); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7211 | } |
| 7212 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7213 | LayerTestResult<float, 4> SimpleMaxPooling2dSize2x2Stride2x2Test( |
| 7214 | armnn::IWorkloadFactory& workloadFactory, |
| 7215 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7216 | bool forceNoPadding) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7217 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7218 | return SimpleMaxPooling2dSize2x2Stride2x2TestCommon<float>(workloadFactory, memoryManager, forceNoPadding); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7219 | } |
| 7220 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7221 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize2x2Stride2x2Uint8Test( |
| 7222 | armnn::IWorkloadFactory& workloadFactory, |
| 7223 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7224 | bool forceNoPadding) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7225 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7226 | return SimpleMaxPooling2dSize2x2Stride2x2TestCommon<uint8_t>( |
| 7227 | workloadFactory, memoryManager, forceNoPadding, 3.0f, -5); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7228 | } |
| 7229 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7230 | LayerTestResult<float, 4> SimpleMaxPooling2dSize3x3Stride2x4Test( |
| 7231 | armnn::IWorkloadFactory& workloadFactory, |
| 7232 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7233 | bool forceNoPadding) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7234 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7235 | return SimpleMaxPooling2dSize3x3Stride2x4TestCommon<float>(workloadFactory, memoryManager, forceNoPadding); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7236 | } |
| 7237 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7238 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize3x3Stride2x4Uint8Test( |
| 7239 | armnn::IWorkloadFactory& workloadFactory, |
| 7240 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7241 | bool forceNoPadding) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7242 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7243 | return SimpleMaxPooling2dSize3x3Stride2x4TestCommon<uint8_t>( |
| 7244 | workloadFactory, memoryManager, forceNoPadding, 0.1f, 128); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7245 | } |
| 7246 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7247 | LayerTestResult<float, 4> SimpleMaxPooling2dTest( |
| 7248 | armnn::IWorkloadFactory& workloadFactory, |
| 7249 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 7250 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7251 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7252 | return SimpleMaxPooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7253 | } |
| 7254 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7255 | LayerTestResult<uint8_t, 4> SimpleMaxPooling2dUint8Test( |
| 7256 | armnn::IWorkloadFactory& workloadFactory, |
| 7257 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 7258 | const armnn::DataLayout dataLayout) |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 7259 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7260 | return SimpleMaxPooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, dataLayout); |
Francis Murtagh | 043d0d0 | 2018-10-05 14:08:48 +0100 | [diff] [blame] | 7261 | } |
| 7262 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7263 | LayerTestResult<float, 4> SimpleAveragePooling2dTest( |
| 7264 | armnn::IWorkloadFactory& workloadFactory, |
| 7265 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 7266 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7267 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7268 | return SimpleAveragePooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout); |
James Conroy | 6948227 | 2018-10-19 10:41:35 +0100 | [diff] [blame] | 7269 | } |
| 7270 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7271 | LayerTestResult<uint8_t, 4> SimpleAveragePooling2dUint8Test( |
| 7272 | armnn::IWorkloadFactory& workloadFactory, |
| 7273 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 7274 | const armnn::DataLayout dataLayout) |
James Conroy | 6948227 | 2018-10-19 10:41:35 +0100 | [diff] [blame] | 7275 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7276 | return SimpleAveragePooling2dTestCommon<uint8_t>( |
| 7277 | workloadFactory, memoryManager, dataLayout, 0.5, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7278 | } |
| 7279 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7280 | LayerTestResult<float, 4> IgnorePaddingAveragePooling2dSize3x2Stride2x2Test( |
| 7281 | armnn::IWorkloadFactory& workloadFactory, |
| 7282 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7283 | bool forceNoPadding) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 7284 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7285 | return IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon<float>( |
| 7286 | workloadFactory, memoryManager, forceNoPadding); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 7287 | } |
| 7288 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7289 | LayerTestResult<float, 4> LargeTensorsAveragePooling2dTest( |
| 7290 | armnn::IWorkloadFactory& workloadFactory, |
| 7291 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7292 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7293 | return LargeTensorsAveragePooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7294 | } |
| 7295 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7296 | LayerTestResult<uint8_t, 4> LargeTensorsAveragePooling2dUint8Test( |
| 7297 | armnn::IWorkloadFactory& workloadFactory, |
| 7298 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7299 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7300 | return LargeTensorsAveragePooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, 0.5, -1); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7301 | } |
| 7302 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7303 | LayerTestResult<float, 4> SimpleL2Pooling2dTest( |
| 7304 | armnn::IWorkloadFactory& workloadFactory, |
| 7305 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 7306 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7307 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7308 | return SimpleL2Pooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7309 | } |
| 7310 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7311 | LayerTestResult<uint8_t, 4> SimpleL2Pooling2dUint8Test( |
| 7312 | armnn::IWorkloadFactory& workloadFactory, |
| 7313 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
Matthew Bentham | 8800c00 | 2018-11-19 13:19:28 +0000 | [diff] [blame] | 7314 | const armnn::DataLayout dataLayout) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7315 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7316 | return SimpleL2Pooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, dataLayout); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7317 | } |
| 7318 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7319 | LayerTestResult<float, 4> L2Pooling2dSize3Stride1Test( |
| 7320 | armnn::IWorkloadFactory& workloadFactory, |
| 7321 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7322 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7323 | return L2Pooling2dSize3Stride1TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7324 | } |
| 7325 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7326 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride1Uint8Test( |
| 7327 | armnn::IWorkloadFactory& workloadFactory, |
| 7328 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7329 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7330 | return L2Pooling2dSize3Stride1TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7331 | } |
| 7332 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7333 | LayerTestResult<float, 4> L2Pooling2dSize3Stride3Test( |
| 7334 | armnn::IWorkloadFactory& workloadFactory, |
| 7335 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7336 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7337 | return L2Pooling2dSize3Stride3TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7338 | } |
| 7339 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7340 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride3Uint8Test( |
| 7341 | armnn::IWorkloadFactory& workloadFactory, |
| 7342 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7343 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7344 | return L2Pooling2dSize3Stride3TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7345 | } |
| 7346 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7347 | LayerTestResult<float, 4> L2Pooling2dSize3Stride4Test( |
| 7348 | armnn::IWorkloadFactory& workloadFactory, |
| 7349 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7350 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7351 | return L2Pooling2dSize3Stride4TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7352 | } |
| 7353 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7354 | LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride4Uint8Test( |
| 7355 | armnn::IWorkloadFactory& workloadFactory, |
| 7356 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7357 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7358 | return L2Pooling2dSize3Stride4TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7359 | } |
| 7360 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7361 | LayerTestResult<float, 4> L2Pooling2dSize7Test( |
| 7362 | armnn::IWorkloadFactory& workloadFactory, |
| 7363 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7364 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7365 | return L2Pooling2dSize7TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7366 | } |
| 7367 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7368 | LayerTestResult<uint8_t, 4> L2Pooling2dSize7Uint8Test( |
| 7369 | armnn::IWorkloadFactory& workloadFactory, |
| 7370 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7371 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7372 | return L2Pooling2dSize7TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7373 | } |
| 7374 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7375 | LayerTestResult<float, 4> L2Pooling2dSize9Test( |
| 7376 | armnn::IWorkloadFactory& workloadFactory, |
| 7377 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7378 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7379 | return L2Pooling2dSize9TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7380 | } |
| 7381 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7382 | LayerTestResult<uint8_t, 4> L2Pooling2dSize9Uint8Test( |
| 7383 | armnn::IWorkloadFactory& workloadFactory, |
| 7384 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7385 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7386 | return L2Pooling2dSize9TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7387 | } |
| 7388 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7389 | LayerTestResult<float, 4> AsymmetricNonSquarePooling2dTest( |
| 7390 | armnn::IWorkloadFactory& workloadFactory, |
| 7391 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7392 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7393 | return AsymmetricNonSquarePooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7394 | } |
| 7395 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7396 | LayerTestResult<uint8_t, 4> AsymmetricNonSquarePooling2dUint8Test( |
| 7397 | armnn::IWorkloadFactory& workloadFactory, |
| 7398 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7399 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7400 | return AsymmetricNonSquarePooling2dTestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7401 | } |
| 7402 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7403 | LayerTestResult<float, 4> ComparePooling2dTest( |
| 7404 | armnn::IWorkloadFactory& workloadFactory, |
| 7405 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7406 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 7407 | armnn::PoolingAlgorithm poolingType) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7408 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7409 | return ComparePooling2dTestCommon<float>( |
| 7410 | workloadFactory, memoryManager, refWorkloadFactory, poolingType); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7411 | } |
| 7412 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7413 | LayerTestResult<uint8_t, 4> ComparePooling2dUint8Test( |
| 7414 | armnn::IWorkloadFactory& workloadFactory, |
| 7415 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7416 | armnn::IWorkloadFactory& refWorkloadFactory, |
| 7417 | armnn::PoolingAlgorithm poolingType) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7418 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7419 | return ComparePooling2dTestCommon<uint8_t>( |
| 7420 | workloadFactory, memoryManager, refWorkloadFactory, poolingType, 0.1f, 128); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7421 | } |
| 7422 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7423 | LayerTestResult<float, 2> FullyConnectedLargeTest( |
| 7424 | armnn::IWorkloadFactory& workloadFactory, |
| 7425 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7426 | bool transposeWeights) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7427 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7428 | return FullyConnectedLargeTestCommon<float>(workloadFactory, memoryManager, transposeWeights); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7429 | } |
| 7430 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7431 | LayerTestResult<float, 4> IgnorePaddingSimpleMaxPooling2dTest( |
| 7432 | armnn::IWorkloadFactory& workloadFactory, |
| 7433 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7434 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7435 | return IgnorePaddingSimpleMaxPooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7436 | } |
| 7437 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7438 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleMaxPooling2dUint8Test( |
| 7439 | armnn::IWorkloadFactory& workloadFactory, |
| 7440 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7441 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7442 | return IgnorePaddingSimpleMaxPooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, -5); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7443 | } |
| 7444 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7445 | LayerTestResult<float, 4> IgnorePaddingMaxPooling2dSize3Test( |
| 7446 | armnn::IWorkloadFactory& workloadFactory, |
| 7447 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7448 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7449 | return IgnorePaddingMaxPooling2dSize3TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7450 | } |
| 7451 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7452 | LayerTestResult<uint8_t, 4> IgnorePaddingMaxPooling2dSize3Uint8Test( |
| 7453 | armnn::IWorkloadFactory& workloadFactory, |
| 7454 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7455 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7456 | return IgnorePaddingMaxPooling2dSize3TestCommon<uint8_t>(workloadFactory, memoryManager, 1.0f, -5); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7457 | } |
| 7458 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7459 | LayerTestResult<float, 4> IgnorePaddingSimpleAveragePooling2dTest( |
| 7460 | armnn::IWorkloadFactory& workloadFactory, |
| 7461 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7462 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7463 | return IgnorePaddingSimpleAveragePooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7464 | } |
| 7465 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7466 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleAveragePooling2dUint8Test( |
| 7467 | armnn::IWorkloadFactory& workloadFactory, |
| 7468 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7469 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7470 | return IgnorePaddingSimpleAveragePooling2dTestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7471 | } |
| 7472 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7473 | LayerTestResult<float, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingTest( |
| 7474 | armnn::IWorkloadFactory& workloadFactory, |
| 7475 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7476 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7477 | return IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7478 | } |
| 7479 | |
| 7480 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test( |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7481 | armnn::IWorkloadFactory& workloadFactory, |
| 7482 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7483 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7484 | return IgnorePaddingSimpleAveragePooling2dNoPaddingTestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7485 | } |
| 7486 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7487 | LayerTestResult<float, 4> IgnorePaddingAveragePooling2dSize3Test( |
| 7488 | armnn::IWorkloadFactory& workloadFactory, |
| 7489 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7490 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7491 | return IgnorePaddingAveragePooling2dSize3TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7492 | } |
| 7493 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7494 | LayerTestResult<uint8_t, 4> IgnorePaddingAveragePooling2dSize3Uint8Test( |
| 7495 | armnn::IWorkloadFactory& workloadFactory, |
| 7496 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7497 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7498 | return IgnorePaddingAveragePooling2dSize3TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7499 | } |
| 7500 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7501 | LayerTestResult<float, 4> IgnorePaddingSimpleL2Pooling2dTest( |
| 7502 | armnn::IWorkloadFactory& workloadFactory, |
| 7503 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7504 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7505 | return IgnorePaddingSimpleL2Pooling2dTestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7506 | } |
| 7507 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7508 | LayerTestResult<uint8_t, 4> IgnorePaddingSimpleL2Pooling2dUint8Test( |
| 7509 | armnn::IWorkloadFactory& workloadFactory, |
| 7510 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7511 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7512 | return IgnorePaddingSimpleL2Pooling2dTestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7513 | } |
| 7514 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7515 | LayerTestResult<float, 4> IgnorePaddingL2Pooling2dSize3Test( |
| 7516 | armnn::IWorkloadFactory& workloadFactory, |
| 7517 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7518 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7519 | return IgnorePaddingL2Pooling2dSize3TestCommon<float>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7520 | } |
| 7521 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7522 | LayerTestResult<uint8_t, 4> IgnorePaddingL2Pooling2dSize3Uint8Test( |
| 7523 | armnn::IWorkloadFactory& workloadFactory, |
| 7524 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7525 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7526 | return IgnorePaddingL2Pooling2dSize3TestCommon<uint8_t>(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7527 | } |
| 7528 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7529 | LayerTestResult<float, 4> SimplePermuteFloat32Test( |
| 7530 | armnn::IWorkloadFactory& workloadFactory, |
| 7531 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7532 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7533 | return SimplePermuteFloat32TestCommon(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7534 | }; |
| 7535 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7536 | LayerTestResult<uint8_t, 4> SimplePermuteUint8Test( |
| 7537 | armnn::IWorkloadFactory& workloadFactory, |
| 7538 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7539 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7540 | return SimplePermuteUint8TestCommon(workloadFactory, memoryManager); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 7541 | }; |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 7542 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7543 | LayerTestResult<float, 4> PermuteFloat32ValueSet1Test( |
| 7544 | armnn::IWorkloadFactory& workloadFactory, |
| 7545 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 7546 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7547 | return PermuteFloat32ValueSet1TestCommon(workloadFactory, memoryManager); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 7548 | }; |
| 7549 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7550 | LayerTestResult<float, 4> PermuteFloat32ValueSet2Test( |
| 7551 | armnn::IWorkloadFactory& workloadFactory, |
| 7552 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 7553 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7554 | return PermuteFloat32ValueSet2TestCommon(workloadFactory, memoryManager); |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 7555 | }; |
| 7556 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7557 | LayerTestResult<float, 4> PermuteFloat32ValueSet3Test( |
| 7558 | armnn::IWorkloadFactory& workloadFactory, |
| 7559 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 7560 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7561 | return PermuteFloat32ValueSet3TestCommon(workloadFactory, memoryManager); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7562 | }; |
| 7563 | |
| 7564 | namespace |
| 7565 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7566 | |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7567 | template <typename T, std::size_t InputDim, std::size_t OutputDim> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7568 | LayerTestResult<T, OutputDim> MeanTestHelper( |
| 7569 | armnn::IWorkloadFactory& workloadFactory, |
| 7570 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 7571 | const unsigned int* inputShape, |
| 7572 | const std::vector<T>& inputData, |
| 7573 | const std::vector<unsigned int>& axis, |
| 7574 | bool keepDims, |
| 7575 | const unsigned int* outputShape, |
| 7576 | const std::vector<T>& outputData, |
| 7577 | float scale = 1.0f, |
| 7578 | int32_t offset = 0) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7579 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7580 | 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] | 7581 | |
| 7582 | armnn::TensorInfo inputTensorInfo(InputDim, inputShape, dataType); |
| 7583 | armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, dataType); |
| 7584 | |
| 7585 | inputTensorInfo.SetQuantizationScale(scale); |
| 7586 | inputTensorInfo.SetQuantizationOffset(offset); |
| 7587 | |
| 7588 | outputTensorInfo.SetQuantizationScale(scale); |
| 7589 | outputTensorInfo.SetQuantizationOffset(offset); |
| 7590 | |
| 7591 | auto input = MakeTensor<T, InputDim>(inputTensorInfo, inputData); |
| 7592 | |
| 7593 | LayerTestResult<T, OutputDim> result(outputTensorInfo); |
| 7594 | result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo, outputData); |
| 7595 | |
| 7596 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 7597 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 7598 | |
| 7599 | armnn::MeanQueueDescriptor data; |
| 7600 | data.m_Parameters.m_Axis = axis; |
| 7601 | data.m_Parameters.m_KeepDims = keepDims; |
| 7602 | armnn::WorkloadInfo info; |
| 7603 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 7604 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 7605 | |
| 7606 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMean(data, info); |
| 7607 | |
| 7608 | inputHandle->Allocate(); |
| 7609 | outputHandle->Allocate(); |
| 7610 | |
| 7611 | CopyDataToITensorHandle(inputHandle.get(), input.origin()); |
| 7612 | |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7613 | workload->Execute(); |
| 7614 | |
| 7615 | CopyDataFromITensorHandle(result.output.origin(), outputHandle.get()); |
| 7616 | |
| 7617 | return result; |
| 7618 | } |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7619 | |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7620 | } // anonymous namespace |
| 7621 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7622 | LayerTestResult<uint8_t, 1> MeanUint8SimpleTest( |
| 7623 | armnn::IWorkloadFactory& workloadFactory, |
| 7624 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7625 | { |
| 7626 | const unsigned int inputShape[] = { 3, 2 }; |
| 7627 | const unsigned int outputShape[] = { 1 }; |
| 7628 | |
| 7629 | std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); |
| 7630 | std::vector<uint8_t> output({ 2 }); |
| 7631 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7632 | return MeanTestHelper<uint8_t, 2, 1>( |
| 7633 | workloadFactory, memoryManager, inputShape, input, {}, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7634 | } |
| 7635 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7636 | LayerTestResult<uint8_t, 3> MeanUint8SimpleAxisTest( |
| 7637 | armnn::IWorkloadFactory& workloadFactory, |
| 7638 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7639 | { |
| 7640 | const unsigned int inputShape[] = { 1, 1, 3, 2 }; |
| 7641 | const unsigned int outputShape[] = { 1, 1, 2 }; |
| 7642 | |
| 7643 | std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); |
| 7644 | std::vector<uint8_t> output({ 2, 2 }); |
| 7645 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7646 | return MeanTestHelper<uint8_t, 4, 3>( |
| 7647 | workloadFactory, memoryManager, inputShape, input, { 2 }, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7648 | } |
| 7649 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7650 | LayerTestResult<uint8_t, 4> MeanUint8KeepDimsTest( |
| 7651 | armnn::IWorkloadFactory& workloadFactory, |
| 7652 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7653 | { |
| 7654 | const unsigned int inputShape[] = { 1, 1, 3, 2 }; |
| 7655 | const unsigned int outputShape[] = { 1, 1, 1, 2 }; |
| 7656 | |
| 7657 | std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); |
| 7658 | std::vector<uint8_t> output({ 2, 2 }); |
| 7659 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7660 | return MeanTestHelper<uint8_t, 4, 4>( |
| 7661 | workloadFactory, memoryManager, inputShape, input, { 2 }, true, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7662 | } |
| 7663 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7664 | LayerTestResult<uint8_t, 4> MeanUint8MultipleDimsTest( |
| 7665 | armnn::IWorkloadFactory& workloadFactory, |
| 7666 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7667 | { |
| 7668 | const unsigned int inputShape[] = { 2, 3, 1, 2 }; |
| 7669 | const unsigned int outputShape[] = { 1, 3, 1, 1 }; |
| 7670 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7671 | 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] | 7672 | std::vector<uint8_t> output({ 1, 3, 5 }); |
| 7673 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7674 | return MeanTestHelper<uint8_t, 4, 4>( |
| 7675 | workloadFactory, memoryManager, inputShape, input, { 0, 3 }, true, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7676 | } |
| 7677 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7678 | LayerTestResult<uint8_t, 1> MeanVtsUint8Test( |
| 7679 | armnn::IWorkloadFactory& workloadFactory, |
| 7680 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7681 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7682 | const unsigned int inputShape[] = { 4, 3, 2 }; |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7683 | const unsigned int outputShape[] = { 2 }; |
| 7684 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7685 | 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, |
| 7686 | 24 }); |
| 7687 | std::vector<uint8_t> output({ 12, 13 }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7688 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7689 | return MeanTestHelper<uint8_t, 3, 1>(workloadFactory, memoryManager, |
| 7690 | inputShape, input, { 0, 1 }, false, outputShape, |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7691 | output, 0.8f, 5); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7692 | } |
| 7693 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7694 | LayerTestResult<float, 1> MeanFloatSimpleTest( |
| 7695 | armnn::IWorkloadFactory& workloadFactory, |
| 7696 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7697 | { |
| 7698 | const unsigned int inputShape[] = { 3, 2 }; |
| 7699 | const unsigned int outputShape[] = { 1 }; |
| 7700 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7701 | std::vector<float> input({ 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f }); |
| 7702 | std::vector<float> output({ 2.0f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7703 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7704 | return MeanTestHelper<float, 2, 1>( |
| 7705 | workloadFactory, memoryManager, inputShape, input, {}, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7706 | } |
| 7707 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7708 | LayerTestResult<float, 3> MeanFloatSimpleAxisTest( |
| 7709 | armnn::IWorkloadFactory& workloadFactory, |
| 7710 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7711 | { |
| 7712 | const unsigned int inputShape[] = { 2, 3, 1, 2 }; |
| 7713 | const unsigned int outputShape[] = { 3, 1, 2 }; |
| 7714 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7715 | 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 }); |
| 7716 | 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] | 7717 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7718 | return MeanTestHelper<float, 4, 3>( |
| 7719 | workloadFactory, memoryManager, inputShape, input, { 0 }, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7720 | } |
| 7721 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7722 | LayerTestResult<float, 4> MeanFloatKeepDimsTest( |
| 7723 | armnn::IWorkloadFactory& workloadFactory, |
| 7724 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7725 | { |
| 7726 | const unsigned int inputShape[] = { 1, 1, 3, 2 }; |
| 7727 | const unsigned int outputShape[] = { 1, 1, 1, 2 }; |
| 7728 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7729 | std::vector<float> input({ 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f }); |
| 7730 | std::vector<float> output({ 2.0f, 2.0f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7731 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7732 | return MeanTestHelper<float, 4, 4>( |
| 7733 | workloadFactory, memoryManager, inputShape, input, { 2 }, true, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7734 | } |
| 7735 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7736 | LayerTestResult<float, 4> MeanFloatMultipleDimsTest( |
| 7737 | armnn::IWorkloadFactory& workloadFactory, |
| 7738 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7739 | { |
| 7740 | const unsigned int inputShape[] = { 2, 3, 1, 2 }; |
| 7741 | const unsigned int outputShape[] = { 1, 3, 1, 1 }; |
| 7742 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7743 | 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 }); |
| 7744 | std::vector<float> output({ 1.5f, 3.5f, 5.5f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7745 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7746 | return MeanTestHelper<float, 4, 4>( |
| 7747 | workloadFactory, memoryManager, inputShape, input, { 0, 3 }, true, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7748 | } |
| 7749 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7750 | LayerTestResult<float, 1> MeanVtsFloat1Test( |
| 7751 | armnn::IWorkloadFactory& workloadFactory, |
| 7752 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7753 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7754 | const unsigned int inputShape[] = { 4, 3, 2 }; |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7755 | const unsigned int outputShape[] = { 2 }; |
| 7756 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7757 | 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, |
| 7758 | 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f }); |
| 7759 | std::vector<float> output({ 12.0f, 13.0f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7760 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7761 | return MeanTestHelper<float, 3, 1>( |
| 7762 | workloadFactory, memoryManager, inputShape, input, { 0, 1 }, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7763 | } |
| 7764 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7765 | LayerTestResult<float, 3> MeanVtsFloat2Test( |
| 7766 | armnn::IWorkloadFactory& workloadFactory, |
| 7767 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7768 | { |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7769 | const unsigned int inputShape[] = { 4, 3, 2 }; |
| 7770 | const unsigned int outputShape[] = { 1, 3, 1 }; |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7771 | |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7772 | 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, |
| 7773 | 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f }); |
| 7774 | std::vector<float> output({ 10.5f, 12.5f, 14.5f }); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7775 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7776 | return MeanTestHelper<float, 3, 3>( |
| 7777 | workloadFactory, memoryManager, inputShape, input, { 0, 2 }, true, outputShape, output); |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7778 | } |
| 7779 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7780 | LayerTestResult<float, 3> MeanVtsFloat3Test( |
| 7781 | armnn::IWorkloadFactory& workloadFactory, |
| 7782 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Matteo Martincigh | 28dcab6 | 2018-10-19 16:40:03 +0100 | [diff] [blame] | 7783 | { |
| 7784 | const unsigned int inputShape[] = { 1, 2, 2, 1 }; |
| 7785 | const unsigned int outputShape[] = { 1, 2, 1 }; |
| 7786 | |
| 7787 | std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f }); |
| 7788 | std::vector<float> output({ 1.5f, 3.5f }); |
| 7789 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7790 | return MeanTestHelper<float, 4, 3>( |
| 7791 | workloadFactory, memoryManager, inputShape, input, { 2 }, false, outputShape, output); |
narpra01 | 1e4c31d | 2018-09-28 11:07:51 +0100 | [diff] [blame] | 7792 | } |
Éanna Ó Catháin | 47c1ddb | 2018-10-12 14:24:13 +0100 | [diff] [blame] | 7793 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7794 | LayerTestResult<float, 4> AdditionAfterMaxPoolTest( |
| 7795 | armnn::IWorkloadFactory& workloadFactory, |
| 7796 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 47c1ddb | 2018-10-12 14:24:13 +0100 | [diff] [blame] | 7797 | { |
| 7798 | // Create Initial Tensor |
| 7799 | // 1, 2, 3 |
| 7800 | // 4, 5, 6 |
| 7801 | // 7, 8, 9 |
| 7802 | |
| 7803 | armnn::TensorInfo poolingInputTensorInfo({ 1, 1, 3, 3}, armnn::GetDataType<float>()); |
| 7804 | armnn::TensorInfo poolingOutputTensorInfo({ 1, 1, 2, 2}, armnn::GetDataType<float>()); |
| 7805 | |
| 7806 | boost::multi_array<float, 4> poolingInput = MakeTensor<float,4>(poolingInputTensorInfo, |
| 7807 | {1, 2, 3, |
| 7808 | 4, 5, 6, |
| 7809 | 7, 8, 9 |
| 7810 | }); |
| 7811 | |
| 7812 | std::unique_ptr<armnn::ITensorHandle> poolingInputHandle = |
| 7813 | workloadFactory.CreateTensorHandle(poolingInputTensorInfo); |
| 7814 | std::unique_ptr<armnn::ITensorHandle> poolingOutputHandle = |
| 7815 | workloadFactory.CreateTensorHandle(poolingOutputTensorInfo); |
| 7816 | |
| 7817 | // Apply MaxPool poolSize = 1x1, stride=2x2 |
| 7818 | // Result = |
| 7819 | // 1, 3 |
| 7820 | // 7, 9 |
| 7821 | armnn::Pooling2dDescriptor descriptor; |
| 7822 | descriptor.m_PoolHeight = 1; |
| 7823 | descriptor.m_PoolWidth = 1; |
| 7824 | descriptor.m_StrideX = 2; |
| 7825 | descriptor.m_StrideY = 2; |
| 7826 | descriptor.m_PoolType = armnn::PoolingAlgorithm::Max; |
| 7827 | |
| 7828 | armnn::Pooling2dQueueDescriptor queueDescriptor; |
| 7829 | queueDescriptor.m_Parameters = descriptor; |
| 7830 | armnn::WorkloadInfo workloadInfo; |
| 7831 | AddInputToWorkload(queueDescriptor, workloadInfo, poolingInputTensorInfo, poolingInputHandle.get()); |
| 7832 | AddOutputToWorkload(queueDescriptor, workloadInfo, poolingOutputTensorInfo, poolingOutputHandle.get()); |
| 7833 | |
| 7834 | // Create the MaxPool |
| 7835 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePooling2d(queueDescriptor, workloadInfo); |
| 7836 | |
| 7837 | //LayerTestResult<float, 4> result(poolingOutputTensorInfo); |
| 7838 | auto shape( GetTensorShapeAsArray<4>(poolingOutputTensorInfo)); |
| 7839 | boost::multi_array<float, 4> resultMaxPool; |
| 7840 | resultMaxPool.resize(shape); |
| 7841 | |
| 7842 | |
| 7843 | // Create addition with another tensor the same size |
| 7844 | // This would be the result to apply a Conv2d with kernel ones(2) and stride 1x1 |
| 7845 | // with the initial tensor. |
| 7846 | // 12, 16 |
| 7847 | // 24, 28 |
| 7848 | |
| 7849 | armnn::TensorInfo addInputTensorInfo({ 1,1,2,2}, armnn::GetDataType<float>()); |
| 7850 | armnn::TensorInfo addOutputTensorInfo({ 1,1,2,2}, armnn::GetDataType<float>()); |
| 7851 | |
| 7852 | boost::multi_array<float, 4> addInput = MakeTensor<float,4>(addInputTensorInfo, |
| 7853 | {12, 16, |
| 7854 | 24, 28, |
| 7855 | }); |
| 7856 | |
| 7857 | // Expected output tensor after MaxPool and Addition. |
| 7858 | LayerTestResult<float,4> addRet(addOutputTensorInfo); |
| 7859 | addRet.outputExpected = MakeTensor<float, 4>(addOutputTensorInfo, std::vector<float>( |
| 7860 | { |
| 7861 | 13, 19, |
| 7862 | 31, 37 |
| 7863 | })); |
| 7864 | |
| 7865 | std::unique_ptr<armnn::ITensorHandle> addInputHandle = workloadFactory.CreateTensorHandle(addInputTensorInfo); |
| 7866 | std::unique_ptr<armnn::ITensorHandle> addOutputHandle = workloadFactory.CreateTensorHandle(addOutputTensorInfo); |
| 7867 | |
| 7868 | armnn::AdditionQueueDescriptor data; |
| 7869 | armnn::WorkloadInfo info; |
| 7870 | |
| 7871 | // Add the output of the MaxPool and the new tensor |
| 7872 | AddInputToWorkload(data, info, poolingOutputTensorInfo, poolingOutputHandle.get()); |
| 7873 | AddInputToWorkload(data, info, addInputTensorInfo, addInputHandle.get()); |
| 7874 | AddOutputToWorkload(data, info, addOutputTensorInfo, addOutputHandle.get()); |
| 7875 | |
| 7876 | std::unique_ptr<armnn::IWorkload> addWorkload = workloadFactory.CreateAddition(data, info); |
| 7877 | |
| 7878 | poolingInputHandle->Allocate(); |
| 7879 | poolingOutputHandle->Allocate(); |
| 7880 | addInputHandle->Allocate(); |
| 7881 | addOutputHandle->Allocate(); |
| 7882 | |
| 7883 | CopyDataToITensorHandle(poolingInputHandle.get(), &poolingInput[0][0][0][0]); |
| 7884 | CopyDataFromITensorHandle(&resultMaxPool[0][0][0][0], poolingOutputHandle.get()); |
| 7885 | |
| 7886 | CopyDataToITensorHandle(poolingOutputHandle.get(), &resultMaxPool[0][0][0][0]); |
| 7887 | CopyDataToITensorHandle(addInputHandle.get(), &addInput[0][0][0][0]); |
| 7888 | |
| 7889 | workload->Execute(); |
| 7890 | addWorkload->Execute(); |
| 7891 | |
| 7892 | CopyDataFromITensorHandle(&addRet.output[0][0][0][0], addOutputHandle.get()); |
| 7893 | |
Éanna Ó Catháin | 47c1ddb | 2018-10-12 14:24:13 +0100 | [diff] [blame] | 7894 | return addRet; |
| 7895 | } |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7896 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7897 | LayerTestResult<float, 4> SpaceToBatchNdSimpleFloat32Test( |
| 7898 | armnn::IWorkloadFactory& workloadFactory, |
| 7899 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7900 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7901 | return SpaceToBatchNdSimpleTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7902 | } |
| 7903 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7904 | LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsFloat32Test( |
| 7905 | armnn::IWorkloadFactory& workloadFactory, |
| 7906 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7907 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7908 | return SpaceToBatchNdMultiChannelsTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7909 | } |
| 7910 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7911 | LayerTestResult<float, 4> SpaceToBatchNdMultiBlockFloat32Test( |
| 7912 | armnn::IWorkloadFactory& workloadFactory, |
| 7913 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7914 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7915 | return SpaceToBatchNdMultiBlockTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7916 | } |
| 7917 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7918 | LayerTestResult<float, 4> SpaceToBatchNdPaddingFloat32Test( |
| 7919 | armnn::IWorkloadFactory& workloadFactory, |
| 7920 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7921 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7922 | return SpaceToBatchNdPaddingTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7923 | } |
| 7924 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7925 | LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleUint8Test( |
| 7926 | armnn::IWorkloadFactory& workloadFactory, |
| 7927 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7928 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7929 | return SpaceToBatchNdSimpleTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7930 | } |
| 7931 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7932 | LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsUint8Test( |
| 7933 | armnn::IWorkloadFactory& workloadFactory, |
| 7934 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7935 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7936 | return SpaceToBatchNdMultiChannelsTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7937 | } |
| 7938 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7939 | LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockUint8Test( |
| 7940 | armnn::IWorkloadFactory& workloadFactory, |
| 7941 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7942 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7943 | return SpaceToBatchNdMultiBlockTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7944 | } |
| 7945 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7946 | LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingUint8Test( |
| 7947 | armnn::IWorkloadFactory& workloadFactory, |
| 7948 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7949 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7950 | return SpaceToBatchNdPaddingTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7951 | } |
| 7952 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7953 | LayerTestResult<float, 4> SpaceToBatchNdSimpleNHWCFloat32Test( |
| 7954 | armnn::IWorkloadFactory& workloadFactory, |
| 7955 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7956 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7957 | return SpaceToBatchNdSimpleNHWCTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7958 | } |
| 7959 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7960 | LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsNHWCFloat32Test( |
| 7961 | armnn::IWorkloadFactory& workloadFactory, |
| 7962 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7963 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7964 | return SpaceToBatchNdMultiChannelsNHWCTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7965 | } |
| 7966 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7967 | LayerTestResult<float, 4> SpaceToBatchNdMultiBlockNHWCFloat32Test( |
| 7968 | armnn::IWorkloadFactory& workloadFactory, |
| 7969 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7970 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7971 | return SpaceToBatchNdMultiBlockNHWCTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7972 | } |
| 7973 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7974 | LayerTestResult<float, 4> SpaceToBatchNdPaddingNHWCFloat32Test( |
| 7975 | armnn::IWorkloadFactory& workloadFactory, |
| 7976 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7977 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7978 | return SpaceToBatchNdPaddingNHWCTest<float>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7979 | } |
| 7980 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7981 | LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleNHWCUint8Test( |
| 7982 | armnn::IWorkloadFactory& workloadFactory, |
| 7983 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7984 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7985 | return SpaceToBatchNdSimpleNHWCTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7986 | } |
| 7987 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7988 | LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsNHWCUint8Test( |
| 7989 | armnn::IWorkloadFactory& workloadFactory, |
| 7990 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7991 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7992 | return SpaceToBatchNdMultiChannelsNHWCTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7993 | } |
| 7994 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7995 | LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockNHWCUint8Test( |
| 7996 | armnn::IWorkloadFactory& workloadFactory, |
| 7997 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 7998 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 7999 | return SpaceToBatchNdMultiBlockNHWCTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 8000 | } |
| 8001 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8002 | LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingNHWCUint8Test( |
| 8003 | armnn::IWorkloadFactory& workloadFactory, |
| 8004 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 8005 | { |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8006 | return SpaceToBatchNdPaddingNHWCTest<uint8_t>(workloadFactory, memoryManager); |
Nattapat Chaimanowong | 3ea76d5 | 2018-11-09 14:10:38 +0000 | [diff] [blame] | 8007 | } |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8008 | |
| 8009 | namespace { |
| 8010 | |
| 8011 | template<typename T, std::size_t InputDim, std::size_t OutputDim> |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8012 | LayerTestResult<T, OutputDim> BatchToSpaceNdHelper( |
| 8013 | armnn::IWorkloadFactory &workloadFactory, |
| 8014 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| 8015 | const armnn::DataLayout& dataLayout, |
| 8016 | const unsigned int *inputShape, |
| 8017 | const std::vector<T> &inputData, |
| 8018 | const std::vector<unsigned int> &blockShape, |
| 8019 | const std::vector<std::pair<unsigned int, unsigned int>> &crops, |
| 8020 | const unsigned int *outputShape, |
| 8021 | const std::vector<T> &outputData, |
| 8022 | float scale = 1.0f, |
| 8023 | int32_t offset = 0) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8024 | { |
| 8025 | auto dataType = (std::is_same<T, uint8_t>::value ? armnn::DataType::QuantisedAsymm8 : armnn::DataType::Float32); |
| 8026 | |
| 8027 | armnn::TensorInfo inputTensorInfo(InputDim, inputShape, dataType); |
| 8028 | armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, dataType); |
| 8029 | |
| 8030 | inputTensorInfo.SetQuantizationScale(scale); |
| 8031 | inputTensorInfo.SetQuantizationOffset(offset); |
| 8032 | |
| 8033 | outputTensorInfo.SetQuantizationScale(scale); |
| 8034 | outputTensorInfo.SetQuantizationOffset(offset); |
| 8035 | |
| 8036 | auto input = MakeTensor<T, InputDim>(inputTensorInfo, inputData); |
| 8037 | |
| 8038 | LayerTestResult<T, OutputDim> result(outputTensorInfo); |
| 8039 | result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo, outputData); |
| 8040 | |
| 8041 | std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| 8042 | std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| 8043 | |
| 8044 | armnn::BatchToSpaceNdQueueDescriptor data; |
| 8045 | data.m_Parameters.m_DataLayout = dataLayout; |
| 8046 | data.m_Parameters.m_BlockShape = blockShape; |
| 8047 | data.m_Parameters.m_Crops = crops; |
| 8048 | armnn::WorkloadInfo info; |
| 8049 | AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| 8050 | AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| 8051 | |
| 8052 | std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchToSpaceNd(data, info); |
| 8053 | |
| 8054 | inputHandle->Allocate(); |
| 8055 | outputHandle->Allocate(); |
| 8056 | |
| 8057 | CopyDataToITensorHandle(inputHandle.get(), input.origin()); |
| 8058 | |
| 8059 | workload->Execute(); |
| 8060 | |
| 8061 | CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); |
| 8062 | |
| 8063 | return result; |
| 8064 | } |
| 8065 | |
| 8066 | } // anonymous namespace |
| 8067 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8068 | LayerTestResult<float, 4> BatchToSpaceNdNhwcFloat32Test1( |
| 8069 | armnn::IWorkloadFactory& workloadFactory, |
| 8070 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8071 | { |
| 8072 | const unsigned int inputShape[] = {4, 2, 2, 1}; |
| 8073 | const unsigned int outputShape[] = {1, 4, 4, 1 }; |
| 8074 | |
| 8075 | std::vector<float> input |
| 8076 | ({ |
| 8077 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 8078 | 1.0f, 3.0f, |
| 8079 | // Batch 0, Height 1, Width (2) x Channel (1) |
| 8080 | 9.0f, 11.0f, |
| 8081 | |
| 8082 | |
| 8083 | // Batch 1, Height 0, Width (2) x Channel (1) |
| 8084 | 2.0f, 4.0f, |
| 8085 | // Batch 1, Height 1, Width (2) x Channel (1) |
| 8086 | 10.0f, 12.0f, |
| 8087 | |
| 8088 | |
| 8089 | // Batch 2, Height 0, Width (2) x Channel (1) |
| 8090 | 5.0f, 7.0f, |
| 8091 | // Batch 2, Height 1, Width (2) x Channel (1) |
| 8092 | 13.0f, 15.0f, |
| 8093 | |
| 8094 | // Batch 3, Height 0, Width (2) x Channel (3) |
| 8095 | 6.0f, 8.0f, |
| 8096 | // Batch 3, Height 1, Width (2) x Channel (1) |
| 8097 | 14.0f, 16.0f |
| 8098 | }); |
| 8099 | |
| 8100 | std::vector<float> expectedOutput |
| 8101 | ({ |
| 8102 | 1.0f, 2.0f, 3.0f, 4.0f, |
| 8103 | 5.0f, 6.0f, 7.0f, 8.0f, |
| 8104 | 9.0f, 10.0f, 11.0f, 12.0f, |
| 8105 | 13.0f, 14.0f, 15.0f, 16.0f |
| 8106 | }); |
| 8107 | |
| 8108 | std::vector<unsigned int> blockShape {2, 2}; |
Éanna Ó Catháin | 95807ce | 2018-11-12 17:14:43 +0000 | [diff] [blame] | 8109 | 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] | 8110 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8111 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 8112 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8113 | crops, outputShape, expectedOutput); |
| 8114 | } |
| 8115 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8116 | LayerTestResult<float, 4> BatchToSpaceNdNhwcFloat32Test2( |
| 8117 | armnn::IWorkloadFactory& workloadFactory, |
| 8118 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8119 | { |
| 8120 | const unsigned int inputShape[] = {4, 1, 1, 1}; |
| 8121 | const unsigned int outputShape[] = {1, 2, 2, 1}; |
| 8122 | |
| 8123 | std::vector<float> input |
| 8124 | ({ |
| 8125 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 8126 | 1.0f, 2.0f, 3.0f, 4.0f |
| 8127 | }); |
| 8128 | |
| 8129 | std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f}); |
| 8130 | |
| 8131 | std::vector<unsigned int> blockShape({2, 2}); |
Éanna Ó Catháin | 95807ce | 2018-11-12 17:14:43 +0000 | [diff] [blame] | 8132 | 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] | 8133 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8134 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 8135 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| 8136 | crops, outputShape, expectedOutput); |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8137 | } |
| 8138 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8139 | LayerTestResult<float, 4> BatchToSpaceNdNhwcFloat32Test3( |
| 8140 | armnn::IWorkloadFactory& workloadFactory, |
| 8141 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8142 | { |
| 8143 | const unsigned int inputShape[] = {4, 1, 1, 3}; |
| 8144 | const unsigned int outputShape[] = {1, 2, 2, 3}; |
| 8145 | |
| 8146 | 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 }); |
| 8147 | |
| 8148 | 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 }); |
| 8149 | |
| 8150 | std::vector<unsigned int> blockShape({2, 2}); |
Éanna Ó Catháin | 95807ce | 2018-11-12 17:14:43 +0000 | [diff] [blame] | 8151 | 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] | 8152 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8153 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 8154 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| 8155 | crops, outputShape, expectedOutput); |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8156 | } |
| 8157 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8158 | LayerTestResult<float, 4> BatchToSpaceNdNchwFloat32Test1( |
| 8159 | armnn::IWorkloadFactory &workloadFactory, |
| 8160 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8161 | { |
| 8162 | const unsigned int inputShape[] = {4, 3, 1, 1}; |
| 8163 | const unsigned int outputShape[] = {1, 3, 2, 2}; |
| 8164 | |
| 8165 | 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 }); |
| 8166 | |
| 8167 | std::vector<float> expectedOutput |
| 8168 | ({ |
| 8169 | // Batch 0, Channel 0, Height (2) x Width (2) |
| 8170 | 1.0f, 4.0f, |
| 8171 | 7.0f, 10.0f, |
| 8172 | |
| 8173 | // Batch 0, Channel 1, Height (2) x Width (2) |
| 8174 | 2.0f, 5.0f, |
| 8175 | 8.0f, 11.0f, |
| 8176 | |
| 8177 | // Batch 0, Channel 2, Height (2) x Width (2) |
| 8178 | 3.0f, 6.0f, |
| 8179 | 9.0f, 12.0f, |
| 8180 | }); |
| 8181 | |
| 8182 | std::vector<unsigned int> blockShape({2, 2}); |
Éanna Ó Catháin | 95807ce | 2018-11-12 17:14:43 +0000 | [diff] [blame] | 8183 | 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] | 8184 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8185 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 8186 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 8187 | crops, outputShape, expectedOutput); |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 8188 | } |
Éanna Ó Catháin | 262553e | 2018-11-14 11:26:23 +0000 | [diff] [blame] | 8189 | |
Mike Kelly | 831faed | 2018-11-28 11:52:08 +0000 | [diff] [blame] | 8190 | LayerTestResult<float, 4> BatchToSpaceNdNchwFloat32Test2( |
| 8191 | armnn::IWorkloadFactory& workloadFactory, |
| 8192 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8193 | { |
| 8194 | const unsigned int inputShape[] = {4, 1, 1, 1}; |
| 8195 | const unsigned int outputShape[] = {1, 1, 2, 2}; |
| 8196 | |
| 8197 | std::vector<float> input |
| 8198 | ({ |
| 8199 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 8200 | 1.0f, 2.0f, 3.0f, 4.0f |
| 8201 | }); |
| 8202 | |
| 8203 | std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f}); |
| 8204 | |
| 8205 | std::vector<unsigned int> blockShape({2, 2}); |
| 8206 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 8207 | |
| 8208 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 8209 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 8210 | crops, outputShape, expectedOutput); |
| 8211 | } |
| 8212 | |
| 8213 | LayerTestResult<float, 4> BatchToSpaceNdNchwFloat32Test3( |
| 8214 | armnn::IWorkloadFactory& workloadFactory, |
| 8215 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8216 | { |
| 8217 | const unsigned int inputShape[] = {4, 3, 1, 1}; |
| 8218 | const unsigned int outputShape[] = {1, 3, 2, 2}; |
| 8219 | |
| 8220 | 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 }); |
| 8221 | |
| 8222 | std::vector<float> expectedOutput |
| 8223 | ({ |
| 8224 | // Batch 0, Channel 0, Height (2) x Width (2) |
| 8225 | 1.0f, 7.0f, |
| 8226 | 2.0f, 8.0f, |
| 8227 | |
| 8228 | // Batch 0, Channel 1, Height (2) x Width (2) |
| 8229 | 3.0f, 9.0f, |
| 8230 | 4.0f, 10.0f, |
| 8231 | |
| 8232 | // Batch 0, Channel 2, Height (2) x Width (2) |
| 8233 | 5.0f, 11.0f, |
| 8234 | 6.0f, 12.0f, |
| 8235 | }); |
| 8236 | |
| 8237 | std::vector<unsigned int> blockShape({2, 2}); |
| 8238 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 8239 | |
| 8240 | return BatchToSpaceNdHelper<float, 4, 4>(workloadFactory, memoryManager, |
| 8241 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 8242 | crops, outputShape, expectedOutput); |
| 8243 | } |
Éanna Ó Catháin | 262553e | 2018-11-14 11:26:23 +0000 | [diff] [blame] | 8244 | |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8245 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcUintTest1( |
| 8246 | armnn::IWorkloadFactory& workloadFactory, |
| 8247 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
Éanna Ó Catháin | 262553e | 2018-11-14 11:26:23 +0000 | [diff] [blame] | 8248 | { |
| 8249 | const unsigned int inputShape[] = {4, 2, 2, 1}; |
| 8250 | const unsigned int outputShape[] = {1, 4, 4, 1}; |
| 8251 | |
| 8252 | std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 }); |
| 8253 | std::vector<uint8_t> expectedOutput({ 1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16}); |
| 8254 | |
| 8255 | std::vector<unsigned int> blockShape({2, 2}); |
| 8256 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 8257 | |
Matteo Martincigh | a65b7ae | 2018-11-14 12:39:55 +0000 | [diff] [blame] | 8258 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, armnn::DataLayout::NHWC, inputShape, |
| 8259 | input, blockShape, crops, outputShape, expectedOutput); |
Aron Virginas-Tar | 5caf907 | 2018-11-14 18:35:18 +0000 | [diff] [blame] | 8260 | } |
Nattapat Chaimanowong | 1216b58 | 2018-11-23 15:33:41 +0000 | [diff] [blame] | 8261 | |
| 8262 | LayerTestResult<float, 4> StridedSlice4DFloat32Test( |
| 8263 | armnn::IWorkloadFactory& workloadFactory, |
| 8264 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8265 | { |
| 8266 | return StridedSlice4DTest<float>(workloadFactory, memoryManager); |
| 8267 | } |
| 8268 | |
| 8269 | LayerTestResult<float, 4> StridedSlice4DReverseFloat32Test( |
| 8270 | armnn::IWorkloadFactory& workloadFactory, |
| 8271 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8272 | { |
| 8273 | return StridedSlice4DReverseTest<float>(workloadFactory, memoryManager); |
| 8274 | } |
| 8275 | |
| 8276 | LayerTestResult<float, 4> StridedSliceSimpleStrideFloat32Test( |
| 8277 | armnn::IWorkloadFactory& workloadFactory, |
| 8278 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8279 | { |
| 8280 | return StridedSliceSimpleStrideTest<float>(workloadFactory, memoryManager); |
| 8281 | } |
| 8282 | |
| 8283 | LayerTestResult<float, 4> StridedSliceSimpleRangeMaskFloat32Test( |
| 8284 | armnn::IWorkloadFactory& workloadFactory, |
| 8285 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8286 | { |
| 8287 | return StridedSliceSimpleRangeMaskTest<float>(workloadFactory, memoryManager); |
| 8288 | } |
| 8289 | |
| 8290 | LayerTestResult<float, 2> StridedSliceShrinkAxisMaskFloat32Test( |
| 8291 | armnn::IWorkloadFactory& workloadFactory, |
| 8292 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8293 | { |
| 8294 | return StridedSliceShrinkAxisMaskTest<float>(workloadFactory, memoryManager); |
| 8295 | } |
| 8296 | |
| 8297 | LayerTestResult<float, 3> StridedSlice3DFloat32Test( |
| 8298 | armnn::IWorkloadFactory& workloadFactory, |
| 8299 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8300 | { |
| 8301 | return StridedSlice3DTest<float>(workloadFactory, memoryManager); |
| 8302 | } |
| 8303 | |
| 8304 | LayerTestResult<float, 3> StridedSlice3DReverseFloat32Test( |
| 8305 | armnn::IWorkloadFactory& workloadFactory, |
| 8306 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8307 | { |
| 8308 | return StridedSlice3DReverseTest<float>(workloadFactory, memoryManager); |
| 8309 | } |
| 8310 | |
| 8311 | LayerTestResult<float, 2> StridedSlice2DFloat32Test( |
| 8312 | armnn::IWorkloadFactory& workloadFactory, |
| 8313 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8314 | { |
| 8315 | return StridedSlice2DTest<float>(workloadFactory, memoryManager); |
| 8316 | } |
| 8317 | |
| 8318 | LayerTestResult<float, 2> StridedSlice2DReverseFloat32Test( |
| 8319 | armnn::IWorkloadFactory& workloadFactory, |
| 8320 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8321 | { |
| 8322 | return StridedSlice2DReverseTest<float>(workloadFactory, memoryManager); |
| 8323 | } |
| 8324 | |
| 8325 | LayerTestResult<uint8_t, 4> StridedSlice4DUint8Test( |
| 8326 | armnn::IWorkloadFactory& workloadFactory, |
| 8327 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8328 | { |
| 8329 | return StridedSlice4DTest<uint8_t>(workloadFactory, memoryManager); |
| 8330 | } |
| 8331 | |
| 8332 | LayerTestResult<uint8_t, 4> StridedSlice4DReverseUint8Test( |
| 8333 | armnn::IWorkloadFactory& workloadFactory, |
| 8334 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8335 | { |
| 8336 | return StridedSlice4DReverseTest<uint8_t>(workloadFactory, memoryManager); |
| 8337 | } |
| 8338 | |
| 8339 | LayerTestResult<uint8_t, 4> StridedSliceSimpleStrideUint8Test( |
| 8340 | armnn::IWorkloadFactory& workloadFactory, |
| 8341 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8342 | { |
| 8343 | return StridedSliceSimpleStrideTest<uint8_t>(workloadFactory, memoryManager); |
| 8344 | } |
| 8345 | |
| 8346 | LayerTestResult<uint8_t, 4> StridedSliceSimpleRangeMaskUint8Test( |
| 8347 | armnn::IWorkloadFactory& workloadFactory, |
| 8348 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8349 | { |
| 8350 | return StridedSliceSimpleRangeMaskTest<uint8_t>(workloadFactory, memoryManager); |
| 8351 | } |
| 8352 | |
| 8353 | LayerTestResult<uint8_t, 2> StridedSliceShrinkAxisMaskUint8Test( |
| 8354 | armnn::IWorkloadFactory& workloadFactory, |
| 8355 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8356 | { |
| 8357 | return StridedSliceShrinkAxisMaskTest<uint8_t>(workloadFactory, memoryManager); |
| 8358 | } |
| 8359 | |
| 8360 | LayerTestResult<uint8_t, 3> StridedSlice3DUint8Test( |
| 8361 | armnn::IWorkloadFactory& workloadFactory, |
| 8362 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8363 | { |
| 8364 | return StridedSlice3DTest<uint8_t>(workloadFactory, memoryManager); |
| 8365 | } |
| 8366 | |
| 8367 | LayerTestResult<uint8_t, 3> StridedSlice3DReverseUint8Test( |
| 8368 | armnn::IWorkloadFactory& workloadFactory, |
| 8369 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8370 | { |
| 8371 | return StridedSlice3DReverseTest<uint8_t>(workloadFactory, memoryManager); |
| 8372 | } |
| 8373 | |
| 8374 | LayerTestResult<uint8_t, 2> StridedSlice2DUint8Test( |
| 8375 | armnn::IWorkloadFactory& workloadFactory, |
| 8376 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8377 | { |
| 8378 | return StridedSlice2DTest<uint8_t>(workloadFactory, memoryManager); |
| 8379 | } |
| 8380 | |
| 8381 | LayerTestResult<uint8_t, 2> StridedSlice2DReverseUint8Test( |
| 8382 | armnn::IWorkloadFactory& workloadFactory, |
| 8383 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8384 | { |
| 8385 | return StridedSlice2DReverseTest<uint8_t>(workloadFactory, memoryManager); |
| 8386 | } |
Mike Kelly | 831faed | 2018-11-28 11:52:08 +0000 | [diff] [blame] | 8387 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcUintTest2( |
| 8388 | armnn::IWorkloadFactory& workloadFactory, |
| 8389 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8390 | { |
| 8391 | const unsigned int inputShape[] = {4, 1, 1, 1}; |
| 8392 | const unsigned int outputShape[] = {1, 2, 2, 1}; |
| 8393 | |
| 8394 | std::vector<uint8_t> input |
| 8395 | ({ |
| 8396 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 8397 | 1, 2, 3, 4 |
| 8398 | }); |
| 8399 | |
| 8400 | std::vector<uint8_t> expectedOutput({1, 2, 3, 4}); |
| 8401 | |
| 8402 | std::vector<unsigned int> blockShape({2, 2}); |
| 8403 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 8404 | |
| 8405 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 8406 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| 8407 | crops, outputShape, expectedOutput); |
| 8408 | } |
| 8409 | |
| 8410 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcUintTest3( |
| 8411 | armnn::IWorkloadFactory& workloadFactory, |
| 8412 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8413 | { |
| 8414 | const unsigned int inputShape[] = {4, 1, 1, 3}; |
| 8415 | const unsigned int outputShape[] = {1, 2, 2, 3}; |
| 8416 | |
| 8417 | std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }); |
| 8418 | |
| 8419 | std::vector<uint8_t> expectedOutput({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }); |
| 8420 | |
| 8421 | std::vector<unsigned int> blockShape({2, 2}); |
| 8422 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 8423 | |
| 8424 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 8425 | armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| 8426 | crops, outputShape, expectedOutput); |
| 8427 | } |
| 8428 | |
| 8429 | |
| 8430 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwUintTest1( |
| 8431 | armnn::IWorkloadFactory &workloadFactory, |
| 8432 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8433 | { |
| 8434 | const unsigned int inputShape[] = {4, 3, 1, 1}; |
| 8435 | const unsigned int outputShape[] = {1, 3, 2, 2}; |
| 8436 | |
| 8437 | std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }); |
| 8438 | |
| 8439 | std::vector<uint8_t> expectedOutput |
| 8440 | ({ |
| 8441 | // Batch 0, Channel 0, Height (2) x Width (2) |
| 8442 | 1, 4, |
| 8443 | 7, 10, |
| 8444 | |
| 8445 | // Batch 0, Channel 1, Height (2) x Width (2) |
| 8446 | 2, 5, |
| 8447 | 8, 11, |
| 8448 | |
| 8449 | // Batch 0, Channel 2, Height (2) x Width (2) |
| 8450 | 3, 6, |
| 8451 | 9, 12, |
| 8452 | }); |
| 8453 | |
| 8454 | std::vector<unsigned int> blockShape({2, 2}); |
| 8455 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 8456 | |
| 8457 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 8458 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 8459 | crops, outputShape, expectedOutput); |
| 8460 | } |
| 8461 | |
| 8462 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwUintTest2( |
| 8463 | armnn::IWorkloadFactory& workloadFactory, |
| 8464 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8465 | { |
| 8466 | const unsigned int inputShape[] = {4, 1, 1, 1}; |
| 8467 | const unsigned int outputShape[] = {1, 1, 2, 2}; |
| 8468 | |
| 8469 | std::vector<uint8_t> input |
| 8470 | ({ |
| 8471 | // Batch 0, Height 0, Width (2) x Channel (1) |
| 8472 | 1, 2, 3, 4 |
| 8473 | }); |
| 8474 | |
| 8475 | std::vector<uint8_t> expectedOutput({1, 2, 3, 4}); |
| 8476 | |
| 8477 | std::vector<unsigned int> blockShape({2, 2}); |
| 8478 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 8479 | |
| 8480 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 8481 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 8482 | crops, outputShape, expectedOutput); |
| 8483 | } |
| 8484 | |
| 8485 | LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwUintTest3( |
| 8486 | armnn::IWorkloadFactory& workloadFactory, |
| 8487 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8488 | { |
| 8489 | const unsigned int inputShape[] = {4, 3, 1, 1}; |
| 8490 | const unsigned int outputShape[] = {1, 3, 2, 2}; |
| 8491 | |
| 8492 | std::vector<uint8_t> input({ 1, 3, 5, 7, 9, 11, 2, 4, 6, 8, 10, 12 }); |
| 8493 | |
| 8494 | std::vector<uint8_t> expectedOutput |
| 8495 | ({ |
| 8496 | // Batch 0, Channel 0, Height (2) x Width (2) |
| 8497 | 1, 7, |
| 8498 | 2, 8, |
| 8499 | |
| 8500 | // Batch 0, Channel 1, Height (2) x Width (2) |
| 8501 | 3, 9, |
| 8502 | 4, 10, |
| 8503 | |
| 8504 | // Batch 0, Channel 2, Height (2) x Width (2) |
| 8505 | 5, 11, |
| 8506 | 6, 12, |
| 8507 | }); |
| 8508 | std::vector<unsigned int> blockShape({2, 2}); |
| 8509 | std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| 8510 | |
| 8511 | return BatchToSpaceNdHelper<uint8_t, 4, 4>(workloadFactory, memoryManager, |
| 8512 | armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| 8513 | crops, outputShape, expectedOutput); |
Nattapat Chaimanowong | cfdcadf | 2018-12-06 11:54:33 +0000 | [diff] [blame] | 8514 | } |
| 8515 | |
| 8516 | LayerTestResult<float, 4> Debug4DFloat32Test( |
| 8517 | armnn::IWorkloadFactory& workloadFactory, |
| 8518 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8519 | { |
| 8520 | return Debug4DTest<float>(workloadFactory, memoryManager); |
| 8521 | } |
| 8522 | |
| 8523 | LayerTestResult<float, 3> Debug3DFloat32Test( |
| 8524 | armnn::IWorkloadFactory& workloadFactory, |
| 8525 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8526 | { |
| 8527 | return Debug3DTest<float>(workloadFactory, memoryManager); |
| 8528 | } |
| 8529 | |
| 8530 | LayerTestResult<float, 2> Debug2DFloat32Test( |
| 8531 | armnn::IWorkloadFactory& workloadFactory, |
| 8532 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8533 | { |
| 8534 | return Debug2DTest<float>(workloadFactory, memoryManager); |
| 8535 | } |
| 8536 | |
| 8537 | LayerTestResult<float, 1> Debug1DFloat32Test( |
| 8538 | armnn::IWorkloadFactory& workloadFactory, |
| 8539 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8540 | { |
| 8541 | return Debug1DTest<float>(workloadFactory, memoryManager); |
| 8542 | } |
| 8543 | |
| 8544 | LayerTestResult<uint8_t, 4> Debug4DUint8Test( |
| 8545 | armnn::IWorkloadFactory& workloadFactory, |
| 8546 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8547 | { |
| 8548 | return Debug4DTest<uint8_t>(workloadFactory, memoryManager); |
| 8549 | } |
| 8550 | |
| 8551 | LayerTestResult<uint8_t, 3> Debug3DUint8Test( |
| 8552 | armnn::IWorkloadFactory& workloadFactory, |
| 8553 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8554 | { |
| 8555 | return Debug3DTest<uint8_t>(workloadFactory, memoryManager); |
| 8556 | } |
| 8557 | |
| 8558 | LayerTestResult<uint8_t, 2> Debug2DUint8Test( |
| 8559 | armnn::IWorkloadFactory& workloadFactory, |
| 8560 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8561 | { |
| 8562 | return Debug2DTest<uint8_t>(workloadFactory, memoryManager); |
| 8563 | } |
| 8564 | |
| 8565 | LayerTestResult<uint8_t, 1> Debug1DUint8Test( |
| 8566 | armnn::IWorkloadFactory& workloadFactory, |
| 8567 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8568 | { |
| 8569 | return Debug1DTest<uint8_t>(workloadFactory, memoryManager); |
| 8570 | } |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 8571 | |
| 8572 | LayerTestResult<uint8_t, 4> PreCompiledConvolution2dTest( |
| 8573 | armnn::IWorkloadFactory& workloadFactory, |
| 8574 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8575 | { |
| 8576 | return PreCompiledConvolution2dTestImpl(workloadFactory, memoryManager); |
| 8577 | } |
| 8578 | |
| 8579 | LayerTestResult<uint8_t, 4> PreCompiledConvolution2dStride2x2Test( |
| 8580 | armnn::IWorkloadFactory& workloadFactory, |
| 8581 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8582 | { |
| 8583 | return PreCompiledConvolution2dStride2x2TestImpl(workloadFactory, memoryManager); |
| 8584 | } |
| 8585 | |
| 8586 | LayerTestResult<uint8_t, 4> PreCompiledDepthwiseConvolution2dTest( |
| 8587 | armnn::IWorkloadFactory & workloadFactory, |
| 8588 | const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager) |
| 8589 | { |
| 8590 | return PreCompiledDepthwiseConvolution2dTestImpl(workloadFactory, memoryManager); |
| 8591 | } |
| 8592 | |
| 8593 | LayerTestResult<uint8_t, 4> PreCompiledDepthwiseConvolution2dStride2x2Test( |
| 8594 | armnn::IWorkloadFactory & workloadFactory, |
| 8595 | const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager) |
| 8596 | { |
| 8597 | return PreCompiledDepthwiseConvolution2dStride2x2TestImpl(workloadFactory, memoryManager); |
| 8598 | } |
| 8599 | |
| 8600 | LayerTestResult<uint8_t, 4> PreCompiledMaxPooling2dTest( |
| 8601 | armnn::IWorkloadFactory& workloadFactory, |
| 8602 | const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) |
| 8603 | { |
| 8604 | return PreCompiledMaxPooling2dTestImpl(workloadFactory, memoryManager); |
| 8605 | } |