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author | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-03-14 12:10:28 +0000 |
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committer | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-03-28 11:41:55 +0100 |
commit | ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9 (patch) | |
tree | a5b8e1ad68a2437f007338f0b6195ca5ed2bddc3 /delegate/test/LstmTest.cpp | |
parent | 9cb3466b677a1048b8abb24661e92c4c83fdda04 (diff) | |
download | armnn-ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9.tar.gz |
IVGCVSW-7555 Restructure Delegate
* New folders created:
* common is for common code where TfLite API is not used
* classic is for existing delegate implementations
* opaque is for new opaque delegate implementation,
* tests is for shared between existing Delegate and Opaque Delegate which have test utils to work which delegate to use.
* Existing delegate is built to libarmnnDelegate.so and opaque delegate is built as libarmnnOpaqueDelegate.so
* Opaque structure is introduced but no API is added yet.
* CmakeList.txt and delegate/CMakeList.txt have been modified and 2 new CmakeList.txt added
* Rename BUILD_ARMNN_TFLITE_DELEGATE as BUILD_CLASSIC_DELEGATE
* Rename BUILD_ARMNN_TFLITE_OPAQUE_DELEGATE as BUILD_OPAQUE_DELEGATE
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ib682b9ad0ac8d8acdc4ec6d9099bb0008a9fe8ed
Diffstat (limited to 'delegate/test/LstmTest.cpp')
-rw-r--r-- | delegate/test/LstmTest.cpp | 189 |
1 files changed, 189 insertions, 0 deletions
diff --git a/delegate/test/LstmTest.cpp b/delegate/test/LstmTest.cpp new file mode 100644 index 0000000000..1034a012e2 --- /dev/null +++ b/delegate/test/LstmTest.cpp @@ -0,0 +1,189 @@ +// +// Copyright © 2021, 2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "LstmTestHelper.hpp" + +#include <armnn_delegate.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <schema_generated.h> +#include <doctest/doctest.h> + +namespace armnnDelegate +{ + +void LstmTest(std::vector<armnn::BackendId>& backends) +{ + int32_t batchSize = 2; + int32_t inputSize = 2; + int32_t outputSize = 4; + // cellSize and outputSize have the same size when there is no projection. + int32_t numUnits = outputSize; + + std::vector<int32_t> inputShape {batchSize , inputSize}; + std::vector<int32_t> cellStateInTensorInfo {batchSize , numUnits}; + std::vector<int32_t> outputStateInTensorInfo {batchSize , outputSize}; + + std::vector<int32_t> scratchBufferTensorInfo {batchSize, numUnits * 4}; + std::vector<int32_t> cellStateOutTensorInfo {batchSize, numUnits}; + std::vector<int32_t> outputStateOutTensorInfo {batchSize, outputSize}; + std::vector<int32_t> outputTensorInfo {batchSize, outputSize}; + + std::vector<int32_t> tensorInfo4 {numUnits}; + std::vector<int32_t> tensorInfo8 {numUnits, 2}; + std::vector<int32_t> tensorInfo16 {numUnits, 4}; + + //tensorInfo8, + bool hasInputToInputWeights = true; + std::vector<float> inputToInputWeights {-0.45018822f, -0.02338299f, -0.0870589f, + -0.34550029f, 0.04266912f, -0.15680569f, + -0.34856534f, 0.43890524f}; + + std::vector<float> inputToForgetWeights {0.09701663f, 0.20334584f, -0.50592935f, + -0.31343272f, -0.40032279f, 0.44781327f, + 0.01387155f, -0.35593212f}; + + std::vector<float> inputToCellWeights {-0.50013041f, 0.1370284f, 0.11810488f, 0.2013163f, + -0.20583314f, 0.44344562f, 0.22077113f, + -0.29909778f}; + + std::vector<float> inputToOutputWeights {-0.25065863f, -0.28290087f, 0.04613829f, + 0.40525138f, 0.44272184f, 0.03897077f, + -0.1556896f, 0.19487578f}; + + //tensorInfo16, + bool hasRecurrentToInputWeights = true; + std::vector<float> recurrentToInputWeights {-0.0063535f, -0.2042388f, 0.31454784f, + -0.35746509f, 0.28902304f, 0.08183324f, + -0.16555229f, 0.02286911f, -0.13566875f, + 0.03034258f, 0.48091322f, -0.12528998f, + 0.24077177f, -0.51332325f, -0.33502164f, + 0.10629296f}; + + std::vector<float> recurrentToForgetWeights {-0.48684245f, -0.06655136f, 0.42224967f, + 0.2112639f, 0.27654213f, 0.20864892f, + -0.07646349f, 0.45877004f, 0.00141793f, + -0.14609534f, 0.36447752f, 0.09196436f, + 0.28053468f, 0.01560611f, -0.20127171f, + -0.01140004f}; + + std::vector<float> recurrentToCellWeights {-0.3407414f, 0.24443203f, -0.2078532f, + 0.26320225f, 0.05695659f, -0.00123841f, + -0.4744786f, -0.35869038f, -0.06418842f, + -0.13502428f, -0.501764f, 0.22830659f, + -0.46367589f, 0.26016325f, -0.03894562f, + -0.16368064f}; + + std::vector<float> recurrentToOutputWeights {0.43385774f, -0.17194885f, 0.2718237f, + 0.09215671f, 0.24107647f, -0.39835793f, + 0.18212086f, 0.01301402f, 0.48572797f, + -0.50656658f, 0.20047462f, -0.20607421f, + -0.51818722f, -0.15390486f, 0.0468148f, + 0.39922136f}; + // tensorInfo4 + bool hasCellToInputWeights = false; + std::vector<float> cellToInputWeights {}; + bool hasCellToForgetWeights = false; + std::vector<float> cellToForgetWeights {}; + bool hasCellToOutputWeights = false; + std::vector<float> cellToOutputWeights {}; + + bool hasInputGateBias = true; + std::vector<float> inputGateBias {0., 0., 0., 0.}; + std::vector<float> forgetGateBias {1., 1., 1., 1.}; + std::vector<float> cellBias {0., 0., 0., 0.}; + std::vector<float> outputGateBias {0., 0., 0., 0.}; + + bool hasProjectionWeights = false; + std::vector<float> projectionWeights; + bool hasProjectionBias = false; + std::vector<float> projectionBias; + + bool hasInputLayerNormWeights = false; + std::vector<float> inputLayerNormWeights; + bool hasForgetLayerNormWeights = false; + std::vector<float> forgetLayerNormWeights; + bool hasCellLayerNormWeights = false; + std::vector<float> cellLayerNormWeights; + bool hasOutputLayerNormWeights = false; + std::vector<float> outputLayerNormWeights; + + std::vector<float> inputValues {2., 3., 3., 4.}; + std::vector<float> expectedOutputValues {-0.02973187f, 0.1229473f, 0.20885126f, -0.15358765f, + -0.0185422f, 0.11281417f, 0.24466537f, -0.1826292f}; + + tflite::ActivationFunctionType activationFunction = tflite::ActivationFunctionType_TANH; + float clippingThresCell = 0.f; + float clippingThresProj = 0.f; + + LstmTestImpl<float>(backends, + ::tflite::TensorType_FLOAT32, + batchSize, + inputSize, + outputSize, + numUnits, + hasInputToInputWeights, + inputToInputWeights, + inputToForgetWeights, + inputToCellWeights, + inputToOutputWeights, + hasRecurrentToInputWeights, + recurrentToInputWeights, + recurrentToForgetWeights, + recurrentToCellWeights, + recurrentToOutputWeights, + hasCellToInputWeights, + cellToInputWeights, + hasCellToForgetWeights, + cellToForgetWeights, + hasCellToOutputWeights, + cellToOutputWeights, + hasInputGateBias, + inputGateBias, + forgetGateBias, + cellBias, + outputGateBias, + hasProjectionWeights, + projectionWeights, + hasProjectionBias, + projectionBias, + hasInputLayerNormWeights, + inputLayerNormWeights, + hasForgetLayerNormWeights, + forgetLayerNormWeights, + hasCellLayerNormWeights, + cellLayerNormWeights, + hasOutputLayerNormWeights, + outputLayerNormWeights, + inputValues, + expectedOutputValues, + activationFunction, + clippingThresCell, + clippingThresProj); +} + +TEST_SUITE("LstmTest_CpuRefTests") +{ + +TEST_CASE ("LstmTest_CpuRef_Test") +{ + std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef}; + LstmTest(backends); +} + +} //End of TEST_SUITE("Convolution2dTest_CpuRef") + +TEST_SUITE("LstmTest_CpuAccTests") +{ + +TEST_CASE ("LstmTest_CpuAcc_Test") +{ + std::vector <armnn::BackendId> backends = {armnn::Compute::CpuAcc}; + LstmTest(backends); +} + +} //End of TEST_SUITE("Convolution2dTest_CpuAcc") + +} // namespace armnnDelegate
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