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Diffstat (limited to 'delegate/src/test/Pooling3dTest.cpp')
-rw-r--r-- | delegate/src/test/Pooling3dTest.cpp | 431 |
1 files changed, 431 insertions, 0 deletions
diff --git a/delegate/src/test/Pooling3dTest.cpp b/delegate/src/test/Pooling3dTest.cpp new file mode 100644 index 0000000000..c0a186210e --- /dev/null +++ b/delegate/src/test/Pooling3dTest.cpp @@ -0,0 +1,431 @@ +// +// Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "Pooling3dTestHelper.hpp" + +#include <armnn_delegate.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <tensorflow/lite/interpreter.h> +#include <tensorflow/lite/kernels/register.h> +#include <tensorflow/lite/model.h> +#include <tensorflow/lite/schema/schema_generated.h> +#include <tensorflow/lite/version.h> + +#include <doctest/doctest.h> + +namespace armnnDelegate +{ + +// Pool3D custom op was only added in tflite r2.6. +#if defined(ARMNN_POST_TFLITE_2_5) + +void MaxPool3dFP32PaddingValidTest(std::vector<armnn::BackendId>& backends) +{ + // Set input and expected output data + std::vector<int32_t> inputShape = { 1, 2, 3, 4, 1 }; + std::vector<int32_t> outputShape = { 1, 1, 2, 3, 1 }; + + std::vector<float> inputValues = { 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6 }; + std::vector<float> expectedOutputValues = { 6, 6, 4 }; + + // poolType string required to create the correct pooling operator + // Padding type required to create the padding in custom options + std::string poolType = "kMax"; + TfLitePadding padding = kTfLitePaddingValid; + + Pooling3dTest<float>(poolType, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + outputShape, + inputValues, + expectedOutputValues, + padding, + 1, + 1, + 1, + 2, + 2, + 2); +} + +void MaxPool3dFP32PaddingSameTest(std::vector<armnn::BackendId>& backends) +{ + // Set input data and expected output data + std::vector<int32_t> inputShape = { 1, 2, 3, 4, 1 }; + std::vector<int32_t> outputShape = { 1, 2, 3, 4, 1 }; + + std::vector<float> inputValues = { 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6 }; + std::vector<float> expectedOutputValues = { 6, 6, 4, 4, 6, 6, 6, 6, 4, 5, 6, 6, 6, 6, 4, 4 }; + + // poolType string required to create the correct pooling operator + // Padding type required to create the padding in custom options + std::string poolType = "kMax"; + TfLitePadding padding = kTfLitePaddingSame; + + Pooling3dTest<float>(poolType, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + outputShape, + inputValues, + expectedOutputValues, + padding, + 1, + 1, + 1, + 2, + 2, + 2); +} + +void MaxPool3dFP32H1Test(std::vector<armnn::BackendId>& backends) +{ + // Set input data and expected output data + std::vector<int32_t> inputShape = { 1, 2, 3, 4, 1 }; + std::vector<int32_t> outputShape = { 1, 1, 3, 3, 1 }; + + std::vector<float> inputValues = { 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6 }; + std::vector<float> expectedOutputValues = { 2, 3 }; + + // poolType string required to create the correct pooling operator + // Padding type required to create the padding in custom options + std::string poolType = "kMax"; + TfLitePadding padding = kTfLitePaddingValid; + + Pooling3dTest<float>(poolType, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + outputShape, + inputValues, + expectedOutputValues, + padding, + 1, + 1, + 1, + 2, + 1, + 2); +} + +void MaxPool3dFP32Test(std::vector<armnn::BackendId>& backends) +{ + // Set input data and expected output data + std::vector<int32_t> inputShape = { 1, 2, 3, 4, 1 }; + std::vector<int32_t> outputShape = { 1, 2, 3, 4, 1 }; + + std::vector<float> inputValues = { 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6 }; + std::vector<float> expectedOutputValues = { 6, 6 }; + + // poolType string required to create the correct pooling operator + // Padding type required to create the padding in custom options + std::string poolType = "kMax"; + TfLitePadding padding = kTfLitePaddingUnknown; + + Pooling3dTest<float>(poolType, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + outputShape, + inputValues, + expectedOutputValues, + padding, + 1, + 1, + 1, + 2, + 2, + 2); +} + +void AveragePool3dFP32PaddingValidTest(std::vector<armnn::BackendId>& backends) +{ + // Set input data and expected output data. + std::vector<int32_t> inputShape = { 1, 2, 3, 4, 1 }; + std::vector<int32_t> outputShape = { 1, 1, 2, 3, 1 }; + + std::vector<float> inputValues = { 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6 }; + std::vector<float> expectedOutputValues = { 3.5, 3, 2.5 }; + + // poolType string required to create the correct pooling operator + // Padding type required to create the padding in custom options + std::string poolType = "kAverage"; + TfLitePadding padding = kTfLitePaddingValid; + + Pooling3dTest<float>(poolType, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + outputShape, + inputValues, + expectedOutputValues, + padding, + 1, + 1, + 1, + 2, + 2, + 2); +} + +void AveragePool3dFP32PaddingSameTest(std::vector<armnn::BackendId>& backends) +{ + // Set input data and expected output data + std::vector<int32_t> inputShape = { 4, 2, 3, 1, 1 }; + std::vector<int32_t> outputShape = { 4, 2, 3, 1, 1 }; + + std::vector<float> inputValues = { 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6 }; + std::vector<float> expectedOutputValues = { 3, 4, 4.5, 4.5, 5.5, 6, 3, 4, 4.5, 4.5, 5.5, 6, 3, 4, 4.5, 4.5 }; + + // poolType string required to create the correct pooling operator + // Padding type required to create the padding in custom options + std::string poolType = "kAverage"; + TfLitePadding padding = kTfLitePaddingSame; + + Pooling3dTest<float>(poolType, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + outputShape, + inputValues, + expectedOutputValues, + padding, + 1, + 1, + 1, + 2, + 2, + 2); +} + +void AveragePool3dFP32H1Test(std::vector<armnn::BackendId>& backends) +{ + // Set input data and expected output data + std::vector<int32_t> inputShape = { 1, 2, 3, 4, 1 }; + std::vector<int32_t> outputShape = { 1, 1, 2, 2, 1 }; + + std::vector<float> inputValues = { 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6 }; + std::vector<float> expectedOutputValues = { 1.5, 3.5 }; + + // poolType string required to create the correct pooling operator + // Padding type required to create the padding in custom options + std::string poolType = "kAverage"; + TfLitePadding padding = kTfLitePaddingUnknown; + + Pooling3dTest<float>(poolType, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + outputShape, + inputValues, + expectedOutputValues, + padding, + 2, + 2, + 2, + 2, + 1, + 2); +} + +void AveragePool3dFP32Test(std::vector<armnn::BackendId>& backends) +{ + // Set input data and expected output data + std::vector<int32_t> inputShape = { 4, 3, 2, 1, 1 }; + std::vector<int32_t> outputShape = { 1, 2, 2, 4, 1 }; + + std::vector<float> inputValues = { 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6, + 1, 2, 3, 4, 5, 6 }; + std::vector<float> expectedOutputValues = { 3.125, 4.25 }; + + // poolType string required to create the correct pooling operator + // Padding type required to create the padding in custom options + std::string poolType = "kMax"; + TfLitePadding padding = kTfLitePaddingUnknown; + + Pooling3dTest<float>(poolType, + ::tflite::TensorType_FLOAT32, + backends, + inputShape, + outputShape, + inputValues, + expectedOutputValues, + padding, + 2, + 2, + 2, + 2, + 2, + 2); +} + +TEST_SUITE("Pooling3d_GpuAccTests") +{ + +TEST_CASE ("MaxPooling3d_FP32_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + MaxPool3dFP32Test(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_PaddingValid_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + MaxPool3dFP32PaddingValidTest(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_PaddingSame_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + MaxPool3dFP32PaddingSameTest(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_H1_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + MaxPool3dFP32H1Test(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_PaddingValid_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + AveragePool3dFP32PaddingValidTest(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_PaddingSame_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + AveragePool3dFP32PaddingSameTest(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_H1_GpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc }; + AveragePool3dFP32H1Test(backends); +} + +} // TEST_SUITE("Pooling3d_GpuAccTests") + +TEST_SUITE("Pooling3d_CpuAccTests") +{ + +TEST_CASE ("MaxPooling3d_FP32_PaddingValid_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + MaxPool3dFP32PaddingValidTest(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_PaddingSame_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + MaxPool3dFP32PaddingSameTest(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + MaxPool3dFP32Test(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_H1_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + MaxPool3dFP32H1Test(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_PaddingValid_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + AveragePool3dFP32PaddingValidTest(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_PaddingSame_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + AveragePool3dFP32PaddingSameTest(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_H1_CpuAcc_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc }; + AveragePool3dFP32H1Test(backends); +} + +} // TEST_SUITE("Pooling3d_CpuAccTests") + +TEST_SUITE("Pooling3d_CpuRefTests") +{ +TEST_CASE ("MaxPooling3d_FP32_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + MaxPool3dFP32Test(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_PaddingValid_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + MaxPool3dFP32PaddingValidTest(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_PaddingSame_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + MaxPool3dFP32PaddingSameTest(backends); +} + +TEST_CASE ("MaxPooling3d_FP32_H1_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + MaxPool3dFP32H1Test(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_PaddingValid_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + AveragePool3dFP32PaddingValidTest(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_PaddingSame_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + AveragePool3dFP32PaddingSameTest(backends); +} + +TEST_CASE ("AveragePooling3d_FP32_H1_CpuRef_Test") +{ + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + AveragePool3dFP32H1Test(backends); +} + +} // TEST_SUITE("Pooling3d_CpuRefTests") + +#endif + +}
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