| // |
| // 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 |
| |
| } |