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-rw-r--r--delegate/src/test/Pooling3dTest.cpp431
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diff --git a/delegate/src/test/Pooling3dTest.cpp b/delegate/src/test/Pooling3dTest.cpp
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+//
+// 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
+
+} \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-15 23:54:08 +0000