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-rw-r--r--delegate/src/test/Convolution3dTest.cpp273
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diff --git a/delegate/src/test/Convolution3dTest.cpp b/delegate/src/test/Convolution3dTest.cpp
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+++ b/delegate/src/test/Convolution3dTest.cpp
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+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ConvolutionTestHelper.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 <doctest/doctest.h>
+
+namespace armnnDelegate
+{
+
+// Conv3d is currently only supports Float32 inputs, filter, bias and outputs in TFLite.
+// Conv3d is only correctly supported for external delegates from TF Lite v2.6, as there was a breaking bug in v2.5.
+#if defined(ARMNN_POST_TFLITE_2_5)
+
+// Create a vector from 0 to size divided to create smaller floating point values.
+template <typename T>
+std::vector<T> CreateFloatData(int32_t size, float divisor)
+{
+ std::vector<float> data;
+ for (int32_t i = 0; i < size; ++i)
+ {
+ float value = static_cast<float>(i);
+ data.push_back(value/divisor);
+ }
+ return data;
+}
+
+void Conv3DWithBiasesSimpleWithPaddingFp32Test(std::vector<armnn::BackendId>& backends)
+{
+ // Set input data
+ std::vector<int32_t> inputShape { 1, 2, 2, 2, 1 };
+ std::vector<int32_t> filterShape { 2, 2, 2, 1, 1 };
+ std::vector<int32_t> biasShape { 1 };
+ std::vector<int32_t> outputShape { 1, 2, 2, 2, 1 };
+
+ static std::vector<float> inputValues =
+ {
+ 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f
+ };
+
+ std::vector<float> filterValues =
+ {
+ 2.f,1.f, 1.f,0.f, 0.f,1.f, 1.f,1.f
+ };
+
+ std::vector<float> biasValues = { 5.f };
+
+ std::vector<float> expectedOutputValues =
+ {
+ 33.f, 21.f, 23.f, 13.f, 28.f, 25.f, 27.f, 21.f
+ };
+
+ Convolution3dTest<float>(tflite::BuiltinOperator_CONV_3D,
+ ::tflite::TensorType_FLOAT32,
+ { 1, 1, 1 }, // strideX, strideY, strideZ
+ { 1, 1, 1 }, // dilationX, dilationY, dilationZ
+ tflite::Padding_SAME,
+ tflite::ActivationFunctionType_NONE,
+ backends,
+ inputShape,
+ filterShape,
+ outputShape,
+ inputValues,
+ filterValues,
+ expectedOutputValues,
+ biasShape,
+ biasValues);
+}
+
+void Conv3DWithBiasesStridesFp32Test(std::vector<armnn::BackendId>& backends)
+{
+ std::vector<int32_t> inputShape { 1, 3, 10, 10, 1 };
+ std::vector<int32_t> filterShape { 3, 5, 5, 1, 1 };
+ std::vector<int32_t> biasShape { 1 };
+ std::vector<int32_t> outputShape { 1, 1, 3, 3, 1 };
+
+ std::vector<float> inputValues = CreateFloatData<float>(300, 1.0f);
+
+ std::vector<float> filterValues =
+ {
+ 1.f, 1.f, 1.f, 1.f, 1.f,
+ 1.f, 1.f, 1.f, 1.f, 1.f,
+ 1.f, 1.f, 1.f, 1.f, 1.f,
+ 1.f, 1.f, 1.f, 1.f, 1.f,
+ 1.f, 1.f, 1.f, 1.f, 1.f,
+
+ 0.f, 0.f, 0.f, 0.f, 0.f,
+ 0.f, 0.f, 0.f, 0.f, 0.f,
+ 0.f, 0.f, 0.f, 0.f, 0.f,
+ 0.f, 0.f, 0.f, 0.f, 0.f,
+ 0.f, 0.f, 0.f, 0.f, 0.f,
+
+ 2.f, 2.f, 2.f, 2.f, 2.f,
+ 2.f, 2.f, 2.f, 2.f, 2.f,
+ 2.f, 2.f, 2.f, 2.f, 2.f,
+ 2.f, 2.f, 2.f, 2.f, 2.f,
+ 2.f, 2.f, 2.f, 2.f, 2.f
+ };
+
+ std::vector<float> biasValues = { 10.f };
+
+ std::vector<float> expectedOutputValues =
+ {
+ 11660.f, 11810.f, 11960.f,
+
+ 13160.f, 13310.f, 13460.f,
+
+ 14660.f, 14810.f, 14960.f
+ };
+
+ Convolution3dTest<float>(tflite::BuiltinOperator_CONV_3D,
+ ::tflite::TensorType_FLOAT32,
+ { 2, 2, 2 }, // strideX, strideY, strideZ
+ { 1, 1, 1 }, // dilationX, dilationY, dilationZ
+ tflite::Padding_VALID,
+ tflite::ActivationFunctionType_NONE,
+ backends,
+ inputShape,
+ filterShape,
+ outputShape,
+ inputValues,
+ filterValues,
+ expectedOutputValues,
+ biasShape,
+ biasValues);
+}
+
+
+void Conv3DWithBiasesDilationFp32Test(std::vector<armnn::BackendId>& backends)
+{
+ std::vector<int32_t> inputShape { 1, 5, 5, 5, 2 };
+ std::vector<int32_t> filterShape { 2, 2, 2, 2, 2 };
+ std::vector<int32_t> biasShape { 2 };
+ std::vector<int32_t> outputShape { 1, 2, 2, 2, 2 };
+
+ std::vector<float> inputValues = CreateFloatData<float>(250, 1.0f);
+
+ std::vector<float> filterValues =
+ {
+ -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, -1.f, 1.f, 1.f, 1.f, -1.f, -1.f,
+ 1.f, 1.f, -1.f, 1.f, -1.f, 1.f, -1.f, 1.f, -1.f, -1.f, -1.f, 1.f, -1.f, 1.f, -1.f, 1.f,
+ };
+
+ std::vector<float> biasValues = { 0.f, 2.f };
+
+ // Since the dilation rate is 3 this will dilate the kernel to be 4x4,
+ // therefore the output will be 2x2
+ std::vector<float> expectedOutputValues =
+ {
+ -1124.f, 976.f,
+ -1148.f, 980.f,
+
+ -1244.f, 996.f,
+ -1268.f, 1000.f,
+
+ -1724.f, 1076.f,
+ -1748.f, 1080.f,
+
+ -1844.f, 1096.f,
+ -1868.f, 1100.f
+ };
+
+ Convolution3dTest<float>(tflite::BuiltinOperator_CONV_3D,
+ ::tflite::TensorType_FLOAT32,
+ { 1, 1, 1 }, // strideX, strideY, strideZ
+ { 3, 3, 3 }, // dilationX, dilationY, dilationZ
+ tflite::Padding_VALID,
+ tflite::ActivationFunctionType_NONE,
+ backends,
+ inputShape,
+ filterShape,
+ outputShape,
+ inputValues,
+ filterValues,
+ expectedOutputValues,
+ biasShape,
+ biasValues);
+}
+
+void Conv3DFp32SmallTest(std::vector<armnn::BackendId>& backends)
+{
+ std::vector<int32_t> inputShape { 1, 3, 10, 10, 1 };
+ std::vector<int32_t> filterShape { 3, 3, 3, 1, 1 };
+ std::vector<int32_t> biasShape { 1 };
+ std::vector<int32_t> outputShape { 1, 1, 4, 4, 1 };
+
+ std::vector<float> inputValues = CreateFloatData<float>(300, 100.0f);
+
+ std::vector<float> filterValues =
+ {
+ 0.125977f, 0.150391f, 0.101562f,
+ 0.0585938f, 0.0864258f, 0.043457f,
+ 0.034668f, 0.0322266f, 0.0385742f,
+
+ 0.125977f, 0.150391f, -0.101562f,
+ -0.0585938f,-0.0864258f,-0.043457f,
+ -0.0104630f, 0.0154114f, 0.0013768f,
+
+ 0.0344238f, 0.035644f, 0.0495605f,
+ 0.0683594f, 0.099121f, -0.0461426f,
+ -0.0996094f,-0.126953f, -0.043457f,
+ };
+
+ std::vector<float> biasValues = { 0 };
+
+ std::vector<float> expectedOutputValues =
+ {
+ -0.08156067f, -0.06891209f, -0.05589598f, -0.04310101f,
+ 0.04584253f, 0.05855697f, 0.07129729f, 0.08325434f,
+ 0.17304349f, 0.18521416f, 0.19818866f, 0.21096253f,
+ 0.29965734f, 0.312698f, 0.32547557f, 0.33818722f
+ };
+
+ Convolution3dTest<float>(tflite::BuiltinOperator_CONV_3D,
+ ::tflite::TensorType_FLOAT32,
+ { 2, 2, 2 }, // strideX, strideY, strideZ
+ { 1, 1, 1 }, // dilationX, dilationY, dilationZ
+ tflite::Padding_VALID,
+ tflite::ActivationFunctionType_NONE,
+ backends,
+ inputShape,
+ filterShape,
+ outputShape,
+ inputValues,
+ filterValues,
+ expectedOutputValues,
+ biasShape,
+ biasValues);
+}
+
+TEST_SUITE("Convolution3dTest_CpuRefTests")
+{
+
+TEST_CASE ("Conv3DWithBiasesSimpleWithPadding_Fp32_CpuRef_Test")
+{
+ std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef};
+ Conv3DWithBiasesSimpleWithPaddingFp32Test(backends);
+}
+
+TEST_CASE ("Conv3DWithBiasesStrides_Fp32_CpuRef_Test")
+{
+ std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef};
+ Conv3DWithBiasesStridesFp32Test(backends);
+}
+
+TEST_CASE ("Conv3DWithBiasesDilation_Fp32_CpuRef_Test")
+{
+ std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef};
+ Conv3DWithBiasesDilationFp32Test(backends);
+}
+
+TEST_CASE ("Conv3DFp32Small_Fp32_CpuRef_Test")
+{
+ std::vector <armnn::BackendId> backends = {armnn::Compute::CpuRef};
+ Conv3DFp32SmallTest(backends);
+}
+
+
+} //End of TEST_SUITE("Convolution3dTest_CpuRefTests")
+
+#endif
+
+} // namespace armnnDelegate \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-07 19:00:46 +0000