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-rw-r--r--delegate/src/test/FullyConnectedTest.cpp33
-rw-r--r--delegate/src/test/FullyConnectedTestHelper.hpp101
2 files changed, 88 insertions, 46 deletions
diff --git a/delegate/src/test/FullyConnectedTest.cpp b/delegate/src/test/FullyConnectedTest.cpp
index 018f7f5190..3bea250988 100644
--- a/delegate/src/test/FullyConnectedTest.cpp
+++ b/delegate/src/test/FullyConnectedTest.cpp
@@ -8,7 +8,7 @@
namespace
{
-void FullyConnectedFp32Test(std::vector<armnn::BackendId>& backends)
+void FullyConnectedFp32Test(std::vector<armnn::BackendId>& backends, bool constantWeights = true)
{
std::vector<int32_t> inputTensorShape { 1, 4, 1, 1 };
std::vector<int32_t> weightsTensorShape { 1, 4 };
@@ -30,10 +30,11 @@ void FullyConnectedFp32Test(std::vector<armnn::BackendId>& backends)
outputTensorShape,
inputValues,
expectedOutputValues,
- weightsData);
+ weightsData,
+ constantWeights);
}
-void FullyConnectedActicationTest(std::vector<armnn::BackendId>& backends)
+void FullyConnectedActicationTest(std::vector<armnn::BackendId>& backends, bool constantWeights = true)
{
std::vector<int32_t> inputTensorShape { 1, 4, 1, 1 };
std::vector<int32_t> weightsTensorShape { 1, 4 };
@@ -55,10 +56,11 @@ void FullyConnectedActicationTest(std::vector<armnn::BackendId>& backends)
outputTensorShape,
inputValues,
expectedOutputValues,
- weightsData);
+ weightsData,
+ constantWeights);
}
-void FullyConnectedInt8Test(std::vector<armnn::BackendId>& backends)
+void FullyConnectedInt8Test(std::vector<armnn::BackendId>& backends, bool constantWeights = true)
{
std::vector<int32_t> inputTensorShape { 1, 4, 2, 1 };
std::vector<int32_t> weightsTensorShape { 1, 4 };
@@ -82,7 +84,8 @@ void FullyConnectedInt8Test(std::vector<armnn::BackendId>& backends)
outputTensorShape,
inputValues,
expectedOutputValues,
- weightsData);
+ weightsData,
+ constantWeights);
}
TEST_SUITE("FullyConnected_GpuAccTests")
@@ -152,6 +155,24 @@ TEST_CASE ("FullyConnected_Activation_CpuRef_Test")
FullyConnectedActicationTest(backends);
}
+TEST_CASE ("FullyConnected_Weights_As_Inputs_FP32_CpuRef_Test")
+{
+ std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
+ FullyConnectedFp32Test(backends, false);
+}
+
+TEST_CASE ("FullyConnected_Weights_As_Inputs_Int8_CpuRef_Test")
+{
+ std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
+ FullyConnectedInt8Test(backends, false);
+}
+
+TEST_CASE ("FullyConnected_Weights_As_Inputs_Activation_CpuRef_Test")
+{
+ std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
+ FullyConnectedActicationTest(backends, false);
+}
+
} // End of TEST_SUITE("FullyConnected_CpuRefTests")
} // anonymous namespace \ No newline at end of file
diff --git a/delegate/src/test/FullyConnectedTestHelper.hpp b/delegate/src/test/FullyConnectedTestHelper.hpp
index 1b6ca941b8..37062c3400 100644
--- a/delegate/src/test/FullyConnectedTestHelper.hpp
+++ b/delegate/src/test/FullyConnectedTestHelper.hpp
@@ -5,6 +5,8 @@
#pragma once
+#include "TestUtils.hpp"
+
#include <armnn_delegate.hpp>
#include <flatbuffers/flatbuffers.h>
@@ -25,8 +27,9 @@ std::vector<char> CreateFullyConnectedTfLiteModel(tflite::TensorType tensorType,
const std::vector <int32_t>& inputTensorShape,
const std::vector <int32_t>& weightsTensorShape,
const std::vector <int32_t>& biasTensorShape,
- const std::vector <int32_t>& outputTensorShape,
- const std::vector <T>& weightsData,
+ std::vector <int32_t>& outputTensorShape,
+ std::vector <T>& weightsData,
+ bool constantWeights = true,
float quantScale = 1.0f,
int quantOffset = 0,
float outputQuantScale = 2.0f,
@@ -36,26 +39,38 @@ std::vector<char> CreateFullyConnectedTfLiteModel(tflite::TensorType tensorType,
flatbuffers::FlatBufferBuilder flatBufferBuilder;
std::array<flatbuffers::Offset<tflite::Buffer>, 3> buffers;
buffers[0] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}));
- buffers[1] = CreateBuffer(flatBufferBuilder,
- flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(weightsData.data()),
- sizeof(T) * weightsData.size()));
auto biasTensorType = ::tflite::TensorType_FLOAT32;
if (tensorType == ::tflite::TensorType_INT8)
{
biasTensorType = ::tflite::TensorType_INT32;
- std::vector<int32_t> biasData = { 10 };
- buffers[2] = CreateBuffer(flatBufferBuilder,
- flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()),
- sizeof(int32_t) * biasData.size()));
+ }
+ if (constantWeights)
+ {
+ buffers[1] = CreateBuffer(flatBufferBuilder,
+ flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(weightsData.data()),
+ sizeof(T) * weightsData.size()));
+ if (tensorType == ::tflite::TensorType_INT8)
+ {
+ std::vector<int32_t> biasData = { 10 };
+ buffers[2] = CreateBuffer(flatBufferBuilder,
+ flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()),
+ sizeof(int32_t) * biasData.size()));
+
+ }
+ else
+ {
+ std::vector<float> biasData = { 10 };
+ buffers[2] = CreateBuffer(flatBufferBuilder,
+ flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()),
+ sizeof(float) * biasData.size()));
+ }
}
else
{
- std::vector<float> biasData = { 10 };
- buffers[2] = CreateBuffer(flatBufferBuilder,
- flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()),
- sizeof(float) * biasData.size()));
+ buffers[1] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}));
+ buffers[2] = CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}));
}
auto quantizationParameters =
@@ -155,10 +170,11 @@ void FullyConnectedTest(std::vector<armnn::BackendId>& backends,
const std::vector <int32_t>& inputTensorShape,
const std::vector <int32_t>& weightsTensorShape,
const std::vector <int32_t>& biasTensorShape,
- const std::vector <int32_t>& outputTensorShape,
- const std::vector <T>& inputValues,
- const std::vector <T>& expectedOutputValues,
- const std::vector <T>& weightsData,
+ std::vector <int32_t>& outputTensorShape,
+ std::vector <T>& inputValues,
+ std::vector <T>& expectedOutputValues,
+ std::vector <T>& weightsData,
+ bool constantWeights = true,
float quantScale = 1.0f,
int quantOffset = 0)
{
@@ -171,10 +187,11 @@ void FullyConnectedTest(std::vector<armnn::BackendId>& backends,
biasTensorShape,
outputTensorShape,
weightsData,
+ constantWeights,
quantScale,
quantOffset);
-
const Model* tfLiteModel = GetModel(modelBuffer.data());
+
// Create TfLite Interpreters
std::unique_ptr<Interpreter> armnnDelegateInterpreter;
CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
@@ -191,25 +208,34 @@ void FullyConnectedTest(std::vector<armnn::BackendId>& backends,
// Create the ArmNN Delegate
armnnDelegate::DelegateOptions delegateOptions(backends);
std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
- theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
- armnnDelegate::TfLiteArmnnDelegateDelete);
+ theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
+ armnnDelegate::TfLiteArmnnDelegateDelete);
CHECK(theArmnnDelegate != nullptr);
+
// Modify armnnDelegateInterpreter to use armnnDelegate
CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
// Set input data
- auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[0];
- auto tfLiteDelageInputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInputId);
- for (unsigned int i = 0; i < inputValues.size(); ++i)
- {
- tfLiteDelageInputData[i] = inputValues[i];
- }
+ armnnDelegate::FillInput<T>(tfLiteInterpreter, 0, inputValues);
+ armnnDelegate::FillInput<T>(armnnDelegateInterpreter, 0, inputValues);
- auto armnnDelegateInputId = armnnDelegateInterpreter->inputs()[0];
- auto armnnDelegateInputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInputId);
- for (unsigned int i = 0; i < inputValues.size(); ++i)
+ if (!constantWeights)
{
- armnnDelegateInputData[i] = inputValues[i];
+ armnnDelegate::FillInput<T>(tfLiteInterpreter, 1, weightsData);
+ armnnDelegate::FillInput<T>(armnnDelegateInterpreter, 1, weightsData);
+
+ if (tensorType == ::tflite::TensorType_INT8)
+ {
+ std::vector <int32_t> biasData = {10};
+ armnnDelegate::FillInput<int32_t>(tfLiteInterpreter, 2, biasData);
+ armnnDelegate::FillInput<int32_t>(armnnDelegateInterpreter, 2, biasData);
+ }
+ else
+ {
+ std::vector<float> biasData = {10};
+ armnnDelegate::FillInput<float>(tfLiteInterpreter, 2, biasData);
+ armnnDelegate::FillInput<float>(armnnDelegateInterpreter, 2, biasData);
+ }
}
// Run EnqueWorkload
@@ -217,16 +243,11 @@ void FullyConnectedTest(std::vector<armnn::BackendId>& backends,
CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
// Compare output data
- auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
- auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateOutputId);
- auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
- auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateOutputId);
- for (size_t i = 0; i < expectedOutputValues.size(); i++)
- {
- CHECK(expectedOutputValues[i] == tfLiteDelageOutputData[i]);
- CHECK(expectedOutputValues[i] == armnnDelegateOutputData[i]);
- CHECK(tfLiteDelageOutputData[i] == armnnDelegateOutputData[i]);
- }
+ armnnDelegate::CompareOutputData<T>(tfLiteInterpreter,
+ armnnDelegateInterpreter,
+ outputTensorShape,
+ expectedOutputValues);
+ armnnDelegateInterpreter.reset(nullptr);
}
} // anonymous namespace \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-07-01 15:33:48 +0000