IVGCVSW-5879 Pass the execute network parameters to the TfLiteDelegate.
* Introduce a mechanism to construct a DelegateOptions from an
ExecuteNetworkParams.
* Modify ExecuteNetwork to use this constructed DelegateOptions.
Signed-off-by: Colm Donelan <Colm.Donelan@arm.com>
Change-Id: Ied663a1e00ac3eece42244ed313ddafd6d2ce078
diff --git a/tests/ExecuteNetwork/ExecuteNetwork.cpp b/tests/ExecuteNetwork/ExecuteNetwork.cpp
index 8acab71..fa8c8c8 100644
--- a/tests/ExecuteNetwork/ExecuteNetwork.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetwork.cpp
@@ -35,8 +35,39 @@
#endif
#include <future>
+
+/**
+ * Given a measured duration and a threshold time tell the user whether we succeeded or not.
+ *
+ * @param duration the measured inference duration.
+ * @param thresholdTime the threshold time in milliseconds.
+ * @return false if the measured time exceeded the threshold.
+ */
+bool CheckInferenceTimeThreshold(const std::chrono::duration<double, std::milli>& duration,
+ const double& thresholdTime)
+{
+ ARMNN_LOG(info) << "\nInference time: " << std::setprecision(2)
+ << std::fixed << duration.count() << " ms\n";
+ // If thresholdTime == 0.0 (default), then it hasn't been supplied at command line
+ if (thresholdTime != 0.0)
+ {
+ ARMNN_LOG(info) << "Threshold time: " << std::setprecision(2)
+ << std::fixed << thresholdTime << " ms";
+ auto thresholdMinusInference = thresholdTime - duration.count();
+ ARMNN_LOG(info) << "Threshold time - Inference time: " << std::setprecision(2)
+ << std::fixed << thresholdMinusInference << " ms" << "\n";
+ if (thresholdMinusInference < 0)
+ {
+ std::string errorMessage = "Elapsed inference time is greater than provided threshold time.";
+ ARMNN_LOG(fatal) << errorMessage;
+ return false;
+ }
+ }
+ return true;
+}
+
#if defined(ARMNN_TFLITE_DELEGATE)
-int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params,
+int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params, const armnn::IRuntime::CreationOptions runtimeOptions,
const std::shared_ptr<armnn::IRuntime>& runtime = nullptr)
{
using namespace tflite;
@@ -54,7 +85,10 @@
if (params.m_TfLiteExecutor == ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteDelegate)
{
// Create the Armnn Delegate
- armnnDelegate::DelegateOptions delegateOptions(params.m_ComputeDevices);
+ // Populate a DelegateOptions from the ExecuteNetworkParams.
+ armnnDelegate::DelegateOptions delegateOptions = params.ToDelegateOptions();
+ delegateOptions.SetExternalProfilingParams(runtimeOptions.m_ProfilingOptions);
+
std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
armnnDelegate::TfLiteArmnnDelegateDelete);
@@ -71,18 +105,11 @@
std::cout << "Running on TfLite without ArmNN delegate\n";
}
-
- std::vector<std::string> inputBindings;
- for (const std::string& inputName: params.m_InputNames)
- {
- inputBindings.push_back(inputName);
- }
-
armnn::Optional<std::string> dataFile = params.m_GenerateTensorData
? armnn::EmptyOptional()
: armnn::MakeOptional<std::string>(params.m_InputTensorDataFilePaths[0]);
- const size_t numInputs = inputBindings.size();
+ const size_t numInputs = params.m_InputNames.size();
for(unsigned int inputIndex = 0; inputIndex < numInputs; ++inputIndex)
{
@@ -212,15 +239,36 @@
for (size_t x = 0; x < params.m_Iterations; x++)
{
+ // Start timer to record inference time in milliseconds.
+ const auto start_time = armnn::GetTimeNow();
// Run the inference
status = tfLiteInterpreter->Invoke();
+ const auto duration = armnn::GetTimeDuration(start_time);
// Print out the output
for (unsigned int outputIndex = 0; outputIndex < params.m_OutputNames.size(); ++outputIndex)
{
auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[outputIndex];
TfLiteIntArray* outputDims = tfLiteInterpreter->tensor(tfLiteDelegateOutputId)->dims;
-
+ // If we've been asked to write to a file then set a file output stream. Otherwise use stdout.
+ FILE* outputTensorFile = stdout;
+ if (!params.m_OutputTensorFiles.empty())
+ {
+ outputTensorFile = fopen(params.m_OutputTensorFiles[outputIndex].c_str(), "w");
+ if (outputTensorFile == NULL)
+ {
+ ARMNN_LOG(fatal) << "Specified output tensor file, \"" <<
+ params.m_OutputTensorFiles[outputIndex] <<
+ "\", cannot be created. Defaulting to stdout. " <<
+ "Error was: " << std::strerror(errno);
+ outputTensorFile = stdout;
+ }
+ else
+ {
+ ARMNN_LOG(info) << "Writing output " << outputIndex << "' of iteration: " << x+1 << " to file: '"
+ << params.m_OutputTensorFiles[outputIndex] << "'";
+ }
+ }
long outputSize = 1;
for (unsigned int dim = 0; dim < static_cast<unsigned int>(outputDims->size); ++dim)
{
@@ -242,7 +290,7 @@
{
for (int i = 0; i < outputSize; ++i)
{
- printf("%f ", tfLiteDelageOutputData[i]);
+ fprintf(outputTensorFile, "%f ", tfLiteDelageOutputData[i]);
}
}
}
@@ -260,7 +308,7 @@
{
for (int i = 0; i < outputSize; ++i)
{
- printf("%d ", tfLiteDelageOutputData[i]);
+ fprintf(outputTensorFile, "%d ", tfLiteDelageOutputData[i]);
}
}
}
@@ -278,7 +326,7 @@
{
for (int i = 0; i < outputSize; ++i)
{
- printf("%d ", tfLiteDelageOutputData[i]);
+ fprintf(outputTensorFile, "%d ", tfLiteDelageOutputData[i]);
}
}
}
@@ -297,7 +345,7 @@
{
for (int i = 0; i < outputSize; ++i)
{
- printf("%u ", tfLiteDelageOutputData[i]);
+ fprintf(outputTensorFile, "%u ", tfLiteDelageOutputData[i]);
}
}
}
@@ -310,6 +358,7 @@
}
std::cout << std::endl;
}
+ CheckInferenceTimeThreshold(duration, params.m_ThresholdTime);
}
return status;
@@ -628,24 +677,7 @@
mapbox::util::apply_visitor(printer, inferenceOutputMap.at(cb->GetInferenceId())[i]);
}
- ARMNN_LOG(info) << "\nInference time: " << std::setprecision(2)
- << std::fixed << inferenceDuration.count() << " ms\n";
-
- // If thresholdTime == 0.0 (default), then it hasn't been supplied at command line
- if (params.m_ThresholdTime != 0.0)
- {
- ARMNN_LOG(info) << "Threshold time: " << std::setprecision(2)
- << std::fixed << params.m_ThresholdTime << " ms";
- auto thresholdMinusInference =
- params.m_ThresholdTime - duration<double, std::milli>(inferenceDuration).count();
- ARMNN_LOG(info) << "Threshold time - Inference time: " << std::setprecision(2)
- << std::fixed << thresholdMinusInference << " ms" << "\n";
-
- if (thresholdMinusInference < 0)
- {
- ARMNN_LOG(fatal) << "Elapsed inference time is greater than provided threshold time. \n";
- }
- }
+ CheckInferenceTimeThreshold(inferenceDuration, params.m_ThresholdTime);
++j;
}
//print duration difference between overallStartTime and overallEndTime
@@ -739,26 +771,8 @@
!params.m_DontPrintOutputs);
mapbox::util::apply_visitor(printer, outputs[j][i]);
}
-
- ARMNN_LOG(info) << "\nInference time: " << std::setprecision(2)
- << std::fixed << inferenceDuration.count() << " ms\n";
-
- // If thresholdTime == 0.0 (default), then it hasn't been supplied at command line
- if (params.m_ThresholdTime != 0.0)
- {
- ARMNN_LOG(info) << "Threshold time: " << std::setprecision(2)
- << std::fixed << params.m_ThresholdTime << " ms";
- auto thresholdMinusInference = params.m_ThresholdTime - inferenceDuration.count();
- ARMNN_LOG(info) << "Threshold time - Inference time: " << std::setprecision(2)
- << std::fixed << thresholdMinusInference << " ms" << "\n";
-
- if (thresholdMinusInference < 0)
- {
- ARMNN_LOG(fatal) << "Elapsed inference time is greater than provided threshold time. \n";
- }
- }
+ CheckInferenceTimeThreshold(inferenceDuration, params.m_ThresholdTime);
ARMNN_LOG(info) << "Asynchronous Execution is finished for Inference ID: " << inferenceID << " \n";
-
}
// finish timer
const auto duration = armnn::GetTimeDuration(start_time);
@@ -781,7 +795,6 @@
return EXIT_SUCCESS;
}
-
// MAIN
int main(int argc, const char* argv[])
{
@@ -853,7 +866,7 @@
ExecuteNetworkParams::TfLiteExecutor::TfliteInterpreter)
{
#if defined(ARMNN_TF_LITE_DELEGATE)
- return TfLiteDelegateMainImpl(ProgramOptions.m_ExNetParams, runtime);
+ return TfLiteDelegateMainImpl(ProgramOptions.m_ExNetParams, ProgramOptions.m_RuntimeOptions, runtime);
#else
ARMNN_LOG(fatal) << "Not built with Arm NN Tensorflow-Lite delegate support.";
return EXIT_FAILURE;