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Benchmarkapp: Added processing of inputs/outputs by index (#9703)

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* Added processing of inputs/outputs by index

* fix

* All tensor's get_friendly_name are replaced with get_any_name

* stylefix
This commit is contained in:
Fedor Zharinov 2022-01-18 13:40:54 +03:00 committed by GitHub
parent 96e7ee58e1
commit 14f8614da6
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3 changed files with 57 additions and 39 deletions
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75
samples/cpp/benchmark_app/main.cpp
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@ -472,39 +472,58 @@ int main(int argc, char* argv[]) {
const auto input_precision = FLAGS_ip.empty() ? ov::element::undefined : getPrecision2(FLAGS_ip); const auto input_precision = FLAGS_ip.empty() ? ov::element::undefined : getPrecision2(FLAGS_ip);
const auto output_precision = FLAGS_op.empty() ? ov::element::undefined : getPrecision2(FLAGS_op); const auto output_precision = FLAGS_op.empty() ? ov::element::undefined : getPrecision2(FLAGS_op);
for (auto& item : model->inputs()) { const auto& inputs = model->inputs();
// if precision for input set by user, then set it to app_inputs for (int i = 0; i < inputs.size(); i++) {
const auto& name = item.get_any_name(); const auto& item = inputs[i];
if (user_precisions_map.count(name)) { auto iop_precision = ov::element::undefined;
const auto precision = getPrecision2(user_precisions_map.at(name)); auto type_to_set = ov::element::undefined;
for (auto& info : app_inputs_info) { std::string name;
info.at(name).type = precision; try {
} // Some tensors might have no names, get_any_name will throw exception in that case.
} else if (input_precision != ov::element::undefined) { // -iop option will not work for those tensors.
for (auto& info : app_inputs_info) { name = item.get_any_name();
info.at(name).type = input_precision; iop_precision = getPrecision2(user_precisions_map.at(item.get_any_name()));
} } catch (...) {
} else if (app_inputs_info[0].at(name).isImage()) {
// image input, set U8
for (auto& info : app_inputs_info) {
info.at(name).type = ov::element::u8;
}
} }
auto& in = preproc.input(name);
in.tensor().set_element_type(app_inputs_info[0].at(name).type);
// Explicitly set inputs layout. if (iop_precision != ov::element::undefined) {
in.model().set_layout(app_inputs_info[0].at(name).layout); type_to_set = iop_precision;
} else if (input_precision != ov::element::undefined) {
type_to_set = input_precision;
} else if (!name.empty() && app_inputs_info[0].at(name).isImage()) {
// image input, set U8
type_to_set = ov::element::u8;
}
auto& in = preproc.input(item.get_index());
if (type_to_set != ov::element::undefined) {
in.tensor().set_element_type(type_to_set);
if (!name.empty()) {
for (auto& info : app_inputs_info) {
info.at(name).type = type_to_set;
}
}
// Explicitly set inputs layout.
in.model().set_layout(app_inputs_info[0].at(name).layout);
}
} }
for (auto& item : model->outputs()) { const auto& outs = model->outputs();
// if precision for input set by user, then set it to app_inputs for (int i = 0; i < outs.size(); i++) {
const auto& name = item.get_any_name(); const auto& item = outs[i];
if (user_precisions_map.count(name)) { auto iop_precision = ov::element::undefined;
const auto precision = getPrecision2(user_precisions_map.at(name)); try {
preproc.output(name).tensor().set_element_type(precision); // Some tensors might have no names, get_any_name will throw exception in that case.
// -iop option will not work for those tensors.
iop_precision = getPrecision2(user_precisions_map.at(item.get_any_name()));
} catch (...) {
}
if (iop_precision != ov::element::undefined) {
preproc.output(i).tensor().set_element_type(iop_precision);
} else if (output_precision != ov::element::undefined) { } else if (output_precision != ov::element::undefined) {
preproc.output(name).tensor().set_element_type(output_precision); preproc.output(i).tensor().set_element_type(output_precision);
} }
} }

7
samples/cpp/benchmark_app/utils.cpp
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@ -477,7 +477,7 @@ std::vector<benchmark_app::InputsInfo> getInputsInfo(const std::string& shape_st
} }
if (info_maps.empty()) { // Show warnings only for 1st test case config, as for other test cases if (info_maps.empty()) { // Show warnings only for 1st test case config, as for other test cases
// they will be the same // they will be the same
slog::warn << item.get_node()->get_friendly_name() << ": layout is not set explicitly" slog::warn << item.get_any_name() << ": layout is not set explicitly"
<< (newLayout != "" ? std::string(", so it is defaulted to ") + newLayout : "") << (newLayout != "" ? std::string(", so it is defaulted to ") + newLayout : "")
<< ". It is STRONGLY recommended to set layout manually to avoid further issues." << ". It is STRONGLY recommended to set layout manually to avoid further issues."
<< slog::endl; << slog::endl;
@ -563,8 +563,7 @@ std::vector<benchmark_app::InputsInfo> getInputsInfo(const std::string& shape_st
})) { })) {
throw std::logic_error("Not enough information in shape and image to determine tensor shape " throw std::logic_error("Not enough information in shape and image to determine tensor shape "
"automatically autmatically. Input: " + "automatically autmatically. Input: " +
item.get_node()->get_friendly_name() + item.get_any_name() + ", File name: " + namesVector[fileIdx - 1]);
", File name: " + namesVector[fileIdx - 1]);
} }
} else if (info.partialShape.is_static()) { } else if (info.partialShape.is_static()) {
@ -595,7 +594,7 @@ std::vector<benchmark_app::InputsInfo> getInputsInfo(const std::string& shape_st
reshape_required = true; reshape_required = true;
} }
} else { } else {
slog::warn << "Input '" << item.get_node()->get_friendly_name() slog::warn << "Input '" << item.get_any_name()
<< "' doesn't have batch dimension in layout. -b option will be ignored for this input." << "' doesn't have batch dimension in layout. -b option will be ignored for this input."
<< slog::endl; << slog::endl;
} }

14
samples/cpp/common/utils/src/args_helper.cpp
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@ -250,15 +250,15 @@ bool isMatchLayoutToDims(InferenceEngine::Layout layout, size_t dimension) {
void printInputAndOutputsInfoShort(const ov::Model& network) { void printInputAndOutputsInfoShort(const ov::Model& network) {
std::cout << "Network inputs:" << std::endl; std::cout << "Network inputs:" << std::endl;
for (auto&& param : network.get_parameters()) { for (auto&& input : network.inputs()) {
auto l = param->get_layout(); std::cout << " " << input.get_any_name() << " : " << input.get_element_type() << " / "
std::cout << " " << param->get_friendly_name() << " : " << param->get_element_type() << " / " << ov::layout::get_layout(input).to_string() << std::endl;
<< param->get_layout().to_string() << std::endl;
} }
std::cout << "Network outputs:" << std::endl; std::cout << "Network outputs:" << std::endl;
for (auto&& result : network.get_results()) { for (auto&& output : network.outputs()) {
std::cout << " " << result->get_friendly_name() << " : " << result->get_element_type() << " / " std::cout << " " << output.get_any_name() << " : " << output.get_element_type() << " / "
<< result->get_layout().to_string() << std::endl; << ov::layout::get_layout(output).to_string() << std::endl;
} }
} }