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Benchmark_app: Command line args processing is modified to use both tensor and corresponding node names (#9968)

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* Node/name conversions

* stylefix
This commit is contained in:
Fedor Zharinov 2022-02-01 16:05:00 +03:00 committed by GitHub
parent 6845392aa6
commit c848e55f5e
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 78 additions and 4 deletions
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7
samples/cpp/benchmark_app/main.cpp
View File

@ -397,6 +397,8 @@ int main(int argc, char* argv[]) {
if (statistics)
statistics->add_parameters(StatisticsReport::Category::EXECUTION_RESULTS,
{{"load network time (ms)", duration_ms}});
convert_io_names_in_map(inputFiles, compiledModel.inputs());
app_inputs_info = get_inputs_info(FLAGS_shape,
FLAGS_layout,
batchSize,
@ -432,6 +434,7 @@ int main(int argc, char* argv[]) {
// ----------------- 5. Resizing network to match image sizes and given
// batch ----------------------------------
next_step();
convert_io_names_in_map(inputFiles, std::const_pointer_cast<const ov::Model>(model)->inputs());
// Parse input shapes if specified
bool reshape = false;
app_inputs_info = get_inputs_info(FLAGS_shape,
@ -465,6 +468,9 @@ int main(int argc, char* argv[]) {
std::map<std::string, std::string> user_precisions_map;
if (!FLAGS_iop.empty()) {
user_precisions_map = parseArgMap(FLAGS_iop);
convert_io_names_in_map(user_precisions_map,
std::const_pointer_cast<const ov::Model>(model)->inputs(),
std::const_pointer_cast<const ov::Model>(model)->outputs());
}
const auto input_precision = FLAGS_ip.empty() ? ov::element::undefined : getPrecision2(FLAGS_ip);
@ -583,6 +589,7 @@ int main(int argc, char* argv[]) {
statistics->add_parameters(StatisticsReport::Category::EXECUTION_RESULTS,
{{"import network time (ms)", duration_ms}});
convert_io_names_in_map(inputFiles, compiledModel.inputs());
app_inputs_info = get_inputs_info(FLAGS_shape,
FLAGS_layout,
FLAGS_b,

37
samples/cpp/benchmark_app/utils.cpp
View File

@ -353,7 +353,7 @@ std::map<std::string, std::vector<std::string>> parse_input_parameters(
input_name = search_string.substr(0, start_pos);
auto input_value = search_string.substr(start_pos + 1, end_pos - start_pos - 1);
if (!input_name.empty()) {
return_value[input_name].push_back(input_value);
return_value[parameter_name_to_tensor_name(input_name, input_info)].push_back(input_value);
} else {
for (auto& item : input_info) {
return_value[item.get_any_name()].push_back(input_value);
@ -797,3 +797,38 @@ std::vector<std::string> filter_files_by_extensions(const std::vector<std::strin
}
return filtered;
}
std::string parameter_name_to_tensor_name(const std::string& name,
const std::vector<ov::Output<const ov::Node>>& inputs_info,
const std::vector<ov::Output<const ov::Node>>& outputs_info) {
if (std::any_of(inputs_info.begin(), inputs_info.end(), [name](const ov::Output<const ov::Node>& port) {
try {
return name == port.get_any_name();
} catch (const ov::Exception&) {
return false; // Some ports might have no names - so this is workaround
}
})) {
return name;
} else if (std::any_of(outputs_info.begin(), outputs_info.end(), [name](const ov::Output<const ov::Node>& port) {
try {
return name == port.get_any_name();
} catch (const ov::Exception&) {
return false; // Some ports might have no names - so this is workaround
}
})) {
return name;
} else {
for (const auto& port : inputs_info) {
if (name == port.get_node()->get_friendly_name()) {
return port.get_any_name();
}
}
for (const auto& port : outputs_info) {
if (name == port.get_node()->get_input_node_ptr(0)->get_friendly_name()) {
return port.get_any_name();
}
}
}
throw std::runtime_error("Provided I/O name \"" + name +
"\" is not found neither in tensor names nor in nodes names.");
}

18
samples/cpp/benchmark_app/utils.hpp
View File

@ -133,3 +133,21 @@ bool is_image_file(const std::string& filePath);
bool contains_binaries(const std::vector<std::string>& filePaths);
std::vector<std::string> filter_files_by_extensions(const std::vector<std::string>& filePaths,
const std::vector<std::string>& extensions);
std::string parameter_name_to_tensor_name(
const std::string& name,
const std::vector<ov::Output<const ov::Node>>& inputs_info,
const std::vector<ov::Output<const ov::Node>>& outputs_info = std::vector<ov::Output<const ov::Node>>());
template <class T>
void convert_io_names_in_map(
T& map,
const std::vector<ov::Output<const ov::Node>>& inputs_info,
const std::vector<ov::Output<const ov::Node>>& outputs_info = std::vector<ov::Output<const ov::Node>>()) {
T new_map;
for (auto& item : map) {
new_map[item.first == "" ? "" : parameter_name_to_tensor_name(item.first, inputs_info, outputs_info)] =
std::move(item.second);
}
map = new_map;
}

20
samples/cpp/common/utils/src/args_helper.cpp
View File

@ -251,13 +251,27 @@ bool isMatchLayoutToDims(InferenceEngine::Layout layout, size_t dimension) {
void printInputAndOutputsInfoShort(const ov::Model& network) {
std::cout << "Network inputs:" << std::endl;
for (auto&& input : network.inputs()) {
std::cout << " " << input.get_any_name() << " : " << input.get_element_type() << " / "
<< ov::layout::get_layout(input).to_string() << std::endl;
std::cout << " " << input.get_any_name() << " (node: " << input.get_node()->get_friendly_name()
<< ") : " << input.get_element_type() << " / " << ov::layout::get_layout(input).to_string()
<< std::endl;
}
std::cout << "Network outputs:" << std::endl;
for (auto&& output : network.outputs()) {
std::cout << " " << output.get_any_name() << " : " << output.get_element_type() << " / "
std::string out_name = "***NO_NAME***";
std::string node_name = "***NO_NAME***";
// Workaround for "tensor has no name" issue
try {
out_name = output.get_any_name();
} catch (const ov::Exception&) {
}
try {
node_name = output.get_node()->get_input_node_ptr(0)->get_friendly_name();
} catch (const ov::Exception&) {
}
std::cout << " " << out_name << " (node: " << node_name << ") : " << output.get_element_type() << " / "
<< ov::layout::get_layout(output).to_string() << std::endl;
}
}