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Merge pull request #18701 from TolyaTalamanov:at/introduce-config-for-ie-params

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Expand ie::Params to support config

* Add config to IE params

* Add test

* Remove comments from tests

* Rename to pluginConfig

* Add one more overloads for pluginConfig

* Add more tests
This commit is contained in:
Anatoliy Talamanov 2020-11-03 20:47:05 +03:00 committed by GitHub
parent 6df92b3bca
commit 2a3cdba724
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 135 additions and 5 deletions
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34
modules/gapi/include/opencv2/gapi/infer/ie.hpp
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@ -11,6 +11,7 @@
#include <string>
#include <array>
#include <tuple> // tuple, tuple_size
#include <map>
#include <opencv2/gapi/opencv_includes.hpp>
#include <opencv2/gapi/util/any.hpp>
@ -42,6 +43,8 @@ enum class TraitAs: int
IMAGE //!< G-API traits an associated cv::Mat as an image so creates an "image" blob (NCHW/NHWC, etc)
};
using IEConfig = std::map<std::string, std::string>;
namespace detail {
struct ParamDesc {
std::string model_path;
@ -63,6 +66,7 @@ namespace detail {
enum class Kind { Load, Import };
Kind kind;
bool is_generic;
IEConfig config;
};
} // namespace detail
@ -86,7 +90,8 @@ public:
, std::tuple_size<typename Net::InArgs>::value // num_in
, std::tuple_size<typename Net::OutArgs>::value // num_out
, detail::ParamDesc::Kind::Load
, false} {
, false
, {}} {
};
Params(const std::string &model,
@ -95,7 +100,8 @@ public:
, std::tuple_size<typename Net::InArgs>::value // num_in
, std::tuple_size<typename Net::OutArgs>::value // num_out
, detail::ParamDesc::Kind::Import
, false} {
, false
, {}} {
};
Params<Net>& cfgInputLayers(const typename PortCfg<Net>::In &ll) {
@ -121,6 +127,16 @@ public:
return *this;
}
Params& pluginConfig(IEConfig&& cfg) {
desc.config = std::move(cfg);
return *this;
}
Params& pluginConfig(const IEConfig& cfg) {
desc.config = cfg;
return *this;
}
// BEGIN(G-API's network parametrization API)
GBackend backend() const { return cv::gapi::ie::backend(); }
std::string tag() const { return Net::tag(); }
@ -138,15 +154,25 @@ public:
const std::string &model,
const std::string &weights,
const std::string &device)
: desc{ model, weights, device, {}, {}, {}, 0u, 0u, detail::ParamDesc::Kind::Load, true}, m_tag(tag) {
: desc{ model, weights, device, {}, {}, {}, 0u, 0u, detail::ParamDesc::Kind::Load, true, {}}, m_tag(tag) {
};
Params(const std::string &tag,
const std::string &model,
const std::string &device)
: desc{ model, {}, device, {}, {}, {}, 0u, 0u, detail::ParamDesc::Kind::Import, true}, m_tag(tag) {
: desc{ model, {}, device, {}, {}, {}, 0u, 0u, detail::ParamDesc::Kind::Import, true, {}}, m_tag(tag) {
};
Params& pluginConfig(IEConfig&& cfg) {
desc.config = std::move(cfg);
return *this;
}
Params& pluginConfig(const IEConfig& cfg) {
desc.config = cfg;
return *this;
}
// BEGIN(G-API's network parametrization API)
GBackend backend() const { return cv::gapi::ie::backend(); }
std::string tag() const { return m_tag; }

4
modules/gapi/src/backends/ie/giebackend.cpp
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@ -185,7 +185,8 @@ struct IEUnit {
inputs = net.getInputsInfo();
outputs = net.getOutputsInfo();
} else if (params.kind == cv::gapi::ie::detail::ParamDesc::Kind::Import) {
this_plugin = cv::gimpl::ie::wrap::getPlugin(params);
this_plugin = cv::gimpl::ie::wrap::getPlugin(params);
this_plugin.SetConfig(params.config);
this_network = cv::gimpl::ie::wrap::importNetwork(this_plugin, params);
// FIXME: ICNNetwork returns InputsDataMap/OutputsDataMap,
// but ExecutableNetwork returns ConstInputsDataMap/ConstOutputsDataMap
@ -225,6 +226,7 @@ struct IEUnit {
// FIXME: In case importNetwork for fill inputs/outputs need to obtain ExecutableNetwork, but
// for loadNetwork they can be obtained by using readNetwork
non_const_this->this_plugin = cv::gimpl::ie::wrap::getPlugin(params);
non_const_this->this_plugin.SetConfig(params.config);
non_const_this->this_network = cv::gimpl::ie::wrap::loadNetwork(non_const_this->this_plugin, net, params);
}

102
modules/gapi/test/infer/gapi_infer_ie_test.cpp
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@ -403,6 +403,108 @@ TEST(TestAgeGenderIE, GenericInfer)
normAssert(cv::gapi::ie::util::to_ocv(ie_gender), gapi_gender, "Test gender output");
}
TEST(TestAgeGenderIE, InvalidConfigGeneric)
{
initDLDTDataPath();
std::string model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
std::string weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
std::string device_id = "CPU";
// Configure & run G-API
cv::GMat in;
GInferInputs inputs;
inputs["data"] = in;
auto outputs = cv::gapi::infer<cv::gapi::Generic>("age-gender-generic", inputs);
auto age = outputs.at("age_conv3");
auto gender = outputs.at("prob");
cv::GComputation comp(cv::GIn(in), cv::GOut(age, gender));
auto pp = cv::gapi::ie::Params<cv::gapi::Generic>{"age-gender-generic",
model_path,
weights_path,
device_id}.pluginConfig({{"unsupported_config", "some_value"}});
EXPECT_ANY_THROW(comp.compile(cv::GMatDesc{CV_8U,3,cv::Size{320, 240}},
cv::compile_args(cv::gapi::networks(pp))));
}
TEST(TestAgeGenderIE, CPUConfigGeneric)
{
initDLDTDataPath();
std::string model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
std::string weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
std::string device_id = "CPU";
// Configure & run G-API
cv::GMat in;
GInferInputs inputs;
inputs["data"] = in;
auto outputs = cv::gapi::infer<cv::gapi::Generic>("age-gender-generic", inputs);
auto age = outputs.at("age_conv3");
auto gender = outputs.at("prob");
cv::GComputation comp(cv::GIn(in), cv::GOut(age, gender));
auto pp = cv::gapi::ie::Params<cv::gapi::Generic>{"age-gender-generic",
model_path,
weights_path,
device_id}.pluginConfig({{"ENFORCE_BF16", "NO"}});
EXPECT_NO_THROW(comp.compile(cv::GMatDesc{CV_8U,3,cv::Size{320, 240}},
cv::compile_args(cv::gapi::networks(pp))));
}
TEST(TestAgeGenderIE, InvalidConfig)
{
initDLDTDataPath();
std::string model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
std::string weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
std::string device_id = "CPU";
using AGInfo = std::tuple<cv::GMat, cv::GMat>;
G_API_NET(AgeGender, <AGInfo(cv::GMat)>, "test-age-gender");
cv::GMat in;
cv::GMat age, gender;
std::tie(age, gender) = cv::gapi::infer<AgeGender>(in);
cv::GComputation comp(cv::GIn(in), cv::GOut(age, gender));
auto pp = cv::gapi::ie::Params<AgeGender> {
model_path, weights_path, device_id
}.cfgOutputLayers({ "age_conv3", "prob" }).pluginConfig({{"unsupported_config", "some_value"}});
EXPECT_ANY_THROW(comp.compile(cv::GMatDesc{CV_8U,3,cv::Size{320, 240}},
cv::compile_args(cv::gapi::networks(pp))));
}
TEST(TestAgeGenderIE, CPUConfig)
{
initDLDTDataPath();
std::string model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
std::string weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
std::string device_id = "CPU";
using AGInfo = std::tuple<cv::GMat, cv::GMat>;
G_API_NET(AgeGender, <AGInfo(cv::GMat)>, "test-age-gender");
cv::GMat in;
cv::GMat age, gender;
std::tie(age, gender) = cv::gapi::infer<AgeGender>(in);
cv::GComputation comp(cv::GIn(in), cv::GOut(age, gender));
auto pp = cv::gapi::ie::Params<AgeGender> {
model_path, weights_path, device_id
}.cfgOutputLayers({ "age_conv3", "prob" }).pluginConfig({{"ENFORCE_BF16", "NO"}});
EXPECT_NO_THROW(comp.compile(cv::GMatDesc{CV_8U,3,cv::Size{320, 240}},
cv::compile_args(cv::gapi::networks(pp))));
}
} // namespace opencv_test
#endif // HAVE_INF_ENGINE