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

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

modules/gapi/include/opencv2/gapi/infer/ie.hpp

@@ -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; }

modules/gapi/src/backends/ie/giebackend.cpp

@@ -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);
         }
 

modules/gapi/test/infer/gapi_infer_ie_test.cpp

@@ -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