Remove ov::core dependency after CPU CompiledModel constructed (#17156)

* fx repr

* remove isNewApi

* add cisLegacyApi

* remove isNewApi

* fix logic

* add test case

* remove comment

* fix bug

* add configuration

* skip in template

* skip failed case

* skip AUTO and MULTI to test

* resolve conflicts

* fix confilcts

* skip AUTO and MULTI to test

* template on

* Revert "template on"

This reverts commit d82a5a4964.

* get log

* add tmp core

* reset to test

* Revert "reset to test"

This reverts commit 7a39d4e24b.

* try to push

* use createCoreWithTemplate()

* remove AUTO and MULTI in skip_config

* Revert "remove AUTO and MULTI in skip_config"

This reverts commit d42420590f.

* fix confilcts

* fix conflicts

* remove AUTO and MULTI in skip config

* fix confilcts

* remove isLegacyAPI

* remove useless code

---------

Co-authored-by: Chen Peter <peter.chen@intel.com>

src/plugins/intel_cpu/src/config.h

@@ -82,7 +82,7 @@ struct Config {
 
     std::map<std::string, std::string> _config;
 
-    bool isNewApi = true;
+    bool isLegacyApi = false;
 
 #ifdef CPU_DEBUG_CAPS
     DebugCapsConfig debugCaps;

src/plugins/intel_cpu/src/exec_network.cpp

@@ -79,8 +79,12 @@ ExecNetwork::ExecNetwork(const InferenceEngine::CNNNetwork &network,
     }
     bool isFloatModel = !ov::op::util::has_op_with_type<ngraph::op::FakeQuantize>(function);
 
-    _cfg.isNewApi = !isLegacyAPI();
     _mutex = std::make_shared<std::mutex>();
+    const auto& core = _plugin->GetCore();
+    if (!core)
+        IE_THROW() << "Unable to get API version. Core is unavailable";
+    _cfg.isLegacyApi = !core->isNewAPI();
+
 
     if (cfg.exclusiveAsyncRequests) {
         // special case when all InferRequests are muxed into a single queue
@@ -209,14 +213,6 @@ std::shared_ptr<ngraph::Function> ExecNetwork::GetExecGraphInfo() {
     return GetGraph()._graph.dump();
 }
 
-bool ExecNetwork::isLegacyAPI() const {
-    const auto& core = _plugin->GetCore();
-    if (!core)
-        IE_THROW() << "Unable to get API version. Core is unavailable";
-
-    return !core->isNewAPI();
-}
-
 Parameter ExecNetwork::GetConfigLegacy(const std::string &name) const {
     if (_graphs.empty())
         IE_THROW() << "No graph was found";
@@ -279,7 +275,7 @@ InferenceEngine::Parameter ExecNetwork::GetMetric(const std::string &name) const
     const auto& graph = graphLock._graph;
     const auto& config = graph.getConfig();
 
-    if (isLegacyAPI()) {
+    if (_cfg.isLegacyApi) {
         return GetMetricLegacy(name, graph);
     }
 

src/plugins/intel_cpu/src/exec_network.h

@@ -76,8 +76,6 @@ protected:
      */
     GraphGuard::Lock GetGraph() const;
 
-    bool isLegacyAPI() const;
-
     InferenceEngine::Parameter GetConfigLegacy(const std::string &name) const;
 
     InferenceEngine::Parameter GetMetricLegacy(const std::string &name, const GraphGuard& graph) const;

src/plugins/intel_cpu/src/graph.cpp

@@ -961,9 +961,9 @@ void Graph::PullOutputData(BlobMap &out) {
         auto srcPrec = actualDesc.getPrecision();
         auto dstPrec = expectedDesc.getPrecision();
 
-        if (getConfig().isNewApi && srcPrec == dstPrec && ext_blob->byteSize() != intr_blob.GetSize())
-                IE_THROW() << "Output blob byte size is not equal network output byte size ("
-                                   << ext_blob->byteSize() << "!=" << intr_blob.GetSize() << ").";
+        if (!getConfig().isLegacyApi && srcPrec == dstPrec && ext_blob->byteSize() != intr_blob.GetSize())
+            IE_THROW() << "Output blob byte size is not equal network output byte size (" << ext_blob->byteSize()
+                       << "!=" << intr_blob.GetSize() << ").";
 
         void *ext_blob_ptr = ext_blob->buffer();
         void *intr_blob_ptr = intr_blob.GetData();

src/plugins/template/tests/functional/skip_tests_config.cpp

@@ -139,4 +139,4 @@ std::vector<std::string> disabledTestPatterns() {
         R"(.*ReferenceConversionLayerTest.CompareWithHardcodedRefs/conversionType=(Convert|ConvertLike)_shape=.*_iType=(f16|f32|bf16)_oType=u4.*)");
 #endif
     return retVector;
-}
+}

src/tests/functional/plugin/shared/include/behavior/compiled_model/compiled_model_base.hpp

@@ -157,7 +157,83 @@ TEST_P(OVCompiledModelBaseTest, canCompileModelFromMemory) {
             </edges>
         </net>
         )V0G0N";
-    EXPECT_NO_THROW(auto execNet = core->compile_model(model, ov::Tensor(), target_device, configuration));
+    EXPECT_NO_THROW(auto execNet = core ->compile_model(model, ov::Tensor(), target_device, configuration));
+}
+
+TEST_P(OVCompiledModelBaseTest, canCompileModelwithBrace) {
+ std::string model = R"V0G0N(
+        <net name="Network" version="10">
+            <layers>
+                <layer name="in1" type="Parameter" id="0" version="opset8">
+                    <data element_type="f16" shape="1,3,22,22"/>
+                    <output>
+                        <port id="0" precision="FP16" names="data1">
+                            <dim>1</dim>
+                            <dim>3</dim>
+                            <dim>22</dim>
+                            <dim>22</dim>
+                        </port>
+                    </output>
+                </layer>
+                <layer name="in2" type="Parameter" id="1" version="opset8">
+                    <data element_type="f16" shape="1,3,22,22"/>
+                    <output>
+                        <port id="0" precision="FP16" names="data2">
+                            <dim>1</dim>
+                            <dim>3</dim>
+                            <dim>22</dim>
+                            <dim>22</dim>
+                        </port>
+                    </output>
+                </layer>
+                <layer name="concat" id="2" type="Concat" version="opset8">
+                    <input>
+                        <port id="0" precision="FP16">
+                            <dim>1</dim>
+                            <dim>3</dim>
+                            <dim>22</dim>
+                            <dim>22</dim>
+                        </port>
+                        <port id="1"  precision="FP16">
+                            <dim>1</dim>
+                            <dim>3</dim>
+                            <dim>22</dim>
+                            <dim>22</dim>
+                        </port>
+                    </input>
+                    <output>
+                        <port id="2" precision="FP16" names="r">
+                            <dim>1</dim>
+                            <dim>6</dim>
+                            <dim>22</dim>
+                            <dim>22</dim>
+                        </port>
+                    </output>
+                </layer>
+                <layer name="output" type="Result" id="3" version="opset8">
+                    <input>
+                        <port id="0" precision="FP16">
+                            <dim>1</dim>
+                            <dim>6</dim>
+                            <dim>22</dim>
+                            <dim>22</dim>
+                        </port>
+                    </input>
+                </layer>
+            </layers>
+            <edges>
+                <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
+                <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
+                <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
+            </edges>
+        </net>
+        )V0G0N";
+    ov::CompiledModel compiled_model;
+    {
+        ov::Core tmp_core = createCoreWithTemplate();
+        compiled_model = tmp_core.compile_model(model, ov::Tensor(), target_device, configuration);
+    }
+    EXPECT_NO_THROW(compiled_model.get_property(ov::optimal_number_of_infer_requests));
 }
 
 TEST(OVCompiledModelBaseTest, canCompileModelToDefaultDevice) {