- elementwise Add mkldnn support in cpu emitter

src/ngraph/runtime/cpu/cpu_emitter.cpp

@@ -172,13 +172,68 @@ namespace ngraph
                        << ", " << args[1].get_size() << ", 1>, Eigen::Unaligned> arg1("
                        << args[1].get_name() << ");\n";
                 writer << "out = arg0 + arg1;\n";
-#else
-                writer << "#pragma omp parallel for\n";
-                writer << "for (size_t i = 0; i < " << out[0].get_size() << "; i++)\n";
-                writer << "{\n";
-                writer << "    " << out[0].get_name() << "[i] = " << args[0].get_name() << "[i] + "
-                       << args[1].get_name() << "[i];\n";
-                writer << "}\n";
+#else   
+                if (args[0].get_element_type() == element::f32 && args[1].get_element_type() == element::f32)
+                {
+                    auto input0_size_1d = 1;
+                    auto input1_size_1d = 1;
+                    auto result_size_1d = 1;
+                    auto src_size = args[0].get_shape().size();
+
+                    for (size_t i=0; i< src_size; i++)
+                    {
+                        input0_size_1d *= args[0].get_shape()[i];
+                        input1_size_1d *= args[1].get_shape()[i];
+                        result_size_1d *= out[0].get_shape()[i];
+                    }
+                    const string& et = get_mkldnn_data_type(args[0].get_element_type().c_type_string());
+
+                    // Bind to CPU engine
+                    writer << "engine cpu_engine = engine(engine::cpu, 0);\n";
+
+                    writer << "std::vector<float>scale_vector(2, 1);\n";
+                    writer << "std::vector<memory::primitive_desc> inputs_pd;\n";
+                    writer << "std::vector<memory::primitive::at> inputs_primitive;\n";
+
+                    // memory desc for inputs
+                    writer << "memory::desc input0_data_desc = memory::desc({" << input0_size_1d
+                           << "}, " << et << ", memory::format::x);\n";
+                    writer << "memory::desc input1_data_desc = memory::desc({" << input1_size_1d
+                           << "}, " << et << ", memory::format::x);\n";
+                    writer << "memory::desc result_desc = memory::desc({" << result_size_1d
+                           << "}, " << et << ", memory::format::x);\n";
+                    // memory for the user data
+                    writer << "memory input0_data = memory({input0_data_desc, cpu_engine}, "
+                           << args[0].get_name() << ");\n";
+                    writer << "memory input1_data = memory({input1_data_desc, cpu_engine}, "
+                           << args[1].get_name() << ");\n";
+                    writer << "memory result = memory({result_desc, cpu_engine}, "
+                           << out[0].get_name() << ");\n";
+
+                    writer << "inputs_pd.push_back(memory::primitive_desc(input0_data_desc, cpu_engine));\n";
+                    writer << "inputs_pd.push_back(memory::primitive_desc(input1_data_desc, cpu_engine));\n";
+
+                    writer << "inputs_primitive.push_back(primitive::at(input0_data));\n";
+                    writer << "inputs_primitive.push_back(primitive::at(input1_data));\n";
+
+                    // elementwise sum primtive descriptor
+                    writer << "sum::primitive_desc sum_pd = sum::primitive_desc(result_desc, scale_vector, inputs_pd);\n";
+                    // sum primitive
+                    writer << "sum sum_primitive = sum(sum_pd, inputs_primitive, result);\n";
+                    // create stream and execute
+                    writer << "stream s = stream(stream::kind::eager);\n"
+                           << "s.submit({sum_primitive}).wait();\n";
+                    
+                }
+                else
+                {
+                    writer << "#pragma omp parallel for\n";
+                    writer << "for (size_t i = 0; i < " << out[0].get_size() << "; i++)\n";
+                    writer << "{\n";
+                    writer << "    " << out[0].get_name() << "[i] = " << args[0].get_name() << "[i] + "
+                        << args[1].get_name() << "[i];\n";
+                    writer << "}\n";
+                }
 #endif
                 writer.indent--;
                 writer << "}\n";

src/ngraph/runtime/cpu/mkldnn_utils.cpp

@@ -21,6 +21,7 @@
 #include <unordered_set>
 
 #include "ngraph/node.hpp"
+#include "ngraph/ops/add.hpp"
 #include "ngraph/ops/avg_pool.hpp"
 #include "ngraph/ops/batch_norm.hpp"
 #include "ngraph/ops/convolution.hpp"
@@ -39,6 +40,7 @@ namespace ngraph
 #define TI(x) std::type_index(typeid(x))
 
                 static const std::unordered_set<std::type_index> s_op_registry{
+                    TI(ngraph::op::Add),
                     TI(ngraph::op::AvgPool),
                     TI(ngraph::op::AvgPoolBackprop),
                     TI(ngraph::op::BatchNorm),