CPU: Implement op::Dot on matrices using Eigen

src/ngraph/runtime/cpu/emitter.cpp

@@ -107,11 +107,11 @@ void Emitter::EMITTER_DECL(EmitDot)
 
     auto arg0_tensor_type =
         dynamic_pointer_cast<const TensorViewType>(arg_nodes.at(0)->get_value_type());
-    assert(nullptr != arg0_tensor_type);
+    assert(arg0_tensor_type);
 
     auto arg1_tensor_type =
         dynamic_pointer_cast<const TensorViewType>(arg_nodes.at(1)->get_value_type());
-    assert(nullptr != arg1_tensor_type);
+    assert(arg1_tensor_type);
 
     auto arg0_shape = arg0_tensor_type->get_shape();
     auto arg1_shape = arg1_tensor_type->get_shape();
@@ -152,6 +152,46 @@ void Emitter::EMITTER_DECL(EmitDot)
                        EIGEN_VECTOR_FORMAT(inputs[1].get_layout<DenseTensorViewLayout>()->get_size()) "));\n"
               "    }\n";
     }
+    else if ((arg0_shape.size() == 2) && (arg1_shape.size() == 1))
+    {
+        auto arg0_layout = inputs[0].get_layout<DenseTensorViewLayout>();
+
+        TU += "    {\n"
+              "        auto arg0 = call_frame->get_tensor_view_data<" + element_type_names[TI(arg0_element_type)] + ">(" +
+                       to_string(inputs[0].get_index()) + ");\n"
+              "        auto arg1 = call_frame->get_tensor_view_data<" + element_type_names[TI(arg0_element_type)] + ">(" +
+                       to_string(inputs[1].get_index()) + ");\n"
+              "        auto out  = call_frame->get_tensor_view_data<" + element_type_names[TI(arg0_element_type)] + ">(" +
+                       to_string(outputs[0].get_index()) + ");\n"
+              "        EigenVector<" + element_type_names[TI(arg0_element_type)] + ">(out, "
+                       EIGEN_VECTOR_FORMAT(outputs[0].get_layout<DenseTensorViewLayout>()->get_size()) ") = \n"
+              "        EigenMatrix<" + element_type_names[TI(arg0_element_type)] + ">(arg0, " +
+                       EIGEN_MATRIX_FORMAT(arg0_layout->get_shape(), arg0_layout->get_strides()) + ") * "
+              "EigenVector<" + element_type_names[TI(arg0_element_type)] + ">(arg1, "
+                       EIGEN_VECTOR_FORMAT(inputs[1].get_layout<DenseTensorViewLayout>()->get_size()) ");\n"
+              "    }\n";
+    }
+    else if ((arg0_shape.size() == 2) && (arg1_shape.size() == 2))
+    {
+        auto arg0_layout = inputs[0].get_layout<DenseTensorViewLayout>();
+        auto arg1_layout = inputs[1].get_layout<DenseTensorViewLayout>();
+        auto out_layout = outputs[0].get_layout<DenseTensorViewLayout>();
+
+        TU += "    {\n"
+              "        auto arg0 = call_frame->get_tensor_view_data<" + element_type_names[TI(arg0_element_type)] + ">(" +
+                       to_string(inputs[0].get_index()) + ");\n"
+              "        auto arg1 = call_frame->get_tensor_view_data<" + element_type_names[TI(arg0_element_type)] + ">(" +
+                       to_string(inputs[1].get_index()) + ");\n"
+              "        auto out  = call_frame->get_tensor_view_data<" + element_type_names[TI(arg0_element_type)] + ">(" +
+                       to_string(outputs[0].get_index()) + ");\n"
+              "        EigenMatrix<" + element_type_names[TI(arg0_element_type)] + ">(out, " +
+                       EIGEN_MATRIX_FORMAT(out_layout->get_shape(), out_layout->get_strides()) + ") = \n"
+              "        EigenMatrix<" + element_type_names[TI(arg0_element_type)] + ">(arg0, " +
+                       EIGEN_MATRIX_FORMAT(arg0_layout->get_shape(), arg0_layout->get_strides()) + ") * "
+              "EigenMatrix<" + element_type_names[TI(arg0_element_type)] + ">(arg1, " +
+                       EIGEN_MATRIX_FORMAT(arg1_layout->get_shape(), arg1_layout->get_strides()) + ");\n"
+              "    }\n";
+    }
     else
     {
         throw ngraph_error("Dot product for given tensors unimplemented");

test/cpu.cpp

@@ -467,14 +467,13 @@ TEST(cpu, dot_0_0)
     ASSERT_EQ((vector<float>{0}), result->get_vector());
 }
 
-/*
-TEST(execute, dot_matrix_2x0_0x2)
+TEST(cpu, dot_matrix_2x0_0x2)
 {
     auto shape_a = Shape{2, 0};
     auto shape_b = Shape{0, 2};
     auto shape_r = Shape{2, 2};
 
-    auto manager = runtime::Manager::get("NGVM");
+    auto manager = runtime::Manager::get("CPU");
     auto backend = manager->allocate_backend();
 
     auto make_external = [&]() {
@@ -500,7 +499,7 @@ TEST(execute, dot_matrix_2x0_0x2)
     ASSERT_EQ((vector<float>{0, 0, 0, 0}), result->get_vector());
 }
 
-TEST(execute, dot_matrix_0x2_2x0)
+TEST(cpu, dot_matrix_0x2_2x0)
 {
     auto shape_a = Shape{0, 2};
     auto A = make_shared<op::Parameter>(element::Float32::element_type(), shape_a);
@@ -510,7 +509,7 @@ TEST(execute, dot_matrix_0x2_2x0)
     auto rt = make_shared<TensorViewType>(element::Float32::element_type(), shape_r);
     auto f = make_shared<Function>(make_shared<op::Dot>(A, B), rt, op::Parameters{A, B});
 
-    auto manager = runtime::Manager::get("NGVM");
+    auto manager = runtime::Manager::get("CPU");
     auto external = manager->compile(f);
     auto backend = manager->allocate_backend();
     auto cf = backend->make_call_frame(external);
@@ -526,7 +525,7 @@ TEST(execute, dot_matrix_0x2_2x0)
     ASSERT_EQ((vector<float>{}), result->get_vector());
 }
 
-TEST(execute, dot_matrix_3x2_2x0)
+TEST(cpu, dot_matrix_3x2_2x0)
 {
     auto shape_a = Shape{3, 2};
     auto A = make_shared<op::Parameter>(element::Float32::element_type(), shape_a);
@@ -536,7 +535,7 @@ TEST(execute, dot_matrix_3x2_2x0)
     auto rt = make_shared<TensorViewType>(element::Float32::element_type(), shape_r);
     auto f = make_shared<Function>(make_shared<op::Dot>(A, B), rt, op::Parameters{A, B});
 
-    auto manager = runtime::Manager::get("NGVM");
+    auto manager = runtime::Manager::get("CPU");
     auto external = manager->compile(f);
     auto backend = manager->allocate_backend();
     auto cf = backend->make_call_frame(external);
@@ -552,6 +551,7 @@ TEST(execute, dot_matrix_3x2_2x0)
     ASSERT_EQ((vector<float>{}), result->get_vector());
 }
 
+/*
 TEST(execute, dot_scalar_0x2)
 {
     auto shape_a = Shape{};