[ONNX] Concat operator (#1524)

* [ONNX] Concat operator

* Style fix

src/ngraph/frontend/onnx_import/CMakeLists.txt

@@ -36,6 +36,8 @@ add_library(onnx_import STATIC
         op/average_pool.hpp
         op/batch_norm.cpp
         op/batch_norm.hpp
+        op/concat.cpp
+        op/concat.hpp
         op/constant.cpp
         op/constant.hpp
         op/conv.cpp

src/ngraph/frontend/onnx_import/op/concat.cpp

+//*****************************************************************************
+// Copyright 2018 Intel Corporation
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//*****************************************************************************
+
+#include "concat.hpp"
+
+#include "ngraph/op/concat.hpp"
+
+namespace ngraph
+{
+    namespace onnx_import
+    {
+        namespace op
+        {
+            NodeVector concat(const Node& node)
+            {
+                NodeVector inputs{node.get_ng_inputs()};
+                auto axis = node.get_attribute_value<int64_t>("axis");
+
+                return {std::make_shared<ngraph::op::Concat>(inputs, axis)};
+            }
+
+        } // namespace  op
+
+    } // namespace  onnx_import
+
+} // namespace  ngraph

src/ngraph/frontend/onnx_import/op/concat.hpp

+//*****************************************************************************
+// Copyright 2018 Intel Corporation
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//*****************************************************************************
+
+#pragma once
+
+#include "ngraph/node_vector.hpp"
+
+#include "core/node.hpp"
+
+namespace ngraph
+{
+    namespace onnx_import
+    {
+        namespace op
+        {
+            NodeVector concat(const Node& node);
+        } // namespace  op
+
+    } // namespace  onnx_import
+
+} // namespace  ngraph

src/ngraph/frontend/onnx_import/ops_bridge.cpp

@@ -21,6 +21,7 @@
 #include "op/add.hpp"
 #include "op/average_pool.hpp"
 #include "op/batch_norm.hpp"
+#include "op/concat.hpp"
 #include "op/constant.hpp"
 #include "op/conv.hpp"
 #include "op/div.hpp"
@@ -86,6 +87,7 @@ namespace ngraph
                                   std::bind(op::average_pool, std::placeholders::_1));
                     m_map.emplace("BatchNormalization",
                                   std::bind(op::batch_norm, std::placeholders::_1));
+                    m_map.emplace("Concat", std::bind(op::concat, std::placeholders::_1));
                     m_map.emplace("Constant", std::bind(op::constant, std::placeholders::_1));
                     m_map.emplace("Conv", std::bind(op::conv, std::placeholders::_1));
                     m_map.emplace("Div", std::bind(op::div, std::placeholders::_1));

test/onnx_import.cpp

@@ -488,6 +488,22 @@ TEST(onnx, model_softmax)
     EXPECT_TRUE(test::all_close_f(expected_output, result_vectors.front()));
 }
 
+TEST(onnx, model_concat)
+{
+    auto function =
+        onnx_import::import_onnx_function(file_util::path_join(SERIALIZED_ZOO, "onnx/concat.onnx"));
+
+    Inputs inputs;
+
+    inputs.emplace_back(test::NDArray<float, 1>({1, 2}).get_vector());
+    inputs.emplace_back(test::NDArray<float, 1>({3, 4}).get_vector());
+
+    Outputs expected_outputs{test::NDArray<float, 1>({1, 2, 3, 4}).get_vector()};
+
+    Outputs outputs{execute(function, inputs, "INTERPRETER")};
+    EXPECT_TRUE(test::all_close_f(expected_outputs.front(), outputs.front()));
+}
+
 TEST(onnx, model_flatten)
 {
     auto function = onnx_import::import_onnx_function(