[ONNX] Softmax operator (#1496)

* [ONNX] Softmax operator

* Review fix pt. 1

* Review fix pt. 2

* Add softmax test

* Update onnx_import.cpp

src/ngraph/frontend/onnx_import/CMakeLists.txt

@@ -46,6 +46,8 @@ add_library(onnx_import STATIC
         op/max_pool.hpp
         op/mul.hpp
         op/relu.hpp
+        op/softmax.cpp
+        op/softmax.hpp
         op/split.cpp
         op/split.hpp
         ops_bridge.cpp

src/ngraph/frontend/onnx_import/op/softmax.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 <numeric>
+
+#include "ngraph/op/softmax.hpp"
+
+#include "exceptions.hpp"
+#include "softmax.hpp"
+
+namespace ngraph
+{
+    namespace onnx_import
+    {
+        namespace op
+        {
+            NodeVector softmax(const Node& node)
+            {
+                NodeVector inputs{node.get_ng_inputs()};
+                auto data = inputs.at(0);
+                auto data_shape = data->get_shape();
+
+                int axis = node.get_attribute_value<int64_t>("axis", 1);
+
+                if (axis < 0)
+                {
+                    axis = data_shape.size() + axis;
+                }
+                else if (axis >= data_shape.size())
+                {
+                    throw error::parameter::Value(
+                        "Softmax node (",
+                        node.get_name(),
+                        "): provided axis attribute is out of input tensor dimensions range.");
+                }
+                // create vector of capacity data_dimensions - axis_divider position
+                std::vector<size_t> axes(data_shape.size() - axis);
+                std::iota(std::begin(axes), std::end(axes), axis);
+                return {std::make_shared<ngraph::op::Softmax>(data, axes)};
+            }
+
+        } // namespace  op
+
+    } // namespace  onnx_import
+
+} // namespace  ngraph

src/ngraph/frontend/onnx_import/op/softmax.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 <memory>
+
+#include "core/node.hpp"
+
+namespace ngraph
+{
+    namespace onnx_import
+    {
+        namespace op
+        {
+            NodeVector softmax(const Node& node);
+        } // namespace  op
+
+    } // namespace  onnx_import
+
+} // namespace  ngraph

src/ngraph/frontend/onnx_import/ops_bridge.cpp

@@ -28,6 +28,7 @@
 #include "op/max_pool.hpp"
 #include "op/mul.hpp"
 #include "op/relu.hpp"
+#include "op/softmax.hpp"
 #include "op/split.hpp"
 #include "ops_bridge.hpp"
 
@@ -85,6 +86,7 @@ namespace ngraph
                     m_map.emplace("MaxPool", std::bind(op::max_pool, std::placeholders::_1));
                     m_map.emplace("Mul", std::bind(op::mul, std::placeholders::_1));
                     m_map.emplace("Relu", std::bind(op::relu, std::placeholders::_1));
+                    m_map.emplace("Softmax", std::bind(op::softmax, std::placeholders::_1));
                     m_map.emplace("Split", std::bind(op::split, std::placeholders::_1));
                 }
 

test/onnx_import.cpp

@@ -358,3 +358,46 @@ TEST(onnx, model_matmul)
     auto result_vectors = execute(function, inputs, "INTERPRETER");
     EXPECT_TRUE(test::all_close_f(expected_output, result_vectors.front()));
 }
+
+TEST(onnx, model_softmax)
+{
+    auto function = ngraph::onnx_import::import_onnx_function(
+        ngraph::file_util::path_join(SERIALIZED_ZOO, "onnx/softmax.onnx"));
+
+    Inputs inputs;
+    inputs.emplace_back(
+        ngraph::test::NDArray<float, 3>(
+            {{{1, 2, 3, 4, 5}, {6, 7, 8, 9, 10}, {11, 12, 13, 14, 15}, {16, 17, 18, 19, 20}},
+
+             {{21, 22, 23, 24, 25},
+              {26, 27, 28, 29, 30},
+              {31, 32, 33, 34, 35},
+              {36, 37, 38, 39, 40}},
+
+             {{41, 42, 43, 44, 45},
+              {46, 47, 48, 49, 50},
+              {51, 52, 53, 54, 55},
+              {56, 57, 58, 59, 60}}})
+            .get_vector());
+
+    auto expected_output =
+        ngraph::test::NDArray<float, 3>(
+            {{{1.50461533e-26, 4.08996852e-26, 1.11176871e-25, 3.02210068e-25, 8.21492137e-25},
+              {2.23304715e-24, 6.07005148e-24, 1.65001106e-23, 4.48519509e-23, 1.21920243e-22},
+              {3.31413582e-22, 9.00875516e-22, 2.44883355e-21, 6.65661973e-21, 1.80945684e-20},
+              {4.91861366e-20, 1.33701781e-19, 3.63439123e-19, 9.87929963e-19, 2.68547207e-18}},
+
+             {{7.29986992e-18, 1.98431037e-17, 5.39391483e-17, 1.46621807e-16, 3.98559393e-16},
+              {1.08339676e-15, 2.94497771e-15, 8.00527940e-15, 2.17606055e-14, 5.91514586e-14},
+              {1.60790335e-13, 4.37073446e-13, 1.18808881e-12, 3.22956021e-12, 8.77885484e-12},
+              {2.38634016e-11, 6.48674509e-11, 1.76328013e-10, 4.79309234e-10, 1.30289758e-09}},
+
+             {{3.54164282e-09, 9.62718331e-09, 2.61693974e-08, 7.11357975e-08, 1.93367146e-07},
+              {5.25626399e-07, 1.42880069e-06, 3.88388295e-06, 1.05574884e-05, 2.86982290e-05},
+              {7.80098743e-05, 2.12052824e-04, 5.76419338e-04, 1.56687021e-03, 4.25919482e-03},
+              {1.15776919e-02, 3.14714295e-02, 8.55482149e-02, 2.32544158e-01, 6.32120559e-01}}})
+            .get_vector();
+
+    auto result_vectors = execute(function, inputs, "INTERPRETER");
+    EXPECT_TRUE(test::all_close_f(expected_output, result_vectors.front()));
+}