[SPEC] Implement MaxPool:v1 and AvgPool:v1 downgrade pass (#3788)

* Implemented downgrade pass

* Added v1 support in onnx importer

* Clang style applied

* Pooling factory refactor

* Removed unused variables

* clang styles apllied

* Fixed avg pool bprop UT

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

@@ -28,7 +28,7 @@ namespace ngraph
             {
                 NodeVector average_pool(const Node& node)
                 {
-                    return pooling::PoolingFactory(node).make_pooling_op<ngraph::op::AvgPool>();
+                    return pooling::PoolingFactory(node).make_avg_pool();
                 }
 
             } // namespace set_1

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

@@ -28,8 +28,7 @@ namespace ngraph
             {
                 NodeVector global_average_pool(const Node& node)
                 {
-                    return pooling::GlobalPoolingFactory(node)
-                        .make_pooling_op<ngraph::op::AvgPool>();
+                    return pooling::GlobalPoolingFactory(node).make_avg_pool();
                 }
 
             } // namespace set_1

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

@@ -28,8 +28,7 @@ namespace ngraph
             {
                 NodeVector global_max_pool(const Node& node)
                 {
-                    return pooling::GlobalPoolingFactory(node)
-                        .make_pooling_op<ngraph::op::MaxPool>();
+                    return pooling::GlobalPoolingFactory(node).make_max_pool();
                 }
 
             } // namespace set_1

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

@@ -29,8 +29,7 @@ namespace ngraph
             {
                 NodeVector max_pool(const Node& node)
                 {
-                    auto max_pool =
-                        pooling::PoolingFactory(node).make_pooling_op<ngraph::op::MaxPool>();
+                    auto max_pool = pooling::PoolingFactory(node).make_max_pool();
                     max_pool.emplace_back(std::make_shared<NullNode>()); // Indices (optional)
                     return max_pool;
                 }

src/ngraph/frontend/onnx_import/utils/pooling_factory.cpp

@@ -41,17 +41,28 @@ namespace ngraph
                 m_padding_above = Shape{std::begin(padding_above), std::end(padding_above)};
             }
 
-            template <>
-            NodeVector PoolingFactory::make_pooling_op<ngraph::op::AvgPool>() const
+            NodeVector PoolingFactory::make_avg_pool() const
             {
                 bool count_include_pad =
                     m_onnx_node.get_attribute_value<std::int64_t>("count_include_pad", 0);
-                return {std::make_shared<ngraph::op::AvgPool>(m_inputs.at(0),
+                return {std::make_shared<ngraph::op::v1::AvgPool>(m_inputs.at(0),
+                                                                  m_strides,
+                                                                  m_padding_below,
+                                                                  m_padding_above,
                                                                   m_kernel_shape,
+                                                                  !count_include_pad,
+                                                                  op::RoundingType::FLOOR,
+                                                                  m_auto_pad)};
+            }
+
+            NodeVector PoolingFactory::make_max_pool() const
+            {
+                return {std::make_shared<ngraph::op::v1::MaxPool>(m_inputs.at(0),
                                                                   m_strides,
                                                                   m_padding_below,
                                                                   m_padding_above,
-                                                              count_include_pad,
+                                                                  m_kernel_shape,
+                                                                  op::RoundingType::FLOOR,
                                                                   m_auto_pad)};
             }
 

src/ngraph/frontend/onnx_import/utils/pooling_factory.hpp

@@ -21,6 +21,7 @@
 #include "core/node.hpp"
 #include "ngraph/node.hpp"
 #include "ngraph/op/avg_pool.hpp"
+#include "ngraph/op/max_pool.hpp"
 #include "ngraph/op/op.hpp"
 #include "ngraph/op/util/attr_types.hpp"
 #include "ngraph/shape.hpp"
@@ -51,23 +52,16 @@ namespace ngraph
                 virtual ~PoolingFactory() = default;
 
                 ///
-                /// \brief      Creates a sub-graph representing appropriate ONNX operation.
+                /// \brief      Creates average pooling ONNX operation.
+                /// \return     Vector of output nodes.
                 ///
-                /// \tparam     NgraphOperator  nGraph operator class type used to build ONNX
-                ///                             operation.
+                NodeVector make_avg_pool() const;
+
                 ///
+                /// \brief      Creates max pooling ONNX operation.
                 /// \return     Vector of output nodes.
                 ///
-                template <typename NgraphOperator>
-                NodeVector make_pooling_op() const
-                {
-                    return {std::make_shared<NgraphOperator>(m_inputs.at(0),
-                                                             m_kernel_shape,
-                                                             m_strides,
-                                                             m_padding_below,
-                                                             m_padding_above,
-                                                             m_auto_pad)};
-                }
+                NodeVector make_max_pool() const;
 
             protected:
                 Node m_onnx_node;
@@ -80,10 +74,6 @@ namespace ngraph
                 ngraph::op::PadType m_auto_pad;
             };
 
-            // AvgPool accepts some additional parameters thus we have specialization for it.
-            template <>
-            NodeVector PoolingFactory::make_pooling_op<ngraph::op::AvgPool>() const;
-
             ///
             /// \brief      Factory class which generates sub-graphs for ONNX 'global' pooling
             ///             operators.

src/ngraph/pass/opset0_downgrade.cpp

@@ -23,6 +23,7 @@
 #include "ngraph/op/constant.hpp"
 #include "ngraph/op/convolution.hpp"
 #include "ngraph/op/get_output_element.hpp"
+#include "ngraph/op/max_pool.hpp"
 #include "ngraph/op/pad.hpp"
 #include "ngraph/op/product.hpp"
 #include "ngraph/op/reduce_prod.hpp"
@@ -91,6 +92,57 @@ bool pass::Opset0Downgrade::run_on_node(shared_ptr<Node> node)
 #endif
     switch (get_typeid(node))
     {
+    case OP_TYPEID::AvgPool:
+    {
+        const auto tmp = as_type_ptr<op::v1::AvgPool>(node);
+
+        auto const input_arg = node->input(0).get_source_output();
+        const auto ceil_mode = static_cast<bool>(tmp->get_rounding_type());
+        const auto include_padding_in_avg_computation = !tmp->get_exclude_pad();
+        const auto pad_type = tmp->get_auto_pad();
+        const auto padding_below = tmp->get_pads_begin();
+        const auto padding_above = tmp->get_pads_end();
+        const auto window_movement_strides = tmp->get_strides();
+        const auto window_shape = tmp->get_kernel();
+
+        auto replacement_node = make_shared<op::v0::AvgPool>(input_arg,
+                                                             window_shape,
+                                                             window_movement_strides,
+                                                             padding_below,
+                                                             padding_above,
+                                                             include_padding_in_avg_computation,
+                                                             pad_type,
+                                                             ceil_mode);
+        replace_node(node, replacement_node);
+        modified = true;
+        break;
+    }
+    case OP_TYPEID::AvgPoolBackprop:
+    {
+        const auto tmp = as_type_ptr<op::v1::AvgPoolBackprop>(node);
+        NGRAPH_CHECK(node->input_value(1).get_node_shared_ptr()->is_constant());
+        const auto forward_arg_shape =
+            static_pointer_cast<op::Constant>(node->input_value(1).get_node_shared_ptr())
+                ->get_shape_val();
+        const auto delta = node->input(0).get_source_output();
+        const auto include_padding_in_avg_computation = !tmp->get_exclude_pad();
+        const auto padding_below = tmp->get_pads_begin();
+        const auto padding_above = tmp->get_pads_end();
+        const auto window_movement_strides = tmp->get_strides();
+        const auto window_shape = tmp->get_kernel();
+
+        auto replacement_node =
+            make_shared<op::v0::AvgPoolBackprop>(forward_arg_shape,
+                                                 delta,
+                                                 window_shape,
+                                                 window_movement_strides,
+                                                 padding_below,
+                                                 padding_above,
+                                                 include_padding_in_avg_computation);
+        replace_node(node, replacement_node);
+        modified = true;
+        break;
+    }
     case OP_TYPEID::Broadcast:
     {
         auto tmp = dynamic_cast<const op::v1::Broadcast*>(node.get());
@@ -178,6 +230,66 @@ bool pass::Opset0Downgrade::run_on_node(shared_ptr<Node> node)
         modified = true;
         break;
     }
+    case OP_TYPEID::MaxPool:
+    {
+        auto tmp = as_type_ptr<op::v1::MaxPool>(node);
+
+        auto const input_arg = node->input(0).get_source_output();
+        auto ceil_mode = static_cast<bool>(tmp->get_rounding_type());
+        auto pad_type = tmp->get_auto_pad();
+        auto padding_below = tmp->get_pads_begin();
+        auto padding_above = tmp->get_pads_end();
+        auto window_movement_strides = tmp->get_strides();
+        auto window_shape = tmp->get_kernel();
+
+        auto replacement_node = make_shared<op::v0::MaxPool>(input_arg,
+                                                             window_shape,
+                                                             window_movement_strides,
+                                                             padding_below,
+                                                             padding_above,
+                                                             pad_type,
+                                                             ceil_mode);
+        replace_node(node, replacement_node);
+        modified = true;
+        break;
+    }
+    case OP_TYPEID::MaxPoolBackprop:
+    {
+        const auto tmp = as_type_ptr<op::v1::MaxPoolBackprop>(node);
+
+        const auto padding_below = tmp->get_pads_begin();
+        const auto padding_above = tmp->get_pads_end();
+        const auto window_movement_strides = tmp->get_strides();
+        const auto window_shape = tmp->get_kernel();
+
+        const auto arg_forward = node->input(0).get_source_output();
+        const auto delta = node->input(1).get_source_output();
+
+        shared_ptr<Node> replacement_node;
+        if (node->get_inputs().size() == 3)
+        {
+            const auto result_forward = node->input(2).get_source_output();
+            replacement_node = make_shared<op::v0::MaxPoolBackprop>(arg_forward,
+                                                                    delta,
+                                                                    result_forward,
+                                                                    window_shape,
+                                                                    window_movement_strides,
+                                                                    padding_below,
+                                                                    padding_above);
+        }
+        else
+        {
+            replacement_node = make_shared<op::v0::MaxPoolBackprop>(arg_forward,
+                                                                    delta,
+                                                                    window_movement_strides,
+                                                                    window_shape,
+                                                                    padding_below,
+                                                                    padding_above);
+        }
+        replace_node(node, replacement_node);
+        modified = true;
+        break;
+    }
     case OP_TYPEID::Pad:
     {
         auto tmp = as_type_ptr<op::v1::Pad>(node);
@@ -290,31 +402,6 @@ bool pass::Opset0Downgrade::run_on_node(shared_ptr<Node> node)
         modified = true;
         break;
     }
-    case OP_TYPEID::AvgPoolBackprop:
-    {
-        auto tmp = dynamic_cast<const op::v1::AvgPoolBackprop*>(node.get());
-        NGRAPH_CHECK(node->input_value(1).get_node_shared_ptr()->is_constant());
-        auto forward_arg_shape =
-            static_pointer_cast<op::Constant>(node->input_value(1).get_node_shared_ptr())
-                ->get_shape_val();
-        auto exclude_pad = tmp->get_exclude_pad();
-        auto pads_begin = tmp->get_pads_begin();
-        auto pads_end = tmp->get_pads_end();
-        auto strides = tmp->get_strides();
-        auto kernel = tmp->get_kernel();
-
-        auto replacement_node =
-            make_shared<op::v0::AvgPoolBackprop>(forward_arg_shape,
-                                                 node->input(0).get_source_output(),
-                                                 kernel,
-                                                 strides,
-                                                 pads_begin,
-                                                 pads_end,
-                                                 exclude_pad);
-        replace_node(node, replacement_node);
-        modified = true;
-        break;
-    }
     default: break;
     }
 #if defined(__clang__)

test/CMakeLists.txt

@@ -79,7 +79,6 @@ set(SRC
     opset_pass/softmax_opset_pass.cpp
     opset_pass/sum_opset_pass.cpp
     opset_pass/topk_opset_pass.cpp
-    opset_pass/avg_pool_opset_pass.cpp
     partial_shape.cpp
     pass.cpp
     pass_liveness.cpp

test/backend/pool.in.cpp

@@ -1374,7 +1374,7 @@ NGRAPH_TEST(${BACKEND_NAME}, avg_pool_bprop_2d_2channel_2image_dyn_shape)
                                                                padding_below,
                                                                padding_above,
                                                                window_shape,
-                                                               false);
+                                                               true);
 
     auto f = make_shared<Function>(NodeVector{avg_pool_bprop},
                                    ParameterVector{delta, forward_arg_shape});

test/opset_pass/avg_pool_opset_pass.cpp

-#include "gmock/gmock.h"
-#include "gtest/gtest.h"
-
-#include "ngraph/ngraph.hpp"
-#include "ngraph/op/util/attr_types.hpp"
-#include "ngraph/pass/manager.hpp"
-#include "ngraph/pass/opset0_downgrade.hpp"
-#include "util/type_prop.hpp"
-
-using namespace std;
-using namespace ngraph;
-
-TEST(opset_transform, opset1_avgpool_downgrade_pass)
-{
-    Shape window_shape{2, 2};
-    auto window_movement_strides = Strides{1, 1};
-    Shape padding_below{0, 0};
-    Shape padding_above{0, 0};
-    auto delta = make_shared<op::Parameter>(element::f32, Shape{2, 2, 2, 2});
-    auto forward_arg_shape = op::Constant::create<int64_t>(element::i64, Shape{4}, {2, 2, 3, 3});
-
-    auto avgpool_v1 = make_shared<op::v1::AvgPoolBackprop>(delta,
-                                                           forward_arg_shape,
-                                                           window_movement_strides,
-                                                           padding_below,
-                                                           padding_above,
-                                                           window_shape,
-                                                           false);
-    auto f = make_shared<Function>(NodeVector{avgpool_v1}, ParameterVector{delta});
-
-    ngraph::pass::Manager pass_manager;
-    pass_manager.register_pass<pass::Opset0Downgrade>();
-    pass_manager.run_passes(f);
-
-    auto avgpool_v0 = static_pointer_cast<op::v0::AvgPoolBackprop>(
-        f->get_results().at(0)->input_value(0).get_node_shared_ptr());
-
-    EXPECT_EQ(avgpool_v0->description(), "AvgPoolBackprop");
-    EXPECT_EQ(avgpool_v0->get_version(), 0);
-    EXPECT_EQ(avgpool_v0->get_forward_arg_shape(), (Shape{2, 2, 3, 3}));
-}

test/opset_pass/poolings_opset_pass.cpp

@@ -3,6 +3,7 @@
 
 #include "ngraph/ngraph.hpp"
 #include "ngraph/pass/manager.hpp"
+#include "ngraph/pass/opset0_downgrade.hpp"
 #include "ngraph/pass/opset1_upgrade.hpp"
 #include "util/test_control.hpp"
 #include "util/type_prop.hpp"
@@ -79,3 +80,161 @@ TEST(opset_transform, opset1_maxpool_upgrade_pass)
     EXPECT_EQ(max_pool_v1_node->get_rounding_type(), op::RoundingType::FLOOR);
     EXPECT_EQ(max_pool_v1_node->get_auto_pad(), pad_mode);
 }
+
+TEST(opset_transform, opset1_avgpool_downgrade_pass)
+{
+    auto arg = make_shared<op::Parameter>(element::f32, Shape{1, 3, 6, 9});
+    Shape padding_below{1, 0};
+    Shape padding_above{0, 1};
+    Strides window_movement_strides{1, 1};
+    Shape window_shape{3, 3};
+    bool exclude_pad = false;
+    auto rounding_type = op::RoundingType::FLOOR;
+    op::PadType auto_pad = op::PadType::EXPLICIT;
+
+    auto avgpool_v1 = make_shared<op::v1::AvgPool>(arg,
+                                                   window_movement_strides,
+                                                   padding_below,
+                                                   padding_above,
+                                                   window_shape,
+                                                   exclude_pad,
+                                                   rounding_type,
+                                                   auto_pad);
+    auto result = make_shared<op::Result>(avgpool_v1);
+    auto f = make_shared<Function>(ResultVector{result}, ParameterVector{arg});
+
+    ngraph::pass::Manager pass_manager;
+    pass_manager.register_pass<pass::Opset0Downgrade>();
+    pass_manager.run_passes(f);
+
+    auto avgpool_s0_result = f->get_results().at(0);
+    auto node = avgpool_s0_result->input(0).get_source_output().get_node_shared_ptr();
+    auto avg_pool_v0_node = static_pointer_cast<op::v0::AvgPool>(node);
+
+    EXPECT_EQ(avg_pool_v0_node->description(), "AvgPool");
+    EXPECT_EQ(avg_pool_v0_node->get_version(), 0);
+
+    EXPECT_EQ(avg_pool_v0_node->get_padding_below(), padding_below);
+    EXPECT_EQ(avg_pool_v0_node->get_padding_above(), padding_above);
+    EXPECT_EQ(avg_pool_v0_node->get_window_movement_strides(), window_movement_strides);
+    EXPECT_EQ(avg_pool_v0_node->get_window_shape(), window_shape);
+    EXPECT_EQ(avg_pool_v0_node->get_ceil_mode(), false);
+    EXPECT_EQ(avg_pool_v0_node->get_include_padding_in_avg_computation(), !exclude_pad);
+    EXPECT_EQ(avg_pool_v0_node->get_pad_type(), auto_pad);
+}
+
+TEST(opset_transform, opset1_maxpool_downgrade_pass)
+{
+    auto arg = make_shared<op::Parameter>(element::f32, Shape{1, 3, 6, 9});
+    Shape padding_below{1, 0};
+    Shape padding_above{0, 1};
+    Strides window_movement_strides{1, 1};
+    Shape window_shape{3, 3};
+    auto rounding_type = op::RoundingType::FLOOR;
+    op::PadType pad_type = op::PadType::EXPLICIT;
+
+    auto maxpool_v1 = make_shared<op::v1::MaxPool>(arg,
+                                                   window_movement_strides,
+                                                   padding_below,
+                                                   padding_above,
+                                                   window_shape,
+                                                   rounding_type,
+                                                   pad_type);
+    auto result = make_shared<op::Result>(maxpool_v1);
+    auto f = make_shared<Function>(ResultVector{result}, ParameterVector{arg});
+
+    ngraph::pass::Manager pass_manager;
+    pass_manager.register_pass<pass::Opset0Downgrade>();
+    pass_manager.run_passes(f);
+
+    auto maxpool_s0_result = f->get_results().at(0);
+    auto node = maxpool_s0_result->input(0).get_source_output().get_node_shared_ptr();
+    auto max_pool_v0_node = static_pointer_cast<op::v0::MaxPool>(node);
+
+    EXPECT_EQ(max_pool_v0_node->description(), "MaxPool");
+    EXPECT_EQ(max_pool_v0_node->get_version(), 0);
+
+    EXPECT_EQ(max_pool_v0_node->get_padding_below(), padding_below);
+    EXPECT_EQ(max_pool_v0_node->get_padding_above(), padding_above);
+    EXPECT_EQ(max_pool_v0_node->get_window_movement_strides(), window_movement_strides);
+    EXPECT_EQ(max_pool_v0_node->get_window_shape(), window_shape);
+    EXPECT_EQ(max_pool_v0_node->get_ceil_mode(), false);
+    EXPECT_EQ(max_pool_v0_node->get_pad_type(), pad_type);
+}
+
+TEST(opset_transform, opset1_avgpool_backprop_downgrade_pass)
+{
+    auto delta = make_shared<op::Parameter>(element::f32, Shape{1, 3, 6, 9});
+    auto forward_arg_shape =
+        op::Constant::create(element::i64, Shape{4}, vector<int64_t>{1, 3, 7, 10});
+    Shape padding_below{1, 0};
+    Shape padding_above{0, 1};
+    Strides window_movement_strides{1, 1};
+    Shape window_shape{3, 3};
+    bool exclude_pad = false;
+
+    auto avgpool_backprop_v1 = make_shared<op::v1::AvgPoolBackprop>(delta,
+                                                                    forward_arg_shape,
+                                                                    window_movement_strides,
+                                                                    padding_below,
+                                                                    padding_above,
+                                                                    window_shape,
+                                                                    exclude_pad);
+    auto result = make_shared<op::Result>(avgpool_backprop_v1);
+    auto f = make_shared<Function>(ResultVector{result}, ParameterVector{delta});
+
+    ngraph::pass::Manager pass_manager;
+    pass_manager.register_pass<pass::Opset0Downgrade>();
+    pass_manager.run_passes(f);
+
+    auto avgpool_backprop_s0_result = f->get_results().at(0);
+    auto node = avgpool_backprop_s0_result->input(0).get_source_output().get_node_shared_ptr();
+    auto avg_pool_backprop_v0_node = static_pointer_cast<op::v0::AvgPoolBackprop>(node);
+
+    EXPECT_EQ(avg_pool_backprop_v0_node->description(), "AvgPoolBackprop");
+    EXPECT_EQ(avg_pool_backprop_v0_node->get_version(), 0);
+
+    EXPECT_EQ(avg_pool_backprop_v0_node->get_padding_below(), padding_below);
+    EXPECT_EQ(avg_pool_backprop_v0_node->get_padding_above(), padding_above);
+    EXPECT_EQ(avg_pool_backprop_v0_node->get_window_movement_strides(), window_movement_strides);
+    EXPECT_EQ(avg_pool_backprop_v0_node->get_window_shape(), window_shape);
+    EXPECT_EQ(avg_pool_backprop_v0_node->get_forward_arg_shape(), Shape({1, 3, 7, 10}));
+    EXPECT_EQ(avg_pool_backprop_v0_node->get_include_padding_in_avg_computation(), !exclude_pad);
+}
+
+TEST(opset_transform, opset1_maxpool_backprop_downgrade_pass)
+{
+    auto arg_forward = make_shared<op::Parameter>(element::f32, Shape{1, 3, 7, 10});
+    auto delta = make_shared<op::Parameter>(element::f32, Shape{1, 3, 6, 9});
+    auto result_forward = make_shared<op::Parameter>(element::f32, Shape{1, 3, 6, 9});
+    Shape padding_below{1, 0};
+    Shape padding_above{0, 1};
+    Strides window_movement_strides{1, 1};
+    Shape window_shape{3, 3};
+
+    auto max_pool_backprop_v1 = make_shared<op::v1::MaxPoolBackprop>(arg_forward,
+                                                                     delta,
+                                                                     result_forward,
+                                                                     window_movement_strides,
+                                                                     padding_below,
+                                                                     padding_above,
+                                                                     window_shape);
+    auto result = make_shared<op::Result>(max_pool_backprop_v1);
+    auto f = make_shared<Function>(ResultVector{result},
+                                   ParameterVector{arg_forward, delta, result_forward});
+
+    ngraph::pass::Manager pass_manager;
+    pass_manager.register_pass<pass::Opset0Downgrade>();
+    pass_manager.run_passes(f);
+
+    auto max_pool_backprop_s0_result = f->get_results().at(0);
+    auto node = max_pool_backprop_s0_result->input(0).get_source_output().get_node_shared_ptr();
+    auto max_pool_backprop_v0_node = static_pointer_cast<op::v0::MaxPoolBackprop>(node);
+
+    EXPECT_EQ(max_pool_backprop_v0_node->description(), "MaxPoolBackprop");
+    EXPECT_EQ(max_pool_backprop_v0_node->get_version(), 0);
+    EXPECT_EQ(max_pool_backprop_v0_node->get_padding_below(), padding_below);
+    EXPECT_EQ(max_pool_backprop_v0_node->get_padding_above(), padding_above);
+    EXPECT_EQ(max_pool_backprop_v0_node->get_window_movement_strides(), window_movement_strides);
+    EXPECT_EQ(max_pool_backprop_v0_node->get_window_shape(), window_shape);
+}