[CPU] Remove BatchNorm node. (#22)

a-sidorova · Apr 30, 2021 · 0824bad · 0824bad
1 parent 32f681e
commit 0824bad
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Showing 9 changed files with 0 additions and 397 deletions.
diff --git a/inference-engine/src/mkldnn_plugin/CMakeLists.txt b/inference-engine/src/mkldnn_plugin/CMakeLists.txt
@@ -14,7 +14,6 @@ endif()
 
 ## TODO
 set(LAYERS
-#    ${CMAKE_CURRENT_SOURCE_DIR}/nodes/mkldnn_batchnorm_node.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/nodes/mkldnn_bin_conv_node.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/nodes/mkldnn_concat_node.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/nodes/mkldnn_conv_node.cpp

diff --git a/inference-engine/src/mkldnn_plugin/mkldnn_descriptor.cpp b/inference-engine/src/mkldnn_plugin/mkldnn_descriptor.cpp
@@ -23,18 +23,6 @@ size_t MKLDNNDescriptor::outputNumbers() const {
     return 1;
 }
 
-MKLDNNDescriptor::MKLDNNDescriptor(std::shared_ptr<mkldnn::batch_normalization_forward::desc> desc) {
-    this->desc.reset(new DescFwdImpl<mkldnn::batch_normalization_forward::desc>(desc));
-}
-
-MKLDNNDescriptor::operator std::shared_ptr<mkldnn::batch_normalization_forward::desc>() {
-    auto typeDesc = std::dynamic_pointer_cast<DescFwdImpl<mkldnn::batch_normalization_forward::desc>>(desc);
-    if (typeDesc == nullptr) {
-        IE_THROW() << "Cannot cast descriptor!";
-    }
-    return typeDesc->getPtr();
-}
-
 MKLDNNDescriptor::MKLDNNDescriptor(std::shared_ptr<mkldnn::convolution_forward::desc> desc) {
     this->desc.reset(new DescFwdImpl<mkldnn::convolution_forward::desc>(desc));
 }

diff --git a/inference-engine/src/mkldnn_plugin/mkldnn_descriptor.h b/inference-engine/src/mkldnn_plugin/mkldnn_descriptor.h
@@ -10,9 +10,6 @@
 
 class MKLDNNDescriptor {
 public:
-    explicit MKLDNNDescriptor(std::shared_ptr<mkldnn::batch_normalization_forward::desc> desc);
-    operator std::shared_ptr<mkldnn::batch_normalization_forward::desc>();
-
     explicit MKLDNNDescriptor(std::shared_ptr<mkldnn::convolution_forward::desc> desc);
     operator std::shared_ptr<mkldnn::convolution_forward::desc>();
 

diff --git a/inference-engine/src/mkldnn_plugin/mkldnn_exec_network.cpp b/inference-engine/src/mkldnn_plugin/mkldnn_exec_network.cpp
@@ -300,7 +300,6 @@ bool MKLDNNExecNetwork::CanProcessDynBatch(const InferenceEngine::CNNNetwork &ne
 //            type != Concatenation &&
 //            type != Eltwise &&
 //            type != Crop &&
-//            type != BatchNormalization &&
 //            type != Copy) {
 //            check_result = false;
 //        }

diff --git a/inference-engine/src/mkldnn_plugin/mkldnn_graph_optimizer.cpp b/inference-engine/src/mkldnn_plugin/mkldnn_graph_optimizer.cpp
@@ -103,15 +103,6 @@ void MKLDNNGraphOptimizer::ApplyCommonGraphOptimizations(MKLDNNGraph &graph) {
     FuseBinaryConvolutionAndQuantize(graph);
     graph.RemoveDroppedNodes();
 
-    OV_ITT_SCOPE_NEXT(FIRST_INFERENCE, taskChain, "FuseBatchNormWithScale");
-    FuseBatchNormWithScale(graph);
-    graph.RemoveDroppedNodes();
-
-    // OV_ITT_SCOPE_NEXT(FIRST_INFERENCE, taskChain, "RemoveIdentityOperator");
-    // RemoveIdentityOperator(graph);
-    // graph.RemoveDroppedNodes();
-
-    OV_ITT_SCOPE_NEXT(FIRST_INFERENCE, taskChain, "FuseConvolutionSumAndConvolutionSumActivation");
     FuseConvolutionSumAndConvolutionSumActivation(graph);
     graph.RemoveDroppedNodes();
 
@@ -714,40 +705,6 @@ void MKLDNNGraphOptimizer::MergeTwoEqualScaleShifts(MKLDNNGraph& graph) {
 //    }
 }
 
-void MKLDNNGraphOptimizer::FuseBatchNormWithScale(MKLDNNGraph &graph) {
-//    auto &graphNodes = graph.GetNodes();
-//
-//    for (int i = 0; i < graphNodes.size(); i++) {
-//        const auto& bn = graphNodes[i];
-//        if (bn->getType() == BatchNormalization) {
-//            const auto& outputNodesMap = graph.GetOutputNodesMap();
-//            const std::string node_name = bn->getName();
-//            // Check that the node is not output node
-//            if (std::find_if(outputNodesMap.begin(), outputNodesMap.end(),
-//                            [&node_name](const MKLDNNNodePtr& x) {
-//                                return x->getName() == node_name;}) == outputNodesMap.end()) {
-//                if (bn->getChildEdges().size() == 1) {
-//                    auto child = bn->getChildEdgeAt(0)->getChild();
-//                    if (child->type == Eltwise && child->getCnnLayer()->type == "ScaleShift") {
-//                        bn->fuseWith(child);
-//
-//                        auto parentEdges = child->parentEdges;
-//                        for (auto &parentEdge : parentEdges) {
-//                            auto p_edge = parentEdge.lock();
-//                            if (p_edge->getParent()->getType() == BatchNormalization)
-//                                continue;
-//
-//                            removeEdge(graph, p_edge);
-//                        }
-//
-//                        graph.DropNode(child);
-//                    }
-//                }
-//            }
-//        }
-//    }
-}
-
 void MKLDNNGraphOptimizer::FuseFullyConnectedAndSimpleOperation(MKLDNNGraph &graph) {
     auto& graphNodes = graph.GetNodes();
 

diff --git a/inference-engine/src/mkldnn_plugin/mkldnn_node.cpp b/inference-engine/src/mkldnn_plugin/mkldnn_node.cpp
@@ -13,7 +13,6 @@
 #include <cstdint>
 #include <unordered_map>
 
-#include <nodes/mkldnn_batchnorm_node.h>
 #include <nodes/mkldnn_concat_node.h>
 #include <nodes/mkldnn_conv_node.h>
 #include <nodes/mkldnn_deconv_node.h>
@@ -167,7 +166,6 @@ static const InferenceEngine::details::caseless_unordered_map<std::string, Type>
 //        { "SimplerNMS", SimplerNMS },
 //        { "ROIAlign", ROIAlign },
 //        { "ROIPooling", ROIPooling },
-//        { "BatchNormalization", BatchNormalization },
 //        { "Flatten", Flatten },
         { "Pad", Pad },
         { "Transpose", Transpose },

diff --git a/inference-engine/src/mkldnn_plugin/mkldnn_node.h b/inference-engine/src/mkldnn_plugin/mkldnn_node.h
@@ -58,7 +58,6 @@ enum Type {
     SimplerNMS,
     ROIAlign,
     ROIPooling,
-    BatchNormalization,
     DepthToSpace,
     Flatten,
     Pad,
@@ -201,8 +200,6 @@ static std::string NameFromType(Type type) {
             return "ROIAlign";
         case ROIPooling:
             return "ROIPooling";
-        case BatchNormalization:
-            return "BatchNormalization";
         case DepthToSpace:
             return "DepthToSpace";
         case Flatten: