Abs layer support (#6475)

* [MyriadX] Abs op support

inference-engine/cmake/vpu_dependencies.cmake

@@ -6,14 +6,14 @@ include_guard(GLOBAL)
 
 set(VPU_SUPPORTED_FIRMWARES usb-ma2x8x pcie-ma2x8x)
 set(VPU_SUPPORTED_FIRMWARES_HASH
-    "420b300d193f7fcfe7e3f9bbec6c247d65b784a500b5cd2effb7cb1ec6e1b209"
+    "d55a824838accec31733e4d4c45e8774bdd5690da8beefe41360f1983476e3d0"
-    "bfe3caf270b168b9de18ef88f04bde3907d7d12a679f1fa7cc580423c35db637")
+    "61797a77b38fc677be4cc63d730e8871bbf169686b88eabb7066b01f9d156129")
 
 #
 # Default packages
 #
 
-set(FIRMWARE_PACKAGE_VERSION 1688)
+set(FIRMWARE_PACKAGE_VERSION 1714)
 set(VPU_CLC_MA2X8X_VERSION "movi-cltools-20.09.2")
 
 #

inference-engine/src/legacy_api/include/legacy/ie_layers.h

@@ -1025,7 +1025,8 @@ public:
         Logical_OR,
         Logical_XOR,
         Logical_NOT,
-        Mean
+        Mean,
+        Abs,
     };
 
     /**

inference-engine/src/vpu/common/src/ngraph/transformations/dynamic_to_static_shape.cpp

@@ -127,6 +127,7 @@ const Transformations& getDefaultTransformations() {
         {ngraph::opset3::Exp::type_info,                   dynamicToStaticUnaryElementwise},
         {ngraph::opset3::Sqrt::type_info,                  dynamicToStaticUnaryElementwise},
         {ngraph::opset3::LogicalNot::type_info,            dynamicToStaticUnaryElementwise},
+        {ngraph::opset3::Abs::type_info,                   dynamicToStaticUnaryElementwise},
         {ngraph::opset5::ScatterElementsUpdate::type_info, dynamicToStaticUnaryElementwise},
         {ngraph::opset3::StridedSlice::type_info,          dynamicToStaticShapeStridedSlice},
         {ngraph::opset3::Squeeze::type_info,               dynamicToStaticShapeSqueeze},

inference-engine/src/vpu/graph_transformer/include/vpu/frontend/frontend.hpp

@@ -162,6 +162,7 @@ public:
     void parseCeiling(const Model& model, const ie::CNNLayerPtr& layer, const DataVector& inputs, const DataVector& outputs) const;
     void parseRound(const Model& model, const ie::CNNLayerPtr& layer, const DataVector& inputs, const DataVector& outputs) const;
     void parseCTCGreedyDecoderSeqLen(const Model& model, const ie::CNNLayerPtr& layer, const DataVector& inputs, const DataVector& outputs) const;
+    void parseAbs(const Model& model, const ie::CNNLayerPtr& layer, const DataVector& inputs, const DataVector& outputs) const;
 
     //
     // Special layers

inference-engine/src/vpu/graph_transformer/include/vpu/model/stage.hpp

@@ -177,6 +177,7 @@ VPU_DECLARE_ENUM(StageType,
     GatherElements = 139,
     Round = 140,
     CTCGreedyDecoderSeqLen = 141,
+    Abs = 142,
 )
 
 //

inference-engine/src/vpu/graph_transformer/src/frontend/frontend.cpp

@@ -156,6 +156,7 @@ FrontEnd::FrontEnd(StageBuilder::Ptr stageBuilder, const std::shared_ptr<ie::ICo
         {"ExpGatherElements",                                  LAYER_PARSER(parseGatherElements)},
         {"Round",                                              LAYER_PARSER(parseRound)},
         {"CTCGreedyDecoderSeqLen",                             LAYER_PARSER(parseCTCGreedyDecoderSeqLen)},
+        {"Abs",                                                LAYER_PARSER(parseAbs)}
     }} {
         VPU_THROW_UNLESS(_core != nullptr, "Argument core is null");
     }

inference-engine/src/vpu/graph_transformer/src/middleend/passes/merge_eltwise_and_relu.cpp

@@ -69,7 +69,8 @@ void PassImpl::run(const Model& model) {
             eltwiseStage->type() != StageType::Logical_AND    &&
             eltwiseStage->type() != StageType::Logical_OR     &&
             eltwiseStage->type() != StageType::Logical_XOR    &&
-            eltwiseStage->type() != StageType::Logical_NOT) {
+            eltwiseStage->type() != StageType::Logical_NOT    &&
+            eltwiseStage->type() != StageType::Abs) {
             continue;
         }
 

inference-engine/src/vpu/graph_transformer/src/stages/activation.cpp

@@ -16,9 +16,18 @@ void FrontEnd::parseLogicalNot(const Model &model, const ie::CNNLayerPtr &layer,
     parseEltwise(model, res, inputs, outputs);
 }
 
+void FrontEnd::parseAbs(const Model &model, const ie::CNNLayerPtr &layer, const DataVector &inputs, const DataVector &outputs) const {
+    LayerParams params = {layer->name, "Eltwise", layer->precision};
+    auto res = std::make_shared<InferenceEngine::EltwiseLayer>(params);
+    res->_operation = InferenceEngine::EltwiseLayer::Abs;
+
+    parseEltwise(model, res, inputs, outputs);
+}
+
 void FrontEnd::parseActivation(const Model& model, const ie::CNNLayerPtr& layer, const DataVector& inputs, const DataVector& outputs) const {
     const ie::details::caseless_map<std::string, LayerParser> activationParsers {
         {"not", LAYER_PARSER(parseLogicalNot)},
+        {"abs", LAYER_PARSER(parseAbs)},
     };
 
     const auto type = layer->GetParamAsString("type");

inference-engine/src/vpu/graph_transformer/src/stages/eltwise.cpp

@@ -72,6 +72,7 @@ static const std::map<ie::EltwiseLayer::eOperation, std::function<StageType(ie::
         MAP_ELEMENTS(Logical_XOR,   moreThanOneInput),
         MAP_ELEMENTS(Pow,           onlyTwoInputs),
         MAP_ELEMENTS(Floor_mod,     onlyTwoInputs),
+        MAP_ELEMENTS(Abs,           onlyOneInput),
 };
 
 class EltwiseStage final : public StageNode {
@@ -150,7 +151,8 @@ private:
                     StageType::Div,
                     StageType::Min,
                     StageType::Logical_NOT,
-                    StageType::Logical_AND
+                    StageType::Logical_AND,
+                    StageType::Abs,
             };
             auto supportedDataTypesInput0 = EnumSet<DataType>{DataType::FP16};
             if (stageTypesWhichSupportS32.count(operation)) {
@@ -264,7 +266,7 @@ void FrontEnd::parseEltwise(const Model& model, const ie::CNNLayerPtr& _layer, c
     DataVector tempInputs(3);
     tempInputs[0] = inputs[0];
 
-    if (stageType == StageType::Logical_NOT)
+    if (stageType == StageType::Logical_NOT || stageType == StageType::Abs)
         tempInputs[1] = model->addFakeData();
     else
         tempInputs[1] = inputs[1];

inference-engine/tests/functional/plugin/myriad/shared_tests_instances/single_layer_tests/activation.cpp

@@ -16,6 +16,7 @@ const std::vector<InferenceEngine::Precision> netPrecisions = {
 };
 
 const std::map<ActivationTypes, std::vector<std::vector<float>>> activationTypes = {
+        {Abs,                   {}},
         {Sigmoid,               {}},
         {Tanh,                  {}},
         {Relu,                  {}},