Merge branch 'master' into cyphers/expdesc

src/contrib/mlir/lowerer.cpp

@@ -43,6 +43,8 @@ namespace
     using namespace mlir::edsc::op;
     using namespace ngraph::runtime;
     using namespace ngraph::runtime::ngmlir;
+    // Index notation to generate standard (i.e., non-affine) loads and stores.
+    using StdIndexedValue = TemplatedIndexedValue<intrinsics::std_load, intrinsics::std_store>;
 
     class DialectLoweringPass;
 
@@ -682,7 +684,8 @@ namespace
         // Create view to write into result.
         MemRefView vRes(result), vParams(params), vIndices(indices);
         // Indexed Values
-        IndexedValue iRes(result), iParams(params), iIndices(indices);
+        IndexedValue iRes(result), iIndices(indices);
+        StdIndexedValue iParams(params);
 
         // Construct outer loop for params dims. Exclude the axis dim.
         SmallVector<ValueHandle, 4> paramsLbs, paramsUbs;
@@ -894,7 +897,8 @@ namespace
         // Views
         MemRefView vRes(result), vArg(arg);
         // Index Values
-        IndexedValue iRes(result), iArg(arg);
+        StdIndexedValue iRes(result), stdArg(arg);
+        IndexedValue affineArg(arg);
         // Bounds Index Handles
         auto resLbs = vRes.getLbs();
         auto resUbs = vRes.getUbs();
@@ -944,9 +948,9 @@ namespace
                 ValueHandle newRedIdx =
                     std::is_same<RedOp, NGArgMinRedOp>()
                         ? edsc::intrinsics::select(
-                              iArg(allIVs) < iArg(tempIVs), allIVs[axis], currRedIdx)
+                              affineArg(allIVs) < stdArg(tempIVs), allIVs[axis], currRedIdx)
                         : edsc::intrinsics::select(
-                              iArg(tempIVs) < iArg(allIVs), allIVs[axis], currRedIdx);
+                              stdArg(tempIVs) < affineArg(allIVs), allIVs[axis], currRedIdx);
 
                 iRes(nonRedIVs) = ValueHandle::create<IndexCastOp>(newRedIdx, resTy);
             });

src/ngraph/op/avg_pool.hpp

@@ -173,6 +173,7 @@ namespace ngraph
         class AvgPoolBackprop : public Op
         {
         public:
+            NGRAPH_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             AvgPoolBackprop() = default;

src/ngraph/op/batch_norm.hpp

@@ -92,6 +92,7 @@ namespace ngraph
         class BatchNormInference : public Op
         {
         public:
+            NGRAPH_API
             static const std::string type_name;
             const std::string& description() const override { return type_name; }
             BatchNormInference() = default;

src/ngraph/op/pad.cpp

@@ -21,12 +21,14 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Pad::type_name{"Pad"};
+
 op::Pad::Pad(const shared_ptr<Node>& arg,
              const shared_ptr<Node>& arg_pad_value,
              const CoordinateDiff& padding_below,
              const CoordinateDiff& padding_above,
              PadMode pad_mode)
-    : Op("Pad", check_single_output_args({arg, arg_pad_value}))
+    : Op(check_single_output_args({arg, arg_pad_value}))
     , m_padding_below(padding_below)
     , m_padding_above(padding_above)
     , m_padding_interior_fake(padding_below.size())

src/ngraph/op/pad.hpp

@@ -28,6 +28,9 @@ namespace ngraph
         class Pad : public Op
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a generic padding operation.
             ///
             /// \param arg The node producing input tensor to be padded.

src/ngraph/op/parameter.cpp

@@ -21,10 +21,12 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Parameter::type_name{"Parameter"};
+
 op::Parameter::Parameter(const element::Type& element_type,
                          const PartialShape& pshape,
                          const bool cacheable)
-    : Op("Parameter", {})
+    : Op(NodeVector{})
     , m_cacheable(cacheable)
     , m_partial_shape(pshape)
     , m_element_type(element_type)

src/ngraph/op/parameter.hpp

@@ -35,6 +35,9 @@ namespace ngraph
                                            const NodeVector& deltas) override;
 
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructions a tensor-typed parameter node.
             ///
             /// \param element_type The element type of the parameter.

src/ngraph/op/passthrough.cpp

@@ -18,12 +18,17 @@
 
 #include "ngraph/op/passthrough.hpp"
 
+using namespace std;
+using namespace ngraph;
+
+const string op::Passthrough::type_name{"Passthrough"};
+
 ngraph::op::Passthrough::Passthrough(const std::string& logical_type,
                                      const std::string& language,
                                      const std::string& function,
                                      const NodeVector& args,
                                      std::vector<std::tuple<element::Type, PartialShape>> outputs)
-    : Op{"Passthrough", args}
+    : Op{args}
     , m_logical_type{logical_type}
     , m_language{language}
     , m_function{function}
@@ -65,5 +70,5 @@ std::shared_ptr<ngraph::Node>
             "Passthrough node input counts cannot be changed for a given Passthrough function"};
     }
     return std::make_shared<Passthrough>(
-        description(), m_language, m_function, new_args, m_output_shapes);
+        m_logical_type, m_language, m_function, new_args, m_output_shapes);
 }

src/ngraph/op/passthrough.hpp

@@ -38,6 +38,9 @@ namespace ngraph
 class ngraph::op::Passthrough final : public Op
 {
 public:
+    NGRAPH_API
+    static const std::string type_name;
+    const std::string& description() const override { return type_name; }
     Passthrough(const std::string& logical_type, // aka "What this operation is doing"
                 const std::string& language,     // The language the implementation is written in
                 const std::string& function,     // The operation implementation

src/ngraph/op/power.cpp

@@ -22,10 +22,12 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Power::type_name{"Power"};
+
 op::Power::Power(const shared_ptr<Node>& arg0,
                  const shared_ptr<Node>& arg1,
                  const AutoBroadcastSpec& autob)
-    : BinaryElementwiseArithmetic("Power", arg0, arg1, autob)
+    : BinaryElementwiseArithmetic(arg0, arg1, autob)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/power.hpp

@@ -39,6 +39,9 @@ namespace ngraph
         class Power : public util::BinaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs an exponentiation operation.
             ///
             /// \param arg0 Node that produces the first input tensor.

src/ngraph/op/relu.cpp

@@ -20,8 +20,11 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Relu::type_name{"Relu"};
+const string op::ReluBackprop::type_name{"ReluBackprop"};
+
 op::Relu::Relu(shared_ptr<Node> arg)
-    : UnaryElementwiseArithmetic("Relu", {arg})
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }
@@ -33,7 +36,7 @@ shared_ptr<Node> op::Relu::copy_with_new_args(const NodeVector& new_args) const
 }
 
 op::ReluBackprop::ReluBackprop(shared_ptr<Node> arg, shared_ptr<Node> delta)
-    : BinaryElementwiseArithmetic("ReluBackprop", arg, delta)
+    : BinaryElementwiseArithmetic(arg, delta)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/relu.hpp

@@ -33,6 +33,9 @@ namespace ngraph
         class Relu : public ngraph::op::util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a Relu operation.
             ///
             /// \param arg Node that produces the input tensor.
@@ -50,6 +53,9 @@ namespace ngraph
         class ReluBackprop : public ngraph::op::util::BinaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a ReluBackprop operation.
             ///
             /// \param arg Node that produces the relu forward input tensor.

src/ngraph/op/reverse.cpp

@@ -23,8 +23,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Reverse::type_name{"Reverse"};
+
 op::Reverse::Reverse(const shared_ptr<Node>& arg, const AxisSet& reversed_axes)
-    : Op("Reverse", check_single_output_args({arg}))
+    : Op(check_single_output_args({arg}))
     , m_reversed_axes(reversed_axes)
 {
     constructor_validate_and_infer_types();

src/ngraph/op/reverse.hpp

@@ -46,6 +46,9 @@ namespace ngraph
         class Reverse : public Op
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a reverse operation.
             ///
             /// \param arg The input tensor, some of whose axes are to be reversed.

src/ngraph/op/reverse_sequence.cpp

@@ -25,11 +25,13 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::ReverseSequence::type_name{"ReverseSequence"};
+
 op::ReverseSequence::ReverseSequence(const std::shared_ptr<Node> arg,
                                      const std::shared_ptr<Node> seq_indices,
                                      size_t batch_axis,
                                      size_t seq_axis)
-    : Op("ReverseSequence", check_single_output_args({arg, seq_indices}))
+    : Op(check_single_output_args({arg, seq_indices}))
     , m_batch_axis(batch_axis)
     , m_seq_axis(seq_axis)
 {

src/ngraph/op/reverse_sequence.hpp

@@ -25,6 +25,9 @@ namespace ngraph
         class ReverseSequence : public Op
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs an arcsin operation.
             ///
             /// \param arg Node that produces the input tensor.

src/ngraph/op/scatter_add.cpp

@@ -24,6 +24,8 @@ static int INPUTS = 0;
 static int INDICES = 1;
 static int UPDATES = 2;
 
+const string op::ScatterAdd::type_name{"ScatterAdd"};
+
 shared_ptr<Node> op::ScatterAdd::copy_with_new_args(const NodeVector& new_args) const
 {
     check_new_args_count(this, new_args);

src/ngraph/op/scatter_add.hpp

@@ -26,13 +26,16 @@ namespace ngraph
         class ScatterAdd : public Op
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \param inputs Tensor
             /// \param indices Index tensor: Data type must be `element::i32` or `element::i64`
             /// \param updates Tensor: Must have same type as inputs
             ScatterAdd(const std::shared_ptr<Node>& inputs,
                        const std::shared_ptr<Node>& indices,
                        const std::shared_ptr<Node>& updates)
-                : Op("ScatterAdd", check_single_output_args({inputs, indices, updates}))
+                : Op(check_single_output_args({inputs, indices, updates}))
             {
                 constructor_validate_and_infer_types();
             }

src/ngraph/op/scatter_nd_add.cpp

@@ -24,6 +24,8 @@ static int INPUTS = 0;
 static int INDICES = 1;
 static int UPDATES = 2;
 
+const string op::ScatterNDAdd::type_name{"ScatterNDAdd"};
+
 shared_ptr<Node> op::ScatterNDAdd::copy_with_new_args(const NodeVector& new_args) const
 {
     check_new_args_count(this, new_args);

src/ngraph/op/scatter_nd_add.hpp

@@ -26,13 +26,16 @@ namespace ngraph
         class ScatterNDAdd : public Op
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \param inputs Tensor
             /// \param indices Index tensor: Data type must be `element::i32` or `element::i64`
             /// \param updates Tensor: Must have same type as inputs
             ScatterNDAdd(const std::shared_ptr<Node>& inputs,
                          const std::shared_ptr<Node>& indices,
                          const std::shared_ptr<Node>& updates)
-                : Op("ScatterNDAdd", check_single_output_args({inputs, indices, updates}))
+                : Op(check_single_output_args({inputs, indices, updates}))
             {
                 constructor_validate_and_infer_types();
             }

src/ngraph/op/sigmoid.cpp

@@ -21,6 +21,9 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Sigmoid::type_name{"Sigmoid"};
+const string op::SigmoidBackprop::type_name{"SigmoidBackprop"};
+
 shared_ptr<Node> op::Sigmoid::copy_with_new_args(const NodeVector& new_args) const
 {
     check_new_args_count(this, new_args);
@@ -28,13 +31,13 @@ shared_ptr<Node> op::Sigmoid::copy_with_new_args(const NodeVector& new_args) con
 }
 
 op::Sigmoid::Sigmoid(shared_ptr<Node> arg)
-    : UnaryElementwiseArithmetic("Sigmoid", arg)
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }
 
 op::SigmoidBackprop::SigmoidBackprop(shared_ptr<Node> arg, shared_ptr<Node> delta)
-    : BinaryElementwiseArithmetic("SigmoidBackprop", arg, delta)
+    : BinaryElementwiseArithmetic(arg, delta)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/sigmoid.hpp

@@ -28,6 +28,9 @@ namespace ngraph
         class Sigmoid : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             Sigmoid(std::shared_ptr<Node> arg);
             virtual std::shared_ptr<Node>
                 copy_with_new_args(const NodeVector& new_args) const override;
@@ -40,6 +43,9 @@ namespace ngraph
         class SigmoidBackprop : public util::BinaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a SigmoidBackprop operation.
             ///
             /// \param arg Node that produces the Sigmoid forward input tensor.

src/ngraph/op/sign.cpp

@@ -19,8 +19,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Sign::type_name{"Sign"};
+
 op::Sign::Sign(const shared_ptr<Node>& arg)
-    : UnaryElementwiseArithmetic("Sign", arg)
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/sign.hpp

@@ -27,6 +27,9 @@ namespace ngraph
         class Sign : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs an elementwise sign operation.
             ///
             /// \param arg Node that produces the input tensor.

src/ngraph/op/sin.cpp

@@ -21,8 +21,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Sin::type_name{"Sin"};
+
 op::Sin::Sin(const shared_ptr<Node>& arg)
-    : UnaryElementwiseArithmetic("Sin", arg)
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/sin.hpp

@@ -38,6 +38,9 @@ namespace ngraph
         class Sin : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a sine operation.
             ///
             /// \param arg Node that produces the input tensor.

src/ngraph/op/sinh.cpp

@@ -21,8 +21,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Sinh::type_name{"Sinh"};
+
 op::Sinh::Sinh(const shared_ptr<Node>& arg)
-    : UnaryElementwiseArithmetic("Sinh", arg)
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/sinh.hpp

@@ -26,6 +26,9 @@ namespace ngraph
         class Sinh : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a hyperbolic sine operation.
             ///
             /// \param arg Node that produces the input tensor.

src/ngraph/op/softmax.cpp

@@ -29,8 +29,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Softmax::type_name{"Softmax"};
+
 op::Softmax::Softmax(const shared_ptr<Node>& arg, const AxisSet& axes)
-    : UnaryElementwiseArithmetic("Softmax", arg)
+    : UnaryElementwiseArithmetic(arg)
     , m_axes(axes)
 {
     constructor_validate_and_infer_types();

src/ngraph/op/softmax.hpp

@@ -27,6 +27,9 @@ namespace ngraph
         class Softmax : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a softmax operation.
             ///
             /// \param arg Node that produces the first input tensor.<br>

src/ngraph/op/sqrt.cpp

@@ -21,8 +21,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Sqrt::type_name{"Sqrt"};
+
 op::Sqrt::Sqrt(const shared_ptr<Node>& arg)
-    : UnaryElementwiseArithmetic("Sqrt", arg)
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/sqrt.hpp

@@ -38,6 +38,9 @@ namespace ngraph
         class Sqrt : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a square operation.
             ///
             /// \param arg Node that produces the input tensor.

src/ngraph/op/stop_gradient.cpp

@@ -21,8 +21,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::StopGradient::type_name{"StopGradient"};
+
 op::StopGradient::StopGradient(const shared_ptr<Node>& arg)
-    : UnaryElementwiseArithmetic("StopGradient", arg)
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/stop_gradient.hpp

@@ -26,6 +26,9 @@ namespace ngraph
         class StopGradient : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs StopGradient
             ///
             /// \param arg Node that produces the input tensor.

src/ngraph/op/tan.cpp

@@ -22,8 +22,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Tan::type_name{"Tan"};
+
 op::Tan::Tan(const shared_ptr<Node>& arg)
-    : UnaryElementwiseArithmetic("Tan", arg)
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/tan.hpp

@@ -38,6 +38,9 @@ namespace ngraph
         class Tan : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a tangent operation.
             ///
             /// \param arg Node that produces the input tensor.

src/ngraph/op/tanh.cpp

@@ -21,8 +21,10 @@
 using namespace std;
 using namespace ngraph;
 
+const string op::Tanh::type_name{"Tanh"};
+
 op::Tanh::Tanh(const shared_ptr<Node>& arg)
-    : UnaryElementwiseArithmetic("Tanh", arg)
+    : UnaryElementwiseArithmetic(arg)
 {
     constructor_validate_and_infer_types();
 }

src/ngraph/op/tanh.hpp

@@ -26,6 +26,9 @@ namespace ngraph
         class Tanh : public util::UnaryElementwiseArithmetic
         {
         public:
+            NGRAPH_API
+            static const std::string type_name;
+            const std::string& description() const override { return type_name; }
             /// \brief Constructs a hyperbolic tangent operation.
             ///
             /// \param arg Node that produces the input tensor.

src/ngraph/pass/constant_folding.hpp

@@ -49,7 +49,9 @@ public:
         SLICE,
         DYN_SLICE,
         DYN_RESHAPE,
-        TRANSPOSE
+        TRANSPOSE,
+        RANGE,
+        SELECT
     };
 
     ConstantFolding(const ngraph::BuildNodeExecutorMap& cfmap = ngraph::BuildNodeExecutorMap())
@@ -74,6 +76,8 @@ public:
         construct_constant_dyn_slice();
         construct_constant_dyn_reshape();
         construct_constant_transpose();
+        construct_constant_range();
+        construct_constant_select();
     }
 
     //this allows to specify the order in which matchers will be run
@@ -105,6 +109,8 @@ public:
             case CFTransformations::DYN_SLICE: construct_constant_dyn_slice(); break;
             case CFTransformations::DYN_RESHAPE: construct_constant_dyn_reshape(); break;
             case CFTransformations::TRANSPOSE: construct_constant_transpose(); break;
+            case CFTransformations::RANGE: construct_constant_range(); break;
+            case CFTransformations::SELECT: construct_constant_select(); break;
             }
         }
     }
@@ -128,6 +134,8 @@ private:
     void construct_constant_dyn_slice();
     void construct_constant_dyn_reshape();
     void construct_constant_transpose();
+    void construct_constant_range();
+    void construct_constant_select();
 
     ngraph::BuildNodeExecutorMap m_cfmap;
 };

src/ngraph/pass/dyn_elimination.cpp

@@ -30,6 +30,7 @@
 #include "ngraph/op/slice.hpp"
 #include "ngraph/pattern/matcher.hpp"
 #include "ngraph/pattern/op/label.hpp"
+#include "ngraph/runtime/reference/range.hpp"
 #include "ngraph/slice_plan.hpp"
 
 using namespace std;
@@ -342,11 +343,10 @@ void pass::DynElimination::construct_dyn_reshape()
 }
 
 template <typename T>
-std::shared_ptr<op::Constant>
-    make_range_replacement_integral(const element::Type& et,
-                                    const Shape& shape,
-                                    const std::shared_ptr<op::Constant>& start_arg,
-                                    const std::shared_ptr<op::Constant>& step_arg)
+std::shared_ptr<op::Constant> make_range_replacement(const element::Type& et,
+                                                     const Shape& shape,
+                                                     const std::shared_ptr<op::Constant>& start_arg,
+                                                     const std::shared_ptr<op::Constant>& step_arg)
 {
     std::vector<T> elements(shape_size(shape));
     std::vector<T> start_vec = start_arg->get_vector<T>();
@@ -354,40 +354,7 @@ std::shared_ptr<op::Constant>
 
     NGRAPH_CHECK(start_vec.size() == 1 && step_vec.size() == 1);
 
-    T start = start_vec[0];
-    T step = step_vec[0];
-
-    T val = start;
-
-    for (size_t i = 0; i < elements.size(); i++)
-    {
-        elements[i] = val;
-        val = val + step;
-    }
-
-    return make_shared<op::Constant>(et, shape, elements);
-}
-
-template <typename T>
-std::shared_ptr<op::Constant>
-    make_range_replacement_floating(const element::Type& et,
-                                    const Shape& shape,
-                                    const std::shared_ptr<op::Constant>& start_arg,
-                                    const std::shared_ptr<op::Constant>& step_arg)
-{
-    std::vector<T> elements(shape_size(shape));
-    std::vector<T> start_vec = start_arg->get_vector<T>();
-    std::vector<T> step_vec = step_arg->get_vector<T>();
-
-    NGRAPH_CHECK(start_vec.size() == 1 && step_vec.size() == 1);
-
-    T start = start_vec[0];
-    T step = step_vec[0];
-
-    for (size_t i = 0; i < elements.size(); i++)
-    {
-        elements[i] = start + (static_cast<T>(i) * step);
-    }
+    runtime::reference::range<T>(start_vec.data(), step_vec.data(), shape, elements.data());
 
     return make_shared<op::Constant>(et, shape, elements);
 }
@@ -426,40 +393,40 @@ void pass::DynElimination::construct_range()
         switch (et.get_type_enum())
         {
         case element::Type_t::bf16:
-            replacement = make_range_replacement_floating<bfloat16>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<bfloat16>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::f16:
-            replacement = make_range_replacement_floating<float16>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<float16>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::f32:
-            replacement = make_range_replacement_floating<float>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<float>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::f64:
-            replacement = make_range_replacement_floating<double>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<double>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::i8:
-            replacement = make_range_replacement_integral<int8_t>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<int8_t>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::i16:
-            replacement = make_range_replacement_integral<int16_t>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<int16_t>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::i32:
-            replacement = make_range_replacement_integral<int32_t>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<int32_t>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::i64:
-            replacement = make_range_replacement_integral<int64_t>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<int64_t>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::u8:
-            replacement = make_range_replacement_integral<uint8_t>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<uint8_t>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::u16:
-            replacement = make_range_replacement_integral<uint16_t>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<uint16_t>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::u32:
-            replacement = make_range_replacement_integral<uint32_t>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<uint32_t>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::u64:
-            replacement = make_range_replacement_integral<uint64_t>(et, shape, start_arg, step_arg);
+            replacement = make_range_replacement<uint64_t>(et, shape, start_arg, step_arg);
             break;
         case element::Type_t::undefined:
         case element::Type_t::dynamic:

src/ngraph/runtime/reference/range.hpp

+//*****************************************************************************
+// Copyright 2017-2019 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 <cmath>
+#include <type_traits>
+
+#include "ngraph/axis_vector.hpp"
+#include "ngraph/check.hpp"
+#include "ngraph/coordinate_transform.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace reference
+        {
+            // Return type is `void`, only enabled if `T` is a built-in FP
+            // type, or nGraph's `bfloat16` or `float16` type.
+            template <typename T>
+            typename std::enable_if<std::is_floating_point<T>::value ||
+                                    std::is_same<T, bfloat16>::value ||
+                                    std::is_same<T, float16>::value>::type
+                range(const T* start, const T* step, const Shape& out_shape, T* out)
+            {
+                for (size_t i = 0; i < shape_size(out_shape); i++)
+                {
+                    out[i] = *start + (static_cast<T>(i) * (*step));
+                }
+            }
+
+            // Return type is `void`, only enabled if `T` is `is_integral`.
+            template <typename T>
+            typename std::enable_if<std::is_integral<T>::value>::type
+                range(const T* start, const T* step, const Shape& out_shape, T* out)
+            {
+                T val = *start;
+
+                for (size_t i = 0; i < shape_size(out_shape); i++)
+                {
+                    out[i] = val;
+                    val += *step;
+                }
+            }
+        }
+    }
+}

test/constant_folding.cpp

@@ -891,6 +891,94 @@ TEST(constant_folding, constant_transpose)
     ASSERT_TRUE(test::all_close_f(values_permute, values_out, MIN_FLOAT_TOLERANCE_BITS));
 }
 
+void range_test_check(const vector<double>& values_out, const vector<double>& values_expected)
+{
+    ASSERT_TRUE(test::all_close_f(values_out, values_expected, MIN_FLOAT_TOLERANCE_BITS));
+}
+
+void range_test_check(const vector<float>& values_out, const vector<float>& values_expected)
+{
+    ASSERT_TRUE(test::all_close_f(values_out, values_expected, MIN_FLOAT_TOLERANCE_BITS));
+}
+
+template <typename T>
+typename std::enable_if<std::is_integral<T>::value>::type
+    range_test_check(const vector<T>& values_out, const vector<T>& values_expected)
+{
+    ASSERT_EQ(values_out, values_expected);
+}
+
+template <typename T>
+void range_test(T start, T stop, T step, const vector<T>& values_expected)
+{
+    vector<T> values_start{start};
+    vector<T> values_stop{stop};
+    vector<T> values_step{step};
+
+    auto constant_start = make_shared<op::Constant>(element::from<T>(), Shape{}, values_start);
+    auto constant_stop = make_shared<op::Constant>(element::from<T>(), Shape{}, values_stop);
+    auto constant_step = make_shared<op::Constant>(element::from<T>(), Shape{}, values_step);
+    auto range = make_shared<op::Range>(constant_start, constant_stop, constant_step);
+    auto f = make_shared<Function>(range, ParameterVector{});
+
+    pass::Manager pass_manager;
+    pass_manager.register_pass<pass::ConstantFolding>();
+    pass_manager.run_passes(f);
+
+    ASSERT_EQ(count_ops_of_type<op::Range>(f), 0);
+    ASSERT_EQ(count_ops_of_type<op::Constant>(f), 1);
+
+    auto new_const =
+        std::dynamic_pointer_cast<op::Constant>(f->get_results().at(0)->get_argument(0));
+    ASSERT_TRUE(new_const);
+
+    auto values_out = new_const->template get_vector<T>();
+
+    range_test_check(values_out, values_expected);
+}
+
+TEST(constant_folding, constant_range)
+{
+    range_test<int8_t>(5, 12, 2, {5, 7, 9, 11});
+    range_test<int32_t>(5, 12, 2, {5, 7, 9, 11});
+    range_test<int64_t>(5, 12, 2, {5, 7, 9, 11});
+    range_test<uint64_t>(5, 12, 2, {5, 7, 9, 11});
+    range_test<double>(5, 12, 2, {5, 7, 9, 11});
+    range_test<float>(5, 12, 2, {5, 7, 9, 11});
+
+    range_test<int32_t>(5, 12, -2, {});
+    range_test<float>(12, 4, -2, {12, 10, 8, 6});
+}
+
+TEST(constant_folding, constant_select)
+{
+    Shape shape{2, 4};
+    vector<char> values_selection{0, 1, 1, 0, 1, 0, 0, 1};
+    vector<int64_t> values_t{2, 4, 6, 8, 10, 12, 14, 16};
+    vector<int64_t> values_f{1, 3, 5, 7, 9, 11, 13, 15};
+
+    auto constant_selection = make_shared<op::Constant>(element::boolean, shape, values_selection);
+    auto constant_t = make_shared<op::Constant>(element::i64, shape, values_t);
+    auto constant_f = make_shared<op::Constant>(element::i64, shape, values_f);
+    auto select = make_shared<op::Select>(constant_selection, constant_t, constant_f);
+    auto f = make_shared<Function>(select, ParameterVector{});
+
+    pass::Manager pass_manager;
+    pass_manager.register_pass<pass::ConstantFolding>();
+    pass_manager.run_passes(f);
+
+    ASSERT_EQ(count_ops_of_type<op::Select>(f), 0);
+    ASSERT_EQ(count_ops_of_type<op::Constant>(f), 1);
+
+    auto new_const =
+        std::dynamic_pointer_cast<op::Constant>(f->get_results().at(0)->get_argument(0));
+    ASSERT_TRUE(new_const);
+    auto values_out = new_const->get_vector<int64_t>();
+
+    vector<int64_t> values_expected{1, 4, 6, 7, 10, 11, 13, 16};
+    ASSERT_EQ(values_expected, values_out);
+}
+
 TEST(constant_folding, pass_property)
 {
     auto pass = std::make_shared<ngraph::pass::ConstantFolding>();