fix generation of ParameterizedConstants that are copied directly to output

src/ngraph/descriptor/primary_tensor_view.cpp

@@ -20,9 +20,10 @@ using namespace descriptor;
 PrimaryTensorView::PrimaryTensorView(const std::shared_ptr<const TensorViewType>& tensor_view_type,
                                      const std::string& name,
                                      bool is_output,
-                                     bool is_input)
+                                     bool is_input,
+                                     bool is_constant)
     : TensorView(tensor_view_type)
-    , m_tensor(tensor_view_type->get_element_type(), this, name, is_output, is_input)
+    , m_tensor(tensor_view_type->get_element_type(), this, name, is_output, is_input, is_constant)
 {
     // Set the name in the parent TensorView.
     // This can't be done until after the m_tensor is constructed.

src/ngraph/descriptor/primary_tensor_view.hpp

@@ -43,7 +43,8 @@ namespace ngraph
             PrimaryTensorView(const std::shared_ptr<const TensorViewType>& tensor_view_type,
                               const std::string& name,
                               bool is_output,
-                              bool is_input);
+                              bool is_input,
+                              bool is_constant);
 
             virtual const Tensor& get_tensor() const override;
             virtual Tensor& get_tensor() override;

src/ngraph/descriptor/tensor.cpp

@@ -23,12 +23,14 @@ Tensor::Tensor(const element::Type& element_type,
                PrimaryTensorView* primary_tensor_view,
                const std::string& name,
                bool is_output,
-               bool is_input)
+               bool is_input,
+               bool is_constant)
     : m_element_type(element_type)
     , m_primary_tensor_view(primary_tensor_view)
     , m_is_output{is_output}
     , m_is_input{is_input}
     , m_is_persistent{false}
+    , m_is_constant{is_constant}
     , m_name{name}
     , m_next_view_id{0}
 {

src/ngraph/descriptor/tensor.hpp

@@ -47,7 +47,8 @@ private:
            PrimaryTensorView* tensor_view,
            const std::string& name,
            bool is_output,
-           bool is_input);
+           bool is_input,
+           bool is_constant);
 
     std::string get_next_view_name();
 
@@ -55,6 +56,7 @@ public:
     bool is_output() const { return m_is_output; }
     bool is_input() const { return m_is_input; }
     bool is_persistent() const { return m_is_persistent; }
+    bool is_constant() const { return m_is_constant; }
     const std::string& get_name() const { return m_name; }
     size_t size() const;
     void set_pool_offset(size_t);
@@ -68,6 +70,7 @@ protected:
     bool m_is_output;
     bool m_is_input;
     bool m_is_persistent;
+    bool m_is_constant;
     std::string m_name;
     size_t m_next_view_id;
     size_t m_size;

src/ngraph/node.cpp

@@ -70,7 +70,8 @@ void Node::set_value_type_checked(const shared_ptr<const ValueType>& value_type)
                     tvt,
                     ngraph::descriptor::Tensor::make_tensor_name(this, i),
                     is_output(),
-                    is_parameter());
+                    is_parameter(),
+                    is_constant());
                 m_outputs.emplace_back(this, i, tensor_view_descriptor);
                 i++;
             }
@@ -124,6 +125,11 @@ void Node::set_is_output()
     }
 }
 
+bool Node::is_constant() const
+{
+    return false;
+}
+
 std::string Node::get_node_id() const
 {
     stringstream ss;

src/ngraph/node.hpp

@@ -89,6 +89,7 @@ namespace ngraph
         bool is_parameter() const;
         bool is_output() const;
         void set_is_output();
+        virtual bool is_constant() const;
 
         size_t get_instance_id() const { return m_instance_id; }
         friend std::ostream& operator<<(std::ostream&, const Node&);

src/ngraph/ops/constant.hpp

@@ -40,6 +40,8 @@ namespace ngraph
             {
                 set_value_type_checked(type);
             }
+
+            virtual bool is_constant() const override { return true; }
         };
 
         /// \brief Class for constants whose element types are known at C++ compile-time.

src/ngraph/pass/liveness.cpp

@@ -125,8 +125,7 @@ bool pass::Liveness::run_on_call_graph(list<shared_ptr<Node>>& ops)
 bool pass::Liveness::is_temporary(const Tensor& tensor)
 {
     return tensor.is_persistent() == false && tensor.is_input() == false &&
-           tensor.is_output() == false;
-    // && tensor.is_constant() == false
+           tensor.is_output() == false && tensor.is_constant() == false;
     // && tensor.is_compile_only() == false;
 }
 

src/ngraph/runtime/cpu/emitter.cpp

@@ -493,17 +493,32 @@ void Emitter::EmitParameterizedConstantBool(const ngraph::Node* n,
     auto value = dynamic_cast<const op::ParameterizedConstant<ngraph::element::Bool>*>(n)
                      ->get_value()
                      ->get_vector();
-    string type = element::Bool::element_type().c_type_string();
 
-    TU << "{   // " << n->get_name() << "\n";
-    TU.indent++;
-    for (size_t i = 0; i < value.size(); i++)
+    TU << "// " << n->get_name() << " EmitParameterizedConstantBool\n";
+    if (outputs[0].get_tensor().is_output())
     {
-        TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type << ">("
-           << (value[i] ? "true" : "false") << ");\n";
+        // Special case where constant is stored directly in the output
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<bool>("
+               << (value[i] ? "true" : "false") << ");\n";
+        }
     }
-    TU.indent--;
-    TU << "}\n";
+    else
+    {
+        TU << "// this should be const but eigen hates const :(\n";
+        TU << "bool " << outputs[0].get_tensor().get_name() << "[] = {\n";
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            if (i != 0)
+            {
+                TU << ",\n";
+            }
+            TU << "    " << (value[i] ? "true" : "false");
+        }
+        TU << "\n};";
+    }
+    TU << "\n";
 }
 
 void Emitter::EmitParameterizedConstantFloat32(const ngraph::Node* n,
@@ -514,17 +529,33 @@ void Emitter::EmitParameterizedConstantFloat32(const ngraph::Node* n,
     auto value = dynamic_cast<const op::ParameterizedConstant<ngraph::element::Float32>*>(n)
                      ->get_value()
                      ->get_vector();
-    string type = element::Float32::element_type().c_type_string();
+    const char* type = "float";
 
-    TU << "{   // " << n->get_name() << "\n";
-    TU.indent++;
-    for (size_t i = 0; i < value.size(); i++)
+    TU << "// " << n->get_name() << " EmitParameterizedConstant_" << type << "\n";
+    if (outputs[0].get_tensor().is_output())
     {
-        TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type << ">("
-           << value[i] << ");\n";
+        // Special case where constant is stored directly in the output
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type
+               << ">(" << value[i] << ");\n";
+        }
     }
-    TU.indent--;
-    TU << "}\n";
+    else
+    {
+        TU << "// this should be const but eigen hates const :(\n";
+        TU << type << " " << outputs[0].get_tensor().get_name() << "[] = {\n";
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            if (i != 0)
+            {
+                TU << ",\n";
+            }
+            TU << "    " << value[i];
+        }
+        TU << "\n};";
+    }
+    TU << "\n";
 }
 
 void Emitter::EmitParameterizedConstantInt8(const ngraph::Node* n,
@@ -535,17 +566,33 @@ void Emitter::EmitParameterizedConstantInt8(const ngraph::Node* n,
     auto value = dynamic_cast<const op::ParameterizedConstant<ngraph::element::Int8>*>(n)
                      ->get_value()
                      ->get_vector();
-    string type = element::Int8::element_type().c_type_string();
+    const char* type = "int8_t";
 
-    TU << "{   // " << n->get_name() << "\n";
-    TU.indent++;
-    for (size_t i = 0; i < value.size(); i++)
+    TU << "// " << n->get_name() << " EmitParameterizedConstant_" << type << "\n";
+    if (outputs[0].get_tensor().is_output())
     {
-        TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type << ">("
-           << value[i] << ");\n";
+        // Special case where constant is stored directly in the output
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type
+               << ">(" << static_cast<int>(value[i]) << ");\n";
+        }
     }
-    TU.indent--;
-    TU << "}\n";
+    else
+    {
+        TU << "// this should be const but eigen hates const :(\n";
+        TU << type << " " << outputs[0].get_tensor().get_name() << "[] = {\n";
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            if (i != 0)
+            {
+                TU << ",\n";
+            }
+            TU << "    " << value[i];
+        }
+        TU << "\n};";
+    }
+    TU << "\n";
 }
 
 void Emitter::EmitParameterizedConstantInt32(const ngraph::Node* n,
@@ -556,17 +603,33 @@ void Emitter::EmitParameterizedConstantInt32(const ngraph::Node* n,
     auto value = dynamic_cast<const op::ParameterizedConstant<ngraph::element::Int32>*>(n)
                      ->get_value()
                      ->get_vector();
-    string type = element::Int32::element_type().c_type_string();
+    const char* type = "int32_t";
 
-    TU << "{   // " << n->get_name() << "\n";
-    TU.indent++;
-    for (size_t i = 0; i < value.size(); i++)
+    TU << "// " << n->get_name() << " EmitParameterizedConstant_" << type << "\n";
+    if (outputs[0].get_tensor().is_output())
     {
-        TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type << ">("
-           << value[i] << ");\n";
+        // Special case where constant is stored directly in the output
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type
+               << ">(" << value[i] << ");\n";
+        }
     }
-    TU.indent--;
-    TU << "}\n";
+    else
+    {
+        TU << "// this should be const but eigen hates const :(\n";
+        TU << type << " " << outputs[0].get_tensor().get_name() << "[] = {\n";
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            if (i != 0)
+            {
+                TU << ",\n";
+            }
+            TU << "    " << value[i];
+        }
+        TU << "\n};";
+    }
+    TU << "\n";
 }
 
 void Emitter::EmitParameterizedConstantInt64(const ngraph::Node* n,
@@ -577,17 +640,33 @@ void Emitter::EmitParameterizedConstantInt64(const ngraph::Node* n,
     auto value = dynamic_cast<const op::ParameterizedConstant<ngraph::element::Int64>*>(n)
                      ->get_value()
                      ->get_vector();
-    string type = element::Int64::element_type().c_type_string();
+    const char* type = "int64_t";
 
-    TU << "{   // " << n->get_name() << "\n";
-    TU.indent++;
-    for (size_t i = 0; i < value.size(); i++)
+    TU << "// " << n->get_name() << " EmitParameterizedConstant_" << type << "\n";
+    if (outputs[0].get_tensor().is_output())
     {
-        TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type << ">("
-           << value[i] << ");\n";
+        // Special case where constant is stored directly in the output
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type
+               << ">(" << value[i] << ");\n";
+        }
     }
-    TU.indent--;
-    TU << "}\n";
+    else
+    {
+        TU << "// this should be const but eigen hates const :(\n";
+        TU << type << " " << outputs[0].get_tensor().get_name() << "[] = {\n";
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            if (i != 0)
+            {
+                TU << ",\n";
+            }
+            TU << "    " << value[i];
+        }
+        TU << "\n};";
+    }
+    TU << "\n";
 }
 
 void Emitter::EmitParameterizedConstantUInt8(const ngraph::Node* n,
@@ -598,17 +677,33 @@ void Emitter::EmitParameterizedConstantUInt8(const ngraph::Node* n,
     auto value = dynamic_cast<const op::ParameterizedConstant<ngraph::element::UInt8>*>(n)
                      ->get_value()
                      ->get_vector();
-    string type = element::UInt8::element_type().c_type_string();
+    const char* type = "uint8_t";
 
-    TU << "{   // " << n->get_name() << "\n";
-    TU.indent++;
-    for (size_t i = 0; i < value.size(); i++)
+    TU << "// " << n->get_name() << " EmitParameterizedConstant_" << type << "\n";
+    if (outputs[0].get_tensor().is_output())
     {
-        TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type << ">("
-           << value[i] << ");\n";
+        // Special case where constant is stored directly in the output
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type
+               << ">(" << static_cast<uint>(value[i]) << ");\n";
+        }
     }
-    TU.indent--;
-    TU << "}\n";
+    else
+    {
+        TU << "// this should be const but eigen hates const :(\n";
+        TU << type << " " << outputs[0].get_tensor().get_name() << "[] = {\n";
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            if (i != 0)
+            {
+                TU << ",\n";
+            }
+            TU << "    " << value[i];
+        }
+        TU << "\n};";
+    }
+    TU << "\n";
 }
 
 void Emitter::EmitParameterizedConstantUInt32(const ngraph::Node* n,
@@ -619,17 +714,33 @@ void Emitter::EmitParameterizedConstantUInt32(const ngraph::Node* n,
     auto value = dynamic_cast<const op::ParameterizedConstant<ngraph::element::UInt32>*>(n)
                      ->get_value()
                      ->get_vector();
-    string type = element::UInt32::element_type().c_type_string();
+    const char* type = "uint32_t";
 
-    TU << "{   // " << n->get_name() << "\n";
-    TU.indent++;
-    for (size_t i = 0; i < value.size(); i++)
+    TU << "// " << n->get_name() << " EmitParameterizedConstant_" << type << "\n";
+    if (outputs[0].get_tensor().is_output())
     {
-        TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type << ">("
-           << value[i] << ");\n";
+        // Special case where constant is stored directly in the output
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type
+               << ">(" << value[i] << ");\n";
+        }
     }
-    TU.indent--;
-    TU << "}\n";
+    else
+    {
+        TU << "// this should be const but eigen hates const :(\n";
+        TU << type << " " << outputs[0].get_tensor().get_name() << "[] = {\n";
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            if (i != 0)
+            {
+                TU << ",\n";
+            }
+            TU << "    " << value[i];
+        }
+        TU << "\n};";
+    }
+    TU << "\n";
 }
 
 void Emitter::EmitParameterizedConstantUInt64(const ngraph::Node* n,
@@ -640,17 +751,33 @@ void Emitter::EmitParameterizedConstantUInt64(const ngraph::Node* n,
     auto value = dynamic_cast<const op::ParameterizedConstant<ngraph::element::UInt64>*>(n)
                      ->get_value()
                      ->get_vector();
-    string type = element::UInt64::element_type().c_type_string();
+    const char* type = "uint64_t";
 
-    TU << "{   // " << n->get_name() << "\n";
-    TU.indent++;
-    for (size_t i = 0; i < value.size(); i++)
+    TU << "// " << n->get_name() << " EmitParameterizedConstant_" << type << "\n";
+    if (outputs[0].get_tensor().is_output())
     {
-        TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type << ">("
-           << value[i] << ");\n";
+        // Special case where constant is stored directly in the output
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            TU << outputs[0].get_tensor().get_name() << "[" << i << "] = static_cast<" << type
+               << ">(" << value[i] << ");\n";
+        }
     }
-    TU.indent--;
-    TU << "}\n";
+    else
+    {
+        TU << "// this should be const but eigen hates const :(\n";
+        TU << type << " " << outputs[0].get_tensor().get_name() << "[] = {\n";
+        for (size_t i = 0; i < value.size(); i++)
+        {
+            if (i != 0)
+            {
+                TU << ",\n";
+            }
+            TU << "    " << value[i];
+        }
+        TU << "\n};";
+    }
+    TU << "\n";
 }
 
 void Emitter::EmitBroadcast(const ngraph::Node* n,
@@ -763,7 +890,7 @@ void Emitter::EmitConstant(const ngraph::Node* n,
     auto& c_element_type = c_tensor_type->get_element_type();
     auto c_value_strings = c->get_value_strings();
 
-    TU << "{   // " << n->get_name() << "\n";
+    TU << "{   // " << n->get_name() << " EmitConstant\n";
     TU.indent++;
     for (size_t i = 0; i < c_value_strings.size(); i++)
     {

src/ngraph/runtime/cpu/emitter.hpp

@@ -103,6 +103,39 @@ namespace ngraph
                 std::string emit_vector(const TensorViewInfo&, const std::string& name = "");
                 std::string emit_array1d(const TensorViewInfo&, const std::string& name = "");
                 std::string emit_matrix(const TensorViewInfo&, const std::string& name = "");
+
+                template <typename T>
+                void EmitParameterizedConstant(const std::string& type,
+                                               const ngraph::Node* n,
+                                               const std::vector<T>& value,
+                                               const TensorViewInfo& tv)
+                {
+                    TU << "// " << n->get_name() << " EmitParameterizedConstant_" << type << "\n";
+                    if (tv.get_tensor().is_output())
+                    {
+                        // Special case where constant is stored directly in the output
+                        for (size_t i = 0; i < value.size(); i++)
+                        {
+                            TU << tv.get_tensor().get_name() << "[" << i << "] = static_cast<"
+                               << type << ">(" << value[i] << ");\n";
+                        }
+                    }
+                    else
+                    {
+                        TU << "// this should be const but eigen hates const :(\n";
+                        TU << type << " " << tv.get_tensor().get_name() << "[] = {\n";
+                        for (size_t i = 0; i < value.size(); i++)
+                        {
+                            if (i != 0)
+                            {
+                                TU << ",\n";
+                            }
+                            TU << "    " << value[i];
+                        }
+                        TU << "\n};";
+                    }
+                    TU << "\n";
+                }
             };
         }
     }

src/ngraph/runtime/cpu/tensor_view.cpp

@@ -25,7 +25,11 @@ using namespace std;
 runtime::cpu::CPUTensorView::CPUTensorView(const ngraph::element::Type& element_type,
                                            const Shape& shape)
     : runtime::TensorView(std::make_shared<ngraph::descriptor::PrimaryTensorView>(
-          std::make_shared<ngraph::TensorViewType>(element_type, shape), "external", true, true))
+          std::make_shared<ngraph::TensorViewType>(element_type, shape),
+          "external",
+          true,
+          true,
+          false))
     , m_allocated_buffer_pool(nullptr)
     , m_aligned_buffer_pool(nullptr)
 

src/ngraph/runtime/parameterized_tensor_view.hpp

@@ -41,7 +41,8 @@ namespace ngraph
                       std::make_shared<ngraph::TensorViewType>(ET::element_type(), shape),
                       "external",
                       true,
-                      true))
+                      true,
+                      false))
             {
                 m_descriptor->set_tensor_view_layout(
                     std::make_shared<ngraph::descriptor::layout::DenseTensorViewLayout>(

test/backend_test.in.cpp

@@ -1065,7 +1065,27 @@ TEST(${BACKEND_NAME}, subtract)
     ASSERT_EQ((vector<float>{1, 2, 4, 8}), result->get_vector<float>());
 }
 
-TEST(${BACKEND_NAME}, scalar_constant)
+TEST(${BACKEND_NAME}, scalar_parameterized_constant_bool)
+{
+    auto shape = Shape{};
+    auto t = runtime::make_tensor<element::Bool>(shape, {true});
+    auto A = make_shared<op::ParameterizedConstant<element::Bool>>(shape, t);
+    auto rt = make_shared<TensorViewType>(element::Bool::element_type(), shape);
+    auto f = make_shared<Function>(A, rt, op::Parameters{});
+
+    auto manager = runtime::Manager::get("${BACKEND_NAME}");
+    auto external = manager->compile(f);
+    auto backend = manager->allocate_backend();
+    auto cf = backend->make_call_frame(external);
+
+    // Create some tensors for input/output
+    auto result = backend->make_primary_tensor_view(element::Bool::element_type(), shape);
+
+    (*cf)({}, {result});
+    ASSERT_EQ((vector<char>{true}), result->get_vector<char>());
+}
+
+TEST(${BACKEND_NAME}, scalar_parameterized_constant_float)
 {
     auto shape = Shape{};
     auto t = runtime::make_tensor<element::Float32>(shape, {-3.0f});
@@ -1085,6 +1105,126 @@ TEST(${BACKEND_NAME}, scalar_constant)
     ASSERT_EQ((vector<float>{-3.0f}), result->get_vector<float>());
 }
 
+TEST(${BACKEND_NAME}, scalar_parameterized_constant_int8)
+{
+    auto shape = Shape{};
+    auto t = runtime::make_tensor<element::Int8>(shape, {-3});
+    auto A = make_shared<op::ParameterizedConstant<element::Int8>>(shape, t);
+    auto rt = make_shared<TensorViewType>(element::Int8::element_type(), shape);
+    auto f = make_shared<Function>(A, rt, op::Parameters{});
+
+    auto manager = runtime::Manager::get("${BACKEND_NAME}");
+    auto external = manager->compile(f);
+    auto backend = manager->allocate_backend();
+    auto cf = backend->make_call_frame(external);
+
+    // Create some tensors for input/output
+    auto result = backend->make_primary_tensor_view(element::Int8::element_type(), shape);
+
+    (*cf)({}, {result});
+    ASSERT_EQ((vector<int8_t>{-3}), result->get_vector<int8_t>());
+}
+
+TEST(${BACKEND_NAME}, scalar_parameterized_constant_int32)
+{
+    auto shape = Shape{};
+    auto t = runtime::make_tensor<element::Int32>(shape, {-3});
+    auto A = make_shared<op::ParameterizedConstant<element::Int32>>(shape, t);
+    auto rt = make_shared<TensorViewType>(element::Int32::element_type(), shape);
+    auto f = make_shared<Function>(A, rt, op::Parameters{});
+
+    auto manager = runtime::Manager::get("${BACKEND_NAME}");
+    auto external = manager->compile(f);
+    auto backend = manager->allocate_backend();
+    auto cf = backend->make_call_frame(external);
+
+    // Create some tensors for input/output
+    auto result = backend->make_primary_tensor_view(element::Int32::element_type(), shape);
+
+    (*cf)({}, {result});
+    ASSERT_EQ((vector<int32_t>{-3}), result->get_vector<int32_t>());
+}
+
+TEST(${BACKEND_NAME}, scalar_parameterized_constant_int64)
+{
+    auto shape = Shape{};
+    auto t = runtime::make_tensor<element::Int64>(shape, {-3});
+    auto A = make_shared<op::ParameterizedConstant<element::Int64>>(shape, t);
+    auto rt = make_shared<TensorViewType>(element::Int64::element_type(), shape);
+    auto f = make_shared<Function>(A, rt, op::Parameters{});
+
+    auto manager = runtime::Manager::get("${BACKEND_NAME}");
+    auto external = manager->compile(f);
+    auto backend = manager->allocate_backend();
+    auto cf = backend->make_call_frame(external);
+
+    // Create some tensors for input/output
+    auto result = backend->make_primary_tensor_view(element::Int64::element_type(), shape);
+
+    (*cf)({}, {result});
+    ASSERT_EQ((vector<int64_t>{-3}), result->get_vector<int64_t>());
+}
+
+TEST(${BACKEND_NAME}, scalar_parameterized_constant_uint8)
+{
+    auto shape = Shape{};
+    auto t = runtime::make_tensor<element::UInt8>(shape, {3});
+    auto A = make_shared<op::ParameterizedConstant<element::UInt8>>(shape, t);
+    auto rt = make_shared<TensorViewType>(element::UInt8::element_type(), shape);
+    auto f = make_shared<Function>(A, rt, op::Parameters{});
+
+    auto manager = runtime::Manager::get("${BACKEND_NAME}");
+    auto external = manager->compile(f);
+    auto backend = manager->allocate_backend();
+    auto cf = backend->make_call_frame(external);
+
+    // Create some tensors for input/output
+    auto result = backend->make_primary_tensor_view(element::UInt8::element_type(), shape);
+
+    (*cf)({}, {result});
+    ASSERT_EQ((vector<uint8_t>{3}), result->get_vector<uint8_t>());
+}
+
+TEST(${BACKEND_NAME}, scalar_parameterized_constant_uint32)
+{
+    auto shape = Shape{};
+    auto t = runtime::make_tensor<element::UInt32>(shape, {3});
+    auto A = make_shared<op::ParameterizedConstant<element::UInt32>>(shape, t);
+    auto rt = make_shared<TensorViewType>(element::UInt32::element_type(), shape);
+    auto f = make_shared<Function>(A, rt, op::Parameters{});
+
+    auto manager = runtime::Manager::get("${BACKEND_NAME}");
+    auto external = manager->compile(f);
+    auto backend = manager->allocate_backend();
+    auto cf = backend->make_call_frame(external);
+
+    // Create some tensors for input/output
+    auto result = backend->make_primary_tensor_view(element::UInt32::element_type(), shape);
+
+    (*cf)({}, {result});
+    ASSERT_EQ((vector<uint32_t>{3}), result->get_vector<uint32_t>());
+}
+
+TEST(${BACKEND_NAME}, scalar_parameterized_constant_uint64)
+{
+    auto shape = Shape{};
+    auto t = runtime::make_tensor<element::UInt64>(shape, {3});
+    auto A = make_shared<op::ParameterizedConstant<element::UInt64>>(shape, t);
+    auto rt = make_shared<TensorViewType>(element::UInt64::element_type(), shape);
+    auto f = make_shared<Function>(A, rt, op::Parameters{});
+
+    auto manager = runtime::Manager::get("${BACKEND_NAME}");
+    auto external = manager->compile(f);
+    auto backend = manager->allocate_backend();
+    auto cf = backend->make_call_frame(external);
+
+    // Create some tensors for input/output
+    auto result = backend->make_primary_tensor_view(element::UInt64::element_type(), shape);
+
+    (*cf)({}, {result});
+    ASSERT_EQ((vector<uint64_t>{3}), result->get_vector<uint64_t>());
+}
+
 TEST(${BACKEND_NAME}, tensor_constant)
 {
     auto shape = Shape{2, 2, 2};