Implement elementwise exp (#187)

* Add elementwise exp to VM

* Formatting

src/ngraph/runtime/ngvm/eigen/exp.hpp

+// ----------------------------------------------------------------------------
+// Copyright 2017 Nervana Systems Inc.
+// 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
+// ----------------------------------------------------------------------------
+
+#pragma once
+
+#include "ngraph/runtime/ngvm/call_frame.hpp"
+#include "ngraph/runtime/ngvm/eigen/utils.hpp"
+#include "ngraph/runtime/ngvm/instruction.hpp"
+#include "ngraph/runtime/tensor_view.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace ngvm
+        {
+            namespace eigen
+            {
+                template <typename ET>
+                class ExpInstruction : public Instruction
+                {
+                public:
+                    ExpInstruction(TensorViewInfo arg, TensorViewInfo out)
+                        : m_arg(arg)
+                        , m_out(out)
+                    {
+                    }
+
+                    virtual void execute(CallFrame& call_frame) const override
+                    {
+                        EigenArray1d<ET, fmt::V>(call_frame, m_out) =
+                            EigenArray1d<ET, fmt::V>(call_frame, m_arg).exp();
+                    }
+
+                protected:
+                    TensorViewInfo m_arg;
+                    TensorViewInfo m_out;
+                };
+            }
+        }
+    }
+}

src/ngraph/runtime/ngvm/external_function.cpp

@@ -32,6 +32,7 @@
 #include "ngraph/ops/divide.hpp"
 #include "ngraph/ops/dot.hpp"
 #include "ngraph/ops/equal.hpp"
+#include "ngraph/ops/exp.hpp"
 #include "ngraph/ops/function_call.hpp"
 #include "ngraph/ops/get_tuple_element.hpp"
 #include "ngraph/ops/greater.hpp"
@@ -66,6 +67,7 @@
 #include "ngraph/runtime/ngvm/eigen/divide.hpp"
 #include "ngraph/runtime/ngvm/eigen/dot.hpp"
 #include "ngraph/runtime/ngvm/eigen/equal.hpp"
+#include "ngraph/runtime/ngvm/eigen/exp.hpp"
 #include "ngraph/runtime/ngvm/eigen/greater_eq.hpp"
 #include "ngraph/runtime/ngvm/eigen/greater_than.hpp"
 #include "ngraph/runtime/ngvm/eigen/less_eq.hpp"
@@ -323,6 +325,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
     static OpMap op_map;
     if (!initialized)
     {
+        REGISTER_NUMERIC_UNOP(op::Exp, eigen::ExpInstruction);
         REGISTER_NUMERIC_UNOP(op::Log, eigen::LogInstruction);
         REGISTER_NUMERIC_UNOP(op::Negative, eigen::NegateInstruction);
 

test/execute.cpp

@@ -1860,3 +1860,26 @@ TEST(type_prop, reshape_m2m_dim_change_transpose)
     (*cf)({a}, {result});
     ASSERT_EQ((vector<float>{1, 3, 5, 2, 4, 6}), result->get_vector());
 }
+
+TEST(execute, exp)
+{
+    auto shape = Shape{8};
+    auto A = make_shared<op::Parameter>(element::Float32::element_type(), shape);
+    auto result_type = make_shared<TensorViewType>(element::Float32::element_type(), shape);
+    auto f = make_shared<Function>(make_shared<op::Exp>(A), result_type, op::Parameters{A});
+
+    auto manager = runtime::Manager::get("NGVM");
+    auto external = manager->compile(f);
+    auto backend = manager->allocate_backend();
+    auto cf = backend->make_call_frame(external);
+
+    // Create some tensors for input/output
+    auto a = backend->make_parameterized_tensor_view<element::Float32>(shape);
+    *a = vector<float>{-4, -3, -2, -1, 0, 1, 2, 3};
+    auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
+
+    (*cf)({a}, {result});
+    ASSERT_EQ(
+        (vector<float>{expf(-4), expf(-3), expf(-2), expf(-1), expf(0), expf(1), expf(2), expf(3)}),
+        result->get_vector());
+}