CPU Direct Execution: Implement Relu

src/ngraph/runtime/cpu/cpu_builder.cpp

@@ -95,6 +95,7 @@
 #include "ngraph/runtime/cpu/kernel/abs.hpp"
 #include "ngraph/runtime/cpu/kernel/add.hpp"
 #include "ngraph/runtime/cpu/kernel/multiply.hpp"
+#include "ngraph/runtime/cpu/kernel/relu.hpp"
 #include "ngraph/runtime/cpu/kernel/result.hpp"
 #include "ngraph/runtime/cpu/mkldnn_utils.hpp"
 #include "ngraph/runtime/cpu/op/batch_norm_relu.hpp"
@@ -229,6 +230,25 @@ namespace ngraph
                 functors.emplace_back(functor);
             }
 
+            template <>
+            void Builder::BUILDER_DECL(ngraph::op::Relu)
+            {
+                auto& functors = external_function->get_functors();
+                auto& tensor_data = external_function->get_tensor_data();
+                std::function<void(void*, void*, size_t)> kernel;
+
+                SELECT_KERNEL(kernel, out[0].get_element_type(), runtime::cpu::kernel::relu);
+
+                auto element_count = out[0].get_size();
+                auto& arg0_tensor = tensor_data[args[0].get_name()];
+                auto& out0_tensor = tensor_data[out[0].get_name()];
+
+                auto functor = [&, kernel, element_count](CPURuntimeContext* ctx) {
+                    kernel(arg0_tensor, out0_tensor, element_count);
+                };
+                functors.emplace_back(functor);
+            }
+
             template <>
             void Builder::BUILDER_DECL(ngraph::op::Result)
             {
@@ -426,6 +446,7 @@ namespace ngraph
                 {TI(ngraph::op::Multiply), &runtime::cpu::Builder::build<ngraph::op::Multiply>},
                 {TI(ngraph::op::Parameter), &runtime::cpu::Builder::nop},
                 {TI(ngraph::op::Abs), &runtime::cpu::Builder::build<ngraph::op::Abs>},
+                {TI(ngraph::op::Relu), &runtime::cpu::Builder::build<ngraph::op::Relu>},
                 {TI(ngraph::op::Result), &runtime::cpu::Builder::build<ngraph::op::Result>},
                 {TI(ngraph::op::MatmulBias), &runtime::cpu::Builder::build<ngraph::op::MatmulBias>},
                 {TI(ngraph::op::Constant), &runtime::cpu::Builder::build<ngraph::op::Constant>}};

src/ngraph/runtime/cpu/kernel/relu.hpp

+/*******************************************************************************
+* Copyright 2018 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
+
+#define EIGEN_USE_THREADS
+#include <unsupported/Eigen/CXX11/Tensor>
+
+#include "ngraph/runtime/cpu/kernel/eigen_thread_pool.hpp"
+
+namespace ngraph
+{
+    namespace runtime
+    {
+        namespace cpu
+        {
+            namespace kernel
+            {
+                template <typename ElementType>
+                void relu(void* input0, void* output, size_t count)
+                {
+                    Eigen::array<Eigen::Index, 1> out_dims, in_dims;
+
+                    out_dims[0] = in_dims[0] = count;
+
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> out(
+                        static_cast<ElementType*>(output), out_dims);
+                    Eigen::TensorMap<Eigen::Tensor<ElementType, 1, Eigen::RowMajor>> in0(
+                        static_cast<ElementType*>(input0), in_dims);
+
+                    out.device(eigen::global_thread_pool_device) = in0.cwiseMax(ElementType(0));
+                }
+            }
+        }
+    }
+}