Soft backend: relu operation (#832)

Add implementation of relu operation

Signed-off-by: Efimov Alexander <a.efimov@samsung.com>

diff --git a/contrib/nnc/libs/backend/soft/include/cpp_operations.def b/contrib/nnc/libs/backend/soft/include/cpp_operations.def
index 38f2239..813a0bc 100644 (file)
--- a/contrib/nnc/libs/backend/soft/include/cpp_operations.def
+++ b/contrib/nnc/libs/backend/soft/include/cpp_operations.def
@@ -226,7 +226,12 @@ void biasAdd(Tensor &out, const char *params, const Tensor &in)
 
 void relu(Tensor &out, const char *params, const Tensor &in)
 {
-  // TODO call actual function
+  const float *input = in.getData();
+  Dims<4> input_d = shapeToDims(in.getShape());
+
+  out.reShape(in.getShape());
+
+  Relu(input, input_d, out.getData(), input_d);
 }
 
 void reshape(Tensor &out, const char *params, const Tensor &in)

diff --git a/contrib/nnc/libs/backend/soft/include/cpp_ops/cpp_relu.def b/contrib/nnc/libs/backend/soft/include/cpp_ops/cpp_relu.def
index 8b13789..0082cf7 100644 (file)
--- a/contrib/nnc/libs/backend/soft/include/cpp_ops/cpp_relu.def
+++ b/contrib/nnc/libs/backend/soft/include/cpp_ops/cpp_relu.def
@@ -1 +1,23 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
 
+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.
+==============================================================================*/
+
+inline void Relu(const float* input_data, const Dims<4>& input_dims,
+                 float* output_data, const Dims<4>& output_dims) {
+
+  const auto input = MapAsVector(input_data, input_dims);
+  auto output = MapAsVector(output_data, output_dims);
+
+  output = input.cwiseMax(0.0f);
+}