1 files changed, 123 insertions, 0 deletions
diff --git a/runtime/neurun/backend/srcn/kernel/AddLayer.cc b/runtime/neurun/backend/srcn/kernel/AddLayer.cc
new file mode 100644
index 000000000..b53dfe89d
--- /dev/null
+++ b/runtime/neurun/backend/srcn/kernel/AddLayer.cc
@@ -0,0 +1,123 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. 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.
+ */
+
+#include "AddLayer.h"
+
+#include "OperationUtils.h"
+#include "ncnn/layer/binaryop.h"
+
+#include "cpp14/memory.h"
+
+namespace
+{
+std::unique_ptr<nnfw::ncnn::Mat>
+convertMatIgnoreLayout(neurun::backend::srcn::kernel::TensorDescriptor &desc, void *data)
+{
+  if (desc.dimensions.size() == 1)
+  {
+    return nnfw::cpp14::make_unique<nnfw::ncnn::Mat>(desc.dimensions[0], data);
+  }
+  else if (desc.dimensions.size() == 2)
+  {
+    return nnfw::cpp14::make_unique<nnfw::ncnn::Mat>(desc.dimensions[1], desc.dimensions[0], data);
+  }
+  else if (desc.dimensions.size() == 3)
+  {
+    return nnfw::cpp14::make_unique<nnfw::ncnn::Mat>(desc.dimensions[2], desc.dimensions[1],
+                                                     desc.dimensions[0], data);
+  }
+  else // rank == 4 and N == 1
+  {
+    return nnfw::cpp14::make_unique<nnfw::ncnn::Mat>(desc.dimensions[3], desc.dimensions[2],
+                                                     desc.dimensions[1], data);
+  }
+}
+} // namespace
+
+namespace neurun
+{
+namespace backend
+{
+namespace srcn
+{
+namespace kernel
+{
+
+void AddLayer::addFloat32()
+{
+  assert(_activation == ir::Activation::NONE);
+
+  // ncnn kernel support
+  // 1. rank < 4
+  // 2. broadcasting
+  //   2-1 lhs, rhs have same rank, or
+  //   2-2 model layout and backend layout is same
+  // For safety, block all broadcasting (enable when ready)
+
+  assert(_lhsDescr.dimensions.size() < 4 ||
+         (_lhsDescr.dimensions.size() == 4 && _lhsDescr.dimensions[0] == 1));
+  assert(_rhsDescr.dimensions.size() < 4 ||
+         (_rhsDescr.dimensions.size() == 4 && _rhsDescr.dimensions[0] == 1));
+  assert((_lhsDescr.dimensions.size() == _rhsDescr.dimensions.size()));
+
+  nnfw::ncnn::BinaryOpParam param;
+  param.op_type = nnfw::ncnn::BinaryOp::Operation_ADD;
+
+  auto lhs_mat = convertMatIgnoreLayout(_lhsDescr, _lhsData.v);
+  auto rhs_mat = convertMatIgnoreLayout(_rhsDescr, _rhsData.v);
+  auto out_mat = convertMatIgnoreLayout(_outputDescr, _outputData.v);
+
+  ::nnfw::ncnn::ncnn_binary_op(param, *lhs_mat.get(), *rhs_mat.get(), *out_mat.get());
+}
+
+void AddLayer::addQuant8()
+{
+  // quant8 add is not implemented yet
+  throw std::runtime_error{"NYI"};
+}
+
+void AddLayer::configure(uint8_t *lhsData, const TensorDescriptor &lhsDescr, uint8_t *rhsData,
+                         const TensorDescriptor &rhsDescr, const ir::Activation activation,
+                         uint8_t *outputData, const TensorDescriptor &outputDescr,
+                         const ir::Layout backendLayout)
+{
+  _lhsData.u8 = lhsData;
+  _lhsDescr = lhsDescr;
+  _rhsData.u8 = rhsData;
+  _rhsDescr = rhsDescr;
+  _inputType = lhsDescr.type;
+  _activation = activation;
+  _outputData.u8 = outputData;
+  _outputDescr = outputDescr;
+  _backendLayout = backendLayout;
+}
+
+void AddLayer::run()
+{
+  if (_inputType == OperandType::FLOAT32)
+  {
+    addFloat32();
+  }
+  else if (_inputType == OperandType::QUANT8_ASYMM)
+  {
+    addQuant8();
+  }
+}
+
+} // namespace kernel
+} // namespace srcn
+} // namespace backend
+} // namespace neurun