catch up to tizen_5.5 and remove unness dir

- update to tizen_5.5
- remove dirs

1 files changed, 83 insertions, 0 deletions

diff --git a/runtimes/neurun/backend/cpu/ConstantInitializer.cc b/runtimes/neurun/backend/cpu/ConstantInitializer.cc
new file mode 100644
index 000000000..cff9fcfa2
--- /dev/null
+++ b/runtimes/neurun/backend/cpu/ConstantInitializer.cc
@@ -0,0 +1,83 @@
+/*
+ * 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 "ConstantInitializer.h"
+
+namespace neurun
+{
+namespace backend
+{
+namespace cpu
+{
+
+ConstantInitializer::ConstantInitializer(const model::Operands &operands,
+                                         const std::shared_ptr<TensorBuilder> &tensor_builder)
+    : _operands{operands}, _tensor_builder{tensor_builder}
+{
+  // DO NOTHING
+}
+
+void ConstantInitializer::run()
+{
+  for (const auto &it : _init_map)
+  {
+    const auto &ind = it.first;
+    const auto &fn = it.second;
+
+    const auto &model_obj = _operands.at(ind);
+    auto tensor_obj = _tensor_builder->wrapTensor(ind);
+    fn(model_obj, *tensor_obj);
+  }
+
+  _init_map.clear();
+}
+
+void ConstantInitializer::visit(const model::operation::Conv2DNode &node)
+{
+  const auto &kernel_index = node.getInputs().at(model::operation::Conv2DNode::KERNEL);
+  const auto &kernel_obj = _operands.at(kernel_index);
+  registerCopyInitializer(kernel_index, kernel_obj);
+
+  const auto &bias_index = node.getInputs().at(model::operation::Conv2DNode::BIAS);
+  const auto &bias_obj = _operands.at(bias_index);
+  registerCopyInitializer(bias_index, bias_obj);
+}
+
+void ConstantInitializer::visit(const model::operation::DepthwiseConv2DNode &node)
+{
+  const auto &kernel_index = node.getInputs().at(model::operation::DepthwiseConv2DNode::KERNEL);
+  const auto &kernel_obj = _operands.at(kernel_index);
+  registerCopyInitializer(kernel_index, kernel_obj);
+
+  const auto &bias_index = node.getInputs().at(model::operation::DepthwiseConv2DNode::BIAS);
+  const auto &bias_obj = _operands.at(bias_index);
+  registerCopyInitializer(bias_index, bias_obj);
+}
+
+void ConstantInitializer::visit(const model::operation::FullyConnectedNode &node)
+{
+  const auto &weight_index = node.getInputs().at(model::operation::FullyConnectedNode::WEIGHT);
+  const auto &weight_obj = _operands.at(weight_index);
+  registerCopyInitializer(weight_index, weight_obj);
+
+  const auto &bias_index = node.getInputs().at(model::operation::FullyConnectedNode::BIAS);
+  const auto &bias_obj = _operands.at(bias_index);
+  registerCopyInitializer(bias_index, bias_obj);
+}
+
+} // namespace cpu
+} // namespace backend
+} // namespace neurun