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diff --git a/runtimes/neurun/backend/acl_cl/ConstantInitializer.cc b/runtimes/neurun/backend/acl_cl/ConstantInitializer.cc
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+++ b/runtimes/neurun/backend/acl_cl/ConstantInitializer.cc
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+/*
+ * 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 acl_cl
+{
+
+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);
+  registerPermuteInitializer(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);
+  registerPermuteInitializer(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::EmbeddingLookupNode &node)
+{
+  const auto &lookups_index = node.getInputs().at(model::operation::EmbeddingLookupNode::LOOKUPS);
+  const auto &lookups_obj = _operands.at(lookups_index);
+  registerCopyInitializer(lookups_index, lookups_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);
+}
+
+void ConstantInitializer::visit(const model::operation::GatherNode &node)
+{
+  const auto &indices_index = node.getInputs().at(model::operation::GatherNode::INDICES);
+  const auto &indices_obj = _operands.at(indices_index);
+  registerCopyInitializer(indices_index, indices_obj);
+}
+
+void ConstantInitializer::visit(const model::operation::HashtableLookupNode &node)
+{
+  const auto &lookups_index = node.getInputs().at(model::operation::HashtableLookupNode::LOOKUPS);
+  const auto &lookups_obj = _operands.at(lookups_index);
+  registerCopyInitializer(lookups_index, lookups_obj);
+
+  const auto &keys_index = node.getInputs().at(model::operation::HashtableLookupNode::KEYS);
+  const auto &keys_obj = _operands.at(keys_index);
+  registerCopyInitializer(keys_index, keys_obj);
+}
+
+void ConstantInitializer::visit(const model::operation::LSTMNode &node)
+{
+  const auto &input_to_input_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::INPUT_TO_INPUT_WEIGHTS);
+  const auto &input_to_input_weights_obj = _operands.at(input_to_input_weights_index);
+  registerCopyInitializer(input_to_input_weights_index, input_to_input_weights_obj);
+
+  const auto &input_to_forget_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::INPUT_TO_FORGET_WEIGHTS);
+  const auto &input_to_forget_weights_obj = _operands.at(input_to_forget_weights_index);
+  registerCopyInitializer(input_to_forget_weights_index, input_to_forget_weights_obj);
+
+  const auto &input_to_cell_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::INPUT_TO_CELL_WEIGHTS);
+  const auto &input_to_cell_weights_obj = _operands.at(input_to_cell_weights_index);
+  registerCopyInitializer(input_to_cell_weights_index, input_to_cell_weights_obj);
+
+  const auto &input_to_output_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::INPUT_TO_OUTPUT_WEIGHTS);
+  const auto &input_to_output_weights_obj = _operands.at(input_to_output_weights_index);
+  registerCopyInitializer(input_to_output_weights_index, input_to_output_weights_obj);
+
+  const auto &recurrent_to_input_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::RECURRENT_TO_INPUT_WEIGHTS);
+  const auto &recurrent_to_input_weights_obj = _operands.at(recurrent_to_input_weights_index);
+  registerCopyInitializer(recurrent_to_input_weights_index, recurrent_to_input_weights_obj);
+
+  const auto &recurrent_to_forget_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::RECURRENT_TO_FORGET_WEIGHTS);
+  const auto &recurrent_to_forget_weights_obj = _operands.at(recurrent_to_forget_weights_index);
+  registerCopyInitializer(recurrent_to_forget_weights_index, recurrent_to_forget_weights_obj);
+
+  const auto &recurrent_to_cell_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::RECURRENT_TO_CELL_WEIGHTS);
+  const auto &recurrent_to_cell_weights_obj = _operands.at(recurrent_to_cell_weights_index);
+  registerCopyInitializer(recurrent_to_cell_weights_index, recurrent_to_cell_weights_obj);
+
+  const auto &recurrent_to_output_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::RECURRENT_TO_OUTPUT_WEIGHTS);
+  const auto &recurrent_to_output_weights_obj = _operands.at(recurrent_to_output_weights_index);
+  registerCopyInitializer(recurrent_to_output_weights_index, recurrent_to_output_weights_obj);
+
+  const auto &cell_to_input_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::CELL_TO_INPUT_WEIGHTS);
+  const auto &cell_to_input_weights_obj = _operands.at(cell_to_input_weights_index);
+  registerCopyInitializer(cell_to_input_weights_index, cell_to_input_weights_obj);
+
+  const auto &cell_to_forget_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::CELL_TO_FORGET_WEIGHTS);
+  const auto &cell_to_forget_weights_obj = _operands.at(cell_to_forget_weights_index);
+  registerCopyInitializer(cell_to_forget_weights_index, cell_to_forget_weights_obj);
+
+  const auto &cell_to_output_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::CELL_TO_OUTPUT_WEIGHTS);
+  const auto &cell_to_output_weights_obj = _operands.at(cell_to_output_weights_index);
+  registerCopyInitializer(cell_to_output_weights_index, cell_to_output_weights_obj);
+
+  const auto &input_gate_bias_index =
+      node.getInputs().at(model::operation::LSTMNode::INPUT_GATE_BIAS);
+  const auto &input_gate_bias_obj = _operands.at(input_gate_bias_index);
+  registerCopyInitializer(input_gate_bias_index, input_gate_bias_obj);
+
+  const auto &forget_gate_bias_index =
+      node.getInputs().at(model::operation::LSTMNode::FORGET_GATE_BIAS);
+  const auto &forget_gate_bias_obj = _operands.at(forget_gate_bias_index);
+  registerCopyInitializer(forget_gate_bias_index, forget_gate_bias_obj);
+
+  const auto &output_gate_bias_index =
+      node.getInputs().at(model::operation::LSTMNode::OUTPUT_GATE_BIAS);
+  const auto &output_gate_bias_obj = _operands.at(output_gate_bias_index);
+  registerCopyInitializer(output_gate_bias_index, output_gate_bias_obj);
+
+  const auto &projection_weights_index =
+      node.getInputs().at(model::operation::LSTMNode::PROJECTION_WEIGHTS);
+  const auto &projection_weights_obj = _operands.at(projection_weights_index);
+  registerCopyInitializer(projection_weights_index, projection_weights_obj);
+
+  const auto &projection_bias_index =
+      node.getInputs().at(model::operation::LSTMNode::PROJECTION_BIAS);
+  const auto &projection_bias_obj = _operands.at(projection_bias_index);
+  registerCopyInitializer(projection_bias_index, projection_bias_obj);
+}
+
+void ConstantInitializer::visit(const model::operation::RNNNode &node)
+{
+  const auto &weights_index = node.getInputs().at(model::operation::RNNNode::WEIGHTS);
+  const auto &weights_obj = _operands.at(weights_index);
+  registerCopyInitializer(weights_index, weights_obj);
+
+  const auto &recurrent_weights_index =
+      node.getInputs().at(model::operation::RNNNode::RECURRENT_WEIGHTS);
+  const auto &recurrent_weights_obj = _operands.at(recurrent_weights_index);
+  registerCopyInitializer(recurrent_weights_index, recurrent_weights_obj);
+
+  const auto &bias_index = node.getInputs().at(model::operation::RNNNode::BIAS);
+  const auto &bias_obj = _operands.at(bias_index);
+  registerCopyInitializer(bias_index, bias_obj);
+}
+
+void ConstantInitializer::visit(const model::operation::TransposeConvNode &node)
+{
+  const auto &kernel_index = node.getInputs().at(model::operation::TransposeConvNode::KERNEL);
+  const auto &kernel_obj = _operands.at(kernel_index);
+  registerPermuteInitializer(kernel_index, kernel_obj);
+}
+
+} // namespace acl_cl
+} // namespace backend
+} // namespace neurun