1 files changed, 0 insertions, 137 deletions
diff --git a/runtime/neurun/backend/cpu/kernel/ConcatLayer.cc b/runtime/neurun/backend/cpu/kernel/ConcatLayer.cc
deleted file mode 100644
index 471c9b3bb..000000000
--- a/runtime/neurun/backend/cpu/kernel/ConcatLayer.cc
+++ /dev/null
@@ -1,137 +0,0 @@
-/*
- * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
- * Copyright (C) 2017 The Android Open Source Project
- *
- * 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 "ConcatLayer.h"
-
-#include "OperationUtils.h"
-
-#include <cker/operation/Concatenation.h>
-
-namespace neurun
-{
-namespace backend
-{
-namespace cpu
-{
-namespace kernel
-{
-
-ConcatLayer::ConcatLayer()
-    : _inputDataPtrs(), _outputData(), _axis(0), _inputDescriptors(), _outputDescr(),
-      _inputType(OperandType::FLOAT32)
-{
-  // DO NOTHING
-}
-
-void ConcatLayer::concatenationFloat32()
-{
-  uint32_t num_inputs = _inputDescriptors.size();
-
-  nnfw::cker::ConcatenationParams op_params;
-  op_params.axis = _axis;
-  op_params.inputs_count = num_inputs;
-
-  std::vector<nnfw::cker::Shape *> inputDimsPtr;
-  std::vector<nnfw::cker::Shape> inputDims;
-  inputDimsPtr.reserve(num_inputs);
-  inputDims.reserve(num_inputs);
-
-  for (uint32_t i = 0; i < num_inputs; i++)
-  {
-    inputDims.push_back(convertTensorDescriptorToCkerShape(_inputDescriptors[i]));
-    inputDimsPtr.push_back(&inputDims[i]);
-  }
-
-  std::vector<const float *> inputFloatPtrs;
-
-  for (auto ptr : _inputDataPtrs)
-  {
-    inputFloatPtrs.emplace_back(reinterpret_cast<const float *>(ptr));
-  }
-
-  nnfw::cker::Concatenation<float>(op_params, inputDimsPtr.data(), inputFloatPtrs.data(),
-                                   convertTensorDescriptorToCkerShape(_outputDescr), _outputData.f);
-}
-void ConcatLayer::concatenationQuant8()
-{
-  uint32_t num_inputs = _inputDescriptors.size();
-
-  std::vector<int32_t> input_zeropoints(num_inputs);
-  std::vector<float> input_scales(num_inputs);
-  for (uint32_t i = 0; i < num_inputs; i++)
-  {
-    input_zeropoints[i] = _inputDescriptors[i].offset;
-    input_scales[i] = _inputDescriptors[i].scale;
-  }
-
-  nnfw::cker::ConcatenationParams op_params;
-  op_params.axis = _axis;
-  op_params.inputs_count = num_inputs;
-  op_params.input_zeropoint = input_zeropoints.data();
-  op_params.input_scale = input_scales.data();
-  op_params.output_zeropoint = _outputDescr.offset;
-  op_params.output_scale = _outputDescr.scale;
-
-  std::vector<nnfw::cker::Shape *> inputDimsPtr;
-  std::vector<nnfw::cker::Shape> inputDims;
-  inputDimsPtr.reserve(num_inputs);
-  inputDims.reserve(num_inputs);
-  for (uint32_t i = 0; i < num_inputs; i++)
-  {
-    inputDims.push_back(convertTensorDescriptorToCkerShape(_inputDescriptors[i]));
-    inputDimsPtr.push_back(&inputDims[i]);
-  }
-
-  nnfw::cker::Concatenation<uint8_t>(op_params, inputDimsPtr.data(), _inputDataPtrs.data(),
-                                     convertTensorDescriptorToCkerShape(_outputDescr),
-                                     _outputData.u8);
-}
-
-void ConcatLayer::configure(const std::vector<const uint8_t *> &inputDataPtrs,
-                            const std::vector<TensorDescriptor> &inputDescriptors, int32_t axis,
-                            uint8_t *outputData, const TensorDescriptor outputDescr)
-{
-  _inputDataPtrs = inputDataPtrs;
-
-  for (auto inputDescr : inputDescriptors)
-  {
-    _inputDescriptors.emplace_back(inputDescr);
-    _inputType = inputDescr.type;
-  }
-
-  _axis = axis;
-
-  _outputData.u8 = outputData;
-  _outputDescr = outputDescr;
-}
-
-void ConcatLayer::run()
-{
-  if (_inputType == OperandType::FLOAT32)
-  {
-    concatenationFloat32();
-  }
-  else if (_inputType == OperandType::QUANT8_ASYMM)
-  {
-    concatenationQuant8();
-  }
-}
-
-} // namespace kernel
-} // namespace cpu
-} // namespace backend
-} // namespace neurun